Inequalities In All-cause Mortality Research Articles

Increasing inequalities in mortality among individuals with a foreign background in Sweden

Abstract Background Previous research indicates that migrants in high-income destination countries not only experience a mortality advantage but also demonstrate lower or absent socioeconomic inequalities in mortality compared to the general native population. Yet the extent to which an income mortality gradient may also be evident among the descendants of migrants has been largely unexamined. Existing evidence has revealed that descendants of migrants face mortality risks higher than both migrants and their native-born peers. Methods This study utilizes longitudinal population registries covering the entire registered population of Sweden from 2004 to 2016. The study population comprises individuals aged 25 to 64, employing an open cohort design. Using Poisson regression, we examine the relationship between income rank position and cause-specific mortality among native-origin Swedes and eight nativity groups based on individuals’ country/region of birth, age of migration or parental origin. Results While foreign-born individuals who migrated as adults exhibited lower inequalities in all-cause mortality compared to native-origin Swedes, descendants of immigrants, particularly those with non-European backgrounds, show larger inequalities. Examination of specific causes of mortality revealed that external causes, notably accidents and assaults, account for increased disparities among non-European foreign-born men who migrated during childhood and male descendants of immigrants with non-European backgrounds. Conclusions Income-related inequalities in mortality are less pronounced among migrants compared to the native-born majority population in Sweden and tend to be higher among descendants of migrants, depending on gender and parental origin. The analysis highlights the role of external causes of mortality in shaping these inequalities, indicating that income disadvantages, augmented by a migrant background during upbringing, amplify specific health risks within these groups. Key messages • The study reveals lower mortality inequalities among migrant adults but a higher magnitude of inequalities among male descendants of immigrants, especially with non-European backgrounds. • Income disparities, combined with migrant backgrounds, amplify health risks among descendants of migrants in Sweden, underscoring the need for tackling social inequalities.

Educational inequality in cause-specific mortality among immigrants and their descendants in Sweden

Abstract Introduction Although immigrants in Western countries often face disadvantages and vulnerabilities such as lower socioeconomic status, they tend to exhibit weaker educational gradients in mortality compared to the native majority populations. However, it is unclear how these gradients vary across specific causes of death and whether they persist among second-generation immigrants. Therefore, this study aims to investigate educational inequalities in cause-specific mortality among first- and second-generation immigrants compared to the native ancestral population in Sweden. Data & Methods Individual-level analysis was conducted on Swedish register data from 2004 to 2016, including men and women aged 25 to 64. Poisson regression was used to examine the association between the highest educational degree attained and mortality due to circulatory diseases, neoplasms, external causes, self-harm, drug and alcohol use. Results The findings indicated that first-generation immigrants exhibited significantly lower educational inequality in all causes of death compared to native ancestral Swedes. In contrast, second-generation immigrants showed similar degrees of educational inequality in all-cause mortality and mortality due to neoplasms when compared to ancestral Swedes. However, they displayed more pronounced educational inequalities in mortality from external causes, self-harm, and drug use. Conclusions The results highlight that while first-generation immigrants experience lower educational inequality in the considered causes of death, second-generation immigrants show pronounced educational inequalities in avoidable causes of death. This study emphasizes the importance of considering heterogeneity in educational disparities in immigrant mortality and calls for policy interventions to address educational inequalities in second-generation immigrants. Key messages • When compared to the native majority population, first-generation immigrants in Sweden demonstrate lower educational inequality in mortality, regardless of the underlying cause. • Conversely, second-generation immigrants display larger educational inequalities, particularly for mortality caused by preventable factors.

Can lifestyle factors explain racial and ethnic inequalities in all-cause mortality among US adults?

