Print version ISSN 0042-9686
Bull World Health Organ vol.80 n.2 Genebra Jan. 2002
Poverty and health sector inequalities*
ABSTRACT: Poverty and ill-health are intertwined. Poor countries tend to have worse health outcomes than better-off countries. Within countries, poor people have worse health outcomes than better-off people. This association reflects causality running in both directions: poverty breeds ill-health, and ill-health keeps poor people poor. The evidence on inequalities in health between the poor and non-poor and on the consequences for impoverishment and income inequality associated with health care expenses is discussed in this article. An outline is given of what is known about the causes of inequalities and about the effectiveness of policies intended to combat them. It is argued that too little is known about the impacts of such policies, notwithstanding a wealth of measurement techniques and considerable evidence on the extent and causes of inequalities.
Keywords Poverty; Health status; Income; Health services accessibility; Financing, organized; Social justice (source: MeSH, NLM).
Mots clés Pauvreté; Etat sanitaire; Revenu; Accessibilité services santé; Organisation financement; Justice sociale (source: MeSH, INSERM).
Palabras clave Pobreza; Estado de salud; Renta; Accessibilidad a los servicios de salud; Organización del financiamiento; Justicia social (fuente: DeCS, BIREME).
Bulletin of the World Health Organization 2002;80:97-105.
Poverty and ill-health are intertwined. Poor countries tend to have worse health outcomes than better-off countries. Within countries, poor people have worse health outcomes than better-off people. The association between poverty and ill-health reflects causality running in both directions. Illness or excessively high fertility may have a substantial impact on household income (1, 2) and may even make the difference between being above and being below the poverty line (3). Furthermore, ill-health is often associated with substantial health care costs (4). But poverty and low income also cause ill-health (5). Poor countries, and poor people within countries, suffer from a multiplicity of deprivations that translate into high levels of ill-health (6, 7). Poor people are thus caught in a vicious circle: poverty breeds ill-health, ill-health maintains poverty (Fig. 1).
Several key international organizations and bilateral donors now have the improvement of the health outcomes of the world's poor as their primary objective (810). This reflects an increasing tendency of such organizations to define their goals in terms of poverty reduction (11, 12) and an ever broader interpretation being given to the term "poverty" (6, 13). However, it also reflects growing agreement that inequalities in health outcomes between rich and poor are unjust and unfair (14), not because the poor are somehow more deserving than the better-off but because these inequalities evidently correspond to widely differing constraints and opportunities facing the poor and better-off rather than a tendency for the two groups to make different choices (1520). The deleterious effects that ill-health has on household living standards are also increasingly seen as an issue of social justice, possibly reflecting a view that the income losses and health care payments associated with ill-health are involuntary and simply the consequence of unwanted health "shocks" (21). This sets health expenditure apart from most other items in household budgets and leads naturally to the view that the community as a whole should bear the financial burden of such shocks, instead of allowing them to impact adversely on income inequality and poverty. In several countries in the Organisation for Economic Co-operation and Development (OECD) (22) and apparently elsewhere (23) there appears to be an acceptance of the view that both out-of-pocket payments and payments towards protection schemes should be linked to household income, a view that WHO has recently championed (24).
This paper provides an overview of research relating to inequalities in health to the disadvantage of the poor, and to changes in impoverishment and income inequality associated with payments for health care. The broader issue of impoverishment associated with income loss through ill-health is not considered because the creation of schemes to protect people from such loss goes beyond the area of health policy as currently interpreted. Nevertheless, it should be noted that lost income is probably a larger cause of impoverishment than out-of-pocket payments for health services (25). The evidence on health inequalities and impoverishment is discussed, together with the factors driving the results and the effectiveness of policies in these areas.
Evidence of health inequalities between the poor and non-poor
In Europe there has been a long tradition of measuring socioeconomic inequalities in health, covering both methodology (2628) and empirical analysis (2937). Less empirical work has been undertaken on the subject in other regions, especially in the developing world (3842).
The following key findings in the literature on empirical data are worth highlighting. Firstly, inequalities in health are almost always to the disadvantage of the poor. The poor tend to die earlier and to have higher levels of morbidity than the better-off.
Secondly, inequalities tend to be more pronounced for objective indicators of ill-health, such as anthropometric measures of malnutrition and mortality, than for subjective indicators. It is often noted that the latter sometimes produce perverse gradients in developing countries, with the better-off reporting worse health than the poor (43). But this tends to occur with indicators that are highly subject to the influence of transitory factors, e.g. whether or not a respondent has experienced illness in the previous two weeks. A similar pattern emerges in industrialized countries in relation to such indicators (44). In the developing (45) as in the industrialized world (31, 36, 46), longer-term illness indicators, e.g. long-standing illness, limitation of a major activity, and self-assessed health, tend to show inequalities to the disadvantage of the poor.
Thirdly, there are large variations in the extent of health inequalities across countries, although these variations themselves vary with the indicators of health and socioeconomic status used. For example, Latin America appears to have higher inequalities in child health between poor and non-poor than other parts of the developing world, whatever health indicator is used. By contrast, inequalities in child mortality and malnutrition are less pronounced in sub-Saharan Africa than in North Africa, Asia, and the Near East, but the opposite is true of inequalities concerning diarrhoea and acute respiratory infections (47).
