Maternal weight gain in different periods of pregnancy and childhood cardio-metabolic outcomes. The Generation R Study

Abstract

Background:

Excessive gestational weight gain seems to be associated with offspring cardio-metabolic risk factors. Little is known about the critical periods of gestational weight gain. We examined the associations of maternal weight gain in different periods of pregnancy with childhood cardio-metabolic risk factors.

Methods:

In a population-based prospective cohort study from early pregnancy onwards among 5908 mothers and their children, we obtained maternal prepregnancy weight and weight in early, mid and late pregnancy. At the age of 6 years (median: 72.6 months; 95% range: 67.9, 95.8), we measured childhood body mass index (BMI), total body and abdominal fat distribution, blood pressure and blood levels of lipids, insulin and c-peptide.

Results:

Overall, the associations of maternal prepregnancy weight with childhood outcomes were stronger than the associations of maternal gestational weight gain. Independent from maternal prepregnancy weight and weight gain in other periods, higher weight gain in early pregnancy was associated with higher childhood BMI, total fat mass, android/gynoid fat mass ratio, abdominal subcutaneous fat mass and systolic blood pressure (P-values<0.05). Independent associations of maternal weight gain in early pregnancy with childhood abdominal preperitoneal fat mass, insulin and c-peptide were of borderline significance. Higher weight gain in mid pregnancy was independently associated with higher childhood BMI, total and abdominal subcutaneous fat mass and systolic blood pressure (P-values<0.05). The associations for childhood cardio-metabolic outcomes attenuated after adjustment for childhood BMI. Weight gain in late pregnancy was not associated with childhood outcomes. Higher weight gain in early, but not in mid or late pregnancy, was associated with increased risks of childhood overweight and clustering of cardio-metabolic risk factors (odds ratio (OR) 1.19 (95% confidence interval (CI): 1.10, 1.29) and OR 1.20 (95% CI: 1.07, 1.35) per standard deviation increase in early gestational weight gain, respectively).

Conclusions:

Higher weight gain in early pregnancy is associated with an adverse cardio-metabolic profile in offspring. This association is largely mediated by childhood adiposity.

Introduction

Increased maternal gestational weight gain (GWG) may influence the long-term cardio-metabolic health of offspring.1 The mechanisms underlying these associations are not known, and may depend upon the timing of GWG.1, 2, 3, 4 GWG is a complex trait. Maternal GWG in early pregnancy largely reflects maternal fat deposition, whereas GWG in mid and late pregnancy largely reflects maternal and amniotic fluid expansion, and growth of the fetus, placenta and uterus.5 Higher placental transfer of nutrients, such as glucose and free fatty acids in mothers with increased fat deposition, may lead to permanent fetal and childhood adaptations in appetite, energy metabolism and neuro-endocrine function, and predispose individuals to a greater risk of cardio-metabolic disease in later life.1, 6 In line with this hypothesis, previous studies suggested that weight gain in early pregnancy is associated with offspring body mass index (BMI), whereas weight gain in mid pregnancy tended to be associated with the offspring's metabolic and inflammatory biomarkers.4, 7, 8 It is not known whether these associations are independent from other periods of GWG or explained by pregnancy complications and infant growth characteristics. Also, previous studies did not examine associations of specific periods of GWG with detailed childhood body fat distribution and cardio-metabolic measures.

Therefore, we aimed to identify critical periods of maternal GWG for cardio-metabolic health in the offspring. In a population-based prospective cohort study among 5908 mothers and their children, we examined the associations of specific periods of GWG and excessive GWG with childhood cardio-metabolic risk factors. We also examined whether these associations were independent from GWG in other periods or explained by pregnancy, birth and infant characteristics.

Methods

Study design

This study was embedded in the Generation R Study, a population-based prospective cohort study from early pregnancy onwards in Rotterdam, the Netherlands.9 The local Medical Ethical Committee approved the study. Written informed consent was obtained from all mothers. All pregnant women were enrolled between 2001 and January 2006. Response rate at birth was 61%. Between March 2008 and January 2012, at the age of 6 years (median: 72.6 months; 95% range: 67.9, 95.8) children were invited to a dedicated research facility in the Erasmus Medical Center, Sophia Children’s Hospital for detailed cardio-metabolic follow-up measurements. In total, 8614 mothers had information about at least one maternal weight measurement during pregnancy available and gave birth to singleton live born children. We excluded children without follow-up data available. The population for analysis included 5908 (69%) mothers and their children. (Flow chart is given in Supplementary Figure S1.) A detailed study description is given in Supplementary Figure S2.

