Abstract

BackgroundDisordered eating behaviors (DEB) are highly prevalent and are associated with negative long-term health outcomes. Extant research on DEB prevalence trajectories has predominantly focused on white women, thereby lacking both gender and ethnic/racial diversity, which may lead to preventive interventions that are not optimally timed for socially minoritized groups. The purpose of this study was to identify patterns in DEB trajectories from adolescence to adulthood across intersecting gender and ethnic/racial identities. MethodsParticipants (n = 1314) were from Project EAT (Eating and Activity in Teens and Young Adults), a population-based sample in the United States. Unhealthy weight control behaviors and binge eating were assessed across four waves at 5-year intervals. Gender-stratified generalized estimating equations (GEE) analyses were applied to examine ethnic/racial and gender differences in the prevalence trajectories of two forms of DEB (unhealthy weight control behaviors and binge eating). ResultsHispanic/Latina young women reported heightened prevalence of unhealthy weight control behaviors and binge eating during adolescence (82.4% and 31.1%) relative to women with other ethnic/racial identities (44–70.2% and 8.8–18.2%) at any other developmental time point. Black/African American women reported linear increases in unhealthy weight control behaviors from adolescence (46.6%) to adulthood (65.5%), with nearly 20% greater prevalence relative to white women (44.6%) during adulthood. Among men, prevalence of unhealthy weight control behaviors was higher among Hispanic/Latinos (60.7–68.0%) and Asian Americans (41.9–56.7%) relative to Black/African American (24.6–36.9%) and white men (25.7–34.9%). Similarly, Hispanic/Latino young men reported up to ten or more times higher prevalence of binge eating during adolescence (22.8%) and adulthood (26.8%) relative to men from other ethnic/racial identities at any other time point (1.7–12.3%). ConclusionsEthnic/racial disparities in DEB prevalence vary across development, DEB subtype, and by gender. Targeted preventive interventions, or interventions that address these different trajectories, that are optimally timed may reduce these disparities.

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