BackgroundRacial and ethnic inequalities in all-cause mortality exist, and individual-level lifestyle factors have been proposed to contribute to these inequalities. In this study, we evaluate the extent to which the association between race and ethnicity and all-cause mortality can be explained by differences in the exposure and vulnerability to harmful effects of different lifestyle factors.MethodsThe 1997–2014 cross-sectional, annual US National Health Interview Survey (NHIS) linked to the 2015 National Death Index was used. NHIS reported on race and ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx), lifestyle factors (alcohol use, smoking, body mass index, physical activity), and covariates (sex, age, education, marital status, survey year). Causal mediation using an additive hazard and marginal structural approach was used.Results465,073 adults (18–85 years) were followed 8.9 years (SD: 5.3); 49,804 deaths were observed. Relative to White adults, Black adults experienced 21.7 (men; 95%CI: 19.9, 23.5) and 11.5 (women; 95%CI: 10.1, 12.9) additional deaths per 10,000 person-years whereas Hispanic/Latinx women experienced 9.3 (95%CI: 8.1, 10.5) fewer deaths per 10,000 person-years; no statistically significant differences were identified between White and Hispanic/Latinx men. Notably, these differences in mortality were partially explained by both differential exposure and differential vulnerability to the lifestyle factors among Black women, while different effects of individual lifestyle factors canceled each other out among Black men and Hispanic/Latinx women.ConclusionsLifestyle factors provide some explanation for racial and ethnic inequalities in all-cause mortality. Greater attention to structural, life course, healthcare, and other factors is needed to understand determinants of inequalities in mortality and to advance health equity.

National estimates of occupation-related inequalities in all-cause mortality using linked Census-mortality data

ObjectiveThis report aims to provide national estimates of occupation-related inequalities in all-cause mortality for Australian residents aged 25–64 years. MethodData came from the 2016 Census linked to Deaths Registrations, available via the Multi-Agency Data Integration Project. Using negative binomial regression, we estimated age-adjusted relative and absolute inequalities in all-cause mortality rates in the 13 months following Census according to occupation, defined using the Australian and New Zealand Standard Classification of Occupations (eight major groups), using managers as the reference group. ResultsAmong 10.8M people, there were 20,987 deaths. Age-adjusted mortality rates were lowest among managers and professionals and were generally highest for manual occupations, for example, among men, relative risks (RR) for labourers ranged across age groups from 1.44 (95% CI 1.19–1.75, age 54–64) to 2.99 (1.93–4.65, age 25–34); among women, the RR for machine operators and drivers were 3.95 (1.39–11.21 in age 25–24 and 2.73 (1.66–4.49) in age 45–54, but there was relatively little variation by occupation in women aged 35–44 and 55–64. Around one in five deaths (23% for men, 17% for women) were associated with being in an occupation other than manager. ConclusionThese findings highlight that there is benefit in documenting national mortality inequalities according to occupation in addition to other measures of socioeconomic position. They provide further insights into socioeconomic inequalities in mortality. Implications for public healthMethods that aim to reduce mortality for those in manual occupations, particularly among young men, will reduce inequalities and improve population health.

Has COVID-19 increased inequality in mortality by income in the Netherlands?

BackgroundIn the Netherlands in 2020, COVID-19 deaths were more concentrated among individuals with a lower income. At the same time, COVID-19 was a new cause that also displaced some deaths...

Systematic review of the effectiveness of the health inequalities strategy in England between 1999 and 2010

ObjectivesThe purpose of this systematic review is to explore the effectiveness of the National Health Inequality Strategy, which was conducted in England between 1999 and 2010.DesignThree databases (Ovid Medline, Embase...

Social inequalities in all-cause mortality among adults with multimorbidity: a 10-year prospective study of 0.5 million Chinese adults.

