Inequalities In Self-assessed Health Research Articles

Socioeconomic inequalities in self-assessed health and food consumption: the mediating roles of daily hassles and the perceived importance of health

BackgroundUrgent daily hassles, which are more common among people with a lower socioeconomic position (SEP), might limit one’s ability to address less pressing goals, such as goals related to health promotion. Consequently, health goals may be viewed as less focal, which could jeopardize one’s health. This study examined an understudied pathway: whether a higher severity of daily hassles resulted in a lower perceived importance of health and whether these two factors sequentially mediate socioeconomic inequalities in self-assessed health (SAH) and food consumption.MethodsA cross-sectional survey among 1,330 Dutch adults was conducted in 2019. Participants self-reported SEP (household income, educational level), the severity of eleven daily hassles (e.g., financial hassles, legal hassles), the perceived importance of health (not being ill, living a long life), SAH, and food consumption. Structural equation modeling was used to examine whether daily hassles and the perceived importance of health sequentially mediated income and educational inequalities in SAH, fruit and vegetable consumption (FVC) and snack consumption.ResultsNo evidence of sequential mediation through daily hassles and the perceived importance of health was found. Daily hassles individually mediated income inequalities in SAH (indirect effect: 0.04, total effect: 0.06) and in FVC (indirect effect: 0.02, total effect: 0.09). The perceived importance of not being ill and living a long life both individually mediated educational inequalities in SAH (indirect effects: 0.01 and -0.01, respectively, total effect: 0.07).ConclusionsIncome inequalities in SAH and FVC were explained by daily hassles, and educational inequalities in SAH were explained by the perceived importance of health. Socioeconomic inequalities may not be sequentially explained by a more severe experience of daily hassles and a lower perceived importance of health. Interventions and policies addressing challenging circumstances associated with a low income may improve SAH and healthy food consumption among lower-income groups.

Health indicators and poor health dynamics during COVID-19 pandemic.

It is expected that the coronavirus pandemic will exacerbate inequality in wellbeing compared to the pre-pandemic situation. However, there are theories (e.g., the Conservation of Resource (COR) theory) that acknowledge situation-specific lower wellbeing for individuals who typically have more resources. The argument is that perception of loss might occur differently across the socioeconomic spectrum such that individuals with higher socioeconomic status perceive that they experience more loss. Therefore, given the pandemic situation, it is possible that indicators of poor wellbeing (e.g., depression) becoming less concentrated among the poor, contrary to expectation. Given the above, we examine income-related inequality in self-assessed health and depressive symptoms in South Africa. This is done using both pre-pandemic data (i.e. National Income Dynamic Study) and data collected during the pandemic (National Income Dynamic Study-Coronavirus Rapid Mobile Survey). Consistent with expectation, we find that poor self-assessed health is not only disproportionately concentrated amongst the poor, but this concentration has increased compared to the pre-pandemic period. However, contrary to expectation, depressive symptoms have become less concentrated amongst the poor compared to the pre-pandemic period. We note that while there may be an alternative explanation for this change in trend, it may also be due to situation-specific lower wellbeing for individuals who typically have more resources. We argue that this has implication for tracking population health in a crisis.

Have Health Inequalities Increased during the COVID-19 Pandemic? Evidence from Recent Years for Older European Union Citizens.

Reducing inequality is one of the current challenges that most societies are facing. Our aim was to analyze the evolution of inequalities in self-assessed health among older Europeans in a time period spanning the 2008 economic crisis and the COVID-19 health crisis. We used data from Waves 2, 4 and 8 of the Survey of Health, Ageing and Retirement in Europe. We used inequality indices that accept ordinal variables. Our empirical results suggest that average inequality declines over time. Gender significantly influences the results. Some of the countries with the highest level of inequality are Denmark and Sweden, and some with the lowest are Estonia and the Netherlands. Our results may be of interest for the development of public policies to reduce inequalities. Special attention should be paid to vulnerable groups, such as the elderly.

Socioeconomic inequalities in health: the role of daily hassles and the importance of health

Abstract A low socioeconomic position (SEP) adversely affects health outcomes and is associated with a lower perceived importance of health. It has been suggested that people with a low SEP disproportionately face daily hassles, as a result of which health may be perceived as less important for those with a low SEP compared to those with a high SEP. A lower perceived importance of health likely influences health-related behaviours that affect health outcomes. This study examines whether socioeconomic inequalities in self-assessed health are mediated by daily hassles and/or the perceived importance of health, and whether there is sequential mediation of daily hassles and perceived importance of health. A cross-sectional survey was conducted in 2019 among N = 1,334 Dutch adults. Participants rated the extent of eleven commonly experienced daily hassles (e.g., financial hassles, legal issues), and indicated the perceived importance of two health-related domains (not being ill, living a long life). Inequalities in self-assessed health according to SEP (indicated by income and education) were examined using structural equation modelling, with daily hassles and perceived importance of not being ill or living long a life either as single or sequential mediators. Daily hassles and perceived importance of health individually mediated the relationship between SEP and self-assessed health, but importance of health did not mediate the association between by daily hassles self-assessed health. Socioeconomic inequalities in self-assessed health were explained by the experience of daily hassles, and by differences in the perceived importance of health individually, but the perceived importance of health did not explain the influence of the experience of daily hassles. Addressing the challenging circumstances (e.g., financial or housing hassles) associated with a low SEP, may contribute to improving self-assessed health. Further research should examine how daily hassles affect health. Key messages Daily hassles and the perceived importance of health mediated the relationship between socioeconomic position and health. There was no association between daily hassles and the perceived importance of health.

Socioeconomic inequalities in self-assessed health and mental health in Barcelona, 2001-2016

ObjectivePrevious research has found persistent socioeconomic inequalities in health outcomes at the national level, with different patterns after the economic crisis. However, inequalities in urban areas are also important. This study analyses socioeconomic inequalities in self-assessed health and mental health in the city of Barcelona. MethodRepeated cross-sectional design using quinquennial data from the Barcelona Health Surveys carried out in 2001, 2006, 2011 and 2016 for the population older than 22 years. Robust Poisson regressions models were used to compute socioeconomic gradients and relative (RII) and slope indexes of inequality (SII) by occupational social class, with stratification by sex. RII and SII were also obtained with further adjustment by employment situation. ResultsA consistent socioeconomic gradient was found for all years except for 2011. Relative and absolute inequalities followed a V-shape, showing a drop during the economic crisis but widening thereafter to recover pre-crisis figures for self-assessed health and widening for mental health, in both relative and absolute terms in 2016. Adjustment for employment situation reduces inequalities but a large part of these inequalities remains, with variability across years. ConclusionsThe lasting effects of the 2008 economic crisis and the austerity programmes imposed since then may have contributed to the persistence of socioeconomic inequalities in self-assessed health and the widening of those for mental health.

Health and Inequality in Health in the Nordic Countries

All five Nordic countries emphasise equal and easy access to healthcare. It is the purpose to explore to which extent the populations of these countries have reached good health and high degree of socio-economic equality of health. Each of the five countries has established extensive public health programmes, although with somewhat different emphasis on the causes of ill-health, such as individual behaviour or social circumstances. Attitudes have changed over time, though. We compare these countries to the UK and Germany by using data from the European Social Survey 2002 and 2012 in addition to OECD Statistics from the same years. Health is measured by self-assessed health in five categories, transformed to a cardinal scale using Swedish time trade-off weights. As socio-economic variable we use household income or length of education. Mean health, based on Swedish TTO weights applied to all countries, is above 0.93 in all the Nordic countries and the UK in 2012, while lower in Germany. Rates in good or very good health in the lower income half of the samples are above 0.6 in most countries and even higher in Iceland and Sweden, but below 0.5 in Germany. However, when displayed in a graph the concentration curves nearly follow the diagonal implying almost no income - or education related inequality in self-assessed health weighted by TTO based preferences. The difference is a natural consequence of using different methods. We compared four key life-style related determinants of ill health and found that while there were differences in relative levels between the countries, Germany had a relatively high level of three of these, followed by the UK. We found no association between level of resources used and health status. In general, the Nordic countries have accomplished good health for their populations and high degree of socioeconomic equality in health. Improvements in life-style related determinants of health would be possible, though.

Trends in socioeconomic inequalities in self-assessed health in 17 European countries between 1990 and 2010

BackgroundBetween the 1990s and 2000s, relative inequalities in all-cause mortality increased, whereas absolute inequalities decreased in many European countries. Whether similar trends can be observed for inequalities in other health...

Trends in income-related health inequalities in self-assessed health in Korea, 1998–2011

This study assesses income-related health inequalities in self-assessed health (SAH) and its trend from 1998 to 2011 in Korea that covers important time periods of financial crisis and post-crisis. Data came from the Korean National Health and Nutrition Examination Survey from 1998 to 2011. A population-representative sample aged 46 years and older was analysed. SAH was used as an indicator of health status, with household equivalence income as a proxy for socio-economic position. Age-adjusted prevalence rates of SAH were analysed to estimate both absolute and relative measures of health inequalities and the trend over time by the relative index of inequality (RII) and the slope index of inequality (SII). Results indicated that the highest level of health inequalities was found among men aged 46–59 years, especially in 2001 and 2005. For men, there was no clear, consistent pattern of increase or decrease in the trend over time. On the other hand, increasing trends in the RII and SII were found for women, except for women aged 46–59 years who reported a decreasing trend in the SII. Trends in health inequalities over time were influenced by economic crisis, demonstrating the need for macro-level economic policies as well as health policies addressing health gaps.

Trends in Socioeconomic and Racial/Ethnic Inequalities in Self-Assessed Health, Disability, and Mental Health in California: Findings from CHIS 2001–2011

Despite growing interest in health inequalities across socioeconomic and racial/ethnic groups, research remains scarce on the subject for California. The purpose of this study is to assess magnitude and trends in socioeconomic and race/ethnicity inequalities in self-assessed health, disability, and psychological distress. This study used the population-representative sample aged 45 and older (n = 181,964) in 2001–2011 California Health Interview Survey (CHIS). Based on poverty as socioeconomic position and race/ethnicity as nominal social group, health inequalities and the trend over time were examined by estimating population-weighted measures on both absolute and relative terms. The most economically disadvantaged Californians showed the highest rates of poor self-assessed health, disability, and serious psychological distress for the entire study period. Socioeconomic health inequalities have widened in poor self-assessed health over time for women, while the inequalities appeared to narrow for disability and psychological distress for both men and women. Race/ethnicity inequalities in disability widened considerably for men and women, while those of psychological distress declined from 2005 to 2011. Socioeconomic and race/ethnicity health inequalities are present and persistent in California. Trends in health inequalities appear to reflect potential impact of recent financial crisis and legislative changes in California. Consistent measurement and monitoring of health inequalities are needed to develop socioeconomic and health policies that address health inequalities in California.

All Part of the Job? The Contribution of the Psychosocial and Physical Work Environment to Health Inequalities in Europe and the European Health Divide

This study is the first to examine the contribution of both psychosocial and physical risk factors to occupational inequalities in self-assessed health in Europe. Data from 27 countries were obtained from the 2010 European Working Conditions Survey for men and women aged 16 to 60 (n = 21,803). Multilevel logistic regression analyses (random intercept) were applied, estimating odds ratios of reporting less than good health. Analyses indicate that physical working conditions account for a substantial proportion of occupational inequalities in health in both Central/Eastern and Western Europe. Physical, rather than psychosocial, working conditions seem to have the largest effect on self-assessed health in manual classes. For example, controlling for physical working conditions reduced the inequalities in the prevalence of"less than good health" between the lowest (semi- and unskilled manual workers) and highest (higher controllers) occupational groups in Europe by almost 50 percent (Odds Ratio 1.87, 95% Confidence Interval 1.62-2.16 to 1.42, 1.23-1.65). Physical working conditions contribute substantially to health inequalities across "post-industrial" Europe, with women in manual occupations being particularly vulnerable, especially those living in Central/Eastern Europe. An increased political and academic focus on physical working conditions is needed to explain and potentially reduce occupational inequalities in health.

Self-rated health among women and their assessment of the health care system / Samoocena zdravja med ženskami in njihov odnos do zdravstvenega sistema v sloveniji

Abstract Background: This article researches gender inequality in health based on subjective assessments of health, the accessibility of health care services and trust in the health care system between different social categories of women in Slovenia. Methods: The study is based on the Slovenian Public Opinion survey (ISSP Health Module) carried out in 2011 on representative samples of the adult Slovenian population. In the data, we investigated the gender differences and difference between different socio-economic categories within the female sub-sample in self-assessed health, and some other related topics such as: trust in doctors, trust in health care system, access to health care services and attitude to the health care policy in Slovenia. Results: The data shows significant inequalities in self-assessed health between different social strata. Self-assessed health is significantly lower among women at the bottom of the educational and income scale. The data also reveals strong support for the preservation of the available public health. Conclusion: Neoliberal economic reforms (of health care) affect vulnerable social categories the most, and women are particularly exposed. The use of women’s unpaid work in the family belongs among the basic (neo)liberal saving strategies. These want to take more care and health work within families from the shoulders of the state and place it onto the shoulders of family members, which mainly means women. In these circumstances, it is understandable that women subjectively assess their health as being worse than men’s. Moreover, conditions are being established that de facto could lead to worse health in the female population in Slovenia.

