2020 DIETARY GUIDELINES ADVISORY COMMITTEE ...

(202) 234-4433 Washington DC www.nealrgross.comNeal R. Gross and Co., Inc.

1

2020 DIETARY GUIDELINES ADVISORY COMMITTEE

+ + + + +

PUBLIC MEETING

+ + + + +

THURSDAY JANUARY 23, 2020

+ + + + +

The Dietary Guidelines Advisory Committee met in the Agricultural Research Service, Children’s Nutrition Research Center, 1100 Bates Street, Houston, Texas, at 9:00 a.m., Barbara Schneeman, Chair, presiding. The meeting allowed for public viewing, both in-person and by webcast.

MEMBERS PRESENT DR. BARBARA SCHNEEMAN, PhD, Chair DR. RONALD KLEINMAN, MD, Vice Chair DR. JAMY ARD, MD, Member DR. REGAN BAILEY, PhD, MPH, RD, Member DR. LYDIA BAZZANO, MD, PhD, Member DR. CAROL BOUSHEY, PhD, MPH, RD, Member DR. TERESA DAVIS, PhD, Member DR. KATHRYN DEWEY, PhD, Member DR. SHARON DONOVAN, PhD, RD, Member DR. STEVEN HEYMSFIELD, MD, Member DR. HEATHER LEIDY, PhD, Member DR. RICHARD MATTES, PhD, MPH, RD, Member DR. ELIZABETH MAYER-DAVIS, PhD, RD, Member DR. TIMOTHY NAIMI, MD, MPH, Member DR. RACHEL NOVOTNY, PhD, RDN, LD, Member DR. JOAN SABATÉ, MD, DrPH, Member DR. LINDA SNETSELAAR, PhD, RD, Member DR. JAMIE STANG, PhD, MPH, RD, Member DR. ELSIE TAVERAS, MD, MPH, Member


2

............ 3

CONTENTS

Call to Order and Opening Remarks

Chair Remarks ................................ 17

.............. 31

Barbara Schneeman, PhD

Subcommittee Updates

Birth to 24 Months Subcommittee

Pregnancy and Lactation Subcommittee.......... 87 Sharon Donovan, PhD, RD

Dietary Fats and Seafood Subcommittee ....... 134 Linda Snetselaar, PhD, RD

Beverages and Added Sugars Subcommittee ..... 175 Elizabeth Mayer-Davis, PhD, MSPH, RD

Data Analysis and Food Pattern Modeling ..... 205 Megan Bailey, PhD, MPH, RD

Committee Discussion ........................ 270

Facilitated by Barbara Schneeman, PhD, Chair, and Ronald Kleinman, MD, Vice Chair

Adjourn ..................................... 292

Eve Stoody, PhD

Kay Dewey, PhD


3

1 P-R-O-C-E-E-D-I-N-G-S

2 9:03 a.m.

3 DR. STOODY: Okay. Good morning. My

4 name is Eve Stoody, and I’m a Lead Nutritionist for

5 Nutrition Guidance at USDA Center for Nutrition

6 Policy and Promotion, and I’m also the designated

7 federal officer for this 2020 Dietary Guidelines

8 Advisory Committee.

9 It is really my pleasure to welcome you

10 to meeting four of the 2020 Committee and also to

11 welcome you to Texas. We are holding this meeting

12 at the USDA Agricultural Research Service

13 Children’s Nutrition Research Center in Houston,

14 Texas, and thanks to Dr. Denny Bier and their team

15 for really welcoming us and for being fantastic

16 hosts for this event.

17 This is the second time that the Dietary

18 Guidelines Advisory Committee has met outside of

19 the Washington, D.C., and the first time was over

20 25 years ago.

21 We also want to welcome all of you who

22 are joining us on YouTube. This meeting, like our


4

1 previous meetings, will be live-streamed. That

2 means -- hello, I would like to see the slides.

3 So this meeting will be live-streamed.

4 There will be -- and just a note that there will

5 be different links for the morning and afternoon;

6 that’s the nature of YouTube. So for those of you

7 who are joining us online, when you registered, in

8 your registration email you should have received

9 four links, two for today and two for tomorrow.

10 We’ll try to remind you to change links

11 after lunch. So we are very happy to have 19 of

12 our 20 members here with us today. Unfortunately,

13 Dr. Linda Van Horn was not able to join us here in

14 person, but she is going to join us remotely as much

15 as she is able.

16 We have about 1,000 people who have

17 registered for this meeting, with about 150 who

18 will join us at some point in person here in

19 Houston. And as always, I just thank you for your

20 interest and your support of the Dietary

21 Guidelines.

22 So just a little bit of background and


5

1 a reminder: The 2020 Committee was established to

2 conduct an independent review of current research

3 on nutrition and health to be considered by the

4 Departments of Agriculture and Health and Human

5 Services, and the development of the 2020-2025

6 Dietary Guidelines for Americans.

7 This Committee was selected by

8 Secretaries Purdue and Azar from USDA and HHS from

9 nominations received from the public, and they were

10 selected based on their education, experience, and

11 expertise, and they were balanced on a number of

12 factors, including things like geographic

13 locations.

14 The Committee was announced in February

15 2019. And just as a reminder, this is not a

16 committee is convened to provide expert opinions

17 or to represent a specific viewpoint, but rather

18 they were selected as independent scientists who

19 will work together to review current evidence on

20 diet and health.

21 Since this is a federal advisory

22 committee, the federal government is required to


6

1 outline the duties -- the missions and specific

2 duties of the Committee, and we have done this

3 through our charge to the Dietary Guidelines

4 Advisory Committee.

5 You can see this charge on our slide.

6 We presented it every meeting, and it’s also on our

7 website, and their charge is to examine the

8 evidence on specific topics and scientific

9 questions identified by the Departments, and I’ll

10 talk about those here more in the next few slides,

11 to develop a report that outlines their

12 science-based review and recommendations to the

13 Department with rationale, and then to submit the

14 report to the Secretaries of USDA and HHS for

15 consideration as the Departments develop the next

16 edition of the Dietary Guidelines.

17 So as we’ve talked about previously,

18 USDA and HHS added a new step to this process to

19 identify the specific topics or the specific

20 questions that the Advisory Committee were asked

21 to address.

22 In the past, we did outline some topic


7

1 areas, but in general the Committee identified the

2 specific questions that they would consider. For

3 this Committee, we added the step for the Committee

4 where the Departments identified those topics and

5 questions and asked the Committee to address those.

6 We did this for a number of reasons.

7 One, it was in part due to recommendations from the

8 National Academies on our process to kind of have

9 the question development occur in a separate step,

10 and we also really felt like it permitted a more

11 transparent, inclusive, and deliberate process.

12 And I do want to note that the topics

13 and questions were not developed in isolation.

14 The process was led by the Center for Nutrition

15 Policy and Promotion at USDA and the Office of

16 Disease Prevention and Health Promotion, our

17 partners at HHS, but it did include input from a

18 number of federal agencies, as well as

19 consideration of thousands of public comments.

20 And so in that process, specifically

21 CNPP and ODPHP developed an initial list with input

22 from some of our federal partners, we posted a list


8

1 of topics and questions for public comment for 30

2 days.

3 We received about 6,000 public comments

4 on those topics and questions and refined the list,

5 based on that input. We did prioritize the topics

6 and questions using four criteria: relevance to

7 the Dietary Guidelines -- and I’ll talk more about

8 that in just a second; importance to public health;

9 potential impact on the federal programs and

10 policies that we inform; and avoiding duplication

11 of other federal efforts.

12 Now, as I think everyone in this room

13 knows, in the field of nutrition, there are many

14 possible questions of scientific and public input

15 that have the potential to be explored. So this

16 includes things on food groups, on very specific

17 foods, questions on nutrients, food safety, food

18 labeling, menu labeling, food settings, food

19 policies, food behaviors, medical nutrition

20 therapy, and more.

21 And we really feel like the Dietary

22 Guidelines have an important slice of that


9

1 nutrition conversation. The Dietary Guidelines

2 have a specific goal and a specific time line, and

3 that is to provide food-based dietary guidance to

4 the general public at least every five years.

5 Now, we do have a number of partners who

6 we work with kind of in this larger nutrition

7 conversation. So for example, the National

8 Academies developed the nutrient recommendations

9 known as the Dietary Reference Intakes, and there

10 are a number of federal agencies and others

11 involved in this space, including the Department

12 of Health and Human Services, Food and Drug

13 Administration, who work on food safety and

14 labeling issues, but the point being here that

15 there’s a lot of pieces, and the hope is that we

16 all work together to kind of speak to the bigger

17 nutrition picture.

18 Now, the topics and scientific

19 questions we’ve asked the Committee to address

20 focus on diet and health across the lifespan, and

21 so kind of the main emphasis for this, I would say,

22 is about that emphasis on the lifespan.


10

1 The topics and questions we asked the

2 Committee to address build on topics and questions

3 examined by previous dietary guidelines -- Dietary

4 Guidelines Advisory Committees, I should say.

5 So we didn’t start from scratch. We

6 had a lot to work with from our previous committees.

7 For example, the 2015 Committee did a number of

8 questions on dietary patterns and added sugars.

9 The 2010 Committee had a number of

10 specific questions on seafood and alcohol. A

11 number of committees have addressed kind of

12 elements of dietary fats, beverages and patterns

13 of eating, perhaps not as -- in kind of a broader

14 scope, but in pieces of it.

15 Previous committees have also

16 described current intakes of Americans, as well as

17 status of health across the American population,

18 which will be talked about today. And since 2005,

19 advisory committees have conducted food pattern

20 modeling analysis.

21 So that’s kind of the exposure element.

22 In terms of the outcome, the Committee was asked


11

1 to consider a range of outcomes. So many previous

2 advisory committees have looked at the outcomes of

3 body weight or obesity, cardiovascular disease,

4 type 2 diabetes and cancer, and we asked the

5 Committee to examine those in kind of that health

6 discussion, but also some additional outcomes, so

7 for example, neurocognitive health has become

8 really a more recent interest in nutrition science.

9 So we did include brain health as part

10 of many of the questions that the Committee were

11 asked to consider. Sarcopenia, in particular,

12 trying to think about the older adult population

13 and having more targeted outcomes for that

14 population.

15 Bone health, which is of course

16 important for the older adults, but also children

17 and adolescents, as well as actual all-cause

18 mortality. We actually haven’t had many

19 committees that considered that broader all-cause

20 mortality outcome.

21 Now, each committee that we’ve had also

22 looks at some unique topic areas, and for 2020


12

1 process, these are the birth to 24 months

2 performance population. There has been a growing

3 interest in us including this population.

4 Traditional dietary guidance has

5 focused on two years and older. And then the 2014

6 Farm Bill really solidified that inclusion in this

7 edition.

8 And then an expanded focus on pregnancy

9 and lactation. Previous advisory committees

10 hadn’t necessarily excluded pregnancy and

11 lactation, but they hadn’t had as focused questions

12 on pregnancy and lactation, and perhaps more

13 specific, they hadn’t really considered outcomes

14 related to pregnancy and lactation. And so that’s

15 been an addition here as well, and both of those

16 are no small additions, as you’ll hear today

17 shortly.

18 So in summary, I would say that there

19 are many similarities between the work of this

20 Committee and previous advisory committees, but

21 there are some new topics.

22 I think a lot of what we’ve been seeing


13

1 is that a lot of the questions are more expanded,

2 so they’re kind of the similar concept areas that

3 kind of broader exposure to more outcomes, and

4 there also are, of course, the new populations.

5 Now, as we’ve talked about previously,

6 and as with all of our Dietary Guidelines Advisory

7 Committees, the Committee’s task is time-limited.

8 As we’ve discussed, USDA and HHS requested the

9 Committee to report by May 2020, and that is so the

10 Departments can meet our mandate to release the new

11 edition of the Dietary Guidelines within five

12 years, which is by December of this year, December

13 of 2020.

14 So as we move into the last phase of the

15 Committee’s work, which is pretty crazy to think,

16 it’s similar to previous committees. The 2020

17 Committee and federal staff have been working to

18 refine, streamline, and prioritize the remaining

19 work within the remaining time, and you’ll hear

20 more about that over course of the next few days.

21 So all meetings of the full Committee

22 are open to the public. As I noted, this is the


14

1 fourth meeting. If you were not able to join us

2 for meetings one, two, and three, that information

3 is archived on our website, including the

4 recordings of the meetings, as well as

5 presentations, transcripts, and minutes.

6 Similar to the second meeting, this

7 meeting will include an opportunity for

8 individuals who had registered to provide oral

9 comments to the Committee. However, if you did not

10 have the opportunity to travel here to provide

11 public comments in person, the written public

12 comment period is always open.

13 We opened it in March of 2019, and it

14 will stay open into May of 2020. So this meeting

15 will be held today and tomorrow from 9:00 a.m. until

16 4:30 p.m. Central. I just note that because we

17 usually function on Eastern Time, and some of us

18 arrived early today, thinking we were still there.

19 So -- but we’ll be on -- the meeting

20 will be in Central Time. The agenda is available

21 at DietaryGuidelines.gov, and Dr. Schneeman will

22 give an overview of the agenda in her remarks.


15

1 We do want to announce today that we

2 will host a -- the Committee will host a meeting

3 on its report on May 11, which is a Monday. This

4 will be a meeting -- you know, as we just talked

5 about, we’ve asked for the Committee’s report in

6 May.

7 Their last meeting was scheduled for

8 March, and we wanted to provide the Committee an

9 opportunity to come together to discuss its final

10 recommendations and refine its report, but also for

11 the public to be able to hear some of the discussion

12 around the Committee’s final recommendations

13 before they submit their report to the Departments.

14 This is the first time that we have

15 hosted a meeting specifically focused on the

16 Committee’s report, and we hope that it is kind of

17 helpful in hearing firsthand about their

18 recommendations before they submit the report.

19 So we’ll provide more information about

20 this. We will publish this in the Federal

21 Register. We’ll include information on our

22 website. We’ll send out listserv messages for


16

1 those of you who have signed up as we have more

2 information, but for now, please save the date for

3 Monday, May 11. This meeting will be held by

4 webinar only. We will not have -- there won’t

5 travel for that meeting.

6 So we encourage you to follow along at

7 DietaryGuidelines.gov in between the meetings, as

8 well as here today. The Committee will talk about

9 a number of different questions that they are

10 reviewing. If you want more information about the

11 questions that they are talking about, you can to

12 go DietaryGuidelines.gov.

13 There is a rotating banner in the middle

14 of that page, the orange banner there, and if you

15 click on "View Protocols," it will take you to a

16 list -- a website with a list of questions, and if

17 you click on your question of interest, then it will

18 take you a webpage devoted to the Committee’s

19 review on that question. So if you have something

20 of interest that you really want to learn more

21 about, we encourage you to go to the website.

22 So with that, I turn it over to the Chair


17

1 of the Committee, Dr. Barbara Schneeman.

2 CHAIR SCHNEEMAN: Thank you, Eve, and

3 let me add my welcome, certainly, to the Committee

4 members. It’s great to see you all, and a full -- a

5 fairly full representation from the Committee, and

6 also to the attendees who are in the room, but also

7 to all of those who are listening on the webinar.

8 We do appreciate the interest in the

9 Dietary Guideline process and the work of this

10 Advisory Committee. And I want to extend a special

11 thank you to the CNRC for hosting the Committee

12 here.

13 I see Dr. Bier sitting over here on the

14 side. Thank you very much for the invitation to

15 be here, and the staff has been fantastic in terms

16 of helping us and making sure that things went

17 smoothly.

18 So thank you. So I will move into the

19 slides. So let me start, first of all, by just

20 giving you an overview. Sort of following on from

21 what Dr. Stoody presented, I’m going to talk more

22 specifically about our subcommittee structure, our


18

1 approaches to examining evidence and the

2 information to be discussed at this meeting.

3 In a sense, I’m now going to talk more

4 about how this Committee has moved forward with the

5 charge that we received from USDA and HHS. So

6 we’ll look at the subcommittee status and the

7 agenda for this meeting.

8 So just to remind you, these are the

9 subcommittee structures that were set up, so that

10 between the -- in the time between the public

11 meetings, work can proceed, and we have six

12 subcommittees and one cross-cutting.

13 I know the font is small there.

14 Dietary Patterns, Pregnancy and Lactation, Birth

15 to 24 Months, Beverages and Added Sugars, Dietary

16 Fats and Seafood, and Frequency of Eating, and the

17 cross-cutting group is the Data Analysis and Food

18 Pattern Modeling subcommittee, so aligned with

19 those topics that you’ve heard.

20 And I’m not going to read out the names,

21 because as we go through the subcommittee reports,

22 you will be getting that information. Just to


19

1 remind you that the subcommittees review the

2 evidence and provide advice to the parent

3 Committee, so the final decisions are being made

4 by the full Committee, and they’re done in this

5 public meeting format, which we’ll be having today

6 and tomorrow.

7 So just, again, we’ve talked about that

8 this each meeting, how the Committee approaches the

9 review of the evidence, the examination of the

10 evidence, and we use three approaches to examine

11 the evidence: data analysis, food pattern

12 modeling, and the NESR systematic reviews.

13 And each of these scientific approaches

14 has a protocol, and the protocol is a plan for how

15 one of the scientific approaches will be used to

16 examine evidence related to one of the questions

17 that the Committee has been asked to address.

18 As they’ve been developed, each of the

19 protocols are available, and Dr. Stoody gave you

20 the web link for that. And we -- in posting the

21 posting the protocols, we have invited feedback

22 from the public, and we found that feedback to be


20

1 very helpful. People have provided additional

2 references for additional consideration.

3 So information on the approaches and

4 the protocols have been presented at previous

5 meetings, and additional information that is

6 available at the DietaryGuidelines.gov.

7 So in the next few slides, I’m going to

8 just go through a brief overview of the information

9 to be presented by the subcommittee so you see the

10 general format of how each of the subcommittee’s

11 reports is structured.

12 So throughout the presentations, you

13 will see an analytic framework which defines the

14 core elements of the diet and health relationship

15 to be examined. So you can see that that analytic

16 framework includes the intervention, exposures,

17 and the comparators that will be used.

18 In some cases, we have intermediate

19 outcomes -- obviously we’re very interested in the

20 health outcomes when available for our

21 review -- then key factors that could impact the

22 relationship; confounders, covariates, moderators


21

1 are specified in the analytical framework, and also

2 key definitions are given.

3 So each of the protocols also look at

4 inclusion and exclusion criteria. And so you will

5 hear discussion of those criteria in each of the

6 systematic reviews, and these criteria are

7 developed up front and are used to screen the

8 articles that will be included or excluded from a

9 review.

10 So there are a number of standard

11 criteria that apply across the different reviews

12 that the subcommittees have used consistently

13 across the reviews, and so these include areas such

14 as the study design.

15 And I’m not going to read all of the

16 inclusion/exclusion, because we have talked about

17 these at each of the public meetings, and it’s also

18 available -- completely available to you on the

19 DietaryGuidelines.gov.

20 So standard inclusion criteria include

21 that study design, what kinds of studies are

22 included, what are excluded, the publication


22

1 status, peer-reviewed articles, the language of

2 publication -- English is what we’ve

3 included -- the country of origin or the country

4 that studied very high or high human development

5 so it’s comparable to the U.S. population and can

6 be generalized to the U.S. population. And then

7 the study participants. We’re primarily

8 interested in studies in humans, males and females,

9 and so exclude animal or in vitro studies.

10 In addition, the health status of the

11 study participants is included in our inclusion and

12 exclusion criteria, and generally you’ll see that,

13 while we’re obviously interested in participants

14 who are healthy, we do also include participants

15 who may be at risk for chronic disease, including

16 those with obesity, and so that concept applies.

17 What we’re excluding are studies in

18 which the participants have been diagnosed with a

19 disease or hospitalized and that -- or

20 participants with the outcome of interest that

21 we’re looking at, and so they’re in a treatment

22 study, or infants who were born preterm or low birth


23

1 weight. So that sets up what we include versus

2 what we exclude in terms of health status.

3 Now, some of the criteria need to be

4 tailored to the specific review, and those kind of

5 tailored criteria might include diet-related

6 interventions or an exposure of interest; health

7 outcomes; the endpoint and/or an intermediate,

8 whether or not that data are available; the date

9 of publication, depending on what we already have

10 from previous versions of the Dietary Guidelines;

11 the work of other advisory committees; the size of

12 the study groups; study duration; and the age of

13 the study participants. And so those will be

14 clearly specified in the protocols that are

15 published.

16 So in the NESR systematic reviews, what

17 you will -- because we’re now moving into that

18 phase where the subcommittees have been doing their

19 work, and they are presenting more than the

20 protocols; they’re moving into presenting their

21 draft conclusions -- you’ll see a flow chart of the

22 literature search and screening results, a


24

1 description of the evidence that is being examined

2 in depth by the subcommittee, the summary of the

3 evidence synthesis, and some draft conclusion

4 statements and grades for those particular

5 questions.

6 And I do want to highlight that what

7 we’re going to be presenting, just in the interest

8 of time, are in fact summary statements. The

9 Committee’s review includes a much more detailed

10 discussion and review of the included articles,

11 which will be provided in the Committee’s final

12 report and supporting online materials.

13 The intent is to summarize the

14 information today and tomorrow for discussion

15 across the full Committee. And again, a lot of

16 what we’re doing now, because it does involve a

17 Committee discussion, we’re presenting things that

18 are in their draft format and it will only be

19 finalized once we submit our report.

20 So there will be data analysis

21 questions that are presented today, and they

22 include -- they also follow a protocol and may


25

1 include some similar elements, including the

2 analytical framework, the analytical plan, the

3 results, and then draft conclusion statements that

4 the Committee will be discussing today.

5 So for both the NESR systematic reviews

6 and the data analysis questions discussed today and

7 tomorrow, conclusion statements -- draft

8 conclusion statements will be presented, and so

9 that draft conclusion statement is an answer to the

10 question of the evidence that is being reviewed.

11 They have been drafted by the

12 subcommittees, and they’re being brought to the

13 full Committee for discussion at these public

14 meetings. And again, these are considered draft

15 until the Committee submits its report to the

16 Secretaries, so they shouldn’t be interpreted as

17 the Committee’s final view or recommendations. The

18 Committee is working toward its final decisions.

19 So I do want to note that after the

20 conclusion statements are discussed by the

21 Committee at the public meetings, the systematic

22 reviews will go through a peer-review process, and


26

1 that is being coordinated by USDA’s Agricultural

2 Research Service, so that these reviews will be

3 peer-reviewed before the Committee finalizes.

4 And we have, in fact, invited Dr. David

5 Klurfeld from ARS to provide remarks at the next

6 meeting, the March meeting, on the process that is

7 being used for the peer-review process.

8 And we will then post the draft

9 conclusion statements online after that peer

10 review is completed. So you’ll be learning more

11 about that as we move forward, and that is a new

12 part of the DGAC process, so we’re learning about

13 it as we go.

14 So subcommittee status. They’re -- I

15 just want to summarize so you understand the full

16 scope of the work. I can assure you that the

17 subcommittees have been very busy, and there’s a

18 lot of demand in terms of time.

19 I also would note that I know everyone

20 on this Committee is fully appreciative of the

21 excellent staff that has been working with us,

22 keeping us on schedule, keeping us on track, and


27

1 doing the tremendous of work that it takes to pull

2 the evidence together so that the Committee can do

3 its evaluation.

4 So if we could go back to that slide,

5 please? So just the draft conclusions for

6 approximately 30 questions will be presented at

7 this meeting, including both NESR’s systematic

8 reviews and data analysis evaluation.

9 And so across the subcommittees, NESR

10 has screened over 265,000 articles and extracted

11 data and assessed risk of bias for over 500

12 articles. And I can assure you those numbers will

13 only still grow as we keep moving forward.

14 We are utilizing nearly 50 different

15 types of data analysis from the NHANES What We Eat

16 in America. We have begun to work on the food

17 pattern modeling, and we’ve refined a report

18 outline and are beginning to prepare some of the

19 report content.

20 So the task at hand is large. There’s

21 a huge amount of work that has been done. We know

22 that there’s still a huge amount of work to be done.


28

1 So members and staff, members of the Committee and

2 the staff have been working to refine, streamline,

3 and prioritize the remaining work so that we can

4 meet the timeline.

5 So in our meeting number four, the

6 meeting that we’re at, we’ll describe the status

7 and provide updates on the work of the Committee.

8 As Dr. Stoody noted, there’s an agenda available

9 at DietaryGuidelines.gov.

10 So just to make sure we -- sort of make

11 sure we connect with our YouTube participants,

12 we’ll be sure that the meeting begins at 9:00 a.m.

13 Central Time, and the afternoon session will begin

14 at 1:00 p.m. Central Time.

15 Breaks, however, can’t really be set at

16 a specific time, because of the nature of the

17 reporting that we’re doing, but we’ll take breaks

18 as they fit within the discussion framework.

19 So for today’s agenda, following the

20 opening remarks, we’ll start with the subcommittee

21 updates, and the subcommittees we expect to hear

22 from today are Birth to 24, Pregnancy and


29

1 Lactation, Dietary Fats and Seafood, Beverages and

2 Added Sugar, and the Data Analysis and Food Pattern

3 Modeling, the cross-cutting working group, and

4 obviously, with each of those subcommittees, we

5 anticipate there will be Committee discussion.

6 So for tomorrow’s agenda, again, we’ll

7 start at 9:00 a.m., and the subcommittee updates

8 that will be held tomorrow are the Dietary Pattern

9 subcommittee, the Frequency of Eating, some

10 Committee discussion, and then we’ve also

11 scheduled public comments, which will take place

12 in the afternoon, and we are looking forward to

13 those public comments.

14 And just to note that, yes, there’s been

15 a lot of interest in the DGAC work. The Committee

16 has received approximately 17,775 written public

17 comments, since the work began.

18 If there’s interest in commenting on

19 the new protocols that are presented in today and

20 tomorrow’s public meetings, it’s most useful to the

21 Committee if those comments on the protocols are

22 received by Friday, February 7.


30

1 And again, we’ve found the comments on

2 the protocols to be helpful, but for the Committee

3 to keep progressing with its work, we need them by

4 February 7. But as noted by Dr. Stoody, the

5 written public comment period for more general

6 comments is open until we complete our work in May

7 of 2020.

8 So with that, that concludes my

9 comments, and I’ll just turn to the Committee

10 members just to see if there’s anything, question

11 or comments that any Committee members may want to

12 make?

13 (No response.)

14 CHAIR SCHNEEMAN: So with that, I’m

15 going to -- Dr. Kleinman, you may have some

16 comments as well, but I’ll turn it over to you for

17 the first subcommittee reports.

18 VICE CHAIR KLEINMAN: Thank you.

19 Thanks, Barbara. That was very complete, and I

20 have very little to add. This is our fourth

21 meeting together, and so it’s an opportunity for

22 us all to be here with each of the subcommittees


31

1 that’s been working on, and a great deal of work

2 has taken place since the last meeting, so the

3 remainder of the day today and tomorrow will be

4 these report outs of the subcommittees.

5 I think we’ll go right into the first

6 one now and then in terms of breaks, we recognize

7 that there are some biological imperatives here,

8 and so we will try to take a brief break, perhaps,

9 between the first and second.

10 So with that, I’m going to go ahead and

11 turn this over to Kay Dewey, and she will talk

12 about the subcommittee for Birth to 24 Months.

13 MEMBER DEWEY: Thank you very much, Ron

14 and Barbara. I am very pleased to be able to report

15 to you today on behalf of this subcommittee. And

16 the members of this subcommittee have been working

17 very hard, many hours every week, to get to this

18 point.

19 We have a number of questions that have

20 been addressed, and the NESR staff have been

21 extremely busy screening the literature, preparing

22 the results, extracting the data, and preparing


32

1 evidence portfolios for us to review.

2 And so today we will be presenting draft

3 conclusion statements for the eight topics shown

4 here. Although it’s eight topics, there are

5 66 conclusion statements we need to go through, and

6 if I did read every single one of them in full, it

7 would take more than an hour.

8 So I’m going to try to go through them

9 as quickly as I can, while not skipping anything

10 important. Those include three questions or

11 topics on the relationship between human milk and

12 infant formula and three outcome areas:

13 micronutrient status, atopic disease, and

14 long-term health outcomes.

15 Then there are five questions on

16 complementary feeding, and five outcome areas:

17 atopic disease, developmental milestones, growth,

18 size, and body composition, micronutrient status

19 and bone health.

20 We still have work to do for five other

21 topics that are listed here, two additional

22 questions related to human milk and infant formula,


33

1 and those relate to growth, size, and body

2 composition and developmental milestones.

3 And then the three new questions that

4 we have on nutrients from supplements or fortified

5 foods, and three outcome domains: growth, size and

6 body composition, bone health and micronutrient

7 status.

8 These are some of the key definitions

9 for our reviews, which we have presented

10 previously, but to remind you of those and the scope

11 of the questions we’re investigating, I wanted to

12 go through them.

13 Human milk refers to mother’s own milk,

14 so our reviews did not include examinations of

15 donor milk. And we’ve used the term human milk

16 feeding, instead of breastfeeding, to be clear that

17 we have examined human milk fed at the breast, as

18 well as human milk that has been expressed and fed

19 fresh or after refrigeration or freezing.

20 Infant formula refers to commercially

21 prepared infant formulas that meet FDA or Codex

22 Alimentarius standards. In practice, this has


34

1 been a tricky definition to apply because there are

2 a lot of studies that examine experimental infant

3 formulas with ingredients such as dietary

4 nucleotides or DHA, prior to putting them on the

5 market.

6 So we have included this evidence if the

7 formulas met the FDA or Codex standards. We did

8 this because we thought it was important to examine

9 infant formulas with ingredients that are

10 commercially available.

11 And lastly, complementary foods and

12 beverages refers to foods and beverages other than

13 human milk or infant formula. That includes

14 liquids, semisolids, and solids that are provided

15 to an infant or young child to provide nutrients

16 and energy.

17 I want to thank the public for

18 submitting comments on the work that was presented

19 during meeting three. We carefully reviewed and

20 discussed all of those comments, and we would very

21 much welcome public comments on what we present

22 today, as Dr. Schneeman mentioned, by February 7.


35

1 So to begin, I will review some draft

2 conclusions for the relationship between duration,

3 frequency, and volume of exclusive human milk

4 and/or infant formula consumption and

5 micronutrient status.

6 This is the analytical framework that

7 we developed that shows the scope of this question,

8 and we divided the duration, frequency, and volume

9 of exclusive milk, of human milk or infant formula,

10 into a series of four comparisons that align with

11 the first feeding decisions that caregivers make,

12 and those include whether or not to feed human milk;

13 and then, for caregivers who do decide to do so,

14 how long to feed human milk, so the duration of

15 human milk consumption, and then how long to feed

16 human milk exclusively.

17 So you’ll note that we examined

18 exclusive human milk consumption prior to the

19 introduction of infant formula only, and that’s to

20 avoid overlap with another review which we will

21 also present today that examines the timing of the

22 introduction of complementary foods and beverages.


36

1 And then if caregivers have decided to

2 supplement human milk with infant formula, our

3 final comparison examines the intensity or

4 proportion or amount of human milk that is fed to

5 mixed-fed infants.

6 And then on the right, you can see that

7 we examined iron, zinc, iodine, vitamins C and B12,

8 and fatty acid status from birth to 24 months.

9 This flow chart shows the literature review and

10 screening results, and we used two different

11 literature searches which are noted with the

12 letters A and B in the flow chart.

13 Literature Search A was from the

14 Pregnancy and Birth to 24 Months Project, which

15 used a search date range of January 1980 to March

16 2016, and this literature search was very large,

17 because it was intended to find studies for several

18 questions related to human milk and infant formula.

19 Literature Search B was smaller,

20 because it was intended to capture just the

21 literature published in the last three years. And

22 you can see that ultimately 23 articles were


37

1 identified that met the inclusion criteria for the

2 question about feeding human milk and infant

3 formula and micronutrient status outcomes.

4 On this slide, we want to give you a

5 snapshot of the evidence by showing how many of

6 those 23 studies provided evidence for each

7 component of our analytical framework. And you

8 can see that where there was evidence to address

9 a topic, the number of studies was small.

10 Now, a small number of studies may

11 provide sufficient evidence to determine

12 associations, for example, if the evidence is

13 consistent and has a low risk of bias. However,

14 that was generally not the case in this body of

15 evidence.

16 You can also see the majority of

17 evidence addressed ever, compared with never,

18 consuming human milk. So we’ll go one by one

19 through those comparisons.

20 This is the evidence related to ever

21 versus never consuming human milk, and these were

22 generally studies that compare infants who were fed


38

1 human milk with infants who were fed infant formula

2 that had a novel composition at the time of the

3 study, such as added DHA or different levels of

4 iron, and infants who were fed conventional infant

5 formula.

6 Now, as you can imagine, the evidence

7 would show that the formula’s composition can

8 impact nutrient status outcomes. For example,

9 formula with DHA can impact DHA status, and this

10 complicates our synthesis of the evidence, because

11 infants in the studies were fed a wide variety of

12 infant formulas.

13 The 23 studies in this body of evidence

14 generally studied healthy full-term infants who

15 were recruited at or close to birth and who were

16 from the U.S. and several other countries.

17 As I’ve already mentioned, the majority

18 of evidence examines ever compared with never

19 consuming human milk and the duration of human milk

20 consumption. It’s important to note that other

21 components of the infants’ diets varied between

22 studies and also didn’t tend to be well reported.


39

1 For example, the exclusivity of human

2 milk, the types and amount of formula fed in

3 addition to human milk, the types and amount of

4 complementary foods and beverages in addition to

5 human milk or infant formula, and any intake of

6 supplements.

7 At the bottom of the slide, you can see

8 the outcomes that were reported by the studies for

9 each of these nutrients. Now, there was evidence

10 available from a small number of studies, and

11 generally they did not show consistent

12 associations between the comparisons that are

13 shown in this slide.

14 So for ever -- compared with never

15 consuming human milk, there were not consistent

16 associations with anemia, hemoglobin, hematocrit

17 and the other indicators of iron status shown here,

18 or with zinc status.

19 Also, that was true for the duration of

20 any human milk consumption among infants fed human

21 milk, and anemia and markers of iron status, zinc

22 status, vitamin D status and fatty acid status.


40

1 And lastly, the same was true for the

2 duration of exclusive human milk consumption

3 before the introduction of infant formula and fatty

4 acid status.

5 The most substantial evidence that we

6 reviewed was from seven studies that examine the

7 relationship between ever compared with never

8 consuming human milk and fatty acid status.

9 And these studies indicated that there

10 may be an association between feeding human milk

11 compared with infant formula and fatty acid status.

12 And this body of evidence had an adequate number

13 of sufficiently powered studies, with some

14 inconsistencies that can likely be explained by

15 methodological differences; for example, the use

16 of formulas with different fatty acid composition.

17 There were several limitations that

18 included the risk of bias, especially confounding;

19 the study directness, because these studies are

20 mostly designed to examine the effects of infant

21 formula composition rather than to directly

22 compare infants fed human milk with those fed


41

1 infant formula.

2 And also generalizability. For

3 example, in two studies, there were no non-white

4 participants, and other studies did not report race

5 or ethnicity. Also, it’s unclear whether the

6 experimental formulas are similar to current

7 formulas on the market in the U.S.

8 But we did draft a conclusion statement

9 regarding ever versus never consuming human milk,

10 and this states that moderate evidence indicates

11 that ever compared with never consuming human milk

12 may be associated with fatty acid status. The

13 difference in fatty acid status between infants who

14 are fed human milk and infant formula likely

15 depends on the fatty acid composition of the human

16 milk and the infant formula being compared.

17 We found insufficient evidence

18 available to determine the relationship between

19 ever compared with never consuming human milk and

20 iron and zinc status from birth to 24 months, and

21 no evidence for the relationship between ever

22 versus never consuming human milk and the other


42

1 micronutrient status outcomes: iodine, vitamin

2 B12 and vitamin D status.

3 Continuing on with regard to duration

4 of human milk feeding, insufficient evidence was

5 available to examine this relationship for iron,

6 zinc, vitamin D and fatty acid status, and there

7 was no evidence to determine that relationship for

8 iodine and vitamin B12 status.

9 In addition, regarding duration of

10 exclusive human milk consumption, there was

11 insufficient evidence for the relationship to

12 fatty acid status, and no evidence for the

13 relationship to iron, zinc, iodine, vitamin B12 and

14 vitamin D status.

15 And finally, with regard to intensity,

16 proportion or amount of human milk in mixed-fed

17 infants, there was no evidence to examine the

18 relationship to iron, zinc, iodine, B12, vitamin

19 D, or fatty acid status.

20 So next we will review the draft

21 conclusions for the relationship between duration

22 of exclusive human milk or infant formula


43

1 consumption, and food allergies and atopic

2 allergic diseases and long-term health outcomes.

3 Now, these questions have been answered

4 with existing NESR systematic reviews, and our

5 updated protocols, which are available at

6 DietaryGuidelines.gov, describe that we will use

7 these reviews as is, because they were completed

8 recently and capture over 35 years of evidence.

9 The papers from those reviews were published in the

10 American Journal of Clinical Nutrition in 2019.

11 However, we would like to ask the public

12 to please submit public comments if you know of any

13 articles published since 2016 that meet the

14 inclusion criteria and would also significantly

15 affect these conclusions.

16 The Committee did carefully review the

17 conclusion statements in the existing NESR

18 systematic reviews; and we flagged those that we

19 thought warranted an informal search to identify

20 new evidence that has emerged since 2016, focusing

21 on other published systematic reviews.

22 We did not locate any studies that would


44

1 have modified the conclusions, but again we do

2 appreciate any comment the public would like to

3 provide. So as I mentioned the Committee will be

4 answering these questions using the nine existing

5 NESR systematic reviews completed as part of the

6 Pregnancy and Birth to 24 Months Project by the

7 Infant Milk-Feeding Practices Technical Expert

8 Collaborative, and the link to the documentation

9 is provided here.

10 We would like to sincerely acknowledge

11 the work of this group of scientists who comprised

12 this technical expert collaborative and conducted

13 these reviews with NESR.

14 For this set of reviews, the literature

15 search was conducted between January 1980 and March

16 2016. For never versus ever feeding human milk and

17 atopic disease, 44 articles met the inclusion

18 criteria, and you can see the distribution of the

19 outcome that was examined. Almost all of this

20 evidence was from observational studies.

21 For duration of any human milk feeding

22 and atopic disease, 35 articles met the criteria,


45

1 and almost all the evidence was from observational

2 studies.

3 For duration of exclusive human milk

4 feeding prior to the introduction of infant

5 formula, only one article met the inclusion

6 criteria.

7 This summarizes what was concluded

8 regarding the relationship between never versus

9 ever feeding human milk and these outcomes.

10 Firstly, moderate evidence suggests that never, in

11 comparison to ever being fed human milk, is

12 associated with a higher risk of childhood asthma.

13 Again, just to emphasize, these

14 statements are worded so that the risk is related

15 to never feeding human milk. And in this case,

16 there were 17 independent studies contributing to

17 that conclusion statement.

18 For the second one, limited evidence

19 does not suggest a relationship between never

20 versus ever being fed human milk and atopic

21 dermatitis in childhood.

22 For the other relationships, evidence


46

1 about never versus ever being fed human milk and

2 atopic dermatitis was inconclusive, and there was

3 insufficient evidence to examine how it related to

4 the other outcomes that are listed here.

5 Again, I’m not going to read every word.

6 All of these statements are available in the

7 published articles.

8 This shows the conclusion statements

9 for the relationship between shorter versus longer

10 duration of any human milk feeding and these

11 outcomes.

12 Moderate evidence, mostly from

13 observational studies, suggests that among infants

14 fed human milk, a shorter versus a longer duration

15 of any human milk feeding is associated with a

16 higher risk of asthma in childhood and adolescence.

17 This included 20 independent studies.

18 Limited evidence does not suggest a

19 relationship between duration of any human milk

20 feeding and allergic rhinitis or atopic dermatitis

21 in childhood.

22 Evidence about the relationship


47

1 between shorter or longer duration of human milk

2 feeding and atopic dermatitis from birth to 24

3 months is inconclusive, and there’s insufficient

4 evidence to determine the relationship with the

5 other outcomes in this set.

6 In terms of the shorter or longer

7 duration of exclusive human milk feeding before

8 introduction of infant formula, there is

9 insufficient evidence to examine this relationship

10 to all of the outcomes that were examined.

11 Moving on, then, to the long-term

12 outcomes, this shows the evidence that was

13 available to examine those. First, with regard to

14 never versus ever feeding human milk and

15 cardiovascular disease outcomes, there were 13

16 articles that met the inclusion criteria, and you

17 can see the types of outcomes that these studies

18 examined.

19 For duration of any human milk feeding,

20 there were 24 articles, and for duration of

21 exclusive human milk feeding and cardiovascular

22 disease outcomes, there were six articles


48

1 included.

2 So I’ll go through those conclusion

3 statements as well. For never versus ever feeding

4 human milk, limited evidence suggests that never

5 versus ever being fed human milk is associated with

6 higher blood pressure, within a normal range, at

7 six to seven years of age.

8 The evidence about the relationship of

9 never versus ever being fed human milk with blood

10 lipids in childhood was inconclusive and there was

11 insufficient evidence for the relationship to the

12 other CVD outcomes examined.

13 In terms of shorter versus longer

14 duration of any human milk feeding, moderate

15 evidence suggests that there is no association

16 between the duration of any human milk feeding and

17 blood pressure in childhood.

18 And I wanted to call out one study here

19 that was quite important. There was compelling

20 evidence from the Promotion of Breastfeeding

21 Intervention trial that is the only randomized

22 trial in this body of evidence, and it showed no


49

1 significant relationship between duration of any

2 human milk feeding and blood pressure at six and

3 a half or 11-1/2 years of age.

4 There was also inconsistent evidence

5 across six independent prospective cohort studies.

6 The second bullet here, the evidence about the

7 relationship of shorter versus longer duration of

8 human milk with blood lipids in childhood and

9 adulthood and with metabolic syndrome, was

10 inconclusive, and there was insufficient evidence

11 to determine the relationship to the other CVD

12 outcomes.

13 Continuing on with shorter versus

14 longer duration, limited evidence suggests that

15 there is no association between the duration of

16 exclusive human milk feeding and blood pressure in

17 childhood or metabolic syndrome at 11.5 years of

18 age, and most of this evidence comes from this one

19 non-U.S. sample that was assessed using a very

20 strong study design.

21 And there was insufficient evidence to

22 determine the relationship of the duration of


50

1 exclusive human milk feeding with the other

2 endpoint CVD outcomes.

3 The other long-term outcome examined

4 was diabetes, and in this case, there were 21

5 articles that met the inclusion criteria for the

6 comparison of never versus ever feeding human milk.

7 You can see that most of those are

8 regard -- with regard to type 1 diabetes. For

9 duration of any human milk feeding and diabetes,

10 37 articles met the criteria, and 30 were focused

11 on type 1 diabetes.

12 For duration of exclusive human milk

13 feeding, there were 18 articles that met the

14 criteria; again, 17 about type 1 diabetes. So this

15 summarizes what was concluded about never versus

16 ever feeding human milk.

17 Limited evidence from observational

18 studies suggests that never versus ever being fed

19 human milk is associated with a higher risk of type

20 1 diabetes. There’s insufficient evidence to

21 determine whether or not there is a relationship

22 between never versus ever feeding human milk and


51

1 type 2 diabetes, prediabetes and the other outcomes

2 shown here.

3 In terms of the duration of human milk

4 feeding, moderate evidence from observational

5 studies suggests that among infants fed some amount

6 of human milk, a shorter versus a longer duration

7 of human milk feeding is associated with a higher

8 risk of type 1 diabetes.

9 Limited but consistent evidence

10 suggests that the duration of any human milk

11 feeding is not associated with fasting glucose or

12 insulin resistance in childhood or during the

13 transition from childhood into adolescence. And

14 there’s insufficient evidence for the relationship

15 to type 2 diabetes, prediabetes or the other

16 outcomes shown here.

17 And then in terms of shorter versus

18 longer duration of exclusive human milk feeding,

19 limited evidence from observational studies

20 suggests that a shorter duration is associated with

21 a higher risk of type 1 diabetes.

22 Limited evidence from a single study


52

1 that used the strong design also suggests that the

2 duration of exclusive human milk feeding is not

3 associated with fasting glucose or insulin

4 resistance at 11.5 years of age. And there’s

5 insufficient evidence to determine the

6 relationship with type 2 diabetes, prediabetes and

7 the other outcomes shown here.

8 Moving on, next we’ll review the draft

9 conclusions for the relationship between

10 complementary feeding and the five outcome domains

11 that are listed here: micronutrient status;

12 growth, size and body composition; developmental

13 milestones, including neurocognitive development;

14 food allergies and atopic allergic diseases; and

15 bone health.

16 These have also been answered with

17 existing NESR systematic reviews, and the

18 protocols again are at DietaryGuidelines.gov.

19 And we will be using these reviews as is, again,

20 because they were completed recently and capture

21 over 35 years of evidence.

22 These papers were also published in the


53

1 American Journal of Clinical Nutrition in 2019.

2 However, as mentioned previously, we would like to

3 ask the public to please submit public comments if

4 you know of any articles published since 2016 that

5 meet the inclusion criteria and would

6 significantly affect the conclusions that I will

7 be presenting.

8 So the Committee will be answering

9 these questions using 10 existing NESR systematic

10 reviews completed as part of the Pregnancy and

11 Birth to 24 Months Project by the Complementary

12 Feeding Technical Expert Collaborative, and this

13 gives the link for the complete documentation of

14 that work.

15 Again, we would like to acknowledge the

16 work of this group of scientists who comprise the

17 complementary feeding TEC, who conducted these

18 reviews with NESR. This literature search spanned

19 from January 1980 to July 2016.

20 For complementary foods and beverages,

21 they were divided into two overarching types of

22 questions: the timing of introduction of


54

1 complementary foods and beverages, and the types

2 of amounts.

3 So for this first set of outcomes, which

4 are micronutrient status, there were nine studies

5 that met the criteria for the timing of

6 introduction. Most of these examined iron status;

7 a few examined zinc, vitamin D, vitamin B12, folate

8 and/or fatty acid status. For the types and

9 amounts of complementary foods and beverages, 31

10 articles met the criteria. Most examined

11 iron-fortified cereals and meats with respect to

12 iron status. Several examined zinc and fatty acid

13 status. And very few studies examined vitamin D,

14 vitamin B12, and folate status.

15 So I’ll begin with the relationship

16 between the timing of introduction of

17 complementary foods and beverages and


19 Moderate evidence suggests that

20 introducing complementary foods and beverages at

21 four months of age compared to six months of age

22 offers no long-term advantages or disadvantages in


55

1 terms of iron status among healthy, full-term

2 infants who are breastfed, fed iron-fortified

3 formula, or both. And there were nine studies that

4 met the criteria for this question.

5 There is not enough evidence to

6 determine the relationship between timing of

7 introduction and zinc, vitamin D, vitamin B12,

8 folate, or fatty acid status.

9 Additional factors that need to be

10 considered in examining the relationship between

11 the age at which complementary foods and beverages

12 are introduced and micronutrient status include

13 birth weight and timing of umbilical cord clamping,

14 both of which affect iron stores of the newborn;

15 postnatal growth; type of feeding, at the breast

16 or formula or mixed feeding; and intake and

17 absorption of iron from sources other than human

18 milk, including the types and amounts of

19 complementary foods and beverages being consumed.

20 This summarizes the conclusions for the

21 types and amounts of complementary foods and

22 micronutrient status. Thirty-one studies met the


56

1 inclusion criteria for this review. And strong

2 evidence suggests that consuming complementary

3 foods and beverages that contain substantial

4 amounts of iron, such as meats or iron-fortified

5 cereal, helps maintain adequate iron status or

6 prevent iron deficiency during the first year of

7 life among infants with insufficient iron stores

8 or breastfed infants who are not receiving adequate

9 iron from another source.

10 However, the benefit of these types of

11 complementary foods and beverages for infants with

12 sufficient iron stores, such as those consuming

13 iron-fortified infant formula, is less evident.

14 There’s not enough evidence to

15 determine the relationship between other types and

16 amounts of complementary foods and beverages

17 containing lesser amounts of iron, such as fruits

18 and vegetables and iron status.

19 Then in terms of the other nutrients of

20 interest, limited evidence suggests that consuming

21 complementary foods and beverages that contain

22 substantial amounts of zinc, such as meats or


57

1 cereals fortified with zinc, support zinc status

2 during the first year of life, particularly among

3 breastfed infants who are not receiving adequate

4 zinc from another source.

5 However, the benefit of these types of

6 complementary foods for infants consuming

7 fortified infant formula is less evident.

8 Moderate evidence suggests that consuming

9 complementary foods and beverages with differing

10 fatty acid profiles, particularly long-chain

11 polyunsaturated fatty acids, can influence fatty

12 acid status.

13 Continuing on this theme, during the

14 second year of life, food sources of micronutrients

15 are still needed, but there’s limited evidence to

16 indicate which types and amounts of complementary

17 foods and beverages are associated with adequate

18 micronutrient status, and there’s not enough

19 evidence to determine the relationship between the

20 types and amounts of complementary foods and

21 beverages and vitamin B-12, vitamin D, or folate

22 status.


58

1 Now I’m going to move on to the next

2 outcome domain, and that is food allergies and

3 atopic allergic diseases. For the timing of

4 introduction of complementary foods and beverages,

5 31 studies met the inclusion criteria, and most of

6 them examined food allergies. For types and

7 amounts of complementary foods and beverages, 39

8 met the criteria and most examined the most common

9 allergenic foods.

10 This has to do with the timing of

11 introduction of complementary foods and beverages.

12 Moderate evidence suggests that there is no

13 relationship between the age at which

14 complementary feeding first begins and the risk of

15 developing food allergy, atopic dermatitis or

16 eczema, or asthma during childhood.

17 There’s insufficient evidence to

18 determine the relationship between age at which

19 complementary foods or beverages are first

20 introduced and risk of developing allergic

21 rhinitis during childhood.

22 Now, the rest of the series of slides


59

1 focuses on the specific types of complementary

2 foods being introduced, and so these are divided

3 into several different slides.

4 I wanted to mention that the studies are

5 mostly focused on food allergy to that particular

6 food component. And in this case, we will be

7 talking about peanut, tree nuts and seeds.

8 There is strong evidence to suggest

9 that introducing peanut in the first year of life

10 after four months of age may reduce the risk of food

11 allergy to peanuts, and this evidence is strongest

12 for introducing peanut in infants at the highest

13 risk with severe atopic dermatitis and/or egg

14 allergy to prevent peanut allergy, but it is also

15 applicable to infants at lower risk.

16 However, the evidence for tree nuts and sesame

17 seeds is limited.

18 Limited evidence also suggests that

19 there is no relationship between consumption of

20 peanut, tree nuts or sesame seeds during the

21 complementary feeding period and the risk of atopic

22 dermatitis or eczema and asthma.


60

1 And there is not enough evidence to

2 determine if there is a relationship between

3 consuming peanut, tree nuts or seeds and allergic

4 rhinitis.

5 What I want to also mention is that many

6 of the studies included in this review exclusively

7 enrolled or primarily enrolled subjects who were

8 at a greater risk of allergies and/or atopic

9 disease than the general population on the basis

10 of family history.

11 However, despite this, the reviewers

12 concluded that the results are probably

13 generalizable to infants and toddlers who are at

14 lower risk for atopic disease, although the

15 magnitude of the associations may be smaller.

16 There were 28 studies that examined the

17 consumption of eggs as a complementary food in

18 relationship to the risk of developing any atopic

19 disease, including six randomized controlled

20 trials.

21 From that body of evidence, it was

22 concluded that moderate evidence suggests that


61

1 introducing egg in the first year of life, after

2 four months of age, may reduce the risk of food

3 allergy to egg.

4 Limited evidence suggests that there is

5 no relationship between the age of introduction to

6 egg and the risk of atopic dermatitis or eczema and

7 asthma, and there’s not enough evidence to

8 determine the relationship between egg and

9 allergic rhinitis.

10 For fish, 24 studies examined fish as

11 a complementary food, including one randomized

12 controlled trial. From this body of evidence,

13 there is limited evidence that suggests that

14 introducing fish in the first year of life after

15 four months of age may reduce the risk of atopic

16 dermatitis and eczema, and there is not enough

17 evidence to determine this relationship to the risk

18 of allergy to fish or other foods, asthma or

19 allergic rhinitis, and also not enough evidence for

20 the relationship to the risk of food allergy,

21 atopic dermatitis, eczema, asthma or allergic

22 rhinitis.


62

1 There were 17 studies that examined the

2 consumption of wheat or cereals and these outcomes,

3 and all of these were observational studies. So

4 limited evidence suggests that there is no

5 relationship between the age of introduction or

6 cow’s milk products such as cheese and yogurt and

7 the risk of food allergy and atopic dermatitis and

8 eczema.

9 There’s not enough evidence to

10 determine if there’s a relationship between

11 consuming milk products during the complementary

12 feeding period and the risk of asthma or allergic

13 rhinitis.

14 Did I skip something? I’m going to go

15 back a second. Here we go. Sorry. There are a lot

16 of outcomes here. So sorry. I’m going to go back

17 to wheat and soy. And I did mention there were 17

18 studies that examined the consumption of wheat or

19 cereals, and these were all observational, and

20 there’s not enough evidence for those related to

21 wheat to determine the relationship to risk of food

22 allergy, atopic dermatitis and eczema, asthma or


63

1 allergic rhinitis.

2 For soy, there were four prospective

3 studies that examined this relationship and that

4 indicated that there was not enough evidence to

5 determine if there was a relationship between

6 soybean consumption and the risk of any of these

7 outcomes. Okay, I think I will move on.

8 There were several observational

9 studies that also examined the relationship

10 between other types of complementary foods and

11 beverages that are generally not considered to be

12 major allergens; for example, fruit, vegetables,

13 and meats, and this conclusion was that there was

14 limited evidence from observational studies that

15 suggest that introducing foods not commonly

16 considered to be allergens in the first year of life

17 after four months of age is not associated with risk

18 of food allergy, atopic dermatitis or eczema,

19 asthma or allergic rhinitis.

20 There were also several observational

21 studies that examined dietary diversity or dietary

22 patterns, and these were 11 prospective cohort


64

1 studies and three case control studies, but there

2 was not enough evidence to determine a relationship

3 between these aspects of the diet and any of these

4 outcomes.

5 Okay. Moving on to the next set of

6 outcomes, which is growth, size, and body

7 composition, there were 81 studies that met the

8 inclusion criteria for the timing of introduction

9 of complementary foods and beverages, and 49 that

10 met the criteria for types and amounts.

11 So in terms of timing of introduction,

12 moderate evidence suggests that the first

13 introduction of any complementary food or beverage

14 between four to five months, compared to

15 approximately six months of age, is not associated

16 with weight status, body composition, body

17 circumferences, weight, or length, among generally

18 healthy, full-term infants.

19 Limited evidence suggests that

20 introducing complementary foods and beverages

21 before four months of age may be associated with

22 higher odds of overweight and obesity. And


65

1 there’s not enough evidence to determine the

2 relationship between introduction of

3 complementary foods and beverages at seven months

4 or later on growth, size, and body composition.

5 In terms of types and amounts of

6 complementary foods, moderate evidence indicates

7 that a higher versus lower meat intake or meat

8 versus iron-fortified cereal intake over a shorter

9 duration during the complementary feeding period,

10 does not favorably or unfavorably influence

11 growth, size and/or body composition.

12 And there’s insufficient evidence to

13 determine the relationship between meat intake and

14 prevalence or incidence of overweight or obesity.

15 Limited evidence suggests that the type or amount

16 of cereal given does not favorably or unfavorably

17 affect these outcomes.

18 In terms of fatty acids, moderate

19 evidence suggests that consumption of

20 complementary foods with different fats and/or

21 fatty acids composition does not favorably or

22 unfavorably influence growth, size, or body


66

1 composition.