Chinese individuals face an increase in multimorbidity, but little is known about the mortality gradients of multimorbid people in different socio-economic groups. This study measures relative and absolute socio-economic inequality in mortality among multimorbid Chinese. For this study, the prospective China Kadoorie Biobank (CKB) enrolled 512712 participants ages 30-79y from 10 areas of China between 25 June 2004 and 15 July 2008. All-cause mortality was accessed with a mean follow-up period of 10y (to 31 December 2016). Associations between multimorbidity and mortality were assessed using Cox proportional hazards models, with the relative index of inequality (RII) and slope index of inequality (SII) in mortality calculated to measure disparities. Mortality risk was highest for those who had not attended formal school and with four or more long-term conditions (LTCs) (hazard ratio 3.11 [95% confidence interval {CI} 2.75 to 3.51]). Relative educational inequality was lower in participants with four or more LTCs (RII 1.92 [95% CI 1.60 to 2.30]), especially in rural areas. Absolute disparities were greater in adults with more LTCs (SII 0.18 [95% CI 0.14 to 0.21] for rural participants with three LTCs). Whereas the relative inequality in all-cause mortality was lower among multimorbid people, absolute inequality was greater among multimorbid men, especially in rural areas.

Socioeconomic Inequalities in All-Cause and Cause-Specific Mortality Among Patients With Osteoarthritis in the Skåne Region of Sweden.

To assess the association between education and all-cause and cause-specific mortality among patients with osteoarthritis (OA) in comparison to an OA-free reference cohort. Using data from the Skåne Healthcare Register, we identified all residents age ≥45 years in the region of Skåne in southern Sweden with doctor-diagnosed OA of peripheral joints between 1998 and 2013 (n=123,993). We created an age- and sex-matched reference cohort without OA diagnosis (n=121,318). Subjects were followed until death, relocation outside Skåne, or the end of 2014. The relative index of inequality (RII) and the slope index of inequality (SII) were estimated by the Cox model and Aalen's additive hazard model, respectively. We found an inverse association between education and mortality. The magnitude of relative inequalities in all-cause mortality were comparable in the OA, with an RII of 1.53 (95% confidence interval [95% CI] 1.46, 1.61), and reference cohorts (RII 1.54 [95% CI 1.47, 1.62]). The absolute inequalities were smaller in the OA cohort (all-cause deaths per 100,000 person-years, SII 937 [95% CI 811, 1,063]) compared with the reference cohort (SII 1,265 [95% CI 1,109, 1,421]). Cardiovascular mortality contributed more to the absolute inequalities in the OA cohort than in the reference cohort (60.1% versus 48.1%) while the opposite was observed for cancer mortality (8.5% versus 22.3%). We found higher all-cause and cause-specific mortality in OA patients with lower education. The observed inequalities in the OA cohort reflect the inequalities in the population at large. The greater burden of cardiovascular diseases in OA patients suggests that proper management of cardiovascular risk factors in OA patients is important.

The Role of Epigenetic Clocks in Explaining Educational Inequalities in Mortality: A Multicohort Study and Meta-analysis.

Educational inequalities in all-cause mortality have been observed for decades. However, the underlying biological mechanisms are not well known. We aimed to assess the role of DNA methylation changes in blood captured by epigenetic clocks in explaining these inequalities. Data were from 8 prospective population-based cohort studies, representing 13 021 participants. First, educational inequalities and their portion explained by Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, and DNAmGrimAge epigenetic clocks were assessed in each cohort via counterfactual-based mediation models, on both absolute (hazard difference) and relative (hazard ratio) scales, and by sex. Second, estimates from each cohort were pooled through a random effect meta-analysis model. Men with low education had excess mortality from all causes of 57 deaths per 10 000 person-years (95% confidence interval [CI]: 38, 76) compared with their more advantaged counterparts. For women, the excess mortality was 4 deaths per 10 000 person-years (95% CI: -11, 19). On the relative scale, educational inequalities corresponded to hazard ratios of 1.33 (95% CI: 1.12, 1.57) for men and 1.15 (95% CI: 0.96, 1.37) for women. DNAmGrimAge accounted for the largest proportion, approximately 50%, of the educational inequalities for men, while the proportion was negligible for women. Most of this mediation was explained by differential effects of unhealthy lifestyles and morbidities of the World Health Organization (WHO) risk factors for premature mortality. These results support DNA methylation-based epigenetic aging as a signature of educational inequalities in life expectancy emphasizing the need for policies to address the unequal social distribution of these WHO risk factors.