Maternal anthropometrics and gestational weight gain

At enrolment (median: 13.9 wks of gestation; 95% range: 9.9, 24.4), we measured maternal height (cm) and obtained information about maternal weight (kg) just before pregnancy by questionnaire. Information about maternal prepregnancy weight was available for 4874 (82.5%) mothers. We calculated prepregnancy BMI (kg m2). Maternal weight was further assessed one to three times during pregnancy depending on the gestational age at enrolment; in early, mid and late pregnancy. We measured maternal weight without shoes and heavy clothing at median gestational ages of 13.2 weeks (95% range: 9.8, 17.4), 20.4 weeks (95% range: 18.5, 23.5) and 30.2 weeks (95% range: 28.5, 32.8). Data were available for 4584 (77.6%), 5548 (93.4%) and 5678 (96.1%) mothers, respectively. In a subgroup of 3118 (52.8%) mothers, information about maximum weight during pregnancy was assessed by questionnaire 2 months after the delivery. Based on the timing of maternal weight measurements within our study cohort, we defined early, mid and late GWG, using self-reported and measured maternal weight data, as: start of pregnancy until 13.4 weeks of gestation (95% range: 9.9, 18.9); from 13.4 until 29.9 weeks of gestation (95% range: 20.5, 31.4); from 29.9 until 39.0 weeks of gestation (95% range: 32.8, 42.0), respectively. Using this method, information about early, mid and late GWG was available for 4062 (68.8%), 4715 (79.8%) and 2852 (48.3%) mothers.

Among the subgroup of mothers with maximum weight during pregnancy available (N=3118), we defined excessive GWG in relation to maternal prepregnancy BMI according to Institute of Medicine guidelines (for underweight and normal weight mothers: total weight gain>16 kg; for overweight mothers: total weight gain>11.5 kg; for obese mothers: total weight gain>9 kg).5

Childhood body fat and cardio-metabolic outcomes

We measured children’s height and weight without shoes and heavy clothing and calculated BMI. Childhood underweight, normal weight, overweight and obesity were defined by the International Obesity Task Force cut-offs.10 Body fat was estimated by dual-energy X-ray absorptiometry (iDXA, General Electrics –Lunar, 2008, Madison, WI, USA), which estimates the percentages of fat, lean and bone mineral masses for the whole body and specific regions with the enCORE software v.12.6 (GE Healthcare Lunar).11 Total fat mass was calculated as percentage of total body weight, as estimated by dual-energy X-ray absorptiometry. We calculated the android/gynoid fat mass ratio. As described previously, we performed abdominal ultrasound examinations to measure preperitoneal and subcutaneous abdominal fat thicknesses.12 Preperitoneal and subcutaneous fat mass areas were measured as areas of 2 cm length along the midline starting from the reference point in direction of the navel.

Systolic and diastolic blood pressure was measured at the right brachial artery, four times with one-minute intervals, using the validated automatic sphygmanometer Datascope Accutor Plus TM (Paramus, NJ, USA).13 We calculated the mean systolic and diastolic blood pressure values using the last three blood pressure measurements.

We obtained 30-min fasting venous blood samples and measured total cholesterol, low-density lipoprotein cholesterol (LDL), high-density lipoprotein (HDL) cholesterol, triglycerides, insulin and C-peptide levels.

In line with previous definitions used among pediatric populations to define childhood metabolic-syndrome-like-phenotype,14 we defined clustering of cardio-metabolic risk factors as having any of the three or more following components: android fat mass % 75th percentile; systolic or diastolic blood pressure 75th percentile; HDL-cholesterol 25th percentile or triglycerides 75th percentile; and insulin level 75th percentile. We used android fat mass as percentage of total body fat mass as proxy for waist circumference since waist circumference was not available.

