Critically examining diversity in end-of-life family caregiving: implications for equitable caregiver support and Canada’s Compassionate Care Benefit

Background

Mental health is of special importance regarding socioeconomic inequalities in health. On the one hand, mental health status mediates the relationship between economic inequality and health; on the other hand, mental health as an "end state" is affected by social factors and socioeconomic inequality. In spite of this, in examining socioeconomic inequalities in health, mental health has attracted less attention than physical health. As a first attempt in Iran, the objectives of this paper were to measure socioeconomic inequality in mental health, and then to untangle and quantify the contributions of potential determinants of mental health to the measured socioeconomic inequality.

Methods

In a cross-sectional observational study, mental health data were taken from an Urban Health Equity Assessment and Response Tool (Urban HEART) survey, conducted on 22 300 Tehran households in 2007 and covering people aged 15 and above. Principal component analysis was used to measure the economic status of households. As a measure of socioeconomic inequality, a concentration index of mental health was applied and decomposed into its determinants.

Results

The overall concentration index of mental health in Tehran was -0.0673 (95% CI = -0.070 - -0.057). Decomposition of the concentration index revealed that economic status made the largest contribution (44.7%) to socioeconomic inequality in mental health. Educational status (13.4%), age group (13.1%), district of residence (12.5%) and employment status (6.5%) also proved further important contributors to the inequality.

Conclusions

Socioeconomic inequalities exist in mental health status in Iran's capital, Tehran. Since the root of this avoidable inequality is in sectors outside the health system, a holistic mental health policy approach which includes social and economic determinants should be adopted to redress the inequitable distribution of mental health.     

Socioeconomic inequalities in health: a comparative longitudinal analysis using the European Community Household Panel

This study measures socioeconomic inequalities in health across European Union Member States between 1994 and 2001. The analysis is based on the European Community Household Panel Users' Database (ECHP-UDB) and uses two binary indicators of health limitations for the full 8 waves of available data. Short- and long-run concentration indices together with mobility and health achievement indices are derived for indicators of severe health limitation and any health limitation. Results demonstrate the existence of socioeconomic inequality in health across Member States in both the short-term (1 year) and the long-term (up to 8 years), with health limitations concentrated among those with lower incomes. For all countries, the long-run indices show that income-related inequalities in health widen over time, in the sense that the longer the period over which an individual's health and income are measured the greater the measure of income-related health inequality. The ranking of countries according to their prevalence of illness differs from ranking by overall health achievement, which takes account of inequalities. This means that an equity-efficiency trade-off has to be faced in evaluating the performance of different countries and in comparing countries with diverse health and social welfare systems.     

Equity in the health sector: evaluation of public policy in Belo Horizonte,Minas Gerais State,Brazil, 1993-1997

This article evaluates government measures to reduce inequity in the health sector in Belo Horizonte from 1993 to 1997. Our hypothesis is that a municipal administration committed to equity can reduce disparities in health with the support of the Unified National Health System (SUS). The methodology used an urban quality of life index in Belo Horizonte to detect social inequalities in living conditions, as well as differences between the component indices in the infant mortality rate. Other municipal measures were assessed according to the investment resulting from the implementation of a participatory local budget and open planning process. The urban quality of life index appeared to be an appropriate measure for orienting municipal administration. The infant mortality rate proved to be a good indicator for measuring inequality in health. There was a reduction in IMR and mortality reducing gaps in the districts studied. We observed greater investment of physical and financial resources in the districts with the lowest urban quality of life index, and it can thus be stated that the municipal administration reduced the prevailing inequalities.     

Deprivation and poor health in rural areas: inequalities hidden by averages

Poor health and social deprivation scores in 570 wards in East Anglia, UK, were much less associated in rural than in urban areas. The deprivation measure most closely related to poor health in the least accessible rural wards was male unemployment, but use of this measure did not remove the urban-rural gradient of association strength. Neither did replacing wards by smaller enumeration districts as the units of analysis. The differences between urban and rural correlations were removed by restricting the comparison to wards with the same unemployment range and combining pairs of rural wards with similar deprivation values. Apparent differences between rural and urban associations are therefore not due to the choice of deprivation indices or census areas but are artifacts of the greater internal variability, smaller average deprivation range and smaller population size of rural small areas. Deprived people with poor health in rural areas are hidden by favourable averages of health and deprivation measures and do not benefit from resource allocations based on area values.     

