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Equality of Opportunity in Health and Healthcare

Summary and Keywords

Recent developments in the analysis of inequality in health and healthcare have turned their interest into an explicit normative understanding of the sources of inequalities that calls upon the concept of equality of opportunity. According to this concept, some sources of inequality are more objectionable than others and could represent priorities for policies aiming to reduce inequality in healthcare use, access, or health status.

Equality of opportunity draws a distinction between “legitimate” and “illegitimate” sources of inequality. While legitimate sources of differences can be attributed to the consequences of individual effort (i.e. determinants within the individual’s control), illegitimate sources of differences are related to circumstances (i.e. determinants beyond the individual’s responsibility).

The study of inequality of opportunity is rooted in social justice research, and the last decade has seen a rapid growth in empirical work using this literature at the core of its approach in both developed and developing countries. Empirical research on inequality of opportunity in health and healthcare is mainly driven by data availability. Most studies in adult populations are based on data from European countries, especially from the UK, while studies analyzing inequalities of opportunity among children are usually based on data from low- or middle-income countries and focus on children under five years old.

Regarding the choice of circumstances, most studies have considered social background to be an illegitimate source of inequality in health and healthcare. Geographical dimensions have also been taken into account, but to a lesser extent, and more frequently in studies focusing on children or those based on data from countries outside Europe. Regarding effort variables or legitimate sources of health inequality, there is wide use of smoking-related variables.

Regardless of the population, health outcome, and circumstances considered, scholars have provided evidence of illegitimate inequality in health and healthcare. Studies on inequality of opportunity in healthcare are mainly found in children population; this emphasizes the need to tackle inequality as early as possible.

Keywords: health, equality of opportunity, inequality, circumstances, effort, health economics

Introduction

Since the call for health equity by the World Health Organization (Commission on Social Determinants of Health, 2008), the reduction of health inequalities has been the main objective of public health policies worldwide. The health economics literature in that context has provided the conceptual foundations for the measurement of inequality and inequity in health and healthcare; an overview of the methods was provided by Wagstaff and Van Doorslaer (2000) and then extensively summarized in Fleurbaey and Schokkaert (2011). This measurement framework has helped to assess the existence and to evaluate the magnitude of inequality in health as well as in healthcare delivery, access, and financing. Beyond the measurement of inequality, it has also provided a methodology with which to decompose inequality within determining factors (Wagstaff & Van Doorslaer, 2000; Mackenbach et al., 2008). While horizontal equity (i.e., those with the same healthcare needs get the same care/access/health) and to a lesser extent vertical equity (i.e., those with unequal needs receive unequal care/access/health) were at the core of this literature, the normative viewpoint was implicit inasmuch as it considered that socioeconomic differences in health or healthcare outcomes were particularly unjust. Recent developments in the analysis of health inequality have turned their focus to an explicit normative understanding of inequalities and their health determinants, and have called upon the philosophical literature regarding social justice and especially the concept of equality of opportunity (Dworkin, 1981a; Arneson, 1989; Cohen, 1989; Roemer, 1998; Barry, 2005; Fleurbaey, 2008). According to this concept, some sources of inequality are more objectionable than others and could represent priorities for policies aiming at reducing inequality in healthcare use or access, or in health status. Equality of opportunity draws a distinction between “legitimate” and “illegitimate” sources of inequality. While legitimate sources of differences can be attributed to the consequences of individual effort (i.e., determinants within people’s control), illegitimate sources of differences are related to circumstances (i.e., determinants beyond people’s control). In the specific context of healthcare, the concept of equality of opportunity consists in a moral right to healthcare according to which healthcare is a matter of justice and it is the responsibility of the public health sector to tackle health inequities and provide care according to needs (Daniels, 1985). Therefore the crucial question for equality of opportunity (EOP) in healthcare is to investigate whether the factors explaining the differences in healthcare use or access are ethically justified (Fleurbaey & Schokkaert, 2011). Typically, differences in healthcare use that reflect differences in health status are likely to be justified, so health needs lead to legitimate sources of inequality. On the other hand, differences in healthcare use or access that are due to factors unrelated to healthcare needs (e.g., socioeconomic status) are considered as illegitimate sources of inequality, and thus as inequality of opportunity in healthcare.

Following the publication of the World Bank Development Report (World Bank, 2006), which brought the question of inequality of opportunity to the forefront (Rosa Dias & Jones, 2007), the last decade has seen the rapid growth, in developed and developing countries, of empirical research using this concept at the core of its approach.

This chapter aims to give the first comprehensive survey of the empirical work on equality of opportunities in health and healthcare published so far. Reviews of empirical work on equality of opportunity as related to other outcomes are already available (see Brunori, Ferreira, & Peragine, 2013; Roemer & Trannoy, 2014; Ferreira & Peragine, 2016; Ramos & Van de Gaer, 2016). Our aim is to provide a state-of-the-art critical survey of the extensive literature that has recently been produced on inequality of opportunity in health and health-related outcomes. In February 2018, the most relevant literature databases1 were searched; this included material dating from the databases’ inception dates to the present. Searches were designed to identify studies by combining the search term “inequality” or “inequalities” with the terms “health” and “opportunity” or “opportunities.” Full details of the search strategy are presented in Appendix A. In addition, gray literature was sought by means of citation-searching Google Scholar for the first published papers on the concept of inequality of opportunity in health (Rosa Dias, 2009; Trannoy, Tubeuf, Jusot, & Devaux, 2010). To be eligible for inclusion, papers had to use the concept of equality of opportunity as the framework for the study. Studies that only touched upon the concept of opportunity in health and in healthcare in their conclusion, and did not offer an interpretation of the results from an equality-of-opportunity perspective, were excluded.

A wide range of literature has looked into the importance of early life conditions for health over the life course and the various mechanisms by means of which social background can influence health status (see for instance Barker, 1996; Wadsworth, 1999; Case, Lubotsky, & Paxson, 2002; Currie & Stabile, 2003; Case, Fertig, & Paxson, 2005; Blane, Netuveli, & Stone, 2007; Kuh et al., 2009; Lindeboom, Llena-Nozal, & Van der Klaauw, 2009; Tubeuf & Jusot, 2011; Tubeuf, Jusot, & Bricard, 2012; Agahi, Shaw, & Fors, 2014; Burkhauser, Hahn, Lilliard, & Wilkens, 2016; Shippee, Rowan, Sivagnanam, & Oakes, 2015). This literature, although not labeled as relating to the concept of equality of opportunity in health, as the studies on which it is based largely predate that practice, could be considered as empirical research on the importance of circumstances that are not chosen by the individual. Similarly, research on the correlation between health statuses across generations (Ahlburg, 1998; Strauss & Duncan, 2008) and the intergenerational transmission of health-related outcomes such as obesity (Zhang, Zheng, Zhang, & Wang, 2011; Classen & Thompson, 2016; Dolton & Xiao, 2017), health conditions (Thompson, 2014, 2017), or physical activity (Kantomaa, Tammelin, Nayha, & Taanila, 2007) are also sources of primary research on inequality of opportunity, although they do not name this concept. However, such examples, which have mostly appeared in the fields of public health and social epidemiology, were only touched upon when the concept of inequality of opportunity in health had been clearly used as a framework for the analysis.

The chapter is organized as follows. Section “The Framework of Equality of Opportunity” presents the framework of equality of opportunity in health, especially for empirical research. In Section “A Review of the EOP in Health and Healthcare Empirical Literature,” the published and unpublished literature currently available on the assessment of inequality of opportunity in health and healthcare is presented and summarized. Two distinct dimensions appear to divide the studies discussed: whether they were about children and younger populations or not, and whether the methodological perspective used was ex ante or ex post. We have therefore divided the review into three main contexts of assessment of inequality of opportunity: (i) Section “Ex Ante Inequality of Opportunities in Health and Healthcare,” (ii) Section “Ex Post Inequality of Opportunities in Health and Healthcare,” and (iii) Section “Inequality of Opportunity in Child Health and Healthcare.” In each of these perspectives the population of interest, the health and healthcare outcomes, and the methods are described. Section “Critical Discussion” of the methods and results of this literature concludes and identifies apparent gaps and expected avenues for future research.

The Framework of Equality of Opportunity

From Inequality to Inequality of Opportunity

The first empirical contributions on inequality in health and healthcare provided insight into the determinants of such inequality, especially the relationship between income and other socioeconomic determinants in the context of health and healthcare use or access. The pioneering work of the ECuity2 and Eurothine3 collaboration projects has dominated empirical research on the magnitude of inequality and its determining factors. While the ECuity project initiated the use of the concentration index and its decomposition, which was then followed with numerous examples of empirical work measuring inequality in health, healthcare access, and healthcare delivery in developed and developing countries, the Eurothine project aimed at evaluating the effectiveness of interventions and policies implemented to reduce inequality in health and healthcare in various European countries. Following the lead of economics research that had demonstrated the importance of social determinism, empirical research in health economics later evolved toward the understanding of mechanisms that could explain the construction of social-health inequality over the lifespan. Scholars have especially turned their interest to the role played by childhood conditions on the health of children and adults. At the same time, the issue of responsibility has become more and more predominant in the literature in social choice and political philosophy, through the concept of luck egalitarianism. From a focus on the objective of equalizing health outcomes across socioeconomic groups by means of positive approaches, or ensuring an equal access to care for people with equal needs, research has moved toward normative discussions on the sources of inequality in health and healthcare with a focus on the importance of fairness. The outcome focused upon when analyzing inequalities thus became “opportunities.”

A Definition of Inequality of Opportunity

Based on the philosophical literature on inequality of opportunity (Dworkin, 1981a; Arneson, 1989; Cohen, 1989; Roemer, 1998; Rawls, 1999; Roemer, 2002; Fleurbaey, 2008), there is a global agreement in the economic literature on the necessity of taking into account the determinants of any outcome in order to judge the legitimacy of differences in this outcome between members of a given society. The concept of equality of opportunities initiated by Roemer (1998) relies on the distinction between sources of inequality. The share of inequality related to health determinants that are beyond individual responsibility, known as circumstances, are considered as the most unacceptable and are recognized as inequality of opportunity. On the other hand, the share of inequality related to determinants that are freely chosen by individuals according to their preferences, namely those associated with effort, may be considered as legitimate inequality. It is worthwhile underlining that the partition between effort and circumstances is sometimes labeled as legitimate versus illegitimate sources of inequality, or ethically acceptable versus ethically unacceptable, or even equitable or fair versus inequitable or unfair. Disagreement as to which sources are considered as legitimate/effort and illegitimate/circumstances is common. Most studies on inequality of opportunity in health and healthcare consider that social and family background constitute relevant circumstances, since individuals cannot be held responsible for their birth lottery. In particular, they cannot be held responsible for their parents’ educational level, occupation, or living conditions during their childhood, or parental health-related characteristics, such as genetic inheritance, lifestyles, or healthcare habits. On the contrary, effort is difficult to observe and measure; nevertheless, there is a consensus in the health field that individuals’ lifestyle choices, such as not smoking, having a balanced diet, not drinking too much, or using preventative healthcare can be considered as examples of individual effort being made for health and healthcare. Lifestyles and healthcare habits represent individual choice and effort invested in health capital. It appears relevant here to underline the importance of referring to an “age of consent” that acts as a threshold below which people cannot be held responsible for their efforts (Arneson, 1989). Individuals can only be held responsible for the lifestyles they have consciously and fully chosen, which is likely to be the case when lifestyles are initiated after a certain age (e.g., 15 years old). Brunori (2017) suggests that a good benchmark for such a discussion is the legal literature on criminal responsibility. In the EOP literature, obesity or healthcare utilization during childhood are more often viewed as children’s health outcomes or as childhood circumstances than as legitimate sources of inequality within a children population.

