Social Inequalities In Mortality Research Articles

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

BackgroundDenmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014–2019).MethodsWe used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.ResultsWe observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.ConclusionsCOVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.

Inequalities in Mortality in the Asia-Pacific: A Cross-National Comparison of Socioeconomic Gradients.

Social inequalities in mortality are poorly studied in much of the Asia-Pacific. Using data from harmonized nationally representative longitudinal health and aging surveys our study systematically assesses mortality disparities across 3 standardized measures of socioeconomic status in 7 Asia-Pacific countries. We used data from multiple waves of 7 representative sample surveys: the Health, Income and Labour Dynamics in Australia survey, China Health and Retirement Longitudinal Study, the Indonesian Family Life Survey, the New Zealand Health, Work and Retirement survey, the Korean Longitudinal Study on Ageing and the Health, Aging and Retirement in Thailand survey, and the Japanese Study of Aging and Retirement. We use Cox proportional hazards modeling to examine how the hazard of mortality differs across domains of social stratification including educational attainment, wealth, and occupational status across countries. We found consistent and pervasive gradients in mortality risk in the high-income countries by all available measures of social stratification. In contrast, patterns of inequality in adult mortality in middle-income and recently transitioned high-income countries investigated varied depending on the measure of social stratification, with strong gradients by wealth but mixed gradients by education. Analyzing social gradients in mortality in the Asia-Pacific shows that inequalities, especially wealth-based inequalities, in later-life health are present across the region, and that the magnitude of social gradients in mortality is overall larger in high-income countries as compared to middle-income countries.

Area-based social inequalities in adult mortality: construction of French deprivation-specific life tables for the period 2016-2018.

In order to tackle social inequalities in mortality, it is crucial to quantify them. We produced French deprivation-specific life tables for the period 2016-2018 to measure the social gradient in adult all-cause mortality. Data from the Permanent Demographic Sample (EDP) were used to provide population and death counts by age, sex and deprivation quintile. The European Deprivation Index (EDI), applied at a sub-municipal geographical level, was used as an ecological measure of deprivation. Smoothed mortality rates were calculated using a one-dimensional Poisson counts smoothing method with P-Splines. We calculated life expectancies by age, sex and deprivation quintile as well as interquartile mortality rate ratios (MRR). At the age of 30, the difference in life expectancy between the most and least deprived groups amounted to 3.9 years in males and 2.2 years in females. In terms of relative mortality inequalities, the largest gaps between extreme deprivation groups were around age 55 for males (MRR = 2.22 [2.0; 2.46] at age 55), around age 50 in females (MRR = 1.77 [1.48; 2.1] at age 47), and there was a decrease or disappearance of the gaps in the very older adults. There is a strong social gradient in all-cause mortality in France for males and females. The methodology for building these deprivation-specific life tables is reproducible and could be used to monitor its development. The tables produced should contribute to improving studies on net survival inequalities for specific diseases by taking into account the pre-existing social gradient in all-cause mortality.

Understanding excess mortality during COVID in Belgium: the influence of health and social factors

Abstract Background This study aims to investigate how pre-existing health status and social background contribute to excess mortality during the COVID-19 crisis in Belgium. Methods The study population consists of 1.4 million adult members of Solidaris, the second largest health insurance fund in Belgium. Pre-existing health status was identified using health care reimbursement data, including medication use. Social characteristics included financial support, migrant background, and household composition. Excess mortality during the COVID-19 crisis was measured as the relative difference between all-cause mortality in 2020 or 2021 versus the pooled yearly estimates in 2015-2019. Yearly age- and sex-adjusted mortality rate ratios (MRR) were estimated using Poisson regression to study potential differences by health status and social factors. Results Compared with healthy persons, all investigated health problems were associated with increased mortality, with most notably an MRR of 8.4 (CI 8.0-8.9) for persons with cancer in 2021. Compared with 2015-2019, MRRs for persons with mental disorders (anxiety, depression) and diabetes were significantly higher than expected in 2020. Interestingly, mortality for persons with mental disorders was significantly lower than expected in 2021. Significant mortality deficits were also observed for persons with cancer and chronic respiratory conditions (COPD, asthma) in 2020 and 2021. After controlling for social characteristics, only the mortality deficits for persons with cancer and chronic respiratory conditions remained significant (p < 0.005), with respectively, 17% and 11% lower mortality in 2020, and 12% and 6% lower mortality in 2021. Conclusions Large mortality differences were observed by pre-existing health problem and social background during the COVID-19 crisis. A significant mortality deficit was observed for persons with cancer and chronic respiratory conditions in 2020 and in 2021. Key messages • Information on pre-existing health problems and social background are key to understanding excess mortality patterns. • The already large health and social inequalities in mortality did not widen further during the COVID-19 crisis in Belgium.

