Obesity from Childhood to Mid-Adulthood in the United States: A Synthetic Cohort Approach to Measuring Health Trajectories

Solveig Cunningham, Emory University
Natalia Poveda Rey, Pontificia Universidad Javeriana
Neil Mehta, University of Texas Medical Branch
Michael Elliott, University of Michigan

Obesity dynamics early in life are likely important for long-term health, but have only been described piecemeal, because nationally representative longitudinal datasets are few and have limited follow-up duration. We created a synthetic cohort by combining two nationally US representative datasets, the Early Childhood Longitudinal Study, Kindergarten Class of 1998-9 (n=21,120; ages 4–16y; birth cohort of 1991-94), and the National Longitudinal Survey of Youth 1997 (n=8,984; ages 12–41y; birth cohort of 1980-84). We used the older-age cohort to impute future weight trajectories of children in the younger-age cohort by matching based on subject-level BMI trajectories estimated via linear mixed models. Trajectories to age 41y in 2035 were projected for children observed up to 2007 (mean age 13.5y). The prevalence of obesity increased from 10.0% at age 4y to 55.4% at age 41y. Obesity incidence rates peak at ages 8y [4.00/100 person-years (PY), 26y [4.48/100 PY], and 38y [3.60/100 PY]. This synthetic cohort approach can be used to characterize dynamics of obesity and other conditions by maximizing data from shorter “life segments”. Findings suggest that today’s young adults will continue to become heavier as they age, and key periods for obesity prevention are middle childhood, mid-twenties, and late thirties.

Keywords: Linked data sets , Longitudinal studies , Health and Morbidity, Children, Adolescents, and Youth

See paper.