The Association Between Pregnancy Weight Gain and Birthweight

Articles

984 www.thelancet.com Vol 376 September 18, 2010

Lancet 2010; 376: 984–90

Published OnlineAugust 5, 2010

DOI:10.1016/S0140-6736(10)60751-9

See Comment page 937

Department of Medicine, Children’s Hospital, Boston,

MA, USA (D S Ludwig MD); and Department of Economics, Columbia University, New

York, NY, USA (Prof J Currie PhD)

Correspondence to:Dr David Ludwig, Department of

Medicine, Children’s Hospital Boston, 300 Longwood Ave,

Boston, MA 02115, USAdavid.ludwig@childrens.

harvard.edu

The association between pregnancy weight gain and birthweight: a within-family comparisonDavid S Ludwig, Janet Currie

SummaryBackground Excessive weight gain during pregnancy seems to increase birthweight and the off spring’s risk of obesity later in life. However, this association might be confounded by genetic and other shared eff ects. We aimed to examine the association between maternal weight gain and birthweight using state-based birth registry data that allowed us to compare several pregnancies in the same mother.

Methods In this population-based cohort study, we used vital statistics natality records to examine all known births in Michigan and New Jersey, USA, between Jan 1, 1989, and Dec 31, 2003. From an initial sample of women with more than one singleton birth in the database, we made the following exclusions: gestation less than 37 weeks or 41 weeks or more; maternal diabetes; birthweight less than 500 g or more than 7000 g; and missing data for pregnancy weight gain. We examined how diff erences in weight gain that occurred during two or more pregnancies for each woman predicted the birthweight of her off spring, using a within-subject design to reduce confounding to a minimum.

Findings Our analysis included 513 501 women and their 1 164 750 off spring. We noted a consistent association between pregnancy weight gain and birthweight (β 7·35, 95% CI 7·10–7·59, p<0·0001). Infants of women who gained more than 24 kg during pregnancy were 148·9 g (141·7–156·0) heavier at birth than were infants of women who gained 8–10 kg. The odds ratio of giving birth to an infant weighing more than 4000 g was 2·26 (2·09–2·44) for women who gained more than 24 kg during pregnancy compared with women who gained 8–10 kg.

Interpretation Maternal weight gain during pregnancy increases birthweight independently of genetic factors. In view of the apparent association between birthweight and adult weight, obesity prevention eff orts targeted at women during pregnancy might be benefi cial for off spring.

Funding US National Institutes of Health.

IntroductionThe fetal origin of adult disease, or prenatal programming, has been the subject of much study during the past two decades. Compelling evidence exists in support of the hypothesis, proposed by Barker and colleagues,1 that undernutrition during pregnancy and low birthweight increase risk of diabetes and cardiovascular disease in adulthood.2,3 Indeed, the adverse eff ect of perinatal undernutrition on long-term health might equal or exceed that of many conventional risk factors measured in adulthood. In view of the rising prevalence of obesity, a variant of the original Barker hypothesis has been formulated wherein overnutrition during pregnancy and high birthweight might cause obesity and related disorders in adulthood.4–9 According to this idea, excessive maternal bodyweight or weight gain during pregnancy perturbs the intrauterine environment during fetal development, producing permanent changes in the hypothalamus, pancreatic islet cells, adipose tissue, or other biological systems that regulate bodyweight. Research in animals has provided an experimental basis for this hypothesis.10,11 Levin and Govek10 studied diet-sensitive female rats on standard or high-energy diets before and during gestation. Progeny of the mothers in the high-energy diet group gained more weight and had

higher leptin concentrations than did progeny of mothers in the standard diet group, even though off spring from both groups were fed the same diet. In man, high birthweight predicts body-mass index (BMI) and adverse health outcomes later in life.12–21

Results of observational studies have generally shown direct associations between maternal bodyweight or weight gain during pregnancy and birthweight or infant adiposity.22–26 Moreover, maternal adiposity tends to be more strongly related to birthweight27,28 or childhood BMI29 than does paternal adiposity. However, these studies involving comparisons between individuals have fundamental limitations, most notably confounding due to genetic and environmental factors. For example, excessive maternal weight gain might be related to high birthweight simply because a mother and her infant share obesity-related genes. Therefore, we aimed to examine the association between maternal weight gain, as a measure of overnutrition during pregnancy, and birthweight using state-based birth registry data that allowed comparison of outcomes from several pregnancies in the same mother. This within-subject design serves to reduce or eliminate potential confounding by genetic, sociodemographic, and other individual characteristics.

