Educational Inequalities In Health Research Articles

Enabling the examination of long-term mortality trends by educational level for England and Wales in a time-consistent and internationally comparable manner

BackgroundStudying long-term trends in educational inequalities in health is important for monitoring and policy evaluation. Data issues regarding the allocation of people to educational groups hamper the study and international comparison of educational inequalities in mortality. For the UK, this has been acknowledged, but no satisfactory solution has been proposed.ObjectiveTo enable the examination of long-term mortality trends by educational level for England and Wales (E&W) in a time-consistent and internationally comparable manner, we propose and implement an approach to deal with the data issues regarding mortality data by educational level.MethodsWe employed 10-year follow-ups of individuals aged 20+ from the Office for National Statistics Longitudinal Study (ONS-LS), which include education information from each decennial census (1971–2011) linked to individual death records, for a 1% representative sample of the E&W population. We assigned the individual cohort data to single ages and calendar years, and subsequently obtained aggregate all-cause mortality data by education, sex, age (30+), and year (1972–2017). Our data adjustment approach optimised the available education information at the individual level, and adjusts—at the aggregate level—for trend discontinuities related to the identified data issues, and for differences with country-level mortality data for the total population.ResultsThe approach resulted in (1) a time-consistent and internationally comparable categorisation of educational attainment into the low, middle, and high educated; (2) the adjustment of identified data-quality related discontinuities in the trends over time in the share of personyears and deaths by educational level, and in the crude and the age-standardised death rate by and across educational levels; (3) complete mortality data by education for ONS-LS members aged 30+ in 1972–2017 which aligns with country-level mortality data for the total population; and (4) the estimation of inequality measures using established methods. For those aged 30+ , both absolute and relative educational inequalities in mortality first increased and subsequently decreased.ConclusionWe obtained additional insights into long-term trends in educational inequalities in mortality in E&W, and illustrated the potential effects of different data issues. We recommend the use of (part of) the proposed approach in other contexts.

Educational inequalities in self-rated health and their mediators in late adulthood: Comparison of China and Japan.

Education has an impact on health, but the magnitude of the impact may vary across countries. This cross-sectional study compared educational inequalities in health and their mediators in late adulthood between China and Japan, which both face rapid population aging. We studied the same age cohort (63-72 years) based on two nationwide population-based surveys in 2018: the China Health and Retirement Longitudinal Study (N = 5,277) and Japan's Longitudinal Survey of Middle-Age and Elderly Persons (N = 20,001). The relative index of inequality (RII) in education was used to measure educational inequality in self-rated health (SRH). We then examined the extent to which income, smoking, leisure-time physical activity, and social participation mediated educational inequalities in SRH. In both countries, a lower educational level was associated with a higher risk of poor SRH; in China, however, the gradient was flatter. In China, the RII of education was 1.69 (95% confidence interval [CI]: 1.20-2.39) for men and 1.47 (95% CI: 1.06-2.05) for women. In Japan, meanwhile, RII was 2.70 (95% CI: 2.21-3.28) for men and 2.60 (95% CI: 2.13-3.18) for women. Our mediation analysis based on logistic regression models with bootstrapping also found that social participation was a key mediator of educational inequalities in health in both countries. In all, the results underscore that one's relative position in educational inequalities is a reliable predictor of subjective health in late adulthood in both China and Japan.

Educational disparities in disability-free life expectancy across Europe: A focus on the East-West gaps from a gender perspective

Education plays a crucial role in shaping the health outcomes of adults. This study examines the relationship between educational attainment and health across Europe. Using data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we estimate educational inequalities in disability-free life expectancy (DFLE) by gender in seven Western European (2004–2019) and three Central and Eastern European (CEE) (2010–2019) countries. We exploit a novel approach that combines the Sullivan method and multivariate life tables to calculate DFLE using SHARE data. We find that educational differences in DFLE favoring the better-educated exist in both CEE and Western European countries, but also that the differences across countries are more pronounced among the low-educated. While the absolute gaps in DFLE between low- and high-educated individuals in CEE and Western European countries are similar, the educational disparities in DFLE impose a more significant burden on the CEE populations due to their overall lower life expectancy. Educational inequalities are larger among women than among men in CEE countries, while the results for Western European countries are mixed. Our findings further highlight the important role of the institutional context in mitigating or exacerbating educational inequalities in health.

