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Circulation. Author manuscript; available in PMC 2012 November 23.
Published in final edited form as:
PMCID: PMC3505019

Association of maternal weight gain in pregnancy with offspring obesity and metabolic and vascular traits in childhood

Abigail Fraser, PhD,1 Kate Tilling, PhD,1 Corrie Macdonald-Wallis, MSc,1 Naveed Sattar, PhD FRCPath,2 Marie-Jo Brion, PhD,1 Li Benfield, PhD,1 Andy Ness, PhD FFPH,3 John Deanfield, BA BCh FRCP,4 Aroon Hingorani, PhD FRCP,5 Scott M Nelson, PhD FRCOG,2 George Davey Smith, MD DSc,1 and Debbie A Lawlor, PhD FFPH1



We aimed to examine the association of gestational weight gain (GWG) and pre-pregnancy weight with offspring adiposity and cardiovascular risk factors.

Methods and results

Data from 5,154 (for adiposity and blood pressure) and 3,457 (for blood assays) mother-offspring pairs from a UK prospective pregnancy cohort were used. Random effects multilevel models were used to assess incremental GWG (median and range of repeat weight measures per woman: 10 (1, 17)). Women who exceeded the 2009 Institute of Medicine recommended GWG were more likely to have offspring with greater body mass index, waist, fat mass, leptin, systolic blood pressure, CRP and IL-6 levels, and lower HDLc and Apolipoprotein A1 levels. Children of women who gained less than the recommended amounts had lower levels of adiposity, but other cardiovascular risk factor tended to be similar in this group to offspring of women gaining recommended amounts. When examined in more detail greater pre-pregnancy weight was associated with greater offspring adiposity and more adverse cardiovascular risk factors at age 9. GWG in early pregnancy (0 to 14 weeks) was positively associated with offspring adiposity across the entire distribution, but strengthened in women gaining more than 500g/week. By contrast, between 14 and 36 weeks GWG was only associated with offspring adiposity in women gaining at least 500g/week. GWG between 14-36 weeks was positively and linearly associated with adverse lipid and inflammatory profiles with these associations largely mediated by the associations with offspring adiposity.


Greater maternal pre-pregnancy weight and GWG up to 36 weeks gestation are associated with greater offspring adiposity and adverse cardiovascular risk factors. Before implementing any GWG recommendations, the balance of risks and benefits of attempts to control GWG for short- and long-term outcomes in mother and child should be ascertained.

Keywords: Pregnancy, Gestational Weight Gain, Offspring cardiovascular risk factors, ALSPAC


A recent systematic review found evidence of associations of maternal pre-pregnancy weight and greater gestational weight gain (GWG) with a wide range of adverse perinatal health outcomes.1 Fewer studies have examined the long term effects of these on offspring health, and this systematic review and the recently revised 2009 US Institute of Medicine (IOM) guidance on GWG identified a need for further high quality research with long-term offspring outcomes.1,2

Several studies have examined associations of GWG with offspring adiposity and have consistently (all but one3) reported positive associations with offspring body mass index (BMI) in childhood,4-6 adolescence7 and adulthood.8 Other studies have examined the association with offspring blood pressure, with conflicting results.4,8-12 The two most recent and largest studies suggest positive associations of GWG with offspring blood pressure in childhood4 and adulthood8 that may be mediated by the association of GWG with offspring adiposity.8

No studies have examined associations of maternal pre-pregnancy weight or GWG with offspring cardiovascular risk factors other than BMI and blood pressure. Most previous studies have been unable to examine patterns of GWG with offspring outcomes. No studies have examined associations of the newly defined IOM GWG categories with offspring outcomes.2 Our aim was to examine associations of GWG and pre-pregnancy weight with a range of offspring cardiovascular risk factors (BMI, fat mass, waist circumference, blood pressure, lipids, apolipoproteins, adiponectin, leptin, IL-6 and C-reactive protein) using detailed repeat measures of gestational weight.


The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based birth cohort study that recruited 14,541 pregnant women resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992 ( There were 13,678 mother-offspring pairs from singleton live births who survived to at least one year of age; only singleton pregnancies are considered in this paper. We further restricted analyses in this paper to women with term deliveries (between 37-44weeks gestation): N = 12,447. Of these women 11,702 (94%) gave consent for abstraction of data from their obstetric records. 6,668 (57%) offspring of these 11,702 women attended the 9-year follow-up clinic. Of the 6,668 mother-offspring eligible pairs, complete data on GWG, offspring anthropometry, blood pressure and potential confounders were available for 5,154 (77% of attendees; 41% of 12,447 total). In addition, 3,457 (52% of attendees; 28% of total) had complete data on offspring blood assays.

