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Social determinants of stressful events (SE) play an important role in justifying the cause of inequality in the experience of SE. The purpose of this study is to investigate the determinants that impact on inequality in the experience of SE.

The statistical population of this study includes all residents of Tehran. The statistical sample was 5,895 people who were selected by multistage cluster method and were proportional to the population size. The research tool is a researcher-made questionnaire designed to measure SE in Tehran, which includes 11 psychological stressors. The Oaxaca–Blinder decomposing method was used to analyze data.

In a total of 11 psychological SE, in 6 of those events, there was significant inequality in the experience of SE. Concentration Index (CI) of political SE is (CI = −0.27, 95% CI: −0.47, −0.07) and in favor of the rich (pro-rich). Education (OR = 1.60) in poor group and region development in poor and rich (respectively in all of the following) (OR = 0.42–0.73) are the main determinants of inequality in this stressor. CI of neighborhood underdevelopment SE is (CI = −0.47, 95% CI: 0.66, −0.28) and pro-rich. Education (OR = 1.26–1.27) and region development (OR = 1.18–2.24) are the main determinants of inequality in this stressor. CI of livelihood problems SE is (CI = −0.58, 95% CI: 0.68, −0.32) and pro-rich. Education (OR = 1.40) and health status (OR = 1.63) in poor group are the main determinants of inequality in this stressor. CI of future uncertainty SE is (CI = −0.12, 95% CI: 0.34, −0.08) and pro-rich. Gender (OR = 1.22) in poor group and region development (OR = 0.24–0.58) are the main determinants of inequality in this stressor. CI of education problems (CI = 0.19, 95% CI: 0.05, 0.32) and pro-poor. Age (OR = 0.32–0.34) and education (OR = 3.65–3.30) are the main determinants of inequality in this stressor. CI of housing problems is (CI = −0.29, 95% CI: −0.49, −0.08) and pro-rich. Education (OR = 1.31) and region development (OR = 1.64) in poor group are the main determinants of inequality in this stressor.

The first limitation is related to the level of data analysis, and the second limitation is the lack of comprehensive data on social determinants.

Social determinants affecting the formation of inequality in the experience of SE. Some social determinants, such as the level of education and development of the region, play a more prominent role in justifying inequality in the experience of stress between rich and poor groups.

Inequality in the experience of SE is a serious threat to mental and social health. One of the ways to reduce the experience of psychological and social stress is to pay attention to social determinants that play a role in the formation of stress.

This original paper was conducted by examining the effect of social determinants on the formation of inequality in the experience of stress, which draws the serious attention of policymakers.

The purpose of this paper is to decompose the inequities induced by the Nigerian health care financing sources and their effect on the income distribution. Inequities in health care financing sources are of immense policy concern particularly in developing countries such as Nigeria, where high-level income inequality exists, and the cost of medical care is generally financed out-of-pocket (OOP) due to limited access to health insurance.

The Duclos et al. decomposition model provided the theoretical framework for the study. Data were obtained from two waves of the Nigeria General Household Survey (GHS) panel, 2012–13 and 2015–16. The analysis covered 3,999 households in 2012–13 and 4,051 households in 2015–16. Two measures of health care financing: OOP payment and health insurance contribution (HIC) were used. The ability to pay measure was household consumption expenditure.

The major inequity issue induced by the OOP payments was vertical inequity. HICs created the problems of vertical inequity, horizontal inequity and reranking among households. Overall both health care financing options were associated with the worsening of income inequality both at the national and sectorial levels in the country. The operations of the NHIS need to be improved to ensuring improved health care coverage for the poor.

This paper fulfills an identified need to determine the income redistributive effects (REs) of the social health insurance (SHI) contribution at the national, urban and rural locations overtime.

This paper reports an analysis of the evolution of equity in the utilisation of health care in Spain over the period 1987–2001, a time span covering the development of the modern Spanish National Health System. Our measures of utilisation are the probabilities of visiting a doctor, using emergency services and being hospitalised. For these three measures, we obtain indices of horizontal inequity from microeconometric models of utilisation that exploit the individual information in the Spanish National Health Surveys of 1987 and 2001. We find that by 2001, the system had improved insofar as differences in income no longer lead to differences in utilisation given the same level of need. However, tenure of private health insurance leads to differences in utilisation given the same level of need, and its contribution to inequity has increased over time, both because insurance is more concentrated among the rich and because the elasticity of utilisation for the three services has also increased.