Articles

www.thelancet.com Vol 376 September 18, 2010 985

MethodsStudy design and populationData for this population-based cohort study were from individual vital statistics natality records covering all births in Michigan and New Jersey, USA, from Jan 1, 1989, to Dec 31, 2003. These records provide information about birth outcomes and maternal characteristics, including weight gain during pregnancy. A summary of the data fi les, including covariates, is available from the US National Center for Health Statistics. The state of Michigan provided a fi le that identifi ed children born to the same mother. For New Jersey, we did this match in the state’s Department of Health offi ces on the basis of mother’s name, race, birth date, and, in some cases, address. The fi le was then de-identifi ed.

From an initial sample of singleton births, we made the following exclusions: gestational age less than 37 weeks or 41 weeks or more (to focus on term pregnancies); maternal diabetes; birthweight less than 500 g or more than 7000 g (ie, extreme values that could result from data entry error); missing data for pregnancy weight gain; and births to mothers with only one child in the database, per study design. All reported pregnancies for the included mothers were retained in the sample. The study was undertaken with approval from the institutional review board at Columbia University, New York, USA.

Data collectionAll data used in this study were mandated by state law to be routinely obtained and recorded in birth records. The variables were: pregnancy weight gain, birthweight, an indicator for diabetes during pregnancy, week of gestation, maternal age, maternal education, maternal marital status, maternal race and ethnicity, maternal smoking, adequacy of prenatal care,30 method of delivery, sex of child, child parity, and year of birth.

Physicians were responsible for completing or verifying birth records. Previous assessment suggests that data for birthweight obtained by this method are highly reliable.31 Physician report of pregnancy weight gain might have somewhat lower reliability. Particularly for women with delayed prenatal care, physicians are likely to establish pregnancy weight gain partly on the basis of mothers’ self-report. Consistent with this possibility, the weight gain variable shows evidence of heaping in the raw data with rounding to 10-lb increments, accounting for the irregular weight gain frequency distribution in fi gure 1, especially around the 18–20 kg (40 lb) category. However, one validation study that compared birth certifi cate data to medical records for a random sample of births in North Carolina reported an exact concordance for pregnancy weight gain in 82·8% of cases.32 Moreover, pregnancy weight gain obtained from birth records, similar to those used in our study, has been associated with many infant and maternal health outcomes,33 providing evidence of validity. Prepregnancy weight and height were not routinely recorded on birth certifi cates. Therefore, prepregnancy

BMI could not be assessed in this study. Because the data fi les link births to the same mother, we could not establish whether siblings had the same father.

Statistical analysisOur primary hypothesis was that maternal weight gain during pregnancy is positively associated with birthweight, independent of confounding factors. The sample selection criteria serve to reduce or eliminate some sources of potential confounding (eg, maternal diabetes or prematurity), but others remain. Of the remaining potential confounders, some were measured by variables in our data (smoking), but others are not (genetic determinants of birthweight). Our strategy was to control for observable confounders through inclusion in the statistical models, and to control for unvarying unobservable confounders by comparing several pregnancies in the same mother. Using this approach, we kept the eff ect of interindividual diff erences in genes and other potentially relevant factors to a minimum.

Our models regressed a measure of birthweight (continuous or dichotomous) on indicators for the following categories of maternal weight gain: 0–2 kg,

0 10 20 30 40 500

5

10

15

20

Prop

ortio

n of

mot

hers

(%)

Weight gain (2 kg intervals)

0 2000 4000 6000 80000

2

4

6

8

10

Prop

ortio

n of

infa

nts (

%)

Birthweight (g)

A

B

Figure 1: Distribution of (A) pregnancy weight gain and (B) birthweight

For National Center for Health Statistics data see http://www.cdc.gov/nchs/births.htm

