Social Inequalities In Mortality Research Articles

Social inequalities in mortality in older women cannot be explained by biological and health behavioural factors — results from a Norwegian health survey (the HUNT Study)

To assess mortality inequalities related to education, employment and marital status in older women, and whether educational and employment inequalities can be explained by biological, health behavioural or marital factors. Data, collected by questionnaires and medical examinations, on 5607 Norwegian women aged > or =70 participating in the population-based Nord-Trøndelag health study in 1995-97, were linked with information from the Death Registry at Statistics Norway at 31.12.2004. Cox regression model was used to estimate hazard ratios (HR) of all-cause and cardiovascular mortality related to educational level and previous employment, and to marital status. Low level of education and never having been in paid work were significantly associated with elevated all-cause mortality. The associations remained significant upon adjustments for age, marital status, biological (systolic blood pressure, body mass index, total cholesterol) and health behavioural (smoking, physical activities) factors. Differences in cardiovascular mortality were related to low level of education and never having been in paid work, though the significant age-adjusted associations only remained significant for education upon adjustments for age, marital, biological and behavioural factors. A raised risk in cardiovascular mortality was found among women previously holding manual jobs (HR1.23, 95% CI 0.99-1.53). The graded association between education, employment and mortality showed a significant trend, except from the occupation gradient in cardiovascular mortality. Widowed and divorced women had an age-adjusted significantly raised all-cause and significant cardiovascular mortality risk compared with married women. The socioeconomic and marital differences in mortality in older women could not be explained by biological and behavioural factors, and remains a public health issue.

Social inequalities in mortality by cause among men and women in France

Background:The aim of this study was to compare inequalities in mortality (all causes and by cause) by occupational group and educational level between men and women living in France in...

Author's Response: Self-rated health may be adequate for broad assessments of social inequalities in health

We thank the authors for their engaging responses,1–3 and especially applaud Singh-Manoux and colleagues and Huisman and colleagues for conducting additional analyses as a response to our letter.4 We take this opportunity to summarize what we have learned from this exchange on the question that implicitly or explicitly motivated the three studies:5–7 are assessments of social inequalities in health based on subjective health problematic? The quick answer, based on the original study and these exchanges, is, maybe not. We reiterate—as we did in our original letter—we do not question the intrinsic relevance of examining whether the association between self-rated health (SRH) and mortality varies by socioeconomic status (SES). Our concern was mainly with interpreting these tests of interaction to comment on whether SRH-based health inequality assessments are misleading. The additional analysis conducted by Singh-Manoux and colleagues bolsters their initial claim that assessment of health inequalities based on SRH are likely to be conservative compared with assessment of health inequalities based on mortality. Their additional analysis also underscores that assessments of social inequalities in health may well depend on the specific measure of SES;1 an aspect that needs attention in general.8 The additional analysis conducted by Huisman and colleagues, meanwhile, suggests that assessments of social inequalities in health using SRH may depend on how we dichotomize ‘poor’ SRH.2 Under one specification (when SRH = fair/poor health or not) there is some over-estimation of social inequalities in health (compared with what is observed based on SES differentials in mortality). However, when SRH is dichotomized as fair/poor/good or not, the social inequalities in health using SRH are similar to those observed using mortality.2 Thus, the studies by Singh-Manoux and colleagues and Huisman and colleagues, with the benefit of these additional analyses, bring us some insights about the use of SES as well as the use of SRH in health inequalities assessment. At the same time, these additional analyses, in our view, do not suggest that we are in danger of getting the magnitude of social inequality in health completely wrong if we used SRH instead of an objective measure such as mortality. Dowd and Zajacova choose not to conduct the additional direct test that we suggested in our letter.3 Instead, they cite reasonable epidemiologic arguments to question our analyses (and comparison) as well as to defend their decision not to conduct a direct test in their sample, though it would have been possible. While we concur with their nuanced epidemiologic reasoning, we still think a direct comparison between social inequalities in SRH and social inequalities in mortality in their sample would have provided broad insights into this big question, with their concerns included as caveats. Without the benefit of a direct comparison, it is difficult to assess the following conclusions from their original study: ‘the finding that SRH does not predict mortality as well at lower levels of SES has important implications for research on health inequalities that has assumed the magnitude of SES inequalities in SRH corresponds well to SES inequalities in mortality’5 (p. 1220) and ‘whether this commonly used measure is ultimately too misleading to be used in the study of health inequalities’5 (p. 1220). Finally, in their response, Singh-Manoux and colleagues cite Amartya Sen's influential editorial that showed discordance between self-reported health and mortality using aggregate data from India in the 1970s.9 One of the authors of this exchange (S.V.S.) has examined more recent data at the individual level, and found the SES patterning in SRH or self-reported morbidity in India is in the expected direction (i.e. low SES are more likely to report poor health or report morbidity).10 Indeed, other recent reports from developing countries,11,12 suggest considerable face validity to self-reported health measures. In conclusion, while rigorous scrutiny of subjective health measures is necessary, it is comforting to know that assessments of the extent of social inequalities in health based on SRH, a measure frequently used due to its ease of assessment, are not likely to be misleading.

