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International Journal of Obesity (2015) 39, 565–570 © 2015 Macmillan Publishers Limited All rights reserved 0307-0565/15 www.nature.com/ijo

PEDIATRIC ORIGINAL ARTICLE

Maternal diet but not gestational weight gain predicts central adiposity accretion in utero among pregnant adolescents CM Whisner1, BE Young2, EK Pressman3, RA Queenan3, EM Cooper3 and KO O’Brien1 BACKGROUND: Modifiable risk factors during pregnancy, such as diet and weight gain, are associated with fetal birth weight but little is known about how these factors influence fetal fat acquisition in utero among pregnant adolescents. OBJECTIVE: To determine whether maternal pre-pregnancy BMI (ppBMI), gestational weight gain (GWG) and dietary intake during pregnancy influence fetal fat accretion in utero. METHODS: Longitudinal data were obtained from 121 pregnant adolescents enrolled in a study designed to identify determinants of maternal and fetal bone changes across gestation. Adolescents (ages 13–18 years) completed up to three study visits during early, mid- and late gestation. Maternal anthropometrics, 24 h dietary recalls and measures of fetal biometry were obtained at each visit. Fetal abdominal wall thickness (abdominal subcutaneous fat thickness, AbFat), a measure of fetal subcutaneous fat, was calculated by sonography at each visit. Statistical determinants of AbFat during late pregnancy were explored using simple and multiple regression. RESULTS: During late pregnancy (34.8 ± 2.0 weeks; range 31.0–40.6 weeks of gestation), the median (inter-quartile range) fetal AbFat and GWG were 0.44 (0.39, 0.55) cm and 14.6 (9.5, 18.3) kg, respectively. After adjusting for infant birth weight, variables significantly associated with fetal AbFat included gestational age (P o 0.0001, 95% confidence interval, CI: 0.01, 0.03), maternal race (P = 0.029, 95% CI: − 0.04, − 0.002) and dietary intake of added sugar (P = 0.025, 95% CI: 1.42e–6, 2.06e–5). Fetal AbFat had a significant positive quadratic relationship with total maternal dietary sugar intake such that both low and high extremes of sugar consumption were associated with significantly higher fetal AbFat. Birth weight was not significantly associated with maternal intake of added sugars. CONCLUSION: Extreme sugar intakes among pregnant adolescents may lead to increased accumulation of fetal abdominal fat with little net effect on birth weight. This finding suggests that increased sugar consumption during pregnancy promotes shifts in fetal body composition. International Journal of Obesity (2015) 39, 565–570; doi:10.1038/ijo.2014.202

INTRODUCTION Adolescent pregnancy remains a public health concern because of the associated increase in risk of premature delivery, low birth weight (LBW) and offspring mortality.1,2 Worldwide, an estimated two million girls younger than 15 years and 16 million girls between 15 and 19 years give birth each year.3 Since 2010, adolescent pregnancy has decreased by 11% but racial disparities remain evident with more than half of all teen pregnancies occurring among African American and Hispanic girls.4 Adolescents are at higher risk for multiple adverse pregnancy outcomes. Many of these risks are influenced by a number of modifiable factors which increase the risk of both inadequate and excessive gestational weight gain (GWG).5 Maternal pre-pregnancy body mass index (ppBMI) was highlighted as a significant predictor of adverse pregnancy outcomes by the 2009 Institute of Medicine (IOM) guidelines on GWG.6 For the adult mother, ppBMI exceeding the normal range has been associated with greater risk of cesarean delivery, gestational diabetes mellitus and preeclampsia.7,8 Among teens, ppBMI has been associated with pregnancy-induced hypertension and hemorrhage.9 In adult women, positive correlations between maternal GWG and infant birth weight have been highlighted,10 but this relationship is less clear among pregnant adolescents

who, despite pregnancy weight gains similar to adult women, are more likely to deliver LBW infants.11 Maternal factors have been linked to fetal and neonatal body composition. Greater maternal BMI among adult women increases the risk for enlarged birth size, greater neonatal fat mass and overweight/obesity during childhood.8,12 Maternal insulin sensitivity in late gestation has also been correlated with neonatal birth weight while pre-conception insulin sensitivity strongly correlates with neonatal fat mass among adult women.13 These data highlight the importance of maternal carbohydrate metabolism in both fetal nutrient partitioning and birth outcomes, yet few studies have assessed the impact of specific maternal nutrients or major dietary components in relation to fetal fat accretion across gestation. A recent study among adult women found that decreased protein and increased starch consumption was associated with a greater percentage of fetal abdominal fat area in utero, as measured by ultrasound.14 Currently, data on pregnant adolescents also support an effect of maternal diet during pregnancy on offspring adiposity, but these associations, to date, are limited to sheep models.15,16 The goal of this study was to examine possible associations between maternal diet across gestaion with longitudinal measures of fetal growth and adiposity in a racially diverse cohort of