Articles


>2–4 kg, >4–6 kg, and so on, until >22–24 kg, >24 kg. Hence, the eff ects of weight gain were not constrained to be linear. Unless otherwise noted, all of our specifi cations allowed this fl exible relation between the measure of birthweight and the measure of maternal weight gain. The other covariates in all our models were: sex of child, maternal education (less than high school, high school, some college, college or more), maternal marital status, an indicator for maternal smoking during pregnancy, child parity (indicators for parity of 1, 2, 3, 4, 5 or more; NB, the fi rst birth recorded in the data was not necessarily the mother’s fi rstborn child), indicators for each year of maternal age, and indicators for each year of birth. We included year of birth as a covariate to control for possible secular trends in birthweight unrelated to maternal weight gain during pregnancy. Where categorical data for controls were missing, we also included controls for missing variables.

For models in which birthweight was a continuous variable, we did two analyses. First, we estimated models that included maternal fi xed eff ects using the XTREG command in STATA (release 11). Any maternal covariate that did not change with time was controlled by this procedure.34 Thus, the eff ect of the mother’s weight before the fi rst observed pregnancy was controlled for, as was the eff ect of maternal height (even though neither were recorded in our data). Although fi xed-eff ects estimates might be less precise than are ordinary least-squares models, this issue is of little concern in a large sample size.35 We accounted for the presence of multiple values for each mother by using the CLUSTER command in STATA to correlate and adjust the errors. This procedure did not change our mean estimates or confi dence intervals, and therefore data are presented without clustering.

As an alternative, conceptually simpler, analytical method to control for covariates that change between but not within individuals, we calculated diff erences in weight gain and in birthweight between adjacent pregnancies for each mother. We then regressed changes in birthweight on categories of changes in maternal weight gain (<–12 kg, ≥–12 to –10 kg, and so on, until >10 to 12 kg, and >12 kg), including those of the other covariates described above which can vary between births for the same mother. The sample in these models was restricted to sibling pairs in whom the diff erence in gestational age was less than 3 weeks. In these fi rst-diff erence models, changes in the year of birth and in maternal age were the same. Also, most changes in parity were equal to one. Therefore, we included indicators for each year of maternal age at the time of the fi rst observed birth, and indicators for parity of the fi rst birth observed in the dataset.

We also estimated models using a dichotomous high birthweight (>4000 g) measure as the dependent variable. The independent variables were categories of maternal weight gain (0–2 kg, >2–4 kg, >4–6 kg, and so on, until >24 kg). We estimated a fi xed-eff ect logit (or conditional logit) using the CLOGIT procedure in STATA.36 These

models controlled for the same variables as did the fi xed-eff ects models. Finally, we did subgroup analyses to examine for eff ect modifi cation. On the basis of our primary results, we constrained the main eff ect of pregnancy weight gain to be linear—ie, the weight gain categories included in the previous models were excluded, and only a single continuous weight gain variable (and its interaction) was included.

We chose 8–10 kg as the reference category for pregnancy weight gain because this category was within the 7·0–11·5 kg range recommended for overweight women by the Institute of Medicine,37 and because the mean BMI in adult women in the USA was within the overweight range. All data are presented as means and SDs for maternal cohort characteristics or 95% CIs for outcome data.

Role of the funding sourcesFunding sources had no role in study design; in the collection, analysis, and interpretation of data; in writing of the report; or in the decision to submit for publication. DSL had full access to all data analyses and JC had full access to all primary data in the study; both had fi nal responsibility to submit for publication.

ResultsFrom an initial sample size of 2 359 843 singleton births, we made the following exclusions: gestational age less than 37 weeks or 41 weeks or more (358 833 births);

Participants included in analysis sample*

Participants in analysis sample plus those missing data for weight gain†

Maternal characteristics

Maternal weight gain (kg) 13·7 (5·7) ··

Maternal age (years) 27·7 (5·8) 27·7 (5·8)

Mother’s education (years) 13·2 (2·5) 13·1 (2·5)

Number of off spring recorded in dataset

2·41 (0·73) 2·46 (0·79)

Parity 2·17 (1·24) 2·17 (1·25)

Infant characteristics

Birthweight (g) 3453 (473) 3446 (477)

Birthweight >4000 g 138 303 (12%) 159 288 (12%)

