scholarly journals Income-related health inequalities associated with the coronavirus pandemic in South Africa: A decomposition analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Chijioke O. Nwosu ◽  
Adeola Oyenubi
Keyword(s):  
South Africa ◽  
Health Inequalities ◽  
Health Inequality ◽  
National Income ◽  
Decomposition Analysis ◽  
Good Health ◽  
Poor Health ◽  
Income Loss ◽  
Per Capita ◽  
Self Assessed Health

Abstract Background The coronavirus disease 2019 (COVID-19) has resulted in an enormous dislocation of society especially in South Africa. The South African government has imposed a number of measures aimed at controlling the pandemic, chief being a nationwide lockdown. This has resulted in income loss for individuals and firms, with vulnerable populations (low earners, those in informal and precarious employment, etc.) more likely to be adversely affected through job losses and the resulting income loss. Income loss will likely result in reduced ability to access healthcare and a nutritious diet, thus adversely affecting health outcomes. Given the foregoing, we hypothesize that the economic dislocation caused by the coronavirus will disproportionately affect the health of the poor. Methods Using the fifth wave of the National Income Dynamics Study (NIDS) dataset conducted in 2017 and the first wave of the NIDS-Coronavirus Rapid Mobile Survey (NIDS-CRAM) dataset conducted in May/June 2020, this paper estimated income-related health inequalities in South Africa before and during the COVID-19 pandemic. Health was a dichotomized self-assessed health measure, with fair and poor health categorized as “poor” health, while excellent, very good and good health were categorized as “better” health. Household per capita income was used as the ranking variable. Concentration curves and indices were used to depict the income-related health inequalities. Furthermore, we decomposed the COVID-19 era income-related health inequality in order to ascertain the significant predictors of such inequality. Results The results indicate that poor health was pro-poor in the pre-COVID-19 and COVID-19 periods, with the latter six times the value of the former. Being African (relative to white), per capita household income and household experience of hunger significantly predicted income-related health inequalities in the COVID-19 era (contributing 130%, 46% and 9% respectively to the inequalities), while being in paid employment had a nontrivial but statistically insignificant contribution (13%) to health inequality. Conclusions Given the significance and magnitude of race, hunger, income and employment in determining socioeconomic inequalities in poor health, addressing racial disparities and hunger, income inequality and unemployment will likely mitigate income-related health inequalities in South Africa during the COVID-19 pandemic.

scholarly journals Income-related health inequalities associated with the coronavirus epidemic in South Africa: A decomposition analysis

2020 ◽  
Author(s):  
Chijioke O. Nwosu ◽  
Adeola Oyenubi
Keyword(s):  
South Africa ◽  
Health Inequalities ◽  
Health Inequality ◽  
National Income ◽  
Decomposition Analysis ◽  
Good Health ◽  
Poor Health ◽  
Income Loss ◽  
Per Capita ◽  
Self Assessed Health

Abstract Background: The coronavirus pandemic (covid-19) has resulted in an enormous dislocation of society especially in South Africa. The South African government has imposed a number of measures aimed at controlling the epidemic, chief being a nationwide lockdown. This has resulted in income loss for individuals and firms, with vulnerable populations (low earners, those in informal and precarious employment, etc.) more likely to be adversely affected through job losses and the resulting income loss. Income loss will likely result in reduced ability to access healthcare and a nutritious diet, thus adversely affecting health outcomes. Given the foregoing, we hypothesize that the economic dislocation caused by the coronavirus will disproportionately affect the health of the poor.Methods: Using the fifth wave of the National Income Dynamics Study (NIDS) dataset conducted in 2017 and the first wave of the NIDS-Coronavirus Rapid Mobile Survey (NIDS-CRAM) dataset conducted in May/June 2020, this paper estimated income-related health inequalities in South Africa before and during the covid-19 epidemic. Health was a dichotomized self-assessed health measure, with fair and poor health categorized as “poor” health, while excellent, very good and good health were categorized as “better” health. Household per capita income was used as the ranking variable. Concentration curves and indices were used to depict the income-related health inequalities. Furthermore, we decomposed the covid-19 era income-related health inequality in order to ascertain the significant predictors of such inequality.Results: The results indicate that poor health was pro-poor in the pre-covid-19 and covid-19 periods, with the latter six times the value of the former. Being African (relative to white), per capita household income and household experience of hunger significantly predicted income-related health inequalities in the covid-19 era, while being in paid employment had a nontrivial but statistically insignificant contribution to health inequality.Conclusion: Addressing racial disparities, tackling hunger, income inequality and unemployment will likely mitigate income-related health inequalities in South Africa during the covid-19 epidemic.

