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      Decomposition analysis of health inequalities between the urban and rural oldest-old populations in China: Evidence from a national survey

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          Abstract

          The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

          Highlights

          • There is significant urban–rural health inequality among the Chinese oldest-old.

          • The urban oldest-old’s health status is better than that of the rural oldest-old.

          • Income, exercise, social activity, alcohol consumption, and age drive this trend.

          • Socioeconomic and lifestyle statuses influence urban-rural health inequality.

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          Most cited references37

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          Survival, disabilities in activities of daily living, and physical and cognitive functioning among the oldest-old in China: a cohort study

          The oldest-old (those aged ≥80 years) are the most rapidly growing age group globally, and are most in need of health care and assistance. We aimed to assess changes in mortality, disability in activities of daily living, and physical and cognitive functioning among oldest-old individuals between 1998 and 2008.
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            The Absence of the African‐American Owned Business: An Analysis of the Dynamics of Self‐Employment

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              A cross-sectional study on health differences between rural and non-rural U.S. counties using the County Health Rankings

              Background By examining 2013 County Health Rankings and Roadmaps data from the University of Wisconsin and the Robert Wood Johnson Foundation, this paper seeks to add to the available literature on health variances between United States residents living in rural and non-rural areas. We believe this is the first study to use the Rankings data to measure rural and urban health differences across the United States and therefore highlights the national need to address shortfalls in rural healthcare and overall health. The data indicates that U.S. residents living in rural counties are generally in poorer health than their urban counterparts. Methods We used 2013 County Health Rankings data to evaluate differences across the six domains of interest (mortality, morbidity, health behaviors, clinical care, social and economic factors, and physical environment) for rural and non-rural U.S. counties. This is a cross-sectional study employing chi-square analysis and logit regression. Results We found that residents living in rural U.S. counties are more likely to have poorer health outcomes along a variety of measurements that comprise the County Health Rankings’ indexed domains of health quality. These populations have statistically significantly (p ≤ 0.05) lower scores in such areas as health behavior, morbidity factors, clinical care, and the physical environment. We attribute the differences to a variety of factors including limitations in infrastructure, socioeconomic differences, insurance coverage deficiencies, and higher rates of traffic fatalities and accidents. Discussions The largest differences between rural and non-rural counties were in the indexed domains of mortality and clinical care. Conclusions Our analysis revealed differences in health outcomes in the County Health Rankings’ indexed domains between rural and non-rural U.S. counties. We also describe limitations and offer commentary on the need for more uniform measurements in the classification of the terms rural and non-rural. These results can influence practitioners and policy makers in guiding future research and when deciding on funding allocation.
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                Author and article information

                Contributors
                Journal
                SSM Popul Health
                SSM Popul Health
                SSM - Population Health
                Elsevier
                2352-8273
                24 December 2022
                March 2023
                24 December 2022
                : 21
                : 101325
                Affiliations
                [a ]Department of Health Management, Faculty of Military Health Service, Naval Medical University, Shanghai, China
                [b ]Department of Military Health Service, Faculty of Military Health Service, Naval Medical University, Shanghai, China
                [c ]Department of Medical Health Service, General Hospital of Northern Theater Command of PLA, Shenyang, China
                [d ]Department of Office, Naval Medical University, Shanghai, China
                [e ]School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
                Author notes
                []Corresponding author. Department of Health Management, Faculty of Military Health Service, Naval Medical University, No. 800 Xiangyin Road, Shanghai, 200433, PR China. yuanleigz@ 123456163.com
                [∗∗ ]Corresponding author. aqualau@ 123456126.com
                [∗∗∗ ]Corresponding author. sunjinhai2003@ 123456sina.cn
                [1]

                These authors contributed equally.

                Article
                S2352-8273(22)00304-4 101325
                10.1016/j.ssmph.2022.101325
                9816804
                36618546
                ddd56e82-c1f2-4506-9ee6-b6d4c6840607
                © 2022 The Authors. Published by Elsevier Ltd.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 April 2022
                : 15 December 2022
                : 18 December 2022
                Categories
                Regular Article

                health inequality,oldest-old,decomposition analysis,china,self-rated health

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