2 And there’s not enough evidence to

3 determine the relationship to the prevalence or

4 incidence of overweight or obesity. Limited

5 evidence suggests that sugar-sweetened beverage

6 consumption during the complementary feeding

7 period is associated with decreased risk of obesity

8 in childhood, but it is not associated with other

9 measures of growth, size, and body composition.

10 There is limited evidence that showed

11 a positive association between juice intake and

12 infant weight-for-length and child BMI z-scores.

13 No conclusion could be made about the

14 relationship about other complementary foods as

15 listed here and growth, size, body composition, or

16 overweight or obesity.

17 And also no conclusion could be made

18 about the relationship between distinct dietary

19 patterns during the complementary feeding period

20 and growth, size, body composition, or these other

21 outcomes.

22 There was a much smaller body of


67

1 evidence regarding developmental outcomes. For

2 the timing of introduction of complementary foods

3 and beverages, only three studies met the criteria,

4 and for types and amounts, only eight studies met

5 those criteria.

6 So not surprisingly, given that small

7 evidence base, there was insufficient evidence to

8 draw conclusions about the relationship between

9 the timing of the introduction of complementary

10 foods and beverages and developmental milestones.

11 One of the issues with this body of

12 evidence is that there is the potential for reverse

13 causation. In other words, the child might be more

14 developed and therefore be more demanding of

15 introduction of other foods and beverages. And so

16 with observational studies, it’s very difficult to

17 study this relationship.

18 There was also insufficient evidence to

19 draw a conclusion about the relationships between

20 the types and amounts of complementary foods and

21 beverages consumed and developmental milestones.

22 There was also a very small evidence


68

1 base in terms of bone health. Three studies met

2 the criteria for timing of introduction of

3 complementary foods and beverages, and eight met

4 the criteria for types and amounts.

5 So again, not surprisingly, the

6 conclusion was that there was insufficient

7 evidence to draw conclusions about the

8 relationship of timing of introduction of

9 complementary foods and beverages and bone health.

10 And similarly, insufficient evidence

11 was available between the types and amounts of

12 complementary foods and beverages and bone health.

13 Okay. So those are the 66 conclusion

14 statements we had to get through today, and now I’m

15 going to present some of the discussions that we’ve

16 had related to refining and prioritizing the

17 remaining work in front of us.

18 So as I mentioned, we have two questions

19 regarding human milk and infant formula and outcome

20 domains, including growth, size, and body

21 composition. So for this one, it’s a very, very

22 large literature, and for this purpose, we’ve


69

1 decided to examine outcomes related to body

2 composition only, which includes obesity and

3 overweight.

4 Our rationale for this is that we

5 already know that growth curves differ between

6 infants fed human milk and those fed infant

7 formula. In fact, the U.S. Government convened an

8 expert panel several years ago to review such

9 evidence, and as a result, the CDC adopted the World

10 Health Organization growth curves from birth to age

11 two years, which reflect the growth of breastfed

12 children.

13 On the other hand, the relationship

14 between human milk or infant formula consumption

15 and body composition outcomes, including obesity,

16 warrants further examination, and for that reason,

17 we have altered the protocol for this, which is

18 going to be available on DietaryGuidelines.gov.

19 We also discussed the remaining

20 questions that examine intake of nutrients from

21 supplements and fortified foods, and for this, we

22 decided to prioritize for the first question


70

1 related to growth, size and body composition, to

2 focus only on iron and iron from supplements.

3 For the second one related to bone

4 health, we decided to focus only on vitamin D and,

5 again, only from supplements. And for the third

6 question related to nutrient status, we decided to

7 focus on iron and vitamin D from supplements only.

8 Our rationale for limiting these

9 reviews to the nutrients from supplements is that

10 the existing reviews from the previous project,

11 which I just reviewed with you today, examined

12 complementary foods and beverages and included

13 fortified foods.

14 So we feel that the real need for new

15 work here is on these nutrients from supplements.

16 Our rationale for examining iron and vitamin D only

17 is that we would like to review evidence about

18 nutrient supplements that are currently

19 recommended for this age group.

20 So that is where we will be moving

21 forward as we continue the work. So our next steps

22 are summarized here. There will be a literature


71

1 search on iron and vitamin D from supplements and

2 nutrient status.

3 There will be screening of the

4 literature also for iron and vitamin D from

5 supplements. Oh, that will include a screening of

6 the literature, as well as vitamin D from

7 supplements and bone health.

8 We will then have to extract the data,

9 assess risk of bias, and develop conclusions and

10 grades for the five questions that are listed here.

11 And again, those are human milk and infant formula

12 consumption, growth, size and body composition,

13 and developmental outcomes, and then the specific

14 nutrients from supplements and the three outcome

15 areas that I mentioned.

16 And then lastly, we will be

17 drafting -- going through the peer-review process

18 and drafting the report. And with that, I would

19 like to again thank the members of the subcommittee

20 very much, thank and acknowledge the very hard and

21 extensive work by our support staff, who are listed

22 on this slide.


72

1 Thank you very much.

2 (Applause.)

3 VICE CHAIR KLEINMAN: Thank you, Kay,

4 for an incredibly complete summary of the work of

5 the subcommittee. So we’ve already had some

6 cross-cutting conversations between a few of the

7 subcommittees, but this is our opportunity now as

8 a full Committee to ask any further questions or

9 to comment on what Kay has presented.

10 So I’ll open it up to the Committee now

11 for questions. Rick. And don’t forget to say your

12 name.

13 MEMBER MATTES: Rick Mattes. So I

14 have five questions, but a lot of them will be

15 really short, I think, responses. The first is, you

16 used the term "intensity" of feeding. I’m just not

17 clear on what intensity means, so a clarification,

18 that would be helpful.

19 Your recommendation regarding fat

20 intake and fatty acid status just referred to

21 association, whereas all the other recommendations

22 had directionality to them.


73

1 If it’s possible to tweak that, I think

2 it would be more useful. If it’s not, it’s not.

3 In the report on never versus ever and

4 risk of type 1 diabetes, you found an association

5 there; this is my lack of knowledge, is there a

6 plausibility? Is there a mechanism that would make

7 that make sense?

8 With the peanut

9 recommendation -- again I’m old school -- is there

10 some subset of people that may actually be at risk

11 so a general recommendation saying early

12 introduction is okay, holds risk for some subgroup

13 of the population, or it really is a clear bill of

14 health for such a recommendation?

15 MEMBER DEWEY: Can you repeat that

16 again?

17 MEMBER MATTES: So the recommendation

18 for early exposure to peanut seemed to be just

19 generally positive, and I’m just wondering if there

20 is a subgroup of individuals that might be at risk?

21 Because if people just look at that recommendation,

22 they’d think that it’s good to go, but maybe there


74

1 are some that would be at risk. I don’t know.

2 And lastly, for the sugar

3 recommendation, it says that sugar-sweetened

4 beverage consumption during complementary feeding

5 is associated with increase of obesity, but not

6 associated with body composition. I’m just not

7 clear how to juxtapose those.

8 MEMBER DEWEY: So those are very good

9 questions, and I’m going to rely on others in the

10 room to help with some of the answers.

11 For the intensity of breastfeeding,

12 this is part of three different aspects of when

13 children are fed both infant formula and human

14 milk.

15 It relates to how many of the feeds are

16 human milk versus formula or the amounts, or in some

17 other way judging the proportion. So the

18 intensity refers to how much of that is human milk.

19 It’s a guesstimate, in most cases,

20 because they’re not measuring human milk intake.

21 So that’s why different words are used by different

22 researchers.


75

1 Is there any -- if anybody wants to add

2 anything from the staff who knows these definitions

3 by heart?

4 Yes, please, Darcy.

5 MS. GUNGOR: Just one clarification,

6 which is that intensity, proportionate amount, be

7 included in any evidence that was examined, either

8 at a single point in time or over a duration of time,

9 and that might have included another variable in

10 the definition such as months or years, that sort

11 of thing.

12 MEMBER MATTES: So in any write-up,

13 that will be defined somewhere?

14 MEMBER DEWEY: In the paper that was

15 published, that is given, yes.

16 And then in terms of fat composition of

17 complementary foods, and that we said there is an

18 association without the direction, and that was on

19 purpose, because it really depends on what fatty

20 acids are in those foods.

21 So if there is an increased amount of

22 polyunsaturated fatty acids, for example, that


76

1 will generally show up in the fatty acid status as

2 a positive relationship in the child. But it’s not

3 simple to summarize that in the conclusion

4 statement.

5 So in the paper that was published, it

6 goes through exactly what all those relationships

7 were. We can talk further about whether there is

8 some way to modify that, but for that question,

9 we’re relying on the existing review that’s been

10 published already, and that’s their exact wording.

11 MEMBER MATTES: So it is possible for

12 it to be inverse in some instances, or could it just

13 be stated as a direct relationship?

14 MEMBER DEWEY: Well, I would have to

15 read again exactly which studies that -- there’s

16 always theoretically the possibility that if you

17 increase intake of omega-6, you might reduce

18 omega-3 status, or vice -- I mean, so -- and that’s

19 why I don’t want to get too specific about it right

20 now.

21 MEMBER DONOVAN: Yeah. And I think in

22 some the ever versus never types of questions,


77

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

because the composition of breast milk fatty acids

differ from formula, because the breastfeeding

moms’ maternal diet, and formulas are added oil,

so I think in some cases they’re higher, and in some

cases, they’re lower.

So rather than have a conclusion

statement that was three paragraphs long to go

through each of them, it was basically a general

statement of there is associations between dietary

intake and the outcome.

MEMBER DEWEY: So I thought you were

referring to fatty acids from complementary foods

and beverages, but we’ve been also referring to the

never versus ever human milk and those questions?

MEMBER MATTES: I’m not sure where my

brain kicked off as you were going through, but for

either of them, I’m --

MEMBER DEWEY: Okay. So there were

two different questions where fatty acid status was

an outcome. One was from complementary foods and

beverages. That’s what I was answering.

22 For human milk, ever versus never,


78

1 duration et cetera, we also shied away, as Sharon

2 explained, from stating a direction, because

3 it’s -- as we were talking yesterday in our

4 subcommittee meeting, it’s complicated, because of

5 the composition of human milk and the possibility

6 that the mammary gland has endogenous synthesis of

7 many of these fatty acids. And so it’s

8 something that we will describe in more detail in

9 the write-up.

10 And then you asked about never versus

11 ever breastfeeding in type 1 diabetes and the

12 plausibility of that argument.

13 Yes, there is a biological rationale

14 for that. I’m not sure I’m ready to explain it

15 thoroughly here, but it relates to the components

16 that are in human milk and their relationship to

17 development of physiological function, immune

18 status and reaction to antigens.

19 If anyone else wants to go further than

20 that, be my guest.

21 VICE CHAIR KLEINMAN: That’s an

22 absolutely fair summary. But one of the things


79

1 that I think is a little bit confusing is the

2 absence of any relationship to prediabetes, yeah

3 type 2.

4 You’d expect that those same markers

5 would be present in type 1 in advance of that

6 disease expressing itself. So we might want to pay

7 a little bit more attention to that, as we put this

8 together, because you’d expect insulin resistance,

9 glucose intolerance, A1Cs.

10 They don’t -- you know, they rise

11 gradually both in type 1 and in type 2.

12 MEMBER DEWEY: Uh-huh.

13 VICE CHAIR KLEINMAN: Just a point

14 of -- for further discussion in the statement.

15 MEMBER DEWEY: That’s a great idea. I

16 think we will take that up.

17 And then your fourth question was

18 regarding peanut exposure in the first year of

19 life, and I think the question was, are there

20 infants who are risk from that exposure because

21 they are at high risk to begin with?

22 Now, I am, again, going to defer, I


80

1 think, to the clinicians, but my understanding is

2 that those with a family history are usually

3 advised to be under the sort of supervision of the

4 health care provider when they first introduce that

5 allergen, to be careful about that.

6 So do you want to go further than that?

7 VICE CHAIR KLEINMAN: No. I think

8 that’s absolutely right, and the studies use

9 test -- use individuals, infants, who have strong

10 family history, so these are the highest-risk

11 infants. So presumably, if they pass this test,

12 everyone else who is at lesser risk isn’t going to

13 be put at greater risk as a result of the

14 introduction.

15 So that -- is that your question?

16 MEMBER MATTES: Yeah, yeah, that’s --

17 VICE CHAIR KLEINMAN: Yeah.

18 MEMBER MATTES: -- exactly my

19 question. So the follow-up is does the

20 recommendation need to have that caveat in it, or

21 does that group of high-risk people sort of fall

22 out of the definition of the healthy population


81

1 that we’re making recommendations for, and so it’s

2 not necessary?

3 MEMBER DEWEY: Well, I’d like to say

4 we’re not yet at the point of making dietary

5 recommendations. Right now we’re only drafting

6 conclusion statements from the evidence. How to

7 put all this together into a recommendation is the

8 next challenge.

9 Yeah. There was one more question from

10 Rick --

11 VICE CHAIR KLEINMAN: Uh-huh?

12 MEMBER DEWEY: -- and that had to do

13 with sugar-sweetened beverages and why were those

14 related to overweight or obesity and not to the

15 continuous markers of body size or composition?

16 I think that the strongest evidence we

17 have is from one very large study where the outcomes

18 were dichotomous only, and so that’s why we felt

19 comfortable saying that. We didn’t have the same

20 amount or strength of evidence for the direct

21 continuous measures of weight for height or BMI or

22 anything like that.


82

1 That’s my recollection. I’d have to go

2 back to that paper and look at it again, but that

3 was what I remember. Any additions to that?

4 MEMBER MAYER-DAVIS: So is this on?

5 They’ll pick it up. Just start talking. I can start

6 talking. Okay. So back to the -- so this is Beth

7 Mayer-Davis. So, Kay, I have a question to follow

8 up to Rick’s about type 1 diabetes. It’s not

9 specified in the question itself, but I wonder if,

10 in your look at infant feeding with regard to type 1

11 diabetes, you were looking also as the occurrence

12 or appearance of diabetes autoimmunity?

13 MEMBER DEWEY: What was that?

14 MEMBER MAYER-DAVIS: The appearance of

15 diabetes autoimmunity, markers of diabetes

16 auto-antibodies, as a prelude to development of

17 Type 1 diabetes, because that’s where some of the

18 mechanism comes in, in answer to your question,

19 Rick. And there is some literature on that.

20 MEMBER DEWEY: Oh. Darcy is quicker

21 than me. I’m looking here.

22 You’re shaking your head, so those


83

1 markers were not --

2 MS. GUNGOR: No.

3 MEMBER DEWEY: Okay. So it was only

4 the other ones that we defined. Yeah. And again,

5 that was just done by the Complementary Feeding

6 TEC, and all of those definitions of outcomes are

7 in those published papers.

8 MEMBER SABATÉ: Yes. Joan Sabaté.

9 Regarding the timing and regarding the types of

10 foods and the outcomes that you have examined,

11 basically anthropometrics, biological measures of

12 fatty acids and minerals so on and so forth, and

13 also allergy, what was the outcome measured of

14 these studies?

15 I mean, within the 24 months, including

16 to the childhood, in adolescence or in adulthood,

17 or all this above?

18 MEMBER DEWEY: The age of outcome

19 assessment, if I’m correct, varied, depending on

20 the outcome domain. So if I remember correctly,

21 micronutrient status was generally the more short

22 term within the first two years of life.


84

1 I’m looking at Julie. She remembers.

2 Growth, size and body composition went up to -- was

3 it 18 or adulthood? Development went, I think, as

4 far as -- was available -- atopic and allergic

5 disease went all the way to adulthood?

6 Is that right?

7 DR. OBBAGY: Yes.

8 MEMBER DEWEY: Up to 18. And bone

9 health?

10 DR. OBBAGY: Eighteen.

11 MEMBER DEWEY: So most of them went

12 pretty long term. But the evidence base or may not

13 have been very strong out of those longer-term time

14 points.

15 VICE CHAIR KLEINMAN: Are there other

16 questions?

17 CHAIR SCHNEEMAN: So given the number

18 of conclusion statements where you’ve had, let’s

19 say, insufficient evidence or no evidence, I’m

20 interested to know, is the subcommittee working on

21 the research agenda and particularly prioritizing

22 some of the most critical needs as far as this


85

1 research?

2 MEMBER DEWEY: Yeah. We are trying to

3 keep track of research recommendations as we go.

4 From the previous reviews that have been published,

5 they also did a good job of summarizing the research

6 needs. So that’s kind of already there.

7 It’s going to be a huge list, as you can

8 imagine. So prioritizing them is something that

9 I feel we need to discuss. In the context of

10 dietary guidelines, it might revolve around not

11 necessarily one of the most interesting questions

12 but which ones might have the biggest influence on

13 what we advise people to do.

14 So if there’s already compelling

15 evidence from outcomes X, Y and Z for, let’s say,

16 breastfeeding, well, do we need to go further

17 than -- and find outcomes -- you know, other

18 outcomes to add to that or not?

19 Whereas for some of the other dietary

20 recommendations for this age group, there’s almost

21 nothing, and in those cases, we may not know what

22 to say at all, and so in that case, it might be a


86

1 higher priority.

2 So I’m just thinking out loud,

3 actually, about would you prioritize in this

4 particular situation.

5 VICE CHAIR KLEINMAN: All right. So I

6 think adults need to have a little break, and we’ve

7 been going for over an hour and a half, so we’re

8 going to take exactly 10 minutes. Get up and

9 stretch or do whatever else you need to do.

10 And then we’ll return and hear from

11 Sharon Donovan and the Pregnancy and Lactation

12 Subcommittee report.

13 Thank you. So 10:48.

14 (A short recess was taken.)

15 DR. STOODY: Thank you. Thanks for

16 joining us again after the break. I do want to just

17 make a quick announcement. We are in a multistory

18 building, and sometimes fire alarms do happen, so

19 if you hear one, please hold tight. We are told

20 if we are asked to evacuate, we’ll hear an

21 announcement.

22 Sometimes they just evacuate the floor


87

1 that’s involved and the floor above and below, so

2 if that is to happen, we’ll hear an announcement,

3 and the exit is just right there at the top of the

4 stairs.

5 And thank y’all. I know several

6 have -- that is the preferred kind of in-and-out

7 for the meeting, if you can help that happen, just

8 to help kind of minimize some of the distraction

9 here at the front of the room.

10 So just a quick announcement, and I’ll

11 turn it back over to the Committee.

12 VICE CHAIR KLEINMAN: Thank you very

13 much, Eve. I’m going to turn it over now to Sharon

14 Donovan, and she’s going to summarize the work of

15 the Pregnancy and Lactation Subcommittee.

16 MEMBER DONOVAN: Okay. My

17 microphone’s on. So my name is Sharon Donovan, and

18 it’s my pleasure to present on behalf of the

19 Pregnancy and Lactation subcommittee. If I can

20 have the slides, please.

21 VICE CHAIR KLEINMAN: We need to have

22 the slides brought up, please.


88

1 MEMBER DONOVAN: So I’ll go ahead and

2 start talking while that’s coming. So this shows

3 the subcommittee members, and I’d like to thank

4 them all for all of their hard work, on our weekly

5 call, and on the work between the calls.

6 So my goal today will be to discuss the

7 evidence synthesis creating a conclusion for eight

8 reviews. But before we get started, I wanted to

9 just provide just kind of an overview to remind

10 people of the questions that were assigned to our

11 subcommittee.

12 So there were three major categories.

13 One -- the first was nutrients and supplements in

14 fortified foods, and this could be consumed before

15 and during pregnancy and lactation.

16 So we looked at up to six months prior

17 to conception, and during pregnancy and/or

18 lactation. We are examining six nutrients, so

19 B-12, folate, iron, iodine, vitamin D, and

20 omega-3s -- they should sound fairly familiar from

21 Kay’s presentation -- and five outcomes, so human

22 milk composition, gestational diabetes,


89

1 hypertensive disorders of pregnancy,

2 neurocognitive development of the infant, and

3 micronutrient status of the mother.

4 So that was our first set of questions.

5 The second relates to dietary patterns during

6 pregnancy and with five outcomes. I’m not going

7 to read all of those, but you can see these are

8 related to the maternal dietary patterns during

9 pregnancy, and three outcomes during lactation, so

10 milk composition, infant neurocognitive

11 development, and postpartum weight loss.

12 We also had a third area, which was

13 maternal diet and food allergies and atopic

14 diseases in the infant. So as noted, the NESR

15 staff has been working very diligently, and thus

16 far has screened 21,500 articles and extracted the

17 data and assessed risk of bias from 42. And

18 obviously, additional searches and extraction are

19 underway.

20 So again, just -- within each of these

21 three areas, just to briefly remind you of where

22 we are in the process:


90

1 So for folate, we have addressed all

2 five questions. And so the effect of maternal

3 folate from supplements or fortified foods on human

4 milk composition and gestational diabetes was

5 presented in meeting three, and that information

6 is available on the Dietary Guidelines.gov.

7 Today, I will be presenting on maternal

8 folate from supplements and fortified foods on

9 hypertensive disorders of pregnancy,

10 neurocognitive development of the infant, and

11 micronutrient status of the mother.

12 As noted, our committee is currently in

13 the process of refining and prioritizing the

14 additional searches for these -- the rest of the

15 nutrients and these outcomes. So you can just do

16 the math to see this would have been quite a number

17 of systematic reviews to address all of these.

18 So in terms of dietary patterns, today

19 I’ll be presenting a new systematic review on the

20 impact of dietary patterns on human milk

21 composition, and as with the B-24 Project, there

22 were four previous NESR systematic reviews that


91

1 were developed as part of the Pregnancy and Birth

2 to 24 Project.

3 So we examined those, as Kay described.

4 We looked at the -- we ran through each of the

5 statements. We also looked at any papers that have

6 been published since January 2017, which was the

7 end of the these reviews, to see whether any primary

8 research -- and we also looked at existing

9 systematic reviews published since that time to see

10 whether they caught any papers, mainly with an eye

11 to has there anything really been published in the

12 last two years that would impact the conclusions

13 made in those systematic reviews?

14 And as with B-24, we decided to accept

15 those existing reviews, NESR reviews, and so I’ll

16 review those outcomes. Currently, we’re looking

17 at the dietary patterns on gestational weight gain,

18 postpartum weight loss, micronutrient status, and

19 infant neurocognitive development, and the plan is

20 to present those at meeting five. Also underway

21 is the question on maternal diet and food allergies

22 and atopic diseases, which will also be presented


92

1 in March.

2 So jumping into our first folic acid

3 questions, what is the relationship between folic

4 acid supplements and/or fortified foods consumed

5 before and during pregnancy on the risk of

6 hypertensive disorders?

7 So just as a reminder, the definitions

8 that we’ve used for dietary supplements, basically

9 from the Dietary Supplement and Health Education

10 Act, so products other than tobacco that is

11 intended to supplement the diet. And

12 fortification, again, the FDA definition -- the

13 deliberate addition of one or more essential

14 nutrients.

15 So briefly, you’ve seen the layout for

16 the analytical framework. So in terms of folic

17 acid, our interventions and exposures were

18 exposure to and including intake of folic acid from

19 supplements, fortified foods or the combination,

20 and the comparators were a different level of

21 exposure, including no exposure from supplements,

22 fortified foods, or a combination.


93

1 In this case, the population was the

2 women before and during pregnancy, either healthy

3 or at risk for chronic diseases, and in this case,

4 hypertensive disorders of pregnancy.

5 We had intermediate outcomes that we

6 examined, including blood pressure and

7 proteinuria, and then we have the longer-term

8 outcomes of eclampsia, preeclampsia, and

9 gestational hypertension.

10 Summarized at the bottom are the key

11 confounders, and most of those are ones that we’re

12 including in all of our systematic reviews. We

13 also have other factors to continue -- or consider

14 for the hypertension -- hypertensive disorders,

15 which include physical activity and substance

16 abuse and gestational age.

17 So this search was done in

18 combination -- oh, I’m sorry. This one. This

19 search was -- actually, it was. I’m sorry. So

20 this was done in combination with the search for

21 folic acid and hypertension and gestational

22 diabetes, and as I mentioned, gestational diabetes


94

1 was presented at the last meeting.

2 So we screened 622 articles and we

3 included eight related to hypertension, and you can

4 see on the right that the included articles were

5 three RCTs, two non-randomized controlled trials,

6 and three prospective cohorts.

7 And all of them directly asked the

8 question of the relationship between folic acid

9 supplements consumed during -- before and during

10 pregnancy -- and we basically will present later,

11 but we did not find evidence on fortified foods --

12 in folate in fortified foods.

13 So describing first the three RCTs, the

14 sample characteristics between 123 and 450, all of

15 these RCTs were conducted in Iran, and two were from

16 the same study. The interventions -- so again,

17 they were 25 in a normal pre-pregnancy BMI. The

18 race and ethnicity and SES were not reported, but

19 again they were all conducted in the same country.

20 The interventions varied by dose, so

21 .5, 1, or five milligrams of folic acid, and they

22 were all initiated in the first trimester and


95

1 continued through delivery. All reported

2 preeclampsia and blood pressure, and some reported

3 other outcomes, proteinuria, eclampsia,

4 gestational hypertension.

5 So the two non-randomized controlled

6 trials, one was conducted in Italy and one in China,

7 range from 146 to nearly 5,000 subjects.

8 Again, Caucasian, and race and ethnicity in China

9 was not directly reported, nor was SES.

10 The group in Italy had pre -- this was

11 in a higher-risk group, so these were women who had

12 preeclampsia in a previous pregnancy, and so this

13 will factor into some of our conclusions.

14 So this was the one thing that you can

15 imagine, with these different studies, they have

16 different levels of exposure, and also in this

17 study, they had 5-methyltetrahydrofolate as a

18 supplement, and they ranged in initiation, but they

19 all went through delivery.

20 And then the three prospective cohort

21 studies, you can see the n’s. These were in

22 Australia, Canada, and Denmark. The women were


96

1 between 20 and 30 years of age, and you can see the

2 race and ethnicity. They range from low to high

3 SES within these countries.

4 So in these, they actually compared no

5 supplement with a folate or folic acid alone. And

6 they had initiation and duration of various times,

7 so you know, by trying to look at the evidence we’re

8 taking into account when the timing of the

9 initiation and the duration was, and the primary

10 outcome was preeclampsia.

11 So the summary of the evidence. So

12 none of the RCTs found an association between folic

13 acid supplementation and the incidence of

14 hypertensive disorders of pregnancy, including

15 gestational hypertension, preeclampsia, or

16 eclampsia, and none of the studies compared folic

17 acid supplementation to a control group that had

18 no supplementation. So in these studies, the

19 control did have a low level -- lower level of

20 exposure.

21 In contrast, when we looked at the

22 non-randomized controlled trials, both found a


97

1 significant association between folic acid

2 supplementation from early pregnancy through

3 delivery and reduced risk of preeclampsia and

4 gestational hypertension, compared to controls

5 with no folic acid supplementation.

6 And you can see, for preeclampsia,

7 significant reduction, both in this case -- both

8 for high risk and low risk, and for gestational

9 hypertension, again, a significant reduction.

10 And one non-controlled RCT was among high-risk

11 population of women who had previously been

12 diagnosed with preeclampsia.

13 So when we looked at the three

14 prospective cohort studies, the results were

15 mixed. One found an association with folic acid

16 in the first trimester and lower incidence of

17 preeclampsia, but specifically for women with a

18 higher BMI.

19 Another found an

20 association -- significant association between

21 folic acid use between 12 and 20 weeks of gestation

22 and preeclampsia, again, in women at high risk, and


98

1 a third found no association.

2 So our draft conclusion statement is

3 that limited evidence suggests that folic acid

4 supplementation during early pregnancy may have a

5 beneficial effect on reducing the risk of

6 hypertensive disorders during pregnancy among

7 women at high risk, either having a history of

8 preeclampsia or a higher pre-pregnancy BMI,

9 compared to no folic acid supplementation.

10 This conclusion was supported by

11 three -- or two non-randomized controlled and the

12 three prospective cohorts. The studies were all

13 direct in terms of the question, and they were

14 consistent for the higher-risk women.

15 And as with all of the studies, there

16 were some concerns about risk of bias, precision,

17 and generalizability, particularly for some of the

18 studies that were not done in the U.S.

19 So there was moderate evidence

20 suggesting that higher levels of folic acid

21 supplementation during pregnancy, compared to

22 lower levels, including no folic acid, does not


99

1 affect the risk of hypertensive disorders during

2 pregnancy among women at low risk. So we had a

3 separate conclusion for women at high versus low

4 risk.

5 And there’s no evidence available to

6 draw a conclusion about the relationship between

7 folic acid from fortified foods before and during

8 pregnancy and the risk of hypertensive disorders

9 during pregnancy.

10 So turning now to the relationship

11 between folic acid supplements and/or fortified

12 foods consumed by the mother before and during

13 pregnancy and developmental milestones, including

14 neurocognitive development of the infants. This

15 is another new systematic review.

16 So the analytical framework,

17 intervention/exposure were the same in terms of the

18 outcomes. In this case, the population for the

19 outcome is the infant.

20 So we had infants and toddlers, birth

21 to 24 months, but we also incorporated children and

22 adolescents from two to 18 for some of the


100

1 developmental outcomes, and you can see these are

2 listed, because not all of the evidence is

3 available in early childhood.

4 So for example, we were looking at

5 academic performance, also attention deficit

6 disorder, ADHD, anxiety, depression, and autism.

7 So in addition to some of the developmental

8 milestones, we needed to extend the search

9 criteria.

10 So with key confounders, some of the

11 aspects that we added to this one were child sex,

12 breastfeeding practices, intensity and duration,

13 and you can see in other factors to be considered,

14 we also looked at -- took into account, a family

15 history of a diagnosis of a neurocognitive

16 disorder.

17 So we had a total of 1,831 articles that

18 were screened, and six were included. There were

19 actually four studies that produced the six

20 articles. Two RCTs that have three articles.

21 One prospective cohort published in two articles,

22 and one nested case-control. And they all


101

1 addressed the question of again, folic acid

2 supplements consumed during pregnancy on the

3 neurocognitive outcomes.

4 So the sample characteristics are

5 shown, range of 39 to 130, 17 to 37 children, that

6 were conducted in the U.K., Germany, and then a

7 study that incorporated participants from three

8 countries in Europe.

9 You can see the mothers were 20 to 31,

10 mostly white and higher SES, and the outcomes of

11 children for -- were older, so the children in

12 these studies were between six and a half and eight

13 and a half.

14 The interventions, again, varied by

15 dose. They also had an intervention with or

16 without fish oil. The initiation was at 14 or 20

17 weeks gestation and through delivery. And again,

18 the outcomes are shown below, but we’ll go through

19 those.

20 So the one prospective cohort was done

21 in Norway. This was a very large study. Again,

22 the maternal age and high SES, and in this case,


102

1 the children were assessed at three years of age.

2 The dose basically was determined from

3 a questionnaire of folic acid supplementation.

4 And they looked at kind of two different phases.

5 So they looked at early, which could be four weeks

6 before conception to eight weeks of gestation, and

7 then those mothers who are supplemented, who

8 reported the folate between nine and 29 weeks of

9 gestation. So we’re looking at the two different,

10 early and late.

11 So the outcomes were language

12 competence and then language delay. The nested

13 case-control was a study from Israel which, in this

14 case, 60 percent were low SES.

15 They assessed the children between six

16 and 12. The major outcome was AS -- autism

17 spectrum disorder diagnosis, and in this case, the

18 folic acid exposure was assessed by pharmaceutical

19 prescriptions.

20 So they basically were able to look at

21 the women who were prescribed folic acid or not,

22 and they looked before and during pregnancy and the


103

1 duration assessed before and during pregnancy or

2 birth.

3 So the summary of the evidence that

4 generally folic acid supplementation before or

5 during pregnancy was either not associated with or

6 had a beneficial association with the following

7 outcomes:

8 So language development. Two articles

9 from the prospective cohort study showed a lower

10 risk of severe language delay in three-year-olds

11 whose mothers consumed folic acid supplements

12 during early pregnancy.

13 For ASD, the one nested case-control

14 found a significant association between folic acid

15 supplementation before and during pregnancy and

16 lower ASD risk in eight-to-12-year-old children.

17 So for cognitive development, the

18 findings were inconsistent and no conclusions can

19 be drawn. For social-emotional development, we

20 included one study with concerns and no conclusion

21 could be drawn.

22 When we looked at movement or physical


104

1 development, academic performance, ADD or ADHD,

2 anxiety and depression, there was no evidence on

3 supplementation before or during pregnancy. And

4 developmental milestones and neurocognitive

5 development, there’s no evidence on

6 supplementation during lactation and/or intake of

7 folic acid from fortified foods consumed before or

8 during pregnancy and lactation.

9 So the draft conclusion statement:

10 Limited evidence suggests folic acid

11 supplementation during early pregnancy may be

12 associated with lower risk of delayed language

13 development in the child.

14 So that, again, the conclusions were

15 based on two studies from one prospective cohort

16 study. The study -- they were direct in terms of

17 the question. We had some issues with

18 consistency, and there were some concerns, again,

19 regarding risk of bias, precision, and

20 generalizability, because it was one study, one

21 prospective cohort study.

22 There was limited evidence to suggest


105

1 that folic acid supplementation before and during

2 pregnancy may be associated with lower risk of

3 autism spectrum disorder in the child.

4 So again, this was based on the one

5 nested case-control study from Israel.

6 Consistency cannot be assigned, and there were some

7 concerns regarding risk of bias, precision, and

8 generalizability.

9 Insufficient evidence is available to

10 determine a relationship between folic acid from

11 supplements and fortified foods consumed before

12 and during pregnancy on cognitive development or

13 social-emotional development.

14 And there’s no evidence on supplements

15 or fortified foods, folate, on movement or physical

16 development of the child, academic performance of

17 the child, and also the ADD or ADHD. So these are

18 supplements and/or fortified foods. And so for

19 these, these are grades not assignable.

20 There was also no evidence for the

21 relationship between folate supplements and

22 fortified foods performed during


106

1 lactation -- pregnancy and lactation on anxiety or

2 depression. So a grade is not assignable.

3 So basically this was looking at

4 lactation. So there was no evidence available to

5 look at supplements consumed during lactation on

6 development milestones, including neurobehavioral

7 development, and no evidence on fortified foods

8 consumed either during pregnancy or lactation.

9 So all the conclusions were based on

10 some folate from supplements before or during

11 pregnancy.

12 So the final folate question from a new

13 systematic review is looking at the relationship

14 between folic acid consumption and maternal


16 Again, similar framework, basically if

17 you look at the health outcomes, when we looked at

18 the folate status, we looked at: plasma blood

19 folate, B12, hemoglobin, mean corpuscular volume

20 and red cell -- red blood cell distribution width,

21 were the outcomes.

22 4,512 articles were screened, of which


107

1 there were four -- I’m sorry -- for the -- I’m

2 sorry -- 14 for micronutrient status, and of those

3 14, there were nine RCTs, three prospective

4 cohorts, one randomized cohort and one

5 uncontrolled before-and-after study.

6 All of the studies addressed directly

7 the question of supplements consumed before and

8 during pregnancy and lactation and micronutrient

9 status.

10 So to go through the nine RCTs, they

11 range from a very small study to a study of 189.

12 Three were conducted in Canada, two in the U.S.,

13 and one each in Iran, the U.K., Mexico, and France.

14 The women in most studies were between the ages of

15 26 and 34, mostly Caucasian and high SES, but one

16 study was in lower -- teenaged mothers with lower

17 SES. And in one study, it was conducted in 100

18 percent iron-deficient anemic women.

19 So the interventions varied across the

20 nine RCTs, ranging from 300 micrograms to five

21 milligrams of folic acid. And also, one study

22 looked at the methyltetrahydrofolate, and one


108

1 study looked at folinic acid.

2 The initiation varied from

3 pre-conception during pregnancy as well as

4 postpartum, and the duration was between one and

5 12 months. And most included serum plasma or red

6 blood cell folate, and other outcomes, common

7 outcomes, were B12, hemoglobin and mean

8 corpuscular volume.

9 So the three prospective

10 cohorts -- again, we’re -- you can see the n,

11 conducted in Ireland, Germany and Canada, again,

12 29- to 30-year-old women, and within these

13 countries, race, ethnicity and SES were not

14 reported.

15 They looked at folic acid

16 supplementation via questionnaire versus none.

17 And there was various times of initiation and

18 duration of the study. So again, when we’re

19 looking at the literature, we’re trying to take

20 into account dose as well as the timing of exposure.

21 All of these reported plasma folate, and two

22 reported red blood cell folate, and one incidence


109

1 of folate deficiency.

2 The retrospective cohort -- Sorry. I

3 think I said that wrong before. The retrospective

4 cohort was conducted in Turkey. They compared

5 zero versus 400 micrograms per day of folic acid.

6 They initiated pre-conception, but the timing of

7 assessment varied by the participant. So they

8 all -- they didn’t have a specific time point.

9 The outcomes, again, folate,

10 hemoglobin, and incidences of folic deficiency.

11 And there was a -- one uncontrolled

12 before-and-after study conducted -- a small study

13 conducted in Japan, and there was a limitation

14 of -- was -- that was not a lot in terms of the

15 participant characteristics, other than all from

16 the same SES.

17 So these were women that they gave a

18 supplement of one milligram per day of folic acid,

19 and then they were each -- sort of -- their own

20 control. They initiated this anywhere between

21 three and 25 weeks postpartum, and the duration was

22 four weeks.


110

1 So, all but one study found a

2 significant association between folic acid

3 supplementation and at least one outcome measure.

4 So, nine of 13 found positive association between

5 folic acid supplementation and plasma or serum

6 folate.

7 Nine of the 10 found positive

8 association between supplementation and red blood

9 cell folate. And two of five reported positive

10 association between folic acid supplementation and

11 hemoglobin. And there was no association found

12 between folic acid supplementation and these other

13 measures that we had included.

14 So, based on that, we’ve drafted a

15 conclusion that strong evidence suggests that

16 folic acid supplementation before and during

17 pregnancy is positively associated with folic acid

18 status using the outcomes of serum and plasma

19 and/or red blood cell folate.

20 The studies, again, were direct and

21 precise and consistent. Some concerns regarding

22 generalizability, but we felt that the evidence was


111

1 strong.

2 There was moderate evidence suggesting

3 that folic acid supplementation during lactation

4 is positively associated with red blood folate and

5 may be positively associated with serum and plasma

6 folate.

7 There was insufficient evidence


9 folic acid supplements before and during pregnancy

10 or during lactation on hemoglobin, MCV or B12, so

11 grade not assignable.

12 And no evidence to determine a

13 relationship with folic acid supplemented during

14 this time on red blood cell distribution width.

15 And again, there was no data, no evidence on folic

16 acid from fortified foods before and during

17 pregnancy and folate status.

18 So that’s the summary of the three, and

19 our final three searches on folic acid. And so now

20 I’m going to turn to the question related to dietary

21 patterns. So, the first is a new NESR systematic

22 review on dietary patterns consumed during


112

1 lactation and human milk composition and quantity.

2 So again, a dietary pattern, as is being

3 defined and used by all of the subcommittees: so,

4 we’re looking at quantities, proportions,

5 varieties, combinations, of the different foods.

6 So, to set up the analytical framework

7 for dietary patterns, the intervention and

8 exposure is consumption of and/or adherence to a

9 dietary pattern versus consumption or adherence to

10 a different dietary pattern or a different level

11 of consumption.

12 For example, we’ll discuss studies that

13 have different fatty acids. So, the population

14 for milk composition, again, women during

15 lactation, healthy or at risk of chronic disease,

16 human milk quantity. These are exclusively or

17 predominantly breastfeeding women who are healthy

18 or at risk of chronic disease.

19 So we had a number of outcomes for human

20 milk composition. And these -- the milk samples

21 were all collected -- needed to be collected after

22 14 days postpartum, so we were looking at more


113

1 mature human milk, not colostrum.

2 So, we had macronutrients. We have

3 water-soluble vitamins including choline,

4 fat-soluble vitamins, iodine and selenium for the

5 minerals, human milk oligosaccharides, and any

6 bioactive -- of these bioactive proteins. And for

7 human milk quantity, it was assessed in milk

8 collected after 14 days.

9 So, the search, over 3,000 articles

10 were screened, of which seven were included in the

11 final summary. So, these were three RCTs that

12 produced four articles and two cross-sectional

13 studies.

14 And I just wanted to mention that, in

15 general, cross-sectional studies are not included,

16 or are excluded, but because oftentimes for human

17 milk composition, that’s the only type of data

18 that’s available -- there’s a lot of RCTs or

19 prospective cohorts -- so we made a decision, and

20 this had been previously published and was open for

21 public comment. So that is just one difference

22 when we’re looking at human milk.


114

1 So, all of them address the

2 relationship between maternal dietary pattern

3 during lactation and either human milk composition

4 or quantity. So, the three RCTs, again,

5 relatively small studies, seven to 15 mothers,

6 conducted in the U.S. and Canada, 29 years of age,

7 and SES and race and ethnicity not reported.

8 So, the initiation between six weeks

9 and six months postpartum. The durations were

10 four to 14 days. And they were reporting

11 different -- varied patterns. So carbohydrate,

12 either lower carbohydrate or higher fat versus

13 within the acceptable macronutrient distribution

14 range, or the AMDR. Another looked at higher fat,

15 and a higher carbohydrate and lower fat, and

16 another, higher fat versus consumption within the

17 AMDR.

18 So, you can see the various outcomes.

19 Most of the studies reported outcomes on fatty

20 acids, and one for B12.

21 So, for the cross-sectional studies,

22 these were conducted in the U.S. and Canada. They


115

1 were, on average, 30 -- nearly 30 -- I’m

2 sorry -- U.S. and China. The moms in the U.S. were

3 highly educated and in China, high-middle income,

4 and within the U.S., the race/ethnicity, reported

5 mostly white.

6 So, initiation, between 21 days

7 postpartum and six months, and nine and a half

8 months postpartum. So, these were ones that

9 looked more at the overall dietary patterns. So,

10 the study in the U.S. compared milk composition

11 with vegan, vegetarian, and non-vegetarian

12 mothers. And the study from China basically divided

13 the mothers into four different dietary patterns.

14 So, it’s mushrooms, meat, seafood; soy, nuts,

15 dairy; fruits, vegetables; and then grains,

16 potato, beans and eggs.

17 So, summary of the evidence. So, one

18 cross-sectional study assessed the relationship

19 between maternal dietary patterns and total fat

20 levels in human milk and found no association.

21 Three RCTs assessed the relationship

22 between maternal diet based on macronutrient


116

1 proportions and total fat level in milk. Two found

2 a positive association -- positive relationship

3 between greater than 35 percent of energy from fat

4 and total fat in human milk, and one study found

5 no association between macronutrient proportions

6 and maternal diet and total fat.

7 So, the draft conclusion statements for

8 total fats is that insufficient evidence is


10 dietary patterns consumed during lactation and

11 total fat in milk, and there’s limited evidence to

12 suggest that maternal consumptions of diets higher

13 in fat during lactation is related to higher total

14 fat, with a grade of Limited.

15 The studies were consistent, but there

16 were concerns about precision, generalizability,

17 and consistency, and we had a long conversation

18 yesterday, because these are also being used for

19 other outcomes that -- probably measuring fat in

20 human milk is one of the most difficult components,

21 because some studies were measuring during the fed

22 state versus the fasting state, and because the


117

1 content of milk differs from fore-milk to

2 hind-milk, so within a single feeding, if they’re

3 just taking a single sample or not a full breast

4 expression or sampling over 24-hour periods, all

5 of these things can really affect the composition.

6 So that was, you know, some of the concerns that

7 we have about the precision.

8 So two cross-sectional studies and

9 three RCTs assessed the relationship between

10 maternal dietary patterns, including based on

11 macronutrient proportions and levels of saturated

12 fatty acids, MUFAs and PUFAs, and there were mixed

13 results.

14 So in terms of saturated fats, MUFAs and

15 PUFAs, there’s limited evidence to suggest the

16 maternal dietary patterns during lactation,

17 including diets based on macronutrient

18 distributions, are related to the relative

19 portions of saturated fat, MUFAs and PUFAs.

20 And we meant to very specifically say

21 relative proportions, because studies also

22 presented concentrations, and they were not


118

1 effects on concentrations, there were primarily

2 with the proportions of these fatty acids. So

3 again, some concerns about risk of bias and limited

4 precision and generalizability were some of the

5 concerns the committee had.

6 So, one RCT assessed the relationship

7 between maternal diet based on macronutrient

8 proportions and milk quantity, and there was no

9 association.

10 Also, there was one that looked

11 at -- one RCT -- on the relationship with total

12 protein levels in milk, and there was no

13 association. And the last, one cross-sectional

14 study assessed the relationship between maternal

15 dietary patterns and B12, and this was the study

16 that compared the vegan, vegetarian and

17 non-vegetarian, and while there is no association

18 with dietary patterns, we found that 56 percent of

19 the vegan women were taking a B12 supplement, and

20 so we thought that they were really kind of unable

21 to determine the impact of dietary patterns on B12.

22 So, in terms of the draft conclusion


119

1 statements, on quantity, there’s no evidence

2 available to determine a relationship between

3 dietary patterns and milk quantity, and

4 insufficient evidence to determine a relationship

5 on maternal diets differing in macronutrient

6 distribution during lactation and milk quantity.

7 Again, similar -- so for total protein,

8 no evidence for dietary patterns and no evidence

9 for dietary patterns differing in macronutrient

10 composition. And for B12, again, insufficient

11 evidence is available to determine the

12 relationship between maternal dietary patterns

13 during lactation and vitamin B12 concentrations in

14 human milk.

15 So, there were no studies found that

16 assessed the relationship between maternal dietary

17 patterns and human milk levels of these other

18 nutrients that were part of our framework, so our

19 water-soluble vitamins, fat-soluble vitamins,

20 iodine, selenium, human milk oligosaccharides or

21 bioactive proteins.

22 So, I’m not going to read all these, but


120

1 basically these are the draft conclusion

2 statements that there was no evidence, and so all

3 are grades not assignable.

4 So now I just -- we’ll go through

5 summarizing the results from the existing NESR

6 reviews. So as was mentioned, as part of the

7 Pregnancy B-24 project, there were four systematic

8 reviews that were conducted that are pertinent to

9 the Pregnancy and Lactation Subcommittee.

10 So, the first was the relationship

11 between dietary patterns during pregnancy and the

12 risk of hypertensive disorders during pregnancy,

13 and the second was risk of gestational diabetes.

14 Then there were two systematic reviews

15 looking at dietary patterns during pregnancy on

16 infant outcomes, so gestational age at birth and

17 birth weight standardized by gestational age and

18 sex.

19 So we are, as I mentioned, adopting the

20 existing reviews. But new protocols are posted on

21 DietaryGuidelines.gov. So again, if you’re

22 interested in the complete documentation, they’re


121

1 available at DietaryGuidelines.gov.

2 In addition, just to acknowledge this

3 was the member of the Pregnancy Technical Expert

4 Collaborative, or TEC, who worked on this and

5 drafted the conclusions. And these four

6 systematic reviews, as with the ones that Kay

7 mentioned, were published in the American Journal

8 of Clinical Nutrition in 2019.

9 So, the two maternal outcome systematic

10 reviews were combined in one paper, and the two

11 infant systematic -- pregnancy outcome, birth

12 outcomes, were in another. So you can not only

13 review the actual results of the systematic reviews

14 on DietaryGuidelines.gov. But, you can also refer

15 to these manuscripts.

16 So just to briefly review the evidence,

17 so for the first, what is the relationship between

18 dietary patterns during pregnancy and the risk of

19 hypertensive disorders?

20 So, this systematic review included

21 eight studies from four cohorts and one RTC, and

22 this was over a 37-year range of evidence. So,


122

1 I’ll just reiterate, and I mentioned before what

2 Kay mentioned, but we also did then look to see what

3 was published after January 2017 in order to make

4 our final decision on whether we would go ahead and

5 accept the existing reviews.

6 So for these questions related to

7 dietary patterns and risk of hypertensive

8 disorders, the limited evidence in healthy

9 Caucasian women with access to health care suggest

10 the dietary patterns before and during pregnancy

11 higher in vegetables, fruits, whole grains, nuts,

12 legumes, fish and vegetable oils and lower in meats

13 and refined grains are associated with reduced risk

14 of hypertensive disorders during pregnancy,

15 including preeclampsia and gestational

16 hypertension.

17 Not all components of the assessed

18 dietary patterns were associated with all

19 hypertensive disorders. So limited -- the grade

20 was limited.

21 Evidence is insufficient to estimate

22 the association between dietary patterns before


123

1 and during pregnancy and the risk of hypertensive

2 disorders in minority women and those of lower

3 socioeconomic status. So, grade not assignable.

4 So, the relationship between dietary

5 patterns during pregnancy and gestational

6 diabetes. This was -- included 10 prospective

7 cohorts and one pilot RCT, again, collected between

8 publication January 1980 and January 2017.

9 So, this systematic review concluded

10 there was limited but consistent evidence

11 suggesting certain dietary patterns before

12 pregnancy are associated with a reduced risk of

13 gestational diabetes.

14 These protective dietary patterns are

15 higher in fruits, vegetables, whole grains, nuts,

16 legumes and fish, and lower in bread and processed

17 meats. Most of the research was conducted in

18 healthy Caucasian women with access to health care.

19 Evidence is insufficient to estimate

20 the association between dietary patterns during

21 pregnancy and the risk of gestational diabetes.

22 So, again a conclusion on diet before pregnancy,


124

1 but not actually during pregnancy, so grade not

2 assignable.

3 So, in turning now to the infant

4 outcomes. The relationship between dietary

5 patterns in pregnancy and gestational age at birth.

6 There were 10 prospective cohorts and one RCT,

7 again, over the same time range.

8 So, limited but consistent evidence

9 suggests that certain dietary patterns during

10 pregnancy are associated with lower risk of preterm

11 birth and spontaneous preterm birth. Protective

12 dietary patterns are higher in vegetables, fruits,

13 whole grains, nuts, legumes and seeds, and seafood,

14 for preterm birth only; and lower in red meat,

15 processed meats, and fried foods. Again, noting

16 a limitation, most of the research was conducted

17 in healthy Caucasian women with access to health

18 care.

19 And this is kind of the opposite, that

20 the evidence was insufficient to estimate the

21 association on dietary patterns before pregnancy

22 and gestational age at birth, as well as preterm


125

1 birth.

2 So, the last relationship between

3 dietary patterns during pregnancy and birth

4 weights, standardized by gestational age and sex,

5 there were 18 prospective cohorts, one

6 retrospective cohort, and two randomized

7 controlled trials.

8 So, the conclusion is that no

9 conclusion can be drawn on the association between

10 dietary patterns during pregnancy and birth weight

11 outcomes. Although research is available, the

12 ability to draw conclusions is restricted by

13 inconsistency of study findings, inadequate

14 adjustment of birth weight for gestational age and

15 sex, and variation in study design, dietary

16 assessment methodology, and adjustment for key

17 confounding factors.

18 And insufficient evidence exists to

19 estimate the association between dietary patterns

20 before pregnancy and birth weight outcomes. In

21 this case, there were not enough studies available

22 to answer the question.


126

1 So, our ongoing work is -- I mentioned

2 that we are refining and prioritizing work on

3 dietary patterns during pregnancy and

4 micronutrient status; dietary patterns during

5 lactation and developmental milestones of the

6 child, including neurocognitive development; and

7 dietary supplements and fortified foods for all the

8 other nutrients besides folate.

9 So as noted, we’ll review the evidence,

10 grade, and draft conclusion statements for these

11 following questions: dietary patterns in

12 pregnancy and gestational weight gain; patterns

13 during lactation and postpartum weight loss; the

14 maternal diet during pregnancy and lactation on the

15 risk of child food allergies and atopic diseases.

16 And the plan is then to present these at the meeting

17 in March.

18 So again, thanking the subcommittee

19 members, as well as our support staff, which we

20 would not be able to get through all of this work

21 without all their hard behind-the-work scenes.

22 So, I will be happy to take questions.


127

1 (Applause.)

2 VICE CHAIR KLEINMAN: That was a great

3 summary. So, any questions from the Committee?

4 Rick?

5 MEMBER MATTES: Only one this time.

6 Rick Mattes. So, what’s known about the validity

7 of self-reported supplement use during pregnancy

8 and lactation? Is it different from the general

9 population? Can we believe this data more or less

10 than general studies about diet and outcomes?

11 And in any of these trials, was there

12 objective verification of compliance with a

13 prescribed dose?

14 MEMBER BAILEY: So, you can get a

15 compliance sometimes in a clinical trial -- this

16 is Regan answering with Sharon, not for Sharon.

17 So, there are ways to look at the supplements by

18 putting PABA in and getting recovery from urine,

19 so that’s one way to test it.

20 I can’t speak to whether or not that was

21 done in your studies, but I just wanted to make that

22 comment.


128

1 MEMBER DONOVAN: I think it’s a great

2 question, and I don’t know if anyone else is aware

3 of studies where they’ve looked at self-reported

4 compliance of pregnant versus non-pregnant women.

5 Obviously, women during pregnancy may

6 be taking supplements more often and may be more

7 motivated, but I don’t think there’s the evidence

8 and -- just thinking offhand -- and if anyone can

9 speak to that in terms of the studies that we

10 reported; I’m not sure that anyone actually

11 confirmed intake of the folate supplements.

12 MEMBER STANG: Jamie Stang. Yeah. I

13 was on the Pregnancy TEC, and studies for the most

14 part did not report compliance. I know from

15 unpublished work that the compliance rates start

16 out high, and as you go through pregnancy, they drop

17 off, but in terms of actual published documentation

18 of what that compliance would be, I’m not aware of

19 any.

20 MEMBER MATTES: So just -- this is a

21 comment that may be a good point to add into the

22 discussion of this section.


129

1 MEMBER DONOVAN: That’s a great point,

2 and also research needs -- to have better

3 collection of that type of data.

4 (Off-mic comments.)

5 MEMBER DONOVAN: Perfect.

6 MEMBER BOUSHEY: So, this is Carol

7 Boushey. And I’m looking at the analytical

8 framework for the folic acid with supplements.

9 And you don’t have to look at it; you have it

10 memorized. So -- but folic acid and supplements

11 and the fortified foods, before and during

12 pregnancy and lactation.

13 And one of the studies, I think, had 11

14 people or 15 or something like that, and you had

15 said it was a small sample size, and in the

16 frequency-of-eating group, we actually did -- went

17 through the process of figuring out sample size so

18 that we could screen out some of the smaller

19 studies.

20 And I wonder if you might consider doing

21 that for some of your studies, so that you can

22 determine if those studies actually didn’t meet


130

1 sample size.

2 So it wasn’t that you, you know, went

3 crazy over it anyway, but still it might be nice

4 to have that documentation.

5 MEMBER DONOVAN: Yeah. No. That’s a

6 great point. I remember we had this conversation

7 at the last meeting, and I think -- we also talked

8 about for the RCTs, that, because they’re more

9 controlled, that the n was not as -- necessarily

10 as much of a consideration, but I think -- I don’t

11 remember if this study with 11 was an RCT or -- so

12 I can’t speak to that directly, but I think it’s

13 an excellent point.

14 And as you could see, the studies varied

15 from 11 to 45,000, so it’s quite a mixed literature

16 that we’re trying to assess and draw conclusions

17 from.

18 CHAIR SCHNEEMAN: I had a quick -- this

19 is Barbara Schneeman. I had a question, again,

20 going back to the supplementation.

21 I know that in your protocol, you

22 allowed for multivitamin supplements, and I’m just


131

1 wondering then, as you went through the data and

2 the evidence where you’re trying to then look at

3 the impact of one nutrient, folic acid, how did you

4 deal with the multivitamin side of it?

5 DR. DONOVAN: So, I think when we

6 looked at that then the control group would have

7 had that exposure without the folic acid. So, we

8 didn’t just look at folate within a multivitamin

9 supplement alone.