scholarly journals Dynamics of Health Among Adults in South Africa

2020 ◽  
Author(s):  
Usengimana Shadrack Mutembereza
Keyword(s):  
South Africa ◽  
Social Determinants Of Health ◽  
Health Inequality ◽  
Social Determinants ◽  
National Income ◽  
Determinants Of Health ◽  
Health Campaigns ◽  
Health Selection ◽  
Policy Makers ◽  
The Poor

Abstract BackgroundThis paper estimates trend of health mobility in South Africa using National Income Dynamic Study (NIDS) and investigate whether the patterns of health mobility differs within socioeconomic groups created by income and gender. Health is measured by SRHS, which correlates with mortality and morbidity; thus, it is the best measure of health. MethodsUsing five waves of NIDS and various econometric models, this research estimates health mobility in the period between 2007 and 2017. This study will use transition matrix as descriptive analysis of health mobility and Conditional Maximum Likelihood Estimations to analyse health mobility, trend of health mobility and relationship between health mobility and health inequality within NIDS. ResultsThe study shows that, among poor males, health mobility neither follows a health selection or health constraint mobility trend; the high health mobility with ambiguous trends has not decreased health inequality. Among the poor females, a negative health mobility trend is observed; this research also found that health inequality has not creased. Among the non-poor males, it is found that health mobility follows a gradient constraint trend which has decreased health inequality. Among non-poor females, it is found that health mobility follows a health selection trend which has not decreased health inequality. The results suggest that policy makers should target both social determinants of health and health campaigns to deal with health inequality among the poor males. ConclusionsThe trend of health mobility among poor females suggest that policy makers should target the social determinants of health to combat health inequality. The trend of health mobility among the non-poor males suggests that health mobility will eliminate health inequality. Lastly, the trend of health mobility suggests that policymakers should target health campaigns to deal with health inequality.

scholarly journals Low economic growth and health inequalities in a rich country: 27-year Japanese time series

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Hiyoshi ◽  
K Honjo ◽  
L G Platts ◽  
Y Suzuki ◽  
M J Shipley ◽  
...  
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Health Inequalities ◽  
Health Inequality ◽  
Time Trends ◽  
Age Groups ◽  
Good Health ◽  
Japanese Economy ◽  
Economic Stagnation ◽  
Working Age

Abstract This presentation extends the public health theme in relation to Sustainable Development Goal #8, focusing on the health inequality trend in Japan. it is important to understand whether low economic growth is compatible with a low level of health inequalities. Unlike the UK and USA, life expectancy in Japan continued to improve despite a stagnant economy. Ten triennial waves of a nationally representative survey in Japan, 1986-2013 (n = 731,647) were used. Slope and Relative Indices of Inequality (SII and RII respectively) in relation to net household income and self-rated good health were calculated. Analyses were stratified by sex and age, for children, working-age adults, younger old and older old, given age differences in relation to labour market. Time trends of SII and RII were tested during the period of economic stagnation 1992-2013. In all age groups, prevalence of good health declined slightly from its peak in 1995 but increased after 2007. In 1992 among children, working-age adults and younger old, health inequality based on SII was small, about 10% lower prevalence of good health in those with lowest compared to highest income. Among working-age adults, time trends of health inequalities based on SII narrowed from 1992 and then widened after 2002 (quadratic trends in men and women p < 0.05), resulting in the magnitude of health inequality returning to its level at the beginning of economic stagnation in 1992 but not exceeding it. Time trends in relative inequality (RII) were qualitatively similar to those in absolute inequality (SII). The long-term low-growth Japanese economy appears compatible with maintaining and improving population health and holding health inequalities at current levels. This evidence is of great significance for sustainable development and the health of current and future generations.

scholarly journals Health inequalities among middle-aged and elderly people in China: analyses of cross-sectional surveys from the China Health and Retirement Longitudinal Study 2011–2016

