Pikhartova Jitka, Chandola Tarani, Kubinova Ruzena, Bobak Martin, Nicholson Amanda, Pikhart Hynek
Department of Epidemiology and Public Health, University College London, London WC1E 6BT, United Kingdom.
Int J Public Health. 2009;54(4):283-93. doi: 10.1007/s00038-009-8029-1.
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.
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.
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.
The effects of neighbourhood characteristics in this study were largely explained by individual socioeconomic variables.
先前的研究表明,关于背景(基于社区)社会经济因素对心理健康和抑郁症的影响,证据有限。我们调查了捷克共和国个体和社区社会经济特征与抑郁症状之间的关联。
在捷克HAPIEE研究中,以45 - 69岁的3534名男性和4082名女性的随机样本为对象,将抑郁症状的二分法CESD评分用作结果。220个小区域的特征是根据2001年人口普查中受过大学教育的人员比例和经济活动人口中的失业比例来确定的。采用多水平逻辑回归进行分析。
在控制个体水平变量后,基于区域的特征影响在很大程度上被消除。基于区域的最强影响因素是受过大学教育的人员比例;与第一四分位数相比,第二、第三和第四四分位数的比值比分别为1.02、0.93和0.82(趋势p值为0.06)。社会经济变量之间不存在跨水平交互作用。
本研究中社区特征的影响在很大程度上可由个体社会经济变量来解释。