scholarly journals Beyond the income inequality hypothesis and human health: a worldwide exploration

2010 ◽  
Vol 44 (4) ◽  
pp. 695-702 ◽  
Author(s):  
Alvaro J Idrovo ◽  
Myriam Ruiz-Rodríguez ◽  
Abigail P Manzano-Patiño
Keyword(s):  
Social Capital ◽  
Income Inequality ◽  
Life Expectancy ◽  
Path Analysis ◽  
Human Health ◽  
Gini Coefficient ◽  
Predictor Variables ◽  
Political Regime ◽  
Outcome Variable ◽  
Life Expectancy At Birth

OBJECTIVE: To analyze whether the relationship between income inequality and human health is mediated through social capital, and whether political regime determines differences in income inequality and social capital among countries. METHODS: Path analysis of cross sectional ecological data from 110 countries. Life expectancy at birth was the outcome variable, and income inequality (measured by the Gini coefficient), social capital (measured by the Corruption Perceptions Index or generalized trust), and political regime (measured by the Index of Freedom) were the predictor variables. Corruption Perceptions Index (an indirect indicator of social capital) was used to include more developing countries in the analysis. The correlation between Gini coefficient and predictor variables was calculated using Spearman's coefficients. The path analysis was designed to assess the effect of income inequality, social capital proxies and political regime on life expectancy. RESULTS: The path coefficients suggest that income inequality has a greater direct effect on life expectancy at birth than through social capital. Political regime acts on life expectancy at birth through income inequality. CONCLUSIONS: Income inequality and social capital have direct effects on life expectancy at birth. The "class/welfare regime model" can be useful for understanding social and health inequalities between countries, whereas the "income inequality hypothesis" which is only a partial approach is especially useful for analyzing differences within countries.

scholarly journals Global Inequality in Life Expectancies: What Role Does Income Inequality Play?

2020 ◽  
Author(s):  
Nirajana Banerjee ◽  
Ritojeet Basu ◽  
Ananya De ◽  
Monalisa Poali
Keyword(s):  
Income Inequality ◽  
Life Expectancy ◽  
Gini Coefficient ◽  
Capita Income ◽  
Health Expenditure ◽  
Global Inequality ◽  
Life Expectancy At Birth ◽  
Choropleth Maps ◽  
Per Capita ◽  
Over Time

Context: Life expectancy best helps to capture the health and well-being of a population. However, wide differences are seen in life expectancies across different countries and at different points of time.Research objective: This study examines trends in global inequalities in Life Expectancy at birth between countries from 1960 to 2017, and studies how income inequality affects inequality in life expectancy.Data and methodology: Life expectancy at birth is the main variable under study. We have also used data on GDP per capita at purchasing power parity, Health Expenditure per capita and Government Expenditure on health per capita. Six measures of inequality have been used, primary being the Gini coefficient. We have divided the countries into four groups according to the World Bank Classification Scheme, and have used graphs, choropleth maps and Moran’s I for statistical analysis. The causal relationship between inequality in Life Expectancy and per capita GDP is examined using reduced form regression models.Findings: The life expectancy at birth shows a steadily rising trend. The choropleth maps indicate considerable spatial variations in life expectancy, which are stable over time. There is a decline in the global inequality in life expectancy over time. Moreover, the decomposition analysis for the Gini coefficient shows that in any year, the between groups inequality is more important than the within groups inequality. This is corroborated by the decomposition of Gini over time. We infer from the devised regression models that there is a positive association between per capita income inequality and inequality in life expectancy. The regressions point out evidence that inequality in lifespan and inequality in per capita income can be explained in terms of inequality in health expenditure.

scholarly journals The Mediating Roles of GDP on the Relationship Between Income Inequality and Life Expectancy

2021 ◽  
Author(s):  
Chia-Chang Chuang
Keyword(s):  
Income Inequality ◽  
Life Expectancy ◽  
Initial Step ◽  
Mediation Effect ◽  
Predictor Variables ◽  
Outcome Variable ◽  
Kuznets Curve ◽  
Set Up ◽  
The Relationship ◽  
Mediator Variable

This study examined the mediation effect of gross domestic product (GDP) on the relationship between life expectancy and income inequality based on data from 23 Organisation for Economic Co-operation and Development (OECD) countries for 2004 through 2014. To form a theoretical framework, Preston curve and Kuznets curve were employed. The study set up a mediation model with life expectancy as an outcome variable, GDP as a mediator variable, and three variables characterising income inequality as predictor variables: Gini index, income share held by highest 20%, and poverty headcount ratio at US$1.90 a day. The study found that GDP clearly mediates the effects of the predictor variables on life expectancy, although the magnitudes of the effects vary. This study takes an important initial step in exploring the mediation effect of GDP on the relationship between life expectancy and income inequality.