Six trained research midwives abstracted data from obstetric medical records. There was no between-midwife variation in mean values of abstracted data and repeat data entry checks demonstrated error rates consistently < 1%. Obstetric data abstractions included every measurement of weight entered into the medical records and the corresponding gestational age and date. To allocate women to IOM categories (box 1) we used weight measurements from the obstetric notes and subtracted the first from the last weight measurement in pregnancy to derive absolute weight gain. Pre-pregnancy BMI was based on the predicted pre-pregnancy weight using multilevel models (see below) and maternal report of height.

Box 1

IOM recommended levels of gestational weight gain according to prepregnancy BMI categories2

Pre-pregnancy BMIRange of recommended absolute weight gain
in kg
Underweight (<18.5kg/m2)12.5-18
Normal weight (18.5-24.9kg/m2)11.5-16
Overweight (25-29.9kg/m2)7-11.5
Obese (>=30kg/m2)5-9

Maternal age, parity, mode of delivery (caesarean section / vaginal delivery) and the child’s sex were obtained from the obstetric records. Based on questionnaire responses, the highest parental occupation was used to allocate the children to family social class groups (classes I (professional / managerial) to V (unskilled manual workers)). Maternal smoking in pregnancy, categorised as - never smoked; smoked before pregnancy or in the first trimester and then stopped; smoked throughout pregnancy – was obtained from questionnaire responses.

Offspring weight and height were measured in light clothing, without shoes. Weight was measured to the nearest 0.1kg using Tanita scales. Height was measured to the nearest 0.1cm using a Harpenden stadiometer. WC was measured to the nearest 1mm at the mid-point between the lower ribs and the pelvic bone with a flexible tape and with the child breathing normally. Fat mass was assessed using dual energy X-ray densitometry (DXA). We examined BMI, WC and fat mass as continuously measured variables. We also examined binary outcomes of overweight/obese (BMI) and abdominally obese (WC) using age- and sex-specific thresholds for both child BMI (International Obesity Task Force) 14 and WC (>=90th percentile15 based on WC percentile curves derived for British children16).

Blood pressure was measured using a Dinamap 9301 Vital Signs Monitor with the child rested and seated and their arm supported at chest level on a table. Two readings of systolic and diastolic blood pressure (SBP and DBP) were recorded and the mean of each was used. Non-fasting blood samples were taken using standard procedures with samples immediately spun and frozen at −80°C. The measurements were assayed in plasma in 2008 after a median of 7.5 years in storage with no previous freeze-thaw cycles during this period. Lipids (total cholesterol, triglycerides and HDL-C) were performed by modification of the standard Lipid Research Clinics Protocol using enzymatic reagents for lipid determinations. Apolipoprotein (apo) A1 and apoB were measured by immunoturbidimetric assays (Hitachi/Roche). Leptin was measured by an in house ELISA validated against commercial methods. Adiponectin and high sensitivity IL-6 were measured by ELISA (R&D systems) and CRP was measured by automated particle-enhanced immunoturbidimetric assay (Roche UK, Welwyn Garden City, UK). All assay coefficients of variation were <5%. Non-HDLc was calculated as total cholesterol minus HDLc.

All pregnancy weight measurements (median number of repeat measurements per woman: 10,range: 1, 17) were used to develop a linear spline multilevel model (with two levels: woman and measurement occasion) relating weight (outcome) to gestational age (exposure). Full details of this statistical modelling are provided in supplementary web-material. High levels of agreement were found between estimated and observed weights (Web-table1 and Web-figure2). We scaled maternal pre-pregnancy weight and gestational weight change to be clinically meaningful – examining the variation in offspring outcomes per additional 1kg of maternal weight at conception and per 400g gain per week of gestation for GWG.2 Sensitivity analyses were conducted in which we repeated analyses including only those women who had at least 9 measurements of gestational weight.