Covariates

Maternal age was assessed at the intake by questionnaire.9 Information on maternal education level, ethnicity, parity, folic acid supplementation use, smoking and alcohol consumption was assessed by questionnaires during pregnancy. First-trimester nutritional intake was obtained by food frequency questionnaire, and total calorie intake was calculated.9 We used medical records to collect information about pregnancy complications and mode of delivery.15 Information about childhood sex, gestational age, weight and length at birth was available from medical records.16, 17 Infant length and weight were measured at community health centers according to standardized procedures at 24 months.9 Information about breastfeeding, timing of introduction of solid foods and average television watching time was obtained by questionnaires.9

Statistical analysis

First, since maternal weight measurements at different time-points throughout pregnancy are strongly correlated, we used conditional change modelling to explore the independent associations of maternal prepregnancy weight and weight gain in each pregnancy period, taking into account their correlations, with childhood outcomes (correlation coefficients between all maternal gestational weight measures shown in Supplementary Table S1).18, 19 We constructed maternal weight gain variables for each period, which are statistically independent from each other, by using standardized residuals obtained from regression of maternal weight at a specific time point on all prior maternal weight measurements. As these conditional maternal weight gain measures are statistically independent of each other, this approach allows inclusion of all maternal weight gain measures simultaneously in one regression model. Thus, associations of maternal weight gain in each period with childhood outcomes can be assessed adjusted for, and compared with, maternal weight gain in other periods of pregnancy.18, 19 This modelling approach thus allows for identification of critical periods, and assessment of the magnitude of effect in different pregnancy periods.19

Second, we examined the associations of maternal GWG in early, mid and late pregnancy with childhood outcomes separately and the role of potential intermediates using regular linear regression models. In these analyses, we did not mutually adjust the maternal GWG measures for each other. For these analyses, we used different linear regression models; a basic model including child’s age and sex; a confounder model, which additionally included covariates selected on their associations with the outcomes of interest or a change in effect estimate of >10%. We included childhood height as covariate in the confounder model in all models focused on fat mass outcomes; an intermediate model, which additionally included potential intermediates (maternal pregnancy complications, gestational age and weight at birth, infant growth from birth until 2 years of age and current childhood BMI). These intermediates were added separately to the confounder model; and a fully adjusted model including all confounders and intermediates. The confounder model was considered as main model.

Third, we examined associations of total and excessive GWG according to Institute of Medicine criteria with childhood outcomes using regular linear regression models. Finally, we examined associations of specific periods of GWG and excessive GWG with the risks of childhood overweight and clustering of cardio-metabolic risk factors using regular logistic regression models. For all analyses, not normally distributed childhood outcome variables (abdominal subcutaneous and preperitoneal fat mass, triglycerides, insulin, C-peptide) were log-transformed. We constructed standard deviation scores values ((observed value- mean)/s.d.) for GWG variables and childhood outcomes to enable comparison of effect estimates. We examined potential interactions between maternal prepregnancy BMI and GWG in each period and total GWG. We also explored potential interactions of GWG with sex, ethnicity, gestational age-adjusted birth weight and childhood BMI for these associations. After taking multiple testing into account, no significant interactions were present, and no further stratified analyses were performed. Missing data of maternal weight variables (for conditional analyses only) and covariates were imputed using multiple imputation. Sensitivity analyses among mothers with all three GWG measurements available were performed. All analyses were performed using Statistical Package of Social Sciences version 17.0 for Windows (SPSS Inc., Chicago, IL, USA).

Results

Subject characteristics

Table 1 shows participants characteristics. Correlation coefficients between maternal gestational weight measures, birth weight and childhood cardio-metabolic outcomes are shown in Supplementary Table S1. Supplementary Table S2 and S3 show that mothers without maximum GWG and childhood follow-up data available were more often lower educated and from a non-European descent.