Sex (male) 594 297 (51%) 692 899 (51%)

Ethnic origin

African American 221 263 (19%) 273 563 (20%)

Hispanic 116 622 (10%) 134 818 (10%)

White/other 826 865 (71%) 949 179 (70%)

Maternal smoking 154 221 (13%) 173 357 (13%)

Adequate prenatal care 649 940 (56%) 751 452 (55%)

Gestation length (weeks) 39·3 (1·1) 39·3 (1·1)

Data are mean (SD) or n (%). *513 501 mothers and 1 164 750 off spring. †590 626 mothers and 1 357 560 off spring, including siblings of off spring for whom information about pregnancy weight gain was missing.

Table: Descriptive characteristics of mothers and infants

Articles


maternal diabetes (75 665 births); extreme values for birthweight (2225 births); missing data for pregnancy weight gain (192 810 births); and births to mothers with only one child in the database (1 204 249 births). The fi nal study sample consisted of 1 164 750 singleton births to 513 501 mothers. The table shows descriptive characteristics of mothers and infants included in the analysis. These characteristics were similar to the 77 125 women and 192 810 off spring excluded from the study because of missing data for pregnancy weight gain.

Figure 1A shows that many women exceeded recommended limits for weight gain during a singleton pregnancy, currently established as 11·5–16 kg for those of normal weight before pregnancy, 7–11·5 kg for those who were overweight, and 5–9 kg for those who were obese.37 Weight gain of more than 20 kg occurred in 139 040 (12%) pregnancies. As expected, pregnancy weight gain was positively associated with length of pregnancy (p<0·0001) and inversely associated with smoking (p<0·0001). Figure 1B shows that the birthweight distribution was roughly normal, with very few infants weighing more than 5000 g.

Figure 2A, using a fi xed-eff ects model, shows a remarkably consistent association between maternal weight gain and birthweight (β 7·35, 95% CI 7·10–7·59, p<0·0001). Relative to the reference category of 8–10 kg, infants of mothers who gained 20–22 kg weighed 103·8 g (97·0–110·6) more on average, whereas infants of mothers who gained greater than 24 kg weighed 148·9 g (141·7–156·0) more. Figure 2B plots coeffi cient estimates from the fi rst-diff erence model. As expected, women who gained the same amount of weight in both pregnancies had infants of similar mean birthweight. Women who gained over 12 kg more in the second pregnancy had second infants who weighed 107·6 g (98·2–117·0) more than fi rst infants, and those who gained over 12 kg less in the second pregnancy had second infants who weighed 85·8 g (93·5–78·1) less. The distribution of changes in weight gain suggested that on average women gained slightly less weight for higher order pregnancies. The 10th, 50th, and 90th percentiles of the distribution of the diff erence in pregnancy weight gain between an older sibling and the next youngest sibling were 6·24 kg, –0·45 kg, and –8·62 kg—ie, most women gained similar amounts of weight during subsequent pregnancies.

Figure 3 shows the odds ratio for birthweight higher than 4000 g according to pregnancy weight gain from the conditional logit models. Relative to the reference category of 8–10 kg, the odds ratio of having a baby with a high birthweight was 1·72 (1·59–1·86) for women who gained between 20 kg and 22 kg, and 2·26 (2·09–2·44) for women who gained more than 24 kg.

To test for residual confounding, we excluded women who had ever smoked, those who delivered by caesarean section, and those who had any pregnancy with gestational length less than 39 weeks or more than 40 weeks. The

results of these analyses did not diff er from those of our other models (data not shown). To examine the reliability of the independent variable, we did an analysis limited to the 208 067 women and their 469 472 infants for whom adequate prenatal care was shown on the birth certifi cate for all siblings. The results were very similar to those of the full group (data not shown). The women excluded from this analysis would have less data in the medical record on which an accurate assessment of pregnancy weight gain could be based, causing the physician to rely more on maternal self-report.