Socio-economic inequality and healthcare costs over the life course – A dynamic microsimulation approach

ObjectivesAlthough there is well-established evidence for the existence of socio-economic inequalities in virtually all dimensions of health, little is known about the implications of these socio-economic disparities for healthcare costs from a cumulative life course perspective. Accounting for differentials in healthcare use patterns and mortality, we assess how lifetime costs differ between socio-economic groups. Study designThis study used dynamic microsimulation modelling. MethodsCombining price weights for healthcare services with information on healthcare consumption from the 2014 Austrian Health Interview Survey (n = 15,771), we calculated average cost profiles by gender, age and education consistent with aggregate System of Health Accounts. A dynamic microsimulation model was used to project cumulative healthcare costs over the entire lifecycle for the 2019 birth cohort in four different scenarios to illustrate the influence of the different cost determinants on lifetime costs. ResultsBefore considering social inequalities in mortality, men with compulsory education have close to 66% higher lifetime costs than men with tertiary education; for women, the difference is close to 20%. Accounting for longevity differentials reduces this gap to approximately 40% for men and 10% for women. Closing the gap in healthcare use and in longevity between socio-economic groups would reduce lifetime healthcare expenditure by 4.1% in the 2019 birth cohort and by 19% in the whole population. ConclusionsAccounting for mortality differentials between socio-economic groups has a large impact on estimated lifetime healthcare costs. Reducing social inequalities in health can contribute to containing healthcare expenditures against the backdrop of rising life expectancy.

Inequalities in adverse birth outcomes and survival in early childhood: birth cohort in South Korea

Abstract Background Adverse birth outcomes (ABOs) are considered the most common factor of deaths in early childhood. Inequalities in child mortality occur due to interactions between intrinsic and socio-environmental factors related to socioeconomic disadvantage. There are, however, few studies investigating the impact of ABOs on mortality in terms of parental SEP. Methods Using the Under-5 Infant Birth-Death Cohort Data in Korea, a pooled retrospective birth cohort of all children born in 2012-2014 was built (N = 1,356,584). We analyzed neonatal, post-neonatal, and childhood mortality by ABOs and with the interaction of parental SEP using the Cox proportional hazard regression model for survival analyses. We further stratified the analysis both by parental SEP and child age. Multiple logistic regression was performed to confirm the social inequalities in ABO itself. Results After adjusting for covariates, children born with ABOs presented higher risk of mortality for all periods. For post-neonatal period, lower maternal education showed significant interaction effect with LBW (HR = 0.57; 95% CI = [0.39-0.85]), PTB (HR = 0.53; 95% CI = [0.33-0.86]), LBW & PTB ([HR = 0.67; 95% CI = [0.54-0.83]) while lower paternal education (HR = 0.67; 95% CI = [0.54-0.82]) and maternal unemployment (HR = 0.80; 95% CI = [0.63-0.99]) showed significance for babies with LBW & PTB. However, stratification analyses suggested that the impact of ABOs on mortality was greater for children born to lower parental SEP in neonatal period. Meanwhile apparent social inequalities in ABOs were suggested from regression analyses. Conclusions We confirmed social inequalities in the incidence of ABOs as well as mortalities from ABOs. However, the difference in mortality between babies with and without ABOs was greater for advantaged children. Policies to reduce the mortality of children with ABOs as well as those of healthy children among socioeconomically disadvantaged families are required. Key messages • Social inequalities in mortality from ABOs were apparent especially in the neonatal period while the incidence of ABOs itself was greater among children from disadvantaged families. • Disadvantaged children are more likely to die not only from ABOs but also from other socio-environmental determinants, especially in the post-neonatal period than their counterparts.