Table 1 Characteristics of mothers and their children (N=5908)a

Gestational weight gain in different periods of pregnancy

Figure 1 shows independent associations of maternal prepregnancy weight and GWG in early, mid and late pregnancy with childhood outcomes using conditional change modelling. Maternal prepregnancy weight was associated with childhood BMI, body fat distribution measures, systolic blood pressure, HDL-cholesterol and insulin and c-peptide levels (all P-values<0.05 in confounder model). The associations of maternal prepregnancy weight with childhood outcomes were stronger than the associations of maternal GWG. Independent from maternal prepregnancy weight and weight gain in other periods, higher maternal GWG in early pregnancy was associated with higher levels of childhood BMI, total fat mass, android/gynoid fat mass ratio, abdominal subcutaneous fat mass and systolic blood pressure (all P-values<0.05). Associations of maternal GWG in early pregnancy with childhood abdominal preperitoneal fat mass, insulin and c-peptide were of borderline significance. Higher maternal GWG in mid pregnancy was independently associated with higher childhood BMI, total fat mass and abdominal subcutaneous fat mass and systolic blood pressure (all P-values<0.05). No independent associations were present for maternal GWG in late pregnancy. Only maternal prepregnancy weight and GWG in early pregnancy were independently associated with the risks of childhood overweight and clustering of cardio-metabolic risk factors (all P-values<0.05) (Figures 1e and f). When we restricted analyses to mothers with all gestational weight measurements available, findings were similar (results not shown).

Figure 1
figure1

Associations of maternal prepregnancy weight and weight gain in each period of pregnancy with childhood cardio-metabolic outcomes from conditional analyses (N=5735). (a) Childhood body fat measures, (b) childhood blood pressure, (c) childhood lipid levels, (d) childhood insulin and c-peptide levels, (e) childhood overweight and (f) childhood clustering of cardio-metabolic risk factors. Values are the regression coefficients (95% confidence interval) from linear and logistic regression models that reflect the difference in childhood outcomes per SDS change in maternal prepregnancy weight and per SDS change in standardised residual change in maternal weight in early, mid and late pregnancy from the conditional change models. For these analyses, mothers were included when they had at least two maternal weight measurements available (N=5735). Estimates are based on multiple imputed data (multiple imputation was also used for missing maternal weight data). Models are adjusted for child sex and age at outcome measurements, gestational age at maternal weight measurement, maternal age, educational level, ethnicity, parity, height at intake, smoking and alcohol consumption during pregnancy and folic acid supplement use, total calorie intake during pregnancy, delivery mode, breastfeeding duration, age at introduction of solid foods and child’s average duration of tv watching. Models focused on fat mass outcomes were also adjusted for childhood height; Models additionally adjusted for potential intermediates (pregnancy complications, birth characteristics, childhood size) are shown in the Supplementary Material (Supplementary Tables S4 and S5).

Role of maternal pregnancy complications, birth outcomes and childhood size

Tables 2 and 3 show the associations of maternal early, mid and late GWG with childhood outcomes per standard deviation score change, and the role of potential intermediates, using regular linear regression models. Table 2 shows that associations of maternal GWG in early pregnancy with childhood BMI, total fat mass, android/gynoid fat mass ratio and abdominal subcutaneous fat mass were not explained by pregnancy complications, gestational age and weight at birth or infant growth. The associations of maternal GWG in early pregnancy with childhood fat mass outcomes attenuated towards non-significant after adjustment for childhood BMI. The association of maternal mid GWG with offspring BMI was partly explained by birth characteristics. Maternal late GWG was associated with childhood BMI only, but this association was fully explained by birth characteristics.

Table 2 Weight gain in early, mid and late pregnancy and childhood body composition (N=5908)
Table 3 Weight gain in early, mid and late pregnancy and childhood cardio-metabolic outcomes (N=5908)

Table 3 shows that specific periods of maternal GWG were not significantly associated with childhood cardio-metabolic outcomes. Maternal GWG in early and mid pregnancy tended to be associated with childhood systolic blood pressure, but this association was explained by childhood BMI. Results for conditional weight gain models additionally adjusted for potential intermediates were similar and are given in Supplementary Table S4 and S5. Associations of total GWG with childhood cardio-metabolic outcomes are shown in Supplementary Table S6. Total GWG was associated with offspring BMI only.