Associations of offspring outcomes with the IOM categories and with the estimates of maternal pre-pregnancy weight and early-, mid- and late-pregnancy GWG were undertaken using linear regression. We explored the linearity of the relationships between all outcomes and the exposures using fractional polynomials. Where there was evidence of non-linearity, we used spline models to approximate the relationship. In the basic model we adjusted for offspring gender and age at the time of outcome measurement and for all models with fat mass for height and height-squared. We considered the following potential confounders: pre-pregnancy weight and GWG in the previous period (for the multilevel model exposures only), gestational age (for IOM categories only, since this is taken account of in the multilevel models), maternal age, parity, pregnancy smoking, social class, and mode of delivery. In order to examine whether effects were mediated by birthweight we adjusted for it and for non-adiposity outcomes we also examined potential mediation by adiposity. Triglycerides, leptin, CRP and IL-6 were log transformed in order to normalize their distributions. The resultant regression coefficients were exponentiated to give a ratio of geometric means per change in exposure. Results are presented jointly for mothers of female and male offspring as associations were all very similar in both genders.


Web-Table2 shows the characteristics of mothers and offspring. Table1 shows the association of IOM categories with adiposity and cardiovascular risk factors. Offspring of women who gained more than IOM recommended GWG were more likely to have greater BMI, WC, fat mass, leptin, SBP, CRP and IL-6 levels. They were also more likely to have lower HDLc and Apolipoprotein A1 levels. Children of women who gained less than recommended amounts had lower levels of adiposity, but other cardiovascular risk factors tended to be similar in this group to offspring of women gaining recommended amounts. IOM categories were not associated with DBP, non-HDLc, apolipoprotein B or triglyceride levels. Associations remained with adjustment for confounders. IOM categories were associated with binary outcomes of offspring overweight/obesity. In confounder adjusted models offspring of women who gained less than recommended, compared to those gaining recommended, levels had odds ratios of overweight/obesity (based on BMI) of 0.80 (0.67, 0.96) and of central obesity (based on waist) of 0.79 (0.69, 0.90) and offspring of mothers who gained more than recommended, compared to those gaining recommended, had odd ratios of overweight/obesity and central obesity of 1.73 (1.45, 2.05) and 1.36 (1.19, 1.57), respectively.

Table 1
Mean difference (95%CI) in offspring adiposity, blood pressure, lipids, apolipoproteins and inflammatory markers by IOM categories of maternal gestational weight gain (N=5154 or 3457 as indicated)

When we used multilevel models including repeat measures of gestational weight to estimate GWG in more detail, three distinct periods of GWG were identified – early-0-14 weeks; mid- >14-36 & late-pregnancy > 36 weeks (Figure1). In early pregnancy 20.0% of women either lost weight or remained stable. The majority of women in both mid- (99.9%) and late-pregnancy (95.7%) gained weight. Web-table3 shows the correlations between estimated pre-pregnancy weight, estimated GWG in early-, mid- and late-pregnancy, total absolute GWG over the whole pregnancy and birthweight. Most correlations were modest or weak. There was a strong inverse association of estimated GWG in early and late pregnancy, and a strong positive association of estimated GWG in mid and late pregnancy.

Figure 1
Weight (kg) by gestational age (weeks) for mothers of boys (dashed line) and girls (solid line)

Table2 shows the associations of estimated pre-pregnancy weight (per 1kg change) and estimated GWG (per 400 kg/wk) with offspring adiposity (BMI, WC, fat mass, leptin) and BP. Estimated pre-pregnancy weight was positively linearly associated with all four measurements of offspring adiposity and SBP and DBP, with these associations remaining after adjustment for confounders.

Table 2
Mean difference (95%CI) in offspring measurements of adiposity and blood pressure per 1kg change in maternal estimated pre-pregnancy weight and 400g/week estimated gestational weight gain (N=5154)

For associations of estimated GWG with adiposity and BP there was evidence of non-linearity with knots (changes in the direction and/or magnitude of association) at 0 and 500 g/week for GWG in early pregnancy and at 250 and 500 g/week in both mid- and late-pregnancy. Estimated GWG in all three periods generally had ‘U’ shaped associations with offspring adiposity, with null or inverse associations in women gaining low levels of weight, then null associations in the middle range of estimated GWG and then positive associations (model1, Table2). However, with adjustment for confounding factors (model2) the inverse associations at low levels of estimated GWG attenuated. In the confounder adjusted model, women who lost weight or did not gain weight in early-pregnancy (i.e. low estimated GWG women) had no association between their average gestational weight change per week and offspring adiposity. However, for those women (i.e. medium or high estimated GWG women) gaining weight during this period there was a positive association of estimated GWG with measures of offspring adiposity, which strengthened in women gaining on average 500g/week or more.