10 So, if they needed, they could have

11 other vitamins without folic acid or those vitamins

12 with the folic acid.

13 VICE CHAIR KLEINMAN: Any other

14 comments or questions? Everybody must be very

15 hungry.

16 (No response.)

17 VICE CHAIR KLEINMAN: All right, then.

18 Any concluding remarks?

19 CHAIR SCHNEEMAN: My only concluding

20 remarks would be to thank the subcommittees, you’ve

21 covered a lot of information in a -- in actually

22 a relatively short period of time, and also thank


132

1 you to the staff for the work that’s done to help

2 pull this together.

3 So, I think -- you know, our next

4 subcommittee is doing to be Dietary Fats and

5 Seafood Subcommittee, but I think we’re best to

6 start that after the lunch break, because I know

7 they have a lot to report back on as well. Correct?

8 So, I’ll just open it up to the

9 Committee. Do you have any general comments at

10 this point before we break, particularly if you

11 start to see things where you’re seeing threads

12 across the different subcommittee work or things

13 that sort of tie these areas together?

14 (No response.)

15 VICE CHAIR KLEINMAN: Hunger wins.

16 CHAIR SCHNEEMAN: Okay. So, we’ll

17 adjourn for now, and then reconvene at one o’clock,

18 and it is important that we start at one o’clock,

19 because that’s for the webinar folks. That’s when

20 we’ll start the YouTube again.

21 So have a good lunch.

22 (A lunch recess was taken.)


133

1 CHAIR SCHNEEMAN: It’s time to get

2 started, and I think they have the YouTube set up.

3 Just a couple of reminders to the Committee: A

4 couple of people pointed out that they couldn’t

5 hear as well, so when you’re using the microphone,

6 please make sure it’s in front of you when you use

7 the microphone, just to make sure people can hear

8 the questions.

9 And I just want to repeat something that

10 I said in my opening remarks, that what you’re

11 hearing are summary statements, draft conclusions,

12 and they’re being presented here for the full

13 Committee consideration in their decision-making

14 process.

15 And the final decisions are what will

16 be in the report. So I just want to, once again,

17 highlight that what you’re hearing about our draft

18 conclusions, summaries of statements.

19 The committee themselves are looking in

20 much more detail at all of the publications that

21 are being presented. So with that, we’re ready to

22 go to our next subcommittee report, and that’s the


134

1 Dietary Fats and Seafood Subcommittee.

2 Dr. Linda Snetselaar is going to give

3 the report.

4 MEMBER SNETSELAAR: I want to

5 acknowledge my committee, Dr. Regan Bailey, Joan

6 Sabaté, and Linda Van Horn, who is here by phone,

7 and also our Advisory Chair, Barbara Schneeman.

8 The NESR, or NESR staff, is

9 implementing protocols for the first two dietary

10 questions that you see on this particular slide,

11 and the topics will be addressed at a future

12 Advisory Committee meeting.

13 We will be presenting a summary of the

14 evidence, draft conclusion statements, and grades

15 on the three seafood questions today. They are in

16 red. And the remaining questions focus on dietary

17 fats and neurocognitive outcomes, along with

18 dietary fats and cancer.

19 As a reminder, we are defining seafood

20 in the following manner. It is marine animals that

21 live in the sea and in freshwater lakes and rivers,

22 and seafood here includes fish and shellfish.


135

1 And this particular slide is designed

2 to sort of orient you to the three questions that

3 we will be focusing on today during my

4 presentation, and we’re doing this because the

5 first two questions have a lot of similarities and

6 some subtle differences.

7 The first question is seafood intake

8 during pregnancy or lactation and neurocognitive

9 development of the child. And the second question

10 is seafood intake during childhood and adolescence

11 and neurocognitive outcomes.

12 As you will see in the upcoming slides,

13 there are many neurocognitive outcomes, and it’s

14 easy to get confused between these two questions

15 and the various outcomes on which we are reporting.

16 Because the neurocognitive outcomes

17 are varied and most studies did not examine all

18 components of the outcomes, we decided to develop

19 separate conclusion statements for each component.

20 And then the third question, the

21 seafood question here, is looking at seafood intake

22 during childhood and adolescence and


136

1 cardiovascular disease outcomes.

2 So the first question we addressed was,

3 what is the relationship between seafood

4 consumption during pregnancy and lactation and

5 neurocognitive development of the infant?

6 And we used NESR systematic review to

7 answer this particular question. As a refresher,

8 here is the analytic framework we used to approach

9 this question. And we did review this framework

10 in detail during the July Advisory Committee

11 meeting.

12 And in this question, the exposure was

13 assessed in pregnant and lactating women, and the

14 outcome was measured in children, birth to 18

15 years. This is a reminder of the specific

16 intervention exposure and comparators that we

17 focused on.

18 The criteria apply to all of our seafood

19 protocols. And the particular item here to note

20 is that studies must measure seafood consumption.

21 So biomarkers of seafood intake, which might

22 include fish oil or omega-3 polyunsaturated fatty


137

1 acid supplement studies, or studies that evaluated

2 infant formula with added DHA or EPA were not

3 included.

4 This flowchart illustrates the

5 literature search and screening results for two

6 systematic review questions related to seafood

7 consumption and neurocognitive outcomes. One

8 question addresses seafood intake during pregnancy

9 and lactation, and the second question, as I noted

10 before, addresses seafood intake during childhood.

11 There were 25 studies that were

12 included in this review of seafood consumption

13 during pregnancy and lactation and neurocognitive

14 development of the infant, and that’s highlighted

15 in red there.

16 As a reminder, we decided to develop

17 separate conclusion statements for each

18 neurocognitive outcome. The outcomes shown in

19 blue here are the ones we presented draft

20 conclusion statements for during the October

21 public meeting.

22 And I’m going to briefly review these


138

1 draft conclusion statements that have been

2 previously presented. So as a review from the

3 October public meeting, our subcommittee found

4 insufficient evidence was available to determine

5 the relationship between seafood intake during

6 pregnancy and attention deficit disorder, ADD;

7 also attention deficit hyperactivity disorder,

8 ADHD; and autism spectrum disorder-like traits or

9 behaviors or an ASD diagnosis in a child.

10 And due to there being no included

11 studies examining the bottom three outcomes, no

12 evidence was available to determine the

13 relationship between seafood intake during

14 pregnancy and academic performance, anxiety, and

15 depression.

16 The grade was not assignable for all of

17 these outcomes, and that then concludes our review

18 of the statements presented at the last public

19 meeting.

20 I will now present draft conclusion

21 statements for the developmental domain outcomes

22 for the very same question: What is the


139

1 relationship between seafood consumption during

2 pregnancy and lactation and neurocognitive

3 development of the infant?

4 Our subcommittee reviewed evidence

5 pertaining to four developmental domains, and they

6 are shown here on this slide, and we then drafted

7 conclusion statements for each. This evidence was

8 reported during the last public meeting, but it

9 does bear repeating.

10 No studies that met inclusion criteria

11 assessed the relationship between maternal seafood

12 intake during lactation and neurocognitive

13 outcomes, including developmental domains in the

14 child.

15 Twenty-four articles from 18

16 prospective cohort studies assessed seafood intake

17 during pregnancy and developmental domains

18 outcomes. These studies were primarily conducted

19 in the U.S. and also in Europe.

20 Maternal seafood exposure was

21 primarily measured using food frequency

22 questionnaires, though the timing, the type, and


140

1 the amounts of seafood intake were varied. The

2 categorization of seafood intake also varied

3 across studies, so that one study might look at

4 quintiles, and another study might look at servings

5 per week. There was a variety of assessment tools

6 used within each outcome domain. Now I

7 will focus on the first domain, developmental

8 domain, cognitive development. There were 20

9 articles from 15 prospective cohorts which met

10 inclusionary criteria.

11 The majority of the studies detected

12 positive or null associations between seafood

13 intake during pregnancy and cognitive development

14 in children five months to 11 years. And then

15 looking at IQ, or composite intelligence measures,

16 that was done in children four to 11 years.

17 Few studies accounted for all of the key

18 confounders, and there was heterogeneity across

19 the studies in seafood intake categories used in

20 analyses and cognitive assessment methods. This

21 tended to limit the specificity of the conclusion.

22 So our draft conclusion statements are


141

1 moderate evidence suggests that seafood intake

2 during pregnancy is associated with improvements

3 in cognitive development in the child.

4 The grade here is moderate for

5 specifically pregnancy. No evidence is available

6 to determine the relationship between seafood

7 intake during lactation and cognitive development

8 in the child, and the grade here is not assignable,

9 specifically for lactation.

10 Next, we looked at the second

11 developmental domain, language and communication

12 development. There were 14 articles from 12

13 prospective cohorts which met inclusionary

14 criteria. The majority of studies

15detected a beneficial or null association between

16seafood intake during pregnancy and language

17development or verbal IQ in children six months to

1811 years of age.

19 Few of these studies accounted for key

20confounders, and there was heterogeneity in

21maternal seafood intake, such as the timing, during

22 pregnancy, the type and the amount of seafood


142

1 intake.

2 Seafood categorization and analysis

3 was varied. Outcome assessment tools and

4 measurements were varied, and the ages of children

5 at assessment was also varied.

6 So our conclusion draft statements are


8 during pregnancy is associated with improvements

9 in language and communication development in the

10 child. The grade here is moderate, specifically

11 for pregnancy.

12 No evidence is available to determine


14 lactation and language and communication

15 development in the child. So the grade here is not

16 assignable, specifically for lactation.

17 Then our third developmental domain

18 involved movement and physical development.

19 There were 13 articles from nine prospective

20 cohorts which met the inclusion criteria.

21 The majority of the studies found

22 either null or beneficial associations between


143

1 seafood intake during pregnancy and movement and

2 physical development in the child. Few of the

3 studies accounted for key confounders, and there

4 was heterogeneity in, again, maternal seafood

5 intake, timing, type and amount, and types of

6 movement and physical development examined were

7 varied.

8 The outcome assessment tools were

9 varied, and the ages of children at follow-up was

10 also varied. Our draft conclusion statement is

11 insufficient evidence is available to determine


13 pregnancy and movement and physical development in

14 the child.



17 lactation and movement and physical development in

18 the child, so the grade here is not unassignable

19 for pregnancy and lactation.

20 Now, for the fourth developmental

21 domain, social, emotional and behavioral

22 development, there were nine articles from six


144

1 prospective cohorts which met the inclusion

2 criteria.

3 There were no apparent trends across

4 studies, since there were mostly non-significant

5 associations. There was a concern for risk of

6 bias, which we cared greatly about, and as we’re

7 working on these questions, we do focus on this,

8 and this risk of bias was due to few studies

9 accounting for all key confounders, differences in

10 measurement of exposure and outcomes, heavy

11 reliance on parental report for most of the

12 outcomes. And it was difficult to determine the

13 relationship due to heterogeneity. And again,

14 maternal seafood intake, the timing, type and

15 amount, the ages of children at follow-up, six

16 months to 13 years, so variable there, and outcome

17 assessment tools varied. The dimension of social,

18 emotional and behavioral development was also

19 varied in these studies.

20 Our draft conclusion statement is




145

1 pregnancy and social, emotional and behavioral

2 development in the child.



5 lactation and social, emotional and behavioral

6 development in the child. And the grade here is

7 not assignable for pregnancy and lactation.

8 Moving on now to question two, this

9 particular question is, what is the relationship

10 between seafood consumption during childhood and

11 adolescence and neurocognitive development? And

12 we did again using NESR’s systematic review to

13 answer this particular question.

14 This is the analytic framework we used

15 to approach this question. This was reviewed in

16 detail during the July Advisory Committee meeting,

17 and in that particular meeting, we discussed the

18 exposure, childhood and adolescence, through 18

19 years of age, and the outcome was measured in

20 individuals two years and older.

21 This flowchart highlights studies

22 which met the inclusion criteria. Thirteen


146

1 studies were included in this review of seafood

2 consumption during childhood and adolescence and

3 neurocognitive development.

4 Thirteen studies from both randomized

5 controlled trials, RCTs, and prospective cohort

6 studies met inclusion criteria for this review.

7 There were six articles from three randomized

8 controlled trials.

9 Two randomized controlled trials

10 evaluated fish intake in children between the ages

11 of four and six, and the intervention for both the

12 RCTs consisted of fatty fish meals compared to meat

13 meals three times a week for 16 weeks.

14 The third RCT, the FINS-TEEN study, was

15 conducted with adolescents 14 to 15 years, and

16 participants in this particular study consumed

17 fish meals compared to meat meals three times a week

18 for 12 weeks.

19 Outcomes were assessed before and after

20 the trial, and assessment tools tended to vary.

21 There were seven articles from six prospective

22 cohort studies which evaluated seafood intake


147

1 during childhood and neurocognitive development.

2 These studies were done in the U.K. and

3 Sweden and China and Canada. Seafood intake was

4 reported as oily fish or just fish intake, and the

5 majority of studies assessed fish intake using a

6 food frequency questionnaire.

7 Outcomes were assessed in children

8 three to 18 years of age, and there were a variety

9 of assessment tools used. For this particular

10 question, no prospective cohort study accounted

11 for all key confounders.

12 Now I will focus on the evidence which

13 evaluated the developmental domains. The four

14 developmental domains are shown here, along with

15 how many articles. We evaluated outcomes from

16 these specific domains. And the majority of

17 studies were conducted in Northern Europe,

18 particularly in Scandinavian countries.

19 For the first developmental domain,

20 cognitive development, there were seven articles

21 included in our review. Of these seven, four

22 articles were from three randomized controlled


148

1 trials and three articles were from prospective

2 cohort studies.

3 The four articles from three randomized

4 controlled trials found predominantly null or

5 beneficial effects of seafood, compared to meat

6 meals in children four to six years, and 14- to

7 15-year-old adolescents.

8 There were three articles from three

9 prospective cohorts. Beneficial associations

10 were found between child seafood intake at nine to

11 15 years and cognitive development in children 12

12 to 18 years of age.

13 No association was found between child

14 seafood intake and cognitive development at 3.5

15 years. Our draft conclusion statement then is


17 whether seafood intake during childhood and

18 adolescence is associated with improvements in

19 cognitive development in children and adolescents.

20 Grade not assignable here for a specific

21 improvement.

22 Then moderate evidence suggests that


149

1 seafood intake during childhood and adolescence

2 does not have detrimental impact on cognitive

3 development in children and adolescents. And

4 here, the grade is moderate relative to no

5 detrimental impact.

6 For the second domain, language and

7 communication development, five articles were

8 included, three from two RCTs and two from

9 prospective cohort studies.

10 Evidence from the two RCTs found no

11 effect of fish compared to meat meals on language

12 and communication development at four to six years

13 in primary analysis. The two prospective cohort

14 studies found a positive association between


16 and language and communication development and

17 verbal IQ in children 12 to 18 years of age.

18 Heterogeneity was found in child

19 seafood intake, looking at timing, type, amount and

20 duration, and the age of children at assessment was

21 variable, and outcome assessment tools were also

22 variable in these studies.


150

1 So our draft conclusion statement here

2 is insufficient evidence is available to determine

3 whether seafood intake during childhood and

4 adolescence is associated with improvements in

5 language and communication development in those

6 children and adolescents. And the grade here is

7 not unassignable, specifically focusing on

8 improvement.

9 Moderate evidence suggests that


11 does not have detrimental impacts on language and

12 communication development in children and

13 adolescents. The grade is moderate for no

14 detrimental impact.

15 For the third domain, movement and

16 physical development, there were two randomized

17 controlled trials included in our review. Both

18 randomized controlled trials used the nine-hole

19 peg test as the assessment tool.

20 In children four to six years of age,

21 intake of fatty fish meals compared to meat meals

22 have predominantly null effects on manual


151

1 dexterity and fine motor coordination.

2 One study found that fish meals had a

3 beneficial effects on fine manual dexterity, and

4 the fine motor coordination only applied in the

5 non-dominant hand.

6 Due to limited amounts of studies, our

7 draft conclusion statement is insufficient



10 childhood and movement and physical development in

11 children. The grade here is not assignable.

12 For the fourth domain then, social,

13 emotional and behavioral development, three

14 studies were included in the review, two randomized

15 controlled trials. One was conducted in four- to

16 six-year-olds, and one in 14- to 15-year-olds, and

17 they did not find a significant effect of fish meals

18 compared to meat meals on change in behavioral

19 symptoms in primary analysis.

20 In the one article from the one

21 prospective cohort study, there was a null

22 association between seafood intake at three years


152

1 and social, emotional and behavioral development

2 in children at four to 13 years of age.

3 All of these studies used strength -- a

4 strength and difficulties questionnaire, and there

5 was heterogeneity in the ages of the children at

6 intervention, exposure and outcome assessment.

7 And child seafood intake varied in terms of timing,

8 type, amount and duration.

9 Our draft conclusion statement is



12 childhood and adolescence and social, emotional

13 and behavioral development in children and

14 adolescents, and the grade here is not assignable.

15 So moving on to attention deficit

16 disorder, ADD; and attention deficit hyperactivity

17 disorder, ADHD-like behavior for seafood intake

18 during childhood and adolescence, there were two

19 randomized controlled trials included in our

20 review, and these studies found fish meals three

21 times a week compared to meat meals had a null

22 effect on ADD, ADHD-like behavior at four to six


153

1 years, and 14 to 15 years.

2 It was difficult to determine a

3 relationship due to the inadequate number of

4 studies, and outcome assessment relied mostly on

5 parental report.



8 the relationship between seafood consumption

9 during childhood and adolescence and attention

10 deficit disorder or attention deficit

11 hyperactivity disorder-like traits or behaviors.

12 And the grade here then is not assignable.

13 No studies included examined autism

14 spectrum disorder as an outcome. Therefore, our

15 draft conclusion statement is no evidence is



18 and autism spectrum disorder-like traits or

19 behaviors or autism spectrum disorder diagnosis,

20 and here the grade is not assignable.

21 Moving onto academic performance for

22 seafood intake during childhood and adolescence,


154

1 there was one prospective cohort study included in

2 our review, and this study found a significant

3 positive association between frequency of

4 consumption of meals containing fish at 15 years

5 and higher total school grade at 16 years.

6 However, it’s important to keep in mind

7 that it’s difficult to determine a conclusion here

8 due to an inadequate number of studies and concern

9 for risk of bias from measurement of exposure and

10 outcome.




14 during adolescence and academic performance in

15 those adolescents. And the grade here is not

16 assignable.

17 For the outcomes of anxiety and

18 depression for seafood intake during childhood and

19 adolescence, there were two prospective cohort

20 studies included in our review.

21 One prospective cohort study found a

22 significant positive association between greater


155

1 fish intake at 10 to 11 years and lower odds of the

2 diagnosis of internalizing disorder; that included

3 anxiety or depression at 10 to 14 years.

4 And then one prospective study did not

5 find an association between fish intake at 14.5

6 years and depressive symptoms at 17.5 years. It’s

7 difficult to determine a relationship here due to

8 an inadequate number of studies, inconsistent

9 results, and little information describing

10 exposure.




14 during childhood and adolescence and anxiety and

15 depression in children and adolescents. The grade

16 here is not assignable.

17 No included studies examined

18 neurocognitive health in adulthood as an outcome,

19 and therefore our draft conclusion statement is no



22 childhood and adolescence and neurocognitive


156

1 health, which includes cognitive decline, anxiety,

2 and depression in adulthood, and the grade here is

3 not assignable.

4 That concludes our review of the second

5 seafood question.

6 And the third seafood question we

7 reviewed was, what is the relationship between

8 seafood consumption during childhood and

9 adolescence and risk of cardiovascular disease, so

10 we’re moving away from the neurocognitive area.

11 We used NESR’s systematic review to

12 answer this particular question. This is the

13 analytic framework we used to approach this

14 particular question.

15 This was reviewed in detail during the

16 July Advisory Committee meeting, and in this

17 question, the seafood exposure was assessed in

18 childhood and adolescence through age 18 years of

19 age, and intermediate outcomes were measured in

20 children and adults, while endpoint outcomes were

21 only measured in adults.

22 This is a flowchart for the literature


157

1 search and screening results for the third seafood

2 question addressing seafood intake during

3 childhood and adolescence and risk of

4 cardiovascular disease.

5 And there were four studies included.

6 Of the four studies included, two were randomized

7 controlled trials. In both randomized controlled

8 trials, children were 10 to 12 years of age.

9 The first study provided children with

10 school meals, and that included either 100 grams

11 of oily fish or a cheese salad sandwich five times

12 per week for 12 weeks. The second randomized

13 controlled trial provided schoolchildren with six,

14 seven or eight grams of tuna fish. And the

15 intervention frequency, duration and control

16 conditions in this particular study were not

17 recorded. These studies measured blood pressure

18 and blood lipids.

19 The other two studies included in the

20 review were prospective cohort studies, and one

21 study assessed fish intake of 10 years using a

22 seven-day food record at baseline, three and six


158

1 months, and outcomes were assessed looking at blood

2 pressure and blood lipids.

3 The other study assessed fish and oily

4 fish intake at 7.5 years. This was done in the late

5 1930s, and it included a household inventory. And

6 those outcomes looked at were stroke mortality and

7 coronary heart disease mortality, and these

8 particular outcomes were measured during 60 years

9 of follow-up.

10 Results from the few available studies

11 were not consistent. It’s difficult to determine

12 a relationship due to an inadequate number of

13 studies and serious methodological limitations in

14 some of the studies.

15 So our draft conclusion statement here

16 is insufficient evidence is currently available to

17 accurately determine the relationship between

18 seafood consumption during childhood and

19 adolescence and risk of developing cardiovascular

20 disease. The grade here is not assignable.

21 We have completed the systematic review

22 of the three seafood questions, and these now will


159

1 undergo peer review, and we will begin drafting

2 this section of the report.

3 Our subcommittee will now move to

4 examining dietary fats with a series of questions

5 related to that topic, and we will be starting with

6 the relationship between dietary fat and risk of

7 cardiovascular disease.

8 I want to thank the subcommittee

9 members, and additionally thank the staff for the

10 huge amount of work that goes into doing these

11 systematic reviews, and thank you all for being

12 here today to listen to what we have synthesized

13 relative to this particular topic.

14 Thank you.

15 (Applause.)

16 CHAIR SCHNEEMAN: So if we could have

17 comments or questions from the Committee?

18 MEMBER DEWEY: Thank you very much.

19 That was very clear and nicely laid out. The

20 question has mainly to do with the seafood intake

21 during childhood and adolescence and cognitive

22 development outcomes.


160

1 As I recall, there were three

2 randomized controlled trials, but the duration of

3 those was 12 or 16 weeks, and so the question is

4 whether you think it’s plausible that that’s long

5 enough to create the kind of tissue changes that

6 one might think would be the link between seafood

7 and something in the brain?

8 And if it’s not long enough, you know,

9 what is the feasibility of addressing that question

10 with randomized controlled trials of sufficient

11 duration? And should we then look more carefully

12 at the prospective cohort studies?

13 In that situation, I think you said

14 there were three, and that two showed a

15 relationship, and one with the younger age group

16 does not.

17 So in this situation, the value of

18 prospective cohort studies might be pretty high,

19 and I would like to know what your group felt were

20 the key limitations that led you, I think, to the

21 conclusion of insufficient evidence, despite those

22 positive relationships?


161

1 MEMBER SNETSELAAR: Yes. I think we

2 did look at type of study. You’re right. I do

3 think that in many instances -- and we are coming

4 up with some future direction kinds of things, that

5 it would be great to certainly include more

6 prospective studies possibly.

7 But in addition to that, we as a

8 committee have looked at what are some of the

9 concerns that went into looking at prospective

10 studies and, in addition, randomized controlled

11 trials?

12 And do we need additional studies that

13 would focus on more consistency among the

14 assessment, the timing, those things, the duration

15 of the study, those kinds of things. So I think

16 everything you’re bringing up is 100 percent

17 correct.

18 We looked at this and came to a

19 conclusion. I think that one of the things

20 following a list of our conclusions is to work

21 closely with your committee as well and come up with

22 some final conclusions that would incorporate both


162

1 ideas from your committee, and the work your

2 committee has done as well, along with our

3 committee, has been helpful.

4 MEMBER DEWEY: If I could just follow

5 up with that? I don’t think you mentioned it, I

6 did know that you didn’t find any studies for

7 exposure from birth to 24 months and where the

8 outcome was assessed after 24 months of age.

9 So we actually don’t have anything to

10 say about seafood consumption in the first two

11 years of life and developmental outcomes.

12 MEMBER SNETSELAAR: So that may be a

13 future direction.

14 MEMBER DEWEY: Yeah.

15 VICE CHAIR KLEINMAN: Linda, that was

16 just great. My question is about, again,

17 neurocognitive outcomes and the positive results

18 of seafood consumption during pregnancy. And I

19 wonder, is there a dose-response in those studies

20 or was that examined, I guess?

21 And then a second question was, you

22 noted that none of those studies adequately


163

1 controlled for confounders. And I’m wondering

2 whether the effect diminished significantly when

3 confounders were considered?

4 MEMBER SNETSELAAR: Yes. I think -- I

5 remember beginning to talk about this question, and

6 then working very carefully on what should our

7 confounders be? Because the more confounders you

8 have, the more likely you are to end up with no

9 results.

10 And so you know, I think that’s an

11 important question. It was just something that

12 came up again and again, but particularly the

13 prospective cohort studies. And then what was

14 your first question again? I’m sorry.

15 VICE CHAIR KLEINMAN: Whether there is

16 a dosed response in consumption of seafood and the

17 outcome. So, as the exposure increased -- did any

18 of the studies look at increasing exposure and the

19 consequence of that, to lend more credibility to

20 the intervention?

21 MEMBER SNETSELAAR: Yeah. I think we

22 need more studies on, certainly, increased


164

1 exposure, more specifics on the studies we looked

2 at, I’d look to our NESR team to answer that

3 question.

4 But certainly, exposure is incredibly

5 important. And when you look at the amount of

6 seafood in some of the studies, it was incredibly

7 small.

8 CHAIR SCHNEEMAN: Dr. Sabaté.

9 MEMBER SABATÉ: In some of the studies,

10 and I don’t remember exactly which on the slide,

11 as far as answering your question on the

12 dose-response, I mean in some studies it was flat.

13 I mean, for some studies there was a

14 dose response and others had a U-shape. So the

15 intermediate, I mean, had some relationship at the

16 highest amount -- I mean, lower back to no

17 exposure, so it had a U-shape in some of the

18 studies.

19 MEMBER BAILEY: There was a lot of

20 variability. Some studies reported fish intake in

21 grams, others reported it in servings, and so it

22 was kind of hard to synthesize how much actually


165

1 was the exposure.

2 MEMBER NAIMI: Tim Naimi, Boston

3 University. Linda, that was a really nice

4 presentation, and I guess my question is similar

5 to Ron’s and related also to the dose-response, but

6 more along the lines of -- for those ones in which

7 you had exclusively observational studies and none

8 of them had all of the key confounders, and you know

9 the confounding is likely to bias in the direction

10 you found, can you talk about giving it a moderate

11 evidence grade, as opposed to a limited one? I

12 guess that’s where I feel a little bit

13 uncomfortable.

14 VICE CHAIR KLEINMAN: I didn’t push

15 that far, but that’s where I was going as well.

16 MEMBER SNETSELAAR: I think that’s a

17 very good point, and certainly, as we look at these

18 conclusion statements, again, these are not carved

19 in stone, as Barbara has been mentioning several

20 times.

21 And I think as we look at these

22 statements and maybe work with some of the other


166

1 subcommittees, we may make some changes. So very

2 good point.

3 MEMBER BAILEY: For most of the studies

4 there was a beneficial association or a null

5 association, and so we really -- I think there was

6 one study in one subgroup that there was a

7 detrimental association.

8 So the vast majority of the literature

9 was either beneficial or null, which is why we went

10 with a moderate, because of all of the

11 consistency -- and the inconsistency.

12 MEMBER SNETSELAAR: But those

13 decisions were hard-fought and we spent a great

14 deal of time thinking about it.

15 MEMBER SCHNEEMAN: But certainly part

16 of the point here is from the discussion for the

17 subcommittee to take the information and consider

18 the points being raised, also to look where we need

19 cross-talk between the subcommittees.

20 MEMBER MATTES: Rick Mattes. Two

21 questions that are bit more global. So your group,

22 I think singularly reports effects of positive and


167

1 negative, and in this case, there was no

2 significant effect, which could also be said

3 there’s no association, which is the way all the

4 rest of our recommendations seem to read, and I

5 think we should be consistent.

6 Either we’re going to say that there’s

7 effects this way or that way, or we’re just going

8 to say there’s no association, and that difference

9 is between the groups now. We --

10 MEMBER SNETSELAAR: Yes. And --

11 MEMBER MATTES: -- probably can report

12 that --

13 MEMBER SNETSELAAR: Yeah. I think

14 your 100 percent correct, that we do need to be very

15 consistent across the subcommittees. And I think

16 that process is being thought about, and will be

17 in the works soon.

18 MEMBER MATTES: One other, in terms of

19 consistency. So in at least one other subgroup,

20 where you have -- like your question one you have

21 all prospective cohort studies. Did you downgrade

22 trials that only had a single estimate of intake


168

1 at baseline and then track for 10 years and look

2 at an outcome, as opposed to trials that repeated,

3 say, a food frequency question or whatever, so you

4 have some sense that that level of exposure was

5 maintained during that 10-year interval or that the

6 response on that question there was reliable.

7 We held, in another group, a higher

8 standard, and I’m just wondering how you use that?

9 MEMBER SNETSELAAR: Good question.

10 Can I defer to Joanne?

11 MS. SPAHN: What was the question?

12 Specifically address seafood intake during

13 pregnancy.


15 MS. SPAHN: So when we extracted the

16 data, there were maybe a third and maybe a little

17 less than a third of the studies that measured

18 seafood intake more than once during pregnancy, and

19 then during childhood, the tables will indicate

20 whether or not there were repeat measures.

21 Certainly, the RCTs, you know, were a

22 definitive measure of time. I don’t recall the


169

1 childhood having a lot of repeat measures.

2 MEMBER MATTES: Yeah. I would just

3 suggest that when you assign the strength, that

4 that would be a factor that you put into the

5 consideration.

6 MEMBER SABATÉ: Joan Sabaté. I think

7 this is a good point. I recall in the discussions,

8 and I think there was no studies which had repeated

9 measures in childhood that I remember.

10 MEMBER DEWEY: Kay Dewey. I want to

11 follow up on the comment about -- I think you

12 mentioned, Rick, the statement that said that


14 during childhood and adolescence does not have

15 detrimental impact, and that’s been one that you

16 thought you’d just say there’s no association?

17 Is that the one you were --

18 MEMBER MATTES: Well, there are --

19 MEMBER DEWEY: -- referring to?

20 MEMBER MATTES: -- a couple where there

21 is a report of whatever the evidence is pro and

22 whatever the evidence is negative, in no case was


170

1 there a significant association in either

2 direction.

3 In some cases, there was insufficient

4 evidence, but if there’s evidence of no

5 detrimental, is that different from no evidence of

6 association?

7 MEMBER DEWEY: Right. And so I just

8 want to clarify that we’re talking about the same

9 conclusion statement. And I’m not sure if this is

10 explained, but my understanding is that this was

11 driven in part by the concern about mercury

12 exposure, and that there is the concern about

13 detrimental effects.

14 MEMBER SNETSELAAR: Uh-huh.

15 MEMBER DEWEY: Now -- so in -- on one

16 hand, I think having a statement about no harm is

17 useful, but on the other hand, the way you approach

18 that question is different than when you’re trying

19 to show a relationship in the sense of it being a

20 safety kind of study analysis.

21 And so I don’t know if the studies

22 looked at it the right way in terms of ruling out


171

1 harm, which is different from the way you approach

2 it when you are saying that there is a benefit.

3 So that might be something to look at

4 again. If they did it the appropriate way --


6 MEMBER DEWEY: -- I think it’s

7 important to say that --


9 MEMBER DEWEY: -- and which -- how many

10 did, because if the statement is possible about no

11 harm, that would be extremely useful.

12 MEMBER SNETSELAAR: Good point.

13 Thank you.

14 MEMBER SABATÉ: Again, Joan Sabaté.

15 The no harm relates to the cognition, not to any

16 other factors. You know we had a series of studies

17 -- maybe 14 or 15, I don’t remember of which only

18 two or three seems to have some relationship that

19 was significant, one with a U-shape included, but

20 many had basically flat, no relationship.

21 So we can do the conclusion that seems

22 there was none that has a detrimental effect as far


172

1 as cognition. And we can do this conclusion. The

2 no harm relates only to cognition, not to any other

3 parameter. As far as the studies, especially the

4 prospective studies, not all, as a matter of fact,

5 if I remember correctly, many of them were not

6 originally designed to test the fish effect; it was

7 mainly to design the harmful effects of mercury.

8 And by the way, in the second

9 publication, there was something as far as the

10 consumption of fish and cognition. So we have some

11 of the studies of the prospective studies that were

12 not originally designed for, you know, fish intake

13 and cognition.

14 MEMBER ARD: Jamy Ard. So just to

15 continue on in terms of how we’re describing

16 certain effects, my initial impression if, after

17 seeing the words around -- associated with

18 "improvements in," et cetera, makes me feel like

19 that’s a treatment effect or that something started

20 from a deficit, and I don’t know if that is shared

21 by others, but I just wanted to share that, in terms

22 of it’s not the same to me as something that might


173

1 say it had a beneficial effect or -- I don’t know

2 exactly the other ways that you -- these things are

3 quantified in terms of cognition or language and

4 communication and those types of things.

5 But that may be something to think

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

about.

MEMBER SNETSELAAR: Good point.

MEMBER NOVOTNY: Rachel Novotny.

This is a little bit out of place, but related to

this conversation about language and how we’re

reporting -- and it makes me wonder with most of

our questions whether we don’t want to consider

both protective effects.

At any rate, to consider whether

there’s another pass at our questions for some of

these things, I’m thinking specifically about --

which I’ve been talking to Sharon about -- the upper

limit for folic acid, which was not specifically

our question, but it feels like we should say

something about that.

So we may need to make another pass at

our studies as well to see if there’s something we


174

1 could legitimately say about that. I think it’s

2 a general question for us as to whether we’re

3 considered sort of both ends of the spectrum for

4 many of our questions.

5 CHAIR SCHNEEMAN: Other comments or

6 questions?

7 MEMBER BAILEY: Linda Van Horn is on

8 the line, I don’t know if she - if we want to give

9 her an opportunity to comment, or if she has

10 anything to say.

11 CHAIR SCHNEEMAN: Is she on the line?

12 She is mainly listening, so she’ll let us know.

13 (Laughter.)

14 CHAIR SCHNEEMAN: I think these were

15 all useful comments for the subcommittee to take

16 back and look at.


18 CHAIR SCHNEEMAN: And also working

19 with the staff to make sure we do have consistency

20 across the subcommittee. So I think then we’ll

21 move to our next subcommittee report, which is the

22 Beverages and Added Sugars subcommittee, and Dr.


175

1

2

3

4

5

6

7

8

9

10

11

12

Mayer-Davis will do that report.

MEMBER MAYER-DAVIS: Thank you very

much. So first I do want to recognize the great

work of the Committee, Drs. Leidy, Mattes, Naimi

and Novotny, and Schneeman, to say nothing of, of

course, the NESR staff that just continues to amaze

us every day.

So let’s see. I’m clicking the

clicker, but see myself instead of a slide. That’s

not really that I want to see, actually. So let’s

see. What do I need to do here? Oh, that’s way

farther than I need to be.

13 Let’s see.

14 (Pause.)

15 MEMBER MAYER-DAVIS: All right.

16 There we go. So let me just overview what we will

17 go over in this session today. This is just a brief

18 summary of the questions that we addressing in this

19 particular committee, questions related to

20 non-alcoholic beverages, added sugars and alcohol.

21 So we have completed our work towards

22 our draft conclusions for birth weight


176

1 standardized for gestational age and sex as an

2 outcome related to non-alcohol beverages underway;

3 a set of questions related to various non-alcoholic

4 beverages in relation growth, size, body

5 composition, and risk of overweight and obesity,

6 for which there’s been a screening of some 17,000

7 articles and 214 articles identified to be included

8 for that set of questions, with 70 articles

9 currently under review for a subset of questions

10 that are focused on milk.

11 I won’t be presenting details on that

12 particular piece today because that is -- we are

13 in the midst of that effort. Also underway are

14 questions related to added sugars and risk of

15 cardiovascular disease, screening is underway

16 relatively early on for that with 5,000 articles

17 screened.

18 Coming up next are questions related to

19 added sugars and risk of type 2 diabetes and also

20 outcomes of growth, size, body composition, and

21 risk of overweight and obesity.

22 We are also working on questions


177

1 related to alcohol and all-cause mortality, and I

2 will be presenting some more information about that

3 today, as well as presenting information about

4 non-alcoholic beverages and birth weight.

5 So that’s the overview. So now we will

6 focus on this particular question that you see here

7 on the screen. What is the relationship between

8 beverage consumption during pregnancy and birth

9 weight standardized for gestational age and sex?

10 And this is approached via the NESR systematic

11 review process.

12 This is our analytic framework, and I

13 do want to take a moment on this, because there are

14 actually quite a large number of decisions embedded

15 in this analytic framework that took a fair amount

16 of time to sort through and that follow for much

17 of our work for a range of questions.

18 So you’ll see in terms of intervention

19 and exposure, you know, we set out these various

20 sub-types of beverages, and you can see the list

21 here. We’ve shown this before. That’s the same

22 list that we’ve had.


178

1 The comparator is something that I want

2 to highlight, because that does impact on the

3 studies that we review. So for our comparator,

4 we’re looking at differences in amount of the same

5 beverage consumed, which could include milk

6 consumption, of a particular beverage, or versions

7 of the beverage diluted with water.

8 We also consider as a comparator a given

9 beverage versus a solid form of that same food,

10 broadly speaking, a given beverage versus water.

11 And then specifically we are looking at

12 sugar-sweetened beverages compared to low- or

13 no-calorie sweetened beverages, and we’re looking

14 at dairy milk with different amounts of fat.

15 So this provides the scope, really, of

16 what we’re doing. Otherwise, you know, if you just

17 have beverages with no clarity with regard to

18 comparator, you would not be able to go through this

19 in any kind of coherent manner.

20 So then for outcomes for this

21 particular question, we’re looking at birth weight

22 that could be presented in a continuous fashion or


179

1 in categories, small for gestational age or large

2 for gestational age, or birth weight for length.

3 The population then for exposure would

4 be women either before or during pregnancy, and

5 then the outcome is infants at birth. You’ll see

6 key confounders here: child sex and gestational

7 age, maternal age, race/ethnicity, SES, and a

8 variety of additional confounders listed there.

9 Other factors that are considered are

10 total energy intake -- that definitely becomes

11 important in a good amount of this work -- and then

12 a variety of other variables related to other

13 components of diet, as well as parity, medications,

14 and supplement use.

15 So for the question here related to

16 beverages during pregnancy and birth weight, these

17 are the numbers of studies. We started out with

18 some 7600, and that got pared down through

19 screening of titles, abstracts and then full text,

20 relative to our criteria, and the articles that

21 emerged then for complete review are 19 in number,

22 to be included in our systematic review.


180

1 So this is a table that we’ve shown

2 before, just showing how we’re sort of categorizing

3 beverages so that we, you know, can go through this

4 work systematically. What you see highlighted are

5 the types of beverages for which there was a

6 literature available for us to look at.

7 So milk, low- and no-calorie sweetened

8 beverages, sugar-sweetened beverages, coffee and

9 tea, and plain water are the relevant categories.

10 And we’ll start here with sugar-sweetened

11 beverages and low- or no-calorie sweetened

12 beverages.

13 Now, for this particular segment of the

14 presentation, our subcommittee opted to provide

15 more detail here than we will subsequently, and the

16 reason that we’re doing that is that we wanted to

17 make sure that it was clear to all of you, you know,

18 really what is the way in which we’re proceeding

19 with this work?

20 How are we looking at the data? What does this

21 really look like?

22 So we’re giving a little bit more


181

1 specifics here, just for that purpose, of providing

2 that kind of an example.

3 So starting again here, beverages

4 during pregnancy and birth weight, for these

5 exposures there were seven studies, all of which

6 are prospective cohort studies.

7 And in terms of the exposures across

8 those studies, three of them examined

9 sugar-sweetened beverages independently. Two of

10 the studies examined low- or no-calorie sweetened

11 beverages, independently. And then two of them

12 had a combined category of sugar-sweetened

13 beverages and low- and no-calorie sweetened

14 beverages intake.

15 The outcomes included continuous birth

16 weight and categorical small for gestational age

17 and large for gestational age. So this is an

18 example of three studies -- and one of the various

19 types of summary tables that we look at, where you

20 can see, for each study, the sample size, the

21 country where the study was conducted, the exposure

22 and the comparator.


182

1 For the first study, sugar-sweetened

2 beverage estimated intake in servings per week

3 assessed in the second or third trimester by

4 validated food frequency, representing current

5 intake.

6 And you can see, glancing through here,

7 there is variability across studies in terms of how

8 the exposure was measured, the timing of the

9 measurement as well. And then the outcomes and

10 whether or not the outcome of birth weight was

11 adjusted for gestational age and/or sex or not.

12 I need to take a moment for a glass of

13 water here. Excuse me. Sorry about that.

14 And for these studies, TEI, we’re

15 looking for adjustment for total energy intake.

16 You can see the first couple did not address this

17 at all, but the last adjusted, albeit a step-wise

18 process.

19 And then you see participant

20 characteristics here, just to give you sort of a

21 glimpse at, you know, what’s considered here.

22 I’m not walking through all this detail. Don’t


183

1 worry. That would be not good.

2 But this just shows sort of a -- some --

3 a couple of reminder of comments about this study,

4 and then the actual results for continuous birth

5 weight and the categorical birth weight, with some

6 color-coding to identify where statistically

7 significant findings were available.

8 Does anyone have a cough drop? That

9 was an actual question.

10 FEMALE VOICE: We have one.

11 (Pause.)

12 MEMBER MAYER-DAVIS: All right. Back

13 to pregnancy and birth weight, looking at

14 sugar-sweetened beverages only, those three

15 studies. So here we found mixed findings, so very

16 mixed findings.

17 So in one study, it was found a greater

18 intake of sugar-sweetened beverages was related to

19 higher birth weight. Another study found the

20 opposite, and then the third study, the

21 relationship was not statistically significant.

22 And none of these particular studies


184

1 used the same categorical outcome, so there wasn’t

2 a way to compare across. This is a view of risk

3 of bias. Many of the presentations have mentioned

4 an evaluation of risk of bias, and there is this

5 specific tool that’s used that considers

6 confounding.

7 Confounding is based on the specific

8 key confounders listed in the analytic framework

9 in this case, as I showed at the beginning, and

10 those -- the risk of bias is then classified as low,

11 moderate, serious or critical, and then as well,

12 selection of participants, classification of

13 exposures, deviation from intended exposures,

14 missing data, outcome measurement, selection of

15 the reported result from the paper as a whole, and

16 the most common risk for bias in this particular

17 set, inadequate adjustment for key confounders and

18 inadequate description or definition of the

19 exposures.

20 So then moving towards the literature

21 that focused on low- and no-calorie sweetened

22 beverages or the combination of those, plus


185

1 sugar-sweetened beverage, two studies examined the

2 low- and no-calorie sweetened beverages

3 independently.

4 One of those studies reported greater

5 intake was related to lower birth weight, and

6 another study relationship was found to be not

7 statistically significant, and neither of those

8 studies examined the categorical birth weight

9 outcomes.

10 There were two studies that combined

11 those categories of beverages, sugar-sweetened and

12 low- and no-calorie sweetened beverages, and for

13 those, one study reported a greater combined intake

14 in relation to lower birth weight.

15 Another study reported greater intake

16 related to higher risk of small for gestational

17 age, and then the third study reporting a

18 relationship between combined intake and small for

19 gestational age that was not statistically

20 significant.

21 So our conclusion then for this

22 particular question is here: insufficient


186


2 relationship between consumption of

3 sugar-sweetened beverages or low- and no-calorie

4 sweetened beverages during pregnancy and birth

5 weight outcomes, so the grade is not assignable.

6 Moving then to the question of

7 beverages during pregnancy and birth weight,

8 focusing now on dairy milk, there were six studies

9 that assessed dairy milk intake: one RCT and then

10 five prospective cohort studies. And the exposure

11 was commercially available dairy milk of varying

12 fat and sweetener content.

13 The outcomes here were five studies

14 that assessed continuous birth weight and three

15 studies that assessed categorical birth weight

16 outcomes.

17 In terms of findings, four studies

18 found greater milk intake related to higher birth

19 weight. One study found lower milk intake related

20 to higher birth weight. With the outcome of SGA,

21 one study found greater dairy milk intake related

22 to lower risk of SGA. Another study found the


187

1 relationship to be not statistically significant.

2 A study that looked at large for

3 gestational age did not find a statistically

4 significant association. And then a study that

5 looked at low birth weight, greater milk intake was

6 related to lower risk.

7 The conclusion statement here was that

8 there was insufficient evidence is available to

9 determine the relationship between consumption of

10 dairy milk during pregnancy and birth weight

11 outcomes, with the grade not assignable.

12 And I’ll just fill in here a little bit.

13 And I’m not sure on all the details of those studies

14 reviewed, but the risk of bias was considerable

15 across studies, primarily due to concerns with

16 adjustment for key confounders, particularly total

17 energy intake, and also very little evidence or no

18 evidence, and certainly not consistent evidence

19 with regard to dose response. So that’s a little

20 bit of, you know, some background that led us to

21 this particular conclusion.

22 Turning then to tea, as the beverage of


188

1 interest, there were eight studies that assessed

2 tea intake. All of these were prospective cohort

3 studies.

4 Most of the studies combined tea into

5 a single exposure variable, although some looked

6 at some specific types of tea, oolong, black, green

7 tea, and three of the studies specifically looked

8 at caffeinated tea versus tea that is without

9 caffeine.

10 Six of the studies assessed birth

11 weight in a continuous fashion. Eight studies

12 looked at categories of birth weight outcomes.

13 And in terms of findings, three of the studies

14 reported greater intake of tea related to lower

15 birth weight. Three studies showed a relationship

16 with birth weight that was not statistically

17 significant.

18 In terms of SGA, three studies showed

19 a relationship to be not statistically

20 significant, while two studies showed greater tea

21 intake in relation to higher risk of SGA.

22 In terms of low birth weight as an


189

1 outcome, three studies showed a relationship that

2 was not statistically significant. And for large

3 for gestational age, one study showed highest

4 intake level was related to higher risk for LGA.

5 And so the conclusion here was also


7 the relationship between consumption of tea during

8 pregnancy and birth weight outcomes, grade not

9 assignable.

10 Moving then to coffee. There were

11 seven studies that assessed coffee intake in

12 relation to birth weight, and again, these were all

13 prospective cohort studies. The exposure

14 generally was average coffee intake.

15 Three out of those studies examined

16 caffeinated coffees specifically. Five studies

17 assessed continuous birth weight. Six assessed

18 categorical birth weight outcomes.

19 From three of those studies, greater

20 coffee intake was related to lower birth weight.

21 In two studies, the relationship with birth weight

22 was not significant. For SGA, in two studies,


190

1 greater coffee intake was associated with higher

2 risk, and in two studies, the relationship was not

3 significant.

4 Low birth weight, similarly, two

5 studies, relationship was not significant. One

6 study, greater coffee intake was associated with

7 higher risk.

8 In terms of our conclusion statement,


10 the relationship between consumption of coffee

11 during pregnancy and birth weight outcomes, grade

12 not assignable for coffee.

13 And again, in terms of risk of bias,

14 there were considerable concerns with regard to

15 adjustment for key confounders, particularly

16 energy intake, and also the difficulty of this

17 issue of, you know, coffee versus caffeine. Now,

18 that may or may not be important, so we

19 just -- there was overall, again, insufficient

20 evidence, grade not assignable.

21 Plain water. Again this is intake

22 during pregnancy with respect to the outcome of


191

1 birth weight. So there were two studies that

2 assessed plain water intake, both of which were

3 prospective cohort studies. The studies looked at

4 tap and bottled water, and did not include

5 flavored, carbonated or fortified water by way of

6 how the exposure was specified.

7 Outcomes: again, two studies assessed

8 continuous birth weight and two assessed

9 categorical birth weight outcomes. In terms of

10 findings, for two studies, the relationship with

11 birth weight was not significant, and two studies

12 found the relationship to not be significant for

13 the outcomes, categorical of small for gestational

14 age or low birth weight.

15 So again, the conclusion:


17 the relationship between consumption of plain

18 water during pregnancy and birth weight outcomes,

19 grade not assignable.

20 So I’ve mentioned some of these, but

21 just in summary, across this literature, with

22 regard to beverage consumption during pregnancy


192

1 and birth weight, there were quite a few of these

2 studies where the attrition was greater than 25

3 percent, which provides a risk of bias in terms of

4 selection.

5 Total energy intake was considered in

6 some studies, but in many studies was not

7 considered. Some of the samples had poor

8 generalizability with respect to lower

9 socioeconomic status and minority populations.

10 In terms of concerns regarding

11 exposure, variation in fat or sweetener levels in

12 these different beverages, that information was

13 generally not available. I mentioned a moment ago

14 that about half of the tea and coffee evidence

15 examined only caffeinated versions or the

16 difference wasn’t clear, between the caffeinated

17 and uncaffeinated.

18 There were a lot of issues regarding

19 exposure definitions and assessment methods and

20 timing of the assessment of intake of those

21 beverages during pregnancy.

22 Birth weight -- and I hadn’t mentioned


193

1 this, and should have highlighted this probably a

2 little bit more -- definitely contributed to some

3 of these conclusions. Birth weight was

4 inconsistently adjusted for gestational age and

5 sex, and actually, our original question specified

6 birth weight for gestational age and sex.

7 Many studies adjusted for one but not

8 the other. Some adjusted for neither. Again,

9 inconsistency in the outcomes assessed and

10 definitions used. And for some of the studies

11 where there was a statistically significant

12 result, the effect size, in some cases, was quite

13 small, with the practical and clinical

14 significance of that was unclear.

15 So moving now to alcohol as an exposure.

16 We are working on the question of what is the

17 relationship between alcohol consumption and

18 all-cause mortality? And again, this is via the

19 NESR systematic review process.

20 We do have a new protocol, compared to

21 what we’ve discussed about before that’s posted on

22 DietaryGuidelines.gov. And we’ll talk about it


194

1 here, but it is posted as well.

2 So first, in terms of definition, for

3 this question of all-cause mortality in relation

4 to alcohol consumption, all-cause mortality is

5 defined as the total number of deaths from any and

6 all causes during a specified time period, and this

7 does not include, then, studies of cause-specific

8 mortality; in other words, total number of deaths

9 from a specific cause, CVD, cancer or otherwise.

10 So that’s the outcome all-cause mortality.

11 So this is the analytic framework, and

12 this -- you know, the alcohol field is one that has

13 a number of unique characteristics that we really

14 thought through carefully with regard to

15 establishing our analytic framework, and so I

16 wanted to highlight a number of things here.

17 In terms of our intervention and

18 exposure, the primary exposure is average

19 consumption of alcoholic beverages, as well as the

20 pattern of consumption of alcoholic beverages,

21 meaning, for example, number of drinks per drinking

22 day or drinks per drinking occasion.


195

1 In terms of comparator, the comparator

2 would be different average alcohol consumption or

3 different pattern of alcohol consumption among

4 current drinkers as a primary comparator.

5 A secondary comparator would be intake

6 compared to never drinkers. And you’ll notice

7 that former drinkers are not shown here, because

8 there are a whole variety of reasons that people

9 are former drinkers such that that group as a

10 comparator would not be appropriate. So primary

11 and secondary comparators here are important to

12 note.

13 The population, we’re focusing

14 primarily on adults 21 years and older, which means

15 that if there are studies that, you know, are

16 primarily adults but happen to include some

17 individuals younger than the drinking age, that’s

18 fine, but we’re not looking at studies that would

19 be specifically focused on underage drinking.

20 And then outcome -- you know, all-cause

21 mortality, I already discussed, and so this again,

22 primarily, adults, 21 years and older. Now, in


196

1 terms of key confounders, we’re looking at sex,

2 age, race, ethnicity; some markers of SES we

3 consider to be quite important in this work, as well

4 as consideration of eating pattern or diet quality,

5 physical activity, and smoking. These are our key

6 confounders.

7 In addition, as a key confounder for

8 average consumption exposure, pattern of

9 consumption would be considered important. And

10 then on the flip side of that, for pattern of

11 consumption as the exposure, average consumption

12 would be important to consider.

13 In addition, other factors to be

14 considered: total energy intake, ideally without

15 alcohol; and then age distribution of the study

16 sample, anthropometric measurements,

17 hypertension, blood pressure, diabetes, glucose,

18 lipids, medications, as well as family history of

19 chronic disease, and beverage type.

20 So we started with the standard

21 criteria for study design, publication status,

22 language, country, and health status of


197

1 participants, as we discussed earlier, and a little

2 bit more detail here, again, because of this

3 particular topic of alcohol. I already mentioned

4 the exposure, and so it’s important in terms of

5 inclusion criteria that the exposure is that which

6 we’ve defined.

7 Information on type of beverage will be

8 collected if available, but we don’t exclude a

9 study if that’s not available; it’s just good if

10 we can have it.

11 And again, in terms of exclusion

12 criteria, data on non-drinker groups, where never

13 and former are combined, say, in an observational

14 study, would actually be excluded, just because of

15 the potential problems and bias with combining and

16 including the former drinker group along with the

17 never drinker group.

18 So the never drinker group is a

19 secondary comparator, but a study would be excluded

20 if the study includes former drinkers. And the

21 comparator, I’ve already focused on that, so don’t

22 need to repeat that.


198

1 And again, in terms of exclusion

2 criteria with regard to the comparator, again, the

3 former drinker issue needs to be considered, and

4 that would be excluded if there was a study where

5 the comparison with never and former drinkers was

6 combined.

7 In terms of the dates here, we include

8 studies from January 2000 to now, January 2020, and

9 exclude articles published prior to January 2000,

10 and again, I already mentioned about the age of

11 participants.

12 So we saw from a couple of the earlier

13 examples for this particular subcommittee, the

14 numbers of studies is very high, and so we, you

15 know, have had to really think about prioritizing

16 our remaining work, and what we’re doing is, with

17 regard to added sugars and health outcomes for

18 cardiovascular disease, we are approaching that,

19 building on the 2015 NESR systematic review.

20 In terms of type 2 diabetes, we’ll be

21 building on the 2015 Advisory Committee report, as

22 well as for growth, size, body composition and risk


199

1 of overweight and obesity, and building on the

2 2015.

3 For alcohol and health outcomes, we are

4 prioritizing all-cause mortality as the first

5 outcome to be examined. I just discussed about

6 that work underway, and as time allows, we will move

7 then to address as outcomes CVD, cancer,

8 neurocognitive health, as well as growth, size, and

9 body composition.

10 So that’s where we are. Again,

11 thanking the members of the subcommittee, as well

12 as the support staff, doing wonderful work.

13 Okay. So questions?

14 CHAIR SCHNEEMAN: Thank you.

15 (Applause.)

16 CHAIR SCHNEEMAN: So questions for the

17 subcommittee? Ron?

18 VICE CHAIR KLEINMAN: That was a great

19 presentation. This is a minor comment, and you

20 alluded to it. It has to do with the outcome of

21 birth weight, and I think you mentioned the small

22 effect size and whether these are biologically


200

1 significant so I wonder if it’s worth just noting

2 that when you say higher birth weight studies,

3 either in parentheses or something, within normal

4 reference weight values or something to indicate,

5 these are still normal children.


7 MEMBER MAYER-DAVIS: Correct, and that

8 is the case. So yes, that’s a good comment. So

9 in the report, it will be important to provide that

10 framework. Yeah. Thank you for that. Yeah.

