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Author: Riosmena, Fernando
Resulting in 2 citations.
1. Ng, Carmen D.
Elliott, Michael R.
Riosmena, Fernando
Cunningham, Solveig A.
Beyond Recent BMI: BMI Exposure Metrics and their Relationship to Health
SSM - Population Health 11 (August 2020): 100547.
Also: https://www.sciencedirect.com/science/article/pii/S2352827319303064
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Body Mass Index (BMI); Health, Chronic Conditions; Health/Health Status/SF-12 Scale

Body mass index (BMI) is generally used to classify adiposity. Despite the fact that the consequences of adiposity for chronic health accumulate and manifest over time, most population health research exploring the implications of high BMI measures only its recent intensity. Some studies have used retrospective measures involving maximum weight, and even fewer have used BMI at multiple time points to estimate cumulative exposure to adiposity. The goal of this study was to compare BMI exposure metrics that captured different dimensions of body mass -- intensity, history, and duration -- in models of health indicators linked with adiposity. We used self-reported BMI of young adults (ages 18 - 33 years, n = 8,608) across 11 waves of data from the National Longitudinal Survey of Youth 1997 to evaluate eight BMI exposure metrics: most recent, maximum, mean, and median BMI, proportion of time with overweight/obesity, and excess BMI-years with overweight/obesity. We used these metrics in models of self-reported general health, chronic condition, and diabetes, and ascertained how most recent BMI performed when compared with other metrics that better capture the dynamics of BMI. The Akaike information criteria and Vuong tests were used for model comparison, and the strengths of associations were also compared. Most recent BMI was the best metric for explaining general health. Median BMI was best for explaining diabetes, with most recent BMI under-estimating the association by 13% relative to median BMI. For chronic condition, there was no clear best metric. We concluded that most recent BMI is useful for explaining health outcomes, though other metrics should also be given consideration, particularly for conditions that develop over time. Metrics that accounted for both intensity and history performed quite well, but the duration measures might be less useful.
Bibliography Citation
Ng, Carmen D., Michael R. Elliott, Fernando Riosmena and Solveig A. Cunningham. "Beyond Recent BMI: BMI Exposure Metrics and their Relationship to Health." SSM - Population Health 11 (August 2020): 100547.
2. Rafei, Ali
Elliott, Michael R.
Jones, Rebecca E.
Riosmena, Fernando
Cunningham, Solveig A.
Mehta, Neil K.
Obesity Incidence in U.S Children and Young Adults: A Pooled Analysis
American Journal of Preventive Medicine published online (4 March 2022): DOI: 10.1016/j.amepre.2021.12.021.
Also: https://www.sciencedirect.com/science/article/pii/S0749379722000666
Cohort(s): NLSY79, NLSY97
Publisher: Elsevier
Keyword(s): Childhood; Early Childhood Longitudinal Study (ECLS-B, ECLS-K); National Longitudinal Study of Adolescent Health (AddHealth); Obesity; Transition, Adulthood

Introduction: Obesity prevalence among children and adolescents has risen sharply, yet there is a limited understanding of the age-specific dynamics of obesity as there is no single nationally representative cohort following children into young adulthood. Investigators constructed a pooled data set of 5 nationally representative panels and modeled age-specific obesity incidence from childhood into young adulthood.

Methods: This longitudinal prospective follow-up used 718,560 person-years of observation in a pooled data set of 5 high-quality nationally representative panels--National Longitudinal Survey of Youth 1979 and 1997, National Longitudinal Study of Adolescent Health, and Early Childhood Longitudinal Study-Kindergarten cohorts of 1998 and 2011--constructed by the authors, covering 1980-2016. Differences in obesity incidence across birth cohorts and disparities in obesity incidence by sex and race/ethnicity (non-Hispanic Black, Hispanic, and non-Hispanic White) were tested in multivariate models. Data were analyzed from September 2018 to October 2021.

Results: Obesity incidence increased by approximately 6% for each 1 year of age (hazard ratio=1.06, 95% CI=1.05, 1.07); however, incidence was nonlinear, exhibiting an inverted "U"-shaped pattern before 15 years of age and then rising from adolescence through 30 years. Obesity incidence more than doubled between the cohorts born in 1957-1965 and those born in 1974-1985 during adolescence. There was no significant change among those born in 1991-1994 and 2003-2006 up to age 15 years. Compared with non-Hispanic White children, non-Hispanic Black and Hispanic children had higher obesity incidence in all study cohorts. The magnitude of these disparities on the relative scale remained stable throughout the study period.

Bibliography Citation
Rafei, Ali, Michael R. Elliott, Rebecca E. Jones, Fernando Riosmena, Solveig A. Cunningham and Neil K. Mehta. "Obesity Incidence in U.S Children and Young Adults: A Pooled Analysis." American Journal of Preventive Medicine published online (4 March 2022): DOI: 10.1016/j.amepre.2021.12.021.