Fourthly, socioeconomic inequalities in health seem to be widening rather than narrowing. This is true of both the developing (4852) and industrialized world (28, 5356).
Causes of health inequalities: proximate determinants
Fig. 2 outlines an approach to conceptualizing the various routes by which health outcomes are determined (7). It provides a framework for understanding health inequalities between the poor and the better-off.
How do proximate determinants vary across socioeconomic groups?
The various factors at the household and community levels which have a direct influence on health outcomes are referred to in some circles as the proximate determinants of health (57) and in others as the health inputs into the production of health (58). A good deal is known about what they are and their etiology (7, 59). They vary widely between households and they tend to be worse in poor households than in better-off households. At one level this explains why there are socioeconomic inequalities in health and why they disfavour the poor. However, the inequalities in the proximate determinants of health vary between determinants and, like inequalities in health itself, also vary between countries.
This is most striking in the case of health service utilization. In the OECD countries the poor tend to use health services more than the better-off, and the question arises as to whether, in the light of their greater medical needs, the greater utilization is sufficient (6065). The picture is quite different in the developing world. Poor children in poor countries are typically far less likely to be immunized than better-off children (39). This is so even in countries with a national immunization programme under which services are provided free at the point of use (66). The utilization of oral rehydration therapy is lower among poor children than among the better off, even though the incidence of diarrhoea is greater among the poor (39). In those countries where the use of oral rehydration therapy is higher among the poor, the inequality is far smaller than the inequality in the incidence of diarrhoea.
The failure of health services to reach the poor in developing countries, despite their higher disease burden, is not just a matter of the better-off using their higher incomes to purchase care from the private sector. The poor also receive less of government subsidies to the health sector (6771). The bias in favour of the rich is especially pronounced in the hospital sector, which benefits from the largest part of government spending. However, a few developing countries apparently manage to achieve pro-poor distributions of public spending on health care, e.g. Costa Rica and Malaysia (47). In India, the State of Kerala manages to secure a roughly even distribution of health subsidies across income groups (72).
Less quantitative evidence seems to be available on the degree of inequality in other proximate determinants of health. The prevalence of breastfeeding is often higher among lower socioeconomic groups (48) but this does not seem to be true of the other proximate determinants of child health. Levels of alcohol consumption are higher among the lower socioeconomic groups in several countries of eastern Europe, Finland, and France (73). Smoking and poor diet tend to be concentrated among the lower socioeconomic groups in the United States of America and northern Europe but not in southern Europe and France (73). Among black people in South Africa, smoking is positively associated with socioeconomic status, whereas among white people the opposite is true (74).
Contributions of inequalities by proximate determinants
Knowing simply that the distribution of one or other proximate determinant disfavours the poor does not tell us how important this inequality is as part of the explanation of health inequalities. The contribution to inequality in health by a particular proximate determinant depends partly on its distribution across socioeconomic groups and partly on its impact on health (52). The Whitehall study of British civil servants assessed the relative contribution of inequalities in the various proximate determinants of health to inequalities in health. North et al. (75) tried to explain the strong inverse relation between grade of employment and absence from work because of sickness. Several risk factors were identified, including health-related behaviours, work characteristics, low levels of job satisfaction, and adverse social circumstances outside work. Standardization methods showed that inequalities in these risk factors accounted for only about a third of the differences in such absence between grades. Marmot et al. (76) undertook a similar exercise looking at coronary heart disease.
Causes of health inequalities: underlying determinants
Why are there inequalities in the proximate determinants of health? Fig. 2 shows the influences of household resources, community factors, and health system determinants. In each of these underlying determinants of health (57, 77, 78) the poor tend to be disadvantaged.
How do underlying determinants vary across socioeconomic groups?
Income and assets, whose inequalities vary widely by country (79), are a key component of household resources. In developing countries under otherwise constant conditions, higher income is associated with more frequent and more intensive use of health services in both the private and public sectors (67); the use of modern health care providers rather than traditional practitioners (67); and the number of children a woman has and the age at which she has her first child. Most dietary and child-feeding practices also improve with higher levels of income, as do sanitary practices (e.g. handwashing and disposal of faeces). The human assets of knowledge, literacy, and education, whose levels tend to be lower among the poor (39, 80), also influence household decisions with regard to the proximate determinants of health. Education, especially that of women, is strongly associated with many behaviours and choices that are conducive to good health, even after controlling for income (77). It is not just the levels of these variables that matter, but also their distribution within the household, especially between men and women. A low level of control over household resources by women, which seems especially likely in poor households, often harms health outcomes for them and their families (7).
With regard to community factors it is important to consider environmental and geographical influences. It is comparatively difficult to reach a health centre if roads are impassable during the rainy season. The environment also matters. Good sanitary practices are relatively difficult to maintain if the conditions of water supply and sanitation in the local community are poor. Communities often share similar values and norms, which, through peer pressure, often play a large part in shaping health behaviours (81). At the community level, as at the household level, the poor are likely to be disadvantaged. For example, they are more likely to live in remote areas. In poor communities, moreover, social pressures among teenagers tend to be strongest and attitudes towards women tend to be least favourable to good health outcomes (81).