Alcohol and educational inequalities: Hazardous drinking prevalence and all-cause mortality by hazardous drinking group in people aged 50 and older in Europe

Background We examined educational inequalities in hazardous drinking prevalence among individuals aged 50 or more in 14 European countries, and explored educational inequalities in mortality in hazardous drinkers in European regions. Methods: We analyzed data from waves 4, 5 and 6 of the Survey of Health Ageing and Retirement in Europe (SHARE). We estimated age-standardized hazardous drinking prevalence, and prevalence ratios (PR) of hazardous drinking by country and educational level using Poisson regression models with robust variance. We estimated the relative index of inequality (RII) for all-cause mortality among hazardous drinkers and non-hazardous drinkers using Cox proportional hazards regression models and for each region (North, South, East and West). Results: In men, educational inequalities in hazardous drinking were not observed (PRmedium = 1.09 [95%CI: 0.98–1.21] and PRhigh = 0.99 [95%CI: 0.88–1.10], ref. low), while in they were observed in women, having the highest hazardous drinking prevalence in the highest educational levels (PRmedium = 1.28 [95%CI: 1.15–1.42] and PRhigh = 1.53 [95%CI: 1.36–1.72]). Overall, the Relative Index of Inequality (RII) in all-cause mortality among hazardous drinkers was 1.12 [95%CI: 1.03–1.22] among men and 1.10 [95%CI: 0.97–1.25] among women. Educational inequalities among hazardous drinkers were observed in Eastern Europe for both men (RIIhazardous = 1.21 [95%CI: 1.01–1.45]) and women (RIIhazardous = 1.46 [95%CI: 1.13–1.87]). Educational inequalities in mortality among non-hazardous drinkers were observed in Southern, Western and Eastern Europe among men, and in Eastern Europe among women. Conclusions: Higher educational attainment is positively associated with hazardous drinking prevalence among women, but not among men in most of the analyzed European countries. Clear educational inequalities in mortality among hazardous drinkers were only observed in Eastern Europe. Further research on the associations between alcohol use and inequalities in all-cause mortality in different regions is needed.

Educational differences in alcohol-related mortality and their impact on life expectancy and lifespan variation in Spain (2016–2018): a cross-sectional analysis using multiple causes of death

BackgroundSocioeconomic inequalities in alcohol-related mortality in Spain exists, and are postulated to contribute to inequalities in all-cause mortality. We aim to assess absolute and relative educational inequalities in alcohol-related mortality,...

Deaths of despair: cause-specific mortality and socioeconomic inequalities in cause-specific mortality among young men in Scotland

BackgroundIncreasing mortality among men from drugs, alcohol and suicides is a growing public health concern in many countries. Collectively known as “deaths of despair”, they are seen to stem from unprecedented economic pressures and a breakdown in social support structures.MethodsWe use high-quality population wide Scottish data to calculate directly age-standardized mortality rates for men aged 15–44 between 1980 and 2018 for 15 leading causes of mortality. Absolute and relative inequalities in mortality by cause are calculated using small-area deprivation and the slope and relative indices of inequality (SII and RIIL) for the years 2001–2018.ResultsSince 1980 there have been only small reductions in mortality among men aged 15–44 in Scotland. In that period drug-related deaths have increased from 1.2 (95% CI 0.7–1.4) to 44.9 (95% CI 42.5–47.4) deaths per 100,000 and are now the leading cause of mortality. Between 2001 and 2018 there have been small reductions in absolute but not in relative inequalities in all-cause mortality. However, absolute inequalities in mortality from drugs have doubled from SII = 66.6 (95% CI 61.5–70.9) in 2001–2003 to SII = 120.0 (95% CI 113.3–126.8) in 2016–2018. Drugs are the main contributor to inequalities in mortality, and together with alcohol harm and suicides make up 65% of absolute inequalities in mortality.ConclusionsContrary to the substantial reductions in mortality across all ages in the past decades, deaths among young men are increasing from preventable causes. Attempts to reduce external causes of mortality have focused on a single cause of death and not been effective in reducing mortality or inequalities in mortality from external causes in the long-run. To reduce deaths of despair, action should be taken to address social determinants of health and reduce socioeconomic inequalities.