Differences in the Mediating Role of HL in Socioeconomic Inequalities in Health Across Age Groups: Results from the Dutch Doetinchem Cohort Study.

Although it is known that health literacy (HL) plays an explanatory role in educational inequalities in health, it is unknown whether this role varies across age groups. The purpose of this study was to investigate whether the mediating role of HL in educational inequalities in four health outcomes varies across age groups: age 46 to 58 years, age 59 to 71 years, and age 72 to 84 years. We used data from the Dutch Doetinchem Cohort Study, which included 3,448 participants. We included years of education as predictor, chronic illness prevalence and incidence, mental and self-perceived health as outcomes, and HL, based on self-report, as mediator. We used multiple-group mediation models to compare indirect effects across age groups. In the complete sample without age stratification, HL partly mediated the effect of education on all health outcomes except for incidence of chronic diseases. These indirect effect estimates were larger for subjective (self-perceived health, proportion mediated [PM] = 37%, and mental health, PM = 37%) than for objective health outcomes (prevalence of chronic disease, PM = 17%). For the prevalence of chronic disease, the indirect effect estimate was significantly larger among individuals age 46 to 58 years compared to individuals age 59 to 71 years and for incidence of chronic disease also compared to individuals age 72 to 84 years. All other indirect effect estimates did not differ significantly between age groups. Using an alternative cut-off point for HL or adjusting for cognitive functioning did not meaningfully change the results. Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years. Future studies may investigate the benefits of starting to intervene on HL from a younger age but means to improve HL may also benefit the subjective health of older adults with lower education. [HLRP: HL Research and Practice. 2023;7(1):e26-e38.] Plain Language Summary: This study examined age-group differences in the mediating role of HL in the relationship between education and health. Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years compared to individuals age 59 to 71 years and individuals age 72 to 84 years.

Trends in absolute and relative educational inequalities in health during times of labour market restructuring in coastal areas: The HUNT Study, Norway

BackgroundRestructuring labour markets offers natural population-level experiments of great social epidemiological interest. Many coastal areas have endured substantial restructuring of their local labour markets following declines in small-scale fishing and transitions to new employment opportunities. It is unknown how educational inequalities in health have developed in formerly fishery-dependent communities during such restructuring. In this study, we compare trends in social inequalities in health in Norwegian coastal areas with adjacent geographical areas between 1984 and 2019. MethodsWe used cross-sectional population-based data from the Trøndelag Health Study (HUNT), collected four times: HUNT1 (1984–86), HUNT2 (1995–97), HUNT3 (2006–08) and HUNT4 (2017–19). Adults above 30 years of age were included. Using Poisson regression, we calculated absolute and relative educational inequalities in self-rated health, using slope (SII) and relative (RII) indices of inequality. ResultsTrends in absolute and relative inequalities in rural coastal health were generally more favourable than in adjacent geographical areas. We found a statistically significant trend of declining relative educational inequalities in self-rated health in the rural coastal population from HUNT1 to HUNT4. Absolute inequalities overall increased from HUNT1 to HUNT4, although a declining trend followed HUNT2. Nonetheless, the rural coastal population exhibited the highest prevalence of poor self-rated health across the four decades. ConclusionsAlthough absolute educational inequalities in self-rated health widened in all geographical areas, the smallest increase was in rural coastal areas. Relative educational inequalities narrowed in this rural coastal population. Considering the concurrent processes of large-scale investments in the Norwegian public sector and welfare schemes, increased fishing fleet safety, and employment opportunities in aquaculture, our findings do not suggest that potential positive effects on public health of this restructuring have benefitted inhabitants with higher educational attainment more than inhabitants with lower educational attainment in this rural coastal population.

