BackgroundThe purpose of this study was to investigate the relationship between multiple chronic diseases and depressive symptoms in middle-aged and elderly populations.MethodsThis study was performed using the 2009 Korean Community Health Survey, which targeted adults over the age of 40 (N = 156,747 participants, 88,749 aged 40–59 years and 67,998 aged ≥60 years). The Korean version of the Center for Epidemiologic Studies Depression Scale (CES-D-K) was used as the measurement tool for depressive symptoms (CES-D-K score over 16). Multiple chronic diseases were defined as the concurrent presence of two or more chronic diseases.ResultsThe prevalence and risk ratios (RRs) of experiencing depressive symptoms increased in the presence of multiple chronic diseases and with the number of comorbidities. The RRs of experiencing depressive symptoms according to the presence of multiple chronic diseases were higher in the middle-aged population (adjusted RR, 1.939, 95% confidence limits (CL), 1.82-2.06) than in the elderly population (adjusted RR, 1.620, 95% CL, 1.55-1.69). In particular, middle-aged women who suffer from 4 or more chronic diseases have the highest RR (adjusted RR, 4.985, 95% CL, 4.13-6.03) for depressive symptoms.ConclusionsMultiple chronic diseases are closely associated with depressive symptoms in middle-aged and elderly populations. Given the mutual relationship between multiple chronic diseases and depressive symptoms, attention to and the assessment of depressive symptoms are needed in people with multiple chronic diseases.Electronic supplementary materialThe online version of this article (10.1186/s12889-017-4798-2) contains supplementary material, which is available to authorized users.

To prevent adolescent drinking and smoking, this study proposed a strategy based on the ecological perspective. Methods: The study applied multilevel moderated logistic regression analysis on nationally representative individual-level (2,046 9th grade adolescents) and neighborhood-level (92 geographic areas) data. Results: There was a positive association between risky neighborhood environments (e.g., rate of smoking, drinking, and presence of saloon/bars accommodation) and rates of adolescent drinking and smoking. Furthermore, the interplay between risky neighborhood environments and school adjustment pointed to a possible protective effect of a high level of school adjustment in predicting smoking and drinking among adolescents. Conclusion: Findings highlighted the importance of considering multiple neighborhood social contexts surrounding adolescents to understand their risky behavior. Furthermore, positive intervention strategies that focus on adolescents' positive development within the school domain may act to protect adolescents from harmful neighborhood environments.