Differences in self-assessed health by socioeconomic group amongst people with and without a history of cancer: an analysis using representative data from Scotland

This paper considers socioeconomic inequalities in self-assessed health amongst people with and without a history of cancer using representative data from Scotland. A cross-sectional analysis using the Scottish Health Survey was done. Cancer survivors were identified using linked Cancer Registry data. Bivariate and multivariate analysis was used to compare and contrast self-assessed health amongst those with a history of cancer to those without. Of the 17,505 survey participants, 432 (2.5%) had a history of cancer. After taking into account potential confounders, those in the lowest socioeconomic group were more likely to report poor health than those in the highest group amongst those with a history of cancer [odds ratio, 2.96; confidence interval (CI), 1.82-4.80] and those with no history of cancer (odds ratio, 2.45; CI, 2.21-2.71). Those in the lowest socioeconomic group with no history of cancer had a greater propensity to report poor health than any of the highest groups that did have a history of cancer (p < 0.01). Differences in propensities to indicate poor health were particularly marked amongst those 4years or more post-cancer diagnosis. Findings underline the scale of socioeconomic gradients in health. That disparities were so wide amongst those most temporally distant from initial diagnosis is particularly a concern given improving survival after a cancer diagnosis. Socioeconomic circumstances have a considerable influence on health and well-being. Practitioners and policy makers should consider socioeconomic circumstances in considering approaches to health and social care of cancer survivors.

Economic costs of health inequalities in the European Union

BackgroundIn order to support the case for inter-sectoral policies to tackle health inequalities, the authors explored the economic costs of socioeconomic inequalities in health in the European Union (EU).MethodsUsing recent...

Educational health inequalities in former Yugoslavia: evidence from the South-East European Social Survey Project

An important gap in our knowledge of social inequalities in health is the former Yugoslavia, a region of culturally and historically diverse countries, with recent conflict. The aim of the present paper is to investigate relative and absolute inequalities in self-assessed health in former Yugoslavia (Bosnia-Herzegovina, Croatia, Kosovo, Macedonia, Montenegro, Slovenia and Serbia) by sex and education. The data source is the South-East European Social Survey Project fielded in December 2003 to Winter 2004, covering the former Yugoslavia with a total sample of 18 481 respondents. Data from Slovenia were obtained from the 2004-wave of the European Social Survey. The health outcome variables were self-reported general health (SRH) and limiting longstanding illness (LLI). Both absolute and relative educational health inequalities were present throughout the former Yugoslavia to a larger or lesser extent, although odds ratios (ORs) for LLI and SRH were not significant for Montenegrin women [LLI OR = 1.12, 95% confidence interval (CI): 0.92-1.37; SRH OR = 1.16, 95% CI: 0.96-1.40] and with respect to the reporting of LLI among Slovenian men (OR = 1.16, 95% CI: 0.96-1.44). Overall, Montenegro held the best position. The prevalence of poor health and the degree of relative inequality in self-assessed health in the former Yugoslavian countries were similar in order to one another, and to other East European countries during the same period. Influences on subjective health require further elucidation. Further research should study a wider range of health outcomes using larger survey samples and a wider range of cultural and other predictor variables.

Socioeconomic Inequalities in Health in 22 European Countries

A b s t r ac t Background Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. Methods We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. Results In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. Conclusions We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care.

SOCIAL POSITION AND HEALTH: ARE OLD AND NEW OCCUPATIONAL CLASSIFICATIONS INTERCHANGEABLE?

There is growing international interest in the choice of socioeconomic indicators for health research. This study used a combination of standard and novel methods to compare three occupation-based measures of social position in terms of their ability to explain variation and measure inequality in self-assessed health. The recently developed National Statistics Socioeconomic Classification (NS-SEC) is compared with its predecessor, the Registrar General's Social Class schema (RGSC), and with another occupation-based measure, the Cambridge Social Interaction and Stratification Scale (CAMSIS). With data from two large, independent, nationally representative samples of adults aged 16-64 living in private households in Scotland, logistic regression models are used to compare the classifications' ability to predict self-assessed health. Concentration indices are estimated to compare how well they capture inequality in self-assessed health. The study shows that all three classifications are strongly associated with self-assessed health, though the associations are heavily attenuated by adjustment for one another and for other measures of social position. Despite their differing theoretical bases, the three are closely related. No evidence is found that any of them systematically under- or overstate the extent of inequality in self-assessed health in either men or women, and the extent to which they measure independent dimensions of social inequality is questioned. It is concluded that the availability of the new classifications is unlikely to transform our understanding of the extent or the causes of socioeconomic inequality in health, but provides useful opportunities for sensitivity analysis.