Changes in the socio-economic system and political regime and the fourth stage of the epidemiological transition

2012 ◽  
Vol 153 (17) ◽  
pp. 662-677 ◽  
Author(s):  
Péter Józan
Keyword(s):  
Life Expectancy ◽  
Economic System ◽  
Circulatory System ◽  
Political Regime ◽  
Time Of Death ◽  
Open Society ◽  
Medical Interventions ◽  
Life Expectancy At Birth ◽  
River Elbe ◽  
Successful Prevention

A new epidemiological stage has begun in Hungary as a result of the implosion of state-socialism. It has made the transition to market economy and open society possible. The emerging economic and social system has created the basis for terminating the chronic qualitative epidemiological crisis and for the renewal of the epidemiological development. The new political and socio-economic system has had a decisive impact on the decrease in mortality and consequently to the increase in life expectancy in the countries east of the River Elbe. Besides the spread of health conscious behaviour, the efficacy of new medications and invasive medical interventions just as much as the network of emergency centres have contributed to the favourable changes. The most characteristic feature of the new epidemiological stage is that it delays the progression of chronic diseases and postpones the time of death. In a large extent the successful prevention, treatment and care of diseases of the circulatory system are mainly responsible for increasing the life expectancy at birth. Paradoxically, whereas life expectancy has increased in the country on the whole, social inequality has also increased. Orv. Hetil., 2012, 153, 662–677.

scholarly journals Human Capital Impacts of Income Inequality: An Extensive Empirical Analysis From The African Continent

2021 ◽  
Author(s):  
Swapnanil Sengupta
Keyword(s):  
Income Inequality ◽  
Life Expectancy ◽  
Empirical Analysis ◽  
Least Square ◽  
African Continent ◽  
African Countries ◽  
Empirical Examination ◽  
Life Expectancy At Birth ◽  
Long Run ◽  
Short Run

Abstract This paper evaluates the impacts of income inequality on life expectancy in the African countries. The empirical analysis has been performed on a panel dataset of 52 African nations covering the period of 1995-2018. For estimating the relationship, I have employed Two-Stage Least Squares (2SLS) technique and a Panel Error Correction Model (PECM). The long-run cointegrating relationship was estimated using a Panel Dynamic Ordinary Least Square (PDOLS) estimator. The outputs of both static and dynamic estimation models suggest that income inequality has negatively affected life expectancy at birth in the African continent overall. Though a positive short-run causal relationship was established, in the long-run, income inequality had deleterious effects. A series of steps had been followed to check the soundness of the result of the main empirical examination and it was confirmed that the results are robust.

The contribution of subjective measures to the quantification of social progress

2016 ◽  
Vol 36 (3/4) ◽  
pp. 258-268
Author(s):  
Wolfgang Messner
Keyword(s):  
Life Expectancy ◽  
Human Health ◽  
Subjective Health ◽  
Health Data ◽  
Social Progress ◽  
Subjective Measures ◽  
Subjective Data ◽  
Content Type ◽  
Life Expectancy At Birth ◽  
Statistical Measures

Purpose – Statistical indicators, such as human health, are important for designing government policies, as well as for influencing the functioning of economic markets. However, there is often a discrepancy between statistical measures and the citizens’ prevalent feelings. In order to produce more relevant indicators of social progress, governments are currently shifting their measurement emphasis from objective to subjective measures. While the philosophical tradition of hedonic psychology views individuals as the best judges of their own conditions, little empirical evidence shows that individually reported health scores provide accurate information about a population’s health status. The purpose of this paper is to evaluate if subjective health questions contain genuine information about the status of human health, and are meaningful at an aggregated level. Design/methodology/approach – Subjective health data are extracted from the 2012/2013 European Social Survey (28 European countries plus Israel, n=54,427). Objective health data are based on the 2012 World Bank statistics for life expectancy at birth. The author check if aggregated subjective health correlates with life expectancy at country level, and can reliably be compared across countries. Findings – The findings support the idea of including subjective data into country statistics of social progress. Because of substantial between-country differences, social development programs should be devised individually for each country. Originality/value – By showing that subjective health measures can reliably contribute to the quantification of social progress, the author offer a bridge between objective neoclassical economics and subjective hedonic psychology.

scholarly journals The decomposition of life expectancy for age and cause of death in Tuscany, Italy

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
N Nante ◽  
L Kundisova ◽  
F Gori ◽  
A Martini ◽  
F Battisti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Causes Of Death ◽  
National Level ◽  
Age Groups ◽  
Resistant Bacteria ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Icd 10 ◽  
Reduction Of Mortality ◽  
The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

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