There is a good deal of evidence on the impacts of health system determinants on health outcomes and health service utilization. Availability, possibly defined in terms of staff in local health facilities, often emerges as an important determinant of service utilization and health outcomes (82 84). Accessibility, i.e. the ease with which people can reach facilities, is also important. Travel time is significant in this connection: it depends on the distance people have to travel, the transport system, road infrastructure, and geographical factors. Distance is the most frequently encountered variable in empirical studies of utilization and often has a significant impact on it (82, 8588). A higher money price tends to reduce or at least delay utilization, especially among the poor, unless accompanied by improvements in service quality (89, 90). Insurance tends to raise the usage of health services (91, 92). Quality, or, more exactly, perceived quality, also increases the demand for health services (82, 88, 89, 93). In most of these areas the poor are disadvantaged. They tend to have to travel further (93) and for longer periods (67) in order to reach health facilities. The quality of care, interpreted broadly to include service and amenities as well as technical quality, also tends to be comparatively low in facilities serving the poor (87). The poor, who are the most price-sensitive users of health services, frequently face a higher price at the point of use because they are less likely to have insurance coverage, whether private (91) or public (94). This tendency is sometimes offset by fee-waiver schemes, although in practice these often have the effect of exempting the near-poor rather than the poor (90, 94, 95).
Contributions of inequalities by underlying determinants
As with the proximate determinants of health, knowing simply that the distribution of one or other underlying determinant disfavours the poor does not indicate how important this inequality is as part of the explanation of health inequalities. The method used in the Whitehall study (75) is one way of tackling this issue. Another is to use decomposition analysis, linking the inequalities in the various determinants of health, via a regression model of the determinants of health, with a measure of inequalities in health (52).
This method was used to unravel the underlying causes of inequalities in childhood survival in Cebu in the Philippines (96). Several significant determinants of child survival were identified, including mother's education, household income, health insurance coverage, drinking-water availability, sanitation conditions, travel time or distance to various health service facilities, staffing levels in local primary care facilities, and local availability of key drugs. In respect of its contribution to survival inequalities between poor and non-poor children, income was the most important of these. Inequalities in mother's education were also found to be significant. Inequalities in health service availability were relatively small, so that although they were found to be important influences on the average child's survival prospects they did not help to explain survival differences between poor and non-poor children. The same method was used to examine the causes of increased inequalities in malnutrition in Viet Nam during 199398 (52) and the causes of inequalities in self-assessed health amongst 33-year-olds in the United Kingdom (97). In both studies, as in the Cebu study, inequalities in variables at the level of the individual (e.g. education) and the household (e.g. income, housing, the availability of safe drinking-water, and sanitation) together accounted for a large share of health inequality.
Poverty and paying for health care
In addition to its concern for improving the health of the poor, the international development community is also concerned with the impact of the costs of health care and lost income on a household's ability to purchase things other than health care. In other words, in addition to the desire to ensure that health improvements occur, especially among the poor, there is a desire to ensure that achieving this does not lead to an excessive decline in the living standards of the households involved.
There are various possible ways in which to interpret these concerns (21). One is that the distribution of health care costs should not be such as to increase income inequality. Regressive payments, i.e. payments that absorb a larger share of a poor household's prepayment income than that of a rich household's, violate this requirement. Out-of-pocket payments are regressive in most OECD countries (98, 99) and in some developing countries, including rural Bangladesh (100), Burkina Faso (101), China (102), Paraguay (101), Sierra Leone (103), and Thailand (104). In several developing countries, however, they are either proportional to income, as in Viet Nam (21, 105), or progressive, as in Guatemala (101), India (72), Mexico (106), Nepal (107) and South Africa (101). In the first group of countries the poor apparently use services but pay a large share of their income for them, while in the latter group it is primarily the better-off who use and pay for health services. A concern over the regressivity of out-of-pocket payments overlooks the possibility that this might be offset, at least in part, by progressivity in prepayments, i.e. taxes, social insurance contributions and private insurance premiums. In many OECD countries the progressivity of these indirect payments is, in fact, more than sufficient to offset the regressivity of direct payments (98).
A second interpretation of these concerns over health care payments is that households should not have to spend more than a specific percentage of their income on health care, payments above this threshold being classified as catastrophic (21). In several countries more than 1% of all households recently spent half or more of their non-food expenditure on health care (24). Another recent study explored trends in catastrophic health spending in Viet Nam, and found that irrespective of the cut-off point used and irrespective of whether spending was calculated as a share of total or non-food expenditure, the proportion of the population making catastrophic payments fell between 1993 and 1998 (21).
A third interpretation is that health care costs should not drive households into or further into poverty. The poverty impact can be measured by the change in the poverty head count (i.e. the proportion of the population in poverty), or the change in the poverty gap (i.e. the average shortfall from the poverty line), induced by health care payments (21). With the poverty gap it is possible to distinguish between already poor people becoming even poorer and previously non-poor people becoming poor. Calculations along these lines suggested that out-of-pocket spending on hospital care might have raised the head count in India by 2% (72), and that, for a food-based poverty line, overall spending on health care in Viet Nam might have added approximately 4.4% to the head count in 1993 and 3.4% in 1998 (21). The impact on the poverty gap in Viet Nam was a good deal smaller than the impact on the head count (1.4% and 0.8% in 1993 and 1998 respectively) and three-quarters of this impact was attributable to already poor people becoming even poorer. Most of the poverty impact of out-of- pocket payments in Viet Nam was attributable to non-hospital expenses.