We also looked for evidence of eff ect modifi cation in subgroup analyses that included a main eff ect of weight gain (β) and an interaction describing the diff erential weight gain between the main group and the subgroup (γ). On the basis of our primary results, we constrained the main eff ect of pregnancy weight gain to be linear. The slope for the association between pregnancy weight gain and birthweight was slightly smaller for African American

0–2>2–4

>4–6>6–8

>8–10

>10–12

>12–14

>14–16

>16–18

>18–20

>20–22

>22–24>24

–50

0

50

100

150

Diffe

renc

e in

birt

hwei

ght (

g)

Pregnancy weight gain (kg)

<–12

–12–<–10

–10–<–8

–8–<

–6

–6–<

–4–4

–<–2

–2–<0

>0–2>2–4

>4–6>6–8

>8–10

>10–12>120

0

50

–50

–100

100

Diffe

renc

e in

birt

hwei

ght (

g)

Difference in weight gain (kg)

A

B

Figure 2: Associations between pregnancy weight gain and birthweight(A) Data from fully adjusted fi xed-eff ect model; diff erences in birthweight are relative to the reference group (infants of mothers who gained 8–10 kg). (B) Data from fi rst diff erence model; values of variables from the fi rst observed pregnancy were subtracted from those of the second observed pregnancy for each mother. Red bands show 95% CIs.

Articles


participants (β 7·63, 7·34 to 7·91; γ –1·05, –1·60 to –0·50) and larger for male infants (β 7·01, 6·69–7·33; γ 0·66, 0·26–1·05) than for the main group. There was no eff ect of increased maternal age (age ≥28 years: β 7·39, 7·23 to 7·71; γ –0·11, –0·54 to 0·34) or state (Michigan: β 7·62, 7·23 to 8·00; γ –0·46, –0·95 to 0·04).

DiscussionWeight gain during pregnancy has been associated with high birthweight and measures of adiposity early in life. Our study, using a state-based registry with more than one million singleton births, provides evidence for a causal association that is independent of shared genes. We noted that every kg increase in pregnancy weight gain increases birthweight by about 7·35 g, and that variation in pregnancy weight gain through the recorded range can aff ect birthweight by about 200 g. Because high birthweight predicts BMI later in life,12,14,17–19,21 these fi ndings suggest that excessive weight gain during pregnancy could raise the long-term risk of obesity-related disease in off spring. High birthweight might also increase risk of other diseases later in life, including asthma, atopy, and cancer.13,15,16,20

With respect to potential mechanisms, the physiological pathways that might link fetal overnutrition to high birthweight have been described. During pregnancy, insulin resistance develops in the mother to shunt vital nutrients to the growing fetus.38 Excessive weight or weight gain during pregnancy exaggerates this normal process by further increasing insulin resistance and possibly also by aff ecting other maternal hormones that regulate placental nutrient transporters.39 The resulting high rate of nutrient transfer stimulates fetal insulin secretion, overgrowth, and increased adiposity. Indeed, maternal postprandial glycaemia in the third trimester, even within the normal range, is strongly associated with birthweight.40 The mechanisms whereby in-utero over-nutrition and related physiological derangements aff ect bodyweight later in life remain speculative,9,11,39 though

the crucial role of maternal hyperglycaemia has been further emphasised by recent research.41

The primary limitations of this study surround the possibility of measurement error and confounding. The pregnancy weight gain variable, more so than birthweight, is subject to recall and reporting bias that might vary by BMI, education, and level of prenatal care, among other factors. However, the within-subject design would tend to keep systematic bias arising from such factors to a minimum. Thus, some individuals might tend to underestimate and others to overestimate weight gain, although each would likely do so in a similar fashion across several pregnancies. Any random measurement error would tend to diminish apparent eff ect size,42 causing our estimates to be conservative. Additionally, results of a secondary analysis excluding individuals with inadequate prenatal care—a group especially subject to error in the measurement of pregnancy weight gain—were very similar to those of the primary analysis. Other evidence of reliability derives from associations in the expected direction here (with length of pregnancy and smoking) and elsewhere (with pre-eclampsia, cephalopelvic disproportion, failed induction, and caesarean delivery)33 involving the pregnancy weight gain variable obtained from birth certifi cates. Furthermore, results of a validation study showed an exact concordance between pregnancy weight gain obtained from birth certifi cates and from medical records 82·8% of the time.32

