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Does a parsimonious measure of complex body mass index trajectories exist?

ABSTRACT: BACKGROUND:A single measure that distills complex body mass index (BMI) trajectories into one value could facilitate otherwise complicated analyses. This study creates and assesses the validity of such a measure: average excess BMI. METHODS:We use data from Waves I-IV of the National Longitudinal Study of Adolescent to Adult Health (n?=?17,669). We calculate average excess BMI by integrating to find the area above a healthy BMI trajectory and below each subject-specific trajectory and divide this value by total study time. To assess validity and utility, we (1) evaluate relationships between average excess BMI from adolescence to adulthood and adult chronic conditions, (2) compare associations and fit to models using subject-specific BMI trajectory parameter estimates as predictors, and (3) compare associations to models using BMI trajectory parameter estimates as outcomes. RESULTS:Average excess BMI from adolescence to adulthood is associated with increased odds of hypertension (OR?=?1.56; 95% CI: 1.47, 1.67), hyperlipidemia (OR?=?1.36; 95% CI: 1.26, 1.47), and diabetes (OR?=?1.57; 95% CI: 1.47, 1.67). The odds associated with average excess BMI are higher than the odds associated with the BMI intercept, linear, or quadratic slope. Correlations between observed and predicted health outcomes are slightly lower for some models using average excess BMI as the focal predictor compared to those using BMI intercept, linear, and quadratic slope. When using trajectory parameters as outcomes, some co-variates associate with the intercept, linear, and quadratic slope in contradicting directions. CONCLUSIONS:This study supports the utility of average excess BMI as an outcome. The higher an individual's average excess BMI from adolescence to adulthood, the greater their odds of chronic conditions. Future studies investigating longitudinal BMI as an outcome should consider using average excess BMI, whereas studies that conceptualize longitudinal BMI as the predictor should continue using traditional latent growth methods.

SUBMITTER: Sokol RL

PROVIDER: S-EPMC6430191 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Does a parsimonious measure of complex body mass index trajectories exist?

Sokol Rebeccah L RL Gottfredson Nisha C NC Poti Jennifer M JM Halpern Carolyn T CT Shanahan Meghan E ME Fisher Edwin B EB Ennett Susan T ST

International journal of obesity (2005) 20180911 5

<h4>Background</h4>A single measure that distills complex body mass index (BMI) trajectories into one value could facilitate otherwise complicated analyses. This study creates and assesses the validity of such a measure: average excess BMI.<h4>Methods</h4>We use data from Waves I-IV of the National Longitudinal Study of Adolescent to Adult Health (n = 17,669). We calculate average excess BMI by integrating to find the area above a healthy BMI trajectory and below each subject-specific trajectory ...[more]

PMID: 30206334

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Project description:Little is known about body size over the life-course and non-communicable disease risk in low- and middle-income country populations. Our study explored the role of body mass index (BMI) trajectories from infancy through mid-adulthood on cardio-metabolic disease (CMD) risk factors in a prospective cohort of Guatemalan adults. Study participants were born in Guatemala from 1962-77 and have been followed prospectively since participating in a nutrition supplementation trial as children. Sex-specific BMI latent class trajectories were derived using latent class growth modeling from up to 22 possible BMI values from age 1 month to 42 years measured between 1969 and 2004. CMD risk factors were assessed in 2015-17 (at age 37-54 years) using anthropometry, blood glucose and lipids, and blood pressure. We used logistic regression to assess the role of BMI trajectory on CMD risk factors in 510 women and 346 men (N = 856). We identified two BMI latent classes for women (low [n = 287, 56.3%] and high [n = 223, 43.7%]) and three classes for men (low [n = 141, 40.8%], medium [n = 160, 46.2%], and high [n = 45, 13.0%]). Given the small percentage of men in the high BMI latent class, we collapsed the medium and high BMI latent classes for men (n = 205, 59.1%). Among the most prevalent CMD risk factors at ages 37-54 years were abdominal obesity defined by waist-height ratio (99.6% of women and 87.3% of men), obesity defined by percent body fat (96.6% of women and 75.9% of men), low HDL-c (87.5% of women and 74.5% of men), and elevated triglycerides (78.3% of women and 73.6% of men). Except for obesity defined by BMI, we found no associations between BMI latent class and CMD risk factors in women. Among men, BMI latent class was not associated with CMD risk factors after controlling for current BMI. For the CMD risk factors we analyzed, the role of early life BMI on adult CMD appeared to be mediated by adult BMI among men-highlighting the need to establish and maintain healthy body weight over the life course.

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Does a parsimonious measure of complex body mass index trajectories exist?

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Does a parsimonious measure of complex body mass index trajectories exist?

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