Impact of COVID-19 pandemic on inequalities in mortality: an analysis in Piedmont and Emilia-Romagna

Abstract Background Italy was heavily hit by the COVID-19 pandemic. According to official statistics, during 2020 there were more than 75,000 excess deaths compared to the average expected mortality in 2015-2019. General mortality (GM) is a good measure of both the direct and indirect effects of the pandemic because it's exempt from potential bias due to misclassification of events. Evidence shows a greater burden of disease and mortality attributable to COVID-19 among disadvantaged populations, with the risk of an exacerbation of existing health inequalities. We aim to analyse the trend of social inequalities in mortality during the first pandemic year in two Italian regions (Piedmont and Emilia-Romagna) using data from Administrative Population Registries (APR) and statistical databases. Methods Data on deaths occurred between Jan 2015 and Jan 2021 in subjects ≥65, stratified by educational level, were obtained from Regional APR and the Census. Using a time series approach, we computed Standardized Mortality Rates (SMR), Relative Index of Inequalities (RII) and Slope Index of Inequalities (SII), adjusted by age, gender, month and region. SMR, RII and SII from March 2020 were forecasted using Holt-Winters method and compared to the observed values in the same period. Results SMRs were higher than expected during the two 2020 epidemic waves (Mar-Apr, Oct-Dec) in both regions. RII didn't increase significantly. Absolute inequalities instead rose in Piedmont during both pandemic waves, mostly among women, and in Emilia-Romagna in March among men. Conclusions The impact of the pandemic on inequalities in GM has been at least of the same size of the impact of other mechanisms of unequal mortality. APR coupled with sociodemographic data are a quick and reliable source for assessing the unequal impact of the COVID-19 pandemic on health. Further research is needed to explore mechanisms underlying these effects e.g. inequalities in cause-specific mortality and access to health services. Key messages

Widening life expectancy inequalities across small areas of England

The UK has a long tradition of investigating geographical differences in mortality going back to the middle of the 19th century. William Farr, the 19th century pioneer of scientific analysis of vital statistics data, regarded identification and investigation of unhealthy districts as a way to help inform policies to reduce social inequalities in mortality.1 The persistence of pronounced geographical inequalities in the UK and their widening over the past 30–40 years has been noted on many occasions.

Family Health Strategy, Primary Health Care, and Social Inequalities in Mortality Among Older Adults in Bagé, Southern Brazil.

Objectives. To investigate the role of the Family Health Strategy (FHS) in reducing social inequalities in mortality over a 9-year follow-up period.Methods. We carried out a population-based cohort study of individuals aged 60 years and older from the city of Bagé, Brazil. Of 1593 participants at baseline (2008), 1314 (82.5%) were included in this 9-year follow-up (2017). We assessed type of primary health care (PHC) coverage and other variables at baseline. In 2017, we ascertained 579 deaths through mortality registers. Hazard ratios and their 95% confidence intervals modeled time to death estimated by Cox regression. We also tested the effect modification between PHC and wealth.Results. The FHS had a protective effect on mortality among individuals aged 60 to 64 years, a result not found among those not covered by the FHS. Interaction analysis showed that the FHS modified the effect of wealth on mortality. The FHS protected the poorest from all-cause mortality (hazard ratio [HR] = 0.59; 95% confidence interval [CI] = 0.36, 0.96) and avoidable mortality (HR = 0.46; 95% CI = 0.25, 0.85).Conclusions. FHS coverage reduced social inequalities in mortality among older adults. Our findings highlight the need to guarantee universal health coverage in Brazil by expanding and strengthening the FHS to promote health equity.

Socioeconomic disparities in U.S. mortality: The role of smoking and alcohol/drug abuse.

Prior studies have identified smoking as a key driver of socioeconomic disparities in U.S. mortality, but the growing drug epidemic leads us to question whether drug abuse is exacerbating those disparities, particularly for mortality from external causes. We use data from a national survey of midlife Americans to evaluate socioeconomic disparities in all-cause and cause-specific mortality over an 18-year period (1995–2013). Then, we use marginal structural modeling to quantify the indirect effects of smoking and alcohol/drug abuse in mediating those disparities. Our results demonstrate that alcohol/drug abuse makes little contribution to socioeconomic disparities in all-cause mortality, probably because the prevalence of substance abuse is low and socioeconomic differences in abuse are small, especially at older ages when most Americans die. Smoking prevalence is much higher than drug/alcohol abuse and socioeconomic differentials in smoking are large and have widened among younger cohorts. Not surprisingly, smoking accounts for the majority (62%) of the socioeconomic disparity in mortality from smoking-related diseases, but smoking also makes a substantial contribution to cardiovascular (38%) and all-cause mortality (34%). Based on the observed cohort patterns of smoking, we predict that smoking will further widen SES disparities in all-cause mortality until at least 2045 for men and even later for women. Although we cannot yet determine the mortality consequences of recent widening of the socioeconomic disparities in drug abuse, social inequalities in mortality are likely to grow even wider over the coming decades as the legacy of smoking and the recent drug epidemic take their toll.