11 MEMBER DEWEY: Kay Dewey. With regard

12 to the dairy milk and birth weight analyses, one

13 of them was, I think, one of the five studies for

14 birth weight showed a positive relationship, and

15 one didn’t.

16 I was wondering what the sample sizes

17 were for all those studies, and I know that you gave

18 the conclusion statement as insufficient evidence.

19 I’m just curious about the choice between limited

20 and insufficient, and knowing in our subcommittee

21 when most of the studies are going in a certain

22 direction, we might have chosen limited. And this


201

1 one seems to be a case where that might be the

2 situation. I know you mentioned some important

3 limitations in -- but one that you mentioned was

4 adjusting for total intake.

5 And I feel that that’s one that is one

6 of those gray areas, because it could be on the

7 causal pathway. So it’s a little bit different

8 than a regular comparator. And so I wondered if

9 you could speak to that and the differing

10 conclusion.

11 MEMBER MAYER-DAVIS: Yeah, yeah. So

12 that -- first of all, it was the case that for those

13 four studies, there were concerns in terms of risk

14 of bias and accounting for key confounders was one

15 of the primary concern.

16 Total energy intake was a concern, and

17 you know, the role of total energy in this kind of

18 situation is always a question. Whether you

19 consider that to be part of a causal pathway or not

20 could be debated probably for hours.

21 So I appreciate that concern. One of

22 the problems with that literature also had to do


202

1 with dose response. So for example, I’m recalling

2 now, although the NESR people will recall better,

3 but I recall now, at least one of the studies where

4 there was a significant effect -- there was no

5 evidence for dose response.

6 So there were quartiles, so any

7 quartile compared to the first, once you got to the

8 second quartile, that was it; flat thereafter.

9 So that’s just an example of one of the several

10 problems across that literature.

11 But I appreciate that, and one of the

12 reasons that I could answer the question with that

13 level of detail in terms of that one study is

14 because I looked at that myself, and again, I said,

15 now, let me make sure I remember why we made that

16 decision.

17 So that was a great comment. And I’m

18 looking over here at Brittany, and I don’t know if

19 you want to add to that. That would be helpful,

20 too.

21 MS. KINGSHIPP: Sure. Brittany

22 Kingshipp. So I was also just glancing at the milk


203

1 literature, the sample size question, and it ranges

2 from the mid 100s up to about 3,000 depending on

3 what cohort they were looking at.

4 And so there were concerns about the

5 things Beth has noted. Also, as was noted, kind

6 across this body of evidence. That body of

7 evidence in particular had multiple studies with

8 very attrition rates, and so that, combined with

9 inconsistency in whether birth weight was adjusted

10 for gestational age and sex or not, half the studies

11 did, half did not.

12 The same was true for total energy

13 intake. So what we did is look at total energy

14 intake kind of beyond the scale of a regular

15 confounder, so that we were interested, if they did

16 adjust for it, that’s answering one question. If

17 they did not, that’s answering another question,

18 both of which we are interested in.

19 And so it wasn’t necessarily that they

20 got penalized if they did not. They just got

21 treated differently in interpreting findings, and

22 so because that was also done inconsistently in


204

1 that body of evidence, all of those inconsistencies

2 kind of snowballed to the point that no clear, even

3 limited, conclusion can be drawn.

4 MEMBER MAYER-DAVIS: Any other

5 questions?

6 (No response.)

7 CHAIR SCHNEEMAN: Okay. Seeing none,

8 I suggest we take a break right now.

9 (A short recess was taken.)

10 CHAIR SCHNEEMAN: So we’re now ready

11 for our last subcommittee report of the day. Is

12 it -- no, it’s working now. So -- and that will

13 be the Data Analysis and Food Pattern Modeling, the

14 Cross-Cutting Working Group.

15 And so Dr. Regan Bailey will be giving

16 that subcommittee report.

17 MEMBER BAILEY: It’s my great pleasure

18 to do so and represent the people on the committee

19 and Jamy Ard, Jamie Stang, Tim Naimi, and Teresa

20 Davis, and supported by Dr. TusaRebecca Pannucci.

21 Wow, I look tired. It’s a very strange

22 thing to see your face that big. So today we will


205

1 be presenting very summary types of statements,

2 draft conclusions of summaries of so much data.

3 So in your Committees, I’m hearing a

4 constant theme of we have insufficient evidence.

5 Subcommittee seven has nothing but evidence. We

6 have so much data. And we can’t -- we will share

7 it all with you in the report, but what I’d like

8 to attempt to do is to show you some of the

9 highlights, the top-level kind of findings today,

10 and where we’re thinking.

11 So you’ll see those. And then the

12 remaining work we have to do is, we have to work

13 within our committee with the B-24, as well as the

14 Pregnancy and Lactation committee, to refine some

15 of those questions as they relate to food and

16 nutrient intakes and nutrients of public health

17 concern.

18 And then the last part, of course, our

19 subcommittee is responsible for the food pattern

20 modeling that will be informed by the evidence that

21 we all have from your committees.

22 So today, we will focus primarily on


206

1 Americans two years and older. So infants and

2 toddlers, the B-24, and pregnant and lactating

3 women aren’t going to be the focus of the data I’m

4 presenting today.

5 So all of the data that we will be

6 talking about, we have as age groups, by sex, by

7 race/ ethnicity, and socioeconomic status, and

8 again, I can’t show you all those, but I’m going

9 to give you some high-level takeaways.

10 And just a reminder of the analytic

11 framework. So we’re using for the dietary

12 intakes, the NHANES What We Eat in America. At

13 this point, the data I’m presenting today are just

14 from foods and beverages, so the nutrient intake

15 data are not inclusive of dietary supplements at

16 this point.

17 We’re presenting data on chronic

18 diseases from these sources, and again, this is all

19 posted online, and we’ve gone over it, but just to

20 have it fresh in your mind.

21 So the first question that we will be

22 presenting evidence on is to describe and evaluate


207

1 current intakes of food groups and nutrients. And

2 so we’ll go through these at a pretty high level.

3 So for fruit, the top contributors to

4 fruit are whole fruit, 100 percent fruit juice, and

5 sweetened beverages. And then in bold, I have the

6 intakes, the mean or average intakes for Americans

7 two and older, so about one cup-equivalent per day

8 of fruit.

9 For vegetables, vegetables are

10 primarily being consumed as part of burgers and

11 sandwiches and mixed dishes. So less than

12 50 percent of the vegetables that are being

13 consumed are discrete vegetables.

14 And if there’s one thing you’re going

15 to hear me say today, again, over and over, is

16 burgers and sandwiches. Okay? So that’s

17 something that really will come through in this

18 data, and that is kind of reflective of the American

19 dietary pattern.

20 Dairy: So most of dairy intake, about

21 one and a half cups per day on average coming from

22 fluid milk and cheese. Fluid milk intake


208

1 decreases with age, and over time, since 2007-08,

2 total dairy intake has decreased in the United

3 States.

4 Whole grains is coming primarily

5 through breakfast cereals and bars. So we have

6 seen increases in whole grain intake across time,

7 but only 2 percent of Americans are currently

8 meeting whole grain recommendations.

9 And then protein foods, primarily

10 coming from animal-based sources. In general,

11 it’s adequate for most Americans, except for

12 females ages 12 to 19 and 70 years and older, with

13 about 5.8 ounce-equivalents per day.

14 The majority of the American population

15 for all groups examined are exceeding recommended

16 energy intake from solid fats and added sugars.

17 The main source of solid fats is burgers and

18 sandwiches, desserts and sweet snacks.

19 And then in children less than 11 years

20 of age, high-fat dairy is also a significant source

21 of solid fat. So the main source of added sugar

22 is sweetened beverages, desserts and sweets and


209

1 snacks, and coffee and tea.

2 And so I use the ampersand to keep food

3 groups together. I don’t generally like the

4 ampersand, but just for clarity. So burgers and

5 sandwiches together, desserts and sweet snacks

6 together, coffee and tea together.


8 that for Americans ages two and older, intakes of

9 fruits, vegetables, dairy and whole grains are

10 generally below recommended amounts and have not

11 changed over time. Intake of total grains and

12 total protein generally meet recommended amounts.

13 Okay.

14 For ages one and older -- because the

15 food group, we’re looking at compliance with

16 previous dietary guidelines. When we’re looking

17 at nutrients, we’re looking at one and older,

18 because the dietary reference intake age groupings

19 are one to three. So sometimes you’ll see

20 two-plus, one-plus, so just for some clarity there.

21 So 9 percent of children and 58 percent

22 of males, 67 percent of females have carbohydrate


210

1 intakes within the AMDR. Across all age groups,

2 protein intake is within the AMDR.

3 Protein also has an EAR, and I mentioned

4 that older adults and teenaged females have intakes

5 that are below the EAR. So the proportion of the

6 population with fat within the AMDR is about 60

7 percent for children and 50 percent for adults, and

8 for all ages, sodium, saturated fats and added

9 sugars are overconsumed.

10 In terms of nutrients that are

11 underconsumed, we have several, including vitamins

12 A, C, D, E, K, calcium, magnesium, fiber, choline,

13 and potassium. In addition to those, other

14 population groups have nutrients or food

15 components that are underconsumed.

16 And so we’re going to focus on these a

17 little bit more when we do the last question,

18 question 5, on nutrients of public health concerns.

19 So keep these in your mind. We’re going to come

20 back to them.

21 And then in young children, retinol,

22 zinc, copper and selenium are overconsumed,


211

1 relative to the upper level.

2 So moving on to dietary patterns and

3 beverage consumption, just a reminder of the

4 analytic framework.

5 At this point, we have the average HEI,

6 total and component scores, but we are awaiting the

7 distribution of those scores. We’ll be looking at

8 that, as well as food category contributions to

9 total energy intake.

10 And so where we’re talking about

11 dietary patterns, just a reminder that we don’t

12 have self-reported patterns of intake. So we’re

13 looking at reported intakes relative to the HEI,

14 not necessarily able to categorize patterns as

15 vegetarian or Mediterranean. Okay?

16 So for children and adults, we will look

17 at beverage intake data in the following ways, and

18 we’ve talked about this, by the population groups,

19 mean intakes, and the percent of energy and

20 nutrients coming from beverages, as well as

21 calories.

22 Just a reminder of the definitions of


212

1 the beverage categories that we’ll be talking about

2 today. We’ve seen these before. Okay. We’ve

3 seen this slide before. Out of 100 points, the

4 American diet is currently at a score of 59.

5 And what’s encouraging is that it has

6 increased slightly over the last decade, from 56

7 to 59. And we do see age differences. So young

8 children, two to five, and adults over the age of

9 65 tend to have higher scores than all other age

10 groups.

11 So this might look complicated, but

12 let’s walk through it. So all of the ways that the

13 100 points are divided are around the edge of this

14 spider web here. So if you start with total fruits

15 and start going clockwise, you get higher points

16 for more compliance, whereas if you went

17 counterclockwise from total fruits, lower intakes

18 are associated with a higher point score.

19 So in an ideal spider web -- I don’t

20 know what these are actually called, but -- and

21 what is called?

22 MALE VOICE: Radar plot.


213

1 MEMBER BAILEY: Radar plot. Okay.

2 In an ideal radar plot, you would have the

3 whole -- if you had a score of 100, it would be all

4 around the outside. So in this slide, we can see

5 some differences among race/ethnic groups.

6 So non-Hispanic Asians have the highest

7 HEI score, and those are represented with the color

8 red on the radar plot. And you’ll see differences

9 and -- within certain food categories. For

10 example, look at greens and beans, how more

11 compliant that race/ethnic group is with the

12 recommendations. Non-Hispanic blacks have the

13 lowest HEI score relative to the other groups.

14 So our draft conclusion one from some

15 of that data is that, while average diet quality

16 has slightly improved, scores are not necessarily

17 consistent with the current recommendations, and

18 we do see differences with sex, age, race,

19 ethnicity and income, but the differences are

20 generally small.

21 This is where the food categories that

22 are contributing to energy. And the -- I’m just


214

1 going to take a second to walk through these,

2 because I know we’ve looked at them before, but just

3 to remind you.

4 So the first bar is for all Americans

5 two and older. All the different colors represent

6 the top 10 food categories. And one thing that is

7 surprisingly consistent is those food categories

8 do not change. What changes is the proportion by

9 age group.

10 So these are food category sources.

11 You can see that for children two to five, there

12 is less proportion from burgers and sandwiches

13 than, say, in adulthood.

14 And we’ll come back and look at some of

15 those when we look at how patterns track across

16 life, but just to give you a sense of food category

17 source of energy for this context right now.

18 So our second draft conclusion is that

19 foods and beverages consumed via mixed dishes, such

20 as sandwiches, casseroles and pizza, sweets and

21 snacks, and beverages, contribute about 50 to 60

22 percent of total energy intake.


215

1 Food subcategory source contributions

2 to energy vary by all of the population

3 demographics that we’ve talked about, but for the

4 total population, about five subcategories make up

5 most of the energy, and that’s burgers and

6 sandwiches, desserts and sweet snacks, rice, pasta

7 and grain-based mixed dishes, sweetened beverages,

8 and chips, crackers and savory snacks.

9 So this is looking at where beverages

10 are contributing to energy intakes. So in

11 general, about 15 percent of energy comes from

12 beverages, and this is specifically among two- to

13 19-year-olds.

14 So beverages contribute about

15 40 percent or more of added sugar in two- to

16 19-year-olds. The percent of added sugar from

17 beverages significantly increases with age, and so

18 when milk is decreasing, it tends to be replaced

19 with sweetened beverages.

20 But all is not lost in the beverage

21 category, for 40 percent of vitamin C and D and more

22 than 20 percent of carbohydrates, calcium,


216

1 potassium, and magnesium are coming from

2 beverages, mainly milk and 100 percent fruit juice.

3 And not surprisingly, more than

4 80 percent of caffeine comes from beverages. This

5 is looking at adults. So this is a pie chart

6 showing, of all the beverages’ calories, what

7 specific foods they are coming from.

8 And the three top sources are sweetened

9 beverages, alcohol, and coffee and tea. And

10 what’s interesting here is there are sex

11 differences. So males have more energy intake in

12 terms of beverage calories from alcohol, whereas

13 women are more likely to have coffee and tea

14 calories, which brings me to conclusion number

15 three.

16 Calories from total beverage account to

17 15 to 18 percent of total energy for Americans.

18 Fluid milk as a beverage decreases, starting in

19 early childhood, and intake of sweetened beverages

20 increases.

21 And beverages account for 40 to

22 50 percent of added sugars in the diet, and


217

1 alcoholic beverages contribute 21 among females

2 and 31 percent among males of total beverage

3 calories.

4 We are probably only about 20 percent

5 of the way through my slides. So I just wanted to

6 give you, like, some context. Just take a deep

7 breath. We’re going to do this.

8 Okay. So this question asks about how

9 patterns track across life stages, and ideally, to

10 answer this type of question we’d have longitudinal

11 data.

12 What we have is cross-sectional data,

13 so we can look at different age groups and try to

14 get some trends and some patterns, but we can’t

15 necessarily say how they track within an individual

16 or within populations or subgroups.

17 So we will use this analytic framework,

18 again looking at food category source, means,

19 beverage contributions, as well as HEI scores,

20 across different life stages for two and above.

21 This radar plot shows you how diet

22 quality and different components of the HEI changes


218

1 by age. So remember, I said the youngest children

2 and older adults have the highest diet quality.

3 When we put the two- and 19-year-olds

4 together, in blue, that kind of changes the story

5 a little bit, but nevertheless, you can see that

6 older adults have a higher HEI score in what foods

7 are represented in the diets of older adults:

8 things like total vegetables, greens, beans,

9 seafood and plant proteins, as well as fruit,

10 refined grains, and lower added sugars, as we

11 talked about before.

12 So once children begin to age, their

13 milk intake goes down, and so do scores in the dairy

14 component. You can see that clearly from this

15 plot.

16 So this is going to be the start of a

17 marathon of slides that look exactly like this, but

18 the title is going to change. And the colors are

19 not always consistent. So if you want me to stop

20 and you want to look at them in a little bit more

21 detail, our safe word in our subcommittee is

22 tangerine.


219

1 So if you want me to stop, just say,

2 tangerine, and I’ll know it’s time to stop. Okay.

3 So this is looking at energy. You’ve already seen

4 this one, so we won’t spend too much time here.

5 But next, looking at vegetables, and

6 how those change with different age groups. So the

7 green is represented by vegetables, including

8 beans and peas that are not starchy. As I

9 mentioned earlier, less than 50 percent of

10 vegetables are consumed as a vegetable alone.

11 Chips, crackers, and savory snacks and

12 pizza are a larger source of vegetables for

13 children than for adults or older adults. And mean

14 vegetable intakes tend to increase with age.

15 Looking at fruit, you can see, as I told

16 you earlier, that primarily coming from, you know,

17 whole fruit, but it does decrease after the age of

18 five, and then pretty much levels off and stays

19 about the same after the age of five.

20 And 100 percent fruit juice decreases after

21 adolescence.

22 This is looking at whole grain intake,


220

1 and we talked about the mean intake earlier, but

2 chips, crackers, and savory snacks as a source of

3 whole grains decreases, and yeast bread and

4 tortillas increases as a source of whole grains

5 among individuals in older age groups.

6 So you can just see some of the

7 patterns. The number-one contributors generally

8 stay the same, but the proportions change with

9 different age groups.

10 So going on to dairy, there is a food

11 category source shift from higher fat among young

12 children to burgers and sandwiches among young and

13 middle-aged adults, and older adults, desserts and

14 sweets and snacks are really a large contributing

15 source to dairy.

16 This is looking at protein foods. So

17 mean total protein is generally within recommended

18 ranges. We talked about those groups that it’s

19 not. For older children and younger adults,

20 burgers and sandwiches is the main category source,

21 and mixed dishes contribute a smaller proportion

22 of protein to the intakes of older adults.


221

1 Looking at added sugars, mean added

2 sugar intake is highest in adolescence and early

3 adulthood. The food category sources here change

4 across the life course. So desserts and sweet

5 snacks are a large contributor for both young

6 children and older adults, whereas in between those

7 age groups, it’s really sweetened beverages, so

8 from six to 50.

9 And for adults, coffee and tea are also

10 a source of added sugar. These are -- coffee and

11 tea are not naturally contained in this, so this

12 inclusive of the additions. I should have made

13 that point earlier.

14 This is looking at calcium. The slide

15 is set up in just the same way. So high-fat milk

16 and yogurt is the largest contributor among young

17 children, and it shifts to burgers and sandwiches

18 for adolescents and adults. And water makes up a

19 large contributor among adults to calcium intakes.

20 This is looking at potassium, so milk

21 and yogurt is a large contributor for young

22 children, and that shifts to --


222

1 VOICE: burgers and sandwiches.

2 MEMBER BAILEY: -- burgers and

3 sandwiches. Thank you. Somebody’s awake. All

4 right. And then coffee and tea and vegetables in

5 adulthood, as a large contributor.

6 This is looking at sodium, and as we

7 mentioned earlier, it’s overconsumed across all

8 life stages, and this is primarily coming from

9 burgers and sandwiches, and that’s pretty

10 consistent across most age groups.

11 This is looking at vitamin D. And

12 remember, I’m only showing you the highlight reel.

13 Okay? So you can imagine how much data we’ve been

14 looking at.

15 So vitamin D is underconsumed across

16 all life stages. Again, children are getting

17 vitamin D, similarly to calcium, from high-fat,

18 low-fat dairy and milk, and in adults, it’s burgers

19 and sandwiches.

20 So this is our draft conclusion

21 statement. There is general consistencies in diet

22 quality seen across life stages. Diet quality is


223

1 better among young children and older adults, but

2 even so, it still does not align with existing

3 guidance.

4 Food category sources of food groups

5 and nutrients differ across life stages. In

6 particular, in the case of milk and yogurt, after

7 early childhood decrease, and intakes of added

8 sugar from beverages increase.

9 Fruit and vegetable intake declines

10 through adolescence and adulthood, and then

11 increases among older adults. Intakes of burgers

12 and sandwiches contribute to most food groups,

13 nutrients and food components which fall outside

14 of recommended ranges.

15 So burgers and sandwiches help

16 contribute to underconsumed nutrients, because

17 they’re so ubiquitously consumed, but they also,

18 at the same time, contribute to those nutrients and

19 food components that we want to limit, such as

20 sodium and saturated fat.

21 Deep breath. Okay. So for the

22 prevalence of nutrition-related chronic


224

1 conditions, we have, as I mentioned earlier,

2 several data sources. What I’m going to do here

3 is a word that I learned yesterday called bookend.

4 So I’m going to tell you the conclusion,

5 and then I’m going to show you the data, and then

6 we’ll revisit the conclusion as a group to get some

7 input, because there is a lot of information I’m

8 going to give to you, and distilling it into a

9 couple of sentences is very complicated. So we’d

10 really love to hear the Committee’s feedback on

11 what you think are the most salient points to

12 include in this section.

13 So we are looking at this with a life

14 stage approach, and the colors are simply there to

15 show you that there are certain things, like body

16 composition, that we will looking at in most age

17 groups, cardiovascular endpoints. So we’ll start

18 with young children.

19 We only have two outcomes in young

20 children. We have body composition. So more U.S.

21 children under the age of 24 months are overweight,

22 about 9 percent, than underweight, based on weight


225

1 for recumbent length.

2 The prevalence of low birth weight and

3 very low birth weight are 8.3 and 1.4 percent

4 respectively. Non-Hispanic black mothers have

5 the highest prevalence of low birth weight babies,

6 and this has increased over time.

7 We have a different age group for

8 allergies. So based on proxy report, the

9 prevalence of food allergy is 6.6 percent. So this

10 is not clinically confirmed data. It’s -- I felt

11 strange using the word self-report, because it was

12 birth to four.

13 And I’m just imagining like a little

14 baby trying to tell you -- anyway. So proxy

15 report. So you know, there’s obvious limitations

16 with that kind of data; it’s not clinically

17 confirmed.

18 So looking at the data that we have

19 available in children in the following categories,

20 the prevalence of overweight is about 17 percent,

21 obesity, 18.5 percent, and underweight, 3 percent.

22 Prevalence of underweight is higher in


226

1 boys than girls and increases with age. However,

2 the prevalence of underweight has decreased over

3 time. The prevalence of obesity is higher in boys

4 than girls. It increases with age, and has

5 increased since 2007 and 2008.

6 Among girls, the race/ethnic group with

7 the highest prevalence of obesity is non-Hispanic

8 black, whereas among boys, highest prevalence is

9 in Hispanic and Mexican-Americans.

10 The prevalence of obesity is lowest

11 among children whose head of household has a

12 college degree or higher.

13 So our draft conclusions for CVD

14 intermediate outcomes: the prevalence of

15 hypertension is 4 percent, and it’s higher in

16 males, non-Hispanic blacks, 18- to 19-year-olds,

17 and those with obesity relative to their peer

18 counterparts.

19 Prevalence of high LDL is 5 percent, and

20 prevalence of low HDL is 15.5 percent. The

21 prevalence of high LDL is higher in non-Hispanic

22 whites, and Hispanic and Mexican-Americans -- you


227

1 can see the percentages there -- when compared with

2 non-Hispanic black and Asian youth.

3 The prevalence of low HDL cholesterol

4 is higher in males, non-Hispanic whites and youths

5 with obesity. So for each chronic health

6 condition we’ve examined in children, the highest

7 prevalence is among those with obesity.

8 We have one cancer outcome, and that is

9 leukemia, and you can see the incidence and

10 mortality rate, both of which are higher among boys

11 than girls, and so this is inclusive of birth to

12 19 years of age, from the SEER data.

13 In terms of diabetes and prediabetes,

14 we have data on 12- to 19-year-olds, and the

15 prevalence of those combined is 23 percent. This

16 is coming from NHANES data.

17 Dental caries: So first, looking at

18 two- to 19-year-olds, the prevalence is about

19 46 percent, and then untreated dental caries is

20 about 13 percent, so this tends to be associated

21 with age.

22 Again, this is cross-sectional data, so


228

1 we can’t say the prevalence of caries increases

2 with age, but the age groups and the prevalence

3 track in the same way.

4 Hispanic youths have the highest

5 prevalence of dental caries, but non-Hispanic

6 blacks have the highest prevalence of untreated

7 dental caries. The prevalence of both caries and

8 untreated caries is lower among families with a

9 higher income. And there has been a slight

10 downward trend over time for the prevalence of

11 total and untreated dental caries.

12 Moving on to adults, the overall

13 prevalence of underweight among adults is 1.5

14 percent. The prevalence of overweight and obesity

15 and severe obesity are highlighted there in

16 parentheses. The prevalence of overweight has

17 decreased, while the prevalence of obesity and

18 severe obesity has increased.

19 And the prevalence of obesity and

20 severe obesity is higher in women than it is in men.

21 Mean body weight, weight circumference, and BMI

22 have increased over time.


229

1 Adults 40 to 59 have the highest

2 prevalence of obesity. Hispanic and

3 Mexican-Americans have the highest prevalence

4 among men, and among women, it’s non-Hispanic black

5 women.

6 Looking at the data, the overall

7 prevalence of dental caries among adults age 20 to

8 64 is 90 percent, and 96 percent among adults ages

9 65 and older.

10 Women have a slightly higher prevalence

11 than men among 20- to 64-year-olds, but the

12 prevalence converges after the age of 65.

13 Non-Hispanic blacks have the highest prevalence of

14 untreated dental caries, and the overall

15 prevalence of complete tooth loss is 2 percent in

16 20 to 64, but increases to 17 percent among those

17 age 65 and older.

18 So looking at cardiovascular,

19 intermediate and outcomes, high cholesterol among

20 adults is 12 percent. Low HDL, 18 percent.

21 Hypertension, 29 percent. Coronary heart

22 disease, 6 percent, and stroke, around 3 percent.


230

1 So when we talk about adults in general,

2 we’re talking about 19 and older, but some of the

3 data come from different surveys, so that is why

4 we have 18 and 19 for some of these age groups here.

5 The prevalence of high cholesterol and

6 low HDL has decreased since 2007-08. Women have

7 a higher prevalence of high cholesterol. Men have

8 a higher prevalence of hypertension, low HDL, CHD

9 and stroke.

10 Adults 40 to 59 have the highest

11 prevalence of total cholesterol and low HDL.

12 However, adults ages 65 and older have the highest

13 prevalence of hypertension, CHD and stroke.

14 So some more key findings here.

15 Non-Hispanic whites have the highest prevalence of

16 high cholesterol among women. However, Hispanics

17 have the highest prevalence of high total

18 cholesterol among men.

19 Hispanics have the highest prevalence

20 of low HDL for both men and women. Non-Hispanic

21 blacks have the highest prevalence of hypertension

22 and stroke. American Indian and Alaska Natives


231

1 have the highest prevalence of coronary heart

2 disease.

3 The prevalence of hypertension,

4 coronary heart disease and stroke are lower among

5 those with higher education levels, and those with

6 a college degree tend to have the lowest prevalence

7 of these cardiovascular outcomes.

8 In terms of diabetes and metabolic

9 syndrome, diabetes is prevalent in about 14 percent

10 of U.S. adults; prediabetes, 34 percent; and

11 metabolic syndrome, almost 35 percent.

12 So men have a higher prevalence of

13 diabetes and prediabetes, but there’s no

14 differences for metabolic syndrome. So the

15 prevalence of diabetes and metabolic syndrome is

16 higher among older age groups.

17 In fact, 52 percent of older adults have

18 metabolic syndrome. The prevalence of diabetes is

19 higher among those with higher BMIs, and Hispanics

20 and Mexican-Americans have the highest prevalence

21 of diabetes and metabolic syndrome.

22 In terms of chronic liver disease, we


232

1 have two different measures. First is

2 self-report, which is about 2 percent, but then

3 looking at ALT and AST, ALT is elevated in about

4 10 percent, and AST in 16 percent of U.S. adults.

5 Hispanics have a higher prevalence of

6 liver disease, high ALT and high AST, when compared

7 with non-Hispanics. American Indian and Alaska

8 Natives have the highest prevalence of liver

9 disease.

10 Men and women have the same prevalence,

11 and mortality rates differ. So men have a higher

12 mortality rate than women. And mortality rates

13 have increased over time, particularly in men.

14 And then men age 55 to 64 have the highest mortality

15 rate from chronic liver disease.

16 So these are a different data source.

17 So this is from the National Vital Statistics

18 System. These are the age-adjusted prevalence

19 rates for chronic liver disease and cirrhosis, and

20 you can see that they have increased since 2006 to

21 2016 in every age group, except for males 45 to 54.

22 And men 55 to 64 have the highest mortality rate


233

1 from chronic liver disease, and the lowest rate is

2 among females 25 to 34.

3 Moving on to cancer, so the cancer with

4 the highest incidence rate among females is breast

5 cancer, followed by male prostate cancer.

6 Age group and cancer type with the

7 highest incidence rate is prostate cancer for men

8 among ages 65 and older. Mortality rate is highest

9 for lung and bronchus cancer, and the age group is

10 the highest mortality rate from that cancer is

11 among older adults, 65 and older.

12 Men have a higher incidence and

13 mortality rates than women across all shared cancer

14 types, and the incidence and mortality rates for

15 every cancer type are highest among individuals 65

16 and older.

17 So we’ll talk last in this section about

18 pregnant women. We’re just going to talk about

19 gestational diabetes today, because the 2018

20 pregnancy-induced hypertension data is just coming

21 into our emails now, so we’ll hold off on that until

22 next time, and just focus on gestational diabetes


234

1 right now.

2 Total prevalence, about 6 percent. It

3 is higher in women who are older than 40. There’s

4 some race/ethnic differences. So non-Hispanic

5 Asians, 11 percent have gestational diabetes.

6 Also very high in American Indian and Alaska

7 Natives and Native Hawaiians and Pacific

8 Islanders.

9 The prevalence remains relatively

10 stable across educational status, but among those

11 with obesity, particularly Class III obesity, the

12 prevalence is 14 percent.

13 So older adults, we have two outcomes

14 here, muscle strength and osteoporosis and bone

15 health. So 19 percent of older adults have reduced

16 muscle strength. This is data coming from NHANES.

17 And there’s really an increase with

18 age. So 48.6 percent of adults over the age of 80

19 have reduced muscle strength. So the age-adjusted

20 prevalence is not different between men and women.

21 It’s about 19 percent, and similarly, women who are

22 older than 80, it’s slightly higher in women than


235

1 men, but not substantially different, so 49 versus

2 47.

3 Non-Hispanic Asians have the highest

4 age-adjusted prevalence rate, followed by

5 Hispanics, and then Non-Hispanic blacks have a

6 prevalence that is about 19 percent, and

7 non-Hispanic whites, about 18 percent.

8 In terms of osteoporosis, it’s

9 estimated that about 11 percent of adults over the

10 age of 50 have osteoporosis, and about 45 percent

11 have low bone mass, and as we know, women are

12 disproportionately affected by both osteoporosis

13 and low bone mass, and that’s amplified here in the

14 last bullet point.

15 So again, given all of the complexity

16 of the data that we showed you, it was very hard

17 to come to a conclusion statement. So this is a

18 work in progress, and we really want it to be

19 informed by you.

20 But we kind of started with this large

21 umbrella, to try to be inclusive of all the things

22 that we found, but we’d like to drill down and have


236

1 some more specific conclusions. Okay.

2 We are on the last question. Evaluate

3 nutrients of public health concern. So we’ve

4 talked a lot about intakes of food groups,

5 short/long nutrients, and this will be our last

6 question.

7 So with nutrients of public health

8 concern, we have tried to use the terminology food

9 component, because there’s things that we’re

10 talking about that aren’t essentially nutrients.

11 So if you are confused, that is why.

12 The question was written for nutrients, but we are

13 trying to use food components. So we developed

14 this flowchart ahead of time. That’s where we

15 looked at the data to make decisions.

16 So sometimes we had dietary data available.

17 Sometimes we have biomarkers. Sometimes we have

18 clinical outcomes.

19 So we had a decision tree in place

20 before we looked at the data to try to be as

21 transparent as possible. And I don’t expect you

22 to read that, because it’s very small. It will be


237

1 in the report.

2 So we first started by casting a wide

3 net. We defined underconsumed or overconsumed

4 when a food component was not within the range of

5 5 percent or higher relative to a dietary reference

6 intake or a quantitative authoritative

7 recommendation, such as a previous dietary

8 guideline recommendation for saturated fat.

9 Similarly, for overconsumed. Then

10 those are elevated to a nutrient or food component

11 of potential public health concern when supporting

12 data through biomarkers, functional indicators,

13 that these low intakes or high intakes are directly

14 related to a health condition.

15 Then we are proposing this category

16 called nutrient or food component that poses

17 special challenges. This is a term that was used

18 by the 2005 Committee to identify food components

19 for which dietary guidelines to meet

20 recommendations was challenging.

21 But we’ve extended this to also include

22 nutrients or food components that pose special


238

1 challenges in identifying at-risk groups. And

2 I’ll show you what I mean on the next couple of

3 slides.

4 So casting our wide net of 5 percent for

5 underconsumed nutrients, there were a number of

6 nutrients that were either in the population or in

7 specific subgroups, noted with an asterisk, that

8 were not well aligned with recommendation, either

9 the EAR or the AI.

10 So when we next evaluated whether there

11 was a biomarker or clinical endpoint that we could

12 tie low intakes to, we were able to eliminate

13 several nutrients, and those that are listed in

14 bold have previously been linked to a health

15 outcome or biomarker, whereas we still have a few

16 that are listed there in red that are special

17 challenges.

18 In terms of overconsumption, we’ve

19 already talked about sodium, saturated fat and

20 added sugars, but compared to the UL, young

21 children are exceeding the UL for retinol, zinc,

22 selenium and copper, and you can see those


239

1 prevalence estimates in the parenthesis there,

2 ranging from about 6 percent for copper to

3 50 percent for zinc and selenium.

4 So then we come to these food components

5 that pose special challenges, and this is where we

6 can also use some of the Committee feedback and

7 guidance. So I mentioned that protein was

8 underconsumed in adolescent and older females.

9 Vitamin B12 might be a concern in older

10 adults, both dietary data and biomarker. Choline

11 intakes are low relative to the AI for most age/sex

12 groups, after young children. Phosphorus intake

13 is low in 9 to 14-year-olds, as well as magnesium.

14 So magnesium is low, relative to the

15 EAR, across most age groups. So our analytic

16 summary so far is that nutrient intakes have not

17 changed considerably since the evaluation.

18 Nutrient intake distributions taken into

19 consideration with biological endpoints and

20 clinical outcomes suggest that vitamin D, calcium,

21 fiber and potassium are underconsumed.

22 Sodium, saturated fat and added sugars


240

1 are overconsumed for all Americans ages one and

2 older. We’re still talking, and that’s why we

3 brought this to you today, in terms of the

4 distinction of what is a nutrient of public health

5 concern for some of those remaining nutrients?

6 In addition to those for all age groups,

7 we’ve looked at this as a life stage kind of

8 approach, and so iron is of particular concern

9 among adolescent and premenopausal females.

10 That’s both dietary and biomarker data.

11 Older adults seem to be at risk for low

12 intakes of protein, and I showed you the data on

13 the muscle strength, as well as vitamin B12.

14 Adolescents, there was -- this is what we’re

15 calling a constellation of dietary risk.

16 So this age group has the highest

17 prevalence of not meeting recommendations across

18 most nutrients, and particularly adolescent girls.

19 So protein, folate, B6, phosphorous, magnesium and

20 choline.

21 And then young children, as I showed you

22 earlier, one to three, have high intakes of


241

1 retinol, zinc, selenium and copper, relative to the

2 UL.

3 So our remaining work I talked about a

4 little bit earlier is what is the role of added

5 sugar in meeting food group recommendations,

6 frequency of eating, looking at beverages, and

7 meeting food group and nutrient recommendations,

8 as well as dietary patterns?

9 We already mentioned that we’re going

10 to be working more with the B to 24 and Pregnancy

11 and Lactation to identify nutrients of public

12 health concern in those populations.

13 And then finally, we’ll end with a few

14 pattern modeling questions. Thank you very much

15 for your time and attention. And I definitely will

16 answer questions, but we also really want to hear

17 from you guys.

18 (Applause.)

19 CHAIR SCHNEEMAN: A long presentation.

20 It was very quick, though. So you’ve heard some

21 questions from the subcommittee, but I think also

22 you have questions or comments for the


242

1 subcommittee.

2 MEMBER DONOVAN: So thanks, Regan. I

3 have two questions, and one is related to the kids

4 in the -- of early ages that are in the upper

5 limits. Do we know what food groups are

6 contributing to the high intakes of the zinc and

7 selenium?

8 MEMBER BAILEY: Yeah. We haven’t

9 really looked at it that way. I could guess at what

10 I think those food sources are, but I think that’s

11 premature.

12 MEMBER DONOVAN: Okay.

13 MEMBER BAILEY: And then, you know,

14 there’s a lot of discussion around are those ULs

15 the right number? So it might be that the diets

16 are okay, and the ULs are often set based on

17 extrapolated data down for children.

18 So that’s why we are calling it, you

19 know -- maybe this is a concern. We certainly

20 didn’t want to make a statement without talking to

21 you all, but we are really unsure about to do, and

22 this is just from food alone.


243

1 So when we will look at supplements for

2 nutrients, those prevalences are going to

3 increase.

4 MEMBER DONOVAN: So my second question

5 was related to some of the -- primarily the

6 cardiovascular outcomes, and is there any

7 factoring in of medications that are used to manage

8 hypertension or cholesterol?

9 MEMBER BAILEY: The way the data are

10 collected is -- so particularly, some of the

11 biomarkers -- no. I mean, we know that a lot of

12 people are on statins. These are the prevalence

13 estimates for a national representative sample of

14 adults.

15 So there are people who taking

16 medications for hypertension. There are people

17 who taking medications for various things, but

18 they’re in the survey.

19 CHAIR SCHNEEMAN: So Kay, and then

20 Richard --

21 MEMBER MATTES: Sure.

22 CHAIR SCHNEEMAN: -- and then -- and


244

1 Steve. So Kay?

2 MEMBER DEWEY: Thank you very much.

3 Kay Dewey. So first, I want to just comment that

4 the UL percent is very, very lightly -- it’s too

5 low, because we see this problem across the board,

6 you know, in many countries, and so that’s just one

7 comment.

8 So I have three questions. The first

9 is when you’re looking at inadequate nutrient

10 intakes, we’ve talked about the fact that people,

11 at least for adults, tend to over -- underreport

12 their energy intake, and so that might make it look

13 like their nutrient intake is too low.

14 And I think you’ve talked about this,

15 but if you’d answer again whether you’re attempting

16 any correction for that, or at least a sensitivity

17 analysis that would let you judge, you know, is it

18 really low, or it’s just they’re underreporting

19 energy?

20 MEMBER BAILEY: Yeah. We know that

21 there is underreporting of energy, but for

22 nutrients, it’s really not well known how


245

1 differential that is. We only have recovery

2 biomarkers for a few food components, and so we

3 really can’t make estimates about what other

4 nutrients are low as a result of energy

5 underreporting.

6 We haven’t really talked about

7 sensitivity analysis. I know there’s been some

8 work done with the survey before, so we might want

9 to look at -- especially the nutrients that we do

10 agree are a public health concern, maybe we could

11 do a sensitivity analysis, trying to exclude energy

12 underreporters, and see what those prevalence

13 estimates would look like.

14 That’s a really good idea.

15 MEMBER DEWEY: Well, you know, I was

16 thinking more along the lines of if we assume that

17 underreporting is not the assumption -- not

18 necessarily a the assumption, but for a sensitivity

19 analysis, if you’re assuming that, you can then

20 apply it as a correction factor across the board,

21 just to see which ones would still emerge as being

22 under the EAR, for example.


246

1 MEMBER BAILEY: Yeah, but people

2 differentially underreport specific food

3 components, like alcohol or sugars, and those

4 aren’t things that really would be good nutrient

5 sources anyway, so I don’t know that we could have

6 a correction factor.

7 MEMBER DEWEY: Okay. Well, anyway,

8 something to think about. The second the question

9 is regarding the birth weight outcome you reported,

10 and just in terms of low birth weights, I

11 remember -- and maybe I don’t remember. But do we

12 have estimates for SGA, LGA, and preterm?

13 MEMBER BAILEY: Yeah. We don’t have

14 preterm right now that I have seen, but we do have

15 all the anthropometrics. We can give you guys all

16 that data, probably be a good conversation to have

17 together.

18 MEMBER DEWEY: Yeah. And one of the

19 issues to take into account is the multiple births

20 and trends in those, because those drive a lot of

21 those numbers. And then lastly, there was a slide

22 where you had a bunch of nutrients, and then you


247

1 crossed them out, and I think it was based on

2 whether there was a biomarker or some other --

3 MEMBER BAILEY: Not whether there was

4 a biomarker --

5 MEMBER DEWEY: Or --

6 MEMBER BAILEY: -- but whether that was

7 linked to low intake. So for example, vitamin E,

8 there is a very prevalence of vitamin E inadequacy

9 if you look at the diet, but when you look at the

10 biomarker, it’s less than 1 percent.

11 MEMBER DEWEY: So when it was crossed

12 out, it meant that --

13 MEMBER BAILEY: That it wasn’t

14 confirmed with a biomarker or a clinical outcome

15 endpoint.

16 MEMBER DEWEY: But what if there is no

17 biomarker? Was it crossed out?

18 MEMBER BAILEY: No, I don’t think so.

19 Like what are you thinking of? We try to be,

20 like -- all the ones that we were -- special case

21 that we wanted to talk about, which if we could pull

22 up that last slide, that might be helpful.


248

1 But for a lot of those, they do have

2 biomarkers or no clinical endpoint. Like we have

3 vitamin C from the blood, we don’t see a lot of

4 scurvy. You know, so that’s why that could be

5 crossed out.

6 CHAIR SCHNEEMAN: So can you go

7 backwards --

8 MEMBER BAILEY: I put it at the end, so

9 I was anticipating this. Okay. Perfect.

10 CHAIR SCHNEEMAN: I think she was

11 looking at the table where you listed everything

12 that was --

13 MEMBER BAILEY: That might take a

14 minute.

15 MEMBER DEWEY: Okay. So here’s the

16 list, and then if you could explain what were the

17 reasons for crossing the ones that are crossed out?

18 I just didn’t -- you went fast.

19 MEMBER BAILEY: Okay. So probably not

20 a nutrient by nutrient, but there was not a

21 biomarker that could confirm low dietary intakes

22 were a problem, and there was not -- it was not


249

1 related to any clinical or health outcome.

2 MEMBER DEWEY: Okay. So in some

3 cases, there is a biomarker, but it didn’t show a

4 problem --

5 MEMBER BAILEY: Right.

6 MEMBER DEWEY: -- but in other cases,

7 there is no biomarker, so we don’t know.

8 MEMBER BAILEY: So what are you

9 thinking there’s no biomarker?

10 MEMBER DEWEY: Well, I’m just -- well,

11 I --

12 MEMBER BAILEY: Can you go back to the

13 flowchart? There we go. Okay. So we would start

14 with -- there are -- for most things, we have

15 dietary data available. So is that available?

16 Yes.

17 Are the prevalence estimates within the

18 threshold, is it more than 5 percent of the

19 population or any population subgroup that might

20 have a problem? Yes. Then is there a biomarker

21 available? Yes.

22 Is there suggested evidence of a risk


250

1 supported by a biological or clinical indicator?

2 No. Like, you know, every path on -- you put the

3 nutrient through -- each nutrient through this

4 kind of pathway to see what was available.

5 MEMBER DEWEY: Okay. So the specific

6 question I have is, the arrow that goes from "Are

7 biomarker data available?" And it says, no.

8 MEMBER BAILEY: Uh-huh.

9 MEMBER DEWEY: And it goes to the left

10 and it says "Lack of evidence to be considered a

11 nutrient or food component of public health

12 concern." Are there any nutrients where there is

13 no biomarker?

14 MEMBER BAILEY: Fiber. And it is a

15 nutrient of public health concern, because it’s

16 linked to a clinical outcome.

17 MEMBER DEWEY: Okay. So there’s

18 only -- yeah. So basically none of them have been

19 excluded on that basis. Okay. Thank you.

20 MEMBER BAILEY: That was a long way

21 around. Sorry. I didn’t get that question.

22 CHAIR SCHNEEMAN: No, but --


251

1 MEMBER BAILEY: But I spent so much

2 time on this, so I just really have to --

3 CHAIR SCHNEEMAN: I know. It’s burned

4 into your mind, so you’ve got to bring us all along.

5 MEMBER BAILEY: And it’s the color.

6 CHAIR SCHNEEMAN: So I can -- did you

7 have anything --

8 MEMBER DEWEY: No.

9 CHAIR SCHNEEMAN: Okay. So Rick?

10 MEMBER MATTES: Rick Mattes. I’m not

11 trying to add anything to your plate, but when you

12 look at beverages, will you be looking at them when

13 consumed alone versus with meals? It’s a question

14 that comes up quite often, and it’s kind of

15 relevant.

16 I mean, beverages serve functions.

17 When they’re consumed with a meal, they help you

18 swallow, and it doesn’t mean that one has to use

19 a sweetened beverage to accomplish that, but

20 weighing costs and benefits and hydration or not,

21 it is a more complicated question of knowing to what

22 degree beverages alone are contributing energy and


252

1 nutrients.

2 MEMBER BAILEY: Yeah. We don’t have

3 that built into the analytic framework right now,

4 but I think that can be something that we

5 incorporate into the report as a research

6 recommendation --

7 MEMBER MATTES: Yeah.

8 MEMBER BAILEY: -- something that

9 could be looked at.

10 CHAIR SCHNEEMAN: Yeah. Is it

11 available?

12 MEMBER BAILEY: Every eating occasion

13 is recorded as a separate eating occasion. So you

14 could do it that way. So if someone just reports

15 a beverage, you could separate that out with the

16 NHANES data.

17 CHAIR SCHNEEMAN: Dr. Heymsfield?

18 MEMBER HEYMSFIELD: How was strength

19 measured?

20 MEMBER BAILEY: With hand grip.

21 MEMBER HEYMSFIELD: Hand grip?

22 MEMBER BAILEY: Yeah.


253

1 MEMBER HEYMSFIELD: Because what

2 caught my eye was the Asians have highest

3 prevalence of low strength, and you use that

4 measure for a sarcopenia diagnosis, and strength

5 is related to body size. I wondered if adjustments

6 were made for body size?

7 MEMBER BAILEY: No. These -- what we

8 presented today are just prevalence estimates. At

9 some point, they were age-adjusted when I specified

10 that for things that -- like cancer, but we haven’t

11 done it like that for the muscle data, but that’s

12 a good idea.

13 So that does bring up the point about

14 protein, and it’s low in older adults. There’s a

15 rather high prevalence of low muscle strength.

16 How do you feel about that in terms of would that

17 rise to the level of something you would consider

18 to be a public health concern?

19 I’m not putting you on the spot --

20 MEMBER HEYMSFIELD: Yeah.

21 MEMBER BAILEY: -- specifically, but I

22 mean, that --


254

1 MEMBER HEYMSFIELD: I’m not sure I know

2 the answer.

3 MEMBER BAILEY: You can just say,

4 tangerine. You know, that’s an option for you.

5 MEMBER HEYMSFIELD: Yeah. Just work

6 with NHANES data a lot and am very interested in

7 sarcopenia, and I think the body size is a very

8 important covariant in that analysis, so I think

9 before you make any conclusions about Asians

10 being -- lacking strength, you need to really

11 adjust for body size in some way.

12 I’m not sure how, but --

13 MEMBER TAVERAS: In the same vein of

14 not wanting to add anything to this long list, but

15 there are two things that I was going to ask about.

16 One was, you talked about obesity in the adults but

17 not in children, and I think there are really good

18 definitions and NHANES, I think, now is reporting

19 on severe obesity in children.

20 So I would ask if that is available and

21 going to be included?

22 MEMBER BAILEY: So Jamy did some


255

1 follow-up on body composition data. Do you recall

2 if those numbers --

3 MEMBER ARD: I am sure they’re probably

4 there, severe obesity for children. So I think

5 that should be included. Yes.

6 MEMBER TAVERAS: And along those same

7 lines with an increase in severe obesity, we’re

8 starting to see nonalcoholic liver disease in

9 children, and it’s not one of the outcomes, so --

10 MEMBER BAILEY: That wasn’t measured.

11 MEMBER TAVERAS: It wasn’t?

12 MEMBER BAILEY: Children -- but we

13 talked a lot of about that. We really know that

14 that’s an issue, and we wish we had more data to

15 address that.

16 MEMBER NAIMI: Yeah. If

17 I -- that’s -- some of the elevated ALTs and ASTs

18 in adults are accounted for by fatty liver, by

19 alcohol as well as by hepatitis C, but there’s no

20 way to tease those apart. And the AST/ALT for kids

21 B-



256

1 MEMBER MAYER-DAVIS: Yeah. So again,

2 speaking of adding things, so you mentioned that

3 HEI was available for the cycle of NHANES data that

4 you are using, but not other indices related to

5 dietary patterns, and not wanting to, you know,

6 steal any thunder from my colleague here to my left,

7 you know, a variety of dietary patterns, you know,

8 are -- you know demonstrate some really

9 interesting findings.

10 So I don’t know how impossible is it to

11 look at other types of indices related to dietary

12 patterns beyond the HEI?

13 MEMBER BAILEY: Yeah. I agree with

14 you. I think that there are a lot of different

15 dietary patterns, but when we really looked at this

16 data, it boiled down to five food groups that were

17 contributing almost half or more energy.

18 So I think what we’re looking at is an

19 American pattern. I think there’s variations in

20 there. But from the 2015 to 2020 extensive work

21 on dietary patterns, they recommended only indexes

22 and scores be applied to characterize dietary


257

1 patterns because, after a cluster analysis, were

2 subject to too many decisions, and couldn’t be

3 reproduced across cohorts.

4 MEMBER MAYER-DAVIS: Right.

5 MEMBER BAILEY: And so --

6 MEMBER MAYER-DAVIS: So I was thinking

7 more specifically about Mediterranean diet, for

8 example, or DASH as another example.

9 MEMBER BAILEY: Well --

10 MEMBER MAYER-DAVIS: And I completely

11 agree with you --

12 MEMBER BAILEY: So the National Cancer

13 Institute has a dietary patterns methods

14 project --

15 MEMBER MAYER-DAVIS: Yes.

16 MEMBER BAILEY: -- and they use all the

17 different scores, and there’s a very high

18 congruency between the HEI and the Mediterranean

19 score and the DASH index. I’m not saying there’s

20 perfect agreement, but they’re pretty robust.

21 MEMBER BOUSHEY: Want me to back you up

22 on that?


258

1 MEMBER BAILEY: Sure do.

2 MEMBER BOUSHEY: Yeah. That’s what I

3 was going to say. I mean -- and the other issue

4 is creating those dietary patterns, you know, for

5 individual food items is actually a little -- it

6 is more challenging, not that it wouldn’t be a

7 wonderful thing to do.

8 It’s just that it would be a large

9 investment of time on your part, and we do know with

10 the adult data from the dietary patterns methods

11 project, but they are -- they all come out very

12 similarly.

13 MEMBER BAILEY: But I really do hear

14 your point, Beth --

15 MEMBER BOUSHEY: Yeah.

16 MEMBER BAILEY: -- and you know, we

17 know what they’re not doing. They’re not doing

18 this, but we don’t know what they are doing, and

19 I think it could be a research recommendation that

20 future committees walk in the door with knowing

21 what the existing patterns are that are different

22 than just HEI. That would be very helpful.


259

1 MEMBER MAYER-DAVIS: Yeah. Because

2 there are established approaches to these scores,

3 some of which are more common in the literature,

4 but some are, you know, fairly obscure.

5 MEMBER BAILEY: Uh-huh.

6 MEMBER MAYER-DAVIS: So -- yeah.

7 MEMBER BOUSHEY: I wanted to give you

8 a shout-out, a team shout-out. Your screener that

9 you developed addressed one of the very comments

10 that have come from the National Academy of

11 Sciences report, so you have a lot to be proud of.

12 That really answered a big question, that you have

13 a method now of looking at these nutrients of

14 concern. So I really have to give you a shout-out.

15 MEMBER BAILEY: We really took that

16 report to heart when we were developing this, but

17 what we realized is that system works nutrient by

18 nutrient, but it failed us when we came across the

19 adolescent females, because we were like this is

20 how we’re going to say something is a food component

21 of concern.

22 And then we were like wait a minute. We


260

1 have this high-risk -- what we consider to be a

2 high-risk group, but -- so nothing is perfect, but

3 we thank you very much.

4 CHAIR SCHNEEMAN: Actually, related to

5 that topic -- and first of all, let me remind the

6 Committee that the subcommittee has also asked for

7 your input on presenting the conclusions around the

8 chronic health conditions.

9 And if you’d recall -- and you can look

10 back at your slides -- but there’s a general

11 statement, and then Regan went through a lot of very

12 specific data. And so part of the question that

13 is being asked is, how do we represent -- well, how

14 do we find a balance in representing that? Do we

15 do just a general statement and then each one

16 separately? Or do we need an overall conclusion

17 statement?

18 And then the other that I think we have

19 gotten some discussion is looking at these

20 nutrients of public health concern.

21 And I’m going to ask you about

22 potassium, because I know that potassium was below


261

1 the AI across the food groups, but we also have the

2 new DRI report which did not give us a chronic

3 disease reference value for potassium.

4 And so maybe just -- some of you in the

5 subcommittee are thinking about potassium as a

6 nutrient of public health concern.

7 MEMBER BAILEY: Yeah. As you know,

8 the DRI was recently updated, and we talked about

9 this. Jamy, if you want to -- can you summarize

10 what we said in our small group meeting yesterday

11 about potassium from -- Jamy was on the committee.

12 MEMBER ARD: Sure. So the issues with

13 potassium, from a clinical standpoint -- yes,

14 there are no issues with people coming into primary

15 care and emergency rooms with rampant hypokalemia.

16 So that’s not an issue.

17 I think the main potential chronic

18 disease risk related to lower potassium intake is

19 related to cardiovascular disease, and in

20 particular, hypertension, and some of the sequelae

21 of that.

22 So you know that there’s a relationship


262

1 between higher potassium intake and lower

2 prevalence of high blood pressure. We know that

3 there are differences in subpopulations in terms

4 of potassium intake and some of those differences

5 maybe explain some disparities in outcomes and

6 health outcomes.

7 So for minority populations,

8 African-Americans in particular, you see higher

9 prevalence of hypertension, lower intake of

10 potassium in that group. And we also know that

11 potassium has a blunting effect in terms of the

12 hypertensive effect of sodium.

13 So in populations where potassium

14 intake is higher, even for a higher sodium intake,

15 you see a less robust response in terms of blood

16 pressure.

17 So I think part of the discussion we had

18 yesterday was there could be an argument made that

19 potassium intake is part of the public health

20 concern group, even though we don’t have some of

21 the, you know, sort of classical direct links; you

22 have more indirect ones, per se.


263

1 But there is a body of evidence that

2 supports the idea that higher potassium intakes may

3 actually have an impact at the population level.

4 So I think that, you know, summarizes the points

5 in the discussion.

6 MEMBER BAZZANO: Lydia Bazzano. So I

7 would second what Jamy just said, Dr. Ard, and also

8 in terms of nutrients of concern, I know Steve can

9 speak -- I know you all did not specifically say

10 protein in older adults, but I think, you know,

11 given the levels that -- the prevalence that we’re

12 seeing, I think they probably should be concerned.

13 MEMBER DEWEY: Kay Dewey. I have

14 another question. I think the list of nutrients

15 where you were examining whether they were of

16 public health concern did not include fats, and is

17 there a reason for that?

