Communities’ Role in Childhood Obesity Prevention:...

Communities’ Role in Childhood Obesity Prevention: BMI

S. Sonia Arteaga, PhD, National Institutes of Health

Biennial Childhood Obesity ConferenceJuly 17, 2019

NHLBI Contract No. HHSN268201000041C

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• I have no disclosures or conflict of interest

Presenter Disclosure


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• Rationale

• Community programs and policies: Behavioral objectives and results

• Community programs and policies: Intensity score and results

• Strengths and limitations

• Conclusions and key takeaway messages

Overview


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Rationale


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• The prevalence of obesity is almost 19% for children and adolescents

Many local programs and policies address childhood obesity, but they have not been systematically assessed in a common way.

There is natural variation in many aspects of these programs and policies, including intensity level, duration, funding, target

population, and how they are implemented

Rationale


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Attributes related to intensity:

– Duration (e.g., Higher—Ongoing; Lower—one time)

– Reach (e.g., Higher—21% or more of children in area; Lower—1-5%)

– Behavioral intervention strategy used (e.g., Higher—Modifying access or policy change; Lower—Providing information)

Other attributes, including:

– Primary goal

– Behavioral objective addressed

– Sector in which implemented

CHARACTERIZING Community Programs/Policies by Key Attributes

Fawcett et al, AJPM, 2015, 49(4), 636-641


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Behavioral Objectives


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Research Question: Do communities with more-comprehensive Community programs and policies have children with lower BMI and waist circumference after adjusting for community, household, and individual characteristics?

Frongillo et al. AJPM 2017; 53(5): 576-583


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• Each community program or policy was coded for specific behaviors targeted for nutrition (e.g. increase consumption of fruits and vegetables) or physical activity (e.g. increase PA in after school programs)

• 24 unique target behaviors: 11 nutrition, 13 physical activity

What is a behavioral objective?


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1010Distribution of CPPs by Behavioral Objective—Nutrition, All Communities

Collie-Akers et al. Pediatr Obes 2018;13 Suppl 1:56-63


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1111Distribution of CPPs by Behavioral Objective—Physical Activity, All Communities

Collie-Akers et al. Pediatr Obes 2018;13 Suppl 1:56-63


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1212Scatter plots of mean BMI vs. CPP nutrition target behavior score & CPP physical activity target behavior score

19.5

2020

.521

21.5

2222

.5

5 10 15 5 10 15

Nutrition Physical ActivityM

ean

of C

hild

BM

I

CPP target behavior scoreGraphs by Type

Frongillo et al. AJPM 2017; 53(5): 576-583


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• Communities showed variation in the number and types of behavior change objectives addressed

• Community investment to implement more comprehensive CPPs—those targeting a greater number of distinct behaviors—was associated with lower child BMI

• Target multiple behaviors to achieve intended results

Take away messages for community efforts to promote healthier weight

19.5

2020

.521

21.5

2222

.5

5 10 15 5 10 15

Nutrition Physical Activity

Mean

of C

hild B

MI

CPP target behavior scoreGraphs by Type


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Intensity Score


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Research questions: • What is the relationship over the past decade

between the intensity of community programs and policies (CPPs) in the 130 communities and BMI in resident children?

• How does this relationship vary by individual, household, community factors?

Longitudinal relationship between community programs and policies and BMI

Strauss et al. 2018; 53(5): 576-583Strauss et al. Pediatr Obes 2018;13 Suppl 1:82-92


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Design: Observational study (2010-2016)

Community – public high school catchment area

• Cross-sectional (2013-2015)- BMI, diet, physical activity, program/policy , school assessments

• Retrospective (2003-2015) - previous 10 years of data on

-Children (medical record abstraction) AND

-Communities (program/policy review)

Study Design

Arteaga et al. AJPM 2015;49(4): 615-23

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Intensity Score Behavioral intervention strategy used, e.g.,

- Higher—Modifying access or policy change; - Lower—Providing information

Duration e.g., - Higher—Ongoing; - Lower—one time

Reach e.g., - Higher—21% or more of children in area; - Lower—1-5%

Standardized to 0-1 for ease of interpretation

CPPs and Intensity score

Fawcett et al. AJPM 2015;49(4): 636-41


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• Height and weight information abstracted from pediatric healthcare provider records

• 31,620 BMI measures among 3,317 children

• Statistical process control applied to time series of BMI for each child, removing 1,512 extreme BMI outliers and 90 children

• Combined with data from the household visit

• 33,335 BMI observations among 3,227 children

BMI: Medical Records and household visits


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Gender Male 48.7Female 51.3

Grade K-2 38.73-5 31.96-8 29.3

Family Income

<20K 25.620-50K 37.550-100K 18.5>100K 18.3

Race White only 71.6African American only 19.1Multi-racial including AA 2.9 Multi-racial excluding AA 1.7Other 4.6

Ethnicity Hispanic/Latino 44.6Not Hispanic/Latino 55.4

Medical Records Sample Characteristics (%) N=3,227

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3,227 children had valid medical records and ht/wtmeasurements

Medical records were more likely to be available if household income was higher and the children were older

On average there were 9.33 BMI measures per child recorded through the medical record review

BMI: Medical Records


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• Examined BMI as a function of CPP intensity score, using longitudinal models

• Integrated current and retrospective information into a time series of community-level program and policy intensity scores

• Used linear mixed model to adjust for– Correlation among participants within schools,

nested within communities– Correlation among repeated measures on children

over time– Random intercept and slope for BMI and CPP

relationship within each community– Potential effect modifiers at community and child

levels

Data Analysis


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• Identified appropriate, parsimonious subset of covariates:

Base model adjusted for separate polynomial age-curves (by gender) and height

Covariate Adjusted Model included child/family level factors (e.g., ethnicity, family income, parental employment status, and seasonality) and community factors (e.g., education, race, and poverty)

• CPP Indices then added to the Base Model and Covariate Adjusted Model to assess the unadjusted and covariate-adjusted relationship between BMI and CPPs

• Multiple imputation dealt with missing information at community, school, and child/family levels

Data Analysis


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2323Distribution of total intensity scores for the 130 communities over the 10-year study period. N=9,681

Collie-Akers et al. Pediatr Obes 2018; 13 Suppl 1: 64-71.


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2424Relationship Between BMI and Standardized Community Program and Policy Intensity Scores

1.4 BMI units

Strauss et al. Pediatr Obes 2018;13 Suppl 1:82-92


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• Relationship between BMI and CPP intensity (highest observed – lowest observed):

– -1.6 kg/m2 in minimally-adjusted model (p=.0028)

– -1.4 kg/m2 in fully-adjusted model (p=0.0077)

Results

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Child/Family Modifiers: Higher intensity scores were related to lower BMI for non-Hispanic white children, children in grades k-2 and 6-8, families with incomes greater than $50,000, and children whose parents are well-educated

- Relationships did not differ by child gender or parental employment status

Community Modifiers: Higher intensity scores were related to lower BMI in high proportion non-Hispanic white communities

- Did not differ by region, urbanicity or income.

Results


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• Unknown/inconsistent data quality for BMI data collected through Pediatric Medical Record Review

• Key informant recruitment/access/recall for CPPs

• Required use of multiple imputation methods to account for missing data from home-visit

• Recruitment of children through schools did not allow for probability-based sampling – therefore potential biases are unknown

Study Limitations


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• Large and diverse samples of communities and families; Oversampled Hispanic and African American Communities

• Extensive BMI repeated-measures information collected through pediatric medical record review

• First study to document and assess relationships between CPPs and BMI

Study Strengths


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• A lagged effect of community programs and policies on BMI.

• Higher intensity of community policies and programs was associated with lower increase in child BMI, suggesting plausible benefit.

• While there is a relationship between the intensity of CPPs and BMI, it varies depending upon the modifiers.

Conclusions


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• Differential exposures/opportunities e.g., quality and availability of food options; safety of places for physical activity

• Differential vulnerabilities/capabilities

– e.g., food insecurity, health literacy

• Differential consequences

– e.g., time and effort, culturally appropriate

Social determinants—Why less benefit for groups experiencing health inequities?


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• Community factors modify the influence of community programs/policies on lower BMI in children

• Those communities benefitting more: Predominately White, Non-Hispanic

• Place (and race/ethnicity) matters in assuring conditions for healthier weight among all children

Take away messages for community efforts to promote healthier weight


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• Planning, implementation, and evaluation of obesity prevention efforts would benefit from systematic measures of the intended (actual) “dose” of interventions

• What matters in achieving a sufficient “dose” to improve BMI outcomes:

o Total intensity (amount/kind) of CPPs

o Targeting of multiple behavioral objectives

o Penetration through multiple sectors

o Time—multiple years of exposure

o Equity and Justice require assuring more intense and targeted dose with populations and places experiencing health inequities

OVERALL Take Away Messages


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Questions???

Contact Information

S. Sonia Arteaga

[email protected]

Thank you!

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