1 Division of Nutritional Sciences, Cornell University, Ithaca, NY, USA; 2Pediatric Nutrition, University of Colorado Denver, Aurora, CO, USA and 3The University of Rochester School of Medicine, Rochester, NY, USA. Correspondence: Dr KO O’Brien, Division of Nutritional Sciences, Cornell University, 230 Savage Hall, Ithaca 14853, NY, USA. E-mail: [email protected] Received 5 May 2014; revised 14 October 2014; accepted 10 November 2014; accepted article preview online 3 December 2014; advance online publication, 6 January 2015

Maternal diet predicts fetal fat accretion CM Whisner et al

566 pregnant adolescents. The impact of ppBMI, race, ethnicity GWG and dietary composition on fetal abdominal subcutaneous fat thickness were evaluated. Indentifying modifiable maternal factors that are associated with fetal adipose deposition in utero may allow for targeted interventions to optimize maternal diet and weight gain recommendations in this vulnerable obstetric population. SUBJECTS AND METHODS Study design and participants The present study is a secondary analysis of data from a prospective longitudinal study undertaken between 2006 and 2010 that included 158 racially diverse pregnant adolescents. The parent study was designed to assess determinants of maternal bone loss and fetal bone growth in relation to calcium and vitamin D status across gestation. Adolescents were recruited from the Rochester Adolescent Maternity Program (RAMP) in Rochester, NY, USA. Pregnant adolescents aged 13–18 years were eligible to participate if they were healthy and between 12 and 30 weeks of gestation. Participants with HIV infection, diabetes, clinically diagnosed eating disorders, those carrying multiple fetuses or those with malabsorptive disorders were excluded from participating. Written informed consent was obtained from all participants and study protocols were approved by the Institutional Review Boards of the University of Rochester (Rochester) and Cornell University (Ithaca, NY, USA). Health history questionnaires were administered at baseline and maternal race (African American, Caucasian, other), ethnicity (Hispanic or non-Hispanic), pre-pregnancy weight and smoking/drug history were selfreported. Paternal race and ethnicity were reported by the mother. Neonates with parents of differing races or ethnicities were classified as biracial or multi-ethnic, respectively. PpBMI was calculated using selfreported pre-pregnancy weight while GWG was calculated as weight at delivery minus self-reported pre-pregnancy weight in kilograms. Previously published analyses of this cohort include data on markers of bone turnover and calcitropic hormone concentrations17,18 as well as determinants of fetal bone growth19 and placental nutrient transporter expression.20–23 Teens completed up to three study visits that were scheduled during early, mid- and late gestation in conjunction with prenatal care visits. Each visit included maternal anthropometric measures, 24 h dietary recalls and fetal biometry measures (biparietal diameter, femur length, humerus length, head circumference and abdominal circumference). The fetal sonogram data were categorized into the gestational window at which the measure was obtained as ⩽ 20.9, 21.0–30.9 and ⩾ 31.0 weeks. GWG was categorized according to the IOM guidelines.6 Study personnel directed the 24 h diet recalls; a registered dietitian analyzed the diet recall data using the Nutrition Data System for Research (NDSR; University of Minnesota, Minneapolis, MN, USA; versions 2006, 2008 and 2009). Macronutrient intakes (carbohydrate, fat and protein) were assessed in relation to the Acceptable Macronutrient Distribution Range.24 Total sugar and added sugar intakes were calculated with the NDSR software. Common dietary items reported that were high in added sugar included soda, juice drinks, dessert items (candy, cake, etc) and sweetened cereals. Dietary items ingested that were high in fat included meats, fast-food items, desserts/snacks and dressings/spreads. The nutrient residual (energy-adjusted) model was used to adjust individual macronutrient intakes based on the predicted nutrient intake at the mean total energy intake.25 This method adjusts for variation in intakes and reduces confounding related to total energy intake. Average dietary intake of this population across gestation has been published.26 Standard fetal biometry measures were obtained by trained sonographers. Fetal femur length was determined by measuring along the femur diaphysis excluding the distal femoral epiphysis. Femur length z scores were calculated using previously published equations from a large cohort of pregnant African American adolescents.27 Fetal humerus length was recorded similarly to femur length and z-scores were calculated with published curves.28 Measures of fetal subcutaneous fat tissue thickness (AbFat) were recorded up to three times across pregnancy. Twodimensional ultrasound images of the abdominal circumference plane were used to measure fetal fat after magnifying the image to fill the sonogram screen area. Electronic calipers were placed at the inner and outer bounds of the subcutaneous fat layer surrounding the abdominal viscera. The fetal AbFat (reported in centimeters) was measured anteriorly and vertically between the mid-axillary lines near the umbilical cord entry point. Additional anthropometric measures at delivery were recorded by International Journal of Obesity (2015) 565 – 570

