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Published on: April 26, 2024
Neighbourhood disadvantage and depressive symptoms among adolescents followed into emerging adulthood
Rise B Goldstein1, Awapuhi K Lee2,3, Denise L Haynie2
1Social and Behavioral Sciences Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA goldster@mail.nih.gov.
Background:
Residents of disadvantaged neighbourhoods report higher levels of depressive symptoms; however, few studies have employed prospective designs during adolescence, when depression tends to emerge. We examined associations of neighbourhood social fragmentation, income inequality and median household income with depressive symptoms in a nationally representative survey of adolescents.
Methods:
The NEXT Generation Health Study enrolled 10th-grade students from 81 US high schools in the 2009-2010 school year. Depressive symptoms were assessed with the Modified Depression Scale (wave 1) and the paediatric Patient-Reported Outcome Measurement Information System (waves 2-6). Neighbourhood characteristics at waves 1, 3, 4, and 5 were measured at the census tract level using geolinked data from the American Community Survey 5-year estimates. We used linear mixed models to relate neighbourhood disadvantage to depressive symptoms controlling for neighbourhood and individual sociodemographic factors.
Results:
None of the models demonstrated evidence for associations of social fragmentation, income inequality or median household income with depressive symptoms.
Conclusion:
Despite the prospective design, repeated measures and nationally representative sample, we detected no association between neighbourhood disadvantage and depressive symptoms. This association may not exist or may be too small to detect in a geographically dispersed sample. Given the public health significance of neighbourhood effects, future research should examine the developmental timing of neighbourhood effects across a wider range of ages than in the current sample, consider both objective and subjective measures of neighbourhood conditions, and use spatially informative techniques that account for conditions of nearby neighbourhoods.
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