While the key idea of responsibility underlying the measurement of inequality of opportunity is easier to conceptualize when the outcome of interest is health status and lifestyles are taken as proxies for effort, the transposition to the concept of inequality of opportunity in healthcare is not straightforward. Equality-of-opportunity theory distinguishes between illegitimate inequality, which is due to non-responsibility characteristics and legitimate inequality, due to responsibility characteristics (Trannoy, 2016). The issue is how to define variables that one can be held responsible for in the context of healthcare access or use. Healthcare use is determined by healthcare needs and availability, which both represent circumstances for which individuals cannot be held responsible. However healthcare use is also likely to express individuals’ healthcare habits and preferences. In social justice theory, there are two competing views on how preferences should be treated. Some philosophers, following Ronald Dworkin (1981a, 1981b), consider that preferences should be fully respected, so that individuals are considered responsible for them, while others like Gerard Cohen (1989) see individuals as only responsible for what they can control. This debate is of particular importance for equality of opportunity in healthcare outcomes where the crucial question is to investigate whether the factors explaining differences in healthcare use or access are ethically justified (Fleurbaey & Schokkaert, 2011).

Theoretically, achieving equality of opportunity implies respecting two basic principles (Fleurbaey, 2008): the compensation principle, which demands that inequality due to circumstances be eliminated or compensated for, and the liberal reward principle, which necessitates that any efforts made by individuals be rewarded, and respected, when drawing up redistribution policies. Despite this general agreement, the measurement of equality of opportunity still entails addressing many theoretical, methodological, and empirical questions (Fleurbaey & Schokkaert, 2011; Brunori et al., 2013; Roemer & Trannoy, 2014; Ramos & Van de Gaer, 2016).

Two Approaches for Measuring of Inequality of Opportunity

Following the typology proposed by Fleurbaey and Peragine (2013) and used by Ramos and Van de Gaer (2016), Li Donni, Peragine, and Pignataro (2014), and Roemer and Trannoy (2014), two different approaches have been proposed to the formulation of the compensation principle: the ex ante and the ex post approaches. The ex post approach consists of looking at differences in the actual outcome between individuals with the same responsibility (effort) characteristics, and finds that there is equality of opportunity if all those who exert the same effort obtain the same outcome. The ex ante approach, in contrast, suggests that there is equality of opportunity if all individuals face the same set of opportunities, regardless of their circumstances.

The ex post approach requires the observation of the efforts that are to be rewarded or the imposition of very restrictive assumptions about the relationship between responsibility characteristics and outcomes. Conversely, the ex ante approach only requires the observation of circumstances, since inequality of opportunity is identified by comparing outcome distributions between types of circumstances. This second approach is less data hungry since it only allows consideration of a limited set of relevant factors, independent of individual responsibility. Fleurbaey and Peragine (2013) have shown the incompatibility of the ex post and the ex ante approaches to the compensation principle. While ex post compensation and liberal reward are often found to be inconsistently related to the timing of the choice to make an effort by the individual, ex ante compensation and liberal reward are consistent. The choice between the ex ante and ex post approaches is driven either by data availability or ethical viewpoint. Effort could be regarded as being unobservable by nature, hence when measurements of effort are used, the choice of those variables must be well justified and it will be necessary to demonstrate that individuals are fully responsible for that effort.

The Correlation Between Effort and Circumstances

An issue in this context was highlighted in Jusot, Tubeuf, and Trannoy (2013); this brought to the forefront the open debate in the literature on the relationship between effort and circumstances, which cannot be assumed to be independent of each other. The key matter in this context is the precise definition of effort, which should be rewarded, and the definition of circumstances, which should be compensated for. The original debate on the correlation between effort and circumstances was between John Roemer and Brian Barry in the field of education (Roemer, 1998, p. 22; Barry, 2005). The context was a debate about the case of Asian students. In Roemer’s words, such students “generally work hard in school and thereby do well because parents press them to do so. The familial pressure is clearly an aspect of their environment outside their control.” Roemer argued that an ideal equal-opportunity policy would respect individual effort through an approach whereby “we could somehow disembody individuals from their circumstances” (Roemer, 1998, p. 15). As a consequence, the extra effort of Asian students should not be rewarded because it is determined by a circumstance outside their control. Conversely, Barry argued that nevertheless, “the fact that their generally high levels of effort were due to familial pressure does not make their having expended high levels of effort less admirable and less deserving than it would have been absent such pressure.” From this point of view, which is the mainstream view in the literature on incentives (Yellen, 1984), the extra effort of Asian students should be fully rewarded and the lack of familial pressure on other types of students should not be compensated for. When transposing this debate to the field of health, lifestyles—such as having a balanced diet, doing exercise, not smoking, or not drinking too much—are often considered as relevant efforts, as they constitute causal determinants of health status. The idea that lifestyles are freely chosen individual behaviors is debatable, in particular because they are likely to be influenced by the family and social environment during childhood as well as by genetic characteristics and preferences. The Barry/Roemer debate in health would then ask about the legitimacy of, for instance, holding sons of smokers less responsible for their own smoking than the sons of nonsmokers. While, for Barry, this distinction is irrelevant, Roemer considers that the share of smoking, which can be attributed to family and social background, is a circumstance and not an effort. This distinction is typically meaningful for the ex post approach; however, an ex ante approach, whereby only circumstances are observed, must adopt a Roemerian viewpoint.

The Equality of Opportunity Principles across Generations

Another challenge in defining effort is identifying “whose” effort it is; as Roemer and Barry respectively observe, “Asian children (. . .) do well because parents press them to do so” and “their generally high levels of effort [are] due to familial pressure.” The transmission of values through parental effort results in what manifests itself in the effort exerted by the next generation and if one views familial pressure on children to be educated as a parental effort, the definition of circumstances to be compensated for is less obvious. Jusot et al. (2013) underline the impossibility of respecting the principles of compensation and natural reward for all generations. If one gives precedence to the younger generation in the application of the two equality-of-opportunity principles of compensation and liberal reward, then one should consider that the whole initial background consist of circumstances, including parental effort, independently of the link with children’s effort. On the other hand, if one gives precedence to the past generation in the application of the two equality-of-opportunity principles, then one should consider that parental effort must be respected whatever its consequences to the next generation. This latter position corresponds to that of Swift (2005), who argued To the extent that the reproduction of inequality across generations occurs through the transmission of cultural traits, it does so substantially (though not exclusively) through intimate familial interactions that we have reason to value and protect. Preventing those interactions would violate the autonomy of the family in a way that stopping parents doing spending their money on, or bequeathing money to their kids would not” (Swift, 2005; Sørensen, 2006). From Swift’s point of view, family is an association, and following on Rawls’ justice theory, the “basic liberties,” including among them freedom of association, take lexical priority over fair equality of opportunity and the principle of difference (Rawls, 1999). Transposed to the fields of health and healthcare, it is easy to see that the way parents use healthcare, especially in terms of health checks and preventative care for children, makes children more likely to use it in a similar way as an adult; this might also be the case with diet, physical activity, or smoking and drinking behaviors.

Empirical Approaches

The empirical literature in equality of opportunity in health and healthcare calls upon two types of methodologies: non-parametric and parametric, which are sometimes coupled in studies. The non-parametric approach follows from the methodology proposed by Lefranc, Pistolesi, and Trannoy (2009) in order to identify inequality of opportunity in income. It relies upon the use of dominance criteria and bilateral tests and compares cumulative distribution functions of outcomes conditional to categories of circumstances (types) of individuals and groups with the same effort (tranches). On the other hand, the parametric approach relies on econometric modeling and is used to identify inequality of opportunity by investigating the association between circumstances and outcome. Parametric studies adopting an ex ante approach simply estimate a reduced-form model in order to identify differences in health opportunities related to circumstances, independently from the influence of any unobserved efforts, as suggested by Ferreira and Gignoux (2011) and Trannoy et al. (2010). On the other hand, methodologies used in the ex post approach vary according to the normative position adopted regarding the correlation between efforts and circumstances or legitimate and illegitimate sources of inequality. Health outcomes can simply be regressed on observed circumstances and observed efforts or auxiliary equations focusing on the efforts on their own or on more complex structural modeling can also be considered. In the ex ante approach, in which effort is by definition not observed, the literature avoids the problem of lacking effort indicators by combining an ex post approach to inequality of opportunity with a concept of relative effort, whereby two people belonging to different types are deemed to have exerted the same effort if and only if they are in the same percentiles of their respective (and different) conditional distributions.

If empirical studies in EOP in health initially tested the existence of inequality of opportunities in health, recent studies go beyond assessment and propose a quantification of the inequality of opportunities in health. Two broad types of measures are used, direct and indirect ones, as emphasized in the literature (Fleurbaey & Schokkaert, 2011; Brunori et al., 2013; Ramos & Van de Gaer, 2016). On one hand, direct measures assess how great the inequality is when only the share of inequality that is attributable to circumstances remains. Empirically, it consists of estimating the inequality using a counterfactual outcome distribution in which all inequalities due to differences in effort have been eliminated. The direct unfairness proposed by Fleurbaey and Schokkaert (2009) is a typical direct measure of inequality of opportunities, which is consistent with the ex ante approach to compensation. Direct unfairness evaluates the level of inequality that would exist if all individuals chose to exert the same reference level of effort. On the other hand, indirect measures assess how much inequality remains after opportunities have been equalized. Empirically, this indirect approach often consists of estimating the level of inequality of opportunity by comparing inequality in the actual outcome distribution to inequality in a counterfactual outcome distribution whereby all individuals would face the same circumstances. The use of this measurement method is, however, debatable (Schokkaert, 2018), since different distributions could lead to the same measure of inequality of opportunities. The fairness gap (Fleurbaey & Schokkaert, 2009) is a preferable indirect measure of inequality of opportunities and quantifies the inequality in the distribution as the distance between the observed outcome and the outcome that would exist if all individuals had the same reference set of circumstances. The fairness gap corresponds to the ex post compensation principle.

A Review of the Empirical Literature on Equality of Opportunity in Health and Healthcare

The literature search yielded 415 potentially relevant studies, and 228 of these were identified as citing the two seminal papers published on the empirical study of inequality of opportunity in health (Rosa Dias, 2009; Trannoy et al., 2010). After removal of duplicates,4 401 references were identified for screening. Titles and abstracts were screened, including studies in which equality of opportunity appeared to be used as the analysis framework, and EndNote software was used to manage references. After screening, 242 studies were excluded and 63 possibly relevant studies were retrieved for full-text assessment. After the full-text review, 44 of these studies were included in the analysis and 19 were excluded. Studies were excluded for the following reasons: 13 of them only focused on intergenerational transmission of health, lifestyles, or health-related outcomes, and did not utilize equality of opportunity in the analysis or as an interpretation framework; 4 were older versions of a published study that had already been included; and 2 did not use a health or healthcare outcome. A PRISMA chart describing the inclusion and exclusion process can be found in Figure 1.