Does personality explain social inequalities in mortality? The French GAZEL cohort study

The 'indirect-selection' hypothesis proposes that some quality of the individual, a personality characteristic or intelligence, leads to both socioeconomic position (SEP) and health. We aim to quantify the contribution of personality measures to the associations between SEP and mortality. Of the GAZEL cohort, 14 445 participants aged 39-54 years in 1993 and followed-up over 12.7 years, completed the Bortner-Type-A-scale, the Buss-Durkee-Hostility-Inventory and the Grossarth-Maticek and Eysenck-Personality-Stress-Inventory. Indicators of SEP, such as father's social class, education, occupational grade and income, were assessed at baseline. Relative indices of inequality in Cox regression models were used to estimate associations. In age-adjusted analyses, risk of death was inversely associated with SEP among men and women. Among men, the attenuation in this association depended on the measures of SEP and was 28-29% for 'neurotic-hostility', 13-22% for 'anti-social' and 13-16% for 'CHD-prone' personality. In women, the attenuation was evident only for type-A-behaviour, by 11%. After controlling simultaneously for all personality factors that predicted mortality, associations between SEP and mortality were attenuated in men: by 34% for education, 29% for occupational position and 28% for income; but were only attenuated by 11% for income in women. For cardiovascular mortality, the corresponding percentages of reduction were 42, 31 and 44% after adjustment for 'CHD-prone' personality in men. Personality measures explained some of the mortality gradients observed for measures of adult socioeconomic position in men, but had little explanatory power in women. Whether personality represents a predictor or an outcome of social circumstances needs further research.

Are social inequalities in mortality in Britain narrowing? Time trends from 1978 to 2005 in a population-based study of older men

Objective:To examine whether social inequalities in all-cause and coronary heart disease (CHD) mortality in Britain have reduced between 1978 and 2005.Design:A prospective study of a socioeconomically representative population.Setting:24 British towns.Participants:7735...

Social inequalities in male mortality, and in male mortality from smoking: indirect estimation from national death rates in England and Wales, Poland, and North America

There are substantial social inequalities in adult male mortality in many countries. Smoking is often more prevalent among men of lower social class, education, or income. The contribution of smoking to these social inequalities in mortality remains uncertain. The contribution of smoking to adult mortality in a population can be estimated indirectly from disease-specific death rates in that population (using absolute lung cancer rates to indicate proportions due to smoking of mortality from certain other diseases). We applied these methods to 1996 death rates at ages 35-69 years in men in three different social strata in four countries, based on a total of 0.6 million deaths. The highest and lowest social strata were based on social class (professional vs unskilled manual) in England and Wales, neighbourhood income (top vs bottom quintile) in urban Canada, and completed years of education (more than vs less than 12 years) in the USA and Poland. In each country, there was about a two-fold difference between the highest and the lowest social strata in overall risks of dying among men aged 35-69 years (England and Wales 21%vs 43%, USA 20%vs 37%, Canada 21%vs 34%, Poland 26%vs 50%: four-country mean 22%vs 41%, four-country mean absolute difference 19%). More than half of this difference in mortality between the top and bottom social strata involved differences in risks of being killed at age 35-69 years by smoking (England and Wales 4%vs 19%, USA 4%vs 15%, Canada 6%vs 13%, Poland 5%vs 22%: four-country mean 5%vs 17%, four-country mean absolute difference 12%). Smoking-attributed mortality accounted for nearly half of total male mortality in the lowest social stratum of each country. In these populations, most, but not all, of the substantial social inequalities in adult male mortality during the 1990s were due to the effects of smoking. Widespread cessation of smoking could eventually halve the absolute differences between these social strata in the risk of premature death.