18 MEMBER BAILEY: Yes. We hadn’t looked

19 at that data specifically, but you’ve reminded me

20 that we really need to do that. So we looked at

21 saturated fats, but we didn’t look at other fatty

22 acids so we should absolutely do that. Thank you.


264

1 CHAIR SCHNEEMAN: Any comments, any

2 questions?

3 Regan, do you want to put that draft

4 conclusion statement up, and let’s see if

5 there’s -- ah. Great.

6 So I guess the question, though, is are

7 we comfortable with this general statement,

8 knowing that the report itself will go through some

9 of the details that Regan has presented?

10 And again, it’s still a draft,

11 so there’s still some tweaking that probably needs

12 to be done.

13 MEMBER ARD: So the alternative to that

14 statement is something that then calls out some

15 specific chronic diseases that, you know, may be

16 of more interest or more concern.

17 So as an example, we had nominated

18 something like dental caries and metabolic

19 syndrome and diabetes as being really concerning,

20 as well as increasing rates of mortality related

21 to chronic liver disease.

22 So these were things that were, you


265

1 know, somewhat striking for us as we reviewed the

2 data, but they were, you know, our perspective.

3 And so I guess the question is, do we just leave

4 this very general and be very generic and point out,

5 you know, things that we all know?

6 Chronic disease is increasing and the

7 disparities, and you know, it’s worse in some

8 subgroups compared to others, and we could stop

9 there.

10 Or we could, you know, incorporate or

11 call out things that we think are, you know,

12 particularly concerning, either across life stages

13 or related to other things that, you know, would

14 be relevant for some of the questions that other

15 subcommittees are dealing with, or related to

16 things that we think are relevant, you know, with

17 regard to where particular recommendations might

18 go or be needed for emphasis?

19 MEMBER DEWEY: Kay Dewey. So one

20 thought is to at least highlight in some way the

21 outcomes that are being examined in some of the

22 literature reviews that the different


266

1 subcommittees are doing.

2 So the certain cardiovascular disease

3 outcomes are part of several of those, and also

4 growth, size, and body composition, so overweight

5 and obesity. All those come to my mind as

6 deserving to be highlighted, because we are going

7 to talk about whether diet is related to them.

8 MEMBER NOVOTNY: Just in general, I

9 would like us to think about what to do with weight

10 status or overweight/obesity. I see it’s kind of

11 listed as a -- almost like a demographic, and

12 whether it goes along with health condition or

13 whether we have to like call it out as an

14 intermediary, metabolic syndrome was mentioned in

15 your review. It’s closer to the diet than the

16 pathway of many of the conditions. So just to -- I

17 think we should think about where that goes and

18 follow it.

19 MEMBER TAVERAS: I wonder also if you

20 can group them in that way, that some of these are

21 obesity-related and make the summary a little

22 more -- that the cluster is associated with


267

1 obesity?

2 MEMBER DONOVAN: Yeah. I’m sort

3 of -- I’m just struggling on whether this is

4 appropriate or how to say it, but I guess when I

5 was looking at your comments and you were talking

6 about racial/ethnic differences, that to me, it

7 seems like we also need to include socioeconomic

8 status and potential health care coverage, because

9 I don’t think it’s just genetics.

10 Right? And that was kind of led to my

11 respect of the genetic components, but we also

12 disparities in prevention, and I think these

13 differences are because people who have health

14 insurance are getting their medications and

15 they’re getting earlier screening of prediabetes

16 and they’re getting a lot more prevention, and diet

17 intervenes with that, but it’s, you know, a broader

18 issue, and it’s quite beyond the scope of dietary

19 guidelines.

20 But this aspect of, you know -- to give

21 you more work, if we could look at things

22 beyond -- you know, other demographics in terms of


268

1 SES or health care or SNAP utilization

2 or -- because to me, that leads directly to

3 potential application of dietary guidelines in

4 nutrition programs.

5 MEMBER BAILEY: Many of our protocols

6 have food security --

7 MEMBER DONOVAN: Yeah.

8 MEMBER BAILEY: -- included --

9 MEMBER DONOVAN: Right.

10 MEMBER BAILEY: -- to try to get --

11 MEMBER DONOVAN: Right.

12 MEMBER BAILEY: -- a

13 different -- other than just, you know, how much

14 money does your family have? How is that money

15 distributed towards nutrition specifically? So

16 that’s ---

17 MEMBER DONOVAN: That would be great.

18 MEMBER BAILEY: -- yeah.

19 MEMBER MAYER-DAVIS: Just looking at

20 this statement, I very much appreciate Rachel’s

21 comment -- this is Beth Mayer-Davis -- to pull out

22 obesity, and then frame obesity-related


269

1 conditions.

2 I think that’s part of calling out and

3 being more specific. Thinking back to Jamy’s

4 comment, particularly about, you know, some of the

5 areas that, you know, maybe are not above the radar

6 right at this moment, you know, like increasing

7 mortality related to liver disease, like dental

8 caries.

9 So seeing those data, we’re not

10 necessary surprised, but it’s not necessarily what

11 would have been front-of-mind, and so you know, I

12 think that was really a good comment. So I think

13 taking opportunity to be a little bit more specific

14 here, in that regard.

15 And then my second part of this comment

16 has to do with being more explicit about health

17 equity and inequity, because that’s really, you

18 know, what we’re talking about.

19 And I think that’s really important as

20 we think about the Dietary Guidelines with respect

21 to informing federal food policy, which is about

22 food security, access, all those kinds of things.


270

1 So I’d like to, you know, see that aspect of health

2 equity brought out as well.

3 CHAIR SCHNEEMAN: So we’re reaching

4 the end of our allotted time, but one of the things

5 that Dr. Kleinman and I have been talking about is,

6 as one of the chapters, it’s important for us to

7 start integrating the work of all the subcommittees

8 and where do we come to after addressing all of

9 these questions.

10 And so I’d like to just finish the

11 meeting by maybe going around if we had any

12 particular thoughts about that issue, or kind of

13 what Regan was asking the Committee about. It’s

14 an opportunity for you to get some final comments

15 for today, based on what we’ve been hearing.

16 And are you beginning to see some things

17 that sort of emerge to top priority from the work

18 that your subcommittees are doing? So it’s always

19 tough to figure out who goes first. I’m going to

20 pick on Kay.

21 MEMBER DEWEY: Well, I mean, the

22 challenge that we have is integrating across the


271

1 B to 24 age group, because this is the first time

2 that recommendations for this age group are going

3 to be this report, and as you all know, we have

4 multiple outcomes for the same exposure, and so we

5 haven’t yet talked about how to integrate across

6 those.

7 Yeah. Well, one thing I do want to

8 repeat that I said at the last meeting, to make sure

9 everyone is aware, that we are only looking at a

10 subset of all the different types of eating advice

11 that might be given for this age group, and in

12 particular, we’re focusing on the what to feed and

13 not the how to feed.

14 So a general question then is, how far

15 do we go in even talking about the ones where we

16 have not done systematic reviews. And so any

17 advice I throw back to you that the overall

18 Committee would like to give us on how that gets

19 approached would be very helpful.

20 MEMBER DONOVAN: I mean, I’ve just been

21 seeing -- we haven’t really had the opportunity to

22 speak in terms of Regan’s committee on intakes and


272

1 the prevalence of things like gestational diabetes

2 and all of those.

3 So I think that will be important to

4 start to integrate, and you know, and while

5 pregnancy and lactation has been a component of

6 previous Dietary Guidelines, I think pulling out,

7 you know, this sort of special life stage, as we’re

8 taking that life stage approach and thinking not

9 only about improvements for maternal health,

10 because we certainly know that women with

11 gestational diabetes are at higher risk for type

12 2 diabetes later.

13 So again, we haven’t really had a lot

14 of time to think about that, I think, in terms of

15 integrating the data in terms of whether pregnant

16 or lactating women are actually consuming and

17 what are the incidence of these health conditions?

18 But I think what we have seen, you know,

19 from both in B-24 and Pregnancy and Lactation, we

20 have a lot of inability to draw conclusions because

21 the data sets -- the data is just not there.

22 So clearly, as we move forward -- and


273

1 there was a comment earlier about research needs.

2 And we’ll have very long lists of research needs,

3 and so that’s -- again, I think at the end, we’ll

4 be able to make some conclusions, but

5 unfortunately, I don’t think very many of them will

6 be strong, but we’ll have lots of recommendations.

7 MEMBER BAILEY: I really like the life

8 stage approach that we’re taking, and it’s very

9 clear for B to 24 and Pregnancy and Lactation.

10 They have specific working groups. It’s been less

11 clear to me how to handle the other life stages.

12 And so integrating all the information

13 from the different life stages is going to be a

14 little bit more challenging, but I think really,

15 really important.

16 And then the other thing that really

17 stuck out to me in going through all of the data

18 that we did is that foods and nutrients are

19 inextricably linked, when you see that the food

20 changes over time, and we see that mirrored with

21 nutrients. And I feel it’s very important that we

22 meet people where they are in terms of


274

1 recommendations. So people are consuming a lot

2 of --

3 MEMBER DONOVAN: Burgers and

4 sandwiches.

5 (General laughter.)

6 MEMBER BAILEY: So we have to give them

7 tools and strategies to do that in a better way,

8 not just, you know, you need to eat more of this,

9 eat less of that. But giving them real strategies

10 for success, I think, will be something that is

11 important, at least from my perspective.

12 MEMBER NOVOTNY: What I’m thinking

13 about is really integration and just trying how to

14 weave this in a useful way, like a sentence, but

15 I think the problem is this last point about

16 socioeconomic status and the -- I know

17 socioeconomic status has been in our models as a

18 variable to consider, but given the potential use

19 of our findings, I’m wondering whether we should

20 be looking at the different subgroups in order to

21 inform policy, and indeed, whether there should

22 have been other kinds of variables in our models


275

1 that might have helped us, like food security or

2 something about health utilization.

3 I’m not sure also about the

4 race/ethnicity route, whether that’s going to be

5 the most helpful way to go about it, but that’s what

6 I’m thinking about.

7 MEMBER STANG: I would follow up

8 with -- I think we’ve talked about the life span,

9 but also thinking about the life course approach.

10 So the fact -- when we were looking at the data

11 yesterday, we saw these adolescent females with

12 this constellation of poor nutrition, and I’m

13 thinking, these are our future mothers.

14 And so there’s this whole circular

15 piece that what’s important during pregnancy and

16 lactation informs what happens to the children,

17 which then grow up to be mothers themselves or

18 fathers.

19 And so somehow to weave that piece

20 throughout the report that there’s this

21 generational piece that I think often we miss

22 because of the way that data is collected or


276

1 reported, but it has a lot of contextual

2 implications for the recommendations we make.

3 MEMBER TAVERAS: I was thinking, I

4 guess, three things.

5 One, Sharon mentioned, it’s

6 discouraging to see so much insufficient evidence

7 and inability to make conclusions from very little,

8 in some cases, data that is out there and results.

9 And I think that’s going to be really

10 important as we summarize, because I think there

11 is quite a bit of attention on what is going to

12 emerge from here, and I think we’ll have to be

13 careful with how do we frame this in a way that sets

14 up the next Dietary Guidelines or the next

15 Committee on what were some of these research

16 recommendations, and where we might be able to

17 contribute for research purposes for the next

18 round?

19 I’m struck, Reagan, with the

20 conversation we just had about so many of these

21 chronic diseases are obesity-related and the

22 increase in trends and the prevalence of obesity,


277

1 and I think that’s important.

2 I think we have to call it out. Even

3 if all the chronic diseases, cancer, CVD, if they

4 all cluster around obesity, I think that it is going

5 to be important that we really drive that home,

6 because in our subcommittee and in many others,

7 growth size and body composition is something we’re

8 paying close attention to.

9 And then the only other thing that I

10 found interesting is there is a big drop-off -- and

11 maybe because I am a pediatrician and I think a lot

12 about the child diet, but there are some really

13 interesting patterns from two to five to six and

14 older that seems to be this critical point where

15 so many of the other patterns that you showed are

16 deteriorating and decreasing.

17 And I wonder if there’s a way -- as we

18 talk also about life course and life stage, if we

19 can point out some areas of opportunity in either

20 these critical periods or setting staff to work

21 with people and populations in those critical

22 periods, that there might be more room for


278

1 influencing diet in those settings and age groups.

2 MEMBER DONOVAN: I think -- I looked at

3 that too as kind of the child care to school, and

4 there’s different policies in school lunch and in

5 CACP, and so I think that’s a really smart

6 observation.

7 MEMBER MATTES: Yeah. I don’t want to

8 just be redundant, but to amplify the importance

9 of paying attention in our discussion sections

10 about future directions, that this is so

11 disheartening.

12 We spent so much time building these

13 models, to find the greatest science, and we’re all

14 ending up with science that isn’t answering the

15 questions, and so it’s vital that we encourage

16 future researchers to design their trials so that

17 we can get to the bottom of all this.

18 The only other thing that I felt

19 compelled to comment on, but nobody anywhere has

20 talked about food palatability. I mean, there are

21 certainly issues and disparity issues and so on

22 with regard to access and so on, but the primary


279

1 reason that we pick one thing over another is

2 because we like one thing more than another, and

3 so I hope we don’t lose sight of that, and somehow

4 we can leave this in, that we have to pay attention

5 to that component of food.

6 MEMBER BAZZANO: So I like the life

7 course approach and the life stages approach that

8 we’re taking, and I do think, you know, that it’s

9 important to distinguish the different periods

10 because nutrition is different and the needs are

11 different in different periods of time, and

12 specifically I think in the older adults, you know,

13 we need to think about that as well, that so far,

14 we’re kind of all lumped in as adults. So you know

15 I think that might be a particular group with

16 particular outcomes to be focused on.

17 And then the other thing I wanted to

18 mention was also kind of along the lines of what

19 Richard, Dr. Mattes just mentioned, that the data

20 that we have, all of these studies, we’ve been

21 reviewing a lot, a tremendous amount of studies,

22 most of which are not actually designed to study


280

1 what we’re trying to use them to -- the question

2 that we’re trying to use them to answer.

3 So that’s a different issue, but it does

4 get to the importance of research for the specific

5 questions that we want to answer.

6 MEMBER SABATÉ: I agree with many of

7 the things that has been said, and I think on the

8 last presentation, I think it struck me that the

9 way that the menu must be -- almost everything is

10 concentrated in sandwiches and burgers.

11 So it’s culprit of many things, but also

12 an opportunity. And I think that changes in social

13 trends from different perspectives, not only from

14 food, but also from the perspectives of

15 sustainability and taste. I think this is an

16 opportunity to try to improve the health of

17 Americans, but also tackle other social issues that

18 are concern to today’s society.

19 MEMBER LEIDY: I’m not sure if I can add

20 too much to the conversation when we get around to

21 this point, but there’s just a couple of things that

22 have come to mind. You know, I think we’ve all said


281

1 it.

2 It’s surprising right now when you see

3 that there’s just a lot of limited evidence, and

4 the evidence that exists seems to be from cohort

5 studies, when we only say we use randomized trials,

6 and I feel like now that kind of just goes to the

7 wayside, because we know we need them.

8 It’s that next step of how do you make

9 that happen, you know, from a funding standpoint

10 of getting that out. But I still think that’s a

11 vital part of trying to answer some of the questions

12 that we have.

13 So it was more of a surprise. Maybe

14 we’ll all sandbagging writing waiting till the end,

15 until March, when all the data come out. I don’t

16 think that’s the case, but it would be nice if it

17 was. An unrelated issue -- when I look at the food

18 patterns and I think I talked to Regan at lunch a

19 little bit about the different food groups, and I’m

20 struck by the fact that even when we look at whole

21 grains and whether there’s an increase in whole

22 grain consumption, we also see that a lot of whole


282

1 grains that are -- whether they’re recommended or

2 they’re either in schools or what-not, also have

3 an added sugar component to them.

4 And you know, we’ll look at

5 interventions, at least from -- you know, if

6 they’re doing added sugars or whatnot, but I think

7 that’s just a point that I don’t -- we kind of

8 missed that.

9 We look at the food groups and we see

10 where they’re coming from, but I’m not sure if we

11 can then tie that fact into a health outcome to say,

12 you know, whole grains may be beneficial, but as

13 an example.

14 But if they’re, you know, including

15 added sugars, then a lot of those maybe potential

16 health benefits go away, and I don’t know -- we

17 probably may not be the group to do that, but it’s

18 just something that, even looking at the food

19 groups, if we could really separate them out based

20 on some of the other food components that are part

21 of that, and whether that’s dietary patterning, I’m

22 not sure that where that fits. It’s just something


283

1 that I always see when we look at the different food

2 groups, that other components, other nutrients

3 with some of the other healthier food items, and

4 it’s just hard to tease that out.

5 And then just a last point. You know,

6 when we look at the different life stages, and

7 adolescents, particularly females, are, you know,

8 the group of interest from a nutrient standpoint,

9 we also -- I know at least from the literature that

10 there are very few studies in that population.

11 So they kind of go hand in hand. You

12 see the nutrition issues, but they’re not always

13 linked with some of the other health outcomes

14 usually for compliance or attrition with that

15 population. But I think that’s a really big area

16 for future recommendations.

17 MEMBER ARD: So I think we have not

18 gotten to the dietary patterns section yet, but if

19 I would say something that integrates what we’re

20 talking about, I think tomorrow we should hopefully

21 be able to have more discussion about the sort of

22 idea of dietary patterns, when they -- you know,


284

1 sort of concept that we can double-down on, and that

2 was brought forth in the previous Guidelines.

3 And I think it speaks to several things,

4 you know, what Heather just talked about and what

5 Regan talked about, where nutrients are not

6 consumed in isolation, and foods are not consumed

7 in isolation, when I have my burger and sandwich,

8 I’m also going to have my starchy potatoes, and my,

9 you know, sugar-sweetened beverage.

10 Right? You know these things travel

11 together in the American pattern, and we need to

12 acknowledge the idea that across life stages and

13 in the life cycle, these patterns tend to change,

14 and even from, you know, the use of complementary

15 foods, and how, you know, we feed infants -- those

16 things are starting to develop early. And so if we

17 could think about that idea of how we help inform

18 people around those, you know, concepts of foods

19 traveling together.

20 And then I also think, you know, with

21 regards to the idea of calling out obesity, that’s

22 very important, but we haven’t really talked about


285

1 energy intake.

2 And so at some point, we’ve got to deal

3 with that piece of, you know, how we integrate that

4 into all of what we’re talking about, because I

5 think at the end of the day, quality matters, foods

6 matter, nutrients matter. But energy is very

7 important.

8 MEMBER DAVIS: I think it’s very

9 important that our report is looking at life stage,

10 and this will be the first time that we’ve ever

11 looked at it from birth all the way up to the elderly

12 population, and I think our doing it that way,

13 presenting our report by life stage, is more useful

14 for the end user, for the public.

15 And indeed I think we can look at

16 certain things that we’ve seen in dietary intake

17 of the trends over the last few years. For

18 example, there’s been a slight increase in whole

19 grains. Although whole grain intake is fairly

20 low, there’s been a slight increase, and is this

21 because the Dietary Guidelines have reported this,

22 and then I think industry may be reacting to this,


286

1 so they’re putting more whole grains into, for

2 example, breakfast cereals and bars, and so forth.

3 So I think, you know, our report is

4 quite important in informing the public, but also

5 industry that feeds the public.

6 MEMBER HEYMSFIELD: Tomorrow, I’ll

7 give the report from the Frequency of Eating

8 subcommittee, and I think that’s a very important

9 front-end part of our report, is what you going to

10 generate from NHANES data. So I’m really looking

11 forward to what that will be, because from what

12 we’ve found so far, there’s huge gaps in

13 literature, and we spent a lot of time trying to

14 define what we mean by frequency of eating and

15 digestion and so on.

16 So it would be very good for you to work

17 with us so we make sure we have the same definition

18 of frequency of eating.

19 MEMBER SNETSELAAR: I also think that

20 what we’re doing in this Committee in terms of

21 looking at younger age groups is incredibly

22 important, and much of what has come up through this


287

1 Committee is the idea that we want to be consistent.

2 We want to be sure that we’re working

3 together as subcommittees, and particularly, as we

4 focus on these younger age groups, being very

5 careful to ensure that we have conclusion

6 statements and then grading that it is very

7 consistent across committees I think is very

8 important.

9 MEMBER MAYER-DAVIS: This is Beth

10 Mayer-Davis. Just wanted to note that to some

11 extent by design some of the questions that we’ve

12 addressed have had quite small numbers of studies

13 that sort of made it all through.

14 But to some extent, that was by design

15 so that we would get our systems in place, and made

16 sure that we were proceeding, you know, in

17 appropriate fashion.

18 So I can at least tell you that, for

19 Beverages and Added Sugars, some of the questions

20 to come have much larger bodies of evidence, so they

21 will not all be three studies here or four studies

22 there, for better or for worse. Right?


288

1 So you know, again, not wanting again

2 to steal the thunder from Carol’s report on dietary

3 patterns, you know, that subcommittee talked about

4 yesterday, and it is relevant, I think, at this

5 point.

6 Jamy alluded to this a little bit as

7 well. I think by way of integration across

8 subcommittees, having a framework of thinking

9 about dietary patterns and what we’ve been thinking

10 about by way of hierarchy of dietary patterns,

11 foods and nutrients, I think that will help with

12 some cohesion, including how we integrate across

13 subcommittees, you know, so for example, thinking

14 about the Beverages and Added Sugars committee.

15 Thinking about seafood and fats, and how, you know,

16 those elements come into play with the dietary

17 patterns.

18 So I think that will be an important

19 aspect that will help us in terms of integration.

20 MEMBER BOUSHEY: I could say wow

21 everyone said it. But no I have a list, and actually

22 it’s a list that supports things that have really


289

1 been said, and I -- Steven, Beth -- you know, Beth

2 is working on this beverage guidelines.

3 I thought going through and describing

4 all those beverages, that’s like doing minor

5 surgery. We really have an issue with vernacular,

6 and a lot of it is driven by popular words, but I

7 think we do need to concentrate a bit on how we can

8 make sure that what we’re doing now will be

9 repeatable, that we use language that does describe

10 what people are eating and the activities.

11 And part of the challenge of this is

12 think about your beverages. Twenty years ago, we

13 only had like one soda that you could select. You

14 know, so really, we’re facing a new world where we

15 get really new foods, you know, almost every year.

16 And so that’s a burden on our Committee,

17 and we have to somehow think of how to make all that

18 make sense and to be able to bring it all together,

19 because this idea of Kay’s -- you know, really we

20 do need -- Kay said we need to put together all of

21 our work across all of our groups.

22 And I thought that was a great


290

1 suggestion. And, Rick, about your palatability,

2 I think it’s surprising that burgers and sandwiches

3 are so high, and yet we have, you know, this low

4 whole grains. It just doesn’t make sense, does it?

5 So we really have a lot to do to make

6 these guidelines exciting, that people want to

7 follow them, that people see them as

8 something -- hey, I’d like to do that, but -- and

9 I’m not sure that we can do that, but let’s try to

10 think that we can.

11 Thank you.

12 CHAIR SCHNEEMAN: So I’m going to give

13 you the last comment.

14 VICE CHAIR KLEINMAN: So I think that

15 we’ve worked very hard to describe the food

16 patterns or consumption patterns at all of the

17 different life stages that we’ve talked about.

18 But one way to integrate this is to talk

19 about how these patterns change over time, and

20 we’ve also examined health consequences at these

21 various life stages of the foods that are being

22 consumed, and that’s another opportunity for


291

1 integration, if we look at cognition,

2 cardiovascular disease, and hypertension and the

3 various other outcomes, and look to see how these

4 relationships change over time as well.

5 So I think -- I liked what everybody had

6 to say. Jamy mentioned the generational aspect of

7 this, and I think we need to weave that into that

8 conversation about change over time.

9 And then I think it’s really important

10 that we couch all of this as food as one of the

11 social determinants, but there are others, and to

12 the degree that we can link food consumption

13 patterns at least to some sense of economic status,

14 that will help us a lot in completing the story and

15 bringing it together so that we demonstrate where

16 the real opportunity here exists.

17 And I’ll stop there.

18 CHAIR SCHNEEMAN: Well, these comments

19 are very helpful; I have been scribbling notes

20 here.

21 So I think at this point we’re adjourned

22 for today. I’m looking at Eve. Do we need to


292

1 highlight anything?

2 So again, we will reconvene tomorrow

3 morning at nine o’clock. We have several more

4 subcommittee reports to go through, and then we

5 will have the period for public comment, which I’m

6 looking forward to.

7 So I hope you all have a good evening.

8 Thank you.

9 (Whereupon, at 4:28 p.m., the meeting

10 was adjourned, to reconvene at 9:00 a.m., Friday,

11 January 24, 2020.)

12

13

14

15

16

17

18

19

20

21

22



293

Aa.m 1:9 3:2 14:15 28:12

29:7 292:10A1Cs 79:9ability 125:12able 4:13,15 14:1 15:11

31:14 102:20 126:20178:18 211:14 238:12273:4 276:16 283:21289:18

absence 79:2absolutely 78:22 80:8

263:22absorption 55:17abstracts 179:19abuse 93:16academic 100:5 104:1

105:16 138:14 153:21154:14

Academies 7:8 9:8Academy 259:10accept 91:14 122:5acceptable 114:13access 122:9 123:18

124:17 269:22 278:22accomplish 251:19account 96:8 100:14

108:20 216:16,21246:19

accounted 140:17141:19 143:3 147:10255:18

accounting 144:9201:14

accurately 158:17acid 36:8 39:22 40:4,8

40:11,16 41:12,13,1542:6,12,19 54:8,1255:8 57:10,12 72:2076:1 77:19 92:2,4,1792:18 93:21 94:8,2196:5,13,17 97:1,5,1597:21 98:3,9,20,2299:7,11 101:1 102:3102:18,21 103:4,11103:14 104:7,10105:1,10 106:14107:21 108:1,15109:5,18 110:2,5,10110:12,16,17 111:3,9111:13,16,19 129:8129:10 131:3,7,11,12137:1 173:18

acids 57:11 65:18,2175:20,22 77:1,12 78:783:12 112:13 114:20117:12 118:2 263:22

acknowledge 44:10

53:15 71:20 121:2134:5 284:12

Act 92:10activities 289:10activity 93:15 196:5actual 11:17 121:13

128:17 183:4,9add 17:3 30:20 75:1

85:18 104:1 105:17128:21 138:6 152:16152:22 202:19 251:11254:14 280:19

added 2:11 6:18 7:310:8 18:15 29:2 38:377:3 100:11 137:2174:22 175:20 176:14176:19 198:17 208:16208:21 210:8 215:15215:16 216:22 218:10221:1,1,10 223:7238:20 239:22 241:4282:3,6,15 287:19288:14

adding 256:2addition 12:15 22:10

39:3,4 42:9 92:13100:7 121:2 161:7,10196:7,13 210:13240:6

additional 11:6 20:1,2,532:21 55:9 89:1890:14 161:12 179:8

additionally 159:9additions 12:16 82:3

221:12address 6:21 7:5 9:19

10:2 19:17 37:8 90:17114:1 168:12 182:16199:7 255:15

addressed 10:11 31:2037:17 90:1 101:1107:6 134:11 136:2259:9 287:12

addresses 137:8,10addressing 157:2 160:9

175:18 270:8adequate 40:12 56:5,8

57:3,17 208:11adequately 162:22ADHD 100:6 104:1

105:17 138:8ADHD-like 152:17,22adherence 112:8,9adjourn 2:17 132:17adjourned 291:21

292:10adjust 203:16 254:11adjusted 182:11,17

193:4,7,8 203:9adjusting 201:4adjustment 125:14,16

182:15 184:17 187:16190:15

adjustments 253:5Administration 9:13adolescence 46:16

51:13 83:16 135:10135:22 145:11,18146:2 148:18 149:1149:15 150:4,10152:12,18 153:9,17153:22 154:14,19155:14,22 156:9,18157:3 158:19 159:21169:14 219:21 221:2223:10

adolescent 239:8 240:9240:18 259:19 275:11

adolescents 11:1799:22 146:15 148:7148:19 149:3 150:6150:13 152:14 154:15155:15 221:18 240:14283:7

adopted 69:9adopting 120:19adult 11:12 258:10adulthood 49:9 83:16

84:3,5 155:18 156:2214:13 221:3 222:5223:10

adults 11:16 86:6156:20,21 195:14,16195:22 210:4,7211:16 212:8 216:5218:2,6,7 219:13,13220:13,13,19,22221:6,9,18,19 222:18223:1,11 228:12,13229:1,7,8,20 230:1,10230:12 231:10,17232:4 233:11 234:13234:15,18 235:9239:10 240:11 243:14244:11 253:14 254:16255:18 263:10 279:12279:14

advance 79:5advantages 54:22advice 19:2 271:10,17advise 85:13advised 80:3advisory 1:1,7 3:8,18

5:21 6:4,20 10:4,1911:2 12:9,20 13:617:10 23:11 134:7,12

136:10 145:16 156:16198:21

affect 43:15 53:6 55:1465:17 99:1 117:5

African-Americans262:8

afternoon 4:5 28:1329:12

age 23:12 48:7 49:3,1852:4 54:21,21 55:1158:13,18 59:10 61:2,561:15 62:5 63:1764:15,21 69:10 70:1983:18 85:20 93:1696:1 101:22 102:1114:6 120:16,17124:5,22 125:4,14141:18 145:19 147:8148:12 149:17,20150:20 152:2 156:18156:19 157:8 160:15162:8 176:1 177:9179:1,2,7,7 181:16,17182:11 185:17,19187:3 189:3 191:14193:4,6 195:17 196:2196:15 198:10 203:10206:6 208:1,20209:18 210:1 212:7,8212:9 213:18 214:9215:17 217:13 218:1218:12 219:6,14,17219:19 220:5,9 221:7222:10 224:16,21225:7 226:1,4 227:12227:21 228:2,2 229:7229:12,17 230:4231:16 232:14,21233:6,9 234:18,18235:10 239:15 240:6240:16 271:1,2,11278:1 286:21 287:4

age-adjusted 232:18234:19 235:4 253:9

age/sex 239:11agencies 7:18 9:10agenda 14:20,22 18:7

28:8,19 29:6 84:21ages 107:14 142:4

143:9 144:15 146:10152:5 208:12 209:8209:14 210:8 229:8230:12 233:8 240:1242:4

ago 3:20 69:8 192:13289:12

agree 245:10 256:13257:11 280:6


294

agreement 257:20Agricultural 1:8 3:12

26:1Agriculture 5:4ah 264:5ahead 31:10 88:1 122:4

236:14AI 238:9 239:11 261:1alarms 86:18Alaska 230:22 232:7

234:6albeit 182:17alcohol 10:10 175:20

177:1 193:15,17194:4,12 195:2,3196:15 197:3 199:3216:9,12 246:3255:19

alcoholic 194:19,20217:1

align 35:10 223:2aligned 18:18 238:8Alimentarius 33:22all-cause 11:17,19

177:1 193:18 194:3,4194:10 195:20 199:4

allergen 80:5allergenic 58:9allergens 63:12,16allergic 43:2 46:20

52:14 58:3,20 60:361:9,19,21 62:12 63:163:19 84:4

allergies 43:1 52:1458:2,6 60:8 89:1391:21 126:15 225:8

allergy 58:15 59:5,1159:14,14 61:3,18,2062:7,22 63:18 83:13225:9

allotted 270:4allowed 1:9 130:22allows 199:6alluded 199:20 288:6ALT 232:3,3,6altered 69:17alternative 264:13ALTs 255:17amaze 175:6AMDR 114:14,17 210:1

210:2,6America 27:16 206:12American 10:17 43:10

53:1 121:7 207:18208:14 212:4 230:22232:7 234:6 256:19284:11

Americans 5:6 10:16

206:1 207:6 208:7,11209:8 214:4 216:17240:1 280:17

amount 27:21,22 36:439:2,3 42:16 51:565:15 75:6,21 81:20141:22 143:5 144:15149:19 152:8 159:10164:5,16 177:15178:4 179:11 279:21

amounts 54:2,9 55:1855:21 56:4,16,17,2257:16,20 58:7 64:1065:5 67:4,20 68:4,1174:16 140:1 151:6178:14 209:10,12

ampersand 209:2,4amplified 235:13amplify 278:8analyses 140:20 200:12analysis 2:13 10:20

18:17 19:11 24:2025:6 27:8,15 29:2142:2 149:13 151:19170:20 204:13 244:17245:7,11,19 254:8257:1

analytic 20:13,15 136:8145:14 156:13 177:12177:15 184:8 194:11194:15 206:10 211:4217:17 239:15 252:3

analytical 21:1 25:2,235:6 37:7 92:16 99:16112:6 129:7

and/or 23:7 35:4 54:859:13 60:8 65:11,2088:17 92:4 99:11104:6 105:18 110:19112:8 182:11

anemia 39:16,21anemic 107:18animal 22:9animal-based 208:10animals 134:20announce 15:1announced 5:14announcement 86:17

86:21 87:2,10answer 25:9 82:18

125:22 136:7 145:13156:12 164:2 202:12217:10 241:16 244:15254:2 280:2,5 281:11

answered 43:3 52:16259:12

answering 44:4 53:877:21 127:16 164:11

203:16,17 278:14answers 74:10anthropometric 196:16anthropometrics 83:11

246:15anticipate 29:5anticipating 248:9antigens 78:18anxiety 100:6 104:2

106:1 138:14 154:17155:3,14 156:1

anybody 75:1anyway 130:3 225:14

246:5,7apart 255:20apparent 144:3appearance 82:12,14Applause 72:2 127:1

159:15 199:15 241:18applicable 59:15application 268:3applied 151:4 256:22applies 22:16apply 21:11 34:1

136:18 245:20appreciate 17:8 44:2

201:21 202:11 268:20appreciative 26:20approach 136:8 145:15

156:13 170:17 171:1224:14 240:8 272:8273:8 275:9 279:7,7

approached 177:10271:19

approaches 18:1 19:819:10,13,15 20:3259:2

approaching 198:18appropriate 171:4

195:10 267:4 287:17approximately 27:6

29:16 64:15archived 14:3Ard 1:12 172:14,14

204:19 255:3 261:12263:7 264:13 283:17

area 89:12 156:10283:15

areas 7:1 11:22 13:221:13 32:12,16 71:1589:21 132:13 201:6269:5 277:19

aren’t 206:3 236:10246:4

argument 78:12 262:18arrived 14:18arrow 250:6ARS 26:5

article 45:5 151:20articles 21:8 22:1 24:10

27:10,12 36:22 43:1344:17,22 46:7 47:1647:20,22 50:5,10,1353:4 54:10 89:16 94:294:4 100:17,20,20,21103:8 106:22 113:9113:12 139:15 140:9141:12 142:19 143:22146:7,21 147:15,20147:22 148:1,3,8149:7 176:7,7,8,16179:20 198:9

ASD 103:13,16 138:9Asian 227:2Asians 213:6 234:5

235:3 253:2 254:9asked 6:20 7:5 9:19

10:1,22 11:4,11 15:519:17 78:10 86:2094:7 260:6,13

asking 270:13asks 217:8aspect 267:20 270:1

288:19 291:6aspects 64:3 74:12

100:11assess 71:9 130:16assessed 27:11 49:19

89:17 102:1,15,18103:1 113:7 115:18115:21 117:9 118:6118:14 119:16 122:17136:13 139:11,16146:19 147:5,7156:17 157:21 158:1158:3 162:8 182:3186:9,14,15 188:1,10189:11,17,17 191:2,7191:8 193:9

assessment 83:19109:7 125:16 140:5140:20 142:3,5 143:8144:17 146:20 147:9149:20,21 150:19152:6 153:4 161:14192:19,20

assign 169:3assignable 105:19

106:2 111:11 120:3123:3 124:2 138:16141:8 142:16 145:7148:20 151:11 152:14153:12,20 154:16155:16 156:3 158:20186:5 187:11 189:9190:12,20 191:19


295

assigned 88:10 105:6associated 41:12 45:12

46:15 48:5 50:19 51:751:11,20 52:3 57:1763:17 64:15,21 66:7,874:5,6 103:5 104:12105:2 110:17 111:4,5122:13,18 123:12124:10 141:2 142:8148:18 150:4 172:17190:1,6 212:18227:20 266:22

association 40:1048:15 49:15 66:1172:21 73:4 75:1896:12 97:1,15,20,2098:1 103:6,14 110:2,4110:8,10,11 115:20116:2,5 118:9,13,17122:22 123:20 124:21125:9,19 141:15148:13 149:14 151:22154:3,22 155:5 166:4166:5,7 167:3,8169:16 170:1,6 187:4

associations 37:1239:12,16 60:15 77:9140:12 142:22 144:5148:9

assume 245:16assuming 245:19assumption 245:17,18assure 26:16 27:12AST 232:3,4,6AST/ALT 255:20asterisk 238:7asthma 45:12 46:16

58:16 59:22 61:7,1861:21 62:12,22 63:19

ASTs 255:17at-risk 238:1atopic 32:13,17 43:1

44:17,22 45:20 46:246:20 47:2 52:14 58:358:15 59:13,21 60:860:14,18 61:6,15,2162:7,22 63:18 84:489:13 91:22 126:15

attempt 205:8attempting 244:15attendees 17:6attention 79:7 100:5

138:6,7 152:15,16153:9,10 241:15276:11 277:8 278:9279:4

attrition 192:2 203:8283:14

Australia 95:22authoritative 237:6autism 100:6 102:16

105:3 138:8 153:13153:18,19

auto-antibodies 82:16autoimmunity 82:12,15available 14:20 19:19

20:6,20 21:18,18 23:828:8 34:10 39:1041:18 42:5 43:5 46:647:13 68:11 69:1884:4 90:6 99:5 100:3105:9 106:4 111:8113:18 116:9 119:2119:11 121:1 125:11125:21 138:4,12141:5 142:12 143:11143:15 144:21 145:3148:16 150:2 151:8152:10 153:7,16154:12 155:12,20158:10,16 180:6183:7 186:1,11 187:8189:6 190:9 191:16192:13 197:8,9225:19 236:16 249:15249:15,21 250:4,7252:11 254:20 256:3

average 115:1 189:14194:18 195:2 196:8196:11 207:6,21211:5 213:15

avoid 35:20avoiding 8:10awaiting 211:6awake 222:3aware 128:2,18 271:9Azar 5:8

BB 36:12,19 241:10

271:1 273:9B- 173:16 255:21B-12 57:21 88:19B-24 90:21 91:14 120:7

205:13 206:2 272:19B12 36:7 42:2,8,13,18

54:7,14 55:7 106:19108:7 111:10 114:20118:15,19,21 119:10119:13 239:9 240:13

B6 240:19babies 225:5baby 225:14back 27:4 62:15,16 82:2

82:6 87:11 130:20132:7 164:16 174:16

183:12 210:20 214:14249:12 257:21 260:10269:3 271:17

background 4:22187:20

backwards 248:7Bailey 1:13 2:13 127:14

134:5 164:19 166:3174:7 204:15,17213:1 222:2 242:8,13243:9 244:20 246:1246:13 247:3,6,13,18248:8,13,19 249:5,8249:12 250:8,14,20251:1,5 252:2,8,12,20252:22 253:7,21254:3,22 255:10,12256:13 257:5,9,12,16258:1,13,16 259:5,15261:7 263:18 268:5,8268:10,12,18 273:7274:6

balance 260:14balanced 5:11banner 16:13,14bar 214:4Barbara 1:9,11 2:4,15

17:1 30:19 31:14130:19 134:7 165:19

bars 208:5 286:2base 67:7 68:1 84:12based 5:10 8:5 104:15

105:4 106:9 110:14115:22 117:10,17118:7 184:7 224:22225:8 242:16 247:1270:15 282:19

baseline 157:22 168:1basically 77:8 83:11

92:8 94:10 102:2,20106:3,16 115:12120:1 171:20 250:18

basis 60:9 250:19Bates 1:8Bazzano 1:13 263:6,6

279:6beans 115:16 213:10

218:8 219:8bear 139:9before-and-after 107:5

109:12began 29:17beginning 27:18 163:5

184:9 270:16begins 28:12 58:14begun 27:16behalf 31:15 87:18behavior 152:17,22

behavioral 143:21144:18 145:1,5151:13,18 152:1,13

behaviors 8:19 138:9153:11,19

behind-the-work126:21

believe 127:9beneficial 98:5 103:6

141:15 142:22 148:5148:9 151:3 166:4,9173:1 282:12

benefit 56:10 57:5171:2

benefits 251:20 282:16best 132:5Beth 82:6 203:5 258:14

268:21 287:9 289:1,1better 129:2 202:2

223:1 274:7 287:22beverage 64:13 66:5

74:4 177:8 178:5,6,7178:9,10 182:2 185:1187:22 191:22 196:19197:7 211:3,17 212:1215:20 216:12,16,18217:2,19 251:19252:15 284:9 289:2

beverages 2:11 10:1218:15 29:1 34:12,1235:22 39:4 53:20 54:154:9,17,20 55:11,1956:3,11,16,21 57:9,1757:21 58:4,7,11,1963:11 64:9,20 65:367:3,10,15,21 68:3,968:12 70:12 77:13,2181:13 174:22 175:20176:2,4 177:4,20178:12,13,17 179:16180:3,5,8,8,11,12181:3,9,11,13,14183:14,18 184:22185:2,11,12 186:3,4,7192:12,21 194:19,20206:14 207:5 208:22211:20 214:19,21215:7,9,12,14,17,19216:2,4,6,9,19,21217:1 221:7 223:8241:6 251:12,16,22287:19 288:14 289:4289:12

beyond 203:14 256:12267:18,22

bias 27:11 37:13 40:1871:9 89:17 98:16104:19 105:7 118:3


296

144:6,8 154:9 165:9184:3,4,10,16 187:14190:13 192:3 197:15201:14

Bier 3:14 17:13big 204:22 259:12

277:10 283:15bigger 9:16biggest 85:12bill 12:6 73:13bioactive 113:6,6

119:21biological 31:7 78:13

83:11 239:19 250:1biologically 199:22biomarker 238:11,15

239:10 240:10 247:2247:4,10,14,17248:21 249:3,7,9,20250:7,13

biomarkers 136:21236:17 237:12 243:11245:2 248:2

birth 2:6 12:1 18:1422:22 28:22 31:1236:8,14 38:15 41:2044:6 47:2 53:11 55:1369:10 91:1 99:20103:2 120:16,17121:11 124:5,11,11124:14,22 125:1,3,10125:14,20 136:14162:7 175:22 177:4,8178:21 179:2,5,16181:4,15 182:10183:4,5,13,19 185:5,8185:14 186:4,7,14,15186:18,20 187:5,10188:10,12,15,16,22189:8,12,17,18,20,21190:4,11 191:1,8,9,11191:14,18 192:1,22193:3,6 199:21 200:2200:12,14 203:9225:2,3,5,12 227:11246:9,10 285:11

births 246:19bit 4:22 79:1,7 165:12

166:21 173:9 180:22187:12,20 193:2197:2 201:7 210:17218:5,20 241:4269:13 273:14 276:11281:19 288:6 289:7

black 188:6 225:4 226:8227:2 229:4

blacks 213:12 226:16228:6 229:13 230:21

235:5blood 48:6,9,17 49:2,8

49:16 93:6 95:2106:18,20 108:6,22110:8,19 111:4,14157:17,18 158:1,2196:17 248:3 262:2262:15

blue 137:19 218:4blunting 262:11BMI 66:12 81:21 94:17

97:18 98:8 228:21BMIs 231:19board 244:5 245:20bodies 287:20body 11:3 32:18 33:1,6

37:14 38:13 40:1248:22 52:12 60:2161:12 64:6,16,16 65:465:11,22 66:9,15,2066:22 67:11 68:2069:1,15 70:1 71:1274:6 81:15 84:2 176:4176:20 198:22 199:9203:6,6 204:1 224:15224:20 228:21 253:5253:6 254:7,11 255:1263:1 266:4 277:7

boiled 256:16bold 207:5 238:14bone 11:15 32:19 33:6

52:15 68:1,9,12 70:371:7 84:8 234:14235:11,13

bookend 224:3born 22:22Boston 165:2bottled 191:4bottom 39:7 93:10

138:11 278:17Boushey 1:14 129:6,7

257:21 258:2,15259:7 288:20

boys 226:1,3,8 227:10brain 11:9 77:16 160:7bread 123:16 220:3break 31:8 86:6,16

132:6,10 204:8breakfast 208:5 286:2breaks 28:15,17 31:6breast 33:17 55:15 77:1

117:3 233:4breastfed 55:2 56:8

57:3 69:11breastfeeding 33:16

48:20 74:11 77:278:11 85:16 100:12112:17

breath 217:7 223:21brief 20:8 31:8 175:17briefly 89:21 92:15

121:16 137:22bring 251:4 253:13

289:18bringing 161:16 291:15brings 216:14Brittany 202:18,21broader 10:13 11:19

13:3 267:17broadly 178:10bronchus 233:9brought 25:12 87:22

240:3 270:2 284:2build 10:2building 86:18 198:19

198:21 199:1 278:12built 252:3bullet 49:6 235:14bunch 246:22burden 289:16burger 284:7burgers 207:10,16

208:17 209:4 214:12215:5 220:12,20221:17 222:1,2,9,18223:11,15 274:3280:10 290:2

burned 251:3busy 26:17 31:21

CC 36:7 210:12 215:21

248:3 255:19CACP 278:5caffeinated 188:8

189:16 192:15,16caffeine 188:9 190:17

216:4calcium 210:12 215:22

221:14,19 222:17239:20

call 2:2 48:18 88:5265:11 266:13 277:2

called 212:20,21 224:3237:16

calling 240:15 242:18269:2 284:21

calls 88:5 264:14calories 211:21 216:6

216:12,14,16 217:3can’t 28:15 127:20

130:12 205:6 206:8217:14 228:1 245:3

Canada 95:22 107:12108:11 114:6,22147:3

cancer 11:4 134:18194:9 199:7 227:8233:3,3,5,5,6,7,9,10233:13,15 253:10257:12 277:3

capture 36:20 43:852:20

carbohydrate 114:11114:12,15 209:22

carbohydrates 215:22carbonated 191:5cardiovascular 11:3

47:15,21 136:1 156:9157:4 158:19 159:7176:15 198:18 224:17229:18 231:7 243:6261:19 266:2 291:2

care 80:4 122:9 123:18124:18 261:15 267:8268:1 278:3

cared 144:6careful 80:5 276:13

287:5carefully 34:19 43:16

160:11 163:6 194:14caregivers 35:11,13

36:1caries 227:17,19 228:1

228:5,7,7,8,11 229:7229:14 264:18 269:8

Carol 1:14 129:6Carol’s 288:2carved 165:18case 37:14 45:15 50:4

59:6 64:1 85:22 93:193:3 97:7 99:18101:22 102:14,17125:21 167:1 169:22184:9 200:8 201:1,12223:6 247:20 281:16

case-control 100:22102:13 103:13 105:5

cases 20:18 74:19 77:477:5 85:21 170:3193:12 249:3,6 276:8

casseroles 214:20casting 237:2 238:4categorical 181:16

183:5 184:1 185:8186:15 189:18 191:9191:13

categories 88:12140:19 179:1 180:9185:11 188:12 212:1213:9,21 214:6,7225:19

categorization 140:2142:2


297

categorize 211:14categorizing 180:2category 181:12 211:8

214:10,16 215:21217:18 220:11,20221:3 223:4 237:15

Caucasian 95:8 107:15122:9 123:18 124:17

caught 91:10 253:2causal 201:7,19causation 67:13cause 194:9cause-specific 194:7causes 194:6caveat 80:20CDC 69:9cell 106:20,20 108:6,22

110:9,19 111:14Center 1:8 3:5,13 7:14Central 14:16,20 28:13

28:14cereal 56:5 65:8,16cereals 54:11 57:1 62:2

62:19 208:5 286:2certain 123:11 124:9

172:16 200:21 213:9224:15 266:2 285:16

certainly 17:3 161:5163:22 164:4 165:17166:15 168:21 187:18242:19 272:10 278:21

cetera 78:1 172:18Chair 1:9,11,12 2:4,15

2:16 16:22 17:2 30:1430:18 72:3 78:2179:13 80:7,17 81:1184:15,17 86:5 87:1287:21 127:2 130:18131:13,17,19 132:15132:16 133:1 134:7159:16 162:15 163:15164:8 165:14 174:5174:11,14,18 199:14199:16,18 204:7,10241:19 243:19,22248:6,10 250:22251:3,6,9 252:10,17260:4 264:1 270:3290:12,14 291:18

challenge 81:8 270:22289:11

challenges 237:17238:1,17 239:5

challenging 237:20258:6 273:14

change 4:10 151:18214:8 218:18 219:6220:8 221:3 284:13

290:19 291:4,8changed 209:11 239:17changes 160:5 166:1

214:8 217:22 218:4273:20 280:12

chapters 270:6characteristics 94:14

101:4 109:15 182:20194:13

characterize 256:22charge 6:3,5,7 18:5chart 23:21 36:9,12

216:5CHD 230:8,13cheese 62:6 157:11

207:22child 34:15 66:12 67:13

76:2 100:11 104:13105:3,16,17 126:6,15135:9 138:9 139:14141:3,8 142:10,15143:2,14,18 145:2,6148:10,13 149:18152:7 179:6 277:12278:3

childhood 45:12,2146:16,21 48:10,1749:8,17 51:12,1358:16,21 66:8 83:16100:3 135:10,22137:10 145:10,18146:2 147:1 148:17149:1,15 150:3,10151:10 152:12,18153:9,17,22 154:18155:14,22 156:8,18157:3 158:18 159:21168:19 169:1,9,14216:19 223:7

children 11:16 69:1274:13 99:21 101:5,11101:11 102:1,15103:16 136:14 140:14140:16 141:17 142:4143:9 144:15 146:10147:7 148:6,11,19149:3,17,20 150:6,12150:20 151:11 152:2152:5,13 155:15156:20 157:8,9 200:5208:19 209:21 210:7210:21 211:16 212:8214:11 218:1,12219:13 220:12,19221:6,17,22 222:16223:1 224:18,20,21225:19 226:11 227:6238:21 239:12 240:21

242:17 254:17,19255:4,9,12 275:16

Children’s 1:8 3:13China 95:6,8 115:2,3,12

147:3chips 215:8 219:11

220:2choice 200:19cholesterol 227:3

229:19 230:5,7,11,16230:18 243:8

choline 113:3 210:12239:10 240:20

chosen 200:22chronic 22:15 93:3

112:15,18 196:19206:17 223:22 227:5231:22 232:15,19233:1 260:8 261:2,17264:15,21 265:6276:21 277:3

circular 275:14circumference 228:21circumferences 64:17cirrhosis 232:19clamping 55:13clarification 72:17 75:5clarify 170:8clarity 178:17 209:4,20Class 234:11classical 262:21classification 184:12classified 184:10clear 33:16 72:17 73:13

74:7 159:19 180:17192:16 204:2 273:9273:11

clearly 23:14 218:14272:22

click 16:15,17clicker 175:9clicking 175:8clinical 43:10 53:1

121:8 127:15 193:13236:18 238:11 239:20247:14 248:2 249:1250:1,16 261:13

clinically 225:10,16clinicians 80:1clockwise 212:15close 38:15 277:8closely 161:21closer 266:15cluster 257:1 266:22

277:4CNPP 7:21CNRC 17:11Codex 33:21 34:7

coffee 180:8 189:10,11189:14,20 190:1,6,10190:12,17 192:14209:1,6 216:9,13221:9,10 222:4

coffees 189:16cognition 171:15 172:1

172:2,10,13 173:3291:1

cognitive 103:17105:12 140:8,13,20141:3,7 147:20148:11,14,19 149:2156:1 159:21

coherent 178:19cohesion 288:12cohort 49:5 63:22 95:20

97:14 100:21 101:20103:9 104:15,21107:4 109:2,4 125:6139:16 146:5,22147:10 148:2 149:9149:13 151:21 154:1154:19,21 157:20160:12,18 163:13167:21 181:6 186:10188:2 189:13 191:3203:3 281:4

cohorts 94:6 98:12107:4 108:10 113:19121:21 123:7 124:6125:5 140:9 141:13142:20 144:1 148:9257:3

collaborative 44:8,1253:12 121:4

colleague 256:6collected 112:21,21

113:8 123:7 197:8243:10 275:22

collection 129:3college 226:12 231:6color 213:7 251:5color-coding 183:6colors 214:5 218:18

224:14colostrum 113:1combination 92:19,22

93:18,20 184:22combinations 112:5combined 121:10

181:12 185:10,13,18188:4 197:13 198:6203:8 227:15

combining 197:15come 15:9 161:21

207:17 210:19 214:14230:3 235:17 239:4


298

258:11 259:10 266:5270:8 280:22 281:15286:22 287:20 288:16

comes 49:18 82:18215:11 216:4 251:14

comfortable 81:19264:7

coming 88:2 161:3176:18 207:21 208:4208:10 211:20 216:1216:7 219:16 222:8227:16 233:20 234:16261:14 282:10

comment 8:1 14:1230:5 44:2 72:9 113:21127:22 128:21 169:11174:9 199:19 200:8202:17 244:3,7268:21 269:4,12,15273:1 278:19 290:13292:5

commenting 29:18comments 7:19 8:3

14:9,11 29:11,13,1729:21 30:1,6,9,11,1634:18,20,21 43:1253:3 129:4 131:14132:9 159:17 168:14174:5,15 183:3 200:6241:22 255:22 259:9264:1 267:5 270:14291:18

commercially 33:2034:10 186:11

committee 1:1,7 2:143:8,10,18 5:1,7,14,165:22 6:2,4,20 7:1,3,37:5 9:19 10:2,7,9,2211:5,10,21 12:20 13:913:17,21 14:9 15:2,816:8 17:1,3,5,10,1118:4 19:3,4,8,1724:15,17 25:4,13,1525:18,21 26:3,20 27:228:1,7 29:5,10,15,2130:2,9,11 43:16 44:353:8 72:8,10 87:1190:12 118:5 127:3132:9 133:3,13,19134:5,12 136:10145:16 156:16 159:17161:8,21 162:1,2,3175:4,19 198:21204:18 205:13,14237:18 239:6 260:6261:11 270:13 271:18271:22 276:15 286:20287:1 288:14 289:16

Committee’s 13:7,1515:5,12,16 16:18 24:924:11 25:17 224:10

committees 10:4,6,1110:15,19 11:2,19 12:912:20 13:7,16 23:11205:3,21 258:20287:7

common 58:8 108:6184:16 259:3

commonly 63:15communication 141:11

142:9,14 149:7,12,16150:5,12 173:4

comparable 22:5comparator 178:1,3,8

178:18 181:22 195:1195:1,4,5,10 197:19197:21 198:2 201:8

comparators 20:1792:20 136:16 195:11

compare 37:22 40:22184:2

compared 37:17 38:1839:14 40:7,11 41:1141:16,19 54:21 64:1496:4,16 97:4 98:9,21109:4 115:10 118:16146:12,17 148:5149:11 150:21 151:18152:21 178:12 193:20195:6 202:7 227:1232:6 238:20 265:8

comparison 36:3 45:1150:6 198:5

comparisons 35:1037:19 39:12

compelled 278:19compelling 48:19 85:14competence 102:12complementary 32:16

34:11 35:22 39:452:10 53:11,17,2054:1,9,17,20 55:11,1955:21 56:2,11,16,2157:6,9,16,20 58:4,758:11,14,19 59:1,2160:17 61:11 62:1163:10 64:9,13,20 65:365:6,9,20 66:6,14,1967:2,9,20 68:3,9,1270:12 74:4 75:1777:12,20 83:5 284:14

complete 30:6,19 53:1372:4 120:22 179:21229:15

completed 26:10 43:744:5 52:20 53:10

158:21 175:21completely 21:18

257:10completing 291:14complexity 235:15compliance 127:12,15

128:4,14,15,18209:15 212:16 283:14

compliant 213:11complicated 78:4

212:11 224:9 251:21complicates 38:10component 37:7 59:6

135:19 211:6 218:14236:9 237:4,10,16250:11 259:20 272:5279:5 282:3

components 38:2178:15 116:20 122:17135:18 179:13 210:15217:22 223:13,19236:13 237:18,22239:4 245:2 246:3267:11 282:20 283:2

composite 140:15composition 32:18

33:2,6 38:2,7 40:1640:21 41:15 52:1264:7,16 65:4,11,2166:1,9,15,20 68:2169:2,15 70:1 71:1274:6 75:16 77:1 78:581:15 84:2 88:2289:10 90:4,21 112:1112:14,20 113:17114:3 115:10 117:5119:10 176:5,20198:22 199:9 224:16224:20 255:1 266:4277:7

comprise 53:16comprised 44:11concentrate 289:7concentrated 280:10concentrations 117:22