2020 ◽  
Author(s):  
Qinxiao Qiu ◽  
Jinfeng Zeng ◽  
Liyuan Han ◽  
Zhuo Chen ◽  
Hongpeng Sun
Keyword(s):  
Longitudinal Study ◽  
Chronic Diseases ◽  
Health Equity ◽  
Health Inequalities ◽  
Health Inequality ◽  
Gdp Per Capita ◽  
Calculated Concentration ◽  
Kendall’S Τ ◽  
Per Capita ◽  
Concentration Indices

Abstract Objectives: China has a history of striving to achieve health equity, including efforts to prevent and control infectious diseases. However, to date, there is no comprehensive assessment of inequalities in chronic diseases in China. Methods: Data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS) conducted from 2011 to 2016. A total of 50,244 Chinese adults aged 45 years and older were included (16,128 in 2011, 16,646 in 2013, and 17,470 in 2015). Principal component analysis was used to construct the socioeconomic status indicator. We calculated concentration indices and corresponding CIs for 14 chronic diseases and comorbidities. We then estimated the Kendall rank correlation coefficient for inequalities and GDP per capita among provinces. Results: For 10 of the 14 chronic diseases, prevalence rates were higher for the poorest tertiles than for the richest tertiles. The concentration indices of dyslipidaemia, diabetes or high blood sugar, and cancer or malignant tumour were, respectively, 0.1256 (95% confidence interval, 0.1052–0.151), 0.098 (0.0704–0.1244), and 0.1305 (0.0528–0.215) in 2015–2016, which indicated pro-rich inequality. Health inequality for chronic lung diseases and eight other diseases grew markedly from 2011 to 2016. Overall, health inequality was lower for urban residents (−0.035 in 2011–2012, −0.036 in 2013–2014, and −0.05 in 2015–2016) than rural residents (−0.053, −0.064, and −0.08, respectively), and inequality was twice as high among women (−0.051, −0.05, and −0.072, respectively) than among men (−0.023, −0.02, and −0.032, respectively). Provinces that were ranked higher for GDP per capita were also ranked higher in the degree to which disease prevalence was higher in people with lower income (Kendall’s τ=−0.2328, p=0.015; Kendall’s τ=−0.3545, p=0.0077; Kendall’s τ=−0.2646, p=0.0079, respectively). Conclusions: Pro-poor health inequalities for many diseases in China are large and widening. Policies associated with health equity, including free public health services and community health programmes, are needed to achieve the Sustainable Development Goals.

scholarly journals The Measurement of Health Inequalities: Does status matter?

2016 ◽  
Author(s):  
Joan Costa-Font ◽  
Frank Cowell
Keyword(s):  
Health Outcomes ◽  
Health Inequalities ◽  
Health Inequality ◽  
World Health ◽  
World Health Survey ◽  
Correlation And Regression Analysis ◽  
Measurement Tools ◽  
The Status ◽  
Self Assessed Health ◽  
Health Variable

The measurement of health inequalities usually involves either estimating the concentration of health outcomes using an income-based measure of status or applying conventional inequality-measurement tools to a health variable that is non-continuous or, in many cases, categorical. However, these approaches are problematic as they ignore less restrictive approaches to status. The approach in this paper is based on measuring inequality conditional on an individual's position in the distribution of health outcomes: this enables us to deal consistently with categorical data. We examine several status concepts to examine self-assessed health inequality using the sample of world countries contained in the World Health Survey. We also perform correlation and regression analysis on the determinants of inequality estimates assuming an arbitrary cardinalisation. Our findings indicate major heterogeneity in health inequality estimates depending on the status approach, distributional-sensitivity parameter and measure adopted. We find evidence that pure health inequalities vary with median health status alongside measures of government quality.

scholarly journals Elderly Health Inequality in China and its Determinants: A Geographical Perspective

2019 ◽  
Vol 16 (16) ◽  
pp. 2953 ◽  
Author(s):  
Chenjing Fan ◽  
Wei Ouyang ◽  
Li Tian ◽  
Yan Song ◽  
Wensheng Miao
Keyword(s):  
Health Status ◽  
Health Inequalities ◽  
Health Inequality ◽  
Elderly Population ◽  
Hot Spot ◽  
Good Health ◽  
The Elderly ◽  
Multilevel Regression ◽  
Health Differences ◽  
Elderly Health

