Latent comorbid depression and anxiety symptoms across sex and race/ethnic subgroupings in a national epidemiologic study. (September 2018)

• Record Type: Journal Article
• Authors: Rudenstine, Sasha; Espinosa, Adriana
• Is Part Of: Journal of psychiatric research. Volume 104(2018)
• Page Start: 114
• Page End: 123
• Publication Date: 2018-09
• Subjects: Depression -- Anxiety -- Comorbidity -- Sex -- Race -- Ethnicity -- Latent class analysis; Psychiatry -- Periodicals; Mental Disorders -- Periodicals; Maladies mentales -- Périodiques; Psychiatry; Electronic journals; Periodicals; 616.89005
• DOI: 10.1016/j.jpsychires.2018.07.005
• Languages: English
• ISSNs: 0022-3956

Abstract

Abstract: The heterogeneity of mood and anxiety disorders has been widely documented and epidemiologic studies have found different prevalence rates for psychiatric disorders across subgroups (i.e. sex and race/ethnic). The current study compares the latent class structure across sex and race/ethnic groups to determine group differences in these latent class configurations. This study utilized data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample from the United States (N = 43, 093). First, latent class analyses (LCAs) were used to assess subtypes of symptoms of depression and anxiety that characterize a latent class structure for the population represented by NESARC. Second, group LCAs were conducted across sex and race/ethnicity to compare the latent class structure across these groups. The results suggest a 7-class model is the best fit for the population as well as for the male, non-Hispanic White, and Black subgroups. Females fit best an 11-class model, Hispanics a 5-class model and Asian and American Indian subgroups a 4-class model. These results indicate that subgroups of sex and race/ethnicity do not share the same latent construct for symptoms of anxiety and depression. Understanding the variability in the presentation of comorbid mood and anxiety across subgroups has the potential to inform person-centered approaches to care as well as targeted and multicultural interventions to improve population health.