Neighbourhood socioeconomic indicators and depressive symptoms in the Czech Republic: a population based study
Language English Country Switzerland Media print
Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
Grant support
064947/Z/01/Z
Wellcome Trust - United Kingdom
081081/Z/06/Z
Wellcome Trust - United Kingdom
1R01 AG23522-01
NIA NIH HHS - United States
- MeSH
- Residence Characteristics * MeSH
- Poverty * MeSH
- Depression economics epidemiology psychology MeSH
- Middle Aged MeSH
- Humans MeSH
- Logistic Models MeSH
- Unemployment MeSH
- Aged MeSH
- Educational Status MeSH
- Population Surveillance MeSH
- Health Surveys MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Geographicals
- Czech Republic epidemiology MeSH
OBJECTIVES: Previous research shows only limited evidence on the contextual (neighbourhood-based) socioeconomic influences on mental health and depression. We investigated the association between individual and neighbourhood socioeconomic characteristics and depressive symptoms in the Czech Republic. METHODS: Dichotomized CESD score of depressive symptoms was used as the outcome in a random sample of 3534 men and 4082 women aged 45-69 years in the Czech HAPIEE Study. 220 small areas were characterized by the proportion of university educated persons and the proportion of unemployed from the economically active population in the 2001 Census. Multilevel logistic regression was used for the analysis. RESULTS: After controlling for individual-level variables, the effects of area-based characteristics were largely eliminated. The strongest area-based effect was that of the proportion of university educated persons; the ORs for 2(nd), 3(rd) and 4(th) quartile, compared with the 1(st) quartile, were 1.02, 0.93, and 0.82, respectively (p-value for trend 0.06). There were no cross-level interactions between socioeconomic variables. CONCLUSIONS: The effects of neighbourhood characteristics in this study were largely explained by individual socioeconomic variables.
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