Health sector inequalities and public policy
Broad-brush studies of policy effects
In a comparative study of nine OECD countries it was found that inequality in self-assessed health was not significantly associated with total health care expenditure per capita, the percentage spent publicly, or gross domestic product per capita, but was positively and significantly associated with income inequality (36). However, in another investigation in which aggregate data from developing countries and a decomposition approach were used, it was found that public spending on health had a larger impact on child mortality among the poor than among the non-poor, and hence served to reduce health inequality (108). In another comparative study it was found that differences between OECD countries in the extent of inequality and inequity in health care utilization partly reflected differences in how the poor and better-off fared with respect to user fees, but not in the extent of insurance coverage (63). This study also found evidence that the distribution of utilization across income groups reflected some characteristics of the delivery system, e.g. how providers were paid, but not others, e.g. the presence of a general practitioner gatekeeper scheme. In another study of OECD countries it was reported that the progressivity of combined direct and indirect health care payments closely reflected the financing mix of the system. In tax-financed systems, payments tended to be broadly proportional to income; in social insurance systems, they tended at worst to be mildly regressive but were sometimes proportional or even slightly progressive; and in predominantly privately financed systems, payments tended to be regressive (98).
Effects of specific programmes
Yip & Berman (109) examined inequalities in insurance coverage between poor and better-off children under Egypt's School Health Insurance Programme (SHIP). They also exploited exogenous differences in health insurance coverage in order to assess the programme's impact on the distribution of both health service utilization and out-of-pocket payments. Although SHIP was intended to cover all children in education, i.e. those aged 618 years, at the time of the survey some children attending school had not yet been covered. These children provided a control group but the authors used regression analysis to control for other differences between children who were covered and those who were not covered. SHIP coverage rose with income, mostly because poorer children were less likely to be in school but also because children who were in school but not yet covered were more likely to be poor. SHIP coverage increased the probability of a visit to a formal health care provider for all income groups but there was an especially large impact among children in the poorest quintile. SHIP coverage resulted in lower out-of- pocket payments for all income groups but the impact was very much smaller in the poorest and richest quintiles than in the middle of the income distribution.
Victora et al. (48) presented evidence on Ceará's maternal and child health programme in Brazil, which aimed specifically to narrow health inequalities. Substantial improvements were observed in average levels of service usage and outcomes following the introduction of the programme. However, although there was a decline in inequalities in vaccination coverage, weighing, and the utilization of oral rehydration therapy, there was an increase in inequality between poor and better-off children in all three of the outcomes studied. The authors also examined the combined impact of a variety of programmes introduced in the city of Pelotas, Brazil. These included a large increase in the number of first-line government health facilities, the introduction of three neonatal care units, and a general increase in government expenditure on preventive and curative health. Over the period studied the proportions of pregnant women receiving antenatal care and of children receiving three doses of diphtheria/pertussis/tetanus vaccine in their first year of life increased, while inequalities in the utilization of these services fell. Furthermore, declines in the average rates of infant mortality and malnutrition were accompanied by reductions in inequalities in these outcomes.
Before-and-after comparisons with control groups, a more effective way of establishing programme impact than simple before-and-after studies, are relatively rare in this field. One such study was that of Bhuiya et al. (110), who considered the impact on differentials in mortality of children between the ages of 1 and 5 years of a maternal and child health programme delivered by Bangladesh's International Centre for Diarrhoeal Disease. In some areas not covered by the programme, i.e. the control group, only government health services were provided, and in others a nongovernmental organization (BRAC, formerly known as the Bangladesh Rural Advancement Committee) was operating a socioeconomic development programme in addition to government health service provision. The BRAC programme was aimed at both poverty alleviation and women's development and most of its activities, which included essential health care, were targeted at poor women. During the study period, both areas saw a reduction in child mortality rates by slightly over 40%, the reduction being marginally higher in the control area. However, the spread of reductions across income groups was quite different. In the control area the biggest percentage reduction was in the richest group, whereas in the area of the maternal and child health programme the largest reductions were among the poorest group.
Diop et al. undertook a before-and-after comparison of two districts in Niger, where financing reforms were introduced in the early 1990s (111). Before the study began, drug availability was improved, health personnel were trained, and management and supervision capacity was strengthened. In Say District, user fees were introduced with exemptions for certain categories, and fee revenues were retained at the district level and used to finance pharmaceutical products and to set up a solidarity fund. In Boboye District, lower fees were set but a local tax was introduced and earmarked for the district's health fund. In Illéla District, which served as a control, the status quo was maintained. In the poorest quarter of the populations in both Illéla and Say, utilization of public health facilities declined during the test period. The decline was larger in Say, where fees were charged, and in this district the decline in utilization was proportionally larger among the poorest quarter of the population than among the population as a whole. However, neither district's change in utilization among the poorest quarter was statistically significant. By contrast, utilization doubled among the poorest quarter of the population under the "fee-cum-tax" system in Boboye. This change, which was statistically significant, was much larger than the change for the district's population as a whole.
