%0 Journal Article %T Wealth inequality and mental disability among the Chinese population: a population based study %J International journal of environmental research and public health %D 2015 %A Wang, Zhenjie %A Du, Wei %A Pang, Lihua %A Zhang, Lei %A Chen, Gong %A Zheng, Xiaoying %V 12 %N 10 %P 13104-13117 %X In the study described herein, we investigated and explored the association between wealth inequality and the risk of mental disability in the Chinese population. We used nationally represented, population-based data from the second China National Sample Survey on Disability, conducted in 2006. A total of 1,724,398 study subjects between the ages of 15 and 64, including 10,095 subjects with mental disability only, were used for the analysis. Wealth status was estimated by a wealth index that was derived from a principal component analysis of 10 household assets and four other variables related to wealth. Logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence interval (CI) for mental disability for each category, with the lowest quintile category as the referent. Confounding variables under consideration were age, gender, residence area, marital status, ethnicity, education, current employment status, household size, house type, homeownership and living arrangement. The distribution of various types and severities of mental disability differed significantly by wealth index category in the present population. Wealth index category had a positive association with mild mental disability (p for trend <0.01), but had a negative association with extremely severe mental disability (p for trend <0.01). Moreover, wealth index category had a significant, inverse association with mental disability when all severities of mental disability were taken into consideration. This study's results suggest that wealth is a significant factor in the distribution of mental disability and it might have different influences on various types and severities of mental disability.

Language: en

%G en %I MDPI: Multidisciplinary Digital Publishing Institute %@ 1661-7827 %U http://dx.doi.org/10.3390/ijerph121013104