Evolución de las desigualdades sociales en la mortalidad general de la ciudad de Sevilla (1994-2002)

Objectives To know trends of social inequalities in general mortality in Seville (Spain) between 1997 and 2002. Material and method Socioeconomic level of its the residential census tracts was assigned for each death, taken from the Socio-economic Synthetic Index built up after applying a principal components analysis from 2001 census variables. Using mortality indicators its magnitude and trend was described according socio-economic level. Results General mortality standardized rates by age in the census tracts of lowest socio-economic level were 1.32 and 1.25 times greater than in the highest census tracts in men and 1.19 and 1.08 in women respectively in each periods. The truncated rates ratio and potential years of lost life in men went from 1.66 to 2.28 in men and 1.74 to 2.10 in women, respectively. The four years difference in life expectancy at birth between the census tracts of highest and lower level remained unchanged in men, and fell from 1.90 to 0.82 in women. The population attributable risk (all ages) went from 13.18% to 10.46% in men and 10.02% to 2.58% in women. Conclusions Social inequalities in mortality for the general population decreased mainly in women. The inequalities increased in the early death and between 35-64 years old in men, basically due to a reduced mortality in higher socio-economic level census tracts.

Smoking and inequalities

Smoking is a modern scourge. The WHO global burden of disease study suggested that, in developed countries, 26% of male deaths and 9% of female deaths could be attributed to smoking—the single most important risk factor.1 We must consider not just aggregate effects but social distribution. In many countries the likelihood of smoking is linked to socioeconomic position: lower status, more smoking. Hence, among other evils, smoking contributes to social inequalities in mortality. The size of that contribution is considerable.

Socioeconomic and country variations in knowledge of health risks of tobacco smoking and toxic constituents of smoke: results from the 2002 International Tobacco Control (ITC) Four Country Survey

Background: Socioeconomic status is strongly associated with smoking prevalence and social class differences contribute substantially to social inequalities in mortality. This research investigated socioeconomic and country variations in smokers’ knowledge...

Contribution of main causes of death to social inequalities in mortality in the whole population of Scania, Sweden.

BackgroundTo more efficiently reduce social inequalities in mortality, it is important to establish which causes of death contribute the most to socioeconomic mortality differentials. Few studies have investigated which diseases contribute to existing socioeconomic mortality differences in specific age groups and none were in samples of the whole population, where selection bias is minimized. The aim of the present study was to determine which causes of death contribute the most to social inequalities in mortality in each age group in the whole population of Scania, Sweden.MethodsData from LOMAS (Longitudinal Multilevel Analysis in Skåne) were used to estimate 12-year follow-up mortality rates across levels of socioeconomic position (SEP) and workforce participation in 975,938 men and women aged 0 to 80 years, during 1991–2002.ResultsThe results generally showed increasing absolute mortality differences between those holding manual and non-manual occupations with increasing age, while there were inverted u-shaped associations when using relative inequality measures. Cardiovascular diseases (CVD) contributed to 52% of the male socioeconomic difference in overall mortality, cancer to 18%, external causes to 4% and psychiatric disorders to 3%. The corresponding contributions in women were 55%, 21%, 2% and 3%. Additionally, those outside the workforce (i.e., students, housewives, disability pensioners, and the unemployed) showed a strongly increased risk of future mortality in all age groups compared to those inside the workforce. Even though coronary heart disease (CHD) played a major contributing role to the mortality differences seen, stroke and other types of cardiovascular diseases also made substantial contributions. Furthermore, while the most common types of cancers made substantial contributions to the socioeconomic mortality differences, in some age groups more than half of the differences in cancer mortality could be attributed to rarer cancers.ConclusionCHD made a major contribution to the socioeconomic differences in overall mortality. However, there were also important contributions from diseases with less well understood mechanistic links with SEP such as stroke and less-common cancers. Thus, an increased understanding of the mechanisms connecting SEP with more rare causes of disease might be important to be able to more successfully intervene on socioeconomic differences in health.