Equality of Opportunity in Health and HealthcareClick to view larger

Figure 1. Flow diagram of excluded and included studies

Of the 44 studies included in the review, 16 were based on data from a European country (U.K. n=7, France n=3, and one each in Luxembourg, Italy, the Netherlands, Norway, Spain, and England); 10 from Africa or the Middle East (Tunisia n=2, Togo n=2, Egypt n=2, and one each in Morocco, Ethiopia, Israel, and South Africa); 4 from Asia (China n=2, Indonesia n=1, India n=1); 6 from Central or South America (Chile n=2, Columbia n=2, Brazil n=1, Mexico n=1); 3 focused on the United States and/or Canada; and 5 used data from multiple countries. The studies included in this review spanned a period of 9 years (2009–2018) and the majority had been published after 2013.

It emerged that a logical way of grouping the studies would be by population of interest and empirical method. Of the 44 studies examined, two thirds focused on adult populations, of which approximately one half used an ex post approach, 38% took an ex ante approach, and four studies (14%) combined ex ante and ex post perspectives. The final third of the 44 studies focused on children’s health-related outcomes. The distinction between the ex ante and ex post approaches makes less sense among this population of interest since it is below the age of consent and thus the subjects could not be considered as responsible for their behaviors. The review is divided into three subsections. First, it summarizes and discusses the studies that used an ex ante perspective for the analysis of inequality of opportunity; then it focuses on studies that adopted an ex-post perspective; and, finally, on empirical work on inequality of opportunities in children’s health and healthcare.

Ex Ante Inequality of Opportunities in Health and Healthcare

The 15 studies that measured inequality of opportunities in health and healthcare using an ex ante perspective are shown in Table 1.

Table 1. Ex ante Analyses of Equality of Opportunity (EOP) in Health and Healthcare.

Study reference

Country

Type, year of data

Study population

Sample size

Health or healthcare outcome

Sources of illegitimate inequalities

Other control variables

Methods

Barbosa, 2016

Brazil

PNAD1 2008

(1) General population

(2) Women 15+

391,868 individuals

110,280 women

Physician visits

Women’s preventive care: mammography, cervical screening

Education

Ethnicity

Region of residence

Household income

Age and sex

SAH

Rural/urban residence

Employment status

Family type

Health insurance coverage Preferences related to medical care

Parametric regression

Fleurbaey and Schokkaert framework

Direct unfairness and fairness gap

Concentration and horizontal indices

Healthcare advantage rank

Bricard, 2013

France

2010 ESPS2

16+

4,608

Healthcare habits during adulthood

Mother’s and father’s education

Mother’s and father’s social class

Family financial situation

Mother’s and father’s health

Region of birth

Parental healthcare habits

Childhood physician density

Age and sex

SAH

Functional limitations

Chronic conditions

Education

Social status

Income

Marital status

Region of residence

Physician density

Parametric regression

Two steps: long-term effect of parental habits during childhood and on healthcare use of their descendants

Chen, 2015$

USA

NLSY793 longitudinal survey

40+

3,505

SAH (1-poor to 5-excellent)

Physical component score

Mental component score

Mother and father’s education

Race

Household characteristics

Incidence of health shocks

Disability and health limitations

Age and sex

Education

Income

Smoking initiation, duration, current and past

Number of daily cigarettes

Non-parametric approach

Stochastic dominance

Kolmogorov-Smirnov test

EOP by type

Fajardo-Gonzalez, 2016

Columbia

2010 LSSM4 survey

Head of household 25-65

2,253

SAH (poor, fair, good, excellent)

Parental educational level

Household socioeconomic assets ownership at age 10

Parental vital status

Rural/urban residence

Region of birth

Ethnicity

Years of education

First- or second-order stochastic dominance and test

Parametric regression

Shapley decomposition

Gini-Opportunity Index

Gallardo, Varras & Gallardo, 2017

Chile

2010 Chilean National Health Survey

General population 20+

4,404

SAH (poor, fair, good, very good, excellent)

Mother’s education

Family income

Rural/urban residence

Region of birth

Non-parametric approach

Second-order stochastic dominance and test

Gigliarano & D’Ambrosio, 2013

Italy

2009 IT-SILC5

General population 16+

43,636

SAH (very good, good, fair, bad, very bad)

Region of residence

Education level

Income

Non-parametric

Kolmogorov-Smirnov tests

Jones, Rice, & Rosa Dias, 2012

UK

1958 NCDS6 birth cohort

From birth to age 46

17,000 (original sample)

SAH at age 46 (excellent, good, fair, poor, very poor)

Mental illness at age 42

Chronic illness/disability at age 46

Smoking at age 42

Alcohol consumption at age 33

Fried food at age 33

Teenage pregnancy

Type of primary and secondary schools

Childhood health (morbidity, height, weight)

Parents’ SES

Parents’ education

Incidence of household financial difficulties

Neighborhood during childhood and adolescence

Cognitive and non-cognitive abilities

Happiness at school

Educational attainment

Health-related lifestyles (smoking, alcohol, food consumption,

Non-parametric approach

First order stochastic dominance and test

Applied testable conditions for stochastic dominance

Jusot, Mage, & Menendez, 2014

Indonesia

IFLS7 2007 wave

40+

7,224

A continuous health indicator using a regression explaining SAH as a function of several objective and quasi-objective health variables (biomarkers, ADL8 and IADL9, CES-D10)

Mother’s and father’s education

Parental health status

Religion

Language spoken

Rural/urban residence

Region of birth

Age and sex

Educational level

Marital status Immigration status

Occupational status

Non-parametric approach First order stochastic dominance and test

Parametric regression

Variance decomposition

Lazar, 2013$

Israel

2003 Israeli Social Survey

20+

3,011

SAH (not good at all, not so good, good, very good)

Father’s education

Father’s country of birth (Israel, Europe, America)

Age and gender

Religion

Ex ante approach: Type approach classifying population by circumstances

Parametric regression Decomposition of overall inequality

Li Donni, Peragine, & Pignataro, 2014$

UK

BHPS11 2000-2005 longitudinal survey

55+

Between 2,519-2,631

SAH (very poor, poor, fair, good, excellent) considered with very poor/poor

Father’s SES

Father’s vital status

Ethnicity

Country of birth

Any accidents

Smoking

Education level

Age and gender

Type approach classifying population by circumstances

Parametric regression

Decomposition of overall inequality using the Atkinson equality index

Ovrum & Rickertsen, 2015

Norway

Norwegian Monitor Survey 2005-2011

25-74

10,591

SAH (very bad, bad, fair, good, very good health)

Eating fruits and vegetables

Physical activity

Fish consumption

Smoking

Obesity

Parents’ educational level

Family economic situation when 10-15 years old

Age and sex

Marital status Educational level

Social occupation

Psychological traits

Parametric regression

Decomposing overall and socioeconomic inequality in health and lifestyles

Gini indices, education- and income-related concentration indices

Pasqualini, Lanari, Minelli, Pieroni, & Salmasi, 2017$

14 European countries

SHARE12 and ELSA13 2005, 2007 and 2008

49+

32,165 SHARE12 and 10,281 ELSA13

SAH (Excellent, very good, good, fair, poor)

Body Mass Index

More than 3 chronic conditions

Number of books in the household at age 10

Financial hardship

Average level of income in the country of residence

Income inequality within the country of residence

Age and sex

Marital status

Employment status, Educational level

Parametric regression

Decomposition of the adjusted R-squared of the models

Pinilla, Lopez-Valcarcel, & Urbanos-Garrido, 2017

Spain

EFF14 2002, 2005, 2008, and 2011 longitudinal survey considered pooled

28-86

Approximately 15,000 people

SAH (very good, good, acceptable, poor, very poor) [also education and occupation as outcome with generalized residuals]

Mother’s and father's occupation

Familys SES"

Age and sex

Educational level

Occupational status

Household income

Age cohort

Parametric regression

Sequential models

Pathway models

Rivera, 2017

Columbia

2010 ELCA15

17+

10,164

EQ-5D VAS16

Medical characteristics adjusted EQ-5D VAS16

EQ-5D score

Race

Birthplace

Region of residence

Household structure

Mother’s and father’s education

Mother and father’s chronic illness

Mother and father’s vital status

Occupation

Education

Household wealth

Age and sex

Parametric regression

Ex ante measure of inequality of opportunities in health in Barry and Roemer approaches

Gini coefficient

Fields’ decomposition of total unjust inequalities

Trannoy , Tubeuf, Jusot, & Devaux, 2010

France

2004 French SHARE12

49+

2,666

SAH (very poor, poor, fair, good, v. good)

Mother’s and father’s vital status, relative longevity

Mother’s and father’s jobs

Education

Professional status

Age and sex

Non-parametric approach

First-order stochastic dominance and test

Parametric regression

Sequential models

Pathway models

Gini and Erreygers indices

($:) References including both ex ante and ex post approaches

(1) PNAD: Pesquisa Nacional por Amostra de Domicílios

(2) ESPS: Enquête Santé et Protection Sociale

(3) NLSY79: National Longitudinal Survey of Young 1979

(4) LSSM: Living Standards and Social Mobility

(5) IT-SILC: Italian data from the European Survey of Income and Living Conditions

(6) NCDS: National Child Development Study

(7) IFLS: Indonesian Family Life Survey

(8) ADL: Activities of Daily Living

(9) IADL: Instrumental Activities of Daily Living

(10) CES-D: Center for Epidemiologic Studies Depression Scale

(11) BHPS: British Household Panel Survey

(12) SHARE: Survey on Health, Ageing and Retirement in Europe

(13) ELSA: English Longitudinal Survey of Ageing

(14) EFF: Encuesta Financiera de las Familias

(15) ELCA: Encuesta Longitudinal de Colombia

(16) EQ-5D VAS: EuroQoL 5 Dimensions Visual Analogue Scale with values between 1 and 100, where 1 represents the worst health status and 100 represents the best.

More than half of the studies focused on European countries: two from the U.K. (Jones, Rice, & Rosa Dias, 2012; Li Donni et al., 2014), two from France (Trannoy et al., 2010; Bricard, 2013), one each from Italy (Gigliarano & D’Ambrosio, 2013), Spain (Pinilla, Lopez-Valcarcel, & Urbanos-Garrido, 2017), and Norway (Ovrum & Rickertsen, 2015), while one study used data from 14 European countries that participated in the Survey on Health, Ageing and Retirement in Europe (SHARE) and the English Longitudinal Study of Ageing (ELSA) (Pasqualini, Lanari, Minelli, Pieroni, & Salmasi, 2017). Outside Europe, one study focused on data from the United States (Chen, 2015), and one on Israel (Lazar, 2013). Finally, only five studies focused on low- or middle-income countries: four on South America, two on Columbia (Fajardo-Gonzalez, 2016; Rivera, 2017), one on Brazil (Barbosa, 2016), one on Chile (Gallardo, Varas, & Gallardo, 2017), and one on Indonesia (Jusot, Mage, & Menendez, 2014).