Figure 2a shows that a higher GWG in early and mid, but not in late pregnancy were associated with increased risks of childhood overweight (odds ratio (OR) 1.19 (95% confidence interval (CI): 1.10, 1.29) and OR 1.09 (95% CI: 1.01, 1.18), per s.d. increase in early and mid GWG, respectively). The association for GWG in mid pregnancy was explained by birth characteristics. Only higher GWG in early pregnancy was associated with an increased risk of childhood clustering of cardio-metabolic risk factors (OR 1.20 (95% CI: 1.07, 1.35) per s.d. increase, respectively). This association was not explained by potential intermediates (Figure 2b). Figures 2a and b also show that children from mothers with excessive GWG had increased risks of childhood overweight (OR 1.54 (95% CI: 1.22, 1.96)) and clustering of cardio-metabolic risk factors (OR 1.68 (95% CI: 1.17, 2.41)), independent of potential intermediates. Associations of excessive GWG with separate childhood cardio-metabolic outcomes are shown in Supplementary Table S7.

Figure 2
figure2

Associations of maternal gestational weight gain with the risk of childhood overweight and clustering of cardio-metabolic risk factors (N=5908). (a) Childhood overweight (b) Childhood clustering of cardio-metabolic risk factors. Values are odds ratios (95% confidence interval) from regular logistic regression models that reflect the risks of childhood overweight and obesity and childhood clustering of cardio-metabolic risk factors per SDS change in early, mid and late GWG, and for excessive GWG as compared to the reference group (non-excessive GWG). Information on excessive GWG was only available in a subgroup of mothers. Estimates are based on multiple imputed data. Confounder models (represented by circle) are adjusted for child sex and age at outcome measurements, gestational age at maternal weight measurement (period-specific GWG models), maternal age, educational level, ethnicity, prepregnancy BMI (period-specific GWG models), parity, smoking and alcohol consumption during pregnancy and folic acid supplement use, total calorie intake during pregnancy, delivery mode, breastfeeding duration, age at introduction of solid foods and child’s average duration of watching tv. Full models (represented by triangle) are additionally adjusted for pregnancy complications, gestational age and weight at birth, infant length and weight growth.

Discussion

We observed that higher maternal GWG in early, but not in mid and late, pregnancy is associated with increased adiposity levels and an adverse cardio-metabolic profile in childhood. These associations were independent from maternal prepregnancy weight and weight gain in other periods, and not explained by pregnancy complications or birth and infant growth characteristics. The associations of weight gain later in pregnancy with childhood outcomes seem to be partly explained by birth characteristics.

Methodological considerations

Strengths of this study were the prospective data collection from early pregnancy onwards, large sample size and multiple maternal weight measurements throughout pregnancy. Follow-up data were available in 69% of our study population. Non-responses analyses showed that mothers without childhood follow-up data available were more often lower educated and from a non-European descent, but no difference in maternal prepregnancy BMI was present. The non-response could lead to biased effect estimates if associations would be different between mothers and children included and not included in the analyses. This seems unlikely. We had up to three maternal weight measurements during pregnancy available. Due to our study design, the gestational age at maternal weight measurements did not fully match with the formal trimester-specific gestational age cut-offs. When we used narrower ranges to define specific periods of GWG, conclusions were similar (results not shown). Further studies with more repeated maternal weight measurements throughout pregnancy are needed to obtain more detailed insight in critical periods of GWG. Furthermore, not all maternal weight measurements were available for all mothers because of later enrolment in the study or non-participation in physical examinations or questionnaires. To avoid bias related to a complete-case analysis and to maintain statistical power, we used multiple imputations for missing information of maternal weight measurements for conditional analyses only.20 Compared with the complete-case analysis, effect estimates changed slightly after using multiple imputations for missing maternal weight values (results not shown), but conclusions were similar. In the regular linear regression analyses used to study the associations of maternal GWG in early, mid and late pregnancy separately, maternal weight measurements were not imputed. Observed differences in significance between conditional and regular linear regression analyses are partly because of smaller numbers in regular linear regression analyses. Information on maternal prepregnancy weight and maximum gestational weight was self-reported. Self-reported weight tends to be underestimated, especially in case of higher maternal weight. This might have led to an underestimation of observed effects for maximum GWG and an overestimation for GWG in early pregnancy. Use of 30-min fasting childhood blood samples may have led to underestimation of the observed associations. However, studies in adults have suggested that in comparison with fasting levels, also non-fasting levels of triglycerides and insulin are strongly associated with cardiovascular disease.21, 22 Finally, although information about a large number of potential confounding factors was available, because of the observational design, residual confounding might still be an issue.