Social inequalities in multimorbidity, frailty, disability, and transitions to mortality: a 24-year follow-up of the Whitehall II cohort study

SummaryBackgroundSocial inequalities in mortality persist in high-income countries with universal health care, and the mechanisms by which these inequalities are generated remain unclear. We aimed to examine whether social inequalities were present before or after the onset of adverse health conditions (multimorbidity, frailty, and disability).MethodsOur analysis was based on data from the ongoing Whitehall II cohort study, which enrolled British civil servants aged 35–55 years in 1985–88. Participants were assessed for three indicators of socioeconomic status (education, occupational position, and literacy) at age 50 years. Participants underwent clinical examinations (in 2002–04, 2007–09, 2012–13, and 2015–16) for assessment of frailty (two or more of low physical activity, slow walking speed, poor grip strength, weight loss, and exhaustion) and disability (two or more difficulties in bathing, dressing, going to the toilet, transferring, feeding, and walking). In addition, electronic health records were used to assess the incidence of multimorbidity (two or more of diabetes, coronary heart disease, stroke, chronic obstructive pulmonary disease, depression, arthritis, cancer, dementia, and Parkinson's disease) and mortality. In analyses adjusted for sociodemographic factors, we used multistate models to examine social inequalities in transitions from healthy state to adverse health conditions and subsequently to mortality.FindingsOf 10 308 individuals in the Whitehall II study cohort, 6425 had relevant data available at 50 years and to the end of follow-up on Aug 31, 2017, and were included in our analysis. Participants were followed up for a median of 23·6 years (IQR 19·6–28·9). 1694 (26·4%) of 6425 participants developed multimorbidity, 1733 (27·0%) became frail, 692 (10·8%) had a disability, and 611 (9·5%) died. Multimorbidity (hazard ratio [HR] 4·12 [95% CI 3·41–4·98]), frailty (HR 2·38 [95% CI 1·93–2·93]), and disability (HR 1·73 [95% CI 1·34–2·22]) were associated with increased risk of mortality; these associations were not modified by socioeconomic status. In multistate models, occupation was the socioeconomic status indicator that was most strongly associated with inequalities in the transition from healthy state to multimorbidity (HR 1·54 [95% CI 1·37–1·73]), to frailty (HR 2·08 [95% CI 1·85–2·33]), and to disability (HR 1·44 [95% CI 1·18–1·74]). Socioeconomic status indicators did not affect transitions to mortality in those with multimorbidity, frailty, or disability.InterpretationSocioeconomic status affects the risk of multimorbidity, frailty, and disability, but does not affect the risk of mortality after the onset of these adverse health conditions. Therefore, primary prevention is key to reducing social inequalities in mortality. Of the three adverse health conditions, multimorbidity had the strongest association with mortality, making it a central target for improving population health.FundingUK Medical Research Council; National Institute on Aging, National Institutes of Health; British Heart Foundation.

The respective parts of incidence and lethality in socioeconomic differences in cancer mortality. An analysis of the French network Cancer registries (FRANCIM) data

BackgroundTo determine relevant public health actions and to guide intervention priorities, it is of great importance to assess the relative contribution of incidence and lethality to social inequalities in cancer mortality.MethodsThe study population comprised 185,518 cases of cancer diagnosed between 2006 and 2009 recorded in the French registries. Survival was known for each patient (endpoint: 30/06/2013). Deprivation was assessed using the European Deprivation Index. We studied the influence of deprivation on mortality, incidence and lethality rates and quantified the respective proportions of incidence and lethality in social inequalities in mortality by calculating attributable deaths.ResultsFor cancers with social inequalities both in incidence and lethality, excess mortality in deprived was mainly caused by social inequalities in incidence (e.g. men lung cancer: 87% of excess deaths in the deprived caused by inequalities in incidence). Proportions were more balanced for some cancer sites (e.g. cervical cancer: 56% incidence, 44% lethality). For cancer sites with a higher incidence in the least deprived (e.g. breast cancer), the excess-lethality in deprived leads entirely the higher mortality among the deprived.ConclusionsMost of the excess mortality in deprived is due to the excess incidence of tobacco-dependent cancers and the excess lethality of screenable cancers.

Social patterning in Indonesian adolescent smoking: A mediation analysis of family smoking, parental control, and parental permissiveness

Objective: In poorer communities, smoking has demonstrated as an indicator of social inequalities in mortality. Adolescents from poor family are often exposed to smoking and are more vulnerable to ...