Three points are worth highlighting. First, we know a good deal about the extent of health inequalities between poor and non-poor in developing countries, and a reasonable amount about inequalities in health determinants. Most striking in this connection is the failure of publicly financed health care to reach the poor in almost all developing countries, an issue that deserves serious attention from governments and aid agencies.
Second, too little is known about the relative importance of inequalities in the determinants of health and health service utilization. What we do know suggests that inequalities in health, and most probably in service utilization, very largely reflect inequalities in variables at the individual and household levels, such as education, income, location, and housing characteristics. This indicates that policies aimed at combating health sector inequalities should aim to reduce both inequalities in, for example, the quality and availability of health services (i.e. the supply side), and inequalities in income, knowledge, especially health-specific knowledge, accessibility of health services, the availability of safe drinking-water, and sanitation, and so on (i.e. the demand side). Health ministries should work more closely with other ministries, but should also take a wider view, e.g. exploring alternative delivery methods to reach the poor and finding improved ways of increasing knowledge among the poor about healthy behaviours.
Third, too little is known about the impact of programmes and policies on health sector inequalities. There is undoubtedly a large gap in our knowledge on how best to reach the poor in the health sector. In order to fill this gap, more work is needed along the lines of the above studies related to health sector inequalities and public policy.
I am grateful to George Alleyne for inviting me to write this paper for the Commission on Macroeconomics and Health, and to my co-authors of the chapter on health, nutrition, and population in the World Bank's Poverty reduction strategy sourcebook on which I have drawn. I am also grateful to two anonymous referees and the editors of the Bulletin of the World Health Organization for helpful comments on an earlier version.
Conflicts of interest: none declared.
Pauvreté et inégalités dans le secteur de la santé
Pauvreté et mauvaise santé vont de pair. Les pays pauvres tendent à avoir de plus mauvais résultats dans le domaine de la santé que les pays plus nantis, et à l'intérieur d'un même pays les pauvres ont une moins bonne santé que les riches. Cette association révèle une relation de causalité à double sens : la pauvreté engendre la mauvaise santé, et la mauvaise santé entretient la pauvreté. Le présent article expose les faits concernant les inégalités de santé entre pauvres et non-pauvres et les conséquences des dépenses de santé sur l'appauvrissement et les inégalités de revenus. Il fait brièvement le point des connaissances sur les causes des inégalités et sur l'efficacité des politiques destinées à les combattre. D'après l'auteur, on ne connaît pas assez l'impact de telles politiques, malgré la variété des techniques de mesure et l'abondance des données sur l'étendue des inégalités et sur leurs causes.
Pobreza y desigualdades en el sector de la salud
La pobreza y la mala salud son fenómenos interrelacionados. Los países pobres tienden a presentar peores resultados sanitarios que los más pudientes, y dentro de cada país las personas pobres tienen más problemas de salud que las acomodadas. Esta asociación refleja una relación de causalidad que funciona en los dos sentidos: la pobreza genera mala salud, y la mala salud hace que los pobres sigan siendo pobres. En este artículo se examina la evidencia disponible respecto a las desigualdades sanitarias entre las personas pobres y las que no lo son, así como respecto a las repercusiones que en forma de empobrecimiento y desigualdad de ingresos pueden tener los gastos en atención de salud. Se hace una exposición sucinta de los actuales conocimientos sobre las causas de las desigualdades y sobre la eficacia de las políticas destinadas a combatirlas, y se señala que es demasiado poco lo que se sabe acerca de los efectos de esas políticas, pese a las abundantes técnicas de medición disponibles y a los muchos datos obtenidos sobre la magnitud y las causas de las desigualdades.
1. World Bank. Confronting AIDS: public priorities in a global epidemic. Oxford: Oxford University Press; 1999. [ Links ]
2. Bloom D, Sachs J. Geography, demography and economic growth in Africa. Brookings Papers on Economic Activity 1998;2:207-95. [ Links ]
3. Eastwood R, Lipton M. The impact of changes in human fertility on poverty. Journal of Development Studies 1999;36:1-30. [ Links ]
4. Narayan D, Patel R, Schafft K, Rademacher A, Koch-Schulte S. Voices of the poor: can anyone hear us? New York: Oxford University Press; 2000. [ Links ]
5. Pritchett L, Summers LH. Wealthier is healthier. Journal of Human Resources 1996;31:841-68. [ Links ]
6. World Bank. World development report 2000/2001: attacking poverty. Oxford and New York: Oxford University Press; 2000. [ Links ]
7. Claeson M, Griffin CG, Johnston TA, McLachlan M, Soucat ALB, Wagstaff A, et al. Health, nutrition and population. In: Poverty reduction strategy sourcebook. Washington (DC): World Bank; 2001. [ Links ]