clinical staff including: infant weight (to nearest gram), birth length (to nearest centimeter), head circumference (to nearest tenth of a centimeter) and neonatal ponderal index (kg m − 3). Data analysis was performed using JMP Pro 10 (SAS Institute, Cary, NC, USA). Variables were assessed for normality and comparisons of normally distributed data were made using two-sample t tests (continuous data) and analysis of variance (categorical data). Nonparametric comparisons were made using Wilcoxon rank sums (continuous data) and Chi-square statistic (categorical data). Categorical variables used in analyses included maternal race and ethnicity, ppBMI categories, parity and neonatal sex. Results are presented as means ± s.d. unless otherwise stated. Simple linear regression was used to explore relationships between descriptive characteristics (GWG, ppBMI (continuous), infant birth weight and macronutrient and energy intakes) and fetal AbFat at the third study visit and expressed longitudinally as a rate (centimeter per week). Multiple linear regression was used to control for differences in gestational age, covariates and interactions while modeling dietary determinants of fetal fat accretion. Missing data in linear analyses were addressed with list-wise deletion. Previous models have identified parity, race, gender, birth weight, GWG and gestational age as potential predictors of fetal abdominal fat14,29 and these variables were initially considered as covariates in the multivariate models. Non-normally distributed variables were log-transformed to ensure the normality of model residuals.

RESULTS Adolescent characteristics are provided in Table 1. To account for the fact that the majority of fetal abdominal fat is accrued during late pregnancy, participants delivering preterm infants (o 37 weeks gestation, n = 13) were excluded from these analyses. Participants with missing dietary data and third trimester fetal AbFat measures (n = 22) and two outliers based on nutrient intake (43 s.d. from the mean sugar and fat intake) were also excluded from the final analysis bringing the final study cohort to 121 adolescents with complete data. Complete birth data were missing for two adolescents: one experienced a fetal death in utero and the other teen delivered at a different hospital precluding collection of infant birth measures. As a result, multivariate models with birth weight as a covariate included only 119 participants. Of the 121 teens studied, 6.7% (n = 8) gave birth to a large for gestational age infant (44500 g) while 1.7% (n = 2) delivered LBW infants (o 2500 g). A total of 8.3% of these adolescents (n = 10) had a parity ⩾ 1. Maternal age and gynecologic age (years since menarche) at conception, prepregnancy weight, ppBMI, GWG and parity did not differ significantly by maternal race or ethnicity. Maternal height was Table 1.

Characteristics of pregnant adolescent cohort (n = 121)

Characteristic Race, % (n) Black White

66.9 (81) 33.1 (40)

Ethnicity, % (n) Hispanic Non-Hispanic

26.4 (32) 73.6 (89)

Pre-pregnancy BMI, kg m − 2 Weight gain, kg GA at delivery, weeks Energy intake, kcal Fat, ga Protein, ga Carbohydrate, ga Total sugar, ga

23.2 (20.4, 28.7) 15.9 (11.8, 20.9) 40.0 (39.0, 40.7) 2258 (1812, 2717) 91.7 ± 13.3 78.8 ± 13.7 299.9 ± 67.9 142.6 ± 35.1

Abbreviations: BMI, body mass index; GA, gestational age. Mean ± s.d., median (25th, 75th inter-quartile range) or as otherwise specified. a Adjusted for energy intake.