This paper uses a unique nationwide survey data derived from the 2003 Utilisation of Health Services Survey (UHSS) in Iran (n=16,935) to analyse inequities of health care utilisation.

Concentration indices are used to measure socioeconomic inequality in actual use of the five types of health services, and in unmet need for two of those types of service (any ambulatory care and hospital admissions). Horizontal inequity indices are employed to examine inequity in ambulatory and hospital care. Generalised linear model (GLM) was employed to investigate factors contributing to the phenomena of “unmet need” and “met unneed”. Moreover, a decomposition analysis of inequality is performed to determine the contributions of each factor to the inequality of “unmet need”.

Results suggest that self‐reported need for ambulatory and inpatient care is concentrated among the poor, whereas the utilisation of ambulatory and inpatient care were generally distributed proportionally. Results of horizontal inequity indices show that the distributions of any ambulatory care and hospital admissions are pro‐rich. The probability of “unmet need” for ambulatory care was higher among wealthier individuals. The decomposition analysis demonstrates that the wealth index, health insurance, and region of residence are the most important factors contributing to the concentration of “unmet need” for ambulatory health care among the poor. Results also illustrate that higher wealth quintiles used more unneeded ambulatory care than their poorer counterparts.

A special characteristic of the UHSS is that it contains questions about the need for medical services use and about actual services use. This characteristic provides an opportunity to measure the inequality of health care consumption against self‐assessed treatment needs, as well as an analysis of which observables are associated with “unmet need”. Moreover, the incidence of health care use when it is reported as not needed can be analysed with this dataset. The analysis of this phenomenon – which we refer to as “met unneed” – is another novel aspect of this work.

The purpose of this paper is to assess the trends of socioeconomic-related inequalities in maternal healthcare utilization in Ghana between 2003 and 2014 and examine the causes of inequalities in maternal healthcare utilization in Ghana.

Data are drawn from three rounds of the Ghana Demographic and Health Survey collected in 2003, 2008 and 2014, respectively. The authors employ two alternative measures of socioeconomic inequalities in health – the Wagstaff and Erreygers indices – to examine the trends of socioeconomic inequalities in maternal healthcare utilization. The authors proceed to decompose the causes of inequalities in maternal healthcare by applying a recently developed generalized decomposition technique based on recentered influence function regressions.

The study finds substantial pro-rich inequalities in maternal healthcare utilization in Ghana. The degree of inequalities has been decreasing since 2003. The elimination of user fees for maternal healthcare has contributed to achieving equity and inclusion in utilization. The decomposition analysis reveals significant contributions of individual, household and locational characteristics to inequalities in maternal healthcare. The authors find that educational attainment, urban residence and challenges with physical access to healthcare facilities increase the socioeconomic gap in maternal healthcare utilization.

There is a need to target vulnerable women who are unlikely to utilize maternal healthcare services. In addition to the elimination of user fees, there is a need to reduce inequalities in the distribution and quality of maternal health services to achieve universal coverage in Ghana.

The purpose of this study is to investigate the status of perceived need, seeking behavior and utilization of health services in the elderly population of Sanandaj (west of Iran).

This is a cross-sectional study conducted on 800 elderly people in Sanandaj. Subjects were selected using multistage sampling and data were collected using self-report questionnaires. A multivariate logistic model with odds ratios (ORs) was used to determine the relationship of independent variables with seeking perceived need. Also, the concentration index was used to measure the inequality in using health services.

The perceived need for outpatient (during the last 30 days) and inpatient health-care services (during the past 12 months) was 69.7% and 29.7%, respectively. Among them, the unmet need for outpatient and inpatient health-care services was 46.6% and 17%, respectively. Having health insurance (adjusted OR 12.08; 95% confidence interval [CI] 1.04–140.11), middle economic status (adjusted OR 5.18; 95% CI 1.30–20.51) and being in an age group of 65–70 years (adjusted OR 7.60; CI 1.42–40.61) increased the chance of seeking inpatient care. Also, being in an age group of 60–65 years (adjusted OR 0.41; 95% CI 0.18–0.95) reduced the chance of seeking outpatient care. There was also a pro-rich inequality in using outpatient health services.

The elderly population suffers from unmet health-care needs, especially in outpatient services. The most important reason for not seeking outpatient and inpatient services was financial barriers and self-medication, respectively. So, designing targeted policies and interventions to address barriers in the conversion of need to demand in the elderly population is essential.