Our within-subject design should eff ectively eliminate confounding by genetic and other unvarying factors. An important study limitation is the absence of information about maternal BMI before pregnancy. We address this limitation to some degree through the use of fi xed-eff ects models and adjustment for age and parity, controlling in part for BMI before the fi rst pregnancy and weight change between pregnancies. In any event, we contend that absence of prepregnancy BMI could not account for the primary fi ndings for a fundamental statistical reason. For a confounder to account for a positive association between an independent variable and a dependent variable, it must be associated with both in the same way, either positive or inverse. But prepregnancy BMI is inversely associated with pregnancy weight gain,43–45 and positively associated with birthweight.22–26

Additionally, we used a secondary analytical approach to examine for residual confounding, comparing diff erences in subsequent pregnancies for each mother (fi gure 2B). We found that weight gain had a similar eff ect on birthweight irrespective of which pregnancy had greatest weight gain. This eff ect would not have occurred if prepregnancy BMI had diff ered between pregnancies in a systematic way that confounded the fi ndings. We recognise that pregnancy weight gain might aff ect birthweight diff erently in women with high compared with low pre pregnancy BMI (ie, eff ect modifi cation). However, the similarity in fi ndings from analyses of subgroups expected to diff er in prepregnancy

0–2>2–4

>4–6>6–8

>8–10

>10–12

>12–14

>14–16

>16–18

>18–20

>20–22

>22–24>24

0·5

1·0

1·5

2·0

2·5

Odd

s rat

io

Pregnancy weight gain (kg)

Figure 3: Odds ratio for high birthweight (>4000 g)Red bands show 95% CIs.

Articles


BMI, such as older and younger women or black and white women, provides evidence against this possibility (and against confounding). Moreover, unrecognised eff ect modifi cation by pre pregnancy BMI, diet quality, level of physical activity, or other factors would not threaten the validity of our primary fi ndings.

Several other methodological issues merit consider ation. Concern about reverse causation can largely be dismissed, because increased fetal weight would make a small contribution (<10%) to the associated increase in maternal weight. Even so, we cannot rule out the possibility that hormonal or metabolic signals from the fetus might have an additional eff ect on maternal weight. Some women with unrecognised diabetes might have been present in our sample and have contributed to the observed eff ect size, especially if they developed the disease in some but not all of their pregnancies. Furthermore, diagnostic criteria and screening practices might have changed during the study. We aimed to minimise these eff ects by excluding individuals who reported diabetes during any pregnancy, a group that would be at highest risk during every pregnancy. Additionally, there was no signifi cant diff erence in a subgroup analysis of older women, who are at substantially increased risk for this complication.46 Finally, we recognise the absence of information about paternity as a study limitation. However, the similar eff ect of maternal weight gain on birthweight in fi rst and second pregnancies, irrespective of which had greater weight gain, argues against any systematic bias. In conclusion, our fi ndings suggest that excessive maternal weight gain during pregnancy increases birthweight; in view of the apparent association between high birthweight and adult adiposity, pregnancy might be an advantageous time to initiate obesity prevention eff orts.

ContributorsDSL and JC both contributed to the design of the study and drafting of

the report. DSL formulated the study hypotheses and JC supervised data

collection and analysis.

Confl icts of interestWe declare that we have no confl icts of interest.

Acknowledgments Data collection for this project was supported under US National

Institutes of Health grant R21 HD055613-01. DSL was supported in part

by a career grant from the National Institute of Diabetes and Digestive

and Kidney Diseases (K24 DK082730) and a grant from the New Balance

Foundation. Cecilia Machado provided assistance with research. We

thank Cara Ebbeling, Matthew Gillman, Steven Gortmaker,

Joseph Majzoub, and Eric Rimm for critical review of the report.

References1 Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes

mellitus: the thrifty phenotype hypothesis. Diabetologia 1992; 35: 595–601.

2 Barker DJP, Godfrey KM, Gluckman PD, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life. Lancet 1993; 341: 938–41.

3 Barker DJ, Osmond C, Forsen TJ, Kajantie E, Eriksson JG. Trajectories of growth among children who have coronary events as adults. N Engl J Med 2005; 353: 1802–09.

4 Ebbeling CB, Pawlak DB, Ludwig DS. Childhood obesity: public-health crisis, common sense cure. Lancet 2002; 360: 473–82.