© 2015 Macmillan Publishers Limited

Maternal diet predicts fetal fat accretion CM Whisner et al

567 slightly greater among African-American adolescents (162.3 ± 7.2 vs 159.2 ± 6.4 cm in African-American (n = 81) vs Caucasian (n = 40), respectively; P = 0.020); significant differences in height by ethnicity were found between adolescents of non-Hispanic and Hispanic heritage (162.2 ± 7.3 cm (n = 89) vs 158.8 ± 6.1 cm (n = 32), respectively; P = 0.018). Although the majority (57.5%, n = 69) of adolescents self-reported a normal ppBMI (18.5–24.9 kg m − 2), 18.3% (n = 22) were overweight, 17.5% (n = 21) were obese and 6.7% (n = 8) were underweight. On the basis of the IOM guidelines, 25.2% (n = 30) of teens gained within the recommended weight range whereas 15.1% (n = 18) and 59.7% (n = 71) did not meet or exceeded the recommended range, respectively, based on ppBMI. Adolescent dietary energy and macronutrient intakes did not differ significantly across gestation within adolescents.26 As a result, values were averaged for each adolescent and mean energy-adjusted intakes of fat, protein, carbohydrate and sugar were used in all subsequent analyses. Energy-adjusted mean daily fat, carbohydrate and protein consumption ranged from 63 to 134, 156 to 481 and 34 to 113 g, respectively. Although the mean percent of calories from fat (34.6%) was within the Acceptable Macronutrient Distribution Range (20–35% of kcal), 45% of adolescents exceeded the recommended upper bound for fat intake (35% of kcal). Caloric intake from both carbohydrate and protein were within recommended ranges (carbohydrate, 45–65% and protein, 10–35%) with mean ± s.d. of 52.1 ± 7.0% and 14.0 ± 2.9%, respectively. Total sugar intake for this population was 143 ± 35 g, of which added sugar accounted for 98 ± 38 g. Added sugar intake represented 1–39% of daily caloric intake. Mean daily caloric intake was not associated with GWG, or categories of weight gain based on the IOM guidelines (under, over or within recommendations). Energy-adjusted total sugar and added sugar consumption were not significantly associated with GWG, categories of weight gain (based on IOM guidelines) or infant birth weight, length and ponderal index. A negative trend was seen between infant head circumference and total sugar consumption (R2 = 0.03, P = 0.061). Total and added sugar intake were significantly positively associated with caloric intake (R2 = 0.53, P o0.0001 and R2 = 0.24, P o 0.0001, respectively; log transformation of calories). Lower gestational age at delivery was significantly associated with higher total sugar consumption (R2 = 0.06, P = 0.008). Fetal and neonatal characteristics are presented in Table 2. Mean birth weights were 3219.4 ± 465.6 g (n = 79) and 3354.8 ± 474.2 g (n = 40) for African American and Caucasian teens, respectively. Birth weights observed in this adolescent cohort were lower than those in the published literature for adult African American and Caucasian women delivering term infants (3244 and 3576 g, respectively).30,31 Infant birth weight, ponderal index and birth length did not differ by maternal ethnicity or race. Maternal ppBMI impacted infant birth weight with slightly greater birth weights evident among adolescents who were overweight compared with normal weight prior to pregnancy (3375.3 ± 464.6 vs 3206.5 ± 467.59 g, respectively; P = 0.061). GWG was significantly positively associated with both infant birth weight (P = 0.0009) and length (P = 0.011). Birth weight and length did not differ significantly by infant sex, race or parity. Fetal AbFat measures were available for both the first (⩽20.9 weeks) and third (⩾31.0 weeks) gestational windows in 64 of the 121 pregnant adolescents and in the second (21.0– 30.9 weeks) and third gestational windows of 105 of these adolescents. Between the first and third gestational windows, adolescents experienced a median (25th, 75th inter-quartile range) total increase in fetal AbFat of 0.23 (0.15, 0.35) cm. This represented a mean rate of change of 0.015 ± 0.008 cm per week between the first and last gestational window of measurement. The mean rates of change in fetal AbFat between the first and second and second and third gestational measures were 0.012 ± 0.012 and 0.019 ± 0.016 cm per week, respectively. © 2015 Macmillan Publishers Limited

Table 2.

