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      Income distribution and health: What do we know from Chinese data?

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      1 , 2 , 3 , 4 , *
      PLoS ONE
      Public Library of Science

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          Abstract

          In the last four decades, the problem of income inequality has gradually become one of the most serious social problems in China at both the regional and individual levels. Recently, the central government announced that the main social contradiction is that between people’s growing need for a better life and unbalanced and insufficient economic development. In this study, we analyse the effects of income distribution on individuals’ health using a series of indicators of income distribution and different measures of individuals’ health status. By utilizing data from the China Health and Nutrition Survey (CHNS) from 1989 to 2015, our empirical findings show that self-reported health (SRH), activities of daily living (ADLs), and diabetes mellitus appear to be negatively related to the income share of rich people when average income is equalized among counties, which indicates that individuals’ health will deteriorate as the income share of rich people increases. In addition, our results show that there is an inverted U-shaped relationship between income inequality, as measured by the county-level Gini coefficient, and individuals’ health status. We also find that income inequality affects health through the accessibility of healthcare facilities and public infrastructures and through hazardous health behaviours such as smoking and alcohol use. These findings suggest that reducing income inequality could be an important means of improving the overall health of China’s population.

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          Most cited references34

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          STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION.

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            Income inequality and health: a causal review.

            There is a very large literature examining income inequality in relation to health. Early reviews came to different interpretations of the evidence, though a large majority of studies reported that health tended to be worse in more unequal societies. More recent studies, not included in those reviews, provide substantial new evidence. Our purpose in this paper is to assess whether or not wider income differences play a causal role leading to worse health. We conducted a literature review within an epidemiological causal framework and inferred the likelihood of a causal relationship between income inequality and health (including violence) by considering the evidence as a whole. The body of evidence strongly suggests that income inequality affects population health and wellbeing. The major causal criteria of temporality, biological plausibility, consistency and lack of alternative explanations are well supported. Of the small minority of studies which find no association, most can be explained by income inequality being measured at an inappropriate scale, the inclusion of mediating variables as controls, the use of subjective rather than objective measures of health, or follow up periods which are too short. The evidence that large income differences have damaging health and social consequences is strong and in most countries inequality is increasing. Narrowing the gap will improve the health and wellbeing of populations.
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              Social capital, income inequality, and mortality.

              Recent studies have demonstrated that income inequality is related to mortality rates. It was hypothesized, in this study, that income inequality is related to reduction in social cohesion and that disinvestment in social capital is in turn associated with increased mortality. In this cross-sectional ecologic study based on data from 39 states, social capital was measured by weighted responses to two items from the General Social Survey: per capita density of membership in voluntary groups in each state and level of social trust, as gauged by the proportion of residents in each state who believed that people could be trusted. Age-standardized total and cause-specific mortality rates in 1990 were obtained for each state. Income inequality was strongly correlated with both per capita group membership (r = -.46) and lack of social trust (r = .76). In turn, both social trust and group membership were associated with total mortality, as well as rates of death from coronary heart disease, malignant neoplasms, and infant mortality. These data support the notion that income inequality leads to increased mortality via disinvestment in social capital.
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                Author and article information

                Contributors
                Role: Data curationRole: MethodologyRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 January 2022
                2022
                : 17
                : 1
                : e0263008
                Affiliations
                [1 ] School of Public Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan, China
                [2 ] School of Insurance, Southwestern University of Finance and Economics, Chengdu, Sichuan, China
                [3 ] School of Public Finance & Economics, Shanxi University of Finance and Economics, Taiyuan, Shanxi, China
                [4 ] Department of Economics, Lehigh University, Bethlehem, PA, United States of America
                University of South Florida, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-0631-7776
                Article
                PONE-D-21-24183
                10.1371/journal.pone.0263008
                8786202
                35073367
                b62e4258-8b62-408e-8db5-d297485a465a
                © 2022 Ting et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 July 2021
                : 10 January 2022
                Page count
                Figures: 0, Tables: 14, Pages: 18
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Behavioral and Social Aspects of Health
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Health Care
                Health Care Facilities
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                People and Places
                Geographical Locations
                Asia
                China
                Engineering and Technology
                Civil Engineering
                Urban Infrastructure
                Earth Sciences
                Geography
                Geographic Areas
                Rural Areas
                Custom metadata
                All data underlying the study can be found in the China Health and Nutrition Survey: ( http://data.cpc.unc.edu/projects/7/view) from the Carolina Population Center.

                Uncategorized
                Uncategorized

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