Abstract
OBJECTIVE: To ascertain the predictors of body size at 2 y of age.
DESIGN: Prospective, longitudinal study of risk factors for weight gain of infants at high or low risk of obesity by virtue of their mothers' obesity or leanness.
SUBJECTS: A total of 40 infants of obese mothers and 38 infants of lean mothers, equally divided among boys and girls.
METHODS: Measurement of dependent variables: weight, length and skinfold thicknesses at 3, 6, 9, 12, 18 and 24 months and percent body fat at 3, 12 and 24 months. Measurement of independent variables: average daily caloric consumption at 3, 6, 9, 12, 18 and 24 months; and, at 3 months, nutritive sucking behavior during a test meal, total energy expenditure (TEE), sleeping energy expenditure (SEE), estimation of nonsleeping energy expenditure (TEE−SEE) and socioeconomic status. Parental weights and heights were obtained by self-report at the time of recruitment. Partial correlation and mixed effects linear regression analyses were performed.
RESULTS: Measures of body size (weight, length, skinfold thicknesses) and percent of body fat were almost identical between high- and low-risk groups at all times. Energy intake during six occasions over the 2 y, sucking behavior, family income and TEE predicted weight gain, controlling for body length. Parental body mass index was not associated with the child's body size during the first 2 y. During the first year, there were strong lagged correlations between energy intake and body weight and smaller correlations between protein intake and body weight.
CONCLUSION: Energy intake, and not energy expenditure, was the determinant of body size in these infants at 2 y of age, as it had been at 1 y. Sucking behavior and TEE (positively) and family income (negatively) also contributed to body weight at 2 y. The novel finding of a lagged correlation between energy intake and body weight early in life suggests that energy intake is programmed for future growth and development.
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Acknowledgements
The authors wish to acknowledge the support of the General Clinical Research Center of the Children's Hospital of Philadelphia and the staff of the Infant Growth Study: Aaron Curry, Julia Kerns, Katherine Maragos, Pelin Munis, Diane Sandefur, Cigdem Tanrikut, Agnes Trinh, Robert Waterland and Linnea Welker and, for anthropometric consultation, Dr Babette Zemel.
Supported in part by Grants 31050 and 01183 from the National Institute of Mental Health, grant MH56251 from the National Institute of Mental Health and the National Institute of Diabetes and Digestive and Kidney Diseases grant 38633 from the National Heart, Lung and Blood Institute, grant RR00240 from the National Institutes of Health, and grant DK30031 from the Clinical Nutrition Research Unit of the University of Chicago.
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Appendix A
Appendix A
Technical details for the mixed model
All correlations presented were partial correlations controlling for sampling by risk group and computation of all partial correlations was repeated using partial rank correlation statistics.
The covariance structure for the linear mixed effects regression model was assumed to be autoregressive with an additional random effect for subject.55 Model parameters were estimated using Restricted Maximum Likelihood (REML)56 as implemented in SAS Proc.Mixed.57 Weights assessed at 6, 9, 12, 18 and 24 months were standardized in order to permit simultaneous estimation of regression slope coefficients over all time points. This was done by subtracting time-specific mean values and dividing by time-specific SDs. The model controlled for prior standardized weight and length (ie, at time=t−1) when predicting future (standardized) weight (ie, at time=t). The primary explanatory variables of interest included average energy intake during time=t−1, total sucks observed at the month 3 feeding behavior assay, family income, SEE assessed at month 3, male gender and maternal BMI. As a consequence of standardization, slope coefficients could be interpreted in terms of standardized effect sizes. Specifically, for each quantitative variable we estimated the expected effects of a 1 SD increase on future weight controlling for prior weight and length in terms of its predicted impact measured in time-specific SD units. The overall predictive value of the model was assessed by computing the proportional reduction in mean squared error (ie, R2) between predictions made by the model to those made by a null model that always predicted time-specific mean values. Similarly, the predictive values of individual factors were assessed by comparing the full model to models eliminating one variable at a time (ie, partial R2). Secondary explanatory variables were examined as additions to the primary set of factors or as replacements and included percentages of caloric intake attributable to proteins, fats, or carbohydrates and TEE (available in a subset of subjects). Results for secondary outcome variables were obtained by replacing weight at time=t and the control variable at time=t−1 with triceps skinfolds, subscapular skinfolds and the mean of four skinfolds.
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Stunkard, A., Berkowitz, R., Schoeller, D. et al. Predictors of body size in the first 2 y of life: a high-risk study of human obesity. Int J Obes 28, 503–513 (2004). https://doi.org/10.1038/sj.ijo.0802517
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DOI: https://doi.org/10.1038/sj.ijo.0802517
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