Inter-regional health differences and apparent inequalities in China have recently received significant attention. By collecting health status data and individual socio-economic information from the 2015 fourth sampling survey of the elderly population in China (4th SSEP), this paper uses the geographical differentiation index to reveal the spatial differentiation of health inequality among Chinese provinces. We test the determinants of inequalities by multilevel regression models at the provincial and individual levels, and find three main conclusions: 1) There were significant health differences on an inter-provincial level. For example, provinces with a very good or good health rating formed a good health hot-spot region in the Yangtze River Delta, versus elderly people living in Gansu and Hainan provinces, who had a poor health status. 2) Nearly 2.4% of the health differences in the elderly population were caused by inter-provincial inequalities; access (or lack of access) to economic, medical and educational resources was the main reason for health inequalities. 3) At the individual level, inequalities in annual income served to deepen elderly health differences, and elderly living in less developed areas were more vulnerable to urban vs. rural-related health inequalities.

scholarly journals The measurement of health inequalities: does status matter?

2021 ◽  
Author(s):  
Joan Costa-Font ◽  
Frank A. Cowell
Keyword(s):  
Regression Analysis ◽  
Health Inequalities ◽  
Health Inequality ◽  
Categorical Data ◽  
World Health ◽  
World Health Survey ◽  
The World ◽  
The Status ◽  
Consistent Treatment ◽  
Self Assessed Health

AbstractApproaches to measuring health inequalities are often problematic because they use methods that are inappropriate for categorical data. In this paper we focus on “pure” or univariate health inequality (rather than income-related or bivariate health inequality) and use a concept of individual status that allows a consistent treatment of such data. We take alternative versions of the status concept and apply methods for treating categorical data to examine self-assessed health inequality for the countries included in the World Health Survey. We also use regression analysis on the apparent determinants of these health inequality estimates. We show that the status concept that is used will affect health-inequality rankings across countries and the way health inequality is related to countries’ median health, income, demographics and governance.

Health Communication: Implications for Diverse Populations

2011 ◽  
Vol 18 (1) ◽  
pp. 12-19
Author(s):  
Amy Hasselkus
Keyword(s):  
Health Care ◽  
Health Communication ◽  
Negative Impact ◽  
Linguistically Diverse ◽  
Good Health ◽  
The United States ◽  
Poor Health ◽  
Health Care Decisions ◽  
Diverse Backgrounds ◽  
Health Related

The need for improved communication about health-related topics is evident in statistics about the health literacy of adults living in the United States. The negative impact of poor health communication is huge, resulting in poor health outcomes, health disparities, and high health care costs. The importance of good health communication is relevant to all patient populations, including those from culturally and linguistically diverse backgrounds. Efforts are underway at all levels, from individual professionals to the federal government, to improve the information patients receive so that they can make appropriate health care decisions. This article describes these efforts and discusses how speech-language pathologists and audiologists may be impacted.

The Politics of Global Health Inequalities

2019 ◽  
pp. 58-84
Author(s):  
Yusra Ribhi Shawar ◽  
Jennifer Prah Ruger
Keyword(s):  
Social Sciences ◽  
Critical Theory ◽  
Global Health ◽  
Health Inequalities ◽  
Health Inequality ◽  
The Political ◽  
State Of Health ◽  
Political Determinants ◽  
The Social

Careful investigations of the political determinants of health that include the role of power in health inequalities—systematic differences in health achievements among different population groups—are increasing but remain inadequate. Historically, much of the research examining health inequalities has been influenced by biomedical perspectives and focused, as such, on ‘downstream’ factors. More recently, there has been greater recognition of more ‘distal’ and ‘upstream’ drivers of health inequalities, including the impacts of power as expressed by actors, as well as embedded in societal structures, institutions, and processes. The goal of this chapter is to examine how power has been conceptualised and analysed to date in relation to health inequalities. After reviewing the state of health inequality scholarship and the emerging interest in studying power in global health, the chapter presents varied conceptualisations of power and how they are used in the literature to understand health inequalities. The chapter highlights the particular disciplinary influences in studying power across the social sciences, including anthropology, political science, and sociology, as well as cross-cutting perspectives such as critical theory and health capability. It concludes by highlighting strengths and limitations of the existing research in this area and discussing power conceptualisations and frameworks that so far have been underused in health inequalities research. This includes potential areas for future inquiry and approaches that may expand the study of as well as action on addressing health inequality.

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