Association Between Educational Attainment and Causes of Death Among White and Black US Adults, 2010-2017

There are substantial and increasing educational differences in US adult life expectancy. To reduce social inequalities in mortality, it is important to understand how specific causes of death have contributed to increasing educational differences in adult life expectancy in recent years. To estimate the relationship of specific causes of death with increasing educational differences in adult life expectancy from 2010 to 2017. Serial cross-sectional study of 4 690 729 deaths recorded in the US National Vital Statistics System in 2010 and 2017. Sex, race/ethnicity, and educational attainment. Life expectancy at age 25 years and years of life lost between ages 25 and 84 years by cause of death. The analysis included a total of 2 211 633 deaths in 2010 and 2 479 096 deaths in 2017. Between 2010 and 2017, life expectancy at age 25 significantly declined among white and black non-Hispanic US residents from an expected age at death of 79.34 to 79.15 years (difference, -0.18 [95% CI, -0.23 to -0.14]). Greater decreases were observed among persons with a high school degree or less (white men: -1.05 years [95% CI, -1.15 to -0.94], white women: -1.14 years [95% CI, -1.24 to -1.04], and black men: -0.30 years [95% CI, -0.56 to -0.04]). White adults with some college education but no 4-year college degree experienced similar declines in life expectancy (men: -0.89 years [95% CI, -1.07 to -0.73], women: -0.59 years [95% CI, -0.77 to -0.42]). In contrast, life expectancy at age 25 significantly increased among the college-educated (white men: 0.58 years [95% CI, 0.42 to 0.73], white women: 0.78 years [95% CI, 0.57 to 1.00], and black women: 1.70 years [95% CI, 0.91 to 2.53]). The difference between high- and low-education groups increased from 2010 to 2017, largely because life-years lost to drug use increased among those with a high school degree or less (white men: 0.93 years [95% CI, 0.90 to 0.96], white women: 0.50 years [95% CI, 0.47 to 0.52], black men: 0.75 years [95% CI, 0.71 to 0.79], and black women: 0.28 years [95% CI, 0.25 to 0.31]). In this serial cross-sectional study, estimated life expectancy at age 25 years declined overall between 2010 and 2017; however, it declined among persons without a 4-year college degree and increased among college-educated persons. Much of the increasing educational differences in years of life lost may be related to deaths attributed to drug use.

Italian Atlas of mortality inequalities by education level.

To evaluate the geographical and socioeconomic differences in mortality and in life expectancy in Italy; to evaluate the proportion of mortality in the population attributable to a medium-low education level through the use of maps and indicators. Longitudinal design of the population enrolled in the 2011 Italian Census, following the population over time and registering any exit due to death or emigration. The study used the database of the Italian National Institute of Statistics (Istat) developed by linking the 2011 Census with the Italian National Register of Causes of Death (2012-2014) for 35 groups of causes of death. Age, sex, residence, and education level information were collected from the Census. Life expectancy at birth was calculated by sex, Italian region, and education level. For the population aged 30-89 years, the following items were developed by sex: 1. provincial maps showing, for each cause of death, the distribution in quintiles of smoothed standardized mortality ratio (SMR), adjusted for age and education level and estimated with Bayesian models for small areas (spatial conditional autoregressive model); 2. regional maps of population attributable fraction (PAF) for low and medium education levels, calculated starting from age-standardized mortality ratios; 3. tables illustrating for each region standardized mortality rates and standardized years of life lost rate by age (standardized YLL rate), and mortality rate ratios standardized by age (MMRs). Males with a lower education level throughout Italy show a life expectancy at birth that is 3 years less than those with higher education; residents in Southern Italy lose an additional year in life expectancy, regardless of education level. Social inequalities in mortality are present in all regions, but are more marked in the poorer regions of Southern Italy. Geographical differences, taking into account the different population distributions in terms of age and education level, produce mortality differences for all causes: from -15% to +30% in women and from -13% to +26% in men, compared to the national average. Among the main groups of causes, the geographical differences are greater for cardiovascular diseases, respiratory diseases, and accidents, and lower for many tumour sites. A clear mortality gradient with an excess in Southern Italy can be seen for cardiovascular diseases: there are some areas where mortality for people with higher education level is higher than that for residents in Northern Italy with low education level. The gradient for "All tumours", instead, is from South to North, as it is for most single tumour sites. Population attributable fraction for low education level in Italy, taking into account the population distribution by age, is 13.4% in women and 18.3% in men. The study highlighted important geographical differences in mortality, regardless of age and socioeconomic level, with a more significant impact in the poorer Southern regions, revealing a never-before-seen health advantage in the regions along the Adriatic coast. A lower education level explains a considerable proportion of mortality risk, although with differing effects by geographical area and cause of death. There are still mortality inequalities in Italy, therefore, representing a possible missed gain in health in our Country; these inequalities suggest a reassessment of priorities and definition of health targets. Forty years after the Italian National Health Service was instituted, the goal of health equity has not yet been fully achieved.