Socioeconomic inequalities in mental health in Australia: Explaining life shock exposure

BackgroundRecent research suggests that there exists a strong link between life shocks and mental health. However, research on the distributional aspects of these shocks on mental health status is limited. In the health inequality literature no Australian studies have examined this relationship.ObjectiveThis study examines the distributional impact of life shocks (negative life events and financial hardships) on mental health inequality among different socioeconomic groups in a longitudinal setting in Australia.MethodsThis study analysed the data of 13,496 individuals from the Household, Income and Labour Dynamics in Australia (HILDA) survey, waves 12–17 (2012–2017). Using concentration index and Blinder-Oaxaca approaches, the study decomposed socioeconomic inequalities in mental health and changes in inequalities in mental health over the study period. The study used frailty indices to capture the severity of life shocks experienced by an individual.ResultsThe results suggest that exposure to just one life shock will result in a greater risk of mental disorder in the most disadvantaged socioeconomic groups. The results also indicate that 24.7%–40.5% of pro-rich socioeconomic mental health inequality are due to life shocks. Financial hardship shocks contributes to 21.6%–35.4% of inequality compared with 2.3%–5.4% inequality generated by negative life event shocks across waves.ConclusionsLower SES groups experience more life shocks than higher SES groups and in turn generate higher socioeconomic mental health inequality. Policies aimed at reducing socioeconomic inequality in mental health should account for these shocks when designing interventions.     

Trends in mental health inequalities in urban Canada

ObjectivesCanadians do not all enjoy equal levels of health. The presence of income-related health inequalities has been well established in Canada, but there is a lack of consistent reporting of mental health inequalities in Canada’s largest cities. This study reports the prevalence and inequalities in mental health outcomes at the city, provincial, and national levels over time.MethodsSelf-reported poor mental health, life stress, and physician-diagnosed self-reported mood and anxiety disorder from the Canadian Community Health Survey were pooled over five-year intervals and combined with neighbourhood income information from the Canadian Census. First, prevalence rates were calculated for each interval at the neighbourhood level for urban communities. Second, the distributions of these neighbourhood rates were summarized at the city level and for Canada as a whole using overall prevalence rates and concentration indices of inequality. Finally, trends in these city- and country-level outcomes were also explored.ResultsAt the national level, starting from 2001 to 2005, the prevalence of poor mental health (27.9%), mood disorder (7.3%), and anxiety disorder (6.8%) had significantly increased by 2011–2015. Inequalities were present in 2001–2005 and worsened over time. The prevalence rate at the national level of life stress was 66.6% in 2001–2005 and decreased over time.ConclusionThe large and increasing values of inequalities and the difference in prevalence rates and inequalities in cities highlight the necessity for mental disorder-specific data and for city-level analysis of inequalities. The next steps in reducing inequalities involve deconstructing the health inequalities, and continued monitoring.     

Understanding wealth-based inequalities in child health in India: A decomposition approach

India experienced tremendous economic growth since the mid-1980s but this growth was paralleled by sharp rises in economic inequality. Urban areas experienced greater economic growth as well as greater increases in economic inequality than rural areas. During the same period, child health improved on average but socioeconomic differentials in child health persisted. This paper attempts to explain wealth-based inequalities in child mortality and malnutrition using a regression-based decomposition approach. Data for the analysis come from the 1992/93, 1998/99, and 2005/06 Indian National Family Health Surveys. Inequalities in child health are measured using the concentration index. The concentration index for each outcome is then decomposed into the contributions of wealth-based inequality in the observed determinants of child health. Results indicate that mortality inequality declined in urban areas but remained unchanged or increased in rural areas. Malnutrition inequality increased dramatically both in urban and rural areas. The two largest individual/household-level sources of disparities in child health are (i) inequality in the distribution of wealth itself, and (ii) inequality in maternal education. The contributions of observed determinants (i) to neonatal mortality inequality remained unchanged, (ii) to child mortality inequality increased, and (ii) to malnutrition inequality increased. It is possible that the increases in child health inequality reflect urban biases in economic growth, and the mixed performance of public programs that could have otherwise offset the impacts of unequal growth.     

