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Trajectories of depressive symptoms and neighborhood changes from adolescence to adulthood: Latent class growth analysis and multilevel growth curve models

  • United States Department of Energy

Research output: Contribution to journal › Article › peer-review

Abstract

The role of neighborhood socioeconomic status (SES) and racial/ethnic composition on depression has received considerable attention in the United States. This study examines associations between trajectory patterns of neighborhood changes and depressive symptoms using data from Waves I-IV of the National Longitudinal Study of Adolescent to Adult Health. We used latent class growth analysis to determine the number and distribution of person-centered trajectories for neighborhood characteristics, and multilevel growth curve models to examine how belonging to each class impacted depression trajectories from ages 13 to 32 among non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, and non-Hispanic Others (NHO). The distribution of neighborhood SES classes across racial/ethnic groups suggests significant levels of economic inequality, but had no effect on depressive symptoms. A more complex picture emerged on the number and distribution of racial/ethnic composition latent class trajectories. Compared to NHB peers who lived in predominantly NHW neighborhoods from adolescence to adulthood, NHBs in more diverse neighborhoods had lower risk for depressive symptoms. Conversely, Hispanics living in neighborhoods with fewer NHWs had higher risk for depressive symptoms. Among NHOs, living in neighborhoods with a critical mass of other NHOs had a protective effect against depressive symptoms.

Original languageEnglish
Article number1829
JournalInternational Journal of Environmental Research and Public Health
Volume17
Issue number6
DOIs
StatePublished - Mar 2 2020

ASJC Scopus Subject Areas

  • Pollution
  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

Keywords

  • Depression
  • Health disparities
  • Latent class growth analysis
  • Multilevel growth curve models
  • Neighborhood changes
  • Neighborhood socioeconomic status
  • Racial/ethnic composition

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