Contribution of psychosocial factors to socioeconomic inequalities in mortality among older Australian men: a population-based cohort study

BackgroundAmong older people, the extent to which psychosocial factors explain socioeconomic inequalities in mortality is debated. We aimed to investigate the potential mediating effect of psychosocial factors on socioeconomic inequalities in mortality.MethodsWe used data from a prospective population-based cohort (the Concord Health and Ageing in Men Project; baseline recruitment in 2005–2007), in Sydney, Australia. The main outcomes were all-cause and cause-specific mortality. Socioeconomic status (SES; educational attainment, occupational position, source of income, housing tenure, and a cumulative SES score) was assessed at baseline. Measures of structural and functional social support, as well as depressive and anxiety symptoms were assessed three times during follow-ups. Associations were quantified using Cox regression. Mediation was calculated using “change-in-estimate method”.Results1522 men (mean age at baseline: 77·4 ± 5·5 years) were included in the analyses with a mean (SD) follow-up time of 9·0 (3·6) years for all-cause and 8·0 (2·8) years for cause-specific mortality. At baseline, psychosocial measures displayed marked social patterning. Being unmarried, living alone, low social interactions, and elevated depressive symptoms were associated with higher risk of all-cause and cardiovascular disease (CVD) mortality. Psychosocial factors explained 35% of SES inequalities in all-cause mortality, 29% in CVD mortality, 12% in cancer mortality, and 39% in non-CVD, non-cancer mortality.ConclusionPsychosocial factors may account for up to one-third of SES inequalities in deaths from all and specific causes (except cancer mortality). Our findings suggest that interventional studies targeting social relationships and/or psychological distress in older men aiming to reduce socioeconomic inequalities in mortality are warranted.

Corrigendum to: Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach.

Corrigendum to: Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach.

Effect of the recent economic crisis on socioeconomic inequalities in mortality in nine urban areas in Europe

ObjectiveTo analyse socioeconomic inequalities in all-cause mortality among men and women in nine European urban areas during the recent economic crisis, and to compare the results to those from two periods before the crisis. MethodThis is an ecological study of trends based on three time periods (2000-2003, 2004-2008 and 2009-2014). The units of analysis were the small areas of nine European urban areas. We used a composite deprivation index as a socioeconomic indicator, along with other single indicators. As a mortality indicator, we used the smoothed standardized mortality ratio, calculated using the hierarchical Bayesian model proposed by Besag, York and Mollié. To analyse the evolution of socioeconomic inequalities, we fitted an ecological regression model that included the socioeconomic indicator, the period of time, and the interaction between these terms. ResultsWe observed significant inequalities in mortality among men for almost all the socioeconomic indicators, periods, and urban areas studied. However, no significant changes occurred during the period of the economic crisis. While inequalities among women were less common, there was a statistically significant increase in inequality during the crisis period in terms of unemployment and the deprivation index in Prague and Stockholm, respectively. ConclusionsFuture analyses should also consider time-lag in the effect of crises on mortality and specific causes of death, and differential effects between genders.

Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach.

BackgroundSocio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors.MethodsData were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education.ResultsLower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest.ConclusionsThese observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities.