Gender and socioeconomic inequalities in health and wellbeing across age in France and Switzerland

There is increasing evidence that wellbeing is unequally distributed across sociodemographicgroups in contemporary societies. However, less is known about thedivergence across social groups of trajectories of wellbeing across age groups.This issue is of great relevance in contexts characterised by changing populationstructures and growing imbalances across and within generations, and in whichensuring that everyone has the opportunity to have a happy and healthy life courseis a primary welfare goal. In this study, we investigate wellbeing trends in Franceand Switzerland across age, gender, and socioeconomic status groups. We use twohousehold surveys (the Sant´e et Itin´eraires Professionnels and the Swiss HouseholdPanel) to compare the unfolding inequalities in health and wellbeing across agegroups in two rich countries. We view wellbeing as multidimensional, followingthe literature highlighting the importance of considering different dimensions andmeasures of wellbeing. Thus, we investigate a number of outcomes, includingdifferent measures of physical and mental health, as well as of relational wellbeing,using a linear regression model and a linear probability model. Our findings showinteresting country and dimension-specific heterogeneities in the development ofhealth and wellbeing over age. While our results indicate that there are gender andeducational inequalities in both Switzerland and France, and that gender inequalitiesin mental health accumulate with age in both countries, we also find that educationalinequalities in health and wellbeing remain rather stable across age groups.

Life stage-specific trends in educational inequalities in health-related quality of life and self-rated health between 2002 and 2016 in Germany: findings from the German Socio-Economic Panel Study (GSOEP)

ObjectivesWhile evidence suggests persisting health inequalities, research on whether these trends may vary according to different stages of life has rarely been considered. Against this backdrop, we analysed life stage-specific...

Health inequalities in Eastern Europe. Does the role of the welfare regime differ from Western Europe?

When we study the impact of social policy on health inequalities, we find that most research is based on Western European countries. This study expands the geographical focus by including post-communist countries from Eastern Europe, Russia, and the Caucasus. The 2008/2009 round of the European Values Study (EVS) provides a unique opportunity for this analysis since it covers 23 post-communist countries and 20 Western European countries. The study uses multilevel cross-sectional analyses to examine the moderating role of welfare regimes on socioeconomic health inequalities. Many reviews claim that the results for welfare systems and health inequalities are inconsistent. However, since the studies selected for the reviews are mainly focused on Western Europe-only a few include Central Eastern European countries-we still need to find out how welfare regimes in post-communist countries moderate the link between socioeconomic status and health. A cluster analysis based on 13 social and economic indicators generates 4 welfare clusters within the post-communist countries which are used for further analyses. Regarding the achievements of the communist countries in compulsory secondary education, the expectation is that the educational health inequalities differ between Eastern and Western Europe. The multilevel analyses confirm that social gradients in health related to education and income exist in both Western and Eastern Europe. However, while income-related health inequalities are similar, educational health inequalities are most pronounced in the welfare cluster of the EU Member States of Central and Eastern Europe.

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach.

Objective:Using a novel mediation method that presents unbiased results even in the presence of exposure–mediator interactions, this study estimated the extent to which working conditions and health behaviors contribute to educational inequalities in self-rated health in the workforce.Methods:Respondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 16 countries were selected, aged 50–64 years, in paid employment at baseline and with information on education and self-rated health (N=15 028). Education, health behaviors [including body mass index (BMI)] and working conditions were measured at baseline and self-rated health at baseline and two-year follow-up. Causal mediation analysis with inverse odds weighting was used to estimate the total effect of education on self-rated health, decomposed into a natural direct effect (NDE) and natural indirect effect (NIE).Results:Lower educated workers were more likely to perceive their health as poor than higher educated workers [relative risk (RR) 1.48, 95% confidence interval (CI) 1.37–1.60]. They were also more likely to have unfavorable working conditions and unhealthy behaviors, except for alcohol consumption. When all working conditions were included, the remaining NDE was RR 1.30 (95% CI 1.15–1.44). When BMI and health behaviors were included, the remaining NDE was RR 1.40 (95% CI 1.27–1.54). Working conditions explained 38% and health behaviors and BMI explained 16% of educational inequalities in health. Including all mediators explained 64% of educational inequalities in self-rated health.Conclusions:Working conditions and health behaviors explain over half of the educational inequalities in self-rated health. To reduce health inequalities, improving working conditions seems to be more important than introducing health promotion programs in the workforce.