5 Barker DJ. Obesity and early life. Obes Rev 2007; 8: 45–49.

6 Eriksson J, Forsen T, Tuomilehto J, Osmond C, Barker D. Size at birth, childhood growth and obesity in adult life. Int J Obes Relat Metab Disord 2001; 25: 735–40.

7 Oken E, Gillman MW. Fetal origins of obesity. Obes Res 2003; 11: 496–506.

8 Pettitt DJ, Jovanovic L. Birth weight as a predictor of type 2 diabetes mellitus: the U-shaped curve. Curr Diab Rep 2001; 1: 78–81.

9 Whitaker RC, Dietz WH. Role of the prenatal environment in the development of obesity. J Pediatr 1998; 132: 768–76.

10 Levin BE, Govek E. Gestational obesity accentuates obesity in obesity-prone progeny. Am J Physiol 1998; 275: R1374–79.

11 Wu Q, Suzuki M. Parental obesity and overweight aff ect the body-fat accumulation in the off spring: the possible eff ect of a high-fat diet through epigenetic inheritance. Obes Rev 2006; 7: 201–08.

12 Araujo CL, Hallal PC, Nader GA, et al. Eff ect of birth size and proportionality on BMI and skinfold thickness in early adolescence: prospective birth cohort study. Eur J Clin Nutr 2009; 63: 634–39.

13 Eriksson M, Wedel H, Wallander MA, et al. The impact of birth weight on prostate cancer incidence and mortality in a population-based study of men born in 1913 and followed up from 50 to 85 years of age. Prostate 2007; 67: 1247–54.

14 Gillman MW, Rifas-Shiman S, Berkey CS, Field AE, Colditz GA. Maternal gestational diabetes, birth weight, and adolescent obesity. Pediatrics 2003; 111: e221–26.

15 Harder T, Plagemann A, Harder A. Birth weight and subsequent risk of childhood primary brain tumors: a meta-analysis. Am J Epidemiol 2008; 168: 366–73.

16 Hjalgrim LL, Westergaard T, Rostgaard K, et al. Birth weight as a risk factor for childhood leukemia: a meta-analysis of 18 epidemiologic studies. Am J Epidemiol 2003; 158: 724–35.

17 Leong NM, Mignone LI, Newcomb PA, et al. Early life risk factors in cancer: the relation of birth weight to adult obesity. Int J Cancer 2003; 103: 789–91.

18 Parsons TJ, Power C, Logan S, Summerbell CD. Childhood predictors of adult obesity: a systematic review. Int J Obes Relat Metab Disord 1999; 23: S1–107.

19 Pietilainen KH, Kaprio J, Rasanen M, Winter T, Rissanen A, Rose RJ. Tracking of body size from birth to late adolescence: contributions of birth length, birth weight, duration of gestation, parents’ body size, and twinship. Am J Epidemiol 2001; 154: 21–29.

20 Remes ST, Patel SP, Hartikainen AL, Jarvelin MR, Pekkanen J. High birth weight, asthma and atopy at the age of 16 yr. Pediatr Allergy Immunol 2008; 19: 541–43.

21 Wei JN, Li HY, Sung FC, et al. Birth weight correlates diff erently with cardiovascular risk factors in youth. Obesity (Silver Spring) 2007; 15: 1609–16.

22 Eastman NJ, Jackson E. Weight relationships in pregnancy. I. The bearing of maternal weight gain and pre-pregnancy weight on birth weight in full term pregnancies. Obstet Gynecol Surv 1968; 23: 1003–25.

23 Fleten C, Stigum H, Magnus P, Nystad W. Exercise during pregnancy, maternal prepregnancy body mass index, and birth weight. Obstet Gynecol 2010; 115: 331–37.

24 Getahun D, Ananth CV, Peltier MR, Salihu HM, Scorza WE. Changes in prepregnancy body mass index between the fi rst and second pregnancies and risk of large-for-gestational-age birth. Am J Obstet Gynecol 2007; 196: e531-538.

25 Simpson JW, Lawless RW, Mitchell AC. Responsibility of the obstetrician to the fetus. II. Infl uence of prepregnancy weight and pregnancy weight gain on birthweight. Obstet Gynecol 1975; 45: 481–87.