8. World Bank. Health, nutrition and population sector strategy. Washington (DC): World Bank; 1997. [ Links ]
9. World Health Organization. The world health report 1999. Making a difference. Geneva: World Health Organization; 1999. [ Links ]
10. Department for International Development. Better health for poor people. London: Department for International Development; 1999. [ Links ]
12. Department for International Development. Eliminating world poverty: a challenge for the 21st century. London: The Stationery Office; 1997. White Paper on international development. [ Links ]
13. Sen A. Development as freedom. New York: Knopf; 1999. [ Links ]
14. Department of Health. Tackling health inequalities: consultation on a plan for delivery. London: Department of Health; 2001. [ Links ]
15. Le Grand J. Equity, health and health care. Social Justice Research 1987; 1:257-74. [ Links ]
16. Alleyne GAO, Casas J, Castillo-Salgado C. Equality, equity: why bother? Bulletin of the World Health Organization 2000;78:76-7. [ Links ]
17. Wagstaff A. Economics, health and development: some ethical dilemmas facing the World Bank and the international community. Journal of Medical Ethics 2001;27:262-7. [ Links ]
18. Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M. Introduction. In: Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M, editors. Challenging inequities in health: from ethics to action. Oxford: Oxford University Press; 2001. [ Links ]
19. Whitehead M. The concepts and principles of equity and health. International Journal of Health Services 1992;22:429-45. [ Links ]
20. Braveman P, Starfield B, Geiger H. World health report 2000: how it removes equity from the agenda for public health monitoring and policy. BMJ 2001;323:678-80. [ Links ]
21. Wagstaff A, van Doorslaer E. Paying for health care: quantifying fairness, catastrophe and impoverishment, with applications to Viet Nam 199398. Washington (DC): World Bank; 2001. Policy Research Working Paper No. 2715. [ Links ]
22. Organisation for Economic Co-operation and Development. The reform of health care: a comparative analysis of seven OECD countries. Paris: Organisation for Economic Co-operation and Development; 1992. [ Links ]
23. Murray C, Knaul F, Musgrove P, Xu K, Kawabata K. Defining and measuring fairness in financial contribution to the health system. Geneva: World Health Organization; 2000. GPE Discussion Paper No. 24. [ Links ]
24. World Health Organization. The world health report 2000. Health systems: improving performance. Geneva: World Health Organization; 2000. [ Links ]
25. Smith J. Healthy bodies and thick wallets: the dual relation between health and socioeconomic status. Journal of Economic Perspectives 1999;13:145- 66. [ Links ]
26. Wagstaff A, Paci P, van Doorslaer E. On the measurement of inequalities in health. Social Science and Medicine 1991;33:545-57. [ Links ]
27. Kakwani N, Wagstaff A, van Doorlsaer E. Socioeconomic inequalities in health: measurement, computation and statistical inference. Journal of Econometrics 1997;77:87-104. [ Links ]
28. Mackenbach JP, Kunst AE. Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Social Science and Medicine 1997;44:757-71. [ Links ]
29. Drever F, Whitehead M, editors. Health inequalities: decennial supplement. London: The Stationery Office; 1997. Series DS No. 15. [ Links ]
30. Fox A. Health inequalities in Europe. Aldershot: Gower; 1989. [ Links ]
31. Kunst AE, Geurts JJ, van den Berg J. International variation in socioeconomic inequalities in self reported health. Journal of Epidemiology and Community Health 1995;49:117-23. [ Links ]
32. Mackenbach JP, Kunst AE, Cavelaars AEJM, Groenhof F, Geurts JJM, EU Working Group on Socioeconomic Inequalities in Health. Socioeconomic inequalities in morbidity and mortality in western Europe. Lancet 1997; 349:1655-9. [ Links ]
33. Marmot M, Davey Smith G, Stansfeld S, Patel C, North F, Head J, et al. Health inequalities among British civil servants: the Whitehall II study. Lancet 1991;337:1387-93. [ Links ]
34. Townsend P, Davidson N. Inequalities in health: the Black report. Harmondsworth: Penguin; 1982. [ Links ]
35. Vagero D, Erikson R. Socioeconomic inequalities in morbidity and mortality in western Europe. Lancet 1997;350:516-7. [ Links ]
36. Van Doorslaer E, Wagstaff A, Bleichrodt H, Caonge S, Gerdtham U-G, Gerfin M, et al. Income-related inequalities in health: some international comparisons. Journal of Health Economics 1997;16:93-112. [ Links ]
37. Whitehead M. William Farr's legacy to the study of health inequalities. Bulletin of the World Health Organization 2000;78:86-7. [ Links ]
38. Bonilla-Chacin M, Hammer J. Life and death among the poorest. Washington (DC): World Bank; 1999. [ Links ]Unpublished document.
39. Gwatkin D, Rutstein S, Johnson K, Pande R, Wagstaff A. Socioeconomic differences in health, nutrition and population. Washington (DC): World Bank; 2000. Health, Nutrition and Population Discussion Paper. [ Links ]
40. Wagstaff A, Watanabe N. Socioeconomic inequalities in child malnutrition in the developing world. Washington (DC): World Bank; 2000. Policy Research Working Paper No. 2434. [ Links ]
41. Wagstaff A. Socioeconomic inequalities in child mortality: comparisons across nine developing countries. Bulletin of the World Health Organization 2000;78:19-29. [ Links ]
42. Filmer D. Malaria among the poor and less poor in sub-Saharan Africa. Washington (DC): World Bank; 2001. [ Links ]Unpublished document.