118:1 119:13concept 13:2 22:16

284:1conception 88:17 102:6concepts 284:18concern 144:5 154:8

170:11,12 201:15,16201:21 205:17 236:3236:8 237:11 239:9240:5,8 241:12242:19 245:10 250:12250:15 253:18 259:14259:21 260:20 261:6

262:20 263:8,16264:16 280:18

concerned 263:12concerning 264:19

265:12concerns 98:16 103:20

104:18 105:7 110:21116:16 117:6 118:3,5161:9 187:15 190:14192:10 201:13 203:4210:18

concluded 45:7 50:1560:12,22 123:9

concludes 30:8 138:17156:4

concluding 131:18,19conclusion 24:3 25:3,7

25:8,9,20 26:9 32:3,541:8 43:17 45:17 46:848:2 63:13 66:13,1767:19 68:6,13 76:377:6 81:6 84:18 88:798:2,10 99:3,6 103:20104:9 110:15 116:7118:22 120:1 123:22125:8,9 126:10134:14 135:19 137:17137:20 138:1,20139:7 140:21,22142:6 143:10 144:20148:15 150:1 151:7152:9 153:6,15 154:7154:11 155:11,19158:15 160:21 161:19165:18 170:9 171:21172:1 185:21 187:7187:21 189:5 190:8191:15 200:18 201:10204:3 209:7 213:14214:18 216:14 222:20224:4,6 235:17260:16 264:4 287:5

conclusions 23:21 27:535:2 42:21 43:15 44:152:9 53:6 55:20 67:868:7 71:9 91:12 95:13103:18 104:14 106:9121:5 125:12 130:16133:11,18 161:20,22175:22 193:3 205:2226:13 236:1 254:9260:7 272:20 273:4276:7

condition 227:6 237:14266:12

conditions 157:16224:1 260:8 266:16269:1 272:17


299

conduct 5:2conducted 10:19 44:12

44:15 53:17 94:15,1995:6 101:6 107:12,17108:11 109:4,12,13114:6,22 120:8123:17 124:16 139:18146:15 147:17 151:15181:21

confirm 248:21confirmed 128:11

225:10,17 247:14confounder 196:7

203:15confounders 20:22

93:11 100:10 140:18141:20 143:3 144:9147:11 163:1,3,7,7165:8 179:6,8 184:8184:17 187:16 190:15196:1,6 201:14

confounding 40:18125:17 165:9 184:6,7

confused 135:14236:11

confusing 79:1congruency 257:18connect 28:11consequence 163:19consequences 290:20consider 7:2 11:1,11

93:13 129:20 166:17173:12,14 178:8196:3,12 201:19253:17 260:1 274:18

considerable 187:14190:14

considerably 239:17consideration 6:15

7:19 20:2 130:10133:13 169:5 196:4239:19

considered 5:3 11:1912:13 25:14 55:1063:11,16 100:13163:3 174:3 179:9182:21 192:5,7 196:9196:14 198:3 250:10

considers 184:5consisted 146:12consistencies 222:21consistency 104:18

105:6 116:17 161:13166:11 167:19 174:19

consistent 37:13 39:1139:15 51:9 98:14110:21 116:15 123:10124:8 158:11 167:5

167:15 187:18 213:17214:7 218:19 222:10287:1,7

consistently 21:12constant 205:4constellation 240:15

275:12consumed 55:19 67:21

88:14 92:4 94:9 99:12101:2 103:11 104:7105:11 106:5,8 107:7111:22 116:10 146:16178:5 207:10,13214:19 219:10 223:17251:13,17 284:6,6290:22

consuming 37:18,2138:19 39:15 40:8 41:941:11,19,22 56:2,1256:20 57:6,8 60:362:11 272:16 274:1

consumption 35:4,1535:18 38:20 39:2040:2 42:10 43:1 59:1960:17 62:2,18 63:665:19 66:6 69:1471:12 74:4 106:14112:8,9,11 114:16136:4,20 137:7,12139:1 145:10 146:2153:8 154:4,13155:13 156:8 158:18162:10,18 163:16172:10 177:8 178:6186:2 187:9 189:7190:10 191:17,22193:17 194:4,19,20195:2,3 196:8,9,11,11211:3 281:22 290:16291:12

consumptions 116:12contain 56:3,21contained 221:11containing 56:17 154:4content 27:19 117:1

186:12CONTENTS 2:1context 85:9 214:17

217:6contextual 276:1continue 70:21 93:13

172:15continued 95:1continues 175:6Continuing 42:3 49:13

57:13continuous 81:15,21

178:22 181:15 183:4

186:14 188:11 189:17191:8

contrast 96:21contribute 214:21

215:14 217:1 220:21223:12,16,18 276:17

contributed 193:2contributing 45:16

213:22 215:10 220:14242:6 251:22 256:17

contributions 211:8215:1 217:19

contributor 221:5,16,19221:21 222:5

contributors 207:3220:7

control 64:1 96:17,19109:20 131:6 157:15

controlled 60:19 61:1294:5 95:5 96:22 98:11125:7 130:9 146:5,8,9147:22 148:4 150:17150:18 151:15 152:19157:7,7,13 160:2,10161:10 163:1

controls 97:4convened 5:16 69:7conventional 38:4converges 229:12conversation 9:1,7

116:17 130:6 173:10246:16 276:20 280:20291:8

conversations 72:6coordinated 26:1coordination 151:1,4copper 210:22 238:22

239:2 241:1cord 55:13core 20:14coronary 158:7 229:21

231:1,4corpuscular 106:19

108:8correct 83:19 132:7

161:17 167:14 200:7correction 244:16

245:20 246:6correctly 83:20 172:5costs 251:20couch 291:10cough 183:8couldn’t 133:4 257:2counterclockwise

212:17counterparts 226:18countries 38:16 96:3

101:8 108:13 147:18

244:6country 22:3,3 94:19

181:21 196:22couple 133:3,4 169:20

182:16 183:3 198:12224:9 238:2 280:21

course 11:15 13:4,20175:6 205:18 221:4275:9 277:18 279:7

covariant 254:8covariates 20:22coverage 267:8covered 131:21cow’s 62:6crackers 215:8 219:11

220:2crazy 13:15 130:3create 160:5creating 88:7 258:4credibility 163:19criteria 8:6 21:4,5,6,11

21:20 22:12 23:3,537:1 43:14 44:18,2245:6 47:16 50:5,10,1453:5 54:5,10 55:456:1 58:5,8 64:8,1067:3,5 68:2,4 100:9136:18 139:10 140:10141:14 142:20 144:2145:22 146:6 179:20196:21 197:5,12198:2

critical 84:22 184:11277:14,20,21

cross-cutting 18:12,1729:3 72:6 204:14

cross-sectional 113:12113:15 114:21 115:18117:8 118:13 217:12227:22

cross-talk 166:19crossed 247:1,11,17

248:5,17crossing 248:17culprit 280:11cup-equivalent 207:7cups 207:21curious 200:19current 5:2,19 10:16

41:6 182:4 195:4207:1 213:17

currently 70:18 90:1291:16 158:16 176:9208:7 212:4

curves 69:5,10CVD 48:12 49:11 50:2

194:9 199:7 226:13277:3


300

cycle 256:3 284:13

DD 39:22 42:2,6,14,19

54:7,13 55:7 57:2170:4,7,16 71:1,4,688:19 210:12 215:21222:11,15,17 239:20

D.C 3:19dairy 115:15 178:14

186:8,9,11,21 187:10200:12 207:20,20208:2,20 209:9218:13 220:10,15222:18

Darcy 75:4 82:20DASH 257:8,19data 2:13 18:17 19:11

23:8 24:20 25:6 27:827:11,15 29:2 31:2271:8 89:17 111:15113:17 127:9 129:3131:1 168:16 180:20184:14 197:12 204:13205:2,6 206:3,5,13,15206:17 207:18 211:17213:15 217:11,12222:13 224:2,5225:10,16,18 227:12227:14,16,22 229:6230:3 232:16 233:20234:16 235:16 236:15236:16,20 237:12239:10 240:10,12242:17 243:9 246:16249:15 250:7 252:16253:11 254:6 255:1255:14 256:3,16258:10 260:12 263:19265:2 269:9 272:15272:21,21 273:17275:10,22 276:8279:19 281:15 286:10

date 16:2 23:8 36:15dates 198:7David 26:4Davis 1:14 204:20

285:8day 31:3 109:5,18 175:7

194:22 204:11 207:7207:21 208:13 285:5

days 8:2 13:20 112:22113:8 114:10 115:6

deal 31:1 131:4 166:14285:2

dealing 265:15deaths 194:5,8debated 201:20

decade 212:6December 13:12,12decide 35:13decided 36:1 69:1,22

70:4,6 91:14 135:18137:16

decision 113:19 122:4202:16 236:19

decision-making133:13

decisions 19:3 25:1835:11 133:15 166:13177:14 236:15 257:2

decline 156:1declines 223:9decrease 219:17 223:7decreased 66:7 208:2

226:2 228:17 230:6decreases 208:1

216:18 219:20 220:3decreasing 215:18

277:16deep 217:6 223:21defer 79:22 168:10deficiency 56:6 109:1

109:10deficit 100:5 138:6,7

152:15,16 153:10,10172:20

define 286:14defined 75:13 83:4

112:3 194:5 197:6237:3

defines 20:13defining 134:19definitely 179:10 193:2

241:15definition 34:1 75:10

80:22 92:12 184:18194:2 286:17

definitions 21:2 33:875:2 83:6 92:7 192:19193:10 211:22 254:18

definitive 168:22degree 226:12 231:6

251:22 291:12delay 102:12 103:10delayed 104:12deliberate 7:11 92:13delivery 95:1,19 97:3

101:17demand 26:18demanding 67:14demographic 266:11demographics 215:3

267:22demonstrate 256:8

291:15

Denmark 95:22Denny 3:14dental 227:17,19 228:5

228:7,11 229:7,14264:18 269:7

Department 6:13 9:11Departments 5:4 6:9,15

7:4 13:10 15:13depending 23:9 83:19

203:2depends 41:15 75:19depression 100:6 104:2

106:2 138:15 154:18155:3,15 156:2

depressive 155:6depth 24:2dermatitis 45:21 46:2

46:20 47:2 58:1559:13,22 61:6,16,2162:7,22 63:18

describe 28:6 43:6 78:8206:22 289:9 290:15

described 10:16 91:3describing 94:13 155:9

172:15 289:3description 24:1

184:18deserving 266:6design 21:14,21 49:20

52:1 125:15 172:7196:21 278:16 287:11287:14

designated 3:6designed 40:20 135:1

172:6,12 279:22despite 60:11 160:21desserts 208:18,22

209:5 215:6 220:13221:4

detail 78:8 133:20136:10 145:16 156:15180:15 182:22 197:2202:13 218:21

detailed 24:9details 176:11 187:13

264:9detected 140:11 141:15deteriorating 277:16determinants 291:11determine 37:11 41:18

42:7 47:4 49:11,2250:21 52:5 55:6 56:1557:19 58:18 60:2 61:861:17 62:10,21 63:564:2 65:1,13 66:3105:10 111:8,12116:9 118:21 119:2,4119:11 129:22 138:4

138:12 141:6 142:12143:11,15 144:12,21145:3 148:16 150:2151:8 152:10 153:2,7153:16 154:7,12155:7,12,20 158:11158:17 186:1 187:9189:6 190:9 191:16

determined 102:2detrimental 149:2,5

150:11,14 166:7169:15 170:5,13171:22

develop 6:11,15 71:9135:18 137:16 284:16

developed 7:13,21 9:819:18 21:7 35:7 67:1491:1 236:13 259:9

developing 58:15,2060:18 158:19 259:16

development 5:5 7:922:4 52:13 78:1782:16 84:3 89:2,1190:10 91:19 99:14103:8,17,19 104:1,5104:13 105:12,13,16106:6,7 126:6 135:9136:5 137:14 139:3140:8,13 141:3,7,12141:17 142:9,15,18143:2,6,13,17,22144:18 145:2,6,11146:3 147:1,20148:11,14,19 149:3,7149:12,16 150:5,12150:16 151:10,13152:1,13 159:22

developmental 32:1733:2 52:12 67:1,10,2171:13 99:13 100:1,7104:4 126:5 138:21139:5,13,17 140:7141:11 142:17 143:20147:13,14,19 162:11

deviation 184:13devoted 16:18Dewey 1:15 2:7 31:11

31:13 73:15 74:875:14 76:14 77:11,1879:12,15 81:3,1282:13,20 83:3,18 84:884:11 85:2 159:18162:4,14 169:10,10169:19 170:7,15171:6,9 200:11,11244:2,3 245:15 246:7246:18 247:5,11,16248:15 249:2,6,10


301

250:5,9,17 251:8263:13,13 265:19,19270:21

dexterity 151:1,3DGAC 26:12 29:15DHA 34:4 38:3,9,9

137:2diabetes 11:4 50:4,8,9

50:11,14,20 51:1,8,1551:21 52:6 73:4 78:1182:8,11,12,15,15,1788:22 90:4 93:22,22120:13 123:6,13,21176:19 196:17 198:20227:13 231:8,9,13,15231:18,21 233:19,22234:5 264:19 272:1272:11,12

diagnosed 22:18 97:12diagnosis 100:15

102:17 138:9 153:19155:2 253:4

dichotomous 81:18didn’t 10:5 38:22 81:19

109:8 129:22 131:8162:6 165:14 200:15242:20 248:18 249:3250:21 263:21

diet 5:20 9:20 20:1464:3 77:3 89:13 91:2192:11 115:22 116:6118:7 123:22 126:14127:10 179:13 196:4212:4 213:15 216:22217:21 218:2 222:21222:22 247:9 257:7266:7,15 267:16277:12 278:1

diet-related 23:5dietary 1:1,7 2:10 3:7

3:17 4:20 5:6 6:3,168:7,21 9:1,3,9 10:3,310:8,12 12:4 13:6,1117:9 18:14,15 23:1029:1,8 34:3 63:21,2166:18 77:9 81:4 85:1085:19 89:5,8 90:6,1890:20 91:17 92:8,9111:20,22 112:2,7,9112:10 114:2 115:9115:13,19 116:10117:10,16 118:15,18118:21 119:3,8,9,12119:16 120:11,15121:18 122:7,10,18122:22 123:4,11,14123:20 124:4,9,12,21125:3,10,15,19 126:3

126:4,7,11 132:4134:1,9,16,18 159:4,6206:11,15 207:19209:16,18 211:2,11236:16 237:5,7,19239:10 240:10,15241:8 248:21 249:15256:5,7,11,15,21,22257:13 258:4,10267:18 268:3 269:20272:6 276:14 282:21283:18,22 285:16,21288:2,9,10,16

DietaryGuidelines.gov14:21 16:7,12 20:621:19 28:9 43:6 52:1869:18 120:21 121:1121:14 193:22

diets 38:21 116:12117:17 119:5 218:7242:15

differ 69:5 77:2 223:5232:11

difference 41:13 113:21167:8 192:16

differences 40:15 135:6144:9 178:4 212:7213:5,8,18,19 216:11231:14 234:4 262:3,4267:6,13

different 4:5 16:9 21:1127:14 36:10 38:340:16 59:3 65:2074:12,21,21 77:1992:20 95:15,16 102:4102:9 112:5,10,10,13114:11 115:13 127:8132:12 170:5,18171:1 178:14 192:12195:2,3 201:7 214:5217:13,20,22 219:6220:9 225:7 230:3232:1,16 234:20235:1 256:14 257:17258:21 265:22 268:13271:10 273:13 274:20278:4 279:9,10,11,11280:3,13 281:19283:1,6 290:17

differential 245:1differentially 246:2differently 203:21differing 57:9 119:5,9

201:9differs 117:1difficult 67:16 116:20

144:12 153:2 154:7155:7 158:11

difficulties 152:4difficulty 190:16digestion 286:15diligently 89:15diluted 178:7dimension 144:17diminished 163:2direct 76:13 81:20

98:13 104:16 110:20262:21

direction 75:18 78:2161:4 162:13 165:9170:2 200:22

directionality 72:22directions 278:10directly 40:21 94:7 95:9

107:6 130:12 237:13268:2

directness 40:19disadvantages 54:22discouraging 276:6discrete 207:13discuss 15:9 85:9 88:6

112:12discussed 13:8 18:2

25:6,20 34:20 69:19145:17 193:21 195:21197:1 199:5

discussing 25:4discussion 2:14 11:6

15:11 21:5 24:10,1424:17 25:13 28:1829:5,10 79:14 128:22166:16 242:14 260:19262:17 263:5 278:9283:21

discussions 68:15169:7

disease 7:16 11:3 22:1522:19 32:13,17 44:1744:22 47:15,22 60:960:14,19 79:6 84:5112:15,18 136:1156:9 157:4 158:7,20159:7 176:15 196:19198:18 229:22 231:2231:4,22 232:6,9,15232:19 233:1 255:8261:3,18,19 264:21265:6 266:2 269:7291:2

diseases 43:2 52:1458:3 89:14 91:22 93:3126:15 206:18 264:15276:21 277:3

disheartening 278:11dishes 207:11 214:19

215:7 220:21

disorder 100:6,16102:17 105:3 138:6,7152:16,17 153:10,14153:19 155:2

disorder-like 138:8153:11,18

disorders 89:1 90:992:6 93:4,14 96:1498:6 99:1,8 120:12121:19 122:8,14,19123:2

disparities 262:5 265:7267:12

disparity 278:21disproportionately

235:12distilling 224:8distinct 66:18distinction 240:4distinguish 279:9distraction 87:8distributed 268:15distribution 44:18

106:20 111:14 114:13119:6 196:15 211:7

distributions 117:18239:18

diversity 63:21divided 35:8 53:21 59:2

115:12 212:13documentation 44:8

53:13 120:22 128:17130:4

doesn’t 251:18 290:4doing 23:18 24:16 27:1

28:17 129:20 132:4135:4 159:10 178:16180:16 198:16 199:12258:17,17,18 266:1270:18 282:6 285:12286:20 289:4,8

domain 58:2 83:20138:21 140:6,7,8141:11 142:17 143:21147:19 149:6 150:15151:12

domains 33:5 52:1068:20 139:5,13,17147:13,14,16

don’t 72:11 74:1 76:1979:10 128:2,7 129:9130:10 162:5,9164:10 168:22 170:21171:17 172:20 173:1173:12 174:8 182:22197:8,21 202:18209:3 211:11 212:19236:21 246:5,11,13


302

247:18 248:3 249:7252:2 256:10 258:18262:20 267:9 273:5278:7 279:3 281:15282:7,16

donor 33:15Donovan 1:15 2:9

76:21 86:11 87:14,1687:17 88:1 128:1129:1,5 130:5 131:5242:2,12 243:4 267:2268:7,9,11,17 271:20274:3 278:2

door 258:20dose 94:20 101:15

102:2 108:20 127:13164:14 187:19 202:1202:5

dose-response 162:19164:12 165:5

dosed 163:16double-down 284:1downgrade 167:21downward 228:10Dr 1:11,12,12,13,13,14

1:14,15,15,16,16,171:17,18,18,19,19,201:20 3:3,14 4:1314:21 17:1,13,2119:19 26:4 28:8 30:430:15 34:22 84:7,1086:15 131:5 134:2,5164:8 174:22 204:15204:20 252:17 263:7270:5 279:19

draft 23:21 24:3,18 25:325:7,9,14 26:8 27:532:2 35:1 41:8 42:2052:8 98:2 104:9 116:7118:22 120:1 126:10133:11,17 134:14137:19 138:1,20140:22 142:6 143:10144:20 148:15 150:1151:7 152:9 153:6,15154:11 155:11,19158:15 175:22 205:2209:7 213:14 214:18222:20 226:13 264:3264:10

drafted 25:11 110:14121:5 139:6

drafting 71:17,18 81:5159:1

draw 67:8,19 68:7 99:6125:12 130:16 272:20

drawn 103:19,21 125:9204:3

DRI 261:2,8drill 235:22drinker 197:16,17,18

198:3drinkers 195:4,6,7,9

197:20 198:5drinking 194:21,22

195:17,19drinks 194:21,22drive 246:20 277:5driven 170:11 289:6drop 128:16 183:8drop-off 277:10DrPH 1:19Drs 175:4Drug 9:12due 7:7 138:10 144:8

144:13 151:6 153:3154:8 155:7 158:12187:15

duplication 8:10duration 23:12 35:2,8

35:14 38:19 39:1940:2 42:3,9,21 44:2145:3 46:10,14,19 47:147:7,19,20 48:14,1649:1,7,14,15,22 50:950:12 51:3,6,10,18,2052:2 65:9 75:8 78:196:6,9 100:12 103:1108:4,18 109:21149:20 152:8 157:15160:2,11 161:14

durations 114:9duties 6:1,2

EE 210:12 247:7,8EAR 210:3,5 238:9

239:15 245:22earlier 197:1 198:12

219:9,16 220:1221:13 222:7 224:1240:22 241:4 267:15273:1

early 14:18 73:11,1897:2 98:4 100:3 102:5102:10 103:12 104:11176:16 216:19 221:2223:7 242:4 284:16

Eastern 14:17easy 135:14eat 27:15 206:12 274:8

274:9eating 10:13 18:16 29:9

196:4 241:6 252:12252:13 271:10 286:7286:14,18 289:10

eclampsia 93:8 95:396:16

economic 291:13eczema 58:16 59:22

61:6,16,21 62:8,2263:18

edge 212:13edition 6:16 12:7 13:11educated 115:3education 5:10 92:9

231:5educational 234:10effect 90:2 98:5 149:11

151:17 152:22 163:2167:2 171:22 172:6172:19 173:1 193:12199:22 202:4 262:11262:12

effects 40:20 118:1148:5 150:22 151:3166:22 167:7 170:13172:7,16 173:13

effort 176:13efforts 8:11egg 59:13 61:1,3,6,8eggs 60:17 115:16eight 32:3,4 67:4 68:3

88:7 94:3 101:12102:6 121:21 157:14188:1,11

eight-to-12-year-old103:16

Eighteen 84:10either 75:7 77:17 93:2

98:7 103:5 106:8114:3,12 142:22157:10 166:9 167:6170:1 179:4 200:3238:6,8 265:12277:19 282:2

elderly 285:11element 10:21elements 10:12 20:14

25:1 288:16elevated 232:3 237:10

255:17eliminate 238:12Elizabeth 1:17 2:12ELSIE 1:20email 4:8emails 233:21embedded 177:14emerge 245:21 270:17

276:12emerged 43:20 179:21emergency 261:15emotional 143:21

144:18 145:1,5

151:13 152:1,12emphasis 9:21,22

265:18emphasize 45:13encourage 16:6,21

278:15encouraging 212:5endogenous 78:6endpoint 23:7 50:2

156:20 238:11 247:15248:2

endpoints 224:17239:19

ends 174:3energy 34:16 116:3

179:10 182:15 187:17190:16 192:5 196:14201:16,17 203:12,13208:16 211:9,19213:22 214:17,22215:2,5,10,11 216:11216:17 219:3 244:12244:19,21 245:4,11251:22 256:17 285:1285:6

English 22:2enrolled 60:7,7ensure 287:5EPA 137:2equity 269:17 270:2especially 40:18 172:3

245:9essential 92:13essentially 236:10established 5:1 259:2establishing 194:15estimate 122:21 123:19

124:20 125:19 167:22estimated 182:2 235:9estimates 239:1 243:13

245:3,13 246:12249:17 253:8

et 78:1 172:18ethnicity 41:5 94:18

95:8 96:2 108:13114:7 196:2 206:7213:19

Europe 101:8 139:19147:17

evacuate 86:20,22evaluate 206:22 236:2evaluated 137:1 146:10

146:22 147:13,15238:10

evaluation 27:3,8 184:4239:17

Eve 2:3 3:4 17:2 87:13291:22


303

evening 292:7event 3:16everybody 131:14

291:5evidence 5:19 6:8 18:1

19:2,9,10,11,16 24:124:3 25:10 27:2 32:134:6 37:5,6,8,11,1237:15,17,20 38:6,1038:13,18 39:9 40:5,1241:10,17,21 42:4,7,1142:12,17 43:8,2044:20 45:1,10,18,2246:3,12,18,22 47:4,947:12 48:4,8,11,15,2048:22 49:4,6,10,14,1849:21 50:17,20 51:4,951:14,19,22 52:5,2154:19 55:5 56:2,14,2057:8,15,19 58:12,1759:8,11,16,18 60:1,2160:22 61:4,7,12,13,1761:19 62:4,9,20 63:463:14 64:2,12,19 65:165:6,12,15,19 66:2,566:10 67:1,7,7,12,1867:22 68:7,10 69:970:17 75:7 81:6,16,2084:12,19,19 85:1588:7 94:11 96:7,1198:3,19 99:5 100:2103:3 104:2,5,10,22105:9,14,20 106:4,7110:15,22 111:2,7,12111:15 115:17 116:8116:11 117:15 119:1119:4,8,8,11 120:2121:16,22 122:8,21123:10,19 124:8,20125:18 126:9 128:7131:2 134:14 138:4138:12 139:4,7 141:1141:5 142:7,12143:11,15 144:21145:3 147:12 148:16148:22 149:10 150:2150:9 151:8 152:10153:7,15 154:12155:12,20 158:16160:21 165:11 169:13169:21,22 170:4,4,5186:1 187:8,17,18,18189:6 190:9,20191:16 192:14 200:18202:5 203:6,7 204:1205:4,5,20 206:22249:22 250:10 263:1276:6 281:3,4 287:20

evident 56:13 57:7exact 76:10exactly 76:6,15 80:18

86:8 164:10 173:2218:17

examination 19:9 69:16examinations 33:14examine 6:7 11:5 19:10

19:16 34:2,8 40:6,2042:5,17 46:3 47:9,1369:1,20 135:17

examined 10:3 20:1524:1 33:17 35:17 36:744:19 47:10,18 48:1250:3 54:6,7,10,12,1358:6,8 60:16 61:1062:1,18 63:3,9,2170:11 75:7 83:10 91:393:6 143:6 153:13155:17 162:20 181:8181:10 185:1,8189:15 192:15 199:5208:15 227:6 265:21290:20

examines 35:21 36:338:18

examining 18:1 55:1070:16 88:18 138:11159:4 263:15

example 9:7 10:7 11:737:12 38:8 39:1 40:1541:3 63:12 75:22100:4 112:12 181:2181:18 194:21 202:1202:9 213:10 245:22247:7 257:8,8 264:17282:13 285:18 286:2288:13

examples 198:13exceeding 208:15

238:21excellent 26:21 130:13exciting 290:6exclude 22:9 23:2

197:8 198:9 245:11excluded 12:10 21:8,22

113:16 197:14,19198:4 250:19

excluding 22:17exclusion 21:4 22:12

197:11 198:1exclusive 35:3,9,18

40:2 42:10,22 45:347:7,21 49:16 50:1,1251:18 52:2

exclusively 35:16 60:6112:16 165:7

exclusivity 39:1

Excuse 182:13existing 43:4,17 44:4

52:17 53:9 70:10 76:991:8,15 120:5,20122:5 223:2 258:21

exists 125:18 281:4291:16

exit 87:3expanded 12:8 13:1expect 28:21 79:4,8

236:21experience 5:10experimental 34:2 41:6expert 5:16 44:7,12

53:12 69:8 121:3expertise 5:11explain 78:14 248:16

262:5explained 40:14 78:2

170:10explicit 269:16explored 8:15exposure 10:21 13:3

23:6 73:18 79:18,2092:18,21,21 95:1696:20 102:18 108:20112:8 131:7 136:12136:16 139:20 144:10145:18 152:6 154:9155:10 156:17 162:7163:17,18 164:1,4,17165:1 168:4 170:12177:19 179:3 181:21182:8 186:10 188:5189:13 191:6 192:11192:19 193:15 194:18194:18 196:8,11197:4,5 271:4

exposures 20:16 92:17181:5,7 184:13,13,19

expressed 33:18expressing 79:6expression 117:4extend 17:10 100:8extended 237:21extensive 71:21 256:20extent 287:11,14extract 71:8extracted 27:10 89:16

168:15extracting 31:22extraction 89:18extrapolated 242:17extremely 31:21 171:11eye 91:10 253:2

Fface 204:22

Facilitated 2:15facing 289:14fact 24:8 26:4 69:7

172:4 231:17 244:10275:10 281:20 282:11

factor 95:13 169:4245:20 246:6

factoring 243:7factors 5:12 20:21 55:9

93:13 100:13 125:17171:16 179:9 196:13

failed 259:18fair 78:22 177:15fairly 17:5 88:20 259:4

285:19fall 80:21 223:13familiar 88:20families 228:8family 60:10 80:2,10

100:14 196:18 268:14fantastic 3:15 17:15far 84:4,22 89:16

164:11 165:15 171:22172:3,9 239:16271:14 279:13 286:12

Farm 12:6farther 175:12fashion 178:22 188:11

287:17fast 248:18fasting 51:11 52:3

116:22fat 72:19 75:16 114:12

114:14,15,16 115:19116:1,3,4,6,11,13,14116:19 117:19 159:6178:14 186:12 192:11208:21 210:6 220:11223:20 237:8 238:19239:22

fat-soluble 113:4119:19

fathers 275:18fats 2:10 10:12 18:16

29:1 65:20 116:8117:14 132:4 134:1134:17,18 159:4208:16,17 210:8263:16,21 288:15

fatty 36:8 39:22 40:3,840:11,16 41:12,13,1542:6,12,19 54:8,1255:8 57:10,11,1165:18,21 72:20 75:1975:22 76:1 77:1,12,1978:7 83:12 112:13114:19 117:12 118:2136:22 146:12 150:21


304

255:18 263:21favorably 65:10,16,21FDA 33:21 34:7 92:12feasibility 160:9February 5:14 29:22

30:4 34:22fed 33:17,18 36:4 37:22

38:1,4,11 39:2,2040:22,22 41:14 45:1145:20 46:1,14 48:5,950:18 51:5 55:2 69:669:6 74:13 116:21

federal 3:7 5:21,22 7:187:22 8:9,11 9:1013:17 15:20 269:21

feed 35:12,14,15271:12,13 284:15

feedback 19:21,22224:10 239:6

feeding 32:16 33:1635:11 37:2 40:10 42:444:16,21 45:4,9,1546:10,15,20 47:2,7,1447:19,21 48:3,14,1649:2,16 50:1,6,9,1350:16,22 51:4,7,11,1852:2,10 53:12,1755:15,16 58:14 59:2162:12 65:9 66:6,1972:16 74:4 82:10 83:5117:2

feeds 74:15 286:5feel 8:21 70:14 85:9

165:12 172:18 201:5253:16 273:21 281:6

feels 173:19felt 7:10 81:18 110:22

160:19 225:10 278:18FEMALE 183:10females 22:8 208:12

209:22 210:4 217:1233:2,4 239:8 240:9259:19 275:11 283:7

fiber 210:12 239:21250:14

field 8:13 194:12figure 270:19figuring 129:17fill 187:12final 15:9,12 19:3 24:11

25:17,18 36:3 106:12111:19 113:11 122:4133:15 161:22 270:14

finalized 24:19finalizes 26:3finally 42:15 241:13find 36:17 85:17 94:11

151:17 155:5 162:6

187:3 260:14 278:13findings 103:18 125:13

183:7,15,16 186:17188:13 191:10 203:21205:9 230:14 256:9274:19

fine 151:1,3,4 195:18finish 270:10FINS-TEEN 146:14fire 86:18first 3:19 15:14 17:19

30:17 31:5,9 35:1147:13 54:3 56:6 57:258:14,19 59:9 61:1,1463:16 64:12 69:2272:15 79:18 80:483:22 88:13 89:4 92:294:13,22 97:16111:21 120:10 121:17134:9 135:5,7 136:2140:7 147:19 157:9162:10 163:14 175:3182:1,16 194:2 199:4201:12 202:7 206:21214:4 227:17 232:1237:2 244:3,8 260:5270:19 271:1 285:10

firsthand 15:17Firstly 45:10fish 61:10,10,14,18

101:16 122:12 123:16134:22 136:22 146:10146:12,17 147:4,4,5149:11 150:21 151:2151:17 152:20 154:4155:1,5 157:11,14,21158:3,4 164:20 172:6172:10,12

fit 28:18fits 282:22five 9:4 13:11 32:15,16

32:20 52:10 64:1471:10 72:14 88:2189:6 90:2 91:20 94:21107:20 110:9 140:14149:7 157:11 186:10186:13 189:16 200:13212:8 214:11 215:4219:18,19 256:16277:13

flagged 43:18flat 164:12 171:20

202:8flavored 191:5flip 196:10floor 86:22 87:1flow 23:21 36:9,12flowchart 137:4 145:21

156:22 236:14 249:13fluid 207:22,22 216:18focus 9:20 12:8 70:2,4

70:7 134:16 140:7144:7 147:12 161:13177:6 205:22 206:3210:16 233:22 287:4

focused 12:5,11 15:1550:10 59:5 136:17176:10 184:21 195:19197:21 279:16

focuses 59:1focusing 43:20 135:3

150:7 186:8 195:13271:12

folate 54:7,14 55:857:21 88:19 90:1,3,894:12 96:5 102:8105:15,21 106:10,12106:18,19 108:6,21108:22 109:1,9 110:6110:9,19 111:4,6,17126:8 128:11 131:8240:19

folic 92:2,3,16,18 93:2194:8,21 96:5,12,1697:1,5,15,21 98:3,998:20,22 99:7,11101:1 102:3,18,21103:4,11,14 104:7,10105:1,10 106:14107:21 108:15 109:5109:10,18 110:2,5,10110:12,16,17 111:3,9111:13,15,19 129:8129:10 131:3,7,11,12173:18

folinic 108:1folks 132:19follow 16:6 24:22 82:7

162:4 169:11 177:16266:18 275:7 290:7

follow-up 80:19 143:9144:15 158:9 255:1

followed 233:5 235:4following 17:20 28:19

103:6 126:11 134:20161:20 211:17 225:19

font 18:13food 2:13 8:16,17,17,18

8:18,19 9:12,13 10:1918:17 19:11 27:1629:2 43:1 52:14 57:1458:2,6,15 59:5,6,1060:17 61:2,11,20 62:762:21 63:18 64:1389:13 91:21 126:15139:21 147:6 157:22

168:3 178:9 182:4204:13 205:15,19207:1 209:2,15210:14 211:8 213:9213:21 214:6,7,10,16215:1 217:18 220:10221:3 223:4,4,12,13223:19 225:9 236:4,8236:13 237:4,10,16237:18,22 239:4241:5,7 242:5,10,22245:2 246:2 250:11256:16 258:5 259:20261:1 268:6 269:21269:22 273:19 275:1278:20 279:5 280:14281:17,19 282:9,18282:20 283:1,3290:15 291:10,12

food-based 9:3foods 8:17 33:5 34:11

34:12 35:22 39:453:20 54:1,9,17,2055:11,19,21 56:3,1156:16,21 57:6,9,17,2058:4,7,9,11,19 59:261:18 63:10,15 64:964:20 65:3,6,20 66:1467:2,10,15,20 68:3,968:12 69:21 70:12,1375:17,20 77:12,2083:10 88:14 90:3,892:4,19,22 94:11,1299:7,12 104:7 105:11105:15,18,22 106:7111:16 112:5 124:15126:7 129:11 206:14208:9 214:19 216:7218:6 220:16 273:18284:6,15,18 285:5288:11 289:15 290:21

fore-milk 117:1forget 72:11form 178:9format 19:5 20:10 24:18former 195:7,9 197:13

197:16,20 198:3,5formula 32:12,22 33:20

34:13 35:4,9,19 36:236:18 37:3 38:1,5,939:2,5 40:3,11,2141:1,14,16 42:22 45:547:8 55:3,16 56:1357:7 68:19 69:7,1471:11 74:13,16 77:2137:2

formula’s 38:7formulas 33:21 34:3,7,9


305

38:12 40:16 41:6,777:3

forth 83:12 284:2 286:2fortification 92:12fortified 33:4 57:1,7

69:21 70:13 88:1490:3,8 92:4,19,2294:11,12 99:7,11104:7 105:11,15,18105:22 106:7 111:16126:7 129:11 191:5

forward 18:4 26:1127:13 29:12 70:21272:22 286:11 292:6

found 19:22 30:1 41:1773:4 96:12,22 97:1597:19 98:1 103:14110:1,4,7,11 115:20116:1,4 118:18119:15 138:3 142:21148:4,10,13 149:10149:14,18 151:2152:20 154:2,21165:10 183:15,17,19185:6 186:18,19,21186:22 191:12 235:22277:10 286:12

four 3:10 4:9 8:6 28:535:10 54:21 59:1061:2,15 63:2,17 64:1464:21 90:22 100:19102:5 107:1 109:22113:12 114:10 115:13120:7 121:5,21 139:5140:16 146:11 147:13147:21 148:3,6149:12 150:20 152:2152:22 157:5,6186:17 201:13 225:12287:21

four- 151:15fourth 14:1 30:20 79:17

143:20 151:12frame 268:22 276:13framework 20:13,16

21:1 25:2 28:18 35:637:7 92:16 99:16106:16 112:6 119:18129:8 136:8,9 145:14156:13 177:12,15184:8 194:11,15200:10 206:11 211:4217:17 252:3 288:8

France 107:13freezing 33:19frequency 18:16 29:9

35:3,8 139:21 147:6154:3 157:15 168:3

182:4 241:6 286:7,14286:18

frequency-of-eating129:16

fresh 33:19 206:20freshwater 134:21Friday 29:22 292:10fried 124:15front 21:7 68:17 87:9

133:6front-end 286:9front-of-mind 269:11fruit 63:12 207:3,4,4,4,8

216:2 218:9 219:15219:17,20 223:9

fruits 56:17 115:15122:11 123:15 124:12209:9 212:14,17

full 13:21 17:4,5 19:424:15 25:13 26:1532:6 72:8 117:3133:12 179:19

full-term 38:14 55:164:18

fully 26:20function 14:17 78:17functional 237:12functions 251:16funding 281:9further 69:16 72:8 76:7

78:19 79:14 80:685:16

future 134:11 161:4162:13 258:20 275:13278:10,16 283:16

Ggain 91:17 126:12gaps 286:12general 7:1 9:4 20:10

30:5 60:9 73:11 77:8113:15 127:8,10132:9 174:2 208:10215:11 222:21 230:1260:10,15 264:7265:4 266:8 271:14274:5

generalizability 41:298:17 104:20 105:8110:22 116:16 118:4192:8

generalizable 60:13generalized 22:6generally 22:12 37:14

37:22 38:14 39:1163:11 64:17 73:1976:1 83:21 103:4189:14 192:13 209:3

209:10,12 213:20220:7,17

generate 286:10generational 275:21

291:6generic 265:4genetic 267:11genetics 267:9geographic 5:12Germany 101:6 108:11gestation 97:21 101:17

102:6,9gestational 88:22 90:4

91:17 93:9,16,21,2295:4 96:15 97:4,8120:13,16,17 122:15123:5,13,21 124:5,22125:4,14 126:12176:1 177:9 179:1,2,6181:16,17 182:11185:16,19 187:3189:3 191:13 193:4,6203:10 233:19,22234:5 272:1,11

getting 18:22 127:18222:16 267:14,15,16281:10

girls 226:1,4,6 227:11240:18

give 14:22 37:4 134:2174:8 182:20 206:9214:16 217:6 224:8246:15 259:7,14261:2 267:20 271:18274:6 286:7 290:12

given 21:2 65:16 67:675:15 84:17 178:8,10235:15 263:11 271:11274:18

gives 53:13giving 17:20 165:10

180:22 204:15 274:9glancing 182:6 202:22gland 78:6glass 182:12glimpse 182:21global 166:21glucose 51:11 52:3

79:9 196:17go 16:12,21 18:21 20:8

25:22 26:13 27:4 31:531:10 32:5,8 33:1237:18 48:2 62:14,1562:16 73:22 77:778:19 80:6 82:1 85:385:16 88:1 101:18107:10 120:4 122:4128:16 133:22 175:16

175:17 178:18 180:3207:2 248:6 249:12249:13 264:8 265:18271:15 275:5 282:16283:11 292:4

goal 9:2 88:6goes 76:6 159:10

218:13 250:6,9266:12,17 270:19281:6

going 4:14 17:21 18:318:20 20:7 21:15 24:730:15 31:10 32:8 46:558:1 62:14,16 68:1569:18 71:17 74:977:16 79:22 80:1285:7 86:7,8 87:13,1489:6 111:20 119:22130:20 134:2 137:22165:15 167:6,7200:21 206:3,8207:14 210:16,19212:15 214:1 217:7218:16,18 220:10224:2,4,5,8 233:18241:9 243:2 254:15254:21 258:3 259:20260:21 266:6 270:11270:19 271:2 273:13273:17 275:4 276:9276:11 277:4 284:8286:9 289:3 290:12

good 3:3 73:22 74:885:5 128:21 132:21165:17 166:2 168:9169:7 171:12 173:7179:11 183:1 197:9200:8 245:14 246:4246:16 253:12 254:17269:12 286:16 292:7

gotten 260:19 283:18government 5:22 69:7grade 106:2 111:11

116:14 122:19 123:3124:1 126:10 138:16141:4,8 142:10,15143:18 145:6 148:20149:4 150:6,13151:11 152:14 153:12153:20 154:5,15155:15 156:2 158:20165:11 186:5 187:11189:8 190:11,20191:19

grades 24:4 71:10105:19 120:3 134:14

grading 287:6gradually 79:11


306

grain 208:6,8 219:22281:22 285:19

grain-based 215:7grains 115:15 122:11

122:13 123:15 124:13208:4 209:9,11218:10 220:3,4281:21 282:1,12285:19 286:1 290:4

grams 157:10,14164:21

gray 201:6great 17:4 31:1 79:15

127:2 128:1 129:1130:6 161:5 162:16166:13 175:3 199:18202:17 204:17 264:5268:17 289:22

greater 60:8 80:13116:3 154:22 183:17185:4,13,15 186:18186:21 187:5 188:14188:20 189:19 190:1190:6 192:2

greatest 278:13greatly 144:6green 188:6 219:7greens 213:10 218:8grip 252:20,21group 18:17 29:3 44:11

53:16 70:19 80:2185:20 95:10,11 96:17129:16 131:6 160:15160:19 166:21 168:7195:9 197:16,17,18204:14 209:15 213:11214:9 224:6 225:7226:6 232:21 233:6,9240:16 241:5,7 260:2261:10 262:10,20266:20 271:1,2,11279:15 282:17 283:8

groupings 209:18groups 8:16 23:12

167:9 197:12 206:6207:1 208:15 209:3210:1,14 211:18212:10 213:5,13217:13 219:6 220:5,9220:18 221:7 222:10223:4,12 224:17228:2 230:4 231:16236:4 238:1 239:12239:15 240:6 242:5256:16 261:1 273:10278:1 281:19 282:9282:19 283:2 286:21287:4 289:21

grow 27:13 275:17growing 12:2growth 32:17 33:1,5

52:12 55:15 64:6 65:465:11,22 66:9,15,2068:20 69:5,10,11 70:171:12 84:2 176:4,20198:22 199:8 266:4277:7

guess 162:20 165:4,12242:9 264:6 265:3267:4 276:4

guesstimate 74:19guest 78:20guidance 3:5 9:3 12:4

223:3 239:7guideline 17:9 237:8guidelines 1:1,7 3:7,18

4:21 5:6 6:3,16 8:7,229:1 10:3,4 13:6,1123:10 85:10 209:16237:19 267:19 268:3269:20 272:6 276:14284:2 285:21 289:2290:6

Guidelines.gov 90:6GUNGOR 75:5 83:2guys 241:17 246:15

Hhadn’t 12:10,11,13

192:22 263:18half 49:3 86:7 101:12

101:13 115:7 192:14203:10,11 207:21256:17

hand 27:20 69:13 151:5170:16,17 252:20,21283:11,11

handle 273:11happen 86:18 87:2,7

195:16 281:9happens 275:16happy 4:11 126:22hard 31:17 71:20 88:4

126:21 164:22 235:16283:4 290:15

hard-fought 166:13harm 170:16 171:1,11

171:15 172:2harmful 172:7haven’t 11:18 242:8

245:6 253:10 271:5271:21 272:13 284:22

Hawaiians 234:7HDL 226:20 227:3

229:20 230:6,8,11,20head 82:22 226:11

health 5:3,4,20 7:16 8:89:12,20 10:17 11:5,711:9,15 20:14,2022:10 23:2,6 32:14,1933:6 43:2 52:15 68:168:9,12 69:10 70:471:7 73:14 80:4 84:992:9 106:17 122:9123:18 124:17 155:18156:1 196:22 198:17199:3,8 205:16210:18 227:5 234:15236:3,7 237:11,14238:14 240:4 241:12245:10 249:1 250:11250:15 253:18 260:8260:20 261:6 262:6262:19 263:16 266:12267:8,13 268:1269:16 270:1 272:9272:17 275:2 280:16282:11,16 283:13290:20

healthier 283:3healthy 22:14 38:14

55:1 64:18 80:22 93:2112:15,17 122:8123:18 124:17

hear 12:16 13:19 15:1121:5 28:21 86:10,1986:20 87:2 133:5,7207:15 224:10 241:16258:13

heard 18:19 241:20hearing 15:17 133:11

133:17 205:3 270:15heart 75:3 158:7 229:21

231:1,4 259:16Heather 1:16 284:4heavy 144:10HEI 211:5,13 213:7,13

217:19,22 218:6256:3,12 257:18258:22

height 81:21held 14:15 16:3 29:8

168:7hello 4:2help 74:10 87:7,8 132:1

223:15 251:17 284:17288:11,19 291:14

helped 275:1helpful 15:17 20:1 30:2

72:18 162:3 202:19247:22 258:22 271:19275:5 291:19

helping 17:16helps 56:5

hematocrit 39:16hemoglobin 39:16

106:19 108:7 109:10110:11 111:10

hepatitis 255:19here’s 248:15heterogeneity 140:18

141:20 143:4 144:13149:18 152:5

hey 290:8Heymsfield 1:16 252:17

252:18,21 253:1,20254:1,5 286:6

HHS 5:8 6:14,18 7:1713:8 18:5

hierarchy 288:10high 22:4,4 79:21 96:2

97:8,22 98:7 99:3101:22 107:15 128:16160:18 198:14 207:2226:19,21 229:19230:5,7,16,17 232:6,6234:6 237:13 240:22242:6 253:15 257:17262:2 290:3

high-fat 208:20 221:15222:17

high-level 206:9high-middle 115:3high-risk 80:21 97:10

260:1,2higher 45:12 46:16 48:6

50:19 51:7,21 64:2265:7 77:4 86:1 97:1898:8,20 101:10114:12,14,15,16116:12,13 122:11123:15 124:12 154:5168:7 183:19 185:16186:18,20 188:21189:4 190:1,7 200:2212:9,15,18 218:6220:11 225:22 226:3226:12,15,21 227:4227:10 228:9,20229:10 230:7,8 231:5231:12,16,19,19232:5,11 233:12234:3,22 237:5 262:1262:8,14,14 263:2272:11

higher-risk 95:11 98:14highest 59:12 164:16

189:3 213:6 218:2221:2 225:5 226:7,8227:6 228:4,6 229:1,3229:13 230:10,12,15230:17,19,21 231:1


307

231:20 232:8,14,22233:4,7,8,10,15 235:3240:16 253:2

highest-risk 80:10highlight 24:6 133:17

178:2 194:16 222:12265:20 292:1

highlighted 137:14180:4 193:1 228:15266:6

highlights 145:21 205:9highly 115:3hind-milk 117:2Hispanic 226:9,22

228:4 229:2Hispanics 230:16,19

231:19 232:5 235:5history 60:10 80:2,10

98:7 100:15 196:18hold 86:19 233:21holding 3:11holds 73:12home 277:5hope 9:15 15:16 279:3

292:7hopefully 283:20Horn 4:13 134:6 174:7hospitalized 22:19host 15:2,2hosted 15:15hosting 17:11hosts 3:16hour 32:7 86:7hours 31:17 201:20household 158:5

226:11Houston 1:9 3:13 4:19huge 27:21,22 85:7

159:10 286:12human 5:4 9:12 22:4

32:11,22 33:13,15,1733:18 34:13 35:3,9,1235:14,15,16,18 36:2,436:18 37:2,18,21 38:138:19,19 39:1,3,5,1539:20,20 40:2,8,10,2241:9,11,14,15,19,2242:4,10,16,22 44:1644:21 45:3,9,11,15,2046:1,10,14,15,19 47:147:7,14,19,21 48:4,548:9,14,16 49:2,8,1650:1,6,9,12,16,19,2251:3,6,7,10,18 52:255:17 68:19 69:6,1471:11 74:13,16,18,2077:14,22 78:5,1688:21 90:3,20 112:1

112:16,19 113:1,5,7113:16,22 114:3115:20 116:4,20119:14,17,20

humans 22:8Hunger 132:15hungry 131:15hydration 251:20hyperactivity 138:7

152:16 153:11hypertension 93:9,14

93:21 94:3 95:4 96:1597:4,9 122:16 196:17226:15 229:21 230:8230:13,21 231:3233:20 243:8,16261:20 262:9 291:2

hypertensive 89:1 90:992:6 93:4,14 96:1498:6 99:1,8 120:12121:19 122:7,14,19123:1 262:12

hypokalemia 261:15

II’d 81:3 82:1 88:3 164:2

205:7 270:1,10 290:8I’ll 6:9 8:7 30:9,16 48:2

54:15 72:10 87:1088:1 90:19 91:15122:1 132:8 187:12219:2 238:2 286:6291:17

I’m 3:4,6 17:21 18:3,2020:7 21:15 30:1431:10 32:8 46:5 58:162:14,16 68:14 72:1673:9,19 74:6,9 77:1577:17 78:14,14 82:2183:19 84:1,19 86:287:13 89:6 93:18,19107:1,1 111:20 115:1119:22 128:10,18129:7 130:22 137:22163:1,14 168:8 170:9173:16 175:8 182:22187:13 200:19 202:1202:17 205:3 206:3,8206:13 213:22 222:12224:2,4,5,7 225:13249:10 251:10 253:19254:1,12 257:19260:21 267:2,3270:19 274:12,19275:3,6,12 276:19280:19 281:19 282:10282:21 284:8 286:10290:9,12 291:22

292:5I’ve 38:17 173:17

191:20 197:21 271:20idea 79:15 245:14

253:12 263:2 283:22284:12,17,21 287:1289:19

ideal 212:19 213:2ideally 196:14 217:9ideas 162:1identified 6:9 7:1,4 37:1

176:7identify 6:19 43:19

183:6 237:18 241:11identifying 238:1III 234:11illustrates 137:4imagine 38:6 85:8

95:15 222:13imagining 225:13immune 78:17impact 8:9 20:21 38:8,9

90:20 91:12 118:21131:3 149:2,5 150:14169:15 178:2 263:3

impacts 150:11imperatives 31:7implementing 134:9implications 276:2importance 8:8 278:8

280:4important 8:22 11:16

32:10 34:8 38:2048:19 132:18 154:6163:11 164:5 171:7179:11 190:18 195:11196:3,9,12 197:4200:9 201:2 254:8269:19 270:6 272:3273:15,21 274:11275:15 276:10 277:1277:5 279:9 284:22285:7,9 286:4,8,22287:8 288:18 291:9

impossible 256:10impression 172:16improve 280:16improved 213:16improvement 148:21

150:8improvements 141:2

142:8 148:18 150:4172:18 272:9

in-and-out 87:6in-person 1:10inability 272:20 276:7inadequacy 247:8inadequate 125:13

153:3 154:8 155:8158:12 184:17,18244:9

incidence 65:14 66:496:13 97:16 108:22227:9 233:4,7,12,14272:17

incidences 109:10include 7:17 11:9 14:7

15:21 21:13,20 22:1423:1,5 24:22 25:132:10 33:14 35:1255:12 71:5 93:15136:22 161:5 178:5191:4 194:7 195:16198:7 224:12 237:21263:16 267:7

included 21:8,22 22:322:11 24:10 34:640:18 46:17 48:1 60:670:12 75:7,9 94:3,4100:18 103:20 108:5110:13 113:10,15121:20 123:6 137:3137:12 138:10 146:1147:21 149:8 150:17151:14 152:19 153:13154:1,20 155:2,17157:5,6,10,19 158:5171:19 176:7 179:22181:15 254:21 255:5268:8

includes 8:16 20:1624:9 34:13 69:2134:22 156:1 197:20

including 5:12 9:1112:3 14:3 22:15 25:127:7 52:13 55:1860:19 61:11 68:2069:15 83:15 92:18,2193:6,12 96:14 98:2299:13 106:6 113:3117:10,17 122:15126:6 139:13 197:16210:11 219:7 282:14288:12

inclusion 12:6 21:4,2022:11 37:1 43:1444:17 45:5 47:16 50:553:5 56:1 58:5 64:8139:10 142:20 144:1145:22 146:6 197:5

inclusion/exclusion21:16

inclusionary 140:10141:13

inclusive 7:11 206:15221:12 227:11 235:21


308

income 115:3 213:19228:9

inconclusive 46:2 47:348:10 49:10

inconsistencies 40:14204:1

inconsistency 125:13166:11 193:9 203:9

inconsistent 49:4103:18 155:8

inconsistently 193:4203:22

incorporate 161:22252:5 265:10

incorporated 99:21101:7

increase 74:5 76:17219:14 223:8 234:17243:3 255:7 276:22281:21 285:18,20

increased 75:21 163:17163:22 212:6 225:6226:5 228:18,22232:13,20

increases 208:6 215:17216:20 220:4 223:11226:1,4 228:1 229:16

increasing 163:18264:20 265:6 269:6

incredibly 72:4 164:4,6286:21

independent 5:2,1845:16 46:17 49:5

independently 181:9,11185:3

index 257:19indexes 256:21Indian 230:22 232:7

234:6indicate 57:16 168:19

200:4indicated 40:9 63:4indicates 41:10 65:6indicator 250:1indicators 39:17 237:12indices 256:4,11indirect 262:22individual 217:15 258:5individuals 14:8 73:20

80:9 145:20 195:17220:5 233:15

industry 285:22 286:5inequity 269:17inextricably 273:19infant 32:12,22 33:20

33:21 34:2,9,13,1535:4,9,19 36:2,1837:2 38:1,4,12 39:5

40:3,11,20 41:1,14,1642:22 44:7 45:4 47:856:13 57:7 66:1268:19 69:6,14 71:1174:13 82:10 89:2,1089:14 90:10 91:1999:19 120:16 121:11124:3 136:5 137:2,14139:3

infants 22:22 36:537:22 38:1,4,11,14,2139:20 40:22 41:1342:17 46:13 51:5 55:256:7,8,11 57:3,659:12,15 60:13 64:1869:6 79:20 80:9,1199:14,20 179:5 206:1284:15

influence 57:11 65:1065:22 85:12

influencing 278:1inform 8:10 274:21

284:17informal 43:19information 14:2 15:19

15:21 16:2,10 18:2,2220:3,5,8 24:14 90:5131:21 155:9 166:17177:2,3 192:12 197:7224:7 273:12

informed 205:20235:19

informing 269:21 286:4informs 275:16ingredients 34:3,9initial 7:21 172:16initiated 94:22 109:6,20initiation 95:18 96:6,9