Most studies considered health status as the outcome of interest (87%) while only two papers used healthcare outcomes such as healthcare habits, physician visits, and preventative care for this. Studies of inequality of opportunity in health mainly focused on self-assessed health (SAH) (73%) while four studies considered various scores as health outcomes. The Columbian study considered the EQ-5D health-related quality-of-life score (Rivera, 2017); the U.S. study used both the physical and mental summary scales of the SF-12 health questionnaire (Chen, 2015); one of the British studies used mental and chronic diseases and disability (Jones et al., 2012); and the Indonesian study used a synthetic health score built on the basis of several self-reported and objective health measures (Jusot et al., 2014). Regarding the type of circumstances considered, most studies considered various characteristics as a proxy for parental social background; these included parental education (53%), parental social class (33%), family financial situation or income (33%), and, more rarely, the number of books in the household at age 10 (Pasqualini et al., 2017), living conditions (Chen, 2015), or assets ownership (Fajardo-Gonzalez, 2016). Some other socio-demographic characteristics were also considered, such as ethnicity (27%), religion and language spoken (Jusot et al., 2014), or family structure (Rivera, 2017). While individual education level is sometimes viewed as an effort variable in the ex post approaches, Barbosa (2016) considered education as a source of illegitimate inequality in healthcare insofar as a child has limited responsibility for parental decisions about which school to attend; and Jones et al. (2012) used cognitive and non-cognitive abilities and happiness, measured while at school, as childhood circumstances.

Geographical characteristics were also used as circumstances; this included the country or region of residence at birth or during childhood (33%), the country or region of residence as an adult (27%), the rural/urban status of the location (20%), parents’ country of birth in one study (7%), or socioeconomic characteristics of the country of residence (7%).

Beyond socioeconomic background, numerous studies considered health-related circumstances, such as parents’ health or vital status (40%), and one used both the parents’ health habits and childhood physician density (Bricard, 2013). Finally, one study considered childhood health status as a circumstance (Jones et al., 2012) and the U.S. analysis treated accidents, health shocks, and disability related to health limitations (Chen, 2015) as circumstances determining the level of SAH.

Empirically, most of the ex ante analyses directly used circumstances in their models while two studies, one in France (Trannoy et al., 2010) and the other in Spain (Pinilla et al., 2017), proposed a pathway analysis to distinguish the direct impact of circumstances on health outcomes from the indirect impact they made through their role in the determination of individual socioeconomic status.

Four studies focused on the impact of circumstances on lifestyles; two looked into the impact of circumstances on healthcare use (one in Brazil [Barbosa, 2016] and one in France [Bricard, 2013]), and two focused on the impact those circumstances had on various unhealthy behaviors such as smoking, alcohol consumption, diet, obesity, physical activity, and teenage pregnancy (one in the U.K. [Jones et al., 2012] and one in Norway [Ovrum & Rickertsen, 2015]). These studies did not measure the consequences of those lifestyles on health, nor discuss their potential impact in terms of the natural-reward principle. This was the reason why those studies could be more easily attached to the ex ante approach since they considered, implicitly or explicitly, that intergenerational transmission of lifestyles is one of the pathways explaining inequality of opportunity in health.

Regarding the methodology used, 11 studies were based on parametric modeling (73%) and one used the Fleurbaey and Schokkaert framework (Barbosa, 2016), whereas ten investigations relied on a non-parametric approach (67%): six used first- or second-order stochastic dominance tests (40%) in order to compare health-outcome distribution by group of circumstances, and three proposed an analysis of EOP by types (20%) or rank analysis (7%).

When measuring inequalities, several indices and methods are used to quantify the inequality of opportunity: these include the direct unfairness and fairness gap (Barbosa, 2016); the Shapley measure (Fajardo-Gonzalez, 2016); variance decomposition (Jusot et al., 2014) or R-squared decomposition (Pasqualini et al., 2017); indices decompositions, including the Gini index (Trannoy et al., 2010; Ovrum & Rickertsen, 2015; Fajardo-Gonzalez, 2016; Rivera, 2017); the Erreygers index (Trannoy et al., 2010), or the Atkinson index (Li Donni et al., 2014); and the concentration index (Ovrum & Rickertsen, 2015; Barbosa, 2016).

Ex Post Inequality of Opportunities in Health and Healthcare

The 18 studies that measured inequality of opportunity in health using an ex post perspective are described in Table 2; none of them considered a healthcare outcome.

Table 2. Ex post Analyses of Equality of Opportunity (EOP) in Health and Healthcare

Study reference

Country

Type, year of data

Study population

Sample size

Health or healthcare outcome

Sources of illegitimate inequality

Sources of legitimate inequality

Other control variables

Methods

Asada, Hurley, Norheim, & Johri, 2014

Canada

2002-03 JCUSH1 cross-sectional survey

18+

3,057

HUI32

Sex

Marital status

Race

Country of birth

Education

Household income

Healthcare use

Health insurance

Age

Smoking

Body Mass Index

Physical activity

Parametric regression

Fleurbaey and Schokkaert framework

Gini index decomposition

Asada, Hurley, Norheim, & Johri, 2015

USA

2002-03 JCUSH1 cross-sectional survey

18+

4,328

HUI32

Sex

Marital status

Race

Country of birth

Education

Household income

Healthcare use

Health insurance

Age

Smoking

Body Mass Index

Physical activity

Parametric regression

Fleurbaey and Schokkaert framework

Gini index decomposition

Direct and indirect fairness standardization

Balia & Jones, 2011

UK

HALS3 1984-1985 and mortality data in 2005

40+ in 1984-84

4,572

Mortality

Smoking-related mortality

Mother’z and father’s smoking

Any regular smoker in the household

Smoking initiation

Smoking quitting

Social status

Education

Marital status

Rural/urban residence

Household size

Age and sex

Birth cohort

Smoking start date

Semi-parametric approach (Duration model with latent factor)

Gini coefficient

Sen welfare index

Generalized Lorenz curve

Carranza & Hojman, 2015

Chile

SPS4 2002, 2004, 2006, 2009 longitudinal study

30+

10,934

SAH (very poor, poor, fair, good, very good) considered as binary

Mother’s and father’s education

Mother’s and father’s literacy

Mother’s and father’s employment

Household composition

Mother’s and father’s vital status

Smoking

Sports activity

Body Mass Index

Age and sex

Numeracy score

Parametric regression

Ex postroemerian approach with relative effort from auxiliary equation

Variance, Gini, Theil, and Atkinson decomposition

Carrieri & Jones, 2018

England

HSE5 2003-2012 cross-sectional survey

16+

2,336 to 10,910

Biomarkers (Cholesterol, glycated hemoglobin, fibrinogen, and mean arterial pressure)

Cohort of birth

Sex

Educational level

Saliva cotinine

Diet

Physical activity

Drinking

Body Mass Index

Medication taking

Household income

Non-parametric approach

EOP by type

Parametric regression

Decomposition of Gini index

Chen, 2015$

USA

NLSY796 longitudinal survey

40+

3,505

SAH (1-poor to 5-excellent)

Physical component score

Mental component score

Mother’s and father’s education

Race

Household characteristics

Incidence of health shocks

Disability and health limitations

Smoking initiation, duration, current and past

Number of daily cigarettes

Age and sex

Education

Income

Non-parametric approach

Stochastic dominance

Kolmogorov-Smirnov test

EOP by type with education attainment and income-lifestyle pair

Parametric regression

Counterfactual decomposition

Deutsch et al., 2017

Luxembourg

PSELL-37 2005, 2007, 2008 longitudinal survey

25–65

2,332

SAH (very poor, poor, fair, good, very good) considered as binary

Mother’s and father’s education

Mother and father’s country of birth

Family financial situation

Years of immigration

Country of birth

Smoking

Physical activity

Education

Age

Sex

Parametric regression

Ex-post roemerian approach with relative effort from auxiliary equations

Shapley decomposition

Garcia-Gomez, Schokkaert, Ourti, and D’uva, 2015

Netherlands

HSLC 1998-2007 cross-sectional survey

40+

12,484

Mortality

Health events (cancer, circulatory, stroke, respiratory, digestive, genitourinary)

Age

Education

Gender

Non-smoker

Exercise

Not overweight

Marital status

Religion

Rural/urban residence

Region of residence

Home ownership

Parametric regression

Fleurbaey and Schokkaert framework

Direct and indirect fairness standardization

Jones, Roemer, & Rosa Dias, 2014

UK

1958 NCDS8 birth cohort

From birth to age 46

17,000 (original sample)

SAH at 46 (excellent, good, fair, poor, very poor)

LSI9 or disability at age 46

Mental health score

Parental SES

Parents’ support to stay in school

Cognitive ability at 7

Childhood health at 7

Diabetes in the family

Happiness at school at 7

SES in local area

Political party in local area prereform

Cigarette smoking at age 46

Social status

Education

Non-parametric regression

EOP by type under two policy regimes

EOP by type with educational, non-educational, and residual path

Parametric regression

Dissimilarity index

Counterfactual decomposition

Jusot, Tubeuf, & Trannoy, 2013

France

2006 ESPS9

16+

6,074

SAH (very good, good, fair, bad, very bad) considered as binary

Mother’s and father’s education

Mother’s and father’s social status

Mother’s and father’s longevity

Mother’s and father’s smoking

Father’s alcohol

Adverse life experiences

Financial situation

Non-smoker

Vegetable consumption

Non obese

Age and gender

Parametric regression

Ex-post roemerian approach with relative effort from auxiliary equation

Variance decomposition

Lazar, 2013$

Israel

2003 Israeli Social Survey

20+

3,011

SAH (not good at all, not so good, good, very good)

Father’s education

Father’s country of birth (Israel, Europe, America)

Smoking

Education level, Occupation

Age and gender

Religion

Non-parametric approach

Tranches approach classifying by levels of effort

Parametric regression Decomposition of overall inequality

Li Donni, Peragine, & Pignataro, 2009

UK

BHPS11 1996-2005

16+

16,204

SAH (very poor/poor, fair, good, excellent)

considered as binary

Father's social class when individual was aged 14

Smoking

Number of cigarettes smoked

Age and sex

Education

Occupation status

Household income

Region of residence

Ethnic group

Year dummies

Non-parametric regression

Type approach

Tranches approach classifying by levels of effort

Parametric regression

Decomposition of overall inequality using the Atkinson equality index

Li Donni, Peragine, V., & Pignataro, 2014$

UK

BHPS11

2000-2005 longitudinal survey

55+

Between 2,519-2,631

SAH (very poor/poor, fair, good, excellent)

Father’s SES

Father’s vital status

Ethnicity

Country of birth

Any accidents

Smoking

Education level

Age and gender

Non-parametric approach

Tranches approach classifying by levels of effort

Parametric regression Decomposition of overall inequality using the Atkinson equality index

Pasqualini, Lanari, Minelli, Pieroni, & Salmasi, 2017$

14 European countries

SHARE12 and ELSA13 2005, 2007 and 2008

49+

32,165 SHARE11 and 10,281 ELSA12

SAH (Excellent, very good, good, fair, poor)

Body Mass Index

Chronic conditions

Number of books in the household at age 10

Financial hardship

Average level of income in the country of residence

Income inequality within the country of residence

Age and sex

Marital status

Employment status, Educational level

Migration from the country of birth

Parametric regression

Decomposition of the adjusted R-squared of the models

Rosa-Dias, 2009

UK

1958 NCDS8 birth cohort

From birth to age 46

4,408

SAH at age 46 (excellent, good, fair, poor, very poor)