Interpretation of main findings

Previous studies have shown that GWG, especially in mid and late pregnancy, is associated with birth weight.23, 24 In the same population as the present study, we previously observed that specific periods of GWG are associated with risks of adverse pregnancy outcomes.24 In the current study, we aimed to identify critical periods of GWG for cardio-metabolic health in offspring. An accumulating body of evidence suggests that GWG might influence offspring cardio-metabolic health in later life.4, 6, 7, 8, 25, 26, 27, 28, 29, 30, 31 The effects may depend upon the timing of GWG. A study performed among 5154 UK mother–offspring pairs showed that GWG in the first 14 weeks tended to be incrementally associated with offspring BMI, waist circumference and fat mass at 9 years, but after 14 weeks of gestation, only high levels of GWG were associated with offspring adiposity measures.4 No associations of trimester-specific weight gain with blood pressure were present, whereas weight gain from 14–36 weeks of gestation tended to be linearly associated with HDL-cholesterol, triglycerides and inflammatory markers. In these analyses, maternal estimated prepregnancy weight and GWG in other pregnancy periods were taken into account. Another study among 3015 US mothers and their children showed that only first-trimester weight gain was independently associated with childhood BMI, and suggested that maternal prepregnancy BMI modified this association.7 In this study, maternal weight was not measured in first trimester, but estimated. A Finnish study among 6637 mothers and their adolescent offspring showed that weight gain of >7 kg in the first 20 weeks of gestation was associated with offspring overweight and higher waist circumference, but this study did not study whether these effects were independent from weight gain in later pregnancy.8

In line with these studies, we observed that maternal GWG in early and mid pregnancy was associated with childhood BMI. In childhood, BMI may not accurately reflect fat mass. In addition, studies have shown that more specific total body and abdominal fat distribution measures are related to the risk of cardio-metabolic disease and mortality in later life, independent of BMI.32, 33, 34 We observed that maternal GWG in early pregnancy was also associated with childhood total fat mass, android/gynoid fat mass ratio, a measure of waist-to-hip-ratio, and abdominal subcutaneous fat mass. The observed associations of maternal GWG with detailed childhood body fat mass measures were not independent of childhood BMI. Thus, our results suggest that higher maternal GWG in early pregnancy is related to higher BMI, higher total fat mass and relatively more abdominal fat mass in childhood. Maternal GWG in early pregnancy tended to be associated with childhood systolic blood pressure, insulin and c-peptide levels and clustering of cardio-metabolic risk factors, but no associations with lipid levels were present. The associations of maternal early GWG with childhood cardio-metabolic risk factors were largely mediated by childhood BMI. We assessed the associations of GWG in different pregnancy periods in comparison with and adjusted for maternal prepregnancy weight. Previously, we have shown that maternal prepregnancy weight is strongly associated with an adverse cardio-metabolic profile in offspring.35 In the current study, we observed that the associations of maternal prepregnancy weight with childhood cardio-metabolic risk factors were stronger than those for early GWG, but did not explain or modify the associations of early GWG with these childhood outcomes. Associations of maternal GWG in early pregnancy with childhood outcomes were also independent of weight gain later in pregnancy.

Increased total weight gain and excessive GWG according to Institute of Medicine criteria have been associated with increased risks of offspring obesity, independent of maternal prepregnancy BMI.4, 6, 25, 26, 27, 28, 29, 31, 36 Associations of increased total GWG with offspring blood pressure, lipid profile and inflammatory markers are less consistent and seem to be mainly driven by offspring adiposity.4, 26, 28 Accordingly, we observed associations of total and excessive GWG with increased childhood adiposity levels and increased risk of childhood overweight. Excessive GWG was also associated with the risk of childhood clustering of cardio-metabolic risk factors, which was largely explained by the association of excessive GWG with childhood adiposity. No significant associations of total and excessive GWG with other separate childhood cardio-metabolic risk factors were present. This may be because of a lack of statistical power as a smaller number of mothers had information about total and excessive GWG available.