For mid-pregnancy estimated GWG up to 500g/week (i.e. low or medium estimated GWG) was not associated with offspring adiposity but offspring adiposity increased linearly with estimated GWG in mid-pregnancy after this level (i.e. in women with high GWG). There was no clear association of estimated GWG in late-pregnancy (beyond 36 weeks) with offspring adiposity or of estimated GWG in any periods with SBP or DBP. Associations of pre-pregnancy weight and estimated GWG with binary outcomes of adiposity (Web-Table4) were consistent with those seen for the continuously measured variables shown in Table2.

Table3 shows the associations of estimated pre-pregnancy weight and estimated GWG with lipids, apolipoproteins and inflammatory markers. For these outcomes there was no strong evidence of non-linear associations. Estimated pre-pregnancy weight and GWG in mid-pregnancy were positively associated with triglyceride levels and IL-6 and inversely associated with HDLc and ApoA1, though for triglyceride and ApoA1 confidence intervals were wide and included the null value. Estimated pre-pregnancy weight was also positively associated with non-HDLc, apolipoprotein B and CRP, but not with adiponectin. GWG in early- and late-pregnancy were not associated with lipids, apolipoproteins or inflammatory markers, with point estimates all close to the null value.

Table 3
Mean difference (95%CI) in offspring lipids, apo-lipoproteins and inflammatory markers per 1kg change in maternal estimated pre-pregnancy weight and 400g/week estimated gestational weight gain for blood assay results (N=3457)

Further adjustment for birthweight did not substantively alter any of the confounder adjusted models (Web-Tables5a-5c). All associations of maternal exposures that were present in confounder adjusted models were attenuated to the null with further adjustment for offspring fat mass (Web-Tables6a-6b). When these additional analyses were repeated with offspring BMI, WC or leptin instead of fat mass results were very similar to those presented.

We found no evidence that associations of estimated GWG with any of our outcomes were modified by pre-pregnancy BMI or weight, irrespective of whether this was estimated or observed, (all p-values for interaction > 0.2). When the analyses with estimated GWG were repeated with only those women who had at least 2, 4 and 3 measures in each time period respectively (i.e. total of at least 9 per woman across pregnancy) there was no substantial change to the results. Associations with estimated GWG in late-pregnancy did not differ substantively from those presented when we used absolute weight gain. Associations did not differ substantively with the removal of women whose first antenatal measurement was after 15 weeks or whose last measurement was before 35 weeks.


To our knowledge this is the most detailed study of the association of GWG and pre-pregnancy weight with offspring adiposity and associated cardiovascular risk factors. Women who gained more weight than recommended by the 2009 IOM criteria had offspring who were more adipose and had higher levels of SBP, CRP, IL-6 and lower levels of HDLc and Apolipoprotein A1. When we examined these associations in more detail we found that any weight gain in the first 14 weeks of gestation was incrementally associated with increased offspring adiposity, but between 14 and 36 weeks gestation only GWG above 500g/week was associated with increased offspring adiposity. By contrast the cardiovascular risk factors that were associated with GWG (triglycerides, HDLc, apolipoprotein A1 and IL-6) were associated with GWG linearly across all levels of GWG in mid-pregnancy (>14-36 weeks). Pre-pregnancy weight was positively associated with offspring adiposity and adverse cardiovascular risk factors but we found no interaction between pre-pregnancy weight/BMI and GWG in their associations with offspring outcomes. The associations of greater than recommended IOM weight gain, pre-pregnancy weight and GWG in mid-pregnancy with adverse lipid profiles and inflammatory markers appeared to be largely mediated by offspring adiposity.

There are a number of mechanisms that could explain our findings. First, our results could reflect tracking in size across the lifecourse. However, consistent with previous studies,4,5,8 we found only weak associations of pre-pregnancy weight and GWG with birthweight and adjustment for birthweight did not substantively alter associations. Furthermore, GWG in early pregnancy (up to 14 weeks) was associated across the entire distribution with offspring adiposity (as compared to GWG >14 to 36 weeks which was only associated if women gained 500g or more/week), but at this stage most GWG will be related to maternal fat deposition and not to fetal growth. Second, offspring could inherit their mother’s genetic potential to gain weight. We are unable to assess this possibility in our study. Third, mothers with greater GWG may engage in lifestyles (high energy diet and low levels of physical activity) during and after their pregnancy that promote weight gain and they may pass them on to their offspring. Fourth, greater maternal pre-pregnancy adiposity and GWG might programme greater adiposity and cardiovascular risk in offspring resulting from the persistent and adverse influences on the fetus arising from the greater delivery of glucose, amino acids and free fatty acids to the developing fetus in utero.17 The continuous association, across the whole distribution, of GWG up to 14 weeks with offspring adiposity provides some support for this since most weight gain in this period will be an increase in maternal fat stores, with concomitant increases in circulating glucose, amino acids and free fatty acids. The fact that GWG in this period was not statistically strongly associated with cardiovascular risk factors might be a consequence of limited statistical power and ideally replication of our findings in larger cohorts with detailed repeat measurements of weight in pregnancy would be useful, though we are unaware of other larger cohorts with such detailed measurements. Finally, our results may be due to chance. We examined a large number of maternal exposure-offspring outcomes in this study. However, we feel that this is a strength. Our work builds importantly on previous publications examining only offspring adiposity and blood pressure and using very limited information on GWG. We acknowledge that replication of these associations in larger, but with similarly detailed exposure and outcome measurements, would be beneficial.

