Global inequality of life expectancy due to AIDS.
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ABSTRACT:
SUBMITTER: Dorling D
PROVIDER: S-EPMC1403259 | biostudies-literature | 2006 Mar
REPOSITORIES: biostudies-literature
Publications
Global inequality of life expectancy due to AIDS.
Dorling Danny D Shaw Mary M Davey Smith George G
BMJ (Clinical research ed.) 20060301 7542
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Project description:SignificanceIndia is one of the most hierarchical societies in the world. Because vital statistics are incomplete, mortality disparities are not quantified. Using survey data on more than 20 million individuals from nine Indian states representing about half of India's population, we estimate and decompose life expectancy differences between higher-caste Hindus, comprising other backward classes and high castes, and three marginalized social groups: Adivasis (indigenous peoples), Dalits (oppressed castes), and Muslims. The three marginalized groups experience large disadvantages in life expectancy at birth relative to higher-caste Hindus. Economic status explains less than half of these gaps. These large disparities underscore parallels between diverse systems of discrimination akin to racism. They highlight the global significance of addressing social inequality in India.
| S-EPMC8915795 | biostudies-literature
Project description:BackgroundVenezuela is one of the most violent countries in the world. According to the United Nations, homicide rates in the country increased from 32.9 to 61.9 per 100 000 people between 2000 and 2014. This upsurge coincided with a slowdown in life expectancy improvements. We estimate mortality trends and quantify the impact of violence-related deaths and other causes of death on life expectancy and lifespan inequality in Venezuela.MethodsLife tables were computed with corrected age-specific mortality rates from 1996 to 2013. From these, changes in life expectancy and lifespan inequality were decomposed by age and cause of death using a continuous-change model. Lifespan inequality, or variation in age at death, is measured by the standard deviation of the age-at-death distribution.ResultsFrom 1996 to 2013 in Venezuela, female life expectancy rose 3.57 [95% confidence interval (CI): 3.08-4.09] years [from 75.79 (75.98-76.10) to 79.36 (78.97-79.68)], and lifespan inequality fell 1.03 (-2.96 to 1.26) years [from 18.44 (18.01-19.00) to 17.41 (17.30-18.27)]. Male life expectancy increased 1.64 (1.09-2.25) years [from 69.36 (68.89-59.70) to 71.00 (70.53-71.39)], but lifespan inequality increased 0.95 (-0.80 to 2.89) years [from 20.70 (20.24-21.08) to 21.65 (21.34-22.12)]. If violence-related death rates had not risen over this period, male life expectancy would have increased an additional 1.55 years, and lifespan inequality would have declined slightly (-0.31 years).ConclusionsAs increases in violence-related deaths among young men (ages 15-39) have slowed gains in male life expectancy and increased lifespan inequality, Venezuelan males face more uncertainty about their age at death. There is an urgent need for more accurate mortality estimates in Venezuela.
| S-EPMC6857745 | biostudies-literature
Project description:This work proposes a method to compute the income gradient in period life expectancy that accounts for income mobility. Using income and mortality records of the Danish population over the period 1980-2013, we validate the method and provide estimates of the income gradient. The period life expectancy of individuals at a certain age, and belonging to a certain income class, is normally computed by using the mortality of older cohorts in the same income class. This approach does not take into account that a substantial fraction of the population moves away from their original income class, which leads to an upward bias in the estimation of the income gradient in life expectancy. For 40-y-olds in the bottom 5% of the income distribution, the risk of dying before age 60 is overestimated by 25%. For the top 5% income class, the risk of dying is underestimated by 20%. By incorporating a classic approach from the social mobility literature, we provide a method that predicts income mobility and future mortality simultaneously. With this method, the association between income and life expectancy is lower throughout the income distribution. Without accounting for income mobility, the estimated difference in life expectancy between persons in percentiles 20 and 80 in the income distribution is 4.6 y for males and 4.1 y for females, while it is only half as big when accounting for mobility. The estimated rise in life-expectancy inequality over time is also halved when accounting for income mobility.
| S-EPMC6243245 | biostudies-literature
Project description:BackgroundAlongside average health measures, namely, life expectancy (LE) and healthy life expectancy (HLE), we sought to investigate the inequality in lifespan and healthy lifespan at the worldwide level with an alternative indicator.MethodsUsing data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, we evaluated the global distribution of life disparity (LD) and healthy life disparity (HLD) for 204 countries and territories in 2019 by sex and socio-demographic index (SDI), and also explored the relationships between average and variation health indicators.ResultsSubstantial gaps in all observed health indicators were found across SDI quintiles. For instance, in 2019, for low SDI, female LE and HLE were 67.3 years (95% confidence interval 66.8, 67.6) and 57.4 years (56.6, 57.9), and their LD and HLD were 16.7 years (16.5, 17.0) and 14.4 years (14.1, 14.7). For high SDI, female LE and HLE were greater [83.7 years (83.6, 83.7) and 70.2 years (69.3, 70.7)], but their LD and HLD were smaller [10.4 years (10.3, 10.4) and 7.9 years (7.7, 8.0)]. Besides, all estimates varied across populations within each SDI quintile. There were also gaps in LD and HLD between males and females, as those found in LE and HLE.ConclusionIn addition to the disadvantaged LE and HLE, greater LD and HLD were also found in low SDI countries and territories. This reveals the serious challenge in achieving global health equality. Targeted policies are thus necessary for improving health performance among these populations.
