Joint effects of ambient air pollution and maternal smoking on neonatal adiposity and childhood BMI trajectories in the Healthy Start study

Background: Coexposure to air pollution and tobacco smoke may influence early-life growth, but few studies have investigated their joint effects. We examined the interaction between fetal exposure to maternal smoking and ozone (O3) or fine particulate matter (PM2.5) on birth weight, neonatal adiposity, and body mass index (BMI) trajectories through age 3 years. Methods: Participants were 526 mother-child pairs, born ≥37 weeks. Cotinine was measured at ∼27 weeks gestation. Whole pregnancy and trimester-specific O3 and PM2.5 were estimated via. inverse-distance weighted interpolation from stationary monitors. Neonatal adiposity (fat mass percentage) was measured via. air displacement plethysmography. Child weight and length/height were abstracted from medical records. Interaction was assessed by introducing cotinine (<31.5 vs. ≥31.5 ng/mL [indicating active smoking]), O3/PM2.5 (low [tertiles 1-2] vs. high [tertile 3]), and their product term in linear regression models for birth weight and neonatal adiposity and mixed-effects models for BMI trajectories. Results: The rate of BMI growth among offspring jointly exposed to maternal smoking and high PM2.5 (between 8.1 and 12.7 μg/m3) in the third trimester was more rapid than would be expected due to the individual exposures alone (0.8 kg/m2 per square root year; 95% CI = 0.1, 1.5; P for interaction = 0.03). We did not detect interactions between maternal smoking and O3 or PM2.5 at any other time on birth weight, neonatal adiposity, or BMI trajectories. Conclusions: Although PM2.5 was generally below the EPA annual air quality standards of 12.0 μg/m3, exposure during the third trimester may influence BMI trajectories when combined with maternal smoking

Exposure to secondhand smoke, exclusive breastfeeding and infant adiposity at age 5 months in the Healthy Start study

Background: Infant adiposity may be influenced by several environmental risk factors, but few studies have explored these interactions. Objective: To examine the interaction between exposure to secondhand smoke and breastfeeding exclusivity on adiposity at age 5 months. Methods: We studied 813 mother-offspring pairs from the longitudinal Healthy Start study. Fat mass and fat-free mass were measured by air displacement plethysmography. Linear regression analyses were used to estimate the association between household smokers (none, any) with fat mass, fat-free mass, percent fat mass, weight-for-age z-score, weight-for-length z-score and BMI-for-age z-score as separate outcomes. Interaction terms between household smokers and breastfeeding exclusivity (<5 months, ≥5 months) were added to separate models. Results: The combination of exposure to secondhand smoke and a lack of exclusive breastfeeding was associated with increased adiposity at age 5 months. For example, within the not exclusively breastfed strata, exposure to secondhand smoke was associated with increased fat mass (0.1 kg; 95% CI: 0.0–0.2; P = 0.05). Conversely, within the exclusively breastfed strata, there was virtually no difference in fat mass between exposed and non-exposed infants (coefficient: −0.1; 95% CI: −0.3–0.1; P = 0.25). Conclusions: Our findings may inform new public health strategies with potential relevance for both smoking cessation and obesity prevention

Predictors of Infant Body Composition at 5 Months of Age: The Healthy Start Study

Objective To examine associations of demographic, perinatal, and infant feeding characteristics with offspring body composition at approximately 5 months of age. Study design We collected data on 640 mother/offspring pairs from early pregnancy through approximately 5 months of age. We assessed offspring body composition with air displacement plethysmography at birth and approximately 5 months of age. Linear regression analyses examined associations between predictors and fat-free mass, fat mass, and percent fat mass (adiposity) at approximately 5 months. Secondary models further adjusted for body composition at birth and rapid infant growth. Results Greater prepregnant body mass index and gestational weight gain were associated with greater fat-free mass at approximately 5 months of age, but not after adjustment for fat-free mass at birth. Greater gestational weight gain was also associated with greater fat mass at approximately 5 months of age, independent of fat mass at birth and rapid infant growth, although this did not translate into increased adiposity. Greater percent time of exclusive breastfeeding was associated with lower fat-free mass (-311 g; P < .001), greater fat mass (+224 g; P < .001), and greater adiposity (+3.51%; P < .001). Compared with offspring of non-Hispanic white mothers, offspring of Hispanic mothers had greater adiposity (+2.72%; P < .001) and offspring of non-Hispanic black mothers had lower adiposity (-1.93%; P < .001). Greater adiposity at birth predicted greater adiposity at approximately 5 months of age, independent of infant feeding and rapid infant growth. Conclusions There are clear differences in infant body composition by demographic, perinatal, and infant feeding characteristics, although our data also show that increased adiposity at birth persists through approximately 5 months of age. Our findings warrant further research into implications of differences in infant body composition

Prenatal exposure to per- and polyfluoroalkyl substances and infant growth and adiposity: the Healthy Start Study

Background: Prenatal exposures to certain per- and polyfluoroalkyl substances (PFAS) have been linked to lower weight and adiposity at birth but greater weight and adiposity in childhood. We hypothesized that faster growth in early infancy may be associated with maternal PFAS concentrations. Methods: Among 415 mother-infant pairs in a longitudinal cohort study, we estimated associations between maternal pregnancy serum concentrations of six PFAS and offspring weight and adiposity at ~5 months of age, and growth in early infancy. Linear and logistic regression models were adjusted for potential confounders including maternal pre-pregnancy body mass index. Effect modification by infant sex was evaluated. We evaluated potential confounding by correlated exposures via multipollutant linear regression and elastic net penalized regression. Results: Associations between maternal PFAS concentrations and infant weight and adiposity differed by offspring sex. In male infants, maternal perfluorooctanoate and perfluorononanoate were positively associated with adiposity, with percent fat mass increases of 1.5–1.7% per ln-ng/mL increase in PFAS (median adiposity at ~5 months: 24.6%). Maternal perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS) were associated with lower weight-for-age z-score among female infants only (−0.26 SD per ln-ng/mL PFOS, 95% CI −0.43, −0.10; −0.17 SD per ln-ng/mL PFHxS, 95% CI −0.33, −0.01). In analyses pooled by sex, 2-(N-methyl-perfluorooctane sulfonamido) acetate above vs. below the limit of detection was associated with greater odds of rapid growth in weight-for-age (odds ratio [OR] 2.2, 95% CI 1.1, 4.3) and weight-for-length (OR 3.3, 95% CI 1.8, 6.2). Multipollutant models generally confirmed the results and strengthened some associations. Discussion: We observed sex- and chemical-specific associations between maternal serum PFAS concentrations and infant weight and adiposity. Multipollutant models suggested confounding by correlated PFAS with opposing effects. Although maternal PFAS concentrations are inversely associated with infant weight and adiposity at birth, rapid gain may occur in infancy, particularly in fat mass

Power and sample size analysis for longitudinal mixed models of health in populations exposed to environmental contaminants: a tutorial

Background: When evaluating the impact of environmental exposures on human health, study designs often include a series of repeated measurements. The goal is to determine whether populations have different trajectories of the environmental exposure over time. Power analyses for longitudinal mixed models require multiple inputs, including clinically significant differences, standard deviations, and correlations of measurements. Further, methods for power analyses of longitudinal mixed models are complex and often challenging for the non-statistician. We discuss methods for extracting clinically relevant inputs from literature, and explain how to conduct a power analysis that appropriately accounts for longitudinal repeated measures. Finally, we provide careful recommendations for describing complex power analyses in a concise and clear manner. Methods: For longitudinal studies of health outcomes from environmental exposures, we show how to [1] conduct a power analysis that aligns with the planned mixed model data analysis, [2] gather the inputs required for the power analysis, and [3] conduct repeated measures power analysis with a highly-cited, validated, free, point-and-click, web-based, open source software platform which was developed specifically for scientists. Results: As an example, we describe the power analysis for a proposed study of repeated measures of per- and polyfluoroalkyl substances (PFAS) in human blood. We show how to align data analysis and power analysis plan to account for within-participant correlation across repeated measures. We illustrate how to perform a literature review to find inputs for the power analysis. We emphasize the need to examine the sensitivity of the power values by considering standard deviations and differences in means that are smaller and larger than the speculated, literature-based values. Finally, we provide an example power calculation and a summary checklist for describing power and sample size analysis. Conclusions: This paper provides a detailed roadmap for conducting and describing power analyses for longitudinal studies of environmental exposures. It provides a template and checklist for those seeking to write power analyses for grant applications

Exploring the association between maternal prenatal multivitamin use and early infant growth: The Healthy Start Study

Background: Prenatal multivitamin supplementation is recommended to improve offspring outcomes, but effects on early infant growth are unknown. Objectives: We examined whether multivitamin supplementation in the year before delivery predicts offspring mass, body composition and early infant growth. Methods: Multivitamin use was assessed longitudinally in 626 women from the Healthy Start Study. Offspring body size and composition was measured with air displacement plethysmography at birth (<3 days) and postnatally (median 5.2 months). Separate multiple linear regressions assessed the relationship of weeks of daily multivitamin use with offspring mass, body composition and postnatal growth, after adjustment for potential confounders (maternal age, race, pre-pregnant body mass index; offspring gestational age at birth, sex; breastfeeding exclusivity). Results: Maternal multivitamin use was not related to offspring mass or body composition at birth, or rate of change in total or fat-free mass in the first 5 months. Multivitamin use was inversely associated with average monthly growth in offspring percent fat mass (β = −0.009, p = 0.049) between birth and postnatal exam. Offspring of non-users had a monthly increase in percent fat mass of 3.45%, while offspring at the top quartile of multivitamin users had a monthly increase in percent fat mass of 3.06%. This association was not modified by exclusive breastfeeding. Conclusions: Increased multivitamin use in the pre-conception and prenatal periods was associated with a slower rate of growth in offspring percent fat mass in the first 5 months of life. This study provides further evidence that in utero nutrient exposures may affect offspring adiposity beyond birth

Blood pressure during pregnancy, neonatal size and altered body composition: The Healthy Start study

Objective: The objective of this study is to estimate associations between changes in maternal arterial pressure during normotensive pregnancies and offspring birth weight and body composition at birth. Study Design: Prospective study of 762 pregnant normotensive Colorado women, recruited from outpatient obstetrics clinics. Repeated arterial pressure measurements during pregnancy were averaged within the second and third trimesters, respectively. Multivariable regression models estimated associations between second to third trimester changes in arterial pressure and small-for-gestational-age birth weight, fat mass, fat-free mass and percent body fat. Results: A greater second to third trimester increase in maternal arterial pressure was associated with greater odds of small-for-gestational-age birth weight. Greater increases in maternal diastolic blood pressure were associated with reductions in offspring percent body fat (-1.1% in highest vs lowest quartile of increase, 95% confidence interval: -1.9%, -0.3%). Conclusion: Mid-to-late pregnancy increases in maternal arterial pressure, which do not meet clinical thresholds for hypertension are associated with neonatal body size and composition

Combined environmental and social exposures during pregnancy and associations with neonatal size and body composition: The Healthy Start study

Background: Prenatal environmental and social exposures have been associated with decreased birth weight. However, the effects of combined exposures (CEs) in these domains are not fully understood. Here we assessed multi-domain exposures for participants in the Healthy Start study (Denver, CO) and tested associations with neonatal size and body composition. Methods: In separate linear regression models, we tested associations between neonatal outcomes and three indices for exposures. Two indices were developed to describe exposures to environmental hazards (ENV) and social determinants of health (SOC). A third index CEs in both domains (CE = ENV/10 × SOC/10). Index scores were assigned to mothers based on address at enrollment. Birth weight and length were measured at delivery, and weight-for-length z-scores were calculated using a reference distribution. Percent fat mass was obtained by air displacement plethysmography. Results: Complete data were available for 897 (64%) participants. Median (range) ENV, SOC, and CE values were 31.9 (7.1-63.2), 36.0 (2.8-75.0), and 10.9 (0.4-45.7), respectively. After adjusting for potential confounders, 10-point increases in SOC and CE were associated with 27.7 g (95% confidence interval [CI] = 12.4, 42.9 g) and 56.3 g (19.4-93.2 g) decreases in birth weight, respectively. SOC and CE were also associated with decreases in percent fat mass. Conclusions: CEs during pregnancy were associated with lower birth weight and percent fat mass. Evidence of a potential synergistic effect between ENV and SOC suggests a need to more fully consider neighborhood exposures when assessing neonatal outcomes

Prenatal Exposure to Tobacco and Offspring Neurocognitive Development in the Healthy Start Study

Objective: To explore the associations between prenatal exposure to tobacco and neurocognitive development, in the absence of prematurity or low birth weight. Study design: We followed mother-child pairs within Healthy Start through 6 years of age. Children were born at ≥37 weeks of gestation with a birth weight of ≥2500 g. Parents completed the Third Edition Ages and Stages Questionnaire (n = 246) and children completed a subset of the National Institutes of Health Toolbox Cognition Battery (n = 200). The Ages and Stages Questionnaire domains were dichotomized as fail/monitor and pass. Maternal urinary cotinine was measured at approximately 27 weeks of gestation. Separate logistic regression models estimated associations between prenatal exposure to tobacco (cotinine below vs above the limit of detection) and the Ages and Stages Questionnaire domains. Separate linear regression models estimated associations between prenatal exposure to tobacco and fully corrected T-scores for inhibitory control, cognitive flexibility, and receptive language, as assessed by the National Institutes of Health Toolbox. A priori covariates included sex, maternal age, maternal education, daily caloric intake during pregnancy, race/ethnicity, household income, maternal psychiatric disorders, and, in secondary models, postnatal exposure to tobacco. Results: Compared with unexposed offspring, exposed offspring were more likely to receive a fail/monitor score for fine motor skills (OR, 3.9; 95% CI, 1.5-10.3) and decreased inhibitory control (B: −3.0; 95% CI, −6.1 to −0.7). After adjusting for postnatal exposure, only the association with fine motor skills persisted. Conclusions: Prenatal and postnatal exposures to tobacco may influence neurocognitive development, in the absence of preterm delivery or low birth weight. Increased developmental screening may be warranted for exposed children

Proinflammatory Diets during Pregnancy and Neonatal Adiposity in the Healthy Start Study

Objective: To evaluate the association between dietary inflammatory index (DII) scores during pregnancy and neonatal adiposity. Study design: The analysis included 1078 mother–neonate pairs in Healthy Start, a prospective prebirth cohort. Diet was assessed using repeated 24-hour dietary recalls. DII scores were obtained by summing nutrient intakes, which were standardized to global means and multiplied by inflammatory effect scores. Air displacement plethysmography measured fat mass and fat-free mass within 72 hours of birth. Linear and logistic models evaluated the associations of DII scores with birth weight, fat mass, fat-free mass, and percent fat mass, and with categorical outcomes of small- and large-for-gestational age. We tested for interactions with prepregnancy BMI and gestational weight gain. Results: The interaction between prepregnancy BMI and DII was statistically significant for birth weight, neonatal fat mass, and neonatal percent fat mass. Among neonates born to obese women, each 1-unit increase in DII was associated with increased birth weight (53 g; 95% CI, 20, 87), fat mass (20 g; 95% CI, 7-33), and percent fat mass (0.5%; 95% CI, 0.2-0.8). No interaction was detected for small- and large-for-gestational age. Each 1-unit increase in DII score was associated a 40% increase in odds of a large-for-gestational age neonate (1.4; 95% CI, 1.0-2.0; P =.04), but not a small-for-gestational age neonate (1.0; 95% CI, 0.8-1.2; P =.80). There was no evidence of an interaction with gestational weight gain. Conclusions: Our findings support the hypothesis that an increased inflammatory milieu during pregnancy may be a risk factor for neonatal adiposity. Trial registration: Clinicaltrials.gov: NCT02273297