The levels of attrition in ALSPAC are similar to those found in previous studies. Offspring of women from higher socioeconomic position, more educated women and those of older age are more likely to attend follow-up clinics in ALSPAC.13 However, we found no evidence of differences in distributions of GWG between women whose offspring had outcome measurements and those whose offspring did not (all p-values > 0.4). The consistency of associations between adiposity measurements and circulating leptin levels suggests that exclusion of those participants who did not complete a blood test did not bias these associations. Offspring blood tests were completed on non-fasting blood samples but the majority of measures are not appreciably altered by this approach.18-20 We used maternal self-report of height to calculate pre-pregnancy BMI which may be inaccurate. With respect to associations examined (outcomes assessed in offspring 9-years later) any measurement error would be non-differential and therefore the expectation would be that it might bias results towards the null.

The fact that GWG in mid-pregnancy was only associated with offspring adiposity in women gaining at least 500g/week suggests that between 14-36 weeks women could ‘safely’ (with respect to offspring adiposity) gain 11kg, which is close to the range of recommended levels of weight gain across the whole of pregnancy for normal and overweight women according to IOM categories, but we found no evidence that this (or other) associations differed by maternal pre-pregnancy BMI categories. It should be acknowledged that in this cohort just 7% of women were obese pre-pregnancy and obesity prevalence is greater for contemporary women. The lack of association with GWG beyond 36 weeks may reflect the fact that the length of this period varies for different maternal-offspring pairs. Very large sample sizes would be required to determine whether different patterns in this late stage were important.

Maternal pre-pregnancy weight was more consistently associated with offspring adiposity and a wider range of cardiovascular risk factors in offspring than were any measurements of GWG and this finding supports initiatives aimed at maintaining healthy weight in women of reproductive age. Long term follow-up of on-going RCTs aimed at controlling GWG21 and Mendelian randomization studies (using genetic variants that are robustly associated with maternal adiposity and fat gain in pregnancy as instrumental variables)22 are necessary to establish whether the associations we have found are causal. The extent to which antenatal care guidelines should be modified to monitor GWG and promote adherence to IOM levels requires additional research that establishes clear benefits and lack of important risk in the short and long term for both mother and child.

Supplementary Material

Online Supplementary Information


We are grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. DA Lawlor, K Tilling, A Fraser and C Macdonald-Wallis had full access to all of the data in the study and jointly take responsibility for its integrity.

Funding This work was funded by a grant from the NIH: National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK077659).

The UK Medical Research Council (MRC), the Wellcome Trust and the University of Bristol provide core-funding support for ALSPAC.

The blood assays were funded by a British Heart Foundation (BHF) grant (PG07/002).

The MRC and the University of Bristol provide core-funding for MRC CAiTE.

AF is funded by a MRC research fellowship and MJB is funded by a Wellcome Trust Henry Wellcome research fellowship.

ADH is funded by a BHF Senior Research Fellowship (FS05/125)


Ethical Approval Ethical approval for all aspects of data collection was obtained from the ALSPAC Law and Ethics Committee (IRB 00003312) and the Local Research Ethics Committee.