Parental SES

Both grandfathers’ SES

Mother’s and father’s education

Mother’s and father’s smoking

Maternal smoking after 4 months pregnant

Breastfed, birth weight

Physical/mental impairment, obesity at 16

Diabetes, epilepsy, health condition in family

Math test score at 11

Arguments with parents about risks of smoking

Smoker at age 33

Avoidance of fried food

Vegetables consumption

Sweets consumption

Education

Social status

Non-parametric approach

First-order stochastic dominance and test

Gini-opportunity index

Health pseudo-Gini

Parametric regression

Separate equations for each of the efforts

Sun, Ma, Song, & Gu, 2013

China

CHNS14 1997, 2000, 2004, 2006 cross-sectional data

18–75

4,168

Healthcare expenditure in the past 4 weeks

Education

Family income

Medical insurance

Regional healthcare statistics (medicine availability and travel time)

Urban/rural residence

Year dummies

Treatment preferences

Smoking

Drinking

Age and sex

Marital status

Health needs (SAH, chronic diseases, illness, inpatient)

Parametric regression

Fleurbaey and Schokkaert framework

Fairness gap decomposition

Bricard, Jusot, Trannoy, & Tubeuf, 2013

13 European countries

SHARE12 2004 and 2007/2007 SHARELIFE in 2008/2009

50–80

20,946

SAH (Excellent, very good, good, fair, poor) considered as binary

Main breadwinner occupation

Number of books at home

Number of rooms per household member

Number of facilities

Financial difficulties

Mother’s and father’s longevity

Parents’ smoking

Parents’ alcohol

Dental visits for children

Smoking

Obesity

Sedentary behaviour

Age and sex

Country dummies

Parametric regression

Ex-post roemerian approach with relative effort from auxiliary equation

Variance decomposition

Rosa-Dias, 2010

UK

1958 NCDS8 birth cohort

From birth to age 46

4,408

SAH at age 46 (excellent, good, fair, poor, very poor)

LSI10 or disability at age 46

Mental health score at age 42

Parental SES

Both grandfathers’ SES

Mother’s and father’s education

Mother’s smoking

Financial hardships

Physical/mental impairment, obesity at 16

Diabetes, epilepsy, heart condition in family

Cognitive ability at 11

Social development at 11

Smoker at 33

Avoidance of fried food at 33

Alcohol at 33

Sex

Education

Parametric regression

Fleurbaey and Schokkaert framework

Separate equations for each of the efforts

($) References including both ex ante and ex post approaches

(1) JCUSH: Joint Canada/United States Survey of Health

(2) HUI: Health Utilities Index Mark 3

(3) HALS: British Health and Lifestyle Survey

(4) SPS: Social Protection Survey

(5) HSE: Health Survey for England

(6) NLSY79: National Longitudinal Survey of Young 1979

(7) PSELL-3” Panel Socio-Economique Liewen zu Lëtzebuerg

(8) NCDS: National Child Development Study

(9) ESPS: Enquête Santé et Protection Sociale

(10) LSI Long-standing illness

(11) BHPS: British Household Panel Survey

(12) SHARE

(13) ELSA

(14) CHNS: China Health and Nutrition Survey

Around half of the studies focused on the U.K. or England, using either the data from the 1958 National Child Development Study (Rosa Dias, 2009, 2010; Jones, Roemer, & Rosa Dias, 2014), the British Household Panel Survey (Li Donni, Peragine, & Pignataro, 2009; Li Donni et al., 2014), the Health and Life Survey (Balia & Jones, 2011), or the Health Survey of England (Carrieri & Jones, 2018). Five other studies focused on single European countries (France [Jusot et al., 2013], Luxembourg [Deutsch, Alperin, & Silber, 2017], the Netherlands [Garcia-Gomez, Schokkaert, Ourti, & Bago D’Uva, 2015]) or cross-country comparisons (13 different countries [Bricard, Jusot, Trannoy, & Tubeuf, 2013], or 14 countries [Pasqualini et al., 2017]). Outside Europe, studies with an ex post approach included two in the United States (Asada, Hurley, Norheim, & Johri, 2015; Chen, 2015), one in Canada (Asada, Hurley, Norheim, & Johri, 2014), one in Israel (Lazar, 2013), one in Chile (Carranza & Hojman, 2015), and one in China (Sun, Ma, Song, & Gu, 2013).

A large majority of studies focused on inequality of opportunity in health, using SAH as the main health outcomes of interest (67%). Four studies considered various scores as health outcomes: The two North American studies considered the Health Utility Index (HUI), which is a quality-of-life score (Asada et al., 2014, 2015); two studies used mental health scores (Rosa Dias, 2010, Chen, 2012); and one used a physical score from the SF12 questionnaire (Chen, 2015). Other health-related outcomes were also considered; these included health events (Garcia-Gomez et al., 2015), chronic diseases or disability in two studies (Rosa Dias, 2010; Pasqualini et al., 2017), various biomarkers (Carrieri & Jones, 2018), and mortality in two studies (Balia & Jones, 2011; Garcia-Gomez et al., 2015). One study used BMI (Pasqualini et al., 2017) although such health-related lifestyle factors are often considered as effort variables to reward in other studies. Another study considered healthcare used as a proxy of health status (Sun et al., 2013). There were no studies where inequality of opportunity in healthcare use per se was measured; this is probably related to the fact that ex post studies require an actual measurement of effort, which is conceptually always difficult to obtain, especially in the case of healthcare.

Regarding the types of circumstances or illegitimate factors considered, most of the studies considered various characteristics as a proxy for parental social background, including: parental education (39%); parental social class or employment (44%); family financial situation and adverse life events (28%); grandfather’s education (11%); and, in a few studies, the number of books in the household at age 10 (11%); parental literacy (6%); or living conditions (6%). Some other socio-demographic characteristics considered included ethnicity (11%) and family structure (11%).

Finally, whereas one’s own education level could be viewed as an effort variable that is under one’s responsibility, several studies considered some circumstances related to educational achievement such as: achieved education (28%); cognitive abilities; happiness at school, as well as parental support to stay at school (6%); math test score at 11 years old (6%); or social development at 11 years old (6%). Two other studies considered marital status or socioeconomic status as illegitimate sources of inequality in health as well (17%).

Geographical dimensions were also often taken into account as circumstances: these included the country of birth and year of immigration (11%); parents’ country of birth (6%); socioeconomic characteristics of the country or region of residence (11%); and, in one study, health-related regional averages (6%).

Beyond socioeconomic background, numerous studies considered health-related circumstances, such as: parents’ health or vital status or longevity (22%); parental smoking (22%), or mother’s smoking during pregnancy and breastfeeding (6%); diabetes, epilepsy, or heart disease in the family (11%); accident (6%); parents’ alcohol consumption (11%); and dental visits for children (6%). Finally, some studies considered respondents’ own health status in childhood or birth weight as a circumstance (17%), as well as current disabilities related to health limitations (11%).

Regarding effort variables, most studies (94%) considered that lack of smoking represented an effort to be rewarded. The next most used variables for effort were body mass index (39%), physical activity (39%), diet (17%), and alcohol consumption (17%). Few studies also considered socioeconomic factors (income, education, employment, home ownership, religion, area of residence, or marital status) as effort variables (28%), especially in order to test different ethical positions on the difference between effort and circumstances. Finally only two studies considered the taking of medication (Carrieri & Jones, 2018) or treatment preferences (Sun et al., 2013) as measures of individual effort.

Regarding the methodology, most studies (94%) used parametric modeling, except one, which used a semi-parametric approach (Balia & Jones, 2011). Four of those studies specifically referred to the Fleurbaey and Schokkaert structural framework (28%). Only two of them relied on non-parametric approaches, including stochastic dominance tests (Rosa Dias, 2009; Chen, 2015), and EOP analysis by types (Jones et al., 2014; Chen, 2015; Carrieri & Jones, 2018) or by tranches (Li Donni et al., 2009; Lazar, 2013; Li Donni et al., 2014). While most of the studies implicitly adopted a Barry viewpoint (Barry, 2005) rewarding the full effort independently from the correlation with circumstances, four studies used a Roemerian approach to assess the full impact of circumstances on health outcomes, including their indirect effect on effort variables (Bricard et al., 2013; Jusot et al., 2013; Carranza & Hojman, 2015; Deutsch et al., 2017).

Several indices and methods were used for the quantification of inequalities of opportunity: direct unfairness and fairness gap (17%); variance decomposition (22%); Gini index (28%); Atkinson decomposition (17%); counterfactual decomposition (11%); rarer were decompositions of a Rho-squared (Pasqualini et al., 2017), Theil (Carranza & Hojman, 2015), Sen welfare (Balia & Jones, 2011), or dissimilarity index (Jones et al., 2014), as well as a generalized Lorenz curve (Balia & Jones, 2011) and a Shapley decomposition (Deutsch et al., 2017).

Inequality of Opportunity in Child Health and Healthcare

The 15 studies that measured inequality of opportunity in child health and healthcare are described in Table 3.

Table 3. Equality of Opportunity (EOP) Studies in Child Health and Healthcare.

Study reference

Country

Type, year of data

Study population

Sample size

Health or healthcare outcome

Sources of illegitimate inequality

Methods

Amara & Jemmali, 2017

Tunisia

MICS1 2011-12

Under 5

N=10,514

Access to basic healthcare

Access to basic nutrition services

Mother’s and father’s education

Household wealth quintile

Urban/rural residence

Age, gender of the household head

Parametric approach

Human Opportunity Index

Dissimilarity Index

Shapley decomposition

Andersen, Griffin, Krause, & Montekio, 2017

60 LMI2 countries

166 cross-sectional surveys DHS3 between 1990 & 2015

Under 5

N=919,343 children (average per country N=5,538)

Height-for-age z-score

Mother's education

Wealth quintiles

Mother's age and height

Birth order, sex of the child

Child of a multiple birth

Parametric approach

Fields’ decomposition

Nutritional Mobility Index for country i at time t

Assaad, Krafft, Hassine, and Salehi-Isfahani, 2012

Egypt

Jordan

Morocco

Turkey

18 cross-sectional surveys DHS3 between 1988 & 2008

Under 5

Not provided

Height

Weigh-for-height z-score

Mother and father’s education

Father's occupation

Household wealth quintile

Urban/rural residence

Mother's age

Birth order, sex of the child

Child of a multiple birth

Parametric approach

Theil-T index

El-Kogali et al., 2016

Morocco

DHS3 2003/04

MICS1 2006/07

ENPSF4 2011

ONDH5 (2012)

Cross-sectional surveys

Under 5

Not provided

ECD6 outcomes: Prenatal care, skilled delivery, infant-mortality immunization, nutrition