| S-EPMC10990531 | biostudies-literature
Project description:Health inequalities are often assessed in terms of life expectancy or health-related quality of life (HRQoL). Few studies combine both aspects into quality-adjusted life expectancy (QALE) to derive comprehensive estimates of lifetime health inequality. Furthermore, little is known about the sensitivity of estimated inequalities in QALE to different sources of HRQoL information. This study assesses inequalities in QALE by educational attainment in Norway using two different measures of HRQoL. We combine full population life tables from Statistics Norway with survey data from the Tromsø study, a representative sample of the Norwegian population aged ≥ 40. HRQoL is measured using the EQ-5D-5L and EQ-VAS instruments. Life expectancy and QALE at 40 years of age are calculated using the Sullivan-Chiang method and are stratified by educational attainment. Inequality is measured as the absolute and relative gap between individuals with lowest (i.e. primary school) and highest (university degree 4 + years) educational attainment. People with the highest educational attainment can expect to live longer lives (men: + 17.9% (95%CI: 16.4 to 19.5%), women: + 13.0% (95%CI: 10.6 to 15.5%)) and have higher QALE (men: + 22.4% (95%CI: 20.4 to 24.4%), women: + 18.3% (95%CI: 15.2 to 21.6%); measured using EQ-5D-5L) than individuals with primary school education. Relative inequality is larger when HRQoL is measured using EQ-VAS. Health inequalities by educational attainment become wider when measured in QALE rather than LE, and the degree of this widening is larger when measuring HRQoL by EQ-VAS than by EQ-5D-5L. We find a sizable educational gradient in lifetime health in Norway, one of the most developed and egalitarian societies in the world. Our estimates provide a benchmark against which other countries can be compared.
| S-EPMC10155341 | biostudies-literature
Project description:BackgroundLife expectancy (LE) and healthy life expectancy (HALE) are indicators measuring the national health level. GAP is the difference between them. This study systematically analyzed and projected LE, HALE, and GAP across global regions from 1995 to 2025.MethodsWe obtained the data of 195 countries/regions on their LE, HALE, and influencing factors from 1995 to 2017. We compared the overall changes of LE, HALE, and GAP. Multiple linear regression analysis examined relationships among LE, HALE, GAP, and the associated factors. Using the Autoregressive Integrated Moving Average (ARIMA) model, we projected trends in LE, HALE, and GAP for 2017-2025.ResultsDuring 1995-2017, LE, HALE, and their GAP in 195 countries/regions in the world showed overall increasing trends. Global average LE increased from 66.20 to 72.98 years, HALE from 57.59 to 63.25 years, and GAP from 8.62 to 9.72 years. LE and HALE in North America, Europe, and Australia were generally higher, while Africa had the lowest rates. Females' LE, HALE, and GAP were all higher than males', but females' growth rates of LE and HALE were lower. Different factors were included to project LE, HALE, and GAP, respectively, and prediction results showed that approximately 18% of the 195 countries/regions might achieve improved LE and HALE and lower GAP.ConclusionsLE, HALE will likely continue to increase in most of countries and regions worldwide in the future and GAP will further expand. While striving to improve LE and HALE, more attention needs be made to reduce GAP and improve quality of life.
| S-EPMC7568920 | biostudies-literature
Project description:Objective: To characterize miRNAs in 41-year archived plasma in relation to life expectancy independent of genes. Method: Plasma miRNAs from nine identical male twins were profiled using next-generation sequencing. Results: The average absolute difference in the minimum life expectancy was 9.68 years. Intra-class correlation coefficients were above 0.4 for 50% of miRNAs. Comparing deceased twins with their alive co-twin brothers, the concentrations were increased for 34 but decreased for 30 miRNAs. Conclusion: Identical twins discordant in life expectancy were unlike in the majority of miRNAs, suggesting that environmental factors are pivotal in miRNAs related to life expectancy.
