Search results

Longitudinal data are required to characterise and measure the dynamics of income-related health inequalities (IRHI). This chapter develops a framework to evaluate the impact of population changes on the level of cross-sectional IRHI over time and thereby provides further insight into how health inequalities develop or perpetuate themselves in a society. The approach is illustrated by an empirical analysis of the increase in IRHI in Great Britain between 1999 and 2004 using the British Household Panel Survey. The results imply that levels of IRHI would have been even higher in 2004 but for the entry of youths into the adult population and deaths, with these natural processes of population turnover serving to partially mask the increase in IRHI among the resident adult population over the five-year period. We conclude that a failure to take demographic changes into account may lead to erroneous conclusions on the effectiveness of policies designed to tackle health inequalities.

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.

The purpose of this paper is to assess the association between socioeconomic status and child overweight/obesity in Portugal and to evaluate income-related inequalities in its distribution.

Data come from the last Portuguese National Health Survey (2005/2006) – sample of 6,903 observations. To define child overweight/obesity, the International Obesity Task Force cut-offs for body mass index (BMI) were used; the logistic regression analysis was adopted to explain the risk of overweight/obesity and inequality was measured by means of concentration curve and index.

The evidence obtained points to income-related inequalities in child overweight/obesity favourable to the better-off. The probability of child overweight/obesity was lower for higher income households, but up to a certain point a positive association between income and caloric food intake was found. The concentration index obtained was −0.072 (p-value<0.001).

Some data limitations, no information on: physical exercise; sleeping habits; parents’ education and BMI; age is coded in groups. Although the data are from 2005/2006, the current analysis is useful to future works aiming to discuss the impact of the economic and financial crisis which occurred after these data were collected.

It is important to tailor policies targeting child obesity/overweight in order to tackle not only the prevalence of this disease but also its distribution.

Drawing attention on inequalities in child obesity/overweight in Portugal as the vast majority of studies have focussed on prevalence. The middle income effect is an issue raised in this work which deserves further investigation.

The authors study the difference between multidimensional well-being inequality and income inequality and propose a method to decompose the difference between the Gini coefficients of income and equivalent income (EI), a multidimensional well-being measure that respects individual preferences towards what constitutes a good life. The authors propose a method to decompose the inequality difference into two parts: the vertical and reranking effects. The vertical effect arises from the correlation between income and non-income dimensions, and between income and preferences. The reranking effect arises from the fact that some persons occupy a different position in the EI distribution compared to the income distribution. The authors also propose a detailed decomposition method based on the Shapley value to decompose each of the two effects by non-income dimensions. The authors apply the decompositions using data for 27 countries, considering five non-income dimensions: unemployment, health, housing, crime and environment. The results show that inequality is much higher for EI that the reranking effect accounts for a large part of the inequality difference, and that health is the non-income dimension contributing most to both effects.

What change in the distribution of a population’s health preserves the level of inequality? The answer to this analogous question in the context of income inequality lies somewhere between a uniform and a proportional change. These polar positions represent the absolute and relative inequality equivalence criterion (IEC), respectively. A bounded health variable may be presented in terms of both health attainments and shortfalls. As a distributional change cannot simultaneously be proportional to attainments and to shortfalls, relative inequality measures may rank populations differently from the two perspectives. In contrast to the literature that stresses the importance of measuring inequality in attainments and shortfalls consistently using an absolute IEC, this chapter formalizes a new compromise concept for a bounded variable by explicitly considering the two relative IECs, defined with respect to attainments and shortfalls, to represent the polar cases of defensible positions.

We use a surplus-sharing approach to provide new insights on commonly used inequality indices by evaluating the underpinning IECs in terms of how infinitesimal surpluses of health must be successively distributed to preserve the level of inequality. We derive a one-parameter IEC that, unlike those implicit in commonly used indices, assigns constant weights to the polar cases independent of the health distribution.

The purpose of this paper is to propose the application of Gini, Theil and concentration indices for measuring inequality in water usage.

Gini coefficients and Theil indices have been used to estimate the overall inequality in domestic water use in a sample of 30 countries around the world. Along with Theil’s L (unweighted) index, liters per capita per day and gross national income weighted Theil index have also been estimated. Theil indices have been further disintegrated into within- and between-group inequalities. Concentration curve is also constructed to study the inequality in water use in accordance to the countries’ economic standing.

Domestic water use is high among the well-off countries considered in the study. Also, the Theil indices indicate that between group inequality contributes more to the overall inequality. It is observed that Theil indices, which consider only per capita water usage and can be decomposed, give a better insight into the existing inequality.

Different approaches were used to quantify inequality. The choice of index depends on the context of the study. The proposed approaches can contribute to planning of sustainable water management and development policies.

There is a dearth of metrics for quantifying inequality in water access or use. The study presents the application of indices, widely used in quantifying inequality in access to other resources such as income and energy, in assessing water inequality.

We compare two approaches to measuring inequity in the health distribution. The first is the concentration index. The second is the calculation of the inequality in an overall measure of individual well-being, capturing both the income and health dimensions. We introduce the concept of equivalent income as a measure of well-being that respects preferences with respect to the trade-off between income and health, but is not subjectively welfarist since it does not rely on the direct measurement of happiness. Using data from a representative survey in France, we show that equivalent incomes can be measured using a contingent valuation method. We present counterfactual simulations to illustrate the different perspectives of the approaches with respect to distributive justice.

India has shown good progress in maternal health outcome indicators. However, an area for improvement is to ensure all deliveries take place in institutions under the supervision of skilled birth attendants. This paper attempts to identify the factors that affect institutional deliveries using nationally representative National Family Health Survey (NFHS) data. Further, the authors investigate the factors contributing to the wealth-based inequality in institutional deliveries.

To address the first aspect of identifying the factors associated with undergoing an institutional delivery, the authors have used logistic and multinominal logistic models. The explanatory variables are broadly socio-economic indicators of the mother and a few other household characteristics. Further, the concentration index and regression-based decomposition were used to carry out an inequality analysis in the institutional deliveries across different wealth groups.

The authors found that women belonging to poor households, backward social groups and rural areas have significantly fewer odds of undergoing an institutional delivery. Age and education level of the mother, number of antenatal visits during pregnancy and place of residence (urban/rural) have contributed to the inequality in institutional deliveries in 2005–2006. However, the inequality due to these factors went down drastically in 2015–2016.

To the best of the authors' knowledge, this study is a distinct attempt to use pooled data of the NFHS-3 [2005–2006] and NFHS-4 [2015–2016] in identifying factors contributing to a woman undergoing an institutional-based delivery. The study also decomposes the wealth-based inequality in the factors contributing to having an institutional delivery and analyses the contributions to inequality across the two time periods.

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.