Latent Heterogeneity in Long-Term Trajectories of Body Mass Index in Older Adults

Abstract

Objectives To evaluate latent heterogeneity in long-term trajectories of body weight in older adults. Methods We analyzed 14-year longitudinal data on 10,314 older adults from the Health and Retirement Study. Semiparametric mixture models identified latent subgroups of similar trajectories of body mass index (BMI). Results Five distinct trajectory subgroups emerged: normal starting-BMI with accelerated increase over time (trajectory #1), overweight and increasing (trajectory #2), borderline-obese and increasing (trajectory #3), obese and increasing (trajectory #4), and morbidly obese with decelerating gain (trajectory #5). Blacks and Hispanics had greater risk of membership in ascending high-BMI trajectory groups. Females had approximately half the risk of following overweight and obese increasing BMI trajectories compared with males. Discussion Distinct latent subgroups of BMI trajectories and significant racial/ethnic and gender trajectory heterogeneity exist in the older adult population. The propensity of men and minorities to experience high-risk BMI trajectories may exacerbate existing disparities in morbidity/ mortality in older age.

Fatores associados e índice de adiposidade corporal (IAC) em adultos: estudo de base populacional

“…Também foi observada uma associação positiva entre a adiposidade corporal e idade, com aumento médio de, aproximadamente, 1,7% em cada categoria de idade. Torna-se importante destacar que há evidencias na literatura demonstrando que a relação entre a adiposidade e mortalidade pode variar em função do aumento da idade [45][46][47] , o que reforça a necessidade de verificarmos o excesso de adiposidade corporal em relação à faixa etária dos indivíduos. Em uma coorte com 77.505 mulheres pós-menopausa, Thomson et al 48 encontraram valores médios para o IAC (32,8 dp 6,4), na faixa etária de 50 a 59 anos, similares aos observados neste estudo (33,4 dp 6,9).…”

Trajectories of Body Mass Index from Young Adulthood to Middle Age among Canadian Men and Women

“…Within each trajectory group, the values of average posterior probability of group membership were ascertained [19]. The trajectory analysis was conducted separately for women and men because of the compelling evidence of gender differences in obesity [5,22,25,28,42,54].…”

“…However, these studies examined the US population and did not consider some important determinants of obesity such as food insecurity and lifestyle factors including smoking and physical activity. Moreover, the majority of previous research has focused on the associations among sociodemographic characteristics, such as gender, race/ethnicity, age, and educational attainment, and BMI trajectories [5,22,25,26,28,29]. Few studies have examined whether behavioural or lifestyle factors, such as smoking, drinking, or physical activity, alter BMI trajectories.…”

“…Trajectory analyses effectively capture body weight changes over time and can offer new insights into the determinants of obesity [5,6]. However, many existing studies that have investigated obesity neither capture weight fluctuations nor detect the trajectory of body weight changes over time.…”

“…For example, the generalized model can test if differences exist across cohorts in their developmental trajectories (i.e., cohort effects) when multiple cohorts are combined in order to construct an overall trajectory model [19]. Furthermore, by utilizing LCGM, the impact of obesity-related factors on distinct levels of BMI trajectories can be examined [5]. Although LCGM has been used to identify BMI trajectories for youth and children [22][23][24], only three studies applied LCGM to analyze the patterns of BMI or body weight changes on a substantial period of adult life [25][26][27].…”