Trends in socioeconomic inequalities in self-assessed health in 10 European countries

Changes over time in inequalities in self-reported health are studied for increasingly more countries, but a comprehensive overview encompassing several countries is still lacking. The general aim of this article is to determine whether inequalities in self-assessed health in 10 European countries showed a general tendency either to increase or to decrease between the 1980s and the 1990s and whether trends varied among countries. Data were obtained from nationally representative interview surveys held in Finland, Sweden, Norway, Denmark, England, The Netherlands, West Germany, Austria, Italy, and Spain. The proportion of respondents with self-assessed health less than 'good' was measured in relation to educational level and income level. Inequalities were measured by means of age-standardized prevalence rates and odds ratios (ORs). Socioeconomic inequalities in self-assessed health showed a high degree of stability in European countries. For all countries together, the ORs comparing low with high educational levels remained stable for men (2.61 in the 1980s and 2.54 in the 1990s) but increased slightly for women (from 2.48 to 2.70). The ORs comparing extreme income quintiles increased from 3.13 to 3.37 for men and from 2.43 to 2.86 for women. Increases could be demonstrated most clearly for Italian and Spanish men and women, and for Dutch women, whereas inequalities in health in the Nordic countries showed no tendency to increase. The results underscore the persistent nature of socioeconomic inequalities in health in modern societies. The relatively favourable trends in the Nordic countries suggest that these countries' welfare states were able to buffer many of the adverse effects of economic crises on the health of disadvantaged groups.

Does inequality in self-assessed health predict inequality in survival by income? Evidence from Swedish data

This paper empirically addresses two questions using a large, individual-level Swedish data set which links mortality data to health survey data. The first question is whether there is an effect of an individual's self-assessed health (SAH) on his subsequent survival probability and if this effect differs by socioeconomic factors. Our results indicate that the effect of SAH on mortality risk declines with age—probably because of adjustment towards ‘milder’ overall health evaluations at higher ages—but does not seem to differ by indicators of socioeconomic status (SES) like income or education. This finding suggests that there is no systematic adjustment of SAH by SES and therefore that any measured income-related inequality in SAH is unlikely to be biased by reporting error. The second question is: how much of the income-related inequality in mortality can be explained by income-related inequality in SAH? Using a decomposition method, we find that inequality in SAH accounts for only about 10% of mortality inequality if interactions are not allowed for, but its contribution is increased to about 28% if account is taken of the reporting tendencies by age. In other words, omitting the interaction between age and SAH leads to a substantial underestimation of the partial contribution of SAH inequality by income. These results suggest that the often observed inequalities in SAH by income do have predictive power for the—less often observed—inequalities in survival by income.

Income-related health inequality in Canada

This study uses data from the 1994 National Population Health Survey and applies the methods developed by Wagstaff and van Doorslaer (1994, measuring inequalities in health in the presence of multiple-category morbidity indicators. Health Economics 3, 281–291) to measure the degree of income-related inequality in self-reported health in Canada by means of concentration indices. It finds that significant inequalities in self-reported ill-health exist and favour the higher income groups — the higher the level of income, the better the level of self-assessed health. The analysis also indicates that lower income individuals are somewhat more likely to report their self-assessed health as poor or less-than-good than higher income groups, at the same level of a more ‘objective’ health indictor such as the McMaster Health Utility Index. The degree of inequality in ‘subjective’ health is slightly higher than in ‘objective’ health, but not significantly different. The degree of inequality in self-assessed health in Canada was found to be significantly higher than that reported by van Doorslaer et al. (1997, income related inequalities in health: some international comparisons, Journal of Health Economics 16, 93–112) for seven European countries, but not significantly different from the health inequality measured for the UK or the US. It also appears as if Canada’s health inequality is higher than what would be expected on the basis of its income inequality.

Income-related inequalities in health: some international comparisons

This paper presents evidence on income-related inequalities in self-assessed health in nine industrialized countries. Health interview survey data were used to construct concentration curves of self-assessed health, measured as a latent variable. Inequalities in health favoured the higher income groups and were statistically significant in all countries. Inequalities were particularly high in the United States and the United Kingdom. Amongst other European countries, Sweden, Finland and the former East Germany had the lowest inequality. Across countries, a strong association was found between inequalities in health and inequalities in income.