Desigualdades sociales en salud. Un análisis de la mortalidad por las principales causas de muerte en España y Francia, 1988-1990

El objetivo de este artículo es comparar las desigualdades sociales en la mortalidad por las principales causas de muerte en España y en Francia durante el período 1988-90. Tanto en España como en Francia, la mortalidad en el grupo de trabajadores manuales es más alta que la mortalidad en el resto de los grupos ocupacionales para todas las causas de muerte analizadas. Por su parte, los agricultores presentan una mortalidad intermedia entre los profesionales y directivos y entre los trabajadores manuales. Los trabajadores manuales tienen una mortalidad 1,89 veces más alta que los profesionales y directivos en España y 1,67 veces más alta en Francia. En España, las mayores diferencias entre la mortalidad de trabajadores manuales y la mortalidad de profesionales y directivos se observa en accidentes y en las enfermedades del aparato respiratorio; por su parte, en Francia, las mayores diferencias se observan en las enfemiedades del aparato digestivo y en las enfermedades del aparato respiratorio.

Thanatopolitics and thanatosociology

Th e aim of the appendix is to show the directions of sociological researchof political use of death. Th ere are two related Social Sciencediscourses on death: (1) thanatos sociological, which deals with socialinequalities in mortality, and (2) thanatopolitical, in which center isthe political instrumentalization of death. It is shown the historicalevolution of these relations to death and are considered diff erent theoreticaland methodological starting points that explain the politicalside of death and its symbolic capital. Th e vision of death has changed,as well as political use of the death. Th e most attention was devotedto a class-tier thanatological diff erences. Classes do not show only economicinequality, but also the symbolic and cultural inequality, andso they also diff er in relation to the death. It is presented a draft forthe sociological framework for the study of historical class interests thatdetermine the ideological use of death.

Analysis of conglomerates for the study of social inequalities due to cardiovascular diseases

To establish social inequalities in mortality from cardiovascular diseases in the municipalities located in the "triángulo del café". Ecological design that measured social inequalities in mortality due to hypertension, ischemia and stroke according to economic indicators in the municipalities located in Caldas, Quindío, and Risaralda. Mortality for calculating rates and Unsatisfied Basic Needs (NBI) were obtained from the National Statistics Department; the Gross Domestic Product (GDP) was calculated for the study. A multivariate cluster analysis was used grouping the municipalities into classes according to the similarity in their characteristics. Three classes were identified: municipalities of the first class have the highest per capita GDP, the lowest BIN, the highest mortality rate for stroke, the lowest mortality rate for the lowest hypertension. Class two has the lowest per capita GDP and the highest mortality rate for ischemic. Class three has the highest NBI, the highest average in mortality due to hypertension and ischemic. The conglomerate conformation suggests a relationship between a high BIN and the mortality rates due to hypertensive and ischemic. A high per capita GDP and low NBI with the mortality rate for stroke. No significant differences in the mortality rates due to stroke, ischemic or hypertension, in the various states under study were observed.

Narrowing mortality gap between men and women over two decades: a registry-based study in Ontario, Canada

BackgroundHistorically, women have lower all-cause mortality than men. It is less understood that sex differences have been converging, particularly among certain subgroups and causes. This has implications for public health...

Des inégalités sociales de santé moins marquées chez les femmes que chez les hommes : une question de mesure ?

Social inequalities in mortality are generally less pronounced for women than for men. Are women's health risks and behaviours more homogeneous, or does this pattern arise from a measurement issue inducing an under-estimation of these inequalities? This article reviews a number of studies covering different dimensions of health and different dimensions of social status. Their findings show that there are large social inequalities in health among women. The focus on the working careers, family histories and conciliation of multiple activities provides evidence of major social determinants of health to which women are widely exposed. This article highlights the need to broaden the notion of social inequality and to redefine the social categories, notably by considering the distinct trajectories of men and women and their different spheres of activity. It highlights that gender differences in health are themselves partly socially constructed, as suggested by the gender approaches in the social sciences.