The associations of GWG with childhood cardio-metabolic outcomes may be explained by several factors. Mothers who gain a large amount of weight during pregnancy are likely to have different socio-demographic and lifestyle characteristics as compared to mothers who gain recommended amounts of weight.24 These factors may account for the observed effects. However, extensive adjustment for socio-demographic and lifestyle factors did not explain our findings. The observed effects of GWG in each pregnancy period were not mediated by maternal pregnancy complications or infant growth characteristics.37, 38, 39 Weight gain during pregnancy, especially in later pregnancy, might also just reflect higher fetal weight and birth weight, which are known to be associated with obesity in later life.40 In line with this hypothesis, we observed that associations of GWG later in pregnancy with childhood outcomes were partly explained by birth characteristics. Thus, the effects of maternal GWG on childhood outcomes may vary during pregnancy, and our results suggest that especially early pregnancy might be a specific and independent critical period for maternal GWG. The observed effect estimates for the associations of maternal GWG in early pregnancy with childhood cardio-metabolic outcomes were small and are mainly of interest from a cardiovascular developmental perspective. However, several large studies have shown that these childhood cardio-metabolic risk factors track from childhood into adulthood and are associated with cardiovascular disease in later life.41, 42, 43, 44 The mechanisms by which maternal GWG in early pregnancy is related to an adverse childhood cardio-metabolic profile are not known. GWG in early pregnancy largely reflects maternal fat deposition.5 Increased maternal fat mass during pregnancy may lead to higher placental transfer of maternal levels of glucose, free fatty acids and amino-acids and subsequent programming of adiposity and an adverse cardio-metabolic profile in offspring.45 It is not known whether especially maternal fat accumulation early in pregnancy is related to adverse outcomes in offspring or whether GWG becomes an increasingly poor measure of maternal fat accumulation with advancing gestation. Further mechanistic studies are needed to obtain further insight in these underlying mechanisms.

Conclusions

We observed that increased maternal weight gain in early pregnancy is associated with an adverse cardio-metabolic profile in childhood. This association is largely mediated by childhood BMI. Future preventive strategies focused on reduction of excessive maternal weight gain, especially in early pregnancy, may lead to better cardio-metabolic health in offspring.

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Acknowledgements

The general design of the Generation R Study is made possible by financial support from the Erasmus Medical Center, Rotterdam, Erasmus University Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), Netherlands Organisation for Scientific Research (NWO), Ministry of Health, Welfare and Sport and the Ministry of Youth and Families. Research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007–2013), project EarlyNutrition under grant agreement n°289346. OHF received a grant from Pfizer Nutrition to set up a new intergenerational center of ageing research (ErasmusAGE). VWVJ received an additional grant from the Netherlands Organization for Health Research and Development (VIDI 016.136.361).

Author Contributions

Drs Gaillard and Jaddoe had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Drs Gaillard and Jaddoe. Acquisition of data: Drs Steegers, Hofman, Franco and Jaddoe. Analysis and interpretation of data: Drs Gaillard and Jaddoe. Drafting of the manuscript: Drs Gaillard and Jaddoe. Critical revision of the manuscript for important intellectual content: Drs Gaillard, Steegers, Hofman, Franco and Jaddoe. Statistical analysis: Drs Gaillard and Jaddoe. Study supervision: Drs Hofman and Jaddoe. All authors read and approved the final version of the manuscript. Additional Contributions: We gratefully acknowledge the contribution of general practitioners, hospitals, midwives, and pharmacies in Rotterdam.

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Correspondence to V W V Jaddoe.

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Gaillard, R., Steegers, E., Franco, O. et al. Maternal weight gain in different periods of pregnancy and childhood cardio-metabolic outcomes. The Generation R Study. Int J Obes 39, 677–685 (2015). https://doi.org/10.1038/ijo.2014.175

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