43. Baker J, van der Gaag J. Equity in health care and health care financing: Evidence from five developing countries. In: Van Doorslaer E, Wagstaff E, Rutten F, editors. Equity in the finance and delivery of health care: an international perspective. Oxford: Oxford University Press; 1993. [ Links ]
44. Van Doorslaer E, Wagstaff A, Rutten F, editors. Equity in the finance and delivery of health care: an international perspective. Oxford: Oxford University Press; 1993. [ Links ]
45. Wagstaff A. Poverty and health. Boston (MA): WHO Commission on Macroeconomics and Health; 2001.Working Group No.1, Working Paper No. 5. [ Links ]
46. Blaxter M. A comparison of measures of inequality in morbidity. In: Fox J, editor. Health inequalities in European countries. Aldershot: Gower;1989. p. 199-230. [ Links ]
47. Wagstaff A. Inequalities in health in developing countries: swimming against the tide? Washington (DC): World Bank; 2001. Policy Research Working Paper. [ Links ]
48. Victora C, Barros F, Vaughan J, Silva A, Tomasi E. Explaining trends in inequities: evidence from Brazilian child health studies. Lancet 2000;356:1093-8. [ Links ]
49. Wagstaff A, Nguyen N. Poverty and survival prospects of Vietnamese children under Doi Moi. Washington (DC): World Bank; 2001. [ Links ]Policy Research Working Paper.
50. Stecklov G, Bommier A, Boerma T. Trends in equity in child survival in developing countries: an illustrative analysis using Ugandan data. Chapel Hill (NC): Carolina Population Center, University of North Carolina at Chapel Hill; 1999. [ Links ]Unpublished document.
51. Vega J, Hollstein R, Delgado I, Perez K, Carrasco S, Marshall G, et al. Chile: socioeconomic differentials and mortality in a middle-income nation. In: Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M, editors. Challenging inequalities in health: from ethics to action. Oxford: Oxford University Press; 2001. [ Links ]
52. Wagstaff A, van Doorslaer E, Watanabe N. On decomposing the causes of health sector inequalities, with an application to malnutrition inequalities in Viet Nam. Washington (DC): World Bank; 2001. Policy Research Working Paper No. 2714. [ Links ]
53. Graham H. The challenge of health inequalities. In: Graham H, editor. Understanding health inequalities. Buckingham and Philadelphia (PA): Open University Press; 2000. [ Links ]
54. Propper C, Upward R. Need, equity and the NHS: the distribution of health care expenditure 197487. Fiscal Studies 1992;13:1-21. [ Links ]
55. Schalick LM, Hadden WC, Pamuk E, Navarro V, Pappas G. The widening gap in death rates among income groups in the United States from 1967 to 1986. International Journal of Health Services 2000;30:13-26. [ Links ]
56. Pappas G, Queen S, Hadden W, Fisher G. The increasing disparity in mortality between socioeconomic groups in the United States, 1960 and 1986. New England Journal of Medicine 1993;329:103-9. [ Links ]
57. Mosley W, and Chen L. An analytical framework for the study of child survival in developing countries. Population and Development Review 1984; 10:25-45. [ Links ]
58. Grossman M. The demand for health: a theoretical and empirical investigation. New York: National Bureau of Economic Research; 1972. [ Links ]
59. World Health Organization. CHD 19961997 report. Geneva: World Health Organization;1998. Unpublished document WHO/CHD/98.5. [ Links ]
60. Le Grand J. The distribution of public expenditure: the case of health care. Economica 1978;45:125-42. [ Links ]
61. Le Grand J. The strategy of equality: redistribution and the social services. London and Boston (MA): Allen and Unwin; 1982. [ Links ]
62. Van Doorslaer E, Wagstaff A, Calonge S, Christiansen T, Gerfin M, Gottschalk P, et al. Equity in the delivery of health care: some international comparisons. Journal of Health Economics 1992;11:389-411. [ Links ]
63. Van Doorslaer E, Wagstaff A, van der Burg H, Christiansen T, De Graeve D, Gerdtham U-G, et al. Equity in the delivery of health care in Europe and the US. Journal of Health Economics 2000;19:553-84. [ Links ]
64. Wagstaff A, Van Doorslaer E, Paci P. On the measurement of horizontal inequity in the delivery of health care. Journal of Health Economics 1991;10:169- 205. [ Links ]
65. Wagstaff A, van Doorslaer E. Measuring and testing for inequity in the delivery of health care. Journal of Human Resources 2000; 35:716-33. [ Links ]
66. Pande R, Yazbeck A. What's in a country average? Income, gender, and regional inequalities in immunization in India. Washington (DC): World Bank; 2001. [ Links ]Unpublished document.