Neonatal and fetal anthropometric measures

Characteristic Sex, % Male Female

52.5 (63) 47.5 (57)

Birth weight, g Birth length, cm Head circumference, cm Ponderal Index, g cm − 3 Fetal AbFat, cm Visit 1, 19.7 ± 4.2 weeks gestation Visit 2, 26.8 ± 3.8 weeks gestation Visit 3, 34.7 ± 2.7 weeks gestation

3265 ± 471 51.1 ± 2.5 33.0 2.4

(119) (118) (32.0, 34.5) (113) (2.2, 2.7) (118)

0.21 (0.16, 0.26) (64) 0.30 (0.26, 0.36) (105) 0.44 (0.39, 0.55) (121)

Abbreviation: AbFat, abdominal subcutaneous fat thickness. Mean ± s.d. (n), median (25th, 75th inter-quartile range) (n) or as otherwise specified.

Stepwise regression to identify dietary and maternal determinants of the rate of increase (centimeter per week) in fetal AbFat between the first and third gestational window was completed using the 64 subjects with fetal AbFat measures during the first and third gestational windows. This model was expressed as a rate (centimeter per week); gestational ages at both measurement times and infant birth weight were included in the model to control for variation in the timing of measurements and birth size. Although the model did not reach significance (P = 0.065), a trend was observed between IOM weight gain categories and the weekly rate of increase in fetal AbFat (P = 0.046), such that teens who gained less than recommended amounts had fetuses with greater rates of in utero AbFat accretion compared with those who gained more than recommended. In addition to identifying determinants of the rate of change in fetal fat accretion between gestational windows, determinants of the total accumulation of fetal AbFat were assessed using the final AbFat measure (collected ⩾ 31 weeks gestation) in the 121 adolescents who had data during late gestation. At 34.8 ± 2.0 weeks of gestation, the median (inter-quartile range) fetal AbFat and GWG were 0.44 (0.39, 0.55) cm and 14.6 (9.5, 18.3) kg, respectively. Maternal race (African-American vs Caucasian) had a significant impact on Fetal AbFat measures during the third gestational window with lower AbFat accretion in African Americans compared with Caucasians (0.45 ± 0.01 vs 0.50 ± 0.02 cm (least squares means ± s.e.), respectively, P = 0.037). A positive and highly significant linear relationship was found between fetal AbFat in late pregnancy and infant birth weight (Figure 1; R2 = 0.08, P = 0.0014, n = 119) while no associations were found between fetal AbFat and maternal ethnicity, ppBMI, GWG, parity, maternal smoking status and infant sex. Upon individual assessment of macronutrients, no associations were found for energy-adjusted dietary protein (P = 0.331) or fat (P = 0.608) intakes. Of the dietary macronutrients evaluated, a positive quadratic trend was observed between fetal AbFat during late gestation and mean energy-adjusted dietary carbohydrate (Figure 2; Carb2, R2 = 0.03, P = 0.057, n = 119). Multiple regression modeling of net fetal AbFat accretion at the final study visit during pregnancy (range: 31.4–40.6 weeks) was undertaken to test the main effects of maternal macronutrient intakes after controlling for significant covariates (infant birth weight, maternal race and gestational age at the time of fetal ultrasound). Energy-adjusted protein and fat intakes were not significantly associated with fetal AbFat in the multivariate models. After adjusting for covariates, energy-adjusted carbohydrate intake remained significantly associated with fetal AbFat (R2 = 0.277, P o0.0001, n = 119). The association between dietary carbohydrate and fetal AbFat was best modeled as a quadratic (U-shaped) relationship. International Journal of Obesity (2015) 565 – 570

Maternal diet predicts fetal fat accretion CM Whisner et al

568 Table 3. Predictors of fetal abdominal fat thickness during late gestation of pregnancy Variable

Coefficient

s.e.

95% CI

P

Intercept − 0.57 0.18 − 0.92– − 0.21 0.002 Birth weight 7.78E-05 2.05E-05 3.72e-5–1.19e-4 0.0002 Gestational age 0.02 0.005 0.01–0.03 o0.0001 at time of US a − 7.68E-05 2.53E-04 − 5.78e-4–4.24e-4 0.8555 Added sugar 0.0006 (Added sugar)2a 1.36E-05 3.85E-06 5.96e-6–2.12e-5 Maternal race − 0.02 0.01 − 0.04– −0.002 0.0289 Abbreviations: CI, confidence interval; US, ultrasound. Po0.0001, R2 = 0.28, n = 119. aEnergy-adjusted dietary intake.