101:16 108:2,17114:8 115:6

input 7:17,21 8:5,14224:7 260:7

instances 76:12 161:3Institute 257:13insufficient 41:17 42:4

42:11 46:3 47:3,948:11 49:10,21 50:2051:14 52:5 56:7 58:1765:12 67:7,18 68:6,1084:19 105:9 111:7116:8 119:4,10122:21 123:19 124:20125:18 138:4 143:11144:21 148:16 150:2151:7 152:10 153:7154:12 155:12 158:16160:21 170:3 185:22187:8 189:6 190:9,19

191:16 200:18,20205:4 276:6

insulin 51:12 52:3 79:8insurance 267:14intake 39:5 55:16 65:7

65:8,13 66:11 69:2072:20 74:20 76:1777:10 92:18 104:6128:11 135:7,10,21136:21 137:8,10138:5,13 139:12,16140:1,2,13,19 141:1,7141:16,21 142:1,7,13143:1,5,12,16 144:14144:22 145:4 146:10146:22 147:3,4,5148:10,14,17 149:1149:15,19 150:3,10150:21 151:9,22152:7,11,17 153:17153:22 154:18 155:1155:5,21 157:2,21158:4 159:20 164:20167:22 168:12,18169:13 172:12 179:10181:14 182:2,5,15183:18 185:5,13,15185:18 186:9,18,19186:21 187:5,17188:2,14,21 189:4,11189:14,20 190:1,6,16190:21 191:2 192:5192:20 195:5 196:14201:4,16 203:13,14206:14 207:20,22208:2,6,16 209:11,18210:2 211:9,12,17214:22 216:11,19218:13 219:22 220:1221:2 223:9 237:6239:12,18 244:12,13247:7 261:18 262:1,4262:9,14,14,19 285:1285:16,19

intakes 9:9 10:16205:16 206:12 207:1207:6,6 209:8 210:1,4211:13,19 212:17215:10 219:14 220:22221:19 223:7,11236:4 237:13,13238:12 239:11,16240:12,22 242:6244:10 248:21 263:2271:22

integrate 271:5 272:4285:3 288:12 290:18

integrates 283:19

integrating 270:7,22272:15 273:12

integration 274:13288:7,19 291:1

intelligence 140:15intended 36:17,20

92:11 184:13intensity 36:3 42:15

72:16,17 74:11,1875:6 100:12

intent 24:13interest 4:20 11:8 12:3

16:17,20 17:8 22:2023:6 24:7 29:15,1856:20 188:1 264:16283:8

interested 20:19 22:822:13 84:20 120:22203:15,18 254:6

interesting 85:11216:10 256:9 277:10277:13

intermediary 266:14intermediate 20:18

23:7 93:5 156:19164:15 226:14 229:19

internalizing 155:2interpreted 25:16interpreting 203:21interval 168:5intervenes 267:17intervention 20:16

48:21 101:15 112:7136:16 146:11 152:6157:15 163:20 177:18194:17

intervention/exposure99:17

interventions 23:692:17 94:16,20101:14 107:19 282:5

intolerance 79:9introduce 80:4introduced 55:12 58:20

59:2introducing 54:20 59:9

59:12 61:1,14 63:1564:20

introduction 35:19,2240:3 45:4 47:8 53:2254:6,16 55:7 58:4,1161:5 62:5 64:8,11,1365:2 67:2,9,15 68:2,873:12 80:14

inventory 158:5inverse 76:12investigating 33:11investment 258:9


309

invitation 17:14invited 19:21 26:4involve 24:16involved 9:11 87:1

142:18iodine 36:7 42:1,8,13

42:18 88:19 113:4119:20

IQ 140:15 141:17149:17

Iran 94:15 107:13Ireland 108:11iron 36:7 38:4 39:17,21

41:20 42:5,13,18 54:654:12 55:1,14,17 56:456:5,6,7,9,12,17,1870:2,2,7,16 71:1,488:19 240:8

iron-deficient 107:18iron-fortified 54:11

55:2 56:4,13 65:8Islanders 234:8isn’t 80:12 278:14isolation 7:13 284:6,7Israel 102:13 105:5issue 190:17 198:3

255:14 258:3 261:16267:18 270:12 280:3281:17 289:5

issues 9:14 67:11104:17 192:18 246:19261:12,14 278:21,21280:17 283:12

it’s 6:6 13:16 17:4 21:1722:5 29:20 30:21 32:438:20 41:5 67:1668:21 73:1,2,2,2274:19 76:2 78:3,4,781:1 82:8 85:7 87:18115:14 128:1 130:12130:15 133:1,6135:13 154:6,7 155:6158:11 160:4,8 171:6172:22 174:1 197:4,9200:1 201:7 204:12204:17,21 208:11219:2 220:18 221:7222:7,18 225:10,16226:15 229:4 234:21234:22 235:8 236:22244:4,18,22 247:10250:15 251:3,5,13,14253:14 255:9 258:8264:10 265:7 266:10266:15 267:9,17,18269:10 270:6,13,18273:8,10,21 276:5278:15 279:8 280:11

281:2,8 282:17,22283:4 285:8 288:22290:2 291:9

Italy 95:6,10item 136:19items 258:5 283:3

JJamie 1:20 128:12

204:19Jamy 1:12 172:14

204:19 254:22 261:9261:11 263:7 288:6291:6

Jamy’s 269:3January 1:5 36:15

44:15 53:19 91:6122:3 123:8,8 198:8,8198:9 292:11

Japan 109:13Joan 1:19 83:8 134:5

169:6 171:14Joanne 168:10job 85:5join 4:13,14,18 14:1joining 3:22 4:7 86:16Journal 43:10 53:1

121:7judge 244:17judging 74:17juice 66:11 207:4 216:2

219:20Julie 84:1July 53:19 136:10

145:16 156:16jumping 92:2juxtapose 74:7

KK 210:12KATHRYN 1:15Kay 2:7 31:11 72:3,9

82:7 91:3 121:6 122:2169:10 200:11 243:19244:1,3 263:13265:19 270:20 289:20

Kay’s 88:21 289:19keep 27:13 30:3 85:3

154:6 209:2 210:19keeping 26:22,22key 20:21 21:2 33:8

93:10 100:10 125:16140:17 141:19 143:3144:9 147:11 160:20165:8 179:6 184:8,17187:16 190:15 196:1196:5,7 201:14230:14

kicked 77:16kids 242:3 255:20kind 7:8 9:6,16,21

10:11,13,21 11:5 13:213:3 15:16 23:4 85:687:6,8 88:9 102:4118:20 124:19 160:5164:22 170:20 178:19181:2 201:17 203:5203:14 204:2 205:9207:18 218:4 225:16235:20 240:7 250:4251:14 266:10 267:10270:12 278:3 279:14279:18 281:6 282:7283:11

kinds 21:21 161:4,15269:22 274:22

Kingshipp 202:21,22Kleinman 1:12 2:16

30:15,18 72:3 78:2179:13 80:7,17 81:1184:15 86:5 87:12,21127:2 131:13,17132:15 162:15 163:15165:14 199:18 270:5290:14

Klurfeld 26:5know 15:4 18:13 26:19

27:21 43:12 53:4 69:574:1 79:10 84:2085:17,21 87:5 96:7117:6 128:2,14 130:2130:21 132:3,6 160:8160:19 162:6 163:10165:8 168:21 170:21171:16 172:12,20173:1 174:8,12177:19 178:16 180:3180:17 182:21 187:20190:17 194:12 195:15195:20 198:15 200:17201:2,17 202:18212:20 214:2 219:2219:16 225:15 235:11242:5,13,19 243:11244:6,17,20 245:7,15246:5 248:4 249:7250:2 251:3 254:1,4255:13 256:5,7,7,8,10258:4,9,16,17,18259:4 260:22 261:7261:22 262:2,10,21263:4,8,9,10 264:15265:1,2,5,5,7,10,11265:13,16 267:17,20267:22 268:13 269:4269:5,6,11,18 270:1

271:3 272:4,7,10,18274:8,16 279:8,12,14280:22 281:7,9 282:4282:5,12,14,16 283:5283:7,9,22 284:4,9,10284:14,15,18,20285:3 286:3 287:16288:1,3,13,15 289:1289:14,15,19 290:3

knowing 200:20 251:21258:20 264:8

knowledge 73:5known 9:9 127:6

244:22knows 8:13 75:2

Llabeling 8:18,18 9:14lack 73:5 250:10lacking 254:10lactating 136:13 206:2

272:16lactation 2:8 12:9,11,12

12:14 18:14 29:186:11 87:15,19 88:1588:18 89:9 104:6,8106:1,1,4,5,8 107:8111:3,10 112:1,15114:3 116:10,13117:16 119:6,13120:9 126:5,13,14127:8 129:12 135:8136:4 137:9,13 139:2139:12 141:7,9142:14,16 143:17,19145:5,7 205:14241:11 272:5,19273:9 275:16

laid 159:19lakes 134:21language 22:1 102:11

102:12 103:8,10104:12 141:11,16142:9,14 149:6,11,16150:5,11 173:3,10196:22 289:9

large 27:20 36:16 68:2281:17 101:21 177:14179:1 181:17 187:2189:2 220:14 221:5221:19,21 222:5235:20 258:8

larger 9:6 219:12287:20

largest 221:16lastly 34:11 40:1 71:16

74:2 246:21late 102:10 158:4


310

laughter 174:13 274:5layout 92:15LD 1:18LDL 226:19,21Lead 3:4leads 268:2learn 16:20learned 224:3learning 26:10,12leave 265:3 279:4led 7:14 160:20 187:20

267:10left 250:9 256:6legitimately 174:1legumes 122:12 123:16

124:13Leidy 1:16 175:4

280:19lend 163:19length 64:17 179:2

225:1lesser 56:17 80:12let’s 84:18 85:15 175:8

175:10,13 212:12264:4 290:9

letters 36:12leukemia 227:9level 92:20 96:19,19

112:10 116:1 168:4189:4 202:13 207:2211:1 253:17 263:3

levels 38:3 95:16 98:2098:22 115:20 117:11118:12 119:17 192:11219:18 231:5 263:11

LGA 189:4 246:12life 56:7 57:2,14 59:9

61:1,14 63:16 79:1983:22 162:11 214:16217:9,20 221:4 222:8222:16,22 223:5224:13 240:7 265:12272:7,8 273:7,11,13275:8,9 277:18,18279:6,7 283:6 284:12284:13 285:9,13290:17,21

lifespan 9:20,22lightly 244:4liked 291:5limit 140:21 173:18

223:19limitation 109:13

124:16limitations 40:17

158:13 160:20 201:3225:15

limited 45:18 46:18

48:4 49:14 50:17 51:951:19,22 56:20 57:1559:17,18 61:4,13 62:463:14 64:19 65:1566:4,10 98:3 104:10104:22 116:11,14117:15 118:3 122:8122:19,20 123:10124:8 151:6 165:11200:19,22 204:3281:3

limiting 70:8limits 242:5Linda 1:19 2:10 4:13

134:2,6 162:15 165:3174:7

line 9:2 174:8,11lines 165:6 245:16

255:7 279:18link 19:20 44:8 53:13

160:6 291:12linked 238:14 247:7

250:16 273:19 283:13links 4:5,9,10 262:21lipids 48:10 49:8

157:18 158:2 196:18liquids 34:14list 7:21,22 8:4 16:16,16

85:7 161:20 177:20177:22 248:16 254:14263:14 288:21,22

listed 32:21 46:4 52:1166:15 71:10,21 100:2179:8 184:8 238:13238:16 248:11 266:11

listen 159:12listening 17:7 174:12lists 273:2listserv 15:22literature 23:22 31:21

36:9,11,13,16,19,2144:14 53:18 68:2270:22 71:4,6 82:19108:19 130:15 137:5156:22 166:8 180:6184:20 191:21 201:22202:10 203:1 259:3265:22 283:9 286:13

little 4:22 30:20 79:1,786:6 155:9 165:12168:16 173:9 180:22187:12,17,19 193:2197:1 201:7 210:17218:5,20 225:13241:4 258:5 266:21269:13 273:14 276:7281:19 288:6

live 134:21

live-streamed 4:1,3liver 231:22 232:6,8,15

232:19 233:1 255:8255:18 264:21 269:7

locate 43:22locations 5:13long 35:14,15 77:7

84:12 116:17 160:4,8241:19 250:20 254:14273:2

long-chain 57:10long-term 32:14 43:2

47:11 50:3 54:22longer 46:9,14 47:1,6

48:13 49:7,14 51:6,18longer-term 84:13 93:7longitudinal 217:10look 18:6 21:3 73:21

82:2,10 96:7 102:20106:5,17 122:2127:17 129:9 131:2,8140:3,4 160:11 161:2163:18 164:2,5165:17,21 166:18168:1 171:3 174:16180:6,21 181:19203:13 204:21 211:16212:11 213:10 214:14214:15 217:13 218:17218:20 243:1 244:12245:9,13 247:9,9251:12 256:11 260:9263:21 267:21 281:17281:20 282:4,9 283:1283:6 285:15 291:1,3

looked 11:2 88:16 91:491:5,8 96:21 97:13100:14 102:4,5,22103:22 106:17,18107:22 108:1,15114:14 115:9 118:10128:3 131:6 141:10158:6 161:8,18 164:1170:22 187:2,5 188:5188:7,12 191:3202:14 214:2 236:15236:20 240:7 242:9252:9 256:15 263:18263:20 278:2 285:11

looking 22:21 29:1282:11,21 84:1 91:16100:4 102:9 106:3,13108:19 112:4,22113:22 120:15 129:7133:19 135:21 140:15149:19 158:1 161:9178:4,11,13,21180:20 182:15 183:13

195:18 196:1 202:18203:3 209:15,16,17211:7,13 215:9 216:5217:18 219:3,5,15,22220:16 221:1,14,20222:6,11,14 224:13224:16 225:18 227:17229:6,18 232:3 241:6244:9 248:11 251:12256:18 259:13 260:19267:5 268:19 271:9274:20 275:10 282:18285:9 286:10,21291:22 292:6

looks 11:22lose 279:3loss 89:11 91:18 126:13

229:15lost 215:20lot 9:15 10:6 12:22 13:1

24:15 26:18 29:1534:2 62:15 72:14109:14 113:18 131:21132:7 135:5 164:19169:1 192:18 224:7236:4 242:14 243:11246:20 248:1,3 254:6255:13 256:14 259:11260:11 267:16 272:13272:20 274:1 276:1277:11 279:21 281:3281:22 282:15 286:13289:6 290:5 291:14

lots 273:6loud 86:2love 224:10low 22:22 37:13 96:2,19

97:8 99:2,3 102:14184:10 187:5 188:22190:4 191:14 225:2,3225:5 226:20 227:3229:20 230:6,8,11,20235:11,13 237:13238:12 239:11,13,14240:11 244:5,13,18245:4 246:10 247:7248:21 253:3,14,15285:20 290:3

low- 178:12 180:7,11181:10,13 184:21185:2,12 186:3

low-fat 222:18lower 59:15 60:14 65:7

77:5 96:19 97:1698:22 103:9,16104:12 105:2 107:16107:16 114:12,15122:12 123:2,16


311

124:10,14 155:1164:16 185:5,14186:19,22 187:6188:14 189:20 192:8212:17 218:10 228:8231:4 261:18 262:1,9

lowest 213:13 226:10231:6 233:1

lumped 279:14lunch 4:11 132:6,21,22

278:4 281:18lung 233:9Lydia 1:13 263:6

Mmacronutrient 114:13

115:22 116:5 117:11117:17 118:7 119:5,9

macronutrients 113:2magnesium 210:12

216:1 239:13,14240:19

magnitude 60:15main 9:21 208:17,21

220:20 261:17maintain 56:5maintained 168:5major 63:12 88:12

102:16majority 37:16 38:17

140:11 141:14 142:21147:5,16 166:8208:14

making 17:16 81:1,4male 212:22 233:5males 22:8 209:22

216:11 217:2 226:16227:4 232:21

mammary 78:6manage 243:7mandate 13:10manner 134:20 178:19manual 150:22 151:3manuscripts 121:15marathon 218:17March 14:13 15:8 26:6

36:15 44:15 92:1126:17 281:15

marine 134:20markers 39:21 79:4

81:15 82:15 83:1196:2

market 34:5 41:7mass 235:11,13materials 24:12maternal 77:3 89:8,13

90:2,7 91:21 101:22106:14 114:2 115:19

115:22 116:6,12117:10,16 118:7,14119:5,12,16 121:9126:14 139:11,20141:21 143:4 144:14179:7 272:9

math 90:16matter 172:4 285:6,6matters 285:5Mattes 1:17 72:13,13

73:17 75:12 76:1177:15 80:16,18 127:5127:6 128:20 166:20166:20 167:11,18169:2,18,20 175:4243:21 251:10,10252:7 278:7 279:19

mature 113:1Mayer-Davis 1:17 2:12

82:4,7,14 175:1,2,15183:12 200:7 201:11204:4 256:1 257:4,6257:10,15 259:1,6268:19,21 287:9,10

MCV 111:10MD 1:12,12,13,16,18,19

1:20 2:16meal 251:17meals 146:12,13,17,17

148:6 149:11 150:21150:21 151:2,17,18152:20,21 154:4157:10 251:13

mean 76:18 83:15106:19 108:7 164:12164:13,15,16 207:6211:19 219:13 220:1220:17 221:1 228:21238:2 243:11 251:16251:18 253:22 258:3270:21 271:20 278:20286:14

meaning 194:21means 4:2 72:17

195:14 217:18meant 117:20 247:12measure 110:3 136:20

168:22 253:4measured 83:13 136:14

139:21 145:19 156:19156:21 157:17 158:8168:17 182:8 252:19255:10

measurement 144:10154:9 182:9 184:14

measurements 142:4196:16

measures 66:9 81:21

83:11 110:13 140:15168:20 169:1,9 232:1

measuring 74:20116:19,21

meat 65:7,7,13 115:14124:14 146:12,17148:5 149:11 150:21151:18 152:21

meats 54:11 56:4,2263:13 122:12 123:17124:15

mechanism 73:6 82:18medical 8:19medications 179:13

196:18 243:7,16,17267:14

Mediterranean 211:15257:7,18

meet 13:10 28:4 33:2143:13 53:5 129:22209:12 237:19 273:22

meeting 1:3,9 3:10,113:22 4:3,17 6:6 14:1,614:7,14,19 15:2,4,715:15 16:3,5 18:2,719:5,8 26:6,6 27:728:5,6,12 30:21 31:234:19 78:4 87:7 90:591:20 94:1 126:16130:7 134:12 136:11137:21 138:3,19139:8 145:16,17156:16 208:8 240:17241:5,7 261:10270:11 271:8 292:9

meetings 4:1 13:2114:2,4 16:7 18:1120:5 21:17 25:14,2129:20

Megan 2:13member 1:12,13,13,14

1:14,15,15,16,16,171:17,18,18,19,19,201:20 31:13 72:1373:15,17 74:8 75:1275:14 76:11,14,2177:11,15,18 79:12,1580:16,18 81:3,12 82:482:13,14,20 83:3,8,1884:8,11 85:2 87:1688:1 121:3 127:5,14128:1,12,20 129:1,5,6130:5 134:4 159:18161:1 162:4,12,14163:4,21 164:9,19165:2,16 166:3,12,15166:20 167:10,11,13167:18 168:9 169:2,6

169:10,18,19,20170:7,14,15 171:5,6,8171:9,12,14 172:14173:7,8 174:7,17175:2,15 183:12200:7,11 201:11204:4,17 213:1 222:2242:2,8,12,13 243:4,9243:21 244:2,20245:15 246:1,7,13,18247:3,5,6,11,13,16,18248:8,13,15,19 249:2249:5,6,8,10,12 250:5250:8,9,14,17,20251:1,5,8,10 252:2,7252:8,12,18,20,21,22253:1,7,20,21 254:1,3254:5,13,22 255:3,6255:10,11,12,16256:1,13 257:4,5,6,9257:10,12,15,16,21258:1,2,13,15,16259:1,5,6,7,15 261:7261:12 263:6,13,18264:13 265:19 266:8266:19 267:2 268:5,7268:8,9,10,11,12,17268:18,19 270:21271:20 273:7 274:3,6274:12 275:7 276:3278:2,7 279:6 280:6280:19 283:17 285:8286:6,19 287:9288:20

members 1:11 4:1217:4 28:1,1 30:10,1131:16 71:19 88:3126:19 159:9 199:11

memorized 129:10men 228:20 229:4,11

230:7,18,20 231:12232:10,11,13,14,22233:7,12 234:20235:1

mention 59:4 60:562:17 113:14 279:18

mentioned 34:22 38:1744:3 53:2 68:18 71:1593:22 120:6,19 121:7122:1,2 126:1 162:5169:12 184:3 191:20192:13,22 197:3198:10 199:21 201:2201:3 210:3 219:9222:7 224:1 239:7241:9 256:2 266:14276:5 279:19 291:6

mentioning 165:19


312

menu 8:18 280:9mercury 170:11 172:7messages 15:22met 1:7 3:18 34:7 37:1

44:17,22 45:5 47:1650:5,10,13 54:5,1055:4,22 58:5,8 64:764:10 67:3,4 68:1,3139:10 140:9 141:13142:20 144:1 145:22146:6

metabolic 49:9,17231:8,11,14,15,18,21264:18 266:14

method 259:13methodological 40:15

158:13methodology 125:16methods 140:20 192:19

257:13 258:10methyltetrahydrofolate

107:22Mexican-Americans

226:9,22 229:3231:20

Mexico 107:13micrograms 107:20

109:5micronutrient 32:13,18

33:6 35:5 37:3 42:152:11 54:4,18 55:1255:22 57:18 83:2189:3 90:11 91:18106:15 107:2,8 126:4

micronutrients 57:14microphone 133:5,7microphone’s 87:17mid 203:2middle 16:13middle-aged 220:13midst 176:13milestones 32:17 33:2

52:13 67:10,21 99:13100:8 104:4 106:6126:5

milk 32:11,22 33:13,1333:15,15,17,18 34:1335:3,9,9,12,14,15,1635:18 36:2,4,18 37:237:18,21 38:1,19,1939:2,3,5,15,20,2140:2,8,10,22 41:9,1141:14,16,19,22 42:442:10,16,22 44:16,2145:3,9,11,15,20 46:146:10,14,15,19 47:1,747:14,19,21 48:4,5,948:14,16 49:2,8,16

50:1,6,9,12,16,19,2251:3,6,7,10,18 52:255:18 62:6,11 68:1969:6,14 71:11 74:1474:16,18,20 77:1,1477:22 78:5,16 88:2289:10 90:4,20 112:1112:14,16,20,20113:1,5,7,7,17,22114:3 115:10,20116:1,4,11,20 117:1118:8,12 119:3,6,14119:17,20 176:10178:5,14 180:7 186:8186:9,11,18,19,21187:5,10 200:12202:22 207:22,22215:18 216:2,18218:13 221:15,20222:18 223:6

Milk-Feeding 44:7milligram 109:18milligrams 94:21

107:21mind 154:6 206:20

210:19 251:4 266:5280:22

minerals 83:12 113:5minimize 87:8minor 199:19 289:4minority 123:2 192:9

262:7minute 248:14 259:22minutes 14:5 86:8mirrored 273:20missed 282:8missing 184:14missions 6:1mixed 55:16 97:15

117:12 130:15 183:15183:16 207:11 214:19215:7 220:21

mixed-fed 36:5 42:16modeling 2:13 10:20

18:18 19:12 27:1729:3 204:13 205:20241:14

models 274:17,22278:13

moderate 41:10 45:1046:12 48:14 51:454:19 57:8 58:1260:22 64:12 65:6,1898:19 111:2 141:1,4142:7,10 148:22149:4 150:9,13165:10 166:10 169:13184:11

moderators 20:22modified 44:1modify 76:8moment 177:13 182:12

192:13 269:6moms 77:3 115:2Monday 15:3 16:3money 268:14,14months 2:6 12:1 18:15

31:12 36:8,14 41:2044:6 47:3 53:11 54:2154:21 59:10 61:2,1563:17 64:14,15,2165:3 75:10 83:1588:16 99:21 108:5114:9 115:7,8 140:14141:17 144:16 158:1162:7,8 224:21

morning 3:3 4:5 292:3mortality 11:18,20

158:6,7 177:1 193:18194:3,4,8,10 195:21199:4 227:10 232:11232:12,12,14,22233:8,10,13,14264:20 269:7

mother 89:3 90:1199:12

mother’s 33:13mothers 101:9 102:7

103:11 107:16 114:5115:12,13 225:4275:13,17

motivated 128:7motor 151:1,4move 13:14 17:18

26:11 58:1 63:7 159:3174:21 199:6 272:22

moved 18:4movement 103:22

105:15 142:18 143:1143:6,13,17 150:15151:10

moving 23:17,20 27:1347:11 52:8 64:5 70:20145:8 152:15 153:21156:10 184:20 186:6189:10 193:15 211:2228:12 233:3

MPH 1:13,14,17,18,201:20 2:13

MSPH 2:12MUFAs 117:12,14,19multiple 203:7 246:19

271:4multistory 86:17multivitamin 130:22

131:4,8

muscle 234:14,16,19240:13 253:11,15

mushrooms 115:14

Nn 108:10 130:9n’s 95:21Naimi 1:18 165:2,2

175:4 204:19 255:16name 3:4 72:12 87:17names 18:20national 7:8 9:7 232:17

243:13 257:12 259:10Native 234:7Natives 230:22 232:8

234:7naturally 221:11nature 4:6 28:16nearly 27:14 95:7 115:1necessarily 12:10

85:11 130:9 203:19211:14 213:16 217:15245:18 269:10

necessary 81:2 269:10need 23:3 30:3 32:5

55:9 70:14 80:20 85:985:16 86:6,9 87:21161:12 163:22 166:18167:14 173:21 175:11175:12 182:12 197:22254:10 260:16 263:20267:7 274:8 279:13281:7 284:11 289:7289:20,20 291:7,22

needed 57:15 100:8112:21 131:10 265:18

needs 84:22 85:6 129:2198:3 264:11 273:1,2279:10

negative 167:1 169:22neither 185:7 193:8NESR 19:12 23:16 25:5

27:9 31:20 43:4,1744:5,13 52:17 53:9,1889:14 90:22 91:15111:21 120:5 134:8,8136:6 164:2 175:6177:10 193:19 198:19202:2

NESR’s 27:7 145:12156:11

nested 100:22 102:12103:13 105:5

net 237:3 238:4neurobehavioral 106:6neurocognitive 11:7

52:13 89:2,10 90:1091:19 99:14 100:15


313

101:3 104:4 126:6134:17 135:8,11,13135:16 136:5 137:7137:13,18 139:2,12145:11 146:3 147:1155:18,22 156:10162:17 199:8

never 37:17,21 38:1839:14 40:7 41:9,11,1941:22 44:16 45:8,1045:15,19 46:1 47:1448:3,4,9 50:6,15,1850:22 73:3 76:2277:14,22 78:10 195:6197:12,17,18 198:5

nevertheless 218:5new 6:18 12:21 13:4,10

26:11 29:19 33:343:20 70:14 90:1999:15 106:12 111:21120:20 193:20 261:2289:14,15

newborn 55:14NHANES 27:15 206:12

227:16 234:16 252:16254:6,18 256:3286:10

nice 130:3 165:3 281:16nicely 159:19nine 44:4 54:4 55:3

102:8 107:3,10,20110:4,7 115:7 142:19143:22 148:10 292:3

nine-hole 150:18no-calorie 178:13 180:7

180:11 181:10,13184:21 185:2,12186:3

nominated 264:17nominations 5:9non-alcohol 176:2non-alcoholic 175:20

176:3 177:4non-controlled 97:10non-dominant 151:5non-drinker 197:12non-Hispanic 213:6,12

225:4 226:7,16,21227:2,4 228:5 229:4229:13 230:15,20234:4 235:3,5,7

non-Hispanics 232:7non-pregnant 128:4non-randomized 94:5

95:5 96:22 98:11non-significant 144:4non-U.S 49:19non-vegetarian 115:11

118:17non-white 41:3nonalcoholic 255:8normal 48:6 94:17

200:3,5Northern 147:17Norway 101:21note 4:4 7:12 14:16

25:19 26:19 29:1435:17 38:20 136:19195:12 287:10

noted 13:22 28:8 30:436:11 89:14 90:12126:9 137:9 162:22203:5,5 238:7

notes 291:19notice 195:6noting 124:15 200:1novel 38:2Novotny 1:18 173:8,8

175:5 266:8 274:12nucleotides 34:4null 140:12 141:15

142:22 148:4 150:22151:21 152:21 166:4166:9

number 5:11 7:6,18 9:59:10 10:7,9,11 16:921:10 28:5 31:19 37:937:10 39:10 40:1284:17 90:16 112:19153:3 154:8 155:8158:12 177:14 179:21194:5,8,13,16,21216:14 238:5 242:15

number-one 220:7numbers 27:12 179:17

198:14 246:21 255:2287:12

nutrient 9:8 38:8 70:670:18 71:2 131:3205:16 206:14 237:10237:16 239:16,18240:4 241:7 244:9,13246:4 248:20,20250:3,3,11,15 259:17259:18 261:6 283:8

nutrients 8:17 33:434:15 39:9 56:1969:20 70:9,15 71:1488:13,18 90:15 92:14119:18 126:8 205:16207:1 209:17 210:10210:14,18 211:20223:5,13,16,18 236:3236:5,7,10,12 237:22238:5,6,13 240:5,18241:11 243:2 244:22

245:4,9 246:22250:12 252:1 259:13260:20 263:8,14273:18,21 283:2284:5 285:6 288:11

nutrition 1:8 3:5,5,135:3 7:14 8:13,19 9:1,69:17 11:8 43:10 53:1121:8 268:4,15275:12 279:10 283:12

nutrition-related223:22

Nutritionist 3:4nuts 59:7,16,20 60:3

115:14 122:11 123:15124:13

Oo’clock 132:17,18

292:3OBBAGY 84:7,10obesity 11:3 22:16

64:22 65:14 66:4,7,1669:2,15 74:5 81:14176:5,21 199:1225:21 226:3,7,10,17227:5,7 228:14,15,17228:18,19,20 229:2234:11,11 254:16,19255:4,7 266:5 267:1268:22 276:22 277:4284:21

obesity-related 266:21268:22 276:21

objective 127:12obscure 259:4observation 278:6observational 44:20

45:1 46:13 50:17 51:451:19 62:3,19 63:8,1463:20 67:16 165:7197:13

obvious 225:15obviously 20:19 22:13

29:4 89:18 128:5occasion 194:22

252:12,13occur 7:9occurrence 82:11October 137:20 138:3odds 64:22 155:1ODPHP 7:21Off-mic 129:4 168:14

200:6 255:22offers 54:22offhand 128:8Office 7:15officer 3:7

oftentimes 113:16oh 71:5 82:20 93:18

175:11oil 77:3 101:16 136:22oils 122:12oily 147:4 157:11 158:3okay 3:3 63:7 64:5

68:13 73:12 77:1882:6 83:3 87:16132:16 199:13 204:7207:16 209:13 211:15212:2 213:1 217:8219:2 222:13 223:21236:1 242:12,16246:7 248:9,15,19249:2,13 250:5,17,19251:9

old 73:9older 11:12,16 12:5

101:11 145:20 195:14195:22 206:1 207:7208:12 209:8,14,17210:4 214:5 218:2,6,7219:13 220:5,13,19220:22 221:6 223:1223:11 229:9,17230:2,12 231:16,17233:8,11,11,16 234:3234:13,15,22 239:8,9240:2,11 253:14263:10 277:14 279:12

oligosaccharides113:5 119:20

omega-3 76:18 136:22omega-3s 88:20omega-6 76:17once 24:19 133:16

168:18 202:7 218:12one-plus 209:20ones 83:4 85:12 93:11

115:8 121:6 137:19165:6 245:21 247:20248:17 262:22 271:15

ongoing 126:1online 4:7 24:12 26:9

206:19oolong 188:6open 13:22 14:12,14

30:6 72:10 113:20132:8

opened 14:13opening 2:2 28:20

133:10opinions 5:16opportunity 14:7,10

15:9 30:21 72:7 174:9269:13 270:14 271:21277:19 280:12,16


314

290:22 291:16opposed 165:11 168:2opposite 124:19 183:20opted 180:14option 254:4oral 14:8orange 16:14order 2:2 122:3 274:20Organization 69:10orient 135:2origin 22:3original 193:5originally 172:6,12osteoporosis 234:14

235:8,10,12ounce-equivalents

208:13outcome 10:22 11:20

22:20 32:12,16 33:544:19 50:3 52:10 58:268:19 71:14 77:10,2083:13,18,20 96:1099:19 102:16 110:3121:9,11 136:14137:18 140:6 142:3143:8 144:16 145:19149:21 152:6 153:4153:14 154:10 155:18162:8 163:17 168:2176:2 179:5 182:10184:1,14 186:20189:1 190:22 194:10195:20 199:5,20227:8 238:15 246:9247:14 249:1 250:16282:11

outcomes 11:1,2,6,1312:13 13:3 20:19,2023:7 32:14 37:3 38:839:8 42:1 43:2 45:946:4,11 47:5,10,12,1547:17,22 48:12 49:1250:2 51:1,16 52:754:3 62:2,16 63:764:4,6 65:17 66:2167:1 69:1,15 71:1381:17 83:6,10 85:1585:17,18 88:21 89:6,990:15 91:16 93:5,895:3 99:18 100:1101:3,10,18 102:11103:7 106:17,21108:6,7 109:9 110:18112:19 114:18,19116:19 120:16 121:12124:4 125:11,20127:10 134:17 135:11135:13,15,16,18

136:1 137:7,18138:11,17,21 139:13139:18 144:10,12146:19 147:7,15154:17 156:19,20158:1,6,8 159:22162:11,17 176:20178:20 181:15 182:9185:9 186:5,13,16187:11 188:12 189:8189:18 190:11 191:7191:9,13,18 193:9198:17 199:3,7224:19 226:14 229:19231:7 234:13 236:18239:20 243:6 255:9262:5,6 265:21 266:3271:4 279:16 283:13291:3

outline 6:1,22 27:18outlines 6:11outs 31:4outside 3:18 213:4

223:13overall 115:9 190:19

228:12 229:6,14260:16 271:17

overarching 53:21overconsumed 210:9

210:22 222:7 237:3,9240:1

overconsumption238:18

overlap 35:20overview 14:22 17:20

20:8 88:9 175:16177:5

overweight 64:22 65:1466:4,16 69:3 81:14176:5,21 199:1224:21 225:20 228:14228:16 266:4

overweight/obesity266:10

PP-R-O-C-E-E-D-I-N-G-S

3:1p.m 14:16 28:14 292:9PABA 127:18Pacific 234:7page 16:14palatability 278:20

290:1panel 69:8Pannucci 204:20paper 75:14 76:5 82:2

121:10 184:15

papers 43:9 52:22 83:791:5,10

paragraphs 77:7parameter 172:3pared 179:18parent 19:2parental 144:11 153:5parentheses 200:3

228:16parenthesis 239:1parity 179:13part 7:7 11:9 26:12 44:5

53:10 74:12 91:1119:18 120:6 128:14166:15 170:11 201:19205:18 207:10 258:9260:12 262:17,19266:3 269:2,15281:11 282:20 286:9289:11

participant 109:7,15182:19

participants 22:7,11,1322:14,18,20 23:1328:11 41:4 101:7146:16 184:12 197:1198:11

particular 11:11 24:459:5 86:4 134:10135:1 136:7,19 145:9145:13,17 146:16147:9 156:12,14157:16 158:8 159:13175:19 176:12 177:6178:6,21 180:13183:22 184:16 185:22187:21 197:3 198:13203:7 223:6 240:8261:20 262:8 265:17270:12 271:12 279:15279:16

particularly 57:2,1084:21 98:17 132:10147:18 163:12 187:16190:15 232:13 234:11240:18 243:10 265:12269:4 283:7 287:3

partners 7:17,22 9:5pass 80:11 173:15,21pasta 215:6path 250:2pathway 201:7,19

250:4 266:16pattern 2:13 10:19

18:18 19:11 27:1729:2,8 112:2,9,10114:2 194:20 195:3196:4,8,10 204:13

205:19 207:19 241:14256:19 284:11

patterning 282:21patterns 10:8,12 18:14

63:22 66:19 89:5,890:18,20 91:17111:21,22 112:7114:11 115:9,13,19116:10 117:10,16118:15,18,21 119:3,8119:9,12,17 120:11120:15 121:18 122:7122:10,18,22 123:5123:11,14,20 124:5,9124:12,21 125:3,10125:19 126:3,4,11,12211:2,11,12,14214:15 217:9,14220:7 241:8 256:5,7256:12,15,21 257:1257:13 258:4,10,21277:13,15 281:18283:18,22 284:13288:3,9,10,17 290:16290:16,19 291:13

Pause 175:14 183:11pay 79:6 279:4paying 277:8 278:9peanut 59:7,9,12,14,20

60:3 73:8,18 79:18peanuts 59:11peas 219:8pediatrician 277:11peer 26:9 159:1 226:17peer-review 25:22 26:7

71:17peer-reviewed 22:1

26:3peg 150:19penalized 203:20people 4:16 20:1 73:10

73:21 80:21 85:1388:10 129:14 133:4,7195:8 202:2 204:18243:12,15,16 244:10246:1 261:14 267:13273:22 274:1 277:21284:18 289:10 290:6290:7

percent 102:14 107:18116:3 118:18 161:16167:14 192:3 207:4207:12 208:7 209:21209:21,22 210:7,7211:19 214:22 215:11215:15,16,21,22216:2,4,17,22 217:2,4219:9,20 224:22


315

225:3,9,20,21,21226:15,19,20 227:15227:19,20 228:14229:8,8,15,16,20,20229:21,22,22 231:9231:10,11,17 232:2,4232:4 234:2,5,12,15234:18,21 235:6,7,9235:10 237:5 238:4239:2,3 244:4 247:10249:18

percentages 227:1perfect 129:5 248:9

257:20 260:2performance 12:2

100:5 104:1 105:16138:14 153:21 154:14

performed 105:22period 14:12 30:5 59:21

62:12 65:9 66:7,19131:22 194:6 292:5

periods 117:4 277:20277:22 279:9,11

permitted 7:10person 4:14,18 14:11perspective 265:2

274:11perspectives 280:13,14pertaining 139:5pertinent 120:8pharmaceutical 102:18phase 13:14 23:18phases 102:4PhD 1:11,13,13,14,14

1:15,15,16,17,17,181:19,20 2:3,4,7,9,102:12,13,15

phone 134:6phosphorous 240:19Phosphorus 239:12physical 93:15 103:22

105:15 142:18 143:2143:6,13,17 150:16151:10 196:5

physiological 78:17pick 82:5 270:20 279:1picture 9:17pie 216:5piece 176:12 275:15,19

275:21 285:3pieces 9:15 10:14pilot 123:7pizza 214:20 219:12place 29:11 31:2 173:9

236:19 287:15plain 180:9 190:21

191:2,17plan 19:14 25:2 91:19

126:16plant 218:9plasma 106:18 108:5

108:21 110:5,18111:5

plate 251:11plausibility 73:6 78:12plausible 160:4play 288:16please 16:2 27:5 43:12

53:3 75:4 86:19 87:2087:22 133:6

pleased 31:14pleasure 3:9 87:18

204:17plot 212:22 213:1,2,8

217:21 218:15plus 184:22point 4:18 9:14 31:18

75:8 79:13 81:4 109:8128:21 129:1 130:6130:13 132:10 165:17166:2,16 169:7171:12 173:7 204:2206:13,16 211:5212:18 221:13 235:14253:9,13 258:14265:4 274:15 277:14277:19 280:21 282:7283:5 285:2 288:5291:21

pointed 133:4points 84:14 166:18

212:3,13,15 224:11263:4

policies 8:10,19 278:4policy 3:6 7:15 269:21

274:21polyunsaturated 57:11

75:22 136:22poor 192:7 275:12popular 289:6population 10:17 11:12

11:14 12:2,3 22:5,660:9 73:13 80:22 93:197:11 99:18 112:13127:9 179:3 195:13208:14 210:6,14211:18 215:2,4 238:6249:19,19 263:3283:10,15 285:12

populations 13:4 192:9217:16 241:12 262:7262:13 277:21

portfolios 32:1portions 117:19pose 237:22 239:5poses 237:16

positive 66:11 73:1976:2 110:4,7,9 116:2116:2 140:12 149:14154:3,22 160:22162:17 166:22 200:14

positively 110:17 111:4111:5

possibility 76:16 78:5possible 8:14 73:1

76:11 171:10 236:21possibly 161:6post 26:8posted 7:22 120:20

193:21 194:1 206:19posting 19:20,21postnatal 55:15postpartum 89:11

91:18 108:4 109:21112:22 114:9 115:7,8126:13

potassium 210:13216:1 221:20 239:21260:22,22 261:3,5,11261:13,18 262:1,4,10262:11,13,19 263:2

potato 115:16potatoes 284:8potential 8:9,15 67:12

197:15 237:11 261:17267:8 268:3 274:18282:15

powered 40:13practical 193:13practice 33:22practices 44:7 100:12pre 95:10pre-conception 108:3

109:6pre-pregnancy 94:17

98:8precise 110:21precision 98:16 104:19

105:7 116:16 117:7118:4

prediabetes 51:1,1552:6 79:2 227:13231:10,13 267:15

predominantly 112:17148:4 150:22

preeclampsia 93:8 95:295:12 96:10,15 97:3,697:12,17,22 98:8122:15

preferred 87:6pregnancy 2:8 12:8,10

12:12,14 18:14 28:2236:14 44:6 53:1086:11 87:15,19 88:15

88:17 89:1,6,9 90:991:1 92:5 93:2,494:10 95:12 96:1497:2 98:4,6,21 99:2,899:9,13 101:2 102:22103:1,5,12,15 104:3,8104:11 105:2,12106:1,8,11 107:8108:3 110:17 111:9111:17 120:7,9,11,12120:15 121:3,11,18122:10,14 123:1,5,12123:21,22 124:1,5,10124:21 125:3,10,20126:3,12,14 127:7128:5,13,16 129:12135:8 136:4 137:8,13138:6,14 139:2,17140:13 141:2,5,16,22142:8,11 143:1,13,19145:1,7 162:18168:13,18 177:8179:4,16 181:4183:13 186:4,7187:10 189:8 190:11190:22 191:18,22192:21 205:14 241:10272:5,19 273:9275:15

pregnancy-induced233:20

pregnant 128:4 136:13206:2 233:18 272:15

prelude 82:16premature 242:11premenopausal 240:9prepare 27:18prepared 33:21preparing 31:21,22prescribed 102:21

127:13prescriptions 102:19present 1:11 34:21

35:21 68:15 79:587:18 91:20 94:10126:16 138:20

presentation 88:21135:4 165:4 180:14199:19 241:19 280:8

presentations 14:520:12 184:3

presented 6:6 17:2120:4,9 24:21 25:827:6 29:19 33:9 34:1872:9 90:5 91:22 94:1117:22 133:12,21137:19 138:2,18178:22 253:8 264:9


316

presenting 23:19,2024:7,17 32:2 53:790:7,19 134:13176:11 177:2,3 205:1206:4,13,17,22 260:7285:13

presiding 1:9pressure 48:6,17 49:2

49:16 93:6 95:2157:17 158:2 196:17262:2,16

presumably 80:11preterm 22:22 124:10

124:11,14,22 246:12246:14

pretty 13:15 84:12160:18 207:2 219:18222:9 257:20

prevalence 65:14 66:3223:22 225:2,5,9,20225:22 226:2,3,7,8,10226:14,19,20,21227:3,7,15,18 228:1,2228:5,6,7,10,13,14,16228:17,19 229:2,3,7229:10,12,13,15230:5,7,8,11,13,15,17230:19,21 231:1,3,6231:12,15,18,20232:5,8,10,18 234:2,9234:12,20 235:4,6239:1 240:17 243:12245:12 247:8 249:17253:3,8,15 262:2,9263:11 272:1 276:22

prevalences 243:2prevalent 231:9prevent 56:6 59:14prevention 7:16 267:12

267:16previous 4:1 10:3,6,15

11:1 12:9,20 13:1620:4 23:10 70:10 85:490:22 95:12 209:16237:7 272:6 284:2

previously 6:17 13:533:10 53:2 97:11113:20 138:2 238:14

primarily 22:7 60:7118:1 139:18,21187:15 195:14,16,22205:22 207:10 208:4208:9 219:16 222:8243:5

primary 91:7 96:9149:13 151:19 194:18195:4,10 201:15261:14 278:22

prior 34:4 35:18 45:488:16 198:9

prioritize 8:5 13:18 28:369:22 86:3

prioritizing 68:16 84:2185:8 90:13 126:2198:15 199:4

priority 86:1 270:17pro 169:21probably 60:12 116:19

167:11 193:1 201:20217:4 246:16 248:19255:3 263:12 264:11282:17

problem 244:5 248:22249:4,20 274:15

problems 197:15201:22 202:10

proceed 18:11proceeding 180:18

287:16process 6:18 7:8,11,14

7:20 12:1 17:9 25:2226:6,7,12 71:17 89:2290:13 129:17 133:14167:16 177:11 182:18193:19

processed 123:16124:15

produced 100:19113:12

products 62:6,11 92:10profiles 57:10programs 8:9 268:4progress 235:18progressing 30:3project 36:14 44:6

53:11 70:10 90:2191:2 120:7 257:14258:11

Promotion 3:6 7:15,1648:20

proportion 36:4 42:1674:17 210:5 214:8,12220:21

proportionate 75:6proportions 112:4

116:1,5 117:11,21118:2,8 220:8

proposing 237:15prospective 49:5 63:2

63:22 94:6 95:2097:14 98:12 100:21101:20 103:9 104:15104:21 107:3 108:9113:19 123:6 124:6125:5 139:16 140:9141:13 142:19 144:1

146:5,21 147:10148:1,9 149:9,13151:21 154:1,19,21155:4 157:20 160:12160:18 161:6,9163:13 167:21 172:4172:11 181:6 186:10188:2 189:13 191:3

prostate 233:5,7protective 123:14

124:11 173:13protein 118:12 119:7

208:9 209:12 210:2,3220:16,17,22 239:7240:12,19 253:14263:10

proteins 113:6 119:21218:9

proteinuria 93:7 95:3protocol 19:14,14

24:22 69:17 130:21193:20

protocols 16:15 19:1919:21 20:4 21:3 23:1423:20 29:19,21 30:243:5 52:18 120:20134:9 136:19 268:5

proud 259:11provide 5:16 9:3 14:8

14:10 15:8,19 19:226:5 28:7 34:15 37:1144:3 88:9 180:14200:9

provided 20:1 24:1134:14 37:6 44:9 157:9157:13

provider 80:4provides 178:15 192:3providing 181:1proxy 225:8,14public 1:3,9 5:9 7:19

8:1,3,8,14 9:4 13:2214:11,11 15:11 18:1019:5,22 21:17 25:1325:21 29:11,13,16,2030:5 34:17,21 43:1143:12 44:2 53:3,3113:21 137:21 138:3138:18 139:8 205:16210:18 236:3,7237:11 240:4 241:11245:10 250:11,15253:18 260:20 261:6262:19 263:16 285:14286:4,5 292:5

publication 21:22 22:223:9 123:8 172:9196:21

publications 133:20publish 15:20published 23:15 36:21

43:9,13,21 46:7 52:2253:4 75:15 76:5,1083:7 85:4 91:6,9,11100:21 113:20 121:7122:3 128:17 198:9

PUFAs 117:12,15,19pull 27:1 132:2 247:21

268:21pulling 272:6Purdue 5:8purpose 68:22 75:19

181:1purposes 276:17push 165:14put 79:7 80:13 81:7

169:4 218:3 248:8250:2 264:3 289:20

putting 34:4 127:18253:19 286:1

Qquality 196:4 213:15

217:22 218:2 222:22222:22 285:5

quantified 173:3quantitative 237:6quantities 112:4quantity 112:1,16 113:7

114:4 118:8 119:1,3,6quartile 202:7,8quartiles 202:6question 7:9 16:17,19

25:10 30:10 35:7 37:255:4 69:22 70:6 76:879:17,19 80:15,1981:9 82:7,9,18 91:2194:8 98:13 101:1104:17 106:12 107:7111:20 125:22 128:2130:19 135:7,9,20,21136:2,7,9,12 137:8,9138:22 145:8,9,13,15147:10 156:5,6,12,14156:17 157:2 159:20160:3,9 162:16,21163:5,11,14 164:3,11165:4 167:20 168:3,6168:9,11 170:18173:19 174:2 177:6178:21 179:15 183:9185:22 186:6 193:5193:16 194:3 201:18202:12 203:1,16,17206:21 210:17,18217:8,10 236:2,6,12


317

243:4 246:8 250:6,21251:13,21 259:12260:12 263:14 264:6265:3 271:14 280:1

questionnaire 102:3108:16 147:6 152:4

questionnaires 139:22questions 6:9,20 7:2,5

7:13 8:1,4,6,14,179:19 10:1,2,8,1011:10 12:11 13:1 16:916:11,16 19:16 24:524:21 25:6 27:6 31:1932:10,15,22 33:3,1136:18 43:3 44:4 53:953:22 68:18 69:2071:10 72:8,11,14 74:976:22 77:14,19 84:1685:11 88:10 89:4 90:292:3 122:6 126:11,22127:3 131:14 133:8134:10,15,16 135:2,5135:14 137:6 144:7158:22 159:4,17166:21 173:12,15174:4,6 175:18,19176:3,8,9,14,18,22177:17 199:13,16204:5 205:15 241:14241:16,21,22 242:3244:8 264:2 265:14270:9 278:15 280:5281:11 287:11,19

quick 86:17 87:10130:18 241:20

quicker 82:20quickly 32:9quintiles 140:4quite 48:19 90:16

130:15 177:14 192:1193:12 196:3 251:14267:18 276:11 286:4287:12

Rrace 41:4 94:18 95:8

96:2 108:13 114:7196:2 213:18

race/ 206:7race/ethnic 213:5,11

226:6 234:4race/ethnicity 115:4

179:7 275:4Rachel 1:18 173:8Rachel’s 268:20racial/ethnic 267:6radar 212:22 213:1,2,8

217:21 269:5

raised 166:18rampant 261:15ran 91:4randomized 48:21

60:19 61:11 107:4125:6 146:4,7,9147:22 148:3 150:16150:18 151:14 152:19157:6,7,12 160:2,10161:10 281:5

range 11:1 36:15 48:695:7 96:2 101:5107:11 114:14 121:22124:7 177:17 237:4

ranged 95:18ranges 203:1 220:18

223:14ranging 107:20 239:2rate 173:14 227:10

232:12,15,22 233:1,4233:7,8,10 235:4

rates 128:15 203:8232:11,12,19 233:13233:14 264:20

rationale 6:13 69:4 70:870:16 78:13

RCT 97:10 118:6,11123:7 124:6 130:11146:14 186:9

RCTs 94:5,13,15 96:12100:20 107:3,10,20113:11,18 114:4115:21 117:9 130:8146:5,12 149:8,10168:21

RD 1:13,14,15,17,17,191:20 2:9,10,12,13

RDN 1:18reaching 270:3reacting 285:22reaction 78:18read 18:20 21:15 32:6

46:5 76:15 89:7119:22 167:4 236:22

ready 78:14 133:21204:10

Reagan 276:19real 70:14 274:9 291:16realized 259:17really 3:9,15 7:10 8:21

11:8 12:6,13 16:2028:15 72:15 73:1375:19 91:11 117:5118:20 165:3 166:5175:10 178:15 180:18180:21 194:13 198:15207:17 220:14 221:7224:10 234:17 235:18

241:16 242:9,21244:18,22 245:3,6,14246:4 251:2 254:10254:17 255:13 256:8256:15 258:13 259:12259:14,15 263:20264:19 269:12,17,19271:21 272:13 273:7273:14,15,16 274:13276:9 277:5,12 278:5282:19 283:15 284:22286:10 288:22 289:5289:14,15,19 290:5291:9

reason 69:16 180:16263:17 279:1

reasons 7:6 195:8202:12 248:17

recall 160:1 168:22169:7 202:2,3 255:1260:9

recalling 202:1received 4:8 5:9 8:3

18:5 29:16,22receiving 56:8 57:3recess 86:14 132:22

204:9recognize 31:6 175:3recollection 82:1recommendation 72:19

73:9,11,14,17,21 74:380:20 81:7 237:7,8238:8 252:6 258:19

recommendations 6:127:7 9:8 15:10,12,1825:17 72:21 81:1,585:3,20 167:4 208:8213:12,17 237:20240:17 241:5,7265:17 271:2 273:6274:1 276:2,16283:16

recommended 70:19208:15 209:10,12220:17 223:14 256:21282:1

reconvene 132:17292:2,10

record 157:22recorded 157:17

252:13recordings 14:4recovery 127:18 245:1recruited 38:15recumbent 225:1red 106:20,20 108:5,22

110:8,19 111:4,14124:14 134:16 137:15

213:8 238:16reduce 59:10 61:2,15

76:17reduced 97:3 122:13

123:12 234:15,19reducing 98:5reduction 97:7,9redundant 278:8reel 222:12refer 121:14reference 9:9 200:4

209:18 237:5 261:3references 20:2referred 72:20referring 77:12,13

169:19refers 33:13,20 34:12

74:18refine 13:18 15:10 28:2

205:14refined 8:4 27:17

122:13 218:10refining 68:16 90:13

126:2reflect 69:11reflective 207:18refresher 136:7refrigeration 33:19Regan 1:13 127:16

134:5 204:15 242:2260:11 264:3,9270:13 281:18 284:5

Regan’s 271:22regard 42:3,15 47:13

50:8,8 82:10 178:17187:19 190:14 191:22194:14 198:2,17200:11 265:17 269:14278:22

regarding 41:9 42:945:8 67:1 68:19 72:1979:18 83:9,9 104:19105:7 110:21 192:10192:18 246:9

regards 284:21Register 15:21registered 4:7,17 14:8registration 4:8regular 201:8 203:14reiterate 122:1relate 33:1 205:15related 12:14 19:16

32:22 36:18 37:2045:14 46:3 62:2068:16 69:1 70:1,3,681:14 89:8 94:3111:20 116:13 117:18122:6 137:6 159:5


318

165:5 173:9 175:19176:2,3,14,18 177:1179:12,15 183:18185:5,16 186:18,19186:21 187:6 188:14189:4,20 237:14242:3 243:5 249:1253:5 256:4,11 260:4261:18,19 264:20265:13,15 266:7269:7

relates 74:15 78:1589:5 171:15 172:2

relation 176:4 185:14188:21 189:12 194:3

relationship 20:14,2232:11 35:2 40:7 41:1841:21 42:5,7,11,13,1842:21 45:8,19 46:9,1946:22 47:4,9 48:8,1149:1,7,11,22 50:2151:14 52:6,9 54:1555:6,10 56:15 57:1958:13,18 59:19 60:260:18 61:5,8,17,2062:5,10,21 63:3,5,964:2 65:2,13 66:3,1466:18 67:8,17 68:869:13 76:2,13 78:1679:2 92:3 94:8 99:699:10 105:10,21106:13 111:8,13114:2 115:18,21116:2,9 117:9 118:6118:11,14 119:2,4,12119:16 120:10 121:17123:4 124:4 125:2136:3 138:5,13 139:1139:11 141:6 142:13143:12,16 144:13,22145:4,9 151:9 152:11153:3,8,16 154:13155:7,13,21 156:7158:12,17 159:6160:15 164:15 170:19171:18,20 177:7183:21 185:6,18186:2 187:1,9 188:15188:19 189:1,7,21190:2,5,10 191:10,12191:17 193:17 200:14261:22

relationships 45:2267:19 76:6 160:22291:4

relative 117:18,21149:4 159:13 179:20211:1,13 213:13

226:17 237:5 239:11239:14 241:1

relatively 114:5 131:22176:16 234:9

release 13:10relevance 8:6relevant 180:9 251:15

265:14,16 288:4reliable 168:6reliance 144:11relied 153:4rely 74:9relying 76:9remainder 31:3remaining 13:18,19