67. Castro-Leal F, Dayton J, Demery L, Mehra K. Public social spending in Africa: Do the poor benefit? World Bank Research Observer 1999;14:49-72. [ Links ]
68. Castro-Leal F, Dayton J, Demery L, Mehra K. Public spending on health care in Africa: do the poor benefit? Bulletin of the World Health Organization 2000;78:66-74. [ Links ]
69. Filmer D, Hammer J, Pritchett L. Health policy in poor countries: weak links in the chain. Washington (DC): World Bank; 1998. Policy Research Working Paper No.1874. [ Links ]
70. Sahn D, Younger S. Expenditure incidence in Africa: microeconomic evidence. Fiscal Studies 2000;21:329-48. [ Links ]
71. Yaqub S. How equitable is public spending on health and education? Washington (DC): World Bank; 1999. Background Paper for World Development Report 2000/1. [ Links ]
72. World Bank. Raising the sights: better health systems for India's poor. Washington (DC): World Bank; 2001. [ Links ]
73. Kunst A. Cross-national comparisons of socioeconomic differences in mortality. The Hague: CIP-Gegevens Koninklijke Bibliotheek; 1997. [ Links ]
74. Marmot M, Mustard J. Coronary heart disease from a population perspective. In: Evans R, Barer M, Marmor T, editors. Why are some people healthy and others not? New York: Aldine de Gruyter; 1994. [ Links ]
75. North F, Syme SL, Feeney A, Head J, Shipley MJ, Marmot MG. Explaining socioeconomic differences in sickness absence: the Whitehall II study. BMJ 1993;306:361-6. [ Links ]
76. Marmot M, Rose G, Shipley M, Hamilton P. Employment grade and coronary heart disease in British civil servants. Journal of Epidemiology and Community Health 1978;32:244-9. [ Links ]
77. Cebu Study Team. Underlying and proximate determinants of child health: The Cebu longitudinal health and nutrition study. American Journal of Epidemiology 1991;133:185-201. [ Links ]
78. Schultz T. Studying the impact of household economic and community variables on child mortality. Population and Development Review 1984;10:215-35. [ Links ]
79. World Bank. World development indicators 2001. Washington (DC): World Bank; 2001. [ Links ]
80. Filmer D, Pritchett L. The effect of household wealth on educational attainment: evidence from 35 countries. Population and Development Review 1999;25:85-120. [ Links ]
81. Woolcock M, Narayan M. Social capital: implications for development theory, research and policy. World Bank Research Observer 2000;15:225-49. [ Links ]
82. Lavy V, Strauss J, Thomas D, de Vreyer P. Quality of care, survival and health outcomes in Ghana. Journal of Health Economics 1996;15:333-57. [ Links ]
83. Panis C, Lillard L. Health inputs and child mortality. Journal of Health Economics 1994;13:455-89. [ Links ]
84. Rosenzweig M, Wolpin K. Governmental interventions and household behavior in a developing country: anticipating the unanticipated consequences of social programs. Journal of Development Economics 1982; 10:209-25. [ Links ]
85. Benefo K, Schultz T. Fertility and child mortality in Côte d'Ivoire and Ghana. World Bank Economic Review 1996;10:123-58. [ Links ]
86. Mwabu G, Ainsworth M, Nyamete A. Quality of medical care and choice of medical treatment in Kenya: an empirical analysis. Journal of Human Resources 1993;28:838-62. [ Links ]
87. Thomas D, Lavy V, Strauss D. Public policy and anthropometric outcomes in the Côte d'Ivoire. Journal of Public Economics 1996;61:155-92. [ Links ]
88. Wong E, Popkin B, Guilkey D, Akin J. Accessibility, quality of care and prenatal care use in the Philippines. Social Science and Medicine 1987;24:927- 44. [ Links ]
89. Alderman H, Lavy V. Household responses to public health services: cost and quality tradeoffs. World Bank Research Observer 1996;11:3-22. [ Links ]
90. Gilson L. The lessons of user fee experience in Africa. Health Policy and Planning 1997;12:273-85. [ Links ]
91. Gertler P, Sturm R. Private health insurance and public expenditures in Jamaica. Journal of Econometrics 1997;77:237-58. [ Links ]
92. Schwartz J, Akin J, Popkin B. Price and income elasticities of demand for modern health care: the case of infant delivery in the Philippines. World Bank Economic Review 1988;2:49-76. [ Links ]
93. Akin J, Hutchinson P. Health care facility choice and the phenomenon of bypassing. Health Policy and Planning 1999;14:135-51. [ Links ]
94. World Bank, Swedish International Development Cooperation Agency, Australian Agency for International Development, Royal Netherlands Embassy, Ministry of Health of Viet Nam. Growing healthy: a review of Viet Nam's health sector. Hanoi: World Bank; 2001. [ Links ]
95. Leighton C, Diop F. Protection of the poor under cost recovery. Bethesda (MD): Abt Associates;1999. [ Links ]Unpublished document.
96. Wagstaff A. Unpacking the causes of inequalities in child survival: the case of Cebu, the Philippines. Washington (DC): World Bank; 2000. [ Links ]Unpublished document.
97. Wagstaff A, Paci P, Joshi H. Inequalities in health: Who you are? Where you live? Or who your parents were? Evidence from a cohort of British 33-year-olds. Washington (DC): World Bank; 2001. Policy Research Working Paper No.2713. [ Links ]
98. Wagstaff A, van Doorslaer E, van der Berg H, Calonge S, Christiansen T, Citoni G. Equity in the finance of health care: some further international comparisons. Journal of Health Economics 1999;18:263-90. [ Links ]
99. Van Doorslaer E, Wagstaff A, van der Berg H, Christiansen T, Citoni G, Di Biase R, et al. The redistributive effect of health care finance in twelve OECD countries. Journal of Health Economics 1999;18:291-314. [ Links ]
100. Sen B. Health and poverty in the context of country development strategy: a case study on Bangladesh. Geneva: World Health Organization; 1997. Macroeconomics and Health Development Series No. