Abstract
BackgroundModeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information.MethodsAmong 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with fractional polynomial functions. From each child's fitted trajectory, we estimated age and BMI at infancy peak and adiposity rebound, and velocity and area under curve between 1 week, infancy peak, adiposity rebound, and 18 years.ResultsAmong boys, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.2 (0.9) and 49.2 (11.9) months, respectively. Among girls, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.4 (1.1) and 46.8 (11.0) months, respectively. Ages at infancy peak and adiposity rebound were weakly inversely correlated (r = -0.09). BMI at infancy peak and adiposity rebound were positively correlated (r = 0.76). Blacks had earlier adiposity rebound and greater velocity from adiposity rebound to 18 years of age than whites. Higher birth weight z-score predicted earlier adiposity rebound and higher BMI at infancy peak and adiposity rebound. BMI trajectories did not differ by birth year or type of health insurance, after adjusting for other socio-demographics and birth weight z-score.ConclusionsChildhood BMI trajectory characteristics are informative in describing childhood body mass changes and can be estimated conveniently. Future research should evaluate associations of these novel BMI trajectory characteristics with adult outcomes.
Highlights
Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes
There were no substantial differences in sex, birth weight, or year of birth between the two samples, but the analytic sample contained a higher proportion of whites (71.8% vs 42.9%) and a lower proportion of unknown race/ethnicity (15.3% vs 37.7%) as well as lower proportion (3.9% vs 5.2%) of Medicaid-insured children than the excluded sample (Table 1)
Our analysis showed that the majority of BMI trajectory characteristics were moderately or strongly correlated with each other
Summary
Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Previous studies have observed weak or moderate correlations (r = 0.2-0.5) between early childhood (< 7 years of age) and adulthood BMI [6,7]. Most of these studies [2,8,9,10] have used BMI at fixed ages or change in BMI between fixed ages as predictors. The capacity of childhood BMI to predict adult BMI can potentially be improved by using a child’s BMI trajectory, in addition to or in place of his or her BMI at specific ages
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