Competing interests There are no competing interests


1. Viswanthan M, Siega-Riz AM, Moos M-K, Deierlein A, Mumford S, Knaack J, Thieda P, Lux LJ, Lohr KN. Outcomes of Maternal Weight Gain, Evidence Report/Technology Assessment No. 168. Agency for Healthcare Research and Quality; Rockville, MD: 2008. AHRQ Publication No. 08-E009.
2. Rasmussen KM, Yaktine AL, editors. Weight Gain During Pregnancy: Reexamining the Guidelines. Committee to Reexamine IOM Pregnancy Weight Guidelines; Institute of Medicine; National Research Council; [accessed for this paper 10th June 2009]. 2009. pre-publication uncorrected proofs available at [PubMed]
3. Whitaker RC. Predicting preschooler obesity at birth: the role of maternal obesity in early pregnancy. Pediatrics. 2004;114:e29–e36. [PubMed]
4. Oken E, Taveras EM, Kleinman KP, Rich-Edwards JW, Gillman MW. Gestational weight gain and child adiposity at age 3 years. Am J Obstet Gynecol. 2007;196:322. [PMC free article] [PubMed]
5. Moreira P, Padez C, Mourao-Carvalhal I, Rosado V. Maternal weigh gain during pregnancy and overweight in Portuguese children. Int J Obes 0 AD. 31:608–614. [PubMed]
6. Wrotniak BH, Shults J, Butts S, Stettler N. Gestational weight gain and risk of overweight in the offspring at age 7 y in a multicenter, multiethnic cohort study. Am J Clin Nutr. 2008;87:1818–1824. [PubMed]
7. Oken E, Rifas-Shiman SL, Field AE, Frazier AL, Gillman MW. Maternal gestational weight gain and offspring weight in adolescence. Obstet Gynecol. 2008;112:999–1006. [PMC free article] [PubMed]
8. Mamun AA, O’Callaghan M, Callaway L, Williams G, Najman J, Lawlor DA. Associations of Gestational Weight Gain With Offspring Body Mass Index and Blood Pressure at 21 Years of Age: Evidence From a Birth Cohort Study. Circulation. 2009;119:1720–1727. [PubMed]
9. Clark PM, Atton C, Law CM, Shiell A, Godfrey K, Barker DJ. Weight gain in pregnancy, triceps skinfold thickness, and blood pressure in offspring. Obstet Gynecol. 1998;91:103–107. [PubMed]
10. Godfrey KM, Forrester T, Barker DJ, Jackson AA, Landman JP, Hall JS, Cox V, Osmond C. Maternal nutritional status in pregnancy and blood pressure in childhood. Br J Obstet Gynaecol. 1994;101:398–403. [PubMed]
11. Margetts BM, Rowland MG, Foord FA, Cruddas AM, Cole TJ, Barker DJ. The relation of maternal weight to the blood pressures of Gambian children. Int J Epidemiol. 1991;20:938–943. [PubMed]
12. Laor A, Stevenson DK, Shemer J, Gale R, Seidman DS. Size at birth, maternal nutritional status in pregnancy, and blood pressure at age 17: population based analysis. BMJ. 1997;315:449–453. [PMC free article] [PubMed]
13. Golding J, Pembrey M, Jones R. ALSPAC--the Avon Longitudinal Study of Parents and Children. I. Study methodology. Paediatr Perinat Epidemiol. 2001;15:74–87. [PubMed]
14. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320:1240–1243. [PMC free article] [PubMed]
15. Zimmet P, Alberti G, Kaufman F, Tajima N, Silink M, Arslanian S, Wong G, Bennett P, Shaw J, Caprio S. The metabolic syndrome in children and adolescents. Lancet. 2007;369:2059–2061. [PubMed]
16. McCarthy HD, Jarrett KV, Crawley HF. The development of waist circumference percentiles in British children aged 5.0-16.9 y. Eur J Clin Nutr. 2001;55:902–907. [PubMed]
17. Taylor PD, Poston L. Developmental programming of obesity in mammals. Exp Physiol. 2007;92:287–98. [PubMed]
18. Rifai N, Merrill JR, Holly RG. Postprandial effect of a high fat meal on plasma lipid, lipoprotein cholesterol and apolipoprotein measurements. Ann ClinBiochem. 1990;27:489–93. [PubMed]
19. Poppitt SD, Keogh GF, Lithander FE, Wang Y, Mulvey TB, Chan YK, McArdle BH, Cooper GJ. Postprandial response of adiponectin, interleukin-6, tumor necrosis factor-alpha, and C-reactive protein to a high-fat dietary load. Nutrition. 2008;24:322–329. [PubMed]
20. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA. 2007;298:309–316. [PubMed]
21. Dodd JM, Crowther CA. Robinson JS Dietary and lifestyle interventions to limit weight gain during pregnancy for obese of overweight women: a systematic review. Acta Obstetricia et Gynecologica. 2008;87:702–706. [PubMed]
22. Lawlor DA, Harbord RM, Sterne JAC, Timpson NJ, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Statistic in Medicine. 2008;27:1133–63. [PubMed]