Cognitive, emotional, and social-development outcomes

Mother and father’s education

Household wealth

Urban/rural residence

Region of residence

Sex of the child

Parametric approach

Dissimilarity Index

Shapley decomposition

Eriksson, Pan, & Qin, 2014

China

CHNS7 1991-2009 longitudinal survey

Under 18

12,749

Height-for-age z-score

Weight-for-age z-score

Mother’s and father’s education

Mother’s and father’s occupation

Household amenities

Mother’s and father's health

Mother’s and father’s height-for-age

Mother’s and father’s weight-for-age

Region of residence

Distance to nearest health facility

Age, sex, birth order of child

Number of siblings

Community smoking prevalence

Parametric approach

IV regression model

Urban/rural Blinder-Oaxaca decomposition

Ersado & Aran, 2014

Egypt

DHS3 2000 & 2008

HIECS8 2000 & 2008 cross-sectional surveys

Under 5

Not provided

Access to healthcare

Access to basic services

Height-for-age z-score

Weight-for-height

Weight-for-age z-score

Mother and father’s education

Household wealth quintile

Imputed household consumption

Region of residence

Age, sex of child

Number of siblings

Parametric approach

Human Opportunity Index and changes over time

Dissimilarity Index

Shapley decomposition

Hoyos & Narayan, 2011

47 LMI2 countries

DHS3 between 2003 & 2010

Under 15

Not provided

Immunization against polio

Immunization against measles

Household wealth

Region of residence

Gender of the child

Parametric approach

Human Opportunity Index

Dissimilarity Index

Shapley decomposition

Hussien, & Ayele, 2016

Ethiopia

YLS9 2002, 2006

Longitudinal survey

Under 8

Not provided

Standardized height-for-age

Weight-for-height z-score

Mother’s and father’s education

Household wealth index

Mother’s religion

Rural/urban residence

Region of residence

Public services (toilet facilities, drinking water)

General entropy measures

Non-parametric type approach

Parametric approach

Saidi, & Hamdaoui, 2017

Tunisia

MICS1 2011-12

Under 5

2,938

Weight-for-age

Length-for-age

Weight-for-height

Access to health services

Household head’s education

Household wealth index

Region of residence sociodemographic variables

Age, gender, sex of household head

Household size, number of children

Parametric approach

Human Opportunity Index

Dissimilarity Index

Shapley decomposition

Sanoussi, 2018

Togo

DHS3 1998 & 2013 cross-sectional surveys

Under 5

28,457

Access to prenatal care

Access to postnatal care

Access to any vaccination

Mother’s and father’s education

Household wealth index

Mother and father’s occupation

Rural/urban residence

Region of residence

Sex of the household head

Sex of the child

Number of children in the household

Parametric approach

Human Opportunity Index

Dissimilarity Index

Shapley decomposition

Sanoussi, 2018

Togo

DHS3 1998 & 2013 cross-sectional surveys

Under 5

44,998

Standardized height

Mother's educational level

Mother’s social class

Rural/urban residence

Region of residence

Non-parametric type approach

from circumstances

Singh, 2011

India

NFHS10 1992-93 and 2005-06 cross-sectional surveys

Under 5

Not provided

Full immunization at age 1+

Underweight child

Average parental education

Household wealth quintiles

Region of residence

Caste of the household head

Religion, sex of the child

Number of siblings

Parametric approach

Human Opportunity Index

Dissimilarity Index

Velez et al. 2012

Egypt

DHS3 2000 & 2009

Under 17

Not provided

Access to clean water

Access to adequate sanitation

Weight-for-height under age 4

Height-for-age age 2–7

Weight-for-age age 10–17

Mother’s and father’s education

Household income per capita

Rural/urban residence

Region of residence

Presence of father and mother in the household

Gender of the child

Number of children under 5, 6–17 in the household

Number of people 70+ or

Parametric approach

Human Opportunity Index and changes over time

Dissimilarity Index

Shapley decomposition

Van de Gaer, Vandenbossche, & Figueroa, 2013

Mexico

Opportunidades program 1997–2003

2–6 years old

2,984

Anemia

Stunting

Standardized BMI

Number of sick days in past four weeks

At least one parent completed primary education

Parents’ indigenous background

Non-parametric type approach

First- or second-order stochastic dominance and test

Parametric regression with propensity score matching

Zoch, 2015

South Africa

KIDS11 1993–2004

NIDS12 2008

Longitudinal surveys

10–14 years old

3,305

Access to adequate sanitation Access to clean water

Mother and father’s education

At least one parent completed high school or attained a higher-education qualification

Household income per capita

Rural/urban residence

At least one biological parent in the household Ethnic background

Number of children

Parametric decomposition

Human Opportunity Index

Dissimilarity Index

(1) MICS: Multiple Indicator Cluster Survey

(2) LMIC: Low and Middle Income

(3) DHS Demographic and Health Survey

(4) ENPSF: National Population and Family Health Survey

(5) ONDH: National Human Development Observatory

(6) ECD: Early Childhood Development

(7) CHNS: China Health and Nutrition Survey

(8) HIECS: Household Income, Expenditure and Consumption Survey

(9) YLS: Young Lives Survey

(10) NFHS: National Family Health Survey

(11) KIDS: KwaZulu-Natal Income Dynamics Study

(12) NIDS: National Income Dynamics Survey

All studies focused on one or several countries that are considered as low- or middle-income countries according to the World Bank. More than half of the research used data from the Demographic and Health Surveys (DHS) program, which provides nationally representative household data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition. The three papers that undertook a comparison of inequality of opportunities in child health used DHS data (Hoyos & Narayan, 2011; Assaad, Krafft, Hassine, & Salehi-Isfahani, 2012, Andersen, Griffin, Krause, & Montekio, 2017). Most of the research focused on health and healthcare outcomes before the age of 5, except for 4 empirical studies, which used longitudinal survey data. These examined the following age groups: 18 in China (Eriksson, Pan, & Qin, 2014), under 8 in Ethiopia (Hussien & Ayele, 2016), between 2 and 6 in Mexico (Van de Gaer, Vandenbossche, & Figueroa, 2013), and between 10 and 14 in South Africa (Zoch, 2015). Six studies in children considered health outcomes, four studies focused on healthcare-specific outcomes, and five considered both of them. Health outcomes corresponded to World Health Organization (WHO) indicators on child growth and malnutrition such as height, weight, and a combination of both or either with age via z-scores. Two studies considered slightly different health outcomes: One, in Morocco (El-Kogali et al., 2016) examined a set of early child-development outcomes including cognitive, emotional, and social development. Another, in Mexico (Van de Gaer, Vandenbossche et al., 2013), looked into the incidence of anemia, stunting, standardized body mass index, and the number of sick days taken from school. When the outcomes were related to access to services these included basic healthcare, pre- and postnatal care, basic nutrition, immunization, and vaccination, as well as clean water and adequate sanitation.

The vector of circumstances variables varied between studies, probably because of data availability. The family social background was used as a circumstance in each. All of the studies except one (Hoyos & Narayan, 2011) took into account parental education level (the mother only or both parents); household wealth or a proxy of wealth such as household amenities was used in 87% of the studies, three of them additionally considered parental occupation (the father only or both parents) and one used the mother’s social class. Another very frequent circumstance was geographical characteristics (80%) such as the region of residence, the urban/rural status, and the distance to the nearest health facility. Two studies also considered variables at regional level: smoking prevalence at community level (Eriksson et al., 2014) and regional averages of socio-demographic variables (Singh, 2011) while one study treated access to public services such as sanitation and clean water as a circumstance (Hussien & Ayele, 2016). Other variables considered as part of the vector of circumstances included further parental characteristics (e.g., age, gender of the head of household, height, height-for-age, weight-for-age, presence in the household, religion, indigenous background, and caste); the child’s characteristics (e.g., age, sex, birth order, number of siblings, and child of a multiple birth); and characteristics of the household (e.g. size, number of children, and number of adults).

In such a case, where the set of circumstances is potentially very broad,, measuring inequality of opportunities non-parametrically is difficult as the types of circumstances become too broad to allow for enough observation in each type. In this case, inequality of opportunity is measured parametrically. Twelve studies (80%) used a parametric approach to measure inequality of opportunity; two studies used both a non-parametric and a parametric approach while one study only used a non-parametric approach. Most parametric studies (75%) assessed the existence of inequality of opportunity in health or in the healthcare of the child population using the Human Opportunity Index. The Human Opportunity Index (HOI) was developed by the World Bank and is an index measuring children’s access to basic services and goods which can be considered as prerequisites needed for childhood development (Paes de Barros et al., 2009). The key services that are included in the HOI vary but generally include access to clean water, immunization, sanitation, basic healthcare, and basic nutrition. The use of the HOI leads to the measuring of an equality of opportunity-sensitive coverage rate, which can rely on various circumstances, outcomes, opportunities, and population groups. Most of the studies using a HOI approach additionally used a dissimilarity index, derived by comparing group means for different combinations of circumstances to the population average to quantify how outcomes differ by circumstances. The dissimilarity index was then completed with a Shapley decomposition to estimate the marginal contribution of each considered circumstance to the inequality of opportunity. One of the parametric studies (Assaad et al., 2012) decomposed the inequality using the Theil-T index while another one undertook an Oaxaca-Blinder decomposition of the inequality between urban and rural areas. The three studies that utilized a non-parametric approach to assess inequality of opportunity used an approach by types (Hussien & Ayele, 2016, Sanoussi, 2018); however only one of the studies (Van de Gaer, Vandenbossche, et al., 2013) compared types with first- or second-order stochastic dominance.

Critical Discussion

In the last two decades economists have provided different analytical tools and empirical assessments aimed at facilitating the measurement and the reduction of inequality of opportunity in education, earnings, and other socioeconomic outcomes. More recently, it has been in the areas of health and healthcare that studies have investigated and measured inequality of opportunity.

Interestingly, empirical research on the measurement of EOP in health and healthcare in adults has mainly been based on data from European countries, especially from the U.K. This is particularly noticeable for those studies using an ex post approach for the measurement of IOP. This research is probably driven by data availability, since an ex post approach requires the observation of both circumstances and efforts variables. The scarcity of empirical studies focusing on EOP in the United States is particularly unforeseen given the great adherence in U.S. society to the philosophy of responsibility (Rawls, 1999).

By contrast, most studies analyzing IOP in health and healthcare among children are based in low- or middle-income countries and focused on children younger than five years old.

A crucial issue for the analysis of inequality in health is the choice of a health indicator. Most studies on an adult population relied on self-assessed health (SAH) status in spite of the debates on the relevance of this subjective indicator for interpersonal comparisons (Kerkhofs & Lindeboom, 1995; Doiron, Fiebig, Johar, & Suziedelyte, 2015; Jusot, Tubeuf, Devaux, & Sermet, 2017). The use of other types of health outcomes has increased in recent studies. These include quality-of-life measures such as the Health Utility Index (HUI), as well as physical and mental health scores, physical impairments, chronic diseases, biomarkers, and mortality. However, the studies conducted among children and younger populations focused on anthropometrical measures (height-for-age, weight-for-age, weight-for-height) and lack of access to goods and services whose absence may be detrimental for health status such as care, immunization, sanitation, basic services, or nutrition (resulting in outcomes such as anemia, or stunting). While many of the children and younger population studies used healthcare variables as the outcomes of interest, only two studies used an ex ante perspective on the measurement of health inequalities. The absence of ex post empirical applications using healthcare as the outcome of interest might be explained by the lack of data on effort, such as preferences in the context of healthcare, which are much harder to come by. More generally, the limited studies of inequality of opportunity in healthcare access or delivery may be explained thus, according to Fleurbaey and Schokkaert (2011): “healthcare itself can be viewed as a transfer of resources, but it would make little sense to advocate that everyone should receive the same amount of healthcare within a group of circumstances.”

Regarding the main objectives of the studies, some of them only aim to test for the existence of inequalities of opportunity in health and healthcare, some provide measurements of the magnitude of those inequalities, while others go a step further, exploring their construction channels. Beyond the clear divide between parametric and non-parametric approaches, methodologies used for identifying IOP in health are quite homogeneous even if they often use different normative assumptions. However, measurement tools for quantifying IOP are very heterogeneous, and this heterogeneity could partly explain the inconsistency that is found in results.