Social inequalities in mortality: changes in the relative importance of income, education and household size over a 27-year period

The aim of this paper was to measure socio-economic inequalities in mortality over a 27-year period, and estimate the simultaneous effects of education and income adjusted for changing proportions and potential confounders. Census data in 1970, 1980 and 1990 with information about income, educational level and household size were linked to mortality records at the individual level and analysed with absolute mortality rates, Poisson regression (univariate and multivariate) and Relative Index of Inequality (RII). Mortality differences increased between income quartiles and educational groups as well as between singles and non-singles. RII between income quartiles increased from 1.6 to 3.6 for men and 1.7 to 2.7 for women while RII between the educational groups increased from 1.6 to 2.8 for men and 1.5 to 2.1 for women. However, RII derived from the adjusted multivariate regression analysis was 1.8 (men) and 1.9 (women) between the income groups in 1990 and 2.2 (men) and 1.7 (women) between the educational groups. In the 1990s current income was more important than previous income, and the rate ratios (RR) increased for groups dropping into the lowest income quartile between two censuses. Low education and single status have become relatively more important risk factors for mortality over time. Confounder effects of education and household size could partly explain the seemingly large increase in inequalities between income groups. Results may also indicate a stronger reverse causation (poor health causing low income) over time.

Intragenerational mobility and mortality in Oslo: Social selection versus social causation

We investigate the relative importance of the selection and causation hypotheses of social inequalities in mortality, and estimate upper and lower bounds for the gender-specific mobility effects. For all inhabitants of Oslo aged 50–69 years in 1990, we knew their social class in 1960 and 1980 and whether they died between 1990 and 1994. Analysing these data with diagonal reference models, we found those moving upwards in the social hierarchy to have lower mortality rates than their class of origin but higher mortality rates than their class of destination. A corresponding pattern was found for those moving downwards. Thus, social mobility may increase or constrict the social class mortality divide. We estimated the upper bound to the mobility effect to be an increase of 52% for males and 28% for females (situation of no causation) and the lower bound to be a decrease of 24% for males and 21% for females (situation of no selection). Because both selection and causation effects are expected to play a role and to work in opposite directions, the resulting effect of social mobility on the mortality divide may be rather small.

“Fundamental Causes” of Social Inequalities in Mortality: A Test of the Theory

Medicine and epidemiology currently dominate the study of the strong association between socioeconomic status and mortality. Socioeconomic status typically is viewed as a causally irrelevant "confounding variable" or as a less critical variable marking only the beginning of a causal chain in which intervening risk factors are given prominence. Yet the association between socioeconomic status and mortality has persisted despite radical changes in the diseases and risk factors that are presumed to explain it. This suggests that the effect of socioeconomic status on mortality essentially cannot be understood by reductive explanations that focus on current mechanisms. Accordingly, Link and Phelan (1995) proposed that socioeconomic status is a "fundamental cause" of mortality disparities-that socioeconomic disparities endure despite changing mechanisms because socioeconomic status embodies an array of resources, such as money, knowledge, prestige, power, and beneficial social connections, that protect health no matter what mechanisms are relevant at any given time. We identified a situation in which resources should be less helpful in prolonging life, and derived the following prediction from the theory: For less preventable causes of death (for which we know little about prevention or treatment), socioeconomic status will be less strongly associated with mortality than for more preventable causes. We tested this hypothesis with the National Longitudinal Mortality Study, which followed Current Population Survey respondents (N = 370,930) for mortality for nine years. Our hypothesis was supported, lending support to the theory of fundamental causes and more generally to the importance of a sociological approach to the study of socioeconomic disparities in mortality.

Does educational level influence the effects of smoking, alcohol, physical activity, and obesity on mortality? A prospective population study

