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      The Associations of Income, Education and Income Inequality and Subjective Well-Being among Elderly in Hong Kong—A Multilevel Analysis

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          Abstract

          Background: Higher income and education and lower income inequality in a neighbourhood have been shown to be related to better mental health outcome in developed countries. However, it is not clear whether these factors would affect the subjective well-being of the elderly, especially in a setting with recent rapid economic development. Methods: This study was conducted in 80 community centres with a total of 7552 community-dwelling elderly (mean age 75.9 years (SD = 7.79), 79% female) in Hong Kong. Income at individual level was measured as perceived disposable income. Education level was also collected. At district level, income was measured by district median household income and education was measured as the proportion of the population with no formal schooling. Income inequality was quantified using Gini coefficients. Low subjective well-being was defined as any one or a combination of the following: not satisfied with life, no meaning of life and being unhappy (Likert scale ≤ 2). Multilevel logistic regression was used to assess the association of income, education and income inequality and low subjective well-being. Results: We found that 15.3% (95% confidence interval (CI): 14.5 to 16.1) of the elderly have low subjective well-being. Compared with elderly who reported a very adequate disposable income, those who reported a very inadequate disposable income are at increased risk of low subjective well-being (OR=5.08, 95%CI: 2.44 to 10.59). Compared with elderly with tertiary education, those with no formal schooling were at higher risk (OR=1.60, 95%CI 1.22 to 2.09). Income inequality was not related to subjective well-being. Conclusions: Elderly with inadequate disposable income and lower education level are more likely to suffer from low subjective well-being. At the neighbourhood level, income inequality was not related to subjective well-being. However, the relationships between neighbourhood income and education level and individuals’ subjective well-being are not clear.

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          Which chronic conditions are associated with better or poorer quality of life?

          The objective of the present study is to compare the QL of a wide range of chronic disease patients. Secondary analysis of eight existing data sets, including over 15,000 patients, was performed. The studies were conducted between 1993 and 1996 and included population-based samples, referred samples, consecutive samples, and/or consecutive samples. The SF-36 or SF-24 were employed as generic QL instruments. Patients who were older, female, had a low level of education, were not living with a partner, and had at least one comorbid condition, in general, reported the poorest level of QL. On the basis of rank ordering across the QL dimensions, three broad categories could be distinguished. Urogenital conditions, hearing impairments, psychiatric disorders, and dermatologic conditions were found to result in relatively favorable functioning. A group of disease clusters assuming an intermediate position encompassed cardiovascular conditions, cancer, endocrinologic conditions, visual impairments, and chronic respiratory diseases. Gastrointestinal conditions, cerebrovascular/neurologic conditions, renal diseases, and musculoskeletal conditions led to the most adverse sequelae. This categorization reflects the combined result of the diseases and comorbid conditions. If these results are replicated and validated in future studies, they can be considered in addition to information on the prevalence of the diseases, potential benefits of care, and current disease-specific expenditures. This combined information will help to better plan and allocate resources for research, training, and health care.
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            Understanding social factors and inequalities in health: 20th century progress and 21st century prospects.

            The development of social epidemiology and medical sociology over the last half of the 20th century, in which Leo Reeder played a central role, transformed scientific and popular understanding of the nature and causes of physical health and illness. Viewed in the early 1950s as shaped almost entirely by biological processes and medical care, physical health and illness are now understood to be as much or more a function of social, psychological, and behavioral factors. Utilizing a stress and adaptation conceptual framework, social epidemiology has identified a broad range of psychosocial risk factors for health, most notably: (1) social relationships and support; (2) acute or event-based stress; (3) chronic stress in work and life; and (4) psychological dispositions such as anger/hostility, lack of self-efficacy/control, and negative affect/hopelessness/pessimism, with new risk factors continuing to be identified. However, proliferation of risk factors must be balanced by conceptual integration and causal understanding of the relationships among them, their causes, and consequences. One source of such integration and understanding has been the rediscovery of large and persistent socioeconomic and racial-ethnic disparities in health. Socioeconomic position and race/ethnicity shape individuals' exposure to and experience of virtually all known psychosocial, and well as many environmental and biomedical, risk factors, and these risk factors help to explain the size and persistence of social disparities in health. Improving the socioeconomic position of a broad range of disadvantaged socioeconomic and racial-ethnic strata constitutes a major avenue for reducing exposure to and experience of deleterious risk factors for health, and hence for improving the health of these groups and the overall population. This in turn requires better understanding of the macrosocial forces that influence the socioeconomic position of individuals.
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              Socioeconomic inequalities in mortality among elderly people in 11 European populations.

              To describe mortality inequalities related to education and housing tenure in 11 European populations and to describe the age pattern of relative and absolute socioeconomic inequalities in mortality in the elderly European population. Data from mortality registries linked with population census data of 11 countries and regions of Europe were acquired for the beginning of the 1990s. Indicators of socioeconomic status were educational level and housing tenure. The study determined mortality rate ratios, relative indices of inequality (RII), and mortality rate differences. The age range was 30 to 90+ years. Analyses were performed on the pooled European data, including all populations, and on the data of populations separately. Data were included from Finland, Norway, Denmark, England and Wales, Belgium, France, Austria, Switzerland, Barcelona, Madrid, and Turin. In Europe (populations pooled) relative inequalities in mortality decreased with increasing age, but persisted. Absolute educational mortality differences increased until the ages 90+. In some of the populations, relative inequalities among older women were as large as those among middle aged women. The decline of relative educational inequalities was largest in Norway (men and women) and Austria (men). Relative educational inequalities did not decrease, or hardly decreased with age in England and Wales (men), Belgium, Switzerland, Austria, and Turin (women). Socioeconomic inequalities in mortality among older men and women were found to persist in each country, sometimes of similar magnitude as those among the middle aged. Mortality inequalities among older populations are an important public health problem in Europe.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                17 February 2020
                February 2020
                : 17
                : 4
                : 1271
                Affiliations
                Jockey Club Institute of Ageing, Chinese University of Hong Kong, Hong Kong SAR, China; rubyyu@ 123456cuhk.edu.hk (R.Y.); jeanwoowong@ 123456cuhk.edu.hk (J.W.)
                Author notes
                [* ]Correspondence: etclai@ 123456cuhk.edu.hk
                Author information
                https://orcid.org/0000-0002-1229-9471
                https://orcid.org/0000-0001-7051-4689
                https://orcid.org/0000-0001-7593-3081
                Article
                ijerph-17-01271
                10.3390/ijerph17041271
                7068358
                32079186
                b4046c91-8d74-46ee-9e4c-21e19e6eebe1
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 January 2020
                : 13 February 2020
                Categories
                Article

                Public health
                subjective well-being,elderly,income inequality,hong kong
                Public health
                subjective well-being, elderly, income inequality, hong kong

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