Country-Level Socioeconomic Indicators Associated with Healthy Life Expectancy: Income, Urbanization, Schooling, and Internet Users: 2000–2012

Kim, Jong In; Kim, Gukbin

doi:10.1007/s11205-015-1107-2

Cited by 30 publications

(61 citation statements)

References 27 publications

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“…ILE can be influenced by country-level socio-ecological indicators that include the Gini coefficient, secondary education, output per worker, and old age pension recipients. Thus, ILE is a useful indicator that can help develop ways to reduce health inequalities [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…Although studies of ILE have been investigated in various countries [ 4 – 7 ], which socio-ecological factors in various countries affect ILE are unclear [ 6 , 7 ]. Especially, a retrospective analysis of country-level socio-ecological factors that contribute to ILE could help identify the most important determinants of ILE [ 3 , 8 ]. With this goal, this study considers how ILE correlates with socio-ecological indicators.…”

Section: Introductionmentioning

confidence: 99%

“…The basic hypothesis of this paper is that as the income level of a country increases, life expectancy increases commensurately [ 3 , 8 , 9 ]. Several studies that estimated ILE for various countries between 2001 and 2012 [ 4 , 6 , 7 , 10 ] showed the relationship between black and white populations, social class, indigenous and non-indigenous people, and women and men in terms of ILE.…”

Section: Introductionmentioning

confidence: 99%

“…The present study examines the possible associations between ILE and socio-ecological inequality using several indicators: (1) national income inequality on the personal level [ 3 , 8 , 13 , 23 , 24 ]; (2) education of at least a secondary education by males and females, which is an indicator of the social environment [ 15 , 17 , 18 ]; (3) labor productivity [ 19 ] (Cervellati and Sunde 2005); and (4) the number of old age pension recipients [ 21 ], which indicates public policy. The authors expect that countries with low-ILE populations will feature combinations with higher level indicators of socio-ecological perspective (national income, secondary educational attainment, labor productivity, and old age pension recipients).…”

Section: Introductionmentioning

confidence: 99%

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Effects on inequality in life expectancy from a social ecology perspective

Kim

2018

BMC Public Health

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BackgroundInequality in life expectancy (ILE) is defined as inequality in the distribution of expected span of life-based on data from survival tables estimated using the Atkinson inequality index. ILE can be influenced by socio-ecological indicators including the Gini coefficient, secondary education, output per worker, and old age pension. This study examined the effects on ILE from a social ecology perspective.MethodsThis analysis is based on ILE data from 108 countries obtained from the United Nations Development Programme. Data on socio-ecological indicators were obtained from the United Nations database. The associations between socio-ecological indicators and ILE were assessed using correlation coefficients and multiple regression models.ResultsSignificant correlations were evident between ILE and the following indicators from a socio-ecological perspective: Gini coefficient (GC: r = 0.335, p = 0.001) as an indicator of income inequality, female population with at least some secondary education (FSE: r = − 0.757, p = 0.001), male population with at least some secondary education (MSE: r = − 0.741, p = 0.001), output per worker as a measure of labor productivity (OPW: r = − 0.714, p = 0.001), and number of old age pension recipients (OPR: r = − 0.641, p = 0.001). In multivariate regression, the ILE predictors were higher GC and lower levels of FSE, MSE, OPW, and OPR (R2 = 0.648, p < 0.001).ConclusionsSocio-ecological factors have an important effect on ILE. Policies that address ILE should consider targeted socio-ecological factors, such as the Gini coefficient of income inequality, that give a personal perspective of economic deprivation, attainment of at least a secondary education by both females and males that gives a social environment perspective, output per worker that indicates labor productivity, and the number of old age pension recipients that indicates social security from a public policy perspective.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effects on inequality in life expectancy from a social ecology perspective

Kim

2018

BMC Public Health

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“…It is widely known that longevity is affected by different factors. Most studies thus far have mainly focused on the aspect such as environmental factors [ 4 , 5 ], socioeconomic factors [ 6 , 7 ], medical factors [ 8 ], and genetic factors [ 8 , 9 , 10 ]. Among them, environmental factors that potentially impact human health have been studied intensively, including climate [ 4 , 11 ], air quality [ 12 , 13 ], natural and drinking water quality [ 14 , 15 , 16 , 17 ], and soil quality [ 18 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Understanding the Association between Environmental Factors and Longevity in Hechi, China: A Drinking Water and Soil Quality Perspective

Deng

Chen

Wei

et al. 2018

IJERPH

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The aging population is a big challenge all over the world. However, there are few studies to date investigating the effects of trace element and mineral levels in drinking water and soil (especially in karst areas) on longevity. This study aims to examine temporal and spatial variations in longevity in Hechi (which is recognized as a longevity city) and to investigate relationships between longevity and trace element and mineral levels in drinking water and soils in this city (the karst landscape). Population data were collected from relevant literature and four national population censuses in 1982, 1990, 2000 and 2010. Drinking water and soil samples from Hechi were collected and analyzed. The results demonstrated an obvious clustered distribution for the longevity population in Hechi that has existed stably for decades. The longevity index tended to be significantly positively correlated with H2SiO3, Ca and Fe in drinking water and significantly negatively correlated with Sr in soil, indicating that drinking water characteristics contributed significantly to the observed regional longevity. The karst landscape is responsible for abundant trace elements in underground rivers in Hechi, which are beneficial to human health when consumed as drinking water. Good quality and slightly alkaline drinking water rich in trace elements such as H2SiO3, Ca, Fe, Na, Mg and low in heavy metals such as Pb and Cd might be an important factor contributing to the longevity phenomenon in Hechi.

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Longer healthy life, but for how many? A stochastic analysis of healthy lifespan inequality

Zarulli,

Caswell

2024

Ann Oper Res

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Over the past 150 years, life expectancy doubled and healthy life expectancy increased. Expectations reveal nothing about variability, so we present a stochastic analysis to investigate changes over time, age and gender of variation, among individuals, in healthy lifespan, for different levels of country income. To complement health-adjusted life expectancy (HALE) data from the Global Burden of Disease Study, we use a stochastic model to compute the standard deviation of healthy life (SDHL). The model is a finite-state absorbing Markov chain with rewards. It includes stochastic survival, mortality, and loss of good health status. An individual surviving from one age to the next gains, as a "reward," a year of good health. This method provides all the moments of healthy longevity. The mean healthy longevity is exactly the HALE. As a measure of variation, here we focus on the standard deviation of healthy longevity. From 1990 to 2019, HALE increased, with greater increases at younger ages. At the same time, SDHL at younger ages decreased and at older ages increased. The most significant changes at birth occurred in low- and lower-middle-income countries. High- and upper-middle-income countries saw notable increases at old ages. Women generally have longer HALE and higher SDHL, but the overall HALE increase was greater for men. The reduction in SDHL over time suggests that more individuals benefit from increased longevity, particularly in low-income countries closing the gap with high-income countries. However, improvements in healthy survival at older ages appear unevenly distributed among individuals in high-income countries.

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Country-Level Socioeconomic Indicators Associated with Healthy Life Expectancy: Income, Urbanization, Schooling, and Internet Users: 2000–2012

Cited by 30 publications

References 27 publications

Effects on inequality in life expectancy from a social ecology perspective

Effects on inequality in life expectancy from a social ecology perspective

Understanding the Association between Environmental Factors and Longevity in Hechi, China: A Drinking Water and Soil Quality Perspective

Longer healthy life, but for how many? A stochastic analysis of healthy lifespan inequality

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