This paper aims to deal with a closer look into the nature and extent of consumer expenditure inequality in India to identify the major contributions those are embedded, particularly after the economic reforms. Relative contributions of major consumption items/sources to the overall expenditure inequality are quantitatively examined in terms of a decomposition exercise. Eventually, the paper investigates the relative marginal effects of expenditure components/sources on overall inequality.

Gini index is used to measure the degree of inequality in consumer expenditure. Contribution of each expenditure sources to overall inequality is estimated by using source decomposition technique of Gini index contributed by Lerman and Yitzhaki.

The study observes that the inequality in consumer expenditure has increased in both the rural and the urban parts of India during the post-reform period. Non-food expenditure is more unevenly distributed, and it has been found to be more pro-rich in nature. Expenditure on cereals and pulses still exhibits higher inequality-reducing effect in rural and urban India. Education and health-care expenses have been inequality-increasing in the country. Contribution of expenditure on miscellaneous consumer services, durable goods, education and health care to the overall expenditure inequality is significantly higher.

The study identifies the capacity of different expenditure sources towards increasing or decreasing the overall inequality which is crucial for better redistributive policies to be adopted to enhance the well-being of the economy in real sense.

The purpose of this paper is to measure inequality in education and examine how socioeconomic factors affect education inequality in Albania and Nepal.

Using large household survey data sets the authors calculate income-related inequality in education and decompose the inequality into factors that determine educational attainment. The decomposition procedure establishes the role played by two sets of factors: elasticities of education demand with respect to its determinants; and inequalities in those determinants. The paper then proposes a new mechanism to quantify the effects of policy simulations regarding income, urbanization, and distance to school on education inequality.

Both the countries show significant inequality in education. Educational attainment in Albania and Nepal is determined by socioeconomic, demographic and geographic factors of which three are particularly significant in affecting inequality – income, urbanization and distance to school.

While schooling for most individuals is largely financed by public subsidy in the countries, attainment is also likely affected by the price of education services and cost of health care. Identification of those factors in the context of more comprehensive data will enable researchers in future to draw firmer conclusions.

The proposed method can help to identify cost-effective and sustainable policies to reduce socioeconomic inequality in education in developing countries.

Reduction in education inequality can lead to higher income and better health which are instrumental in uplifting the poor in developing countries.

This is the first paper to measure education inequality using a concentration index and to propose a new mechanism to show the effect of simulated policies on education inequality.

This chapter attempts to explicitly integrate the idea of reference group when measuring relative deprivation. It assumes that in assessing his situation in society an individual compares himself with individuals whose environment can be considered as being similar to his. By environment we mean the set of people with a similar set of observable characteristics such as human capital, household attributes, and location. We therefore propose to measure relative deprivation by comparing the actual income of an individual with the one he could have expected on the basis of the level of these characteristics. We then aggregate these individual comparisons by computing an index of “distributional change” that compares, on a non anonymous basis, the distributions of the actual and “expected” incomes. At the difference of other approaches to relative deprivation, our measure takes into account not only the difference between the actual and “expected” individual incomes but also that between the actual and “expected” individual ranks. We applied our approach to Moldova, the poorest country in Europe, using a survey that covered a period of six years (from 2000 to 2005). We then observed that our measure of deprivation is well suited to study wage deprivation across genders and is able to proxy subjective deprivation in living standards reported by survey respondents better than conventional measures of relative deprivation.

Recent decades have witnessed a rising interest in the measurement of inequality from a multidimensional perspective. This literature has however remained largely theoretical. This chapter presents an empirical application of a recent methodology and in doing so offers practical insights on how multidimensional inequality can be measured over two attributes (wealth and health) in the developing country context. Following Abul Naga and Geoffard (2006), a methodological framework allowing the decomposition of multidimensional inequality into two univariate Atkinson–Kolm–Sen equality indices and a third term measuring the association between the attributes is implemented. The methodology is then illustrated using data from the World Health Surveys 2002–2003. Specifically, this study presents the first comparative analysis on multidimensional inequality for a set of Middle East and North African (MENA) countries. Results reveal that the multidimensional (in-)equality indices tend to mimic the (in-)equality ordering of the wealth distributions as the latter are always less equally distributed than health. An empirical conclusion that emerges is that reducing the correlation between the attributes may help to reduce overall welfare inequality, specifically when socioeconomic inequality in health is pro-poor. The finding that the correlation between attributes has a significant contribution in the quantification of inequality has important policy implications since it reveals that it is not only wealth and health inequalities per se that matter in the measurement of welfare inequality but also the associations between them.