Literature DB >> 20819785

Body mass trajectories through adulthood: results from the National Longitudinal Survey of Youth 1979 Cohort (1981-2006).

Truls Ostbye1, Rahul Malhotra, Lawrence R Landerman.   

Abstract

BACKGROUND: Most studies describing change in body mass through adulthood model an 'average' trajectory bearing the same functional form in the underlying population. Latent-class growth modelling has revealed the presence of several underlying body mass/obesity trajectory groups among children and adolescents, but has not been applied to capture adult body mass trajectories. We apply the technique to identify adult body mass trajectory groups, risk factors for group membership and (time-varying) modifiers of trajectory level within each group, and assess association between group membership and important health outcomes in midlife.
METHODS: Body mass trajectory groups, from age 18 to 49 years, were identified using latent-class growth modelling based on the National Longitudinal Survey of Youth 1979 (n = 9681). Role of gender, race/ethnicity and age cohort as risk factors for group membership, and of highest grade of education completed, years of urban living, years in employment, years in poverty and years married as modifiers of trajectory level was evaluated.
RESULTS: Four trajectory groups, 'normal weight', 'overweight', 'late adulthood obesity' and 'early adulthood obesity' were identified. Males, Blacks and those born later had higher odds of being in the three latter groups. More education and years married lowered the trajectory within each group. The prevalence of most health outcomes was lowest in the 'normal weight' group, somewhat greater in the 'overweight' group, greater again in the 'late adult obesity group' and highest in the 'early adulthood obesity' group.
CONCLUSION: Regular body mass index screening and monitoring in early adult life may identify a person as belonging to one of these four groups early, and allow the individual and health-care providers opportunities to initiate behavioural or other interventions better tailored to the specific group.

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Mesh:

Year:  2010        PMID: 20819785     DOI: 10.1093/ije/dyq142

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  47 in total

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