Regarding the choice of circumstances, most studies considered social background as an illegitimate source of inequality in health and healthcare. Geographical dimensions were also considered, but to a lesser extent and more widely in studies in children or in countries outside Europe. Interestingly, a relatively small number of studies that included parental health characteristics such as their longevity, number of chronic diseases, or lifestyles found their contribution to the explanation of inequality of opportunity substantial. However parental health variables are rarely available in surveys because they often are retrospective and challenging to measure.

Regarding effort variables or legitimate sources of health inequality, all ex post studies but one used a smoking-related variable. This statement is probably data-driven since smoking information, is collected in most health surveys, but it is also related to the agreement in the general population that smoking represents a chosen risky behavior. This is consistent with lab experiments showing that individuals widely agree that smoking is an individual choice for which they can be held responsible (Le Clainche & Wittwer, 2015). On the other hand, a smaller number of studies considered BMI as an effort variable despite the fact that height and weight are likely to be frequently collected in surveys; this could be attributable to the debate on whether obesity represents a lack of health effort or occurs as a result of a combination of aging, socioeconomic status, and health problems.

What was learned from this literature review on inequality of opportunity in health and healthcare? Regardless of the population, health outcome, and circumstances considered, scholars provided evidence of illegitimate inequalities in health. Given the important contribution of health to both well-being and productivity, this emerging literature contributes to the highlighting of unfair inequalities in welfare, in addition to the already substantial literature showing inequalities of opportunity in income or education. Most studies also concluded that there is an impact of circumstances on effort variables. Independently of the methodology used, whether it is an ex ante or an ex post approach, and the normative viewpoint chosen on how to treat the correlation between circumstances and efforts, the diagnosis on the existence of inequality of opportunity is the same. The results on the magnitude of these inequalities of health opportunities are less consistent and this is mainly related to the types and the number of circumstances and efforts that are mobilized in the empirical studies. In any case, this literature provides evidence of unfair inequalities in health and the need for related public policies to tackle them. It appears important, however, to mention the debate on the additional knowledge provided from the analysis of inequality of opportunity in health for policymakers when compared to the literature on income-related health inequalities (Kanbur & Wagstaff, 2015; Schokkaert, 2015; Wagstaff & Kanbur, 2015).

More importantly, the literature on inequality of opportunity in health has also contributed at to the literature on equality of opportunity in general, because of three key specificities.

First, the literature on IOP in health has contributed to the development of the ex post approach for measuring inequality of opportunity. As individual efforts are certainly easier to define and observe in the field of health than in other fields, given the broad consensus on the fact that health-related behaviors, such as lack of smoking or obesity, or prudent alcohol drinking, which are measured in most health-interview surveys, should be rewarded.

Second, there is a specific challenge with age and genetic inheritance, and to a lesser extent sex, in the study of IOP in health and healthcare: Should they be compensated for or not? While the way to treat age has not been at the forefront in studies of inequality of opportunity in income, the aging process and biological determinants in general explain a share of health outcomes. Similarly, the large number of studies focusing on inequality of opportunity in access to healthcare in children emphasize the necessity to tackle inequality as early as possible as it can have long-term consequences over one’s life. This opens new avenues of research on the normative status of genes, age, and sex.

Third, the debate on the role played by preferences as being formed under the control of the past generation or being under the full responsibility of individuals could easily be further developed when studying EOP in healthcare, since discrete-choice experiments are increasingly used to measure individual preferences regarding health and healthcare (Clark, Determann, Petrou, Morro, & De Bekker-Grob, 2014).

The last specificity of EOP in health relates to that part of health inequality that can be explained by a parametric regression model. Most models of health outcomes only explain about 20% of the variance and a large residual share remains, whatever the number of circumstances and effort variables considered in the analysis. This raises the issue of the importance of unobserved variables and the normative status of “luck.” Theoretical EOP has discussed the type of luck that can be recognized as circumstance or as effort (Dworkin, 1981b; Fleurbaey, 2008; Roemer & Trannoy, 2014; Schokkaert, 2015); however the translation of this debate to empirical studies presents challenges for future research.

Acknowledgments

We are grateful to Josephine Aikpitanyi and Rocio Rodriguez-Lopez for their help with literature searches and selection of literature references.

Further Reading

Fleurbaey, M. (2008). Fairness, responsibility, and welfare. Oxford: Oxford University Press.Find this resource:

    Fleurbaey, M., and Schokkaert, E. (2011). Equity in health and health care. In M. Pauly, T. McGuire & P. Barros (Eds.), Handbook of health economics (Vol. 2, pp. 1003–1092). North-Holland, Amsterdam.Find this resource:

      Ramos, X., and Van de Gaer, D. (2016). Approaches to inequality of opportunities: principles, measures and evidence. Journal of Economic Surveys, 30(5), 855–883.Find this resource:

        Roemer, J. (1998). Equality of opportunity. Cambridge, MA: Harvard University Press.Find this resource:

          Roemer, J. (2002). Equality of opportunity: A progress report. Social Choice and Welfare, 13(2), 455–471.Find this resource:

            Roemer, J., & Trannoy, A. (2014). Equality of opportunity. In A. Atkinson & F. Bourguignon (Eds.), Handbook of income distribution (Vol. 2, pp. 217–300). North-Holland, Amsterdam.Find this resource:

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                                                                                                                                                                                                                              Appendix A. Search Strategies

                                                                                                                                                                                                                              Project Name: Inequalities of Opportunities in Health – Book Chapter

                                                                                                                                                                                                                              Date: 19/03/2018

                                                                                                                                                                                                                              Database: Medline; Medline In-Process & Other Non-Indexed Citations; Medline Epub Ahead of Print; Embase; Econlit; The Cochrane library

                                                                                                                                                                                                                              Ovid MEDLINE(R) <1946 to January Week 4 2018>

                                                                                                                                                                                                                              Search Strategy:

                                                                                                                                                                                                                              --------------------------------------------------------------------------------

                                                                                                                                                                                                                              1. 1 ((Inequalit* or equal* or equit* or inequit*) adj "of opportunit*").ab. (474)

                                                                                                                                                                                                                              2. 2 ((Inequalit* or equal* or equit* or inequit*) adj2 opportunit*).ti,kf. (320)

                                                                                                                                                                                                                              3. 3 1 or 2 (764)

                                                                                                                                                                                                                              4. 4 health*.tw,kf. (1976096)

                                                                                                                                                                                                                              5. 5 3 and 4 (305)

                                                                                                                                                                                                                              6. 6 Economics/ (26852)

                                                                                                                                                                                                                              7. 7 exp Economics, Dental/ (4032)

                                                                                                                                                                                                                              8. 8 exp Economics, Nursing/ (3978)

                                                                                                                                                                                                                              9. 9 exp Economics, Medical/ (13992)

                                                                                                                                                                                                                              10. 10 exp Economics, pharmaceutical/ (2723)

                                                                                                                                                                                                                              11. 11 exp Economics, Hospital/ (22604)

                                                                                                                                                                                                                              12. 12 exp "Costs and Cost Analysis"/ (211426)

                                                                                                                                                                                                                              13. 13 exp "Fees and Charges"/ (29059)

                                                                                                                                                                                                                              14. 14 exp budgets/ (13192)

                                                                                                                                                                                                                              15. 15 exp "Value of Life"/ec [Economics] (240)

                                                                                                                                                                                                                              16. 16 budget*.tw. (20676)

                                                                                                                                                                                                                              17. 17 cost*.ti. (91261)

                                                                                                                                                                                                                              18. 18 (cost* adj2 (effective* or utilit* or benefit* or minimi* or evaluat* or analy* or study or studies or consequenc* or compar* or efficienc* or variable or unit or estimate* or variable* or unit)).ab. (123712)

                                                                                                                                                                                                                              19. 19 (economic* or pharmacoeconomic* or pharmaco-economic*).tw. (182428)

                                                                                                                                                                                                                              20. 20 (price or prices or pricing).tw. (27302)

                                                                                                                                                                                                                              21. 21 (financ* adj2 (cost* or data or "health care")).tw. (6510)

                                                                                                                                                                                                                              22. 22 (fee or fees).tw. (13725)

                                                                                                                                                                                                                              23. 23 (value adj1 (money or monetary)).tw. (430)

                                                                                                                                                                                                                              24. 24 quality-adjusted life years/ (9743)

                                                                                                                                                                                                                              25. 25 (eq-5d* or eq5d* or euroquol* or euroqol* or euroqual* or euro-quol* or euro-qol* or euro-qual*).tw. (6344)

                                                                                                                                                                                                                              26. 26 exp models, economic/ (12938)

                                                                                                                                                                                                                              27. 27 markov chains/ (12389)

                                                                                                                                                                                                                              28. 28 quality adjusted life.tw. (8408)

                                                                                                                                                                                                                              29. 29 (qaly or qalys or qald or qale or qtime).tw. (6830)

                                                                                                                                                                                                                              30. 30 disability adjusted life.tw. (1947)

                                                                                                                                                                                                                              31. 31 (daly or dalys).tw. (1787)

                                                                                                                                                                                                                              32. 32 "Global Burden of Disease"/ [new 2017] (105)

                                                                                                                                                                                                                              33. 33 health* year* equivalent*.tw. (38)

                                                                                                                                                                                                                              34. 34 (hye or hyes).tw. (57)

                                                                                                                                                                                                                              35. 35 (hui1 or hui2 or hui3).tw. (310)

                                                                                                                                                                                                                              36. 36 disutil*.tw. (300)

                                                                                                                                                                                                                              37. 37 standard gamble*.tw. (718)

                                                                                                                                                                                                                              38. 38 (time trade off or time tradeoff).tw. (1104)

                                                                                                                                                                                                                              39. 39 (hqol or h qol or hrqol or hr qol).tw. (10941)

                                                                                                                                                                                                                              40. 40 (pqol or qls).tw. (286)

                                                                                                                                                                                                                              41. 41 (sf6d or sf 6d or short form 6d or shortform 6d or sf sixd or sf six d).tw. (599)

                                                                                                                                                                                                                              42. 42 exp animals/ not (exp animals/ and exp humans/) (4417696)

                                                                                                                                                                                                                              43. 43 exp Veterinary Medicine/ (23906)

                                                                                                                                                                                                                              44. 44 exp Animal Experimentation/ (8565)

                                                                                                                                                                                                                              45. 45 ((energy or oxygen* or metaboli*) adj3 (expenditure* or cost*)).tw. (25772)

                                                                                                                                                                                                                              46. 46 or/42-45 (4454796)

                                                                                                                                                                                                                              47. 47 or/6-41 (567374)

                                                                                                                                                                                                                              48. 48 47 not 46 (528603)

                                                                                                                                                                                                                              49. 49 5 and 48 (71)

                                                                                                                                                                                                                              ***************************

                                                                                                                                                                                                                              Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations <February 01, 2018>, Ovid MEDLINE(R) Epub Ahead of Print <February 01, 2018>

                                                                                                                                                                                                                              Search Strategy:

                                                                                                                                                                                                                              --------------------------------------------------------------------------------

                                                                                                                                                                                                                              1. 1 ((Inequalit* or equal* or equit* or inequit*) adj "of opportunit*").ab. (81)