Objectives: This study aims at examining whether the relation between established risk factors and mortality differs with socioeconomic status as measured by level of education. Methods: A population-based sample of 14,399 women and 16,236 men aged 20 - 93 years from Copenhagen was stratified into three educational levels measured as basic schooling, and the effect of smoking habits, alcohol consumption, physical activity, and body mass index, respectively, on mortality was assessed. Results: Those with the lowest level of education were most frequently heavy smokers, heavy drinkers, physically inactive, and obese. During a mean follow up of 16 years 10,952 subjects died. Compared with subjects with the lowest educational level, women with the highest educational level had a relative risk of 0.80 (95% CI; 0.70 - 0.91), and men of 0.71 (0.65 - 0.78). Heavy smoking compared with never smoking implied a more than twofold increased risk at all three educational levels among both men and women. The relation between alcohol intake and mortality was J-shaped on all three educational levels. There were decreasing risk functions describing the relations between physical activity and mortality on all three strata. Further, subjects who were either very lean or obese had increased risks of death compared with those of normal weight at all educational levels in both genders. Conclusions: The difference in distribution of the main known risk factors may be part of the explanation for the differences in mortality risk. However, these risk factors seem to influence mortality equally at different educational levels. Therefore, social inequalities in mortality do not seem to be explained only by differences in effect of lifestyle risk factors, but are also related to the social rank or unexamined factors within.

Les inégalités sociales de santé en France

Social inequalities in mortality in France are relatively well known, at least for adults. Data are available also on general morbidity (health “less than good”, impairments and disability). Tobacco and alcohol consumption, leisure physical exercise and obesity are also documented in relation with socioeconomic status. The most striking result is the magnitude of social inequalities for adult men, documented for the period 1982-1996. The health expectancy of a men of 35 classified as higher professional is 7.5 years more than that of an unskilled worker of the same age. For women the corresponding difference is 4 years. Those social inequalities in mortality are larger in France than in other European countries. The study of social inequalities in mortality according to causes of deaths shows that some causes of death play an important role; some others, especially cardiovascular diseases, explain a relatively small part of social inequalities, especially if France is compared with northern European countries. Since data are not available yet for the most recent period, it is difficult to know whether those specificities of France are reducing. In the future, new data will be available; they will allow to get a more precise picture of the situation in France, and to develop comparisons with other countries.

Desigualdades en mortalidad en la ciudad de Sevilla

Objectives: To describe social inequalities in mortality in Seville from 1994 to 1998 according to socioeconomic status. Methods: Life expectancy, crude and age-adjusted rates of total mortality as well as mortality by causes and potential years of life lost were estimated using the number of deaths and the population of Seville, aggregated by Basic Health Areas (BHA). BHA were divided in three levels according to the unemployment rate among men. The relative risks of total mortality and mortality by causes were estimated for men and women in each of these levels, using Poisson regression. The unemployment rate of each of the BHA was related to total mortality and to some of its causes. Results: Differences in life expectancy of up to 7.9 years for men and 4.6 years for women were found among BHA. Concerning potential years of life lost, the areas with the highest mortality showed 4.1 times greater mortality in men and 2.6 times greater mortality in women than those with the lowest mortality. Total mortality increased with unemployment rate: the BHA with the highest unemployment rate showed a 15% increase in mortality in men and a 6% increase in that in women than those with the lowest unemployment rate. Among causes of mortality, AIDS showed the greatest inequalities in both men and women. Conclusions: From 1994 to 1998, Seville presented inequalities in total mortality and premature mortality, as well as in mortality by causes per BHA. Inequalities were present in men and women, although they were greater in men. There was a clear association between socioeconomic variables and mortality.

Inequalities in mortality in Seville [Spain

OBJECTIVES To describe social inequalities in mortality in Seville from 1994 to 1998 according to socioeconomic status. METHODS Life expectancy, crude and age-adjusted rates of total mortality as well as mortality by causes and potential years of life lost were estimated using the number of deaths and the population of Seville, aggregated by Basic Health Areas (BHA). BHA were divided in three levels according to the unemployment rate among men. The relative risks of total mortality and mortality by causes were estimated for men and women in each of these levels, using Poisson regression. The unemployment rate of each of the BHA was related to total mortality and to some of its causes. RESULTS Differences in life expectancy of up to 7.9 years for men and 4.6 years for women were found among BHA. Concerning potential years of life lost, the areas with the highest mortality showed 4.1 times greater mortality in men and 2.6 times greater mortality in women than those with the lowest mortality. Total mortality increased with unemployment rate: the BHA with the highest unemployment rate showed a 15% increase in mortality in men and a 6% increase in that in women than those with the lowest unemployment rate. Among causes of mortality, AIDS showed the greatest inequalities in both men and women. CONCLUSIONS From 1994 to 1998, Seville presented inequalities in total mortality and premature mortality, as well as in mortality by causes per BHA. Inequalities were present in men and women, although they were greater in men. There was a clear association between socioeconomic variables and mortality.