Educational Inequalities in Self-Rated Health in Europe and South Korea.

While numerous comparative works on the magnitude of health inequalities in Europe have been conducted, there is a paucity of research that encompasses non-European nations such as Asian countries. This study was conducted to compare Europe and Korea in terms of educational health inequalities, with poor self-rated health (SRH) as the outcome variable. The European Union Statistics on Income and Living Conditions and the Korea National Health and Nutrition Examination Survey in 2017 were used (31 countries). Adult men and women aged 20+ years were included (207,245 men and 238,007 women). The age-standardized, sex-specific prevalence of poor SRH by educational level was computed. The slope index of inequality (SII) and relative index of inequality (RII) were calculated. The prevalence of poor SRH was higher in Korea than in other countries for both low/middle- and highly educated individuals. Among highly educated Koreans, the proportion of less healthy women was higher than that of less healthy men. Korea’s SII was the highest for men (15.7%) and the ninth-highest for women (10.4%). In contrast, Korea’s RII was the third-lowest for men (3.27), and the lowest among women (1.98). This high-SII–low-RII mix seems to have been generated by the high level of baseline poor SRH.

Educational inequalities in health after work exit: the role of work characteristics

BackgroundEducational inequalities in health have been widely reported. A low educational level is associated with more adverse working conditions. Working conditions, in turn, are associated with health and there is evidence that this association remains after work exit. Because many countries are raising the statutory retirement age, lower educated workers have to spend more years working under adverse conditions. Therefore, educational health inequalities may increase in the future. This study examined (1) whether there were educational differences over time in health after work exit and (2) whether work characteristics mediate these educational inequalities in health.MethodsData from five prospective cohort studies were used: The Netherlands (Longitudinal Aging Study Amsterdam), Denmark (Danish Longitudinal Study of Aging), England (English Longitudinal Study of Ageing), Germany (German Aging Study), and Finland (Finnish Longitudinal Study on Municipal Employees). In each dataset we used Generalized Estimating Equations to examine the relationship between education and self-rated health after work exit with a maximum follow-up of 15 years and possible mediation of work characteristics, including physical demands, psychosocial demands, autonomy, and variation in activities.ResultsThe low educated reported significantly poorer health after work exit than the higher educated. Lower educated workers had a higher risk of high physical demands and a lower risk of high psychosocial demands, high variation in tasks, and high autonomy at work, compared to higher educated workers. These work characteristics were found to be mediators of the relationship between education and health after work exit, consistent across countries.ConclusionEducational inequalities in health are still present after work exit. If workers are to spend an extended part of their lives at work due to an increase in the statutory retirement age, these health inequalities may increase. Improving working conditions will likely reduce these inequalities in health.

Do comprehensive school reforms impact the health of early school leavers? Results of a comparative difference-in-difference design

In the current article, we examine whether and how reforms in tracking age affect educational inequalities in health among people between the ages of 25–75 years. Particular attention is paid to the health consequences for early school leavers. The study combines data from the European Social Survey (2002–2016) on 21 countries with country-cohort information on education policies. Moreover, a difference-in-difference design is used, which takes advantage of both the cross-national and cross-temporal variability in the implementation of comprehensive schooling reforms. The results reveal statistically significant, but very small effects of de-tracking policies on people's health. That is, comprehensive education leads to slight improvements in health among people who have attained upper secondary or tertiary education, but these improvements are achieved at the expense of the health of those with the lowest levels of education. Our study should encourage future research to further explore the institutional impact of educational systems on the health of individuals.

Educational inequalities in self-rated health and social relationships - analyses based on the European Social Survey 2002-2016.