                                                                                                                                                                                                                              2. 2 ((Inequalit* or equal* or equit* or inequit*) adj2 opportunit*).ti,kf. (39)

                                                                                                                                                                                                                              3. 3 1 or 2 (120)

                                                                                                                                                                                                                              4. 4 health*.tw,kf. (305961)

                                                                                                                                                                                                                              5. 5 3 and 4 (49)

                                                                                                                                                                                                                              6. 6 Economics/ (2)

                                                                                                                                                                                                                              7. 7 exp Economics, Dental/ (1)

                                                                                                                                                                                                                              8. 8 exp Economics, Nursing/ (0)

                                                                                                                                                                                                                              9. 9 exp Economics, Medical/ (0)

                                                                                                                                                                                                                              10. 10 exp Economics, pharmaceutical/ (6)

                                                                                                                                                                                                                              11. 11 exp Economics, Hospital/ (0)

                                                                                                                                                                                                                              12. 12 exp "Costs and Cost Analysis"/ (16)

                                                                                                                                                                                                                              13. 13 exp "Fees and Charges"/ (1)

                                                                                                                                                                                                                              14. 14 exp budgets/ (1)

                                                                                                                                                                                                                              15. 15 exp "Value of Life"/ec [Economics] (0)

                                                                                                                                                                                                                              16. 16 budget*.tw. (4317)

                                                                                                                                                                                                                              17. 17 cost*.ti. (13614)

                                                                                                                                                                                                                              18. 18 (cost* adj2 (effective* or utilit* or benefit* or minimi* or evaluat* or analy* or study or studies or consequenc* or compar* or efficienc* or variable or unit or estimate* or variable* or unit)).ab. (23504)

                                                                                                                                                                                                                              19. 19 (economic* or pharmacoeconomic* or pharmaco-economic*).tw. (34221)

                                                                                                                                                                                                                              20. 20 (price or prices or pricing).tw. (4922)

                                                                                                                                                                                                                              21. 21 (financ* adj2 (cost* or data or "health care")).tw. (710)

                                                                                                                                                                                                                              22. 22 (fee or fees).tw. (1714)

                                                                                                                                                                                                                              23. 23 (value adj1 (money or monetary)).tw. (79)

                                                                                                                                                                                                                              24. 24 quality-adjusted life years/ (0)

                                                                                                                                                                                                                              25. 25 (eq-5d* or eq5d* or euroquol* or euroqol* or euroqual* or euro-quol* or euro-qol* or euro-qual*).tw. (1525)

                                                                                                                                                                                                                              26. 26 exp models, economic/ (0)

                                                                                                                                                                                                                              27. 27 markov chains/ (1)

                                                                                                                                                                                                                              28. 28 quality adjusted life.tw. (1450)

                                                                                                                                                                                                                              29. 29 (qaly or qalys or qald or qale or qtime).tw. (1235)

                                                                                                                                                                                                                              30. 30 disability adjusted life.tw. (428)

                                                                                                                                                                                                                              31. 31 (daly or dalys).tw. (366)

                                                                                                                                                                                                                              32. 32 "Global Burden of Disease"/ [new 2017] (0)

                                                                                                                                                                                                                              33. 33 health* year* equivalent*.tw. (2)

                                                                                                                                                                                                                              34. 34 (hye or hyes).tw. (4)

                                                                                                                                                                                                                              35. 35 (hui1 or hui2 or hui3).tw. (23)

                                                                                                                                                                                                                              36. 36 disutil*.tw. (57)

                                                                                                                                                                                                                              37. 37 standard gamble*.tw. (61)

                                                                                                                                                                                                                              38. 38 (time trade off or time tradeoff).tw. (120)

                                                                                                                                                                                                                              39. 39 (hqol or h qol or hrqol or hr qol).tw. (2049)

                                                                                                                                                                                                                              40. 40 (pqol or qls).tw. (57)

                                                                                                                                                                                                                              41. 41 (sf6d or sf 6d or short form 6d or shortform 6d or sf sixd or sf six d).tw. (67)

                                                                                                                                                                                                                              42. 42 exp animals/ not (exp animals/ and exp humans/) (228)

                                                                                                                                                                                                                              43. 43 exp Veterinary Medicine/ (59)

                                                                                                                                                                                                                              44. 44 exp Animal Experimentation/ (1)

                                                                                                                                                                                                                              45. 45 ((energy or oxygen* or metaboli*) adj3 (expenditure* or cost*)).tw. (4012)

                                                                                                                                                                                                                              46. 46 or/42-45 (4251)

                                                                                                                                                                                                                              47. 47 or/6-41 (73992)

                                                                                                                                                                                                                              48. 48 47 not 46 (73408)

                                                                                                                                                                                                                              49. 49 5 and 48 (9)

                                                                                                                                                                                                                              ***************************

                                                                                                                                                                                                                              Embase Classic+Embase <1947 to 2018 February 01>

                                                                                                                                                                                                                              Search Strategy:

                                                                                                                                                                                                                              --------------------------------------------------------------------------------

                                                                                                                                                                                                                              1. 1 ((Inequalit* or equal* or equit* or inequit*) adj "of opportunit*").ab. (682)

                                                                                                                                                                                                                              2. 2 ((Inequalit* or equal* or equit* or inequit*) adj2 opportunit*).ti,kw. (387)

                                                                                                                                                                                                                              3. 3 1 or 2 (1024)

                                                                                                                                                                                                                              4. 4 health*.tw,kw. (3025080)

                                                                                                                                                                                                                              5. 5 3 and 4 (391)

                                                                                                                                                                                                                              6. 6 health economics/ (35528)

                                                                                                                                                                                                                              7. 7 exp economic evaluation/ (268224)

                                                                                                                                                                                                                              8. 8 exp health care cost/ (257726)

                                                                                                                                                                                                                              9. 9 pharmacoeconomics/ or "drug cost"/ or drug utilization/ or "utilization review"/ (156867)

                                                                                                                                                                                                                              10. 10 socioeconomics/ and economics/ (15284)

                                                                                                                                                                                                                              11. 11 *socioeconomics/ (20197)

                                                                                                                                                                                                                              12. 12 Economic model/ (1024)

                                                                                                                                                                                                                              13. 13 *fee/ (6567)

                                                                                                                                                                                                                              14. 14 *"cost"/ (13768)

                                                                                                                                                                                                                              15. 15 cost*.ti. (137666)

                                                                                                                                                                                                                              16. 16 (cost* adj2 (effective* or utilit* or benefit* or minimi* or evaluat* or analy* or study or studies or consequenc* or compar* or efficienc* or variable or unit or estimate* or variable* or unit)).ab. (205380)

                                                                                                                                                                                                                              17. 17 (price or prices or pricing).tw. (46578)

                                                                                                                                                                                                                              18. 18 (economic* or pharmacoeconomic* or pharmaco-economic*).tw. (288148)

                                                                                                                                                                                                                              19. 19 budget*.tw. (32786)

                                                                                                                                                                                                                              20. 20 (value adj1 (money or monetary)).tw. (663)

                                                                                                                                                                                                                              21. 21 (financ* adj2 (cost* or data or "health care")).tw. (9433)

                                                                                                                                                                                                                              22. 22 financ*.tw. and economics/ (13933)

                                                                                                                                                                                                                              23. 23 (expenditure* not energy).tw. (34035)

                                                                                                                                                                                                                              24. 24 quality adjusted life year/ (20346)

                                                                                                                                                                                                                              25. 25 (eq-5d* or eq5d* or euroquol* or euroqol* or euroqual* or euro-quol* or euro-qol* or euro-qual*).tw. (14581)

                                                                                                                                                                                                                              26. 26 quality adjusted life.tw. (14901)

                                                                                                                                                                                                                              27. 27 (qaly or qalys or qald or qale or qtime).tw. (15268)

                                                                                                                                                                                                                              28. 28 disability adjusted life.tw. (2882)

                                                                                                                                                                                                                              29. 29 (daly or dalys).tw. (2840)

                                                                                                                                                                                                                              30. 30 (SF6D or sf 6d or short form 6d or shortform6d).tw. (1196)

                                                                                                                                                                                                                              31. 31 health* year* equivalent*.tw. (40)

                                                                                                                                                                                                                              32. 32 (hye or hyes).tw. (115)

                                                                                                                                                                                                                              33. 33 health utilit*.tw. (2607)

                                                                                                                                                                                                                              34. 34 (hui1 or hui2 or hui3).tw. (465)

                                                                                                                                                                                                                              35. 35 disutil*.tw. (689)

                                                                                                                                                                                                                              36. 36 standard gamble*.tw. (987)

                                                                                                                                                                                                                              37. 37 (time trade off or time tradeoff).tw. (1678)

                                                                                                                                                                                                                              38. 38 (hqol or h qol or hr qol or hrqol).tw. (20716)

                                                                                                                                                                                                                              39. 39 (pqol or qls).tw. (541)

                                                                                                                                                                                                                              40. 40 or/6-39 (1011709)

                                                                                                                                                                                                                              41. 41 exp animals/ not (exp animals/ and exp humans/) (4961162)

                                                                                                                                                                                                                              42. 42 exp nonhuman/ not (exp nonhuman/ and exp human/) (4064264)

                                                                                                                                                                                                                              43. 43 exp experimental animal/ (589993)

                                                                                                                                                                                                                              44. 44 exp veterinary medicine/ (36589)

                                                                                                                                                                                                                              45. 45 animal experiment/ (2157220)

                                                                                                                                                                                                                              46. 46 ((energy or oxygen* or metaboli*) adj3 (expenditure* or cost*)).tw. (37032)

                                                                                                                                                                                                                              47. 47 or/41-46 (7005151)

                                                                                                                                                                                                                              48. 48 40 not 47 (940128)

                                                                                                                                                                                                                              49. 49 5 and 48 (91)

                                                                                                                                                                                                                              The Cochrane Library (Wiley)

                                                                                                                                                                                                                              #1     ((Inequalit* or equal* or equit* or inequit*) near/2 opportunit*):ti,ab,kw (Word variations have been searched)     11

                                                                                                                                                                                                                              ***********************

                                                                                                                                                                                                                              EconLit (EBSCO) 1886 - present

                                                                                                                                                                                                                              1. S5 (TX health*) AND (S3 AND S4)     (224)

                                                                                                                                                                                                                              2. S4 TX health*     98,589)

                                                                                                                                                                                                                              3. S3 S1 OR S2     (1,519)

                                                                                                                                                                                                                              4. S2 TI ( ((Inequalit* or equal* or equit* or inequit*) N2 opportunit*) ) OR SU ( ((Inequalit* or equal* or equit* or inequit*) N2 opportunit*) )     (593)

                                                                                                                                                                                                                              5. S1 AB ((Inequalit* or equal* or equit* or inequit*) N1 "of opportunit*")     (1,205)

                                                                                                                                                                                                                              Notes:

                                                                                                                                                                                                                              (1.) These included Ovid Embase; Ovid Medline; Ovid Medline In-Process & Other Non-Indexed Citations; Ovid MEDLINE(R) Epub Ahead of Print; Cochrane Database of Systematic Reviews (Cochrane Library, Wiley); NHSEED (Cochrane Library, Wiley); RePEc Ideas; and Econlit.

                                                                                                                                                                                                                              (4.) Duplicates were identified as versions of a paper available under the same title, and were sometimes found in multiple forms, for example as a working paper and published version.