Educational inequalities in all-cause and cause-specific mortality among people with gout: a register-based matched cohort study in southern Sweden

BackgroundGout is the most common inflammatory arthritis with a rising prevalence around the globe. While educational inequalities in incidence and prevalence of gout have been reported, no previous study investigated educational inequality in mortality among people with gout. The aim of this study was to assess absolute and relative educational inequalities in all-cause and cause-specific mortality among people with gout in comparison with an age- and sex-matched cohort free of gout in southern Sweden.MethodsWe identified all residents aged ≥30 years of Skåne region with doctor-diagnosed gout (ICD-10 code M10, n = 24,877) during 1998–2013 and up to 4 randomly selected age- and sex-matched comparators free of gout (reference cohort, n = 99,504). These were followed until death, emigration, or end of 2014. We used additive hazards models and Cox regression adjusted for age, sex, marital status, and country of birth to estimate slope and relative indices of inequality (SII/RII). Three cause-of-death attribution approaches were considered for RII estimation: “underlying cause”, “any mention”, and “weighted multiple-cause”.ResultsGout patients with the lowest education had 1547 (95% CI: 1001, 2092) more deaths per 100,000 person-years compared with those with the highest education. These absolute inequalities were larger than in the reference population (1255, 95% CI: 1038, 1472). While the contribution of cardiovascular (cancer) mortality to these absolute inequalities was greater (smaller) in men with gout than those without, the opposite was seen among women. Relative inequality in all-cause mortality was smaller in gout (RII 1.29 [1.18, 1.41]) than in the reference population (1.46 [1.38, 1.53]). The weighted multiple-cause approach generally led to larger RIIs than the underlying cause approach.ConclusionsOur register-based matched cohort study showed that low level of education was associated with increased mortality among gout patients. Although the magnitude of relative inequality was smaller in people with gout compared with those without, the absolute inequalities were greater reflecting a major mortality burden among those with lower education.

Education inequalities in adult all-cause mortality: first national data for Australia using linked census and mortality data.

BackgroundNational linked mortality and census data have not previously been available for Australia. We estimated education-based mortality inequalities from linked census and mortality data that are suitable for international comparisons.MethodsWe used the Australian Bureau of Statistics Death Registrations to Census file, with data on deaths (2011–2012) linked probabilistically to census data (linkage rate 81%). To assess validity, we compared mortality rates by age group (25–44, 45–64, 65–84 years), sex and area-inequality measures to those based on complete death registration data. We used negative binomial regression to quantify inequalities in all-cause mortality in relation to five levels of education [‘Bachelor degree or higher’ (highest) to ‘no Year 12 and no post-secondary qualification’ (lowest)], separately by sex and age group, adjusting for single year of age and correcting for linkage bias and missing education data.ResultsMortality rates and area-based inequality estimates were comparable to published national estimates. Men aged 25–84 years with the lowest education had age-adjusted mortality rates 2.20 [95% confidence interval (CI): 2.08‒2.33] times those of men with the highest education. Among women, the rate ratio was 1.64 (1.55‒1.74). Rate ratios were 3.87 (3.38‒4.44) in men and 2.57 (2.15‒3.07) in women aged 25–44 years, decreasing to 1.68 (1.60‒1.76) in men and 1.44 (1.36‒1.53) in women aged 65–84 years. Absolute education inequalities increased with age. One in three to four deaths (31%) was associated with less than Bachelor level education.ConclusionsThese linked national data enabled valid estimates of education inequality in mortality suitable for international comparisons. The magnitude of relative inequality is substantial and similar to that reported for other high-income countries.