While there is evidence for educational health inequalities in Europe, studies on time trends and on the explanatory contribution of social relations are less consistent. It has been shown that the use of welfare state typologies can be helpful to examine health inequalities in a comparative perspective. Against this background, analyses are focused on three research questions: (1) How did educational inequalities in self-rated health (SRH) develop between 2002 and 2016 in different European countries? (2) In how far can structural and functional aspects of social relations help to explain these inequalities? (3) Do these explanatory contributions vary between different types of welfare states? Data stem from the European Social Survey. Data from 20 countries across 8 waves (2002-2016) was included in the sample (allocated to 5 types of welfare states). Structural aspects of social relations were measured by living with a partner, frequency of social contacts and social participation. Availability of emotional support was used as functional dimension. Educational level was assessed based on the International Standard Classification of Education. SRH was measured in all waves on a five-point scale by one question: "How is your health in general? Would you say it is very good, good, fair, bad or very bad?" Across all countries, educational inequalities were increasing between 2002 and 2016. Explanatory contribution of emotional support, living with a partner, and social contacts was small (5% or less across the eight waves). Social participation explained 11% of the educational inequalities in SRH in the European countries. There were small variations in the explanatory contribution of social participation between welfare states. Promoting social participation, especially of people with low education is a possible intervention to reduce inequalities in SRH in Europe.

Age, Cohort, and Social Change: Parental and Spousal Education and White Women's Health Limitations From 1967 to 2012.

A large body of research finds that the association between educational attainment and health is at historic highs for White women. Rapid changes in labor force participation, access to high-paying jobs, and gender attitudes have radically altered the meaning of education for women's lives and their dependence on the socioeconomic attainments of their families. Drawing on three nationally representative longitudinal surveys conducted from 1967 to 2012, this study examines how personal, parental, and spousal attainments contribute to the widening education gap in health for successive cohorts of White women ( N = 8,405). Overall, the health of women did not change substantially across cohorts, but results did uncover cohort differences among low-educated women that were linked to parental and spousal educational attainments and personal earnings. These findings confirm growing educational inequalities in health and demonstrate the importance of historical context and family attainments when examining cohort variation in the education-health relationship.

Educational inequalities in mortality are larger at low levels of income: A register-based study on premature mortality among 2.3 million Swedes, 2006–2009

Education develops skills that help individuals use available material resources more efficiently. When material resources are scarce, each decision becomes comparatively more important. Education may also protect from health-related income decline, since the highly educated tend to work in occupations with lower physical demands. Educational inequalities in health may, therefore, be more pronounced at lower levels of income. The aim of this study is to assess whether the shape of the income gradient in premature mortality depends on the level of education.Total population data on education, income and mortality was obtained by linking several Swedish registers. Income was defined as five-year average disposable household income for ages 35–64 and mortality follow-up covered the period 2006–2009. The final population comprised 2.3 million individuals, 6.2 million person-years and 14,362 deaths. Income was modeled using splines in order to allow variation in the functional form of the association across educational categories. Poisson regression with robust standard errors was used.The curvilinear shape of the association between income and mortality was more pronounced among those with a low education. Both absolute and relative educational inequalities in premature mortality tended to be larger at low levels of income. The greatest income differences in mortality were observed for those with a low education and the smallest for the highly educated.Education and income interact as predictors of mortality. Education is a more important factor for health when access to material resources is limited.

Educational inequalities in subjective health in Germany from 1994 to 2014: a trend analysis using the German Socio-Economic Panel study (GSOEP)

IntroductionAs trend studies have shown, health inequalities by income and occupation have widened or remained stable. However, research on time trends in educational inequalities in health in Germany is scarce....

Mental and physical health impairments at the transition to college: Early patterns in the education-health gradient

Part of the education-health gradient may be related to inequalities in the transition from high school to college by health impairment status. In this paper, we use the National Longitudinal Survey of Youth 1997 to investigate the link between health impairments beginning prior to high school completion and college-going, distinguishing between individuals with mental, physical, or multiple health impairments and between enrollment in 2-year and 4-year postsecondary institutions. We find that individuals with mental impairments or multiple impairments are less likely to initially enroll in 4-year postsecondary institutions than individuals without health impairments, controlling on background and high school preparation. We also find evidence that advanced math course-taking in high school, an important step on the pathway to a 4-year college for all students, does not provide students with mental impairments the same return as students without health impairments. We discuss implications for policy to address educational inequalities in health.