Figure 1. Late gestation fetal AbFat is increased in infants with greater birth weights; R2 = 0.08, P o = 0.0014, n = 119.

Figure 2. Dietary carbohydrate intake (energy-adjusted) has a significant quadratic relationship with fetal AbFat at late gestation; Model R2 = 0.03, P = 0.057, n = 119.

To better understand this relationship, carbohydrate intake was further assessed to identify specific carbohydrate sources that had the greatest impact on fetal AbFat. These variables were assessed in separate models because of correlation with one another. Total sugar intake was not significantly associated with fetal AbFat. Conversely, added sugar intake was significantly associated with fetal AbFat and contributed to the best predictive model of fetal AbFat during late gestation (Table 3; R2 = 0.282, P o 0.0001, n = 119). Total energy-adjusted added sugar intake accounted for approximately 3.3% of the variation in fetal AbFat while energy-adjusted carbohydrate consumption accounted for only 2.8%, making added sugar the best dietary predictor of late gestation fetal AbFat in this cohort of pregnant adolescents. DISCUSSION In this group of pregnant adolescents, excessive GWG was common. In spite of adequate or excessive maternal weight gain in this population, fetal abdominal adiposity was not significantly influenced by maternal ppBMI or GWG. Of all the determinants examined, maternal dietary intake of sugar, specifically added International Journal of Obesity (2015) 565 – 570

sugar, among a group of healthy, racially and ethnically diverse pregnant adolescents, was associated with significant increases in fetal abdominal fat thickness. Interestingly, the nature of this relationship was not linear, such that teens ingesting both low and high extremes of added sugar gave birth to infants with greater net in utero abdominal fat accretion. This impact of maternal sugar intake was specific to fetal abdominal fat accretion as no significant association was evident between maternal sugar intake and infant birth weight in this adolescent cohort. Maternal ppBMI and GWG were significantly associated with infant birth weight but not with fetal AbFat during late gestation suggesting that offspring birth weight and body composition are likely differentially regulated in utero. These findings are supported by previous data highlighting differential effects of genetics and environment on birth weight and estimated fetal fat mass in adult women.32 Although fetal fat-free mass accretion in utero is deposited at a fixed rate, differences in fat mass accretion have been found to vary substantially and to explain a significant amount of the variation in birth weight.33 In this cohort, after controlling for birth weight, gestational age and maternal race, energy-adjusted added sugar intake was the most significant dietary predictor of fetal adiposity and together explained 28% of the variability in fetal AbFat. Other data in 183 adult women suggested that 17% of the variation in estimated total fetal fat mass was explained by parity, gestational age, pregravid weight, maternal weight gain and neonatal sex, but these data were estimated using skinfold and anthropometric measurements at birth32 and were therefore not direct measures of in utero AbFat as we obtained in this study. A trend was observed between the rate of fetal AbFat accretion and weight gain when GWG was expressed as categories based on the IOM guidelines. Although insignificant, this association suggests that weight gain may influence the rate of fetal fat accumulation. The IOM weight gain recommendations, based on ppBMI, have been associated with lower risks of unfavorable birth outcomes.6 Compared with adult women, reduced birth weight and premature birth are more common among teens.2,34 Although only 2 teens in this cohort delivered LBW infants while 13 delivered prematurely, the mean birth weight was lower than that of adult women.30,31 The prevalence of LBW and preterm births was lower than previous reports2,34 and may be explained by the greater quality of care that teens received in the RAMP. Growing evidence suggests the importance and complexity of in utero events on fetal growth but little work has been done until recently to isolate the impact of maternal dietary intake on fetal body composition in utero. The observed relationship between fetal AbFat and maternal added sugar intake in this study suggests that optimal intake ranges of specific nutrients during pregnancy may positively influence fetal body composition. A recent study in 179 adult Australian women highlighted the importance of carbohydrate consumption in relation to abdominal adiposity.14 Protein:carbohydrate ratio and net starch intake (food-frequency © 2015 Macmillan Publishers Limited