Educational inequalities in all-cause and cause-specific mortality among patients with osteoarthritis in southern Sweden

Purpose: To assess the association between socioeconomic status, measured by education, and all-cause and cause-specific mortality among patients with osteoarthritis (OA) in southern Sweden. Methods: A register-based open cohort study was conducted. The Region of Skåne, which is the southeast part of Sweden, was the geographical area of interest. All residents aged ≥45 years in the region with doctor-diagnosed OA (ICD-10 codes: M15-M19) between the 1st of January 1998 and the 31st of December 2013 (n=123,981) were followed until death, relocation outside the Skåne region, or the end of 2014, whichever occurred first. Individual-level data was obtained from the Skåne Healthcare Register (SHR), Statistics Sweden and the National Board of Health and Welfare´s Cause of Death Register. The Slope index of inequality (SII) and the Relative index of inequality (RII), which measure the absolute and relative educational inequality, respectively, were estimated. The Aalen´s additive hazard model was used to estimate the SII and Cox model was used to estimate the RII. Two cause-of-death attribution approaches were used to estimate the RIIs: “underlying cause” and “weighted multiple-cause”. All estimates were adjusted for age, sex, marital status and whether the subject had a Swedish or foreign background. Results: During a mean follow-up of 7.1 years, we identified 24,493 deaths. Age-standardized all-cause mortality rates increased as the educational level decreased (Figure 1). The RII showed that all-cause mortality rate was 1.54 (95% CI: 1.47, 1.62) times higher in low vs. high educated OA patients (Table 1). Among causes of death, the greatest relative inequality was seen in deaths caused by diseases in circulatory system (RII 1.88, 95% CI: 1.73, 2.04). Higher mortality rates were observed in low educated for all causes except for mental and behavioural disorders & diseases of the nervous system. Regarding the results for the subgroups based on sex, age and OA-type, there were a higher all-cause mortality in low educated patients. A higher cause-specific mortality in favour of high educated was also generally seen in these groups.Table 1Relative index of inequality (RII) and slope index of inequality (SII) in mortality.Disease group (ICD-10 codes)All (≥45 years)SexesAge groupsOA-typeMenWomen45-74 years≥75 yearsKnee OA (M17)Hip OA (M16)RIISII*RIISII*RIISII*RIISII*RIISII*RIISII*RIISII*All-cause1.54 ( 1.47, 1.62)904 (779, 1030)1.55 (1.44, 1.67)1270 (1060, 1480)1.54 (1.44, 1.65)924 (767, 1080)1.72 (1.59, 1.86)700 (600, 800)1.44 (1.35, 1.54)1350 (1050, 1650)1.52 (1.41, 1.64)874 (680, 1070)1.53 (1.39, 1.67)1300 (990, 1610)Diseases of the circulatory system (I00-I99)1.88 (1.73, 2.04)555 (475, 635)1.85 (1.64, 2.08)732 (596, 868)1.86 (1.67, 2.08)542 (443, 641)2.25 (1.94, 2.60)325 (269, 381)1.68 (1.53, 1.85)981 (775, 1190)1.78 (1.58, 2.01)515 (389, 641)1.90 (1.64, 2.19)840 (642, 1040)Malignant neoplasms (C00-C97)1.20 (1.09, 1.32)77.6 (11.7, 143)1.30 (1.13, 1.49)193 (80.7, 305)1.19 (1.04, 1.37)86 (5.1, 167)1.27 (1.12, 1.45)127 (64.5, 190)1.11 (0.96, 1.29)-4.7 (-136, 127)1.19 (1.02, 1.39)66.3 (-32.3, 165)1.21 (1.01, 1.45)137 (-21.6, 296)Mental and behavioural disorders (F00-F99) & Diseases of the nervous system (G00-G99)1.12 (0.93, 1.34)4.8 (-30.8, 40.5)0.98 (0.71, 1.35)-6.7 (-59.5, 46)1.17 (0.93, 1.47)7.6 (-40.3, 55.4)1.47 (1.04, 2.08)24.7 (0.59, 48.8)0.97 (0.78, 1.20)-31.5 (-123, 60.4)1.14 (0.85, 1.52)0.8 (-54.1, 55.6)0.95 (0.69, 1.32)-38.3 (-125, 48.7)Diseases of the respiratory system (J00-J99)1.58 (1.28, 1.93)53 (20.3, 85.7)1.70 (1.25, 2.32)101 (44, 158)1.54 (1.16 2.06)55.1 (15.5, 94.7)2.45 (1.73, 3.48)63.9 (40.2, 87.6)1.30 (1.01, 1.68)42.9 (-38.4, 124)1.66 (1.18, 2.34)51.5 (4.7, 98.3)1.48 (1.01, 2.19)63.6 (-13.4, 141)Other causes1.70 (1.52, 1.91)234 (178, 290)1.55 (1.31, 1.84)258 (164, 352)1.81 (1.55, 2.12)258 (187, 329)1.93 (1.61, 2.32)163 (119, 207)1.60 (1.38, 1.85)375 (239, 511)1.69 (1.42, 2.01)228 (141, 315)1.68 (1.35, 2.09)327 (191, 463)* per 100,000 person-years. 