Time trends in adult chronic disease inequalities by education in Brazil: 1998-2013.

BackgroundSocioeconomic differences in health in Brazil are largely driven by differences in educational attainment. In this paper, we assess whether educational gradients in chronic disease prevalence have narrowed in Brazil from 1998 to 2013, a period of a booming economy accompanied by major investments in public health in the country.MethodsIndividual-level data came from the 1998, 2003 and 2008 Brazilian National Household Survey and the 2013 National Health Survey. We first evaluate age-standardized prevalence rates of chronic disease by education and second, we predict the estimated prevalence rate between those in low vs. high education to assess if relative changes in chronic disease have narrowed over time. Third, we estimate the slope index of inequality (SII) that evaluates the absolute change in the predicted prevalence of a disease between those in low vs. high education. Finally, we tested for statistically significant time trends in adult chronic disease inequalities by education.ResultsPrevalence of diabetes and hypertension have increased over the period, whereas the prevalence of heart disease decreased. Brazilian adults with no education had higher levels of diabetes, hypertension and heart disease than those with some college or more. Adjusted prevalence for hypertension and heart disease indicate some progress in reducing educational disparities over time. However, for diabetes, adjusted results show a continuously increasing educational disparity from 1998 to 2013. By 2013, individuals with no education had about two times higher diabetes prevalence than those with higher education with larger disparity among women.ConclusionsResults confirm findings from previous work that educational inequalities in health are large in Brazil but also provide evidence suggesting some improvement in narrowing these differentials in recent times. Recent policies aiming at reducing the prevalence of obesity, smoking and alcohol consumption, and increasing physical activity and consumption of fruits and vegetables may increase the overall health and wellbeing of the Brazilian population. These programs are likely to be more effective if they target those with low socioeconomic status, as they appeared to be at a higher risk of developing chronic conditions, and promote educational opportunities.

Exploring trends in and determinants of educational inequalities in self-rated health.

Educational inequalities in self-rated health (SRH) in European welfare countries are documented, but recent trends in these inequalities are less well understood. We examined educational inequalities in SRH in different age groups, and the contribution of selected material, behavioural and psychosocial determinants from 2000 to 2008. Data were derived from cross-sectional surveys conducted in 2000, 2004 and 2008 including 37,478, 34,876 and 32,982 respondents, respectively, aged 25-75 in mid-Sweden. Inequalities were analysed by age-standardized and age-stratified rate ratios of poor SRH and age-standardized prevalence of determinants, and contribution of determinants by age-adjusted logistic regression. Relative educational inequalities in SRH increased among women from 2000 (rate ratio (RR) 1.70, 95% CI 1.55-1.85) to 2008 (RR 2.07, 95% CI 1.90-2.26), but were unchanged among men (RR 1.91-2.01). The increase among women was mainly due to growing inequalities in the age group 25-34 years. In 2008, significant age differences emerged with larger inequalities in the youngest compared with the oldest age group in both genders. All determinants were more prevalent in low educational groups; the most prominent were lack of a financial buffer, smoking and low optimism. Educational differences were unchanged over the years for most determinants. In all three surveys, examined determinants together explained a substantial part of the educational inequalities in SRH. Increased relative educational health inequalities among women, and persisting inequalities among men, were paralleled by unchanged, large differences in material/structural, behavioural and psychosocial factors. Interventions to reduce these inequalities need to focus on early mid-life.

The mediating role of material/structural factors in explaining educational inequalities in psychosocial factors – Analysis of data from a Swedish population survey from 2008 using structural equation modelling

Background Psychosocial factors are contributing to educational inequalities in health. There are two competing theories explaining the role of psychosocial factors. One, the vulnerability theory, assumes that the psychosocial resources are unevenly distributed among educational level groups. The other one, social stress epidemiology, assumes that material/structural factors are unevenly distributed among educational level groups, leading to differential loads of psychosocial stress. The aim of the study was to compare …