Desigualdades en mortalidad en la ciudad de Sevilla

ObjectivesTo describe social inequalities in mortality in Seville from 1994 to 1998 according to socioeconomic status. MethodsLife expectancy, crude and age-adjusted rates of total mortality as well as mortality by causes and potential years of life lost were estimated using the number of deaths and the population of Seville, aggregated by Basic Health Areas (BHA). BHA were divided in three levels according to the unemployment rate among men. The relative risks of total mortality and mortality by causes were estimated for men and women in each of these levels, using Poisson regression. The unemployment rate of each of the BHA was related to total mortality and to some of its causes. ResultsDifferences in life expectancy of up to 7.9 years for men and 4.6 years for women were found among BHA. Concerning potential years of life lost, the areas with the highest mortality showed 4.1 times greater mortality in men and 2.6 times greater mortality in women than those with the lowest mortality. Total mortality increased with unemployment rate: the BHA with the highest unemployment rate showed a 15% increase in mortality in men and a 6% increase in that in women than those with the lowest unemployment rate. Among causes of mortality, AIDS showed the greatest inequalities in both men and women. ConclusionsFrom 1994 to 1998, Seville presented inequalities in total mortality and premature mortality, as well as in mortality by causes per BHA. Inequalities were present in men and women, although they were greater in men. There was a clear association between socioeconomic variables and mortality.

Does educational level influence the effects of smoking, alcohol, physical activity, and obesity on mortality? A prospective population study.

This study aims at examining whether the relation between established risk factors and mortality differs with socioeconomic status as measured by level of education. A population-based sample of 14,399 women and 16,236 men aged 20-93 years from Copenhagen was stratified into three educational levels measured as basic schooling, and the effect of smoking habits, alcohol consumption, physical activity, and body mass index, respectively, on mortality was assessed. Those with the lowest level of education were most frequently heavy smokers, heavy drinkers, physically inactive, and obese. During a mean follow up of 16 years 10,952 subjects died. Compared with subjects with the lowest educational level, women with the highest educational level had a relative risk of 0.80 (95% CI; 0.70-0.91), and men of 0.71 (0.65-0.78). Heavy smoking compared with never smoking implied a more than twofold increased risk at all three educational levels among both men and women. The relation between alcohol intake and mortality was J-shaped on all three educational levels. There were decreasing risk functions describing the relations between physical activity and mortality on all three strata. Further, subjects who were either very lean or obese had increased risks of death compared with those of normal weight at all educational levels in both genders. The difference in distribution of the main known risk factors may be part of the explanation for the differences in mortality risk. However, these risk factors seem to influence mortality equally at different educational levels. Therefore, social inequalities in mortality do not seem to be explained only by differences in effect of lifestyle risk factors, but are also related to the social rank or unexamined factors within.

Association between social class and food consumption in the Italian EPIC population.

The objectives of the present study were to validate the social stratification variables adopted by the European Prospective Investigation into Cancer and Nutrition (EPIC) by comparing them with data from another independent source and to evaluate the geographic and social distribution of eating habits in the Italian EPIC population. The validation of the socioeconomic data collected by the EPIC study was performed with the Turin Longitudinal Study as gold standard and using Cohen's kappa statistics to evaluate the concordance between the studies. We then analyzed food groups based on the consumption of meat and fats, carbohydrates, sweets and alcohol, and on an index of the Mediterranean diet. The standardized scores for each food group were subdivided into quartiles, which were used to compare persons in the extreme quartiles. Analysis of the differences in eating habits by center and by educational level was conducted separately for men and women, calculating the prevalence rate ratios and controlling for age, area of birth and body mass index. Concordance between the two data sources was high for educational level and low for the social-class index based on occupation. Most of the eating habits considered to be potentially harmful (high consumption of meat or fats and alcohol and low consumption of olive oil and fish) were more frequent in Northern than in Southern Italy. These habits were inversely correlated with educational level, especially in the South. A significant improvement in health could be obtained in the Italian population if culturally and socioeconomically disadvantaged individuals were to abandon their diet rich in meat and fats, as done by more advantaged persons. In the absence of preventive interventions specifically addressed to disadvantaged groups, it is likely that social inequalities in mortality and morbidity will increase.