Inequality aversion,health inequalities and health achievement

This paper addresses two issues. The first is how health inequalities can be measured in such a way as to take into account policymakers' attitudes towards inequality. The Gini coefficient and the related concentration index embody one particular set of value judgements. By generalising these indices, alternative sets of value judgements can be reflected. The other issue addressed is how information on health inequality can be used together with information on the mean of the relevant distribution to obtain an overall measure of health "achievement".     

On the measurement of relative and absolute income-related health inequality

In recent work on international comparisons of income-related inequalities in health, the concentration index has been used as a measure of health inequality. A drawback of this measure is that it is sensitive to whether it is estimated with respect to health or morbidity. An alternative would be to use the generalized concentration index that is based on absolute rather than relative health differences. In this methodological paper, we explore the importance of the choice of health inequality measure by comparing the income-related inequality in health status and morbidity between Sweden and Australia. This involves estimating a concentration index and a generalized concentration index for the eight-scale health profile of the Short Form 36 (SF-36) health survey. We then transform the scores for each scale into a measure of morbidity and show that whether the concentration index is estimated with respect to health or morbidity has an impact on the results. The ranking between the two countries is reversed for two of the eight dimensions of SF-36 and within both countries the ranking across the eight SF-36 scales is also affected. However, this change in ranking does not occur when the generalized concentration index is compared and we conclude with the implications of these results for reporting comparisons of income-related health inequality in different populations.     

'Crowded suburbs' and 'killer cities': a brief review of the relationship between urban environments and mental health

Most of the world's population now lives in cities, with 90% of Australians living in urban settlements of more than 10 000 people. Urban environments help shape population health, particularly among disadvantaged people, where poor health is concentrated. A growing body of research has focussed on the association between cities and mental health. Three hypotheses have been proposed to explain this association: psychosocial stressors; concentrated disadvantage; and social drift. It remains unclear, however, how the characteristics of urban environments are related to each other and to mental health, and what might be the pathways underpinning the experience of different individuals. With one in five Australian adults meeting the diagnostic criteria for a mental disorder each year, investigation of the relationship between urban environments and mental health is urgently needed. This paper briefly reviews recent studies linking disadvantaged urban environments with mental health and proposes a hypothetical model to help guide future research.     

Understanding differences in income-related health inequality between geographic regions in Taiwan using the SF-36

This paper measures and decomposes socio-economic inequality in general and mental health of Taiwan residents using concentration indices. The data from the 2001 Taiwanese National Health Interview Survey is based on multi-stage systematic sampling: 18,142 subjects aged 12 and above provided answers to questions on general and mental health domains of SF-36 Taiwan version. Significant inequalities favouring higher income groups emerge in both general and mental health, but these are particularly high for residents in remote areas. The decomposition analysis shows that in both areas income itself accounts for a significant and sizeable contribution (40-73%) of general and mental health inequality. The second largest contribution comes from inequality in education (15-22%) for general health and from employment status (17-18%) for mental health. Apart from these factors, age, and lifestyles are also important contributors for both general and mental health. We also find important regional disparities in income-related inequalities.     

Measuring achievement: Changes in risk factors for cardiovascular disease in Australia

A possible measure for evaluating health system performance is the achievement index, which can be calculated using prevalence and distribution of a health measure across different socioeconomic groups. This study extends this approach by examining how achievement can be represented on a two-dimensional plane with the x-axis being the difference in mean ill-health and the y-axis being the difference in an absolute measure of inequality based on the generalised concentration index. The achievement plane is an easily understandable visual aid which provides a method of tracking changes in health and inequality over time, as well as uncertainty around these measures. We also demonstrate how comparisons over time and at different levels of inequality aversion can be undertaken using measures of net achievement. To illustrate the use of the achievement plane, we compared changes in prevalence of various cardiovascular risk factors and absolute inequality in the distribution of these factors, using data from four successive Australian National Health Surveys conducted between 1989 and 2005. While self-reported rates of smoking and high cholesterol have been declining, inequalities have been rising as the greatest reductions in these risk factors have been among higher income groups. Conversely for risk factors where the prevalence has been increasing, health inequalities are either not changing (i.e. diabetes and obesity), or diminishing over time (overweight/obese). All of these changes can be summarized using an achievement plane and graphs of net achievement to examine changes in prevalence and distribution of these risk factors over time.     