95 % Confidence intervals are shown in parenthesis. Models were adjusted for sex, marital status, and background. Open table in a new tab There were 904 (95% CI: 779, 1030) more all-cause deaths per 100,000 person-years in the low educated compared with high educated OA patients (Table 1). Diseases of the circulatory system and mental and behavioural disorders & diseases of the nervous system contributed the most and least, respectively, to the absolute inequalities in all-cause mortality in the whole study population and all subgroups (Table 2).Table 2Contribution (%) of specific causes of death to the absolute inequality in mortality.Disease group (ICD-10 codes)All (≥45years)SexesAge groupsOA-typeDiseases of the circulatory system (I00-I99)MenWomen45-74 years≥75 yearsKneeHipDiseases of the circulatory system (I00-I99)60.057.357.146.272.059.863.2Malignant neoplasms (C00-C97)8.415.19.118.1-0.37.710.3Mental and behavioural disorders (F00-F99) & Diseases of the nervous system (G00-G99)0.5-0.50.83.5-2.30.1-2.9Diseases of the respiratory system (J00-J99)5.77.95.89.13.16.04.8Other causes25.320.227.223.227.526.524.6Total mortality99.9100.0100.0100.1100.0100.1100.0 Open table in a new tab When we used the weighted multiple-cause approach, the RII for diseases of the circulatory system increased, while the RII for malignant neoplasms decreased. In addition, the RII for respiratory system was no longer statistically significant when the weighted multiple-cause approach was used. Conclusions: We found an inverse association between educational level and all-cause mortality in OA-patients. The cause-of-death attribution approaches generally led to similar conclusion. These findings suggest that educational level is an important factor to consider in OA-patients, especially if they suffer from cardiovascular diseases. Further studies are required to explain the inequality observed in our study.

Quantifying the impact of reducing socioeconomic inequalities in modifiable risk factors on mortality and mortality inequalities in South Korea.

We quantified the impact of reducing socioeconomic inequalities in risk factors on mortality and mortality inequalities in South Korea. The mortality risk function from the 12-year mortality follow-up data of the National Health Insurance Service-National Health Screening Cohort, the prevalence of major risk factors from the Korea National Health and Nutrition Examination Survey 2013-2015, and the Health Plan 2020 (HP2020) goals for major risk factors were used to estimate the magnitude of reduction in mortality inequalities by changing the magnitude of income-based inequalities in risk factors in various scenarios under gender-specific models among participants aged 40-79years. The greatest reduction in absolute and relative inequalities in mortality would occur if the low-income group achieved the HP2020 goals earlier than the high-income group. A 10-20% reduction in all-cause mortality inequalities was expected if absolute gaps between income groups in risk factors were halved. With the practical goal halving the socioeconomic gaps in modifiable risk factors, reducing inequalities in all-cause mortality by 10-20% would be possible. Further reduction in mortality inequalities would need more aggressive policies on social determinants of health.