28:3 68:17 69:19134:16 198:16 205:12240:5 241:3

remains 234:9remarks 2:2,4 14:22

26:5 28:20 131:18,20133:10

remember 82:3 83:20130:6,11 163:5164:10 169:9 171:17172:5 202:15 218:1222:12 246:11,11

remembers 84:1remind 4:10 18:8 19:1

33:10 88:9 89:21214:3 260:5

reminded 263:19reminder 5:1,15 92:7

134:19 136:15 137:16183:3 206:10 211:3211:11,22

reminders 133:3remotely 4:14repeat 73:15 133:9

168:20 169:1 197:22271:8

repeatable 289:9repeated 168:2 169:8repeating 139:9replaced 215:18report 6:11,14 13:9

15:3,5,10,13,16,1824:12,19 25:15 27:1727:19 31:4,14 41:471:18 73:3 86:12128:14 132:7 133:16133:22 134:3 144:11153:5 159:2 167:11169:21 174:21 175:1198:21 200:9 204:11204:16 205:7 225:8225:15 237:1 252:5259:11,16 261:2

264:8 271:3 275:20285:9,13 286:3,7,9288:2

reported 38:22 39:894:18 95:1,2,9 102:8108:14,21,22 110:9114:7,19 115:4128:10 139:8 147:4164:20,21 184:15185:4,13,15 188:14211:13 246:9 276:1285:21

reporting 28:17 114:10135:15 173:11 185:17254:18

reports 18:21 20:1130:17 166:22 252:14292:4

represent 5:17 204:18214:5 260:13

representation 17:5representative 243:13represented 213:7

218:7 219:7representing 182:4

260:14reproduced 257:3requested 13:8required 5:22research 1:8,8 3:12,13

5:2 26:2 84:21 85:1,385:5 91:8 123:17124:16 125:11 129:2252:5 258:19 273:1,2276:15,17 280:4

researchers 74:22278:16

resistance 51:12 52:479:8

respect 54:11 190:22192:8 267:11 269:20

respectively 225:4response 30:13 131:16

132:14 163:16 164:14168:6 187:19 202:1,5204:6 262:15

responses 72:15responsible 205:19rest 58:22 90:14 167:4restricted 125:12result 69:9 80:13

184:15 193:12 245:4results 23:22 25:3

31:22 36:10 60:1297:14 117:13 120:5121:13 137:5 155:9157:1 158:10 162:17163:9 183:4 276:8

retinol 210:21 238:21241:1

retrospective 109:2,3125:6

return 86:10reverse 67:12review 5:2,19 6:12

16:19 19:1,9 20:2121:9 23:4 24:9,1026:10 32:1 35:1,2036:9 42:20 43:16 52:856:1 60:6 69:8 70:1776:9 90:19 91:1699:15 106:13 111:22121:13,16,20 123:9126:9 136:6,9 137:6137:12,22 138:2,17145:12 146:1,6147:21 150:17 151:14152:20 154:2,20156:4,11 157:20158:21 159:1 176:9177:11 178:3 179:21179:22 193:19 198:19266:15

reviewed 25:10 34:1940:6 70:11 139:4145:15 156:7,15187:14 265:1

reviewers 60:11reviewing 16:10 279:21reviews 19:12 21:6,11

21:13 23:16 25:5,2226:2 27:8 33:9,1443:4,7,9,18,21 44:544:13,14 52:17,1953:10,18 70:9,10 85:488:8 90:17,22 91:7,991:13,15,15 93:12120:6,8,14,20 121:6121:10,13 122:5159:11 265:22 271:16

revisit 224:6revolve 85:10rhinitis 46:20 58:21

60:4 61:9,19,22 62:1363:1,19

rice 215:6Richard 1:17 243:20

279:19Rick 72:11,13 81:10

82:19 127:4,6 166:20169:12 251:9,10290:1

Rick’s 82:8right 31:5 36:6 76:19

80:8 81:5 84:6 86:587:3 94:4 131:17


319

161:2 170:7,22175:15 183:12 204:8214:17 222:4 234:1242:15 246:14 249:5252:3 257:4 267:10268:9,11 269:6 281:2284:10 287:22

rise 79:10 253:17risk 22:15 27:11 37:13

40:18 45:12,14 46:1650:19 51:8,21 58:1458:20 59:10,13,15,2160:8,14,18 61:2,6,1561:17,20 62:7,12,2163:6,17 66:7 71:973:4,10,12,20 74:179:20,21 80:12,1389:17 92:5 93:3 97:397:8,8,22 98:5,7,1699:1,2,4,8 103:10,16104:12,19 105:2,7112:15,18 118:3120:12,13 121:18122:7,13 123:1,12,21124:10 126:15 144:5144:8 154:9 156:9157:3 158:19 159:6176:5,14,19,21 184:2184:4,10,16 185:16186:22 187:6,14188:21 189:4 190:2,7190:13 192:3 198:22201:13 240:11,15249:22 261:18 272:11

rivers 134:21robust 257:20 262:15role 201:17 241:4Ron 31:13 199:17Ron’s 165:5Ronald 1:12 2:16room 8:12 17:6 74:10

87:9 277:22rooms 261:15rotating 16:13round 276:18route 275:4RTC 121:21ruling 170:22

SSabaté 1:19 83:8,8

134:6 164:8,9 169:6,6171:14,14 280:6

safe 218:21safety 8:17 9:13 170:20salad 157:11salient 224:11sample 49:19 94:14

101:4 117:3 129:15129:17 130:1 181:20196:16 200:16 203:1243:13

samples 112:20 192:7sampling 117:4sandbagging 281:14sandwich 157:11 284:7sandwiches 207:11,16

208:18 209:5 214:12214:20 215:6 220:12220:20 221:17 222:1222:3,9,19 223:12,15274:4 280:10 290:2

sarcopenia 11:11 253:4254:7

saturated 117:11,14,19210:8 223:20 237:8238:19 239:22 263:21

save 16:2savory 215:8 219:11

220:2saw 198:12 275:11saying 73:11 81:19

171:2 257:19says 74:3 250:7,10scale 203:14Scandinavian 147:18scenes 126:21schedule 26:22scheduled 15:7 29:11Schneeman 1:9,11 2:4

2:15 14:21 17:1,230:14 34:22 84:17130:18,19 131:19132:16 133:1 134:7159:16 164:8 166:15174:5,11,14,18 175:5199:14,16 204:7,10241:19 243:19,22248:6,10 250:22251:3,6,9 252:10,17260:4 264:1 270:3290:12 291:18

school 73:9 154:5157:10 278:3,4

schoolchildren 157:13schools 282:2science 11:8 278:13,14science-based 6:12Sciences 259:11scientific 6:8 8:14 9:18

19:13,15scientists 5:18 44:11

53:16scope 10:14 26:16

33:10 35:7 178:15267:18

score 212:4,18 213:3,7213:13 218:6 257:19

scores 211:6,7 212:9213:16 217:19 218:13256:22 257:17 259:2

scratch 10:5screen 21:7 129:18

177:7screened 27:10 89:16

94:2 100:18 106:22113:10 176:17

screener 259:8screening 23:22 31:21

36:10 71:3,5 137:5157:1 176:6,15179:19 267:15

scribbling 291:19scurvy 248:4se 262:22sea 134:21seafood 2:10 10:10

18:16 29:1 115:14124:13 132:5 134:1134:15,19,22 135:7135:10,21,21 136:3136:18,20,21 137:6,8137:10,12 138:5,13139:1,11,16,20 140:1140:2,12,19 141:1,6141:16,21,22 142:2,7142:13 143:1,4,12,16144:14,22 145:4,10146:1,22 147:3 148:5148:10,14,17 149:1149:15,19 150:3,10151:9,22 152:7,11,17153:8,17,22 154:13154:18 155:13,21156:5,6,8,17 157:1,2158:18,22 159:20160:6 162:10,18163:16 164:6 168:12168:18 169:13 218:9288:15

search 23:22 36:13,1536:16,19 43:19 44:1553:18 71:1 93:17,1993:20 100:8 113:9137:5 157:1

searches 36:11 89:1890:14 111:19

second 3:17 8:8 14:631:9 45:18 49:6 57:1462:15 70:3 89:5120:13 135:9 137:9141:10 149:6 156:4157:12 162:21 172:8182:3 202:8 214:1,18

243:4 246:8 263:7269:15

secondary 195:5,11197:19

Secretaries 5:8 6:1425:16

section 128:22 159:2224:12 233:17 283:18

sections 278:9security 268:6 269:22

275:1see 4:2 6:5 17:4,13 20:9

20:13,15 22:12 23:2130:10 36:6,22 37:8,1639:7 44:18 47:17 50:789:7 90:16 91:7,994:4 95:21 96:1 97:6100:1,13 101:9108:10 114:18 122:2130:14 132:11 134:10135:12 173:22 175:8175:9,10,11,13 177:6177:18,20 179:5180:4 181:20 182:6182:16,19 204:22205:11 209:19 212:7213:4,8,18 214:11218:5,14 219:15220:6 227:1,9 232:20238:22 244:5 245:12245:21 248:3 250:4255:8 262:8,15 264:4266:10 270:1,16273:19,20 276:6281:2,22 282:9 283:1283:12 290:7 291:3

seeds 59:7,17,20 60:3124:13

seeing 12:22 132:11172:17 204:7 263:12269:9 271:21

seen 92:15 208:6 212:2212:3 219:3 222:22246:14 272:18 285:16

SEER 227:12segment 180:13select 289:13selected 5:7,10,18selection 184:12,14

192:4selenium 113:4 119:20

210:22 238:22 239:3241:1 242:7

self-report 225:11232:2

self-reported 127:7128:3 211:12

semisolids 34:14


320

send 15:22sense 18:3 73:7 168:4

170:19 214:16 289:18290:4 291:13

sensitivity 244:16245:7,11,18

sentence 274:14sentences 224:9separate 7:9 99:3

135:19 137:17 252:13252:15 282:19

separately 260:16sequelae 261:20series 35:10 58:22

159:4 171:16serious 158:13 184:11serum 108:5 110:5,18

111:5serve 251:16Service 1:8 3:12 26:2Services 5:5 9:12servings 140:4 164:21

182:2SES 94:18 95:9 96:3

101:10,22 102:14107:15,17 108:13109:16 114:7 179:7196:2 268:1

sesame 59:16,20session 28:13 175:17set 18:9 28:15 44:14

47:5 54:3 64:5 89:4112:6 133:2 176:3,8177:19 184:17 221:15242:16

sets 23:1 272:21 276:13setting 277:20settings 8:18 278:1seven 40:6 48:7 65:3

113:10 114:5 146:21147:20,21 157:14181:5 189:11 205:5

seven-day 157:22severe 59:13 103:10

228:15,18,20 254:19255:4,7

sex 100:11 120:18125:4,15 176:1 177:9179:6 182:11 193:5,6196:1 203:10 206:6213:18 216:10

SGA 186:20,22 188:18188:21 189:22 246:12

shaking 82:22share 172:21 205:6shared 172:20 233:13Sharon 1:15 2:9 78:1

86:11 87:13,17

127:16,16 173:17276:5

she’ll 174:12she’s 87:14shellfish 134:22shied 78:1shift 220:11shifts 221:17,22short 72:15 83:21 86:14

131:22 204:9short/long 236:5shorter 46:9,14 47:1,6

48:13 49:7,13 51:6,1751:20 65:8

shortly 12:17shouldn’t 25:16shout-out 259:8,8,14show 38:7 39:11 76:1

170:19 205:8 206:8224:5,15 238:2 249:3

showed 48:22 66:10103:9 160:14 184:9188:15,18,20 189:1,3200:14 235:16 240:12240:21 277:15

showing 37:5 180:2216:6 222:12

shown 32:3 39:13,1751:2,16 52:7 101:5,18137:18 139:6 147:14177:21 180:1 195:7

shows 35:7 36:9 46:847:12 88:2 183:2217:21

side 17:14 131:4 196:10sight 279:3signed 16:1significance 193:14significant 49:1 97:1,7

97:9,20 103:14 110:2151:17 154:2,22167:2 170:1 171:19183:7,21 185:7,20187:1,4 188:17,20189:2,22 190:3,5191:11,12 193:11200:1 202:4 208:20

significantly 43:14 53:6163:2 215:17

similar 13:2,16 14:625:1 41:6 106:16119:7 165:4

similarities 12:19 135:5similarly 68:10 190:4

222:17 234:21 237:9258:12

simple 76:3simply 224:14

sincerely 44:10single 32:6 51:22 75:8

117:2,3 167:22 188:5singularly 166:22sitting 17:13situation 86:4 160:13

160:17 201:2,18six 18:11 47:22 48:7

49:2,5 54:21 60:1964:15 88:16,18100:18,19 101:12102:15 114:8,9 115:7141:17 143:22 144:15146:7,11,21 148:6149:12 150:20 152:22157:13,22 186:8188:10 189:17 221:8277:13

six-year-olds 151:16size 23:11 32:18 33:1,5

52:12 64:6 65:4,11,2266:9,15,20 68:20 70:171:12 81:15 84:2129:15,17 130:1176:4,20 181:20193:12 198:22 199:8199:22 203:1 253:5,6254:7,11 266:4 277:7

sizes 200:16skip 62:14skipping 32:9slice 8:22slide 6:5 27:4 37:4 39:7

39:13 71:22 134:10135:1 139:6 164:10175:9 212:3 213:4221:14 246:21 247:22

slides 4:2 6:10 17:1920:7 58:22 59:3 87:2087:22 135:12 217:5218:17 238:3 260:10

slight 228:9 285:18,20slightly 212:6 213:16

229:10 234:22small 12:16 18:13 37:9

37:10 39:10 67:6,22107:11 109:12 114:5129:15 164:7 179:1181:16 185:16,18191:13 193:13 199:21213:20 236:22 261:10287:12

smaller 36:19 60:1566:22 129:18 220:21

smart 278:5smoking 196:5smoothly 17:17snacks 208:18 209:1,5

214:21 215:6,8219:11 220:2,14221:5

SNAP 268:1snapshot 37:5Snetselaar 1:19 2:10

134:2,4 161:1 162:12163:4,21 165:16166:12 167:10,13168:9 170:14 171:5,8171:12 173:7 174:17286:19

snowballed 204:2social 143:21 144:17

145:1,5 151:12 152:1152:12 280:12,17291:11

social-emotional103:19 105:13

society 280:18socioeconomic 123:3

192:9 206:7 267:7274:16,17

soda 289:13sodium 210:8 222:6

223:20 238:19 239:22262:12,14

solid 178:9 208:16,17208:21

solidified 12:6solids 34:14Somebody’s 222:3somewhat 265:1soon 167:17sorry 62:15,16 93:18,19

107:1,2 109:2 115:2163:14 182:13 250:21

sort 17:20 28:10 75:1080:3,21 109:19132:13 135:2 174:3177:16 180:2 182:20183:2 262:21 267:2270:17 272:7 283:21284:1 287:13

sound 88:20source 56:9 57:4

208:17,20,21 214:17215:1 217:18 219:12220:2,4,11,15,20221:10 232:16

sources 55:17 57:14206:18 208:10 214:10216:8 221:3 223:4224:2 242:10 246:5

soy 62:17 63:2 115:14soybean 63:6space 9:11SPAHN 168:11,15


321

span 275:8spanned 53:18speak 9:16 127:20

128:9 130:12 201:9263:9 271:22

speaking 178:10 256:2speaks 284:3special 17:10 237:17,22

238:16 239:5 247:20272:7

specific 5:17 6:1,8,196:19 7:2 8:16 9:2,210:10 12:13 23:428:16 59:1 71:1376:19 109:8 136:15147:16 148:20 184:5184:7 188:6 194:9216:7 236:1 238:7246:2 250:5 260:12264:15 269:3,13273:10 280:4

specifically 7:20 15:1517:22 97:17 117:20141:5,9 142:10,16150:7 168:12 173:16173:18 178:11 188:7189:16 195:19 215:12253:21 257:7 263:9263:19 268:15 279:12

specificity 140:21specifics 164:1 181:1specified 21:1 23:14

82:9 191:6 193:5194:6 253:9

spectrum 102:17 105:3138:8 153:14,18,19174:3

spend 219:4spent 166:13 251:1

278:12 286:13spider 212:14,19spontaneous 124:11spot 253:19stable 234:10staff 13:17 17:15 26:21

28:1,2 31:20 71:2175:2 89:15 126:19132:1 134:8 159:9174:19 175:6 199:12277:20

stage 224:14 240:7272:7,8 273:8 277:18285:9,13

stages 217:9,20 222:8222:16,22 223:5265:12 273:11,13279:7 283:6 284:12290:17,21

stairs 87:4standard 21:10,20

168:8 196:20standardized 120:17

125:4 176:1 177:9standards 33:22 34:7standpoint 261:13

281:9 283:8Stang 1:20 128:12,12

204:19 275:7starchy 219:8 284:8start 10:5 17:19 28:20

29:7 82:5,5 88:2128:15 132:6,11,18132:20 180:10 212:14212:15 218:16 224:17249:13 270:7 272:4

started 88:8 133:2172:19 179:17 196:20235:20 237:2

starting 159:5 181:3216:18 255:8 284:16

state 116:22,22stated 76:13statement 25:9 41:8

45:17 76:4 77:7,979:14 98:2 104:9143:10 144:20 148:15150:1 151:7 152:9153:6,15 154:11155:11,19 158:15169:12 170:9,16171:10 187:7 190:8200:18 209:7 222:21235:17 242:20 260:11260:15,17 264:4,7,14268:20

statements 24:4,8 25:325:7,8,20 26:9 32:3,543:17 45:14 46:6,848:3 68:14 81:6 84:1891:5 116:7 119:1120:2 126:10 133:11133:18 134:14 135:19137:17,20 138:1,18138:21 139:7 140:22142:6 165:18,22205:1 287:6

states 41:10 208:3stating 78:2statins 243:12statistically 183:6,21

185:7,19 187:1,3188:16,19 189:2193:11

Statistics 232:17status 10:17 18:6 22:1

22:10 23:2 26:14 28:6

32:13,18 33:7 35:536:8 37:3 38:8,939:17,18,21,22,22,2240:4,8,11 41:12,13,2042:1,2,6,8,12,14,1952:11 54:4,6,8,12,1354:14,18 55:1,8,12,2256:5,18 57:1,12,18,2264:16 70:6 71:2 72:2076:1,18 77:19 78:1883:21 89:3 90:1191:18 106:15,18107:2,9 110:18111:17 123:3 126:4192:9 196:21,22206:7 234:10 266:10267:8 274:16,17291:13

stay 14:14 220:8stays 219:18steal 256:6 288:2step 6:18 7:3,9 281:8step-wise 182:17steps 70:21Steve 244:1 263:8Steven 1:16 289:1stone 165:19Stoody 2:3 3:3,4 17:21

19:19 28:8 30:4 86:15stop 218:19 219:1,2

265:8 291:17stores 55:14 56:7,12story 218:4 291:14strange 204:21 225:11strategies 274:7,9streamline 13:18 28:2Street 1:8strength 81:20 152:3,4

169:3 234:14,16,19240:13 252:18 253:3253:4,15 254:10

stretch 86:9striking 265:1stroke 158:6 229:22

230:9,13,22 231:4strong 49:20 52:1 56:1

59:8 80:9 84:13110:15 111:1 273:6

strongest 59:11 81:16struck 276:19 280:8

281:20structure 17:22structured 20:11structures 18:9struggling 267:3stuck 273:17studied 22:4 38:14studies 21:21 22:8,9,17

34:2 36:17 37:6,9,1037:22 38:11,13,2239:8,10 40:6,9,13,1941:3,4 43:22 44:2045:2,16 46:13,1747:17 49:5 50:18 51:551:19 54:4,13 55:3,2258:5 59:4 60:6,1661:10 62:1,3,18 63:363:9,14,21 64:1,1,767:3,4,16 68:1 76:1580:8 83:14 95:15,2196:16,18 97:14 98:1298:15,18 100:19101:12 104:15 107:6107:14 110:20 112:12113:13,15 114:5,19114:21 116:15,21117:8,21 119:15121:21 125:21 127:10127:21 128:3,9,13129:13,19,21,22130:14 135:17 136:20137:1,1,11 138:11139:10,16,18 140:3140:11,17,19 141:14141:19 142:21 143:3144:4,8,19 145:21146:1,4,6,22 147:2,5147:17 148:2 149:9149:14,22 151:6,14152:3,20 153:4,13154:8,20 155:8,17157:5,6,17,19,20158:10,13,14 160:12160:18 161:6,10,12162:6,19,22 163:13163:18,22 164:1,6,9164:12,13,18,20165:7 166:3 167:21168:17 169:8 170:21171:16 172:3,4,11,11173:22 178:3 179:17181:5,6,8,10,18 182:7182:14 183:15,22185:1,4,8,10 186:8,10186:13,15,17 187:13187:15 188:1,3,4,7,10188:11,13,15,18,20189:1,11,13,15,16,19189:21,22 190:2,5191:1,3,3,7,10,11192:2,6,6 193:7,10194:7 195:15,18198:8,14 200:2,13,17200:21 201:13 202:3203:7,10 279:20,21281:5 283:10 287:12


322

287:21,21study 21:14,21 22:7,11

22:22 23:12,12,1338:3 40:19 48:1849:20 51:22 67:1781:17 94:16 95:17101:7,21 102:13103:9,20 104:16,16104:20,21 105:5107:5,11,11,16,17,21108:1,18 109:12,12110:1 115:10,12,18116:4 118:14,15125:13,15 130:11140:3,4 146:14,16147:10 151:2,21154:1,2,21 155:4157:9,16,21 158:3161:2,15 166:6170:20 181:20,21182:1 183:3,17,19,20185:6,13,15,17186:19,21,22 187:2,4189:3 190:6 196:15196:21 197:9,14,19197:20 198:4 202:13279:22

sub-types 177:20subcategories 215:4subcategory 215:1subcommittee 2:5,6,8

2:10,11 17:22 18:6,918:18,21 20:9 24:226:14 28:20 29:7,930:17 31:12,15,1671:19 72:5 78:4 84:2086:12 87:15,19 88:388:11 120:9 126:18132:4,5,12 133:22134:1 138:3 139:4159:3,8 166:17174:15,20,21,22180:14 198:13 199:11199:17 200:20 204:11204:16 205:5,19218:21 241:21 242:1260:6 261:5 277:6286:8 288:3 292:4

subcommittee’s 20:10subcommittees 18:12

19:1 21:12 23:1825:12 26:17 27:928:21 29:4 30:22 31:472:7 112:3 131:20166:1,19 167:15265:15 266:1 270:7270:18 287:3 288:8288:13

subgroup 73:12,20166:6 167:19 249:19

subgroups 217:16238:7 265:8 274:20

subject 257:2subjects 60:7 95:7submit 6:13 15:13,18

24:19 43:12 53:3submits 25:15submitting 34:18subpopulations 262:3subsequently 180:15subset 73:10 176:9

271:10substance 93:15substantial 40:5 56:3

56:22substantially 235:1subtle 135:6success 274:10sufficient 37:11 56:12

160:10sufficiently 40:13sugar 29:2 74:2 208:21

215:15,16 221:2,10223:8 241:5 282:3

sugar-sweetened 66:574:3 81:13 178:12180:8,10 181:9,12182:1 183:14,18185:1,11 186:3 284:9

sugars 2:11 10:8 18:15174:22 175:20 176:14176:19 198:17 208:16210:9 216:22 218:10221:1 238:20 239:22246:3 282:6,15287:19 288:14

suggest 45:19 46:1859:8 63:15 104:22116:12 117:15 122:9169:3 204:8 239:20

suggested 249:22suggesting 98:20 111:2

123:11suggestion 290:1suggests 45:10 46:13

48:4,15 49:14 50:1851:5,10,20 52:1 54:1956:2,20 57:8 58:1259:18 60:22 61:4,1362:4 64:12,19 65:1565:19 66:5 98:3104:10 110:15 124:9141:1 142:7 148:22150:9 169:13

summaries 133:18205:2

summarize 24:13 26:1576:3 87:14 261:9276:10

summarized 70:2293:10

summarizes 45:7 50:1555:20 263:4

summarizing 85:5120:5

summary 12:18 24:2,872:4 78:22 96:11103:3 111:18 113:11115:17 127:3 133:11134:13 175:18 181:19191:21 205:1 239:16266:21

supervision 80:3supplement 36:2 92:9

92:11 95:18 96:5109:18 118:19 127:7131:9 137:1 179:14

supplementation 96:1396:17,18 97:2,5 98:498:9,21 102:3 103:4103:15 104:3,6,11105:1 108:16 110:3,5110:8,10,12,16 111:3130:20

supplemented 102:7111:13

supplements 33:4 39:669:21 70:2,5,7,9,1570:18 71:1,5,7,1488:13 90:3,8 92:4,892:19,21 94:9 99:11101:2 103:11 105:11105:14,18,21 106:5106:10 107:7 111:9126:7 127:17 128:6128:11 129:8,10130:22 206:15 243:1

support 4:20 57:171:21 126:19 199:12

supported 98:10204:20 250:1

supporting 24:12237:11

supports 263:2 288:22sure 17:16 28:10,11,12

77:15 78:14 128:10133:6,7 170:9 174:19180:17 187:13 202:15202:21 243:21 254:1254:12 255:3 258:1261:12 271:8 275:3280:19 282:10,22286:17 287:2,16289:8 290:9

surgery 289:5surprise 281:13surprised 269:10surprising 281:2 290:2surprisingly 67:6 68:5

214:7 216:3survey 243:18 245:8surveys 230:3sustainability 280:15swallow 251:18Sweden 147:3sweet 208:18 209:5

215:6 221:4sweetened 178:13

180:7,11 181:10,13184:21 185:2,12186:4 207:5 208:22215:7,19 216:8,19221:7 251:19

sweetener 186:12192:11

sweets 208:22 214:20220:14

symptoms 151:19155:6

syndrome 49:9,17231:9,11,14,15,18,21264:19 266:14

synthesis 24:3 38:1078:6 88:7

synthesize 164:22synthesized 159:12system 232:18 259:17systematic 19:12 21:6

23:16 25:5,21 27:743:4,18,21 44:5 52:1753:9 90:17,19,22 91:991:13 93:12 99:15106:13 111:21 120:7120:14 121:6,9,11,13121:20 123:9 136:6137:6 145:12 156:11158:21 159:11 177:10179:22 193:19 198:19271:16

systematically 180:4systems 287:15

Ttable 180:1 248:11tables 168:19 181:19tackle 280:17tailored 23:4,5take 16:15,18 28:17

29:11 31:8 32:7 79:1686:8 108:19 126:22166:17 174:15 177:13182:12 204:8 214:1


323

217:6 246:19 248:13takeaways 206:9taken 31:2 86:14

132:22 204:9 239:18takes 27:1talk 6:10 8:7 16:8 17:21

18:3 31:11 76:7 163:5165:10 193:22 230:1233:17,18 247:21266:7 277:18 290:18

talked 6:17 10:18 13:515:4 19:7 21:16 130:7211:18 215:3 218:11220:1,18 236:4238:19 241:3 244:10244:14 245:6 254:16255:13 261:8 271:5275:8 278:20 281:18284:4,5,22 288:3290:17

talking 16:11 59:7 78:382:5,6 88:2 170:8173:17 206:6 211:10212:1 230:2 236:10240:2 242:20 267:5269:18 270:5 271:15283:20 285:4

tangerine 218:22 219:2254:4

tap 191:4targeted 11:13task 13:7 27:20taste 280:15TAVERAS 1:20 254:13

255:6,11 266:19276:3

tea 180:9 187:22 188:2188:4,6,7,8,8,14,20189:7 192:14 209:1,6216:9,13 221:9,11222:4

team 3:14 164:2 259:8tease 255:20 283:4TEC 53:17 83:6 121:4

128:13technical 44:7,12 53:12

121:3teenaged 107:16 210:4TEI 182:14tell 224:4 225:14 287:18tend 38:22 212:9

219:14 231:6 244:11284:13

tended 140:21 146:20tends 215:18 227:20Teresa 1:14 204:19term 33:15 72:16 83:22

84:12 237:17

terminology 236:8terms 10:22 17:15 23:2

26:18 31:6 47:6 48:1351:3,17 55:1 56:1964:11 65:5,18 68:175:16 90:18 92:1698:13 99:17 104:16109:14 117:14 118:22128:9,17 152:7167:18 170:22 172:15172:21 173:3 177:18181:7 182:7 186:17188:13,18,22 190:8190:13 191:9 192:3192:10 194:2,17195:1 196:1 197:4,11198:1,7,20 201:13202:13 210:10 216:12227:13 231:8,22235:8 238:18 240:3246:10 253:16 262:3262:11,15 263:8267:22 271:22 272:14272:15 273:22 286:20288:19

test 80:9,11 127:19150:19 172:6

Texas 1:9 3:11,14text 179:19thank 4:19 17:2,11,14

17:18 30:18 31:1334:17 71:19,20 72:1,386:13,15 87:5,12 88:3131:20,22 159:8,9,11159:14,18 171:13175:2 199:14 200:10222:3 241:14 244:2250:19 260:3 263:22290:11 292:8

thanking 126:18 199:11thanks 3:14 30:19

86:15 242:2that’s 4:6 10:21 12:14

31:1 35:19 74:21 76:976:10,18 77:21 78:2179:15 80:8,16 81:1882:1,17 85:6 87:188:2 111:18 113:17113:18 127:19 129:1130:5 132:1,19,19133:22 137:14 160:4163:10 165:12,15,16169:15 172:19 175:9175:11 177:5,21184:5 187:19 193:21194:10 195:17 197:9199:10 200:8 201:5202:9 203:16,17

207:16 215:5 222:9235:13 236:14 240:2240:10 242:10,18244:6 245:14 248:4253:11 254:4 255:14255:17 258:2 261:16268:16 269:2,17,19273:3 275:4,5 276:9277:1 278:5 280:3281:10,16 282:7,21283:15 284:21 286:8289:4,16 290:22

theme 57:13 205:4theoretically 76:16therapy 8:20there’s 9:15 26:17

27:20,22 28:8 29:1429:18 30:10 47:350:20 51:14 52:456:14 57:15,18 58:1761:7 62:9,10,20 65:165:12 66:2 76:1585:14,20 99:5 104:5105:14 113:18 116:11117:15 119:1 128:7167:3,6,8 169:16170:4 173:15,22176:6 207:14 225:15231:13 234:3,17236:9 242:14 245:7249:9 250:17 253:14255:19 256:19 257:17257:19 260:10 261:22264:5,11 275:14,20277:17 278:4 280:21281:3,21 285:18,20286:12

they’d 73:22They’ll 82:5they’re 13:2 19:4 22:21

23:20 25:12 26:1474:20 77:4,5 117:2120:22 130:8 133:12223:17 243:18 244:18251:17 255:3 257:20258:17,17 267:15,16282:1,2,6,10,14283:12 286:1

they’ve 19:18 128:3thing 75:11 95:14

204:22 207:14 214:6258:7 271:7 273:16277:9 278:18 279:1,2279:17

things 5:12 8:16 17:1624:17 78:22 117:5132:11,12 161:4,14161:15,19 173:2,4,16

194:16 203:5 218:8224:15 235:21 236:9243:17 246:4 249:14253:10 254:15 256:2264:22 265:5,11,13265:16 267:21 269:22270:4,16 272:1 276:4280:7,11,21 284:3,10284:16 285:16 288:22

think 8:12 11:12 12:2213:15 31:5 63:7 72:1573:1,22 76:21 77:479:1,16,19 80:1,781:16 84:3 86:6 109:3128:1,7 129:13 130:7130:10,12 131:5132:3,5 133:2 160:4,6160:13,20 161:1,3,15161:19 162:5 163:4163:10,21 165:16,21166:5,22 167:5,13,15169:6,8,11 170:16171:6 173:5 174:1,14174:20 198:15 199:21200:13 224:11 241:21242:10,10 244:14246:8 247:1,18248:10 252:4 254:7,8254:17,18 255:4256:14,18,19 258:19260:18 261:17 262:17263:4,10,12,14265:11,16 266:9,17266:17 267:9,12269:2,12,12,19,20272:3,6,14,14,18273:3,5,14 274:10,15275:8,21 276:9,10,12277:1,2,4,11 278:2,5279:8,12,13,15 280:7280:8,12,15,22281:10,16,18 282:6283:15,17,20 284:3284:17,20 285:5,8,12285:15,22 286:3,8,19287:7 288:4,7,11,18289:7,12,17 290:2,10290:14 291:5,7,9,21

thinking 14:18 86:2128:8 166:14 173:16205:10 245:16 247:19249:9 257:6 261:5269:3 272:8 274:12275:6,9,13 276:3288:8,9,13,15

third 70:5 89:12 98:1135:20 142:17 146:14150:15 156:6 157:1


324

168:16,17 182:3183:20 185:17

Thirteen 145:22 146:4Thirty-one 55:22thoroughly 78:15thought 34:8 43:19

77:11 118:20 167:16169:16 194:14 265:20289:3,22

thoughts 270:12thousands 7:19threads 132:11three 14:2 19:10 32:10

32:12 33:3,5 34:1936:21 64:1 67:3 68:171:14 74:12 77:788:12 89:9,21 90:594:5,6,13 95:20 97:1398:11,12 100:20101:7 102:1 107:3,12108:9 109:21 111:18111:19 113:11 114:4115:21 117:9 134:15135:2 138:11 146:7146:13,17 147:8,22148:1,3,8,8 149:8151:13,22 152:20157:22 158:22 160:1160:14 171:18 181:8181:18 183:14 186:14188:7,13,15,18 189:1189:15,19 209:19216:8,15 240:22244:8 276:4 287:21

three-year-olds 103:10threshold 249:18throw 271:17thunder 256:6 288:2THURSDAY 1:5tie 132:13 238:12

282:11tight 86:19till 281:14Tim 165:2 204:19time 3:17,19 9:2 13:19

14:17,20 15:14 18:1024:8 26:18 28:13,1428:16 38:2 75:8,884:13 91:9 109:8111:14 124:7 127:5131:22 133:1 166:14168:22 177:16 194:6199:6 208:1,6 209:11219:2,4 223:18 225:6226:3 228:10,22232:13 233:22 236:14241:15 251:2 258:9270:4 271:1 272:14

273:20 278:12 279:11285:10 286:13 290:19291:4,8

time-limited 13:7timeline 28:4times 96:6 108:17

146:13,17 152:21157:11 165:20

timing 35:21 53:22 54:554:16 55:6,13 58:3,1064:8,11 67:2,9 68:2,883:9 96:8 108:20109:6 139:22 141:21143:5 144:14 149:19152:7 161:14 182:8192:20

TIMOTHY 1:18tired 204:21tissue 160:5title 218:18titles 179:19tobacco 92:10today 4:9,12 10:18

12:16 14:15,18 15:116:8 19:5 24:14,2125:4,6 28:22 29:1931:3,15 32:2 34:2235:21 68:14 70:1188:6 90:7,18 134:15135:3 159:12 175:17176:12 177:3 204:22205:9,22 206:4,13207:15 212:2 233:19240:3 253:8 270:15291:22

today’s 28:19 280:18toddlers 60:13 99:20

206:2told 86:19 219:15tomorrow 4:9 14:15

19:6 24:14 25:7 29:831:3 283:20 286:6292:2

tomorrow’s 29:6,20tool 150:19 184:5tools 140:5 142:3 143:8

144:17 146:20 147:9149:21 274:7

tooth 229:15top 87:3 207:3 214:6

216:8 270:17top-level 205:9topic 6:22 11:22 37:9

159:5,13 197:3 260:5topics 6:8,19 7:4,12 8:1

8:4,5 9:18 10:1,212:21 18:19 32:3,4,1132:21 134:11

tortillas 220:4total 100:17 115:19

116:1,4,6,8,11,13118:11 119:7 154:5179:10 182:15 187:16192:5 194:5,8 196:14201:4,16,17 203:12203:13 208:2 209:11209:12 211:6,9212:14,17 214:22215:4 216:16,17217:2 218:8 220:17228:11 230:11,17234:2

tough 270:19track 26:22 85:3 168:1

214:15 217:9,15228:3

Traditional 12:4traits 138:8 153:11,18transcripts 14:5transition 51:13transparent 7:11

236:21travel 14:10 16:5

284:10traveling 284:19treated 203:21treatment 22:21 172:19tree 59:7,16,20 60:3

236:19tremendous 27:1

279:21trend 228:10trends 144:3 217:14

246:20 276:22 280:13285:17

trial 48:21,22 61:12127:15 146:20 157:13

trials 60:20 94:5 95:696:22 125:7 127:11146:5,8,9 148:1,4150:17,18 151:15152:19 157:7,8 160:2160:10 161:11 167:22168:2 278:16 281:5

tricky 34:1tried 236:8trimester 94:22 97:16

182:3true 39:19 40:1 203:12try 4:10 31:8 32:8

217:13 235:21 236:20247:19 268:10 280:16290:9

trying 11:12 85:2 96:7108:19 130:16 131:2170:18 225:14 236:13

245:11 251:11 274:13280:1,2 281:11286:13

tuna 157:14Turkey 109:4turn 16:22 30:9,16

31:11 87:11,13111:20

turning 99:10 124:3187:22

TusaRebecca 204:20tweak 73:1tweaking 264:11Twenty 289:12Twenty-four 139:15two 4:9,9 12:5 14:2

32:21 36:10 41:353:21 68:18 69:1177:19 83:22 91:1294:5,15 95:5 98:1199:22 100:20,21102:4,9 103:8 104:15107:12 108:21 110:9113:12 116:1 117:8120:14 121:9,10125:6 134:9 135:5,14137:5 145:8,20 146:9149:8,8,10,13 150:16151:14 152:18 154:19157:6,19 160:14162:10 166:20 171:18181:9,11 185:1,10188:20 189:21,22190:2,4 191:1,7,8,10191:11 206:1 207:7209:8 212:8 214:5,11217:20 224:19 232:1234:13 242:3 254:15277:13

two- 215:12,15 218:3227:18

two-plus 209:20type 11:4 50:8,11,14,19

51:1,8,15,21 52:655:15 65:15 73:478:11 79:3,5,11,1182:8,10,17 113:17129:3 139:22 141:22143:5 144:14 149:19152:8 161:2 176:19196:19 197:7 198:20217:10 233:6,15272:11

types 27:15 39:2,347:17 53:21 54:1,855:18,21 56:10,1557:5,16,20 58:6 59:163:10 64:10 65:5 67:4


325

67:20 68:4,11 76:2283:9 143:5 173:4180:5 181:19 188:6205:1 233:14 256:11271:10

UU-shape 164:14,17

171:19U.K 101:6 107:13 147:2U.S 22:5,6 38:16 41:7

69:7 98:18 107:12114:6,22 115:2,2,4,10139:19 224:20 231:10232:4

ubiquitously 223:17Uh-huh 79:12 81:11

170:14 171:5,8174:17 250:8 259:5

UL 238:20,21 241:2244:4

ULs 242:14,16ultimately 36:22umbilical 55:13umbrella 235:21unable 118:20unassignable 143:18

150:7uncaffeinated 192:17unclear 41:5 193:14uncomfortable 165:13uncontrolled 107:5

109:11underage 195:19underconsumed

210:11,15 222:15223:16 237:3 238:5239:8,21

undergo 159:1underreport 244:11

246:2underreporters 245:12underreporting 244:18

244:21 245:5,17understand 26:15understanding 80:1

170:10underway 89:19 91:20

176:2,13,15 199:6underweight 224:22

225:21,22 226:2228:13

unfavorably 65:10,1665:22

unfortunately 4:12273:5

unique 11:22 194:13United 208:2

University 165:3unpublished 128:15unrelated 281:17unsure 242:21untreated 227:19 228:6

228:8,11 229:14upcoming 135:12updated 43:5 261:8updates 2:5 28:7,21

29:7upper 173:17 211:1

242:4urine 127:18USDA 3:5,12 5:8 6:14

6:18 7:15 13:8 18:5USDA’s 26:1use 19:10 40:15 43:6

80:8,9 97:21 127:7133:6 168:8 179:14209:2 217:17 236:8236:13 239:6 251:18253:3 257:16 274:18280:1,2 281:5 284:14289:9

useful 29:20 73:2170:17 171:11 174:15274:14 285:13

user 285:14usually 14:17 80:2

283:14utilization 268:1 275:2utilizing 27:14

Vvalidated 182:4validity 127:6value 160:17 261:3values 200:4Van 4:13 134:6 174:7variability 164:20 182:7variable 75:9 144:16

149:21,22 188:5274:18

variables 179:12274:22

variation 125:15 192:11variations 256:19varied 38:21 83:19

94:20 101:14 107:19108:2 109:7 114:11130:14 135:17 140:1140:2 142:3,4,5 143:7143:9,10 144:17,19152:7

varieties 112:5variety 38:11 140:5

147:8 179:8,12 195:8256:7

various 96:6 108:17114:18 135:15 176:3177:19 181:18 243:17290:21 291:3

vary 146:20 215:2varying 186:11vast 166:8vegan 115:11 118:16

118:19vegetable 122:12

219:10,14 223:9vegetables 56:18 63:12

115:15 122:11 123:15124:12 207:9,9,12,13209:9 218:8 219:5,7219:10,12 222:4

vegetarian 115:11118:16 211:15

vein 254:13verbal 141:17 149:17verification 127:12vernacular 289:5versions 23:10 178:6

192:15versus 23:1 37:21 41:9

41:22 44:16 45:8,2046:1,9,14 47:14 48:348:5,9,13 49:7,1350:6,15,18,22 51:6,1765:7,8 73:3 74:1676:22 77:14,22 78:1099:3 108:16 109:5112:9 114:12,16116:22 128:4 178:9178:10 188:8 190:17235:1 251:13

vice 1:12 2:16 30:1872:3 76:18 78:2179:13 80:7,17 81:1184:15 86:5 87:12,21127:2 131:13,17132:15 162:15 163:15165:14 199:18 290:14

view 16:15 25:17 184:2viewing 1:10viewpoint 5:17vital 232:17 278:15

281:11vitamin 39:22 42:1,2,6

42:8,13,14,18 54:7,754:13,14 55:7,7 57:2157:21 70:4,7,16 71:171:4,6 88:19 119:13215:21 222:11,15,17239:9,20 240:13247:7,8 248:3

vitamins 36:7 113:3,4119:19,19 131:11,11

210:11vitro 22:9VOICE 183:10 212:22

222:1volume 35:3,8 106:19

108:8

Wwait 259:22waiting 281:14walk 212:12 214:1

258:20walking 182:22want 3:21 7:12 15:1

16:10,20 17:10 24:625:19 26:15 30:1134:17 37:4 60:5 76:1979:6 80:6 86:16 133:9133:16 134:4 159:8169:10 170:8 173:12174:8 175:3,10177:13 178:1 202:19218:19,20 219:1223:19 235:18 241:16242:20 244:3 245:8257:21 261:9 264:3271:7 278:7 280:5287:1,2 290:6

wanted 15:8 33:1148:18 59:4 88:8113:14 127:21 172:21180:16 194:16 217:5247:21 259:7 279:17287:10

wanting 254:14 256:5288:1

wants 75:1 78:19warranted 43:19warrants 69:16Washington 3:19wasn’t 130:2 184:1

192:16 203:19 247:13255:10,11

water 178:7,10 180:9182:13 190:21 191:2191:4,5,18 221:18

water-soluble 113:3119:19

way 74:17 76:8 84:5127:19 167:3,7,7170:17,22 171:1,4172:8 175:11 180:18184:2 191:5 217:5221:15 228:3 242:9243:9 250:20 252:14254:11 255:20 265:20266:20 274:7,14275:5,22 276:13


326

277:17 280:9 285:11285:12 288:7,10290:18

ways 127:17 173:2211:17 212:12

wayside 281:7we’d 217:10 224:9

235:22we’ll 4:10 14:19 15:19

15:21,22 18:6 19:528:6,12,17,20 29:631:5 37:18 52:8 86:1086:20 87:2 101:18112:12 120:4 126:9132:16,20 174:20180:10 193:22 198:20207:2 211:7 212:1214:14 224:6,17233:17,21 241:13273:2,3,6 276:12281:14 282:4

we’re 20:19 22:7,13,1722:21 23:17 24:7,1624:17 26:12 28:6,1733:11 76:9 81:1,4,586:7 91:16 93:11 96:7102:9 108:10,18,19112:4 113:22 130:16132:5 133:21 135:4144:6 156:10 167:6,7170:8 172:15 173:10174:2 178:4,13,16,21180:2,16,18,22182:14 195:13,18196:1 198:16 204:10205:10 206:11,17209:15,16,17 210:16210:19 211:10,12217:7 230:2 233:18236:9 240:2,14 241:9255:7 256:18 259:20263:11 269:9,18270:3 271:12 272:7273:8 277:7 278:13279:8,14 280:1,2283:19 285:4 286:20287:2 289:8,14291:21

we’ve 6:17 9:19 11:2112:22 13:5,8 15:519:7 22:2 27:17 29:1030:1 33:15 68:15,2272:5 77:13 86:6 92:8110:14 177:21,22180:1 193:21 197:6206:19 211:18 212:2212:2 214:2 215:3222:13 227:6 236:3

237:21 238:18 240:7244:10 270:15 275:8279:20 280:22 285:2285:10,16 286:12287:11 288:9 290:15290:17,20

weave 274:14 275:19291:7

web 19:20 212:14,19webcast 1:10webinar 16:4 17:7

132:19webpage 16:18website 6:7 14:3 15:22

16:16,21week 31:17 140:5

146:13,17 152:21157:12 182:2

weekly 88:4weeks 97:21 101:17

102:5,6,8 109:21,22114:8 146:13,18157:12 160:3

weighing 251:20weight 11:3 23:1 55:13

64:16,17 81:21 89:1191:17,18 120:17125:10,14,20 126:12126:13 175:22 177:4177:9 178:21 179:2179:16 181:4,16182:10 183:5,5,13,19185:5,8,14 186:5,7,14186:15,19,20 187:5187:10 188:11,12,15188:16,22 189:8,12189:17,18,20,21190:4,11 191:1,8,9,11191:14,18 192:1,22193:3,6 199:21 200:2200:4,12,14 203:9224:22 225:2,3,5228:21,21 246:9266:9

weight-for-length66:12

weights 125:4 246:10welcome 3:9,11,21 17:3

34:21welcoming 3:15went 17:16 84:2,3,5,11

95:19 129:16 130:2131:1 161:9 166:9212:16 248:18 260:11

what-not 282:2what’s 127:6 182:21

212:5 216:10 275:15whatnot 282:6

wheat 62:2,17,18,21white 101:10 115:5whites 226:22 227:4

230:15 235:7wide 38:11 237:2 238:4width 106:20 111:14wins 132:15wish 255:14women 93:2 95:11,22

97:11,17,22 98:7,1499:2,3 102:21 107:14107:18 108:12 109:17112:14,17 118:19122:9 123:2,18124:17 128:4,5136:13 179:4 206:3216:13 228:20 229:4229:5,10 230:6,16,20232:10,12 233:13,18234:3,20,21,22235:11 272:10,16

won’t 16:4 176:11219:4

wonder 82:9 129:20162:19 173:11 200:1266:19 277:17

wondered 201:8 253:5wonderful 199:12 258:7wondering 73:19 131:1

163:1 168:8 200:16274:19

word 46:5 218:21 224:3225:11

worded 45:14wording 76:10words 67:13 74:21

172:17 194:8 289:6work 5:19 9:6,13,16

10:6 12:19 13:15,1917:9 18:11 23:11,1926:16 27:1,16,21,2228:3,7 29:15,17 30:330:6 31:1 32:20 34:1844:11 53:14,16 68:1770:15,21 71:21 72:487:14 88:4,5 126:1,2126:20 128:15 132:1132:12 159:10 161:20162:1 165:22 175:4175:21 177:17 179:11180:4,19 196:3198:16 199:6,12205:12,12 235:18241:3 245:8 254:5256:20 267:21 270:7270:17 277:20 286:16289:21

worked 121:4 290:15

working 13:17 25:1826:21 28:2 29:3 31:131:16 84:20 89:15144:7 163:6 174:18176:22 193:16 204:12204:14 241:10 273:10287:2 289:2

works 167:17 259:17world 69:9 289:14worry 183:1worse 265:7 287:22worth 200:1wouldn’t 258:6wow 204:21 288:20write-up 75:12 78:9writing 281:14written 14:11 29:16

30:5 236:12wrong 109:3

XX 85:15

YY 85:15y’all 87:5yeah 76:21 79:2 80:16

80:16,17 81:9 83:485:2 128:12 130:5162:14 163:21 167:13169:2 200:10,10201:11,11 242:8244:20 246:1,13,18250:18 252:2,7,10,22253:20 254:5 255:16256:1,13 258:2,15259:1,6 261:7 267:2268:7,18 271:7 278:7

year 13:12 56:6 57:2,1459:9 61:1,14 63:1679:18 289:15

years 3:20 9:4 12:513:12 36:21 43:8 48:749:3,17 52:4,21 69:869:11 75:10 83:2291:12 96:1 102:1114:6 136:15 140:14140:16 141:18 144:16145:19,20 146:15147:8 148:6,11,12,15149:12,17 150:20151:22 152:2 153:1,1154:4,5 155:1,3,6,6156:18 157:8,21158:4,8 162:11 168:1195:14,22 206:1208:12,19 227:12285:17 289:12


327

yeast 220:3yesterday 78:3 116:18

224:3 261:10 262:18275:11 288:4

yogurt 62:6 221:16,21223:6

you’d 79:4,8 169:16244:15 260:9

you’ll 12:16 13:1922:12 23:21 26:1035:17 177:18 179:5195:6 205:11 209:19213:8

you’re 82:22 120:21131:2 132:11 133:5133:10,17 161:2,16170:18 207:14 244:9244:15 245:19

you’ve 18:19 84:1892:15 131:20 219:3241:20 244:14 251:4263:19

young 34:15 210:21212:7 220:11,12221:5,16,21 223:1224:18,19 238:20239:12 240:21

younger 160:15 195:17220:19 286:21 287:4

youngest 218:1youth 227:2youths 227:4 228:4YouTube 3:22 4:6

28:11 132:20 133:2

ZZ 85:15z-scores 66:12zero 109:5zinc 36:7 39:18,21

41:20 42:6,13,18 54:754:12 55:7 56:22 57:157:1,4 210:22 238:21239:3 241:1 242:6

0

11 50:8,11,14,20 51:8,21

73:4 78:11 79:5,1182:8,10,17 94:21247:10

1,000 4:161,831 100:171.4 225:31.5 228:131:00 28:1410 53:9 86:8 110:7

123:6 124:6 155:1,3157:8,21 168:1 214:6232:4

10-year 168:510:48 86:13100 107:17 157:10

161:16 167:14 207:4212:3,13 213:3 216:2219:20

100s 203:211 15:3 16:3 63:22

129:13 130:11,15140:14,16 141:18155:1 208:19 234:5235:9

11-1/2 49:311.5 49:17 52:41100 1:812 97:21 102:16 108:5

141:12 146:18 148:11149:17 157:8,12160:3 208:12 229:20

12- 227:14123 94:1413 47:15 110:4 142:19

144:16 152:2 227:20130 101:5134 2:1014 101:16 107:2,3

112:22 113:8 114:10141:12 146:15 153:1155:3 171:17 231:9234:12

14- 148:6 151:1614-year-olds 239:1314.5 155:5146 95:715 114:5 129:14 140:9

146:15 148:11 153:1154:4 171:17 215:11216:17

15-year-old 148:715-year-olds 151:1615.5 226:20150 4:1716 146:13 154:5 160:3

232:417 2:4 45:16 50:14 62:1

62:17 101:5 225:20229:16

17,000 176:617,775 29:1617.5 155:6175 2:1118 50:13 84:3,8 99:22

125:5 136:14 139:15145:18 147:8 148:12149:17 156:18 216:17

229:20 230:4 235:718- 226:1618.5 225:21189 107:1119 4:11 179:21 208:12

227:12 230:2,4234:15,21 235:6

19-year-olds 215:13,16218:3 226:16 227:14227:18

1930s 158:51980 36:15 44:15 53:19

123:8

22 11:4 51:1,15 52:6 79:3

79:11 176:19 198:20208:7 229:15 232:2272:12

20 4:12 46:17 96:197:21 101:9,16 140:8215:22 217:4 229:7229:16

20- 229:112000 198:8,92005 10:18 237:182006 232:202007 226:52007-08 208:1 230:62008 226:52010 10:92014 12:52015 10:7 198:19,21

199:2 256:202016 36:16 43:13,20

44:16 53:4,19 232:212017 91:6 122:3 123:82018 233:192019 5:15 14:13 43:10

53:1 121:82020 1:1,5 3:7,10 5:1

11:22 13:9,13,1614:14 30:7 198:8256:20 292:11

2020-2025 5:5205 2:1321 50:4 115:6 195:14,22

217:121,500 89:16214 176:723 1:5 36:22 37:6 38:13

227:1524 2:6 12:1 18:15 28:22

31:12 36:8,14 41:2044:6 47:2,20 53:1161:10 83:15 91:299:21 162:7,8 224:21241:10 271:1 273:9

292:1124-hour 117:425 3:20 94:17 109:21

137:11 192:2 233:226 107:15265,000 27:10270 2:1528 60:1629 102:8 114:6 229:2129- 108:12292 2:17

33 2:2 225:21 229:223,000 113:9 203:23.5 148:1430 8:1 27:6 50:10 96:1

115:1,130-year-old 108:12300 107:2031 2:7 54:9 58:5 101:9

217:234 107:15 231:10 233:235 43:8 44:22 52:21

116:3 231:1137 50:10 101:537-year 121:2239 58:7 101:5

44 226:154,512 106:224:28 292:94:30 14:1640 215:15,21 216:21

229:1 230:10 234:3400 109:542 89:1744 44:1745 232:21 235:1045,000 130:15450 94:1446 227:1947 235:248.6 234:1849 64:9 235:1

55 94:21 210:18 226:19

237:5 238:4 249:185-methyltetrahydrofo...

95:175,000 95:7 176:165.8 208:1350 27:14 207:12 210:7

214:21 216:22 219:9221:8 235:10 239:3

500 27:11


328

52 231:1754 232:2155 232:14,2256 118:18 212:658 209:2159 212:4,7 229:1 230:10

66 229:22 234:2 239:26,000 8:36.6 225:960 102:14 158:8 210:6

214:21622 94:264 229:8,16 232:14,2264-year-olds 229:1165 212:9 229:9,12,17

230:12 233:8,11,1566 32:5 68:1367 209:22

77 29:22 30:4 34:227.5 158:470 176:8 208:127600 179:18

88.3 225:380 216:4 234:18,2281 64:787 2:8

99 209:21 224:22 239:139:00 1:9 14:15 28:12

29:7 292:109:03 3:290 229:896 229:8

COURT REPORTERS AND TRANSCRIBERS 1323 RHODE ISLAND AVE., N.W.

(202) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com

C E R T I F I C A T E

This is to certify that the foregoing transcript

In the matter of:

Before:

Date:

Place:

was duly recorded and accurately transcribed under

my direction; further, that said transcript is a

true and accurate record of the proceedings.

-----------------------Court Reporter

329

Public Meeting

2020 Dietary Guidelines Advisory Committee

01-23-20

Houston, Texas

2020 DIETARY GUIDELINES ADVISORY COMMITTEE ...

Documents

Transcript of 2020 DIETARY GUIDELINES ADVISORY COMMITTEE ...