Poverty and health sector inequalities

Poverty and ill-health are intertwined. Poor countries tend to have worse health outcomes than better-off countries. Within countries, poor people have worse health outcomes than better-off people. This association reflects causality running in both directions: poverty breeds ill-health, and ill-health keeps poor people poor. The evidence on inequalities in health between the poor and non-poor and on the consequences for impoverishment and income inequality associated with health care expenses is discussed in this article. An outline is given of what is known about the causes of inequalities and about the effectiveness of policies intended to combat them. It is argued that too little is known about the impacts of such policies, notwithstanding a wealth of measurement techniques and considerable evidence on the extent and causes of inequalities.     

The Experience of Implementing Urban HEART Barcelona: a Tool for Action

Urban Health Equity Assessment and Response Tool (HEART) is a tool developed by the World Health Organization whose objective is to provide evidence on urban health inequalities so as to help to decide the best interventions aimed to promote urban health equity. The aim of this paper is to describe the experience of implementing Urban HEART in Barcelona city, both the adaptation of Urban HEART to the city of Barcelona, its use as a means of identifying and monitoring health inequalities among city neighbourhoods, and the difficulties and barriers encountered throughout the process. Although ASPB public health technicians participated in the Urban HEART Advisory Group, had large experience in health inequalities analysis and research and showed interest in implementing the tool, it was not until 2015, when the city council was governed by a new left-wing party for which reducing health inequalities was a priority that Urban HEART could be used. A provisional matrix was developed, including both health and health determinant indicators, which allowed to show how some neighbourhoods in the city systematically fare worse for most of the indicators while others systematically fare better. It also allowed to identify 18 neighbourhoods—those which fared worse in most indicators—which were considered a priority for intervention, which entered the Health in the Barcelona Neighbourhoods programme and the Neighbourhoods Plan. This provisional version was reviewed and improved by the Urban HEART Barcelona Working Group. Technicians with experience in public health and/or in indicator and database management were asked to indicate suitability and relevance from a list of potential indicators. The definitive Urban HEART Barcelona version included 15 indicators from the five Urban HEART domains and improved the previous version in several requirements. Several barriers were encountered, such as having to estimate indicators in scarcely populated areas or finding adequate indicators for the physical context domain. In conclusion, the Urban HEART tool allowed to identify urban inequalities in the city of Barcelona and to include health inequalities in the public debate. It also allowed to reinforce the community health programme Health in the Barcelona Neighbourhoods as well as other city programmes aimed at reducing health inequalities. A strong political will is essential to place health inequalities in the political agenda and implement policies to tackle them.     

Income‐related health inequalities in working age men and women in Australia and New Zealand

Objective : To examine income‐related inequalities in health in working age men and women in Australia and New Zealand. Methods : We used data from two longitudinal surveys, Wave 8 (2008) of the Household Income and Labour Dynamics in Australia (HILDA) Survey and Wave 7 (2008/2009) of the New Zealand Survey of Family Income and Employment (SoFIE). We compared concentration indices (a measure of income‐related health inequality) that examined the distribution of general and mental health‐related quality of life scores (from the SF‐36) across income in working age (20–65 year old) men and women. Decomposition analyses of the concentration indices were done to identify the relative contribution of various determinants to the income‐related health inequality. Results : General health (GH) scores generally decline with age, and mental health (MH) scores increase with age, in both surveys. Income‐related health inequalities were present in both the HILDA and SoFIE samples, with better health in high income groups. Decomposition analyses found that income, area deprivation and being inactive in the labour force were major contributors to income‐related health inequality, in both surveys, and for both health outcomes. Conclusions and implications : Despite some baseline differences in income‐related health inequalities using Australian and New Zealand surveys, we found similar modifiable determinants, which could be targeted to improve health inequalities in both countries.     

Robust rankings of socioeconomic health inequality using a categorical variable

When assessing socioeconomic health inequalities, researchers often draw upon measures of income inequality that were developed for ratio scale variables. As a result, the use of categorical data (such as self‐reported health status) produces rankings that may be arbitrary and contingent to the numerical scale adopted. In this paper, we develop a method that overcomes this issue by providing conditions for which these rankings are invariant to the numerical scale chosen by the researcher. In doing so, we draw on the insight provided by Allison and Foster (2004) and extend their method to the dimension of socioeconomic inequality by exploiting the properties of rank‐dependent indices such as Wagstaff (2002) achievement and extended concentration indices. We also provide an empirical illustration using the National Institute of Health Survey 2012.     

