Health Disparities between the Rural and Urban Elderly in China: A Cross-Sectional Study

Abstract

Background: China is becoming an aging society, and the proportion of the population aged 60 years and above is increasing. There is a dualistic urban–rural economic structure between urban and rural areas in China, but there are few comparative health studies on the self-assessed health (SAH) status of the elderly between urban and rural areas. The aim of this study is to explore the SAH status of the elderly in China, and to identify the health disparity between the urban and rural elderly. Methods: The data from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS) in 2018 were adopted. A total of 9630 participants aged 60 and above were included in this study. SAH was used as the indicator, measuring the health status. Fairlie decomposition analysis was conducted to find the SAH disparity. Results: The proportion of good SAH of the rural elderly (24.01%) was significantly higher than the urban elderly (19.99%). The association of SAH was widely different between the rural and urban elderly. There was a stronger association between SAH and sleeping time in the urban elderly (Odds ratios (OR) = 3.347 of 4–8 hours; OR = 3.337 of above 8 hours) than the rural elderly (OR = 1.630 of 4–8 hours; OR = 2.293 of above 8 hours). Smoking and social activity were significant only in the urban elderly, while region and assets were significant only in the rural elderly. Drinking (11.45%), region (−33.92%), and assets (73.50%) were the main factors contributing to the urban–rural health disparities. Conclusions: This is the first comparative study examining SAH disparity, focusing on the elderly aged 60 and above in China. From the perspective of drinking, region, and assets, our study highlighted substantial urban–rural health disparities, and provided evidence for policy making on narrowing the health gap between urban and rural areas in China.

Decomposition and Comparative Analysis of the Prevalence of and Factors Associated With Smoking Between the Rural and Urban Elderly Population in China: A National Cross-Sectional Study

“…Our study revealed that the rate of correct responses to all smoking-related problems was significantly higher among the urban elderly compared with the rural elderly, perhaps because urban residents have better educational opportunities and can learn more about the effects of smoking ( 20 ). The stepwise multiple logistic regression model showed that gender, age, region, education, knowing about e-cigarettes, rules about smoking at home, and smoking-related knowledge scores were major risk factors for smoking in the elderly; age and education were found to be protective factors against smoking.…”

“…However, it was not that people with higher smoking-related knowledge scores are less likely to smoke; only moderate smoking-related knowledge scores served as protective factors against smoking. Some studies have shown that this may be because people with higher scores are those who had better academic qualifications, occupations that are more inclined to mental work or retired, may be subject to greater mental stress or bored, and compared with elderly people who scored low, those with high scores were often from urban areas, with a higher constant pension, and thus, had stronger purchasing power for cigarettes ( 6 , 7 , 20 ).…”

“…The research data were taken from the Global Adult Tobacco Survey (GATS)-China 2018 ( 20 ); therefore, no ethics approval was required. The GATS China 2018 was a survey conducted by the CCDC.…”

“…Chi-square test was used to analyse the univariate of urban and rural, the test standard was α = 0.05, and multiple logistic regression model was established to evaluate the impact of different variables on smoking and quitting status (including α = 0.05, excluding α = 0.10). The Fairlie model was used for decomposition analysis; the construction of this model is explained in detail in Dr. Zhang's article ( 20 ). A two-tailed test of significance was conducted, with P < 0.05 as statistically significant.…”

Decomposing Differences of Health Service Utilization among Chinese Rural Migrant Workers with New Cooperative Medical Scheme: A Comparative Study

“…Rural migrant workers tend to pay more attention to the people and things around them; rural migrant workers would like to compare the reference object. In fact, social comparison occurred mainly within homogeneous groups in western developed countries [32,33].…”