Maternal diet predicts fetal fat accretion CM Whisner et al

569 survey data) had significant negative associations with the percentage of abdominal fat, as measured by fetal ultrasound.14 Although we did not find a significant association between the protein:carbohydrate ratio or starch and fetal AbFat, these data suggest the importance of dietary carbohydrate composition in relation to other nutrients when evaluating fetal fat distribution. Dietary inadequacies are common among pregnant adolescents.26,35 Teens in this study ingested high-calorie diets containing excessive amounts of fat and added sugar.26 The negative impact of these particular nutrients on fetal AbFat is of concern because of the potential prolonged impact on body composition later in life. Previous research in rats suggests that altered offspring body composition (increased body weight and BMI) was evident at 10 weeks of age following maternal consumption of diets high in fat and sugar when compared with offspring of mothers fed a control diet.36,37 Conversely, a study of 337 pregnant adolescents reported significantly lower birth weights (by 215 ± 104 g) among adolescents consuming highsugar diets (⩾206 g per day).38 Excessive sugar intake may influence glucose metabolism via the insulin response. Previous studies have reported that pre-pregnancy maternal insulin sensitivity was the best predictor of estimated neonatal fat mass among adult women with both normal and abnormal glucose tolerance.13,39 Interestingly, a recent study of adolescent sheep suggested that significantly greater insulin sensitivity was observed in over-nourished sheep which further implicates the importance of glucose metabolism in regulating in utero fetal growth.15 Together, these findings may explain why a stronger relation was observed between fetal AbFat and added sugar, irrespective of the null association between calories and infant birth weight. Although unexpected, the lack of an association between GWG or birth weight and dietary energy intake data may represent unique nutrient-growth interactions among pregnant teens. A previous review article highlighted the complicated mechanistic relationships between maternal weight gain, infant birth weight and diet by suggesting that a causal pathway does not always occur between the three.40 Whereas one study in adult women with gestational diabetes found no association between tertiles of caloric intake and GWG or infant birth weight,41 another study identified a positive correlation between infant birth weight and maternal GWG, but not between maternal dietary intake and birth weight.42 Work in both humans and sheep models has suggested that in adolescents, there is a risk of competition for nutrients between the mother and growing fetus that may even further confound the ability to see relationships between dietary intake and maternal and fetal weight.15,16,43,44 A limitation of this study was the use of a single location for measuring fetal adiposity rather than total body measures (dual energy x-ray absorptiometry) at birth. Food intake data may have lacked accuracy as increased nutrient intakes were not noted across gestation despite the hyperphagic tendencies that are often reported among pregnant women.45 Another weakness, arising from the scheduling difficulties, was the large gestational windows in which ultrasound measurements were obtained. Despite limitations, longitudinal estimates of in utero abdominal subcutaneous fat thickness provided a safe way to measure fetal body composition throughout gestation. Strengths of this study included the repeated measures of both maternal anthropometrics and fetal ultrasound assessments and the use of 24 h recalls which remain the gold standard for collecting dietary intake data. In conclusion, this study demonstrates that both low and high extremes of maternal added sugar intake lead to increased fetal abdominal fat acquisition. Unexpected outcomes including null associations between nutrient intake and GWG or infant birth weight were contradictory to previous literature findings and may be the result of dietary measurement inaccuracies or social and © 2015 Macmillan Publishers Limited

age-related factors. Further research is needed to understand how maternal dietary intake deregulates offspring metabolism and results in altered body composition and whether these effects persist long-term. Overall, the dietary data combined with the lack of an association between fetal AbFat and maternal ppBMI or GWG suggest that greater emphasis should be placed on monitoring and improving dietary composition among pregnant adolescents. Encouraging this population to limit added sugars to the recommended intakes may improve long-term offspring health outcomes including obesity risk. CONFLICT OF INTEREST The authors declare no conflict of interest.

ACKNOWLEDGEMENTS We would like to thank Tera Kent for sample processing and laboratory analyses, the University of Rochester Medical Center Midwifery Group and Allison McIntyre for their assistance in sample collection and patient care, as well as the adolescents who generously participated in this study. Data analysis for this manuscript was supported by the Agriculture and Food Research Initiative Competitive Grant No. 2005-35200 and 2012-67012-19815 from the USDA National Institute of Food and Agriculture. Sources of Support: USDA Grant No. 2005-35200. USDA/NIFA Grant No. 2012-6701219815.

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