Achieving better measles immunization in developing countries: does higher coverage imply lower inequality?

Changes in measles immunization are commonly expressed in terms of a change in mean coverage rates but these mean changes may conceal substantial disparities within societies by poverty status. This paper analyzes trends in both the level and the socio-economic distribution of measles immunization coverage in the 1990s for 21 developing countries with two rounds of Demographic and Health Surveys available. We examine these trends using "achievement" indices that combine trends in means and in inequality. We propose and employ "achievement contours" to illustrate graphically how a greater degree of societal aversion to inequality may affect the ranking of countries in terms of achieved measles immunization coverage. The results indicate that most countries have experienced an improvement in their mean measles immunization rate but that this improvement was often unequally distributed across wealth groups, disfavouring the poor in all countries. Mean improvements were found to be associated with both increasing and decreasing inequality. When the trend in the mean and in the degree of inequality was opposite, the trend in the overall "achievement" score is determined by the assumed underlying degree of inequality aversion. As such, the achievement measure "penalizes" coverage improvements that leave the poor lagging behind.     

贫困人群利用卫生服务的不公平状况与影响因素

贫困与疾病的关系是相当紧密的。贫穷会破坏人的健康状况，而恶劣的健康状况往往又使穷人不得不继续在贫困中挣扎。讨论了造成贫困人群与高收入人群间不平等的健康状况的原因，以及贫困和低收入对于卫生保障费用的影响。文中列出了一组造成卫生保健服务不平等性的原因，并讨论了针对这些现象的一些解决措施。尽管已经有许多评价这些措施的方法和实例，但对于它们的作用还是了解得不够。     

Monitoring equity in vaccination coverage: A systematic analysis of demographic and health surveys from 45 Gavi-supported countries

Objectives(1) To conduct a systematic analysis of inequalities in childhood vaccination coverage in Gavi-supported countries; (2) to comparatively assess alternative measurement approaches and how they may affect cross-country comparisons of the level of inequalities.MethodsUsing the most recent Demographic and Health Surveys (2005–2014) in 45 Gavi-supported countries, we measured inequalities in vaccination coverage across seven dimensions of social stratification and of vulnerability to poor health outcomes. We quantified inequalities using pairwise comparisons (risk differences and ratios) and whole spectrum measures (slope and relative indices of inequality). To contrast measurement approaches, we pooled the estimates using random-effects meta-analyses, ranked countries by the magnitude of inequality and compared agreement in country ranks.ResultsAt the aggregate level, maternal education, multidimensional poverty, and wealth index poverty were the dimensions associated with the largest inequalities. In 36 out of 45 countries, inequalities were substantial, with a difference in coverage of 10 percentage points or more between the top and bottom of at least one of these social dimensions. Important inequalities by child sex, child malnutrition and urban/rural residence were also found in a smaller set of countries. The magnitude of inequality and ranking of countries differed across dimension and depending on the measure used. Pairwise comparisons could not be estimated in certain countries. The slope and relative indices of inequality were estimated in all countries and produced more stable country rankings, and should thus facilitate more reliable international comparisons.ConclusionsInequalities in vaccination coverage persist in a large majority of Gavi-supported countries. Inequalities should be monitored across multiple dimensions of vulnerability. Using whole spectrum measures to quantify inequality across multiple ordered social groups has important advantages. We illustrate these findings using an equity dashboard designed to support decision-making in the Sustainable Development Goals period.     

ON THE CHOICE OF HEALTH INEQUALITY MEASURE FOR THE LONGITUDINAL ANALYSIS OF INCOME‐RELATED HEALTH INEQUALITIES

Changes in rank‐dependent income‐related health inequality measures over time may usefully be decomposed into contributions due to changes in health outcomes and changes in individuals' positions in the income distribution. This paper establishes the normative implications of this type of decomposition by embedding it within a broader analysis of changes in the ‘health achievement’ index. We further show that the choice of health inequality measure implies a particular vertical equity judgement, which may be expressed on a common scale in terms of the concentration index of health changes that would be inequality preserving. We illustrate the empirical implications of this choice by reporting results from a longitudinal analysis of changes in income‐related health inequality in Great Britain using the concentration, the Erreygers and Wagstaff indices of health attainments and the concentration index of health shortfalls. Copyright © 2012 John Wiley & Sons, Ltd.