2016-12-30 | GSE80730 | GEO
Project description:BACKGROUND:The aim of this study was to measure differences in quality-adjusted life expectancy (QALE) by income in Korea at the national and district levels. METHODS:Mortality rates and EuroQol-5D (EQ-5D) scores were obtained from the National Health Information Database of the National Health Insurance Service and the Korea Community Health Survey, respectively. QALE and differences in QALE among income quintiles were calculated using combined 2008-2014 data for 245 districts in Korea. Correlation analyses were conducted to investigate the associations of neighborhood characteristics with QALE and income gaps therein. RESULTS:QALE showed a graded pattern of inequality according to income, and increased over time for all levels of income and in both sexes, except for low-income quintiles among women, resulting in a widened inequality in QALE among women. In all 245 districts, pro-rich inequalities in QALE were found in both men and women. Districts with higher QALE and smaller income gaps in QALE were concentrated in metropolitan areas, while districts with lower QALE and larger income gaps in QALE were found in rural areas. QALE and differences in QALE by income showed relatively close correlations with socioeconomic characteristics, but relatively weak correlations with health behaviors, except for smoking and indicators related to medical resources. CONCLUSIONS:This study provides evidence of income-based inequalities in health measured by QALE in all subnational areas in Korea. Furthermore, QALE and differences in QALE by income were closely associated with neighborhood-level socioeconomic characteristics.
| S-EPMC7045490 | biostudies-literature
Project description:Population is aging rapidly in Europe. Older age life expectancy (OLE) can be influenced by country-level depth of credit information (DCI) as an indicator of financial crisis, gross national income (GNI) per capita, and gender inequality index (GII). These factors are key indicators of socio-ecological inequality. They can be used to develop strategies to reduce country-level health disparity. The objective of this study was to confirm the relationship between socio-ecological factors and OLE in Europe.Data were obtained from World Bank, WHO, and UN database for 34 Europe countries. Associations between socio-ecological factors and OLE were assessed with Pearson correlation coefficients and three regression models. These models assumed that appropriate changes in country-level strategies of healthy aging would produce changes in GNI per capital as personal perspective, GII in social environment perspective, and DCI in public policy perspective to implement socio-ecological changes. Hierarchal linear regression was used for final analysis.Although OLE (women and men) had significant negative correlation with GII (gender inequality index, r = - 0.798, p = 0.001), it had positive correlations with GNI (gross national income per capita, r = 0.834, p = 0.001) and DCI (depth of credit information index, r = 0.704, p = 0.001) levels caused by financial crisis. Higher levels GNI and DCI but lower GII were found to be predictors of OLE (women and men) (R2 = 0.804, p < 0.001).Factors affecting older age life expectancy in Europe were identified from socio-ecological perspective. Socio-ecological indicators (GII, GNI, and DCI) in Europe appear to have a latent effect on OLE levels. Thus, country-level strategies of successful aging in Europe should target socio-ecological factors such as GII, GNI, and DCI value.
| S-EPMC5561580 | biostudies-other
Project description:Background Geographic inequality in US mortality has increased rapidly over the last 25 years, particularly between metropolitan and nonmetropolitan areas. These gaps are sizeable and rival life expectancy differences between the US and other high-income countries. This study determines the contribution of smoking, a key contributor to premature mortality in the US, to geographic inequality in mortality over the past quarter century. Methods We used death certificate and census data covering the entire US population aged 50+ between Jan 1, 1990 and Dec 31, 2019. We categorized counties into 40 geographic areas cross-classified by region and metropolitan category. We estimated life expectancy at age 50 and the index of dissimilarity for mortality, a measure of inequality in mortality, with and without smoking for these areas in 1990–1992 and 2017–2019. We estimated the changes in life expectancy levels and percent change in inequality in mortality due to smoking between these periods. Results We find that the gap in life expectany between metros and nonmetros increased by 2.17 years for men and 2.77 years for women. Changes in smoking-related deaths are responsible for 19% and 22% of those increases, respectively. Among the 40 geographic areas, increases in life expectancy driven by changes in smoking ranged from 0.91 to 2.34 years for men while, for women, smoking-related changes ranged from a 0.61-year decline to a 0.45-year improvement. The most favorable trends in years of life lost to smoking tended to be concentrated in large central metros in the South and Midwest, while the least favorable trends occurred in nonmetros in these same regions. Smoking contributed to increases in mortality inequality for men aged 70+, with the contribution ranging from 8 to 24%, and for women aged 50–84, ranging from 14 to 44%. Conclusions Mortality attributable to smoking is declining fastest in large cities and coastal areas and more slowly in nonmetropolitan areas of the US. Increasing geographic inequalities in mortality are partly due to these geographic divergences in smoking patterns over the past several decades. Policies addressing smoking in non-metropolitan areas may reduce geographic inequality in mortality and contribute to future gains in life expectancy.
| S-EPMC9490306 | biostudies-literature