A survey-wide association study to identify youth-specific correlates of major depressive episodes

• Published in: PloS one 2020-05, Vol.15 (5), p.e0232373-e0232373
• Main Author: Dhodapkar, Rahul Madhav
• Format: Article
• Language: English
• Subjects: Adolescence; Adolescent; Adults; Age; Age Distribution; Biology and Life Sciences; Cannabis; Child; Child health; Codes; Cognitive ability; Confidence intervals; Correlation; Correlation analysis; Correlation coefficient; Correlation coefficients; Demographic aspects; Depression (Mood disorder); Depressive Disorder, Major - epidemiology; Diseases; Drinking (Alcoholic beverages); Drug abuse; Drug use; Female; Genetics; Genomes; Government programs; Health aspects; Humans; Hypotheses; Hypothesis testing; Identification methods; Juvenile drug abuse; Major depressive disorder; Male; Marijuana; Measurement methods; Medical research; Medicine and Health Sciences; Mental depression; Mental disorders; Mental health; Morbidity; Mortality; Novels; People and Places; Physical Sciences; Polls & surveys; Psychological aspects; Research and Analysis Methods; Risk analysis; Risk factors; Screening; Social Sciences; Statistics; Studies; Surveys; Surveys and Questionnaires; Teenagers; Variables; Young Adult; Youth
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0232373

Major depressive disorder is a common disease with high mortality and morbidity worldwide. Though peak onset is during late adolescence, the prevalence of major depressive disorder remains high throughout adulthood. Leveraging an association study design, this study screened a large number of variables in the 2017 National Survey on Drug Use and Health to characterize differences between adult and youth depression across a wide array of phenotypic measurements. All dichotomous variables were manually identified from the survey for association screening. Association between each dichotomous variable and past-year major depressive episode (MDE) occurrence was calculated as an odds ratio for adults (≥18 years) and youth (12-17 years), and tested for significance with Fischer's exact test. Logarithm of the calculated odds ratios were plotted and fitted to a linear model to assess correlation between adult and youth risk factors. Many of the screened variables showed similar association between past-year depressive episode occurrence in youth and adults; Lin's concordance correlation coefficient between adult and youth associations was 0.91 (95% CI 0.89-0.92). Differentially associated variables were identified, tracking: female sex, alcohol use, cigarette use, marijuana use, Medicaid/CHIP coverage, cognitive changes due to a mental, physical or emotional condition, and respondents' identification of a single depressive event as the worst experienced. While some youth-specific correlates of major depressive episodes were identified through screening, including some novel associations, most examined variables showed similar association with youth and adult depression. Further study of results is warranted, especially concerning the finding of increased association between marijuana use and depressive episodes in youth.