26 Verhaeghe J, van Bree R, Van Herck E. Maternal body size and birth weight: can insulin or adipokines do better? Metabolism 2006; 55: 339–44.

27 Guillaume M, Lapidus L, Beckers F, Lambert A, Bjorntorp P. Familial trends of obesity through three generations: the Belgian-Luxembourg child study. Int J Obes Relat Metab Disord 1995; 3: S5–9.

28 Okun N, Verma A, Mitchell BF, Flowerdew G. Relative importance of maternal constitutional factors and glucose intolerance of pregnancy in the development of newborn macrosomia. J Matern Fetal Med 1997; 6: 285–90.

Articles


29 Lawlor DA, Smith GD, O’Callaghan M, et al. Epidemiologic evidence for the fetal overnutrition hypothesis: fi ndings from the mater-university study of pregnancy and its outcomes. Am J Epidemiol 2007; 165: 418–24.

30 Kiely JL, Kogan MD. Prenatal care. In: Wilcox LS, Marks JS, eds. From data to action: CDC’s public health surveillance for women, infants, and children. Atlanta, GA, USA: US Centers for Disease Control and Prevention, 1994: 105–18.

31 Northam S, Knapp TR. The reliability and validity of birth certifi cates. J Obstet Gynecol Neonatal Nurs 2006; 35: 3–12.

32 Buescher PA, Taylor KP, Davis MH, Bowling JM. The quality of the new birth certifi cate data: a validation study in North Carolina. Am J Public Health 1993; 83: 1163–65.

33 DeVader SR, Neeley HL, Myles TD, Leet TL. Evaluation of gestational weight gain guidelines for women with normal prepregnancy body mass index. Obstet Gynecol 2007; 110: 745–51.

34 Allison PD. Fixed eff ects regression models. Vol 160. Los Angeles, USA: Sage Publications, 2009.

35 Kaufman JS. Commentary: why are we biased against bias? Int J Epidemiol 2008; 37: 624–26.

36 Chamberlain G. Analysis of covariance with qualitative data. Rev Econ Stud 1980; 47: 225–38.

37 Kuehn BM. Guideline for pregnancy weight gain off ers targets for obese women. JAMA 2009; 302: 241–42.

38 Ryan EA. Hormones and insulin resistance during pregnancy. Lancet 2003; 362: 1777–78.

39 Jansson N, Nilsfelt A, Gellerstedt M, et al. Maternal hormones linking maternal body mass index and dietary intake to birth weight. Am J Clin Nutr 2008; 87: 1743–49.

40 Parretti E, Mecacci F, Papini M, et al. Third-trimester maternal glucose levels from diurnal profi les in nondiabetic pregnancies: correlation with sonographic parameters of fetal growth. Diabetes Care 2001; 24: 1319–23.

41 Hillier TA, Pedula KL, Schmidt MM, Mullen JA, Charles MA, Pettitt DJ. Childhood obesity and metabolic imprinting: the ongoing eff ects of maternal hyperglycemia. Diabetes Care 2007; 30: 2287–92.

42 Alwin DF. Margins of error: a study of reliability in survey measurement. Hoboken, NY, USA: Wiley-Interscience, 2007.

43 Dietz PM, Callaghan WM, Sharma AJ. High pregnancy weight gain and risk of excessive fetal growth. Am J Obstet Gynecol 2009; 201: e51–56.

44 Nohr EA, Vaeth M, Baker JL, Sorensen TI, Olsen J, Rasmussen KM. Pregnancy outcomes related to gestational weight gain in women defi ned by their body mass index, parity, height, and smoking status. Am J Clin Nutr 2009; 90: 1288–94.

45 Wise LA, Palmer JR, Heff ner LJ, Rosenberg L. Prepregnancy body size, gestational weight gain, and risk of preterm birth in African-American women. Epidemiology 2010; 21: 243–52.

46 King H. Epidemiology of glucose intolerance and gestational diabetes in women of childbearing age. Diabetes Care 1998; 21: B9–13.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

The Association Between Pregnancy Weight Gain and Birthweight

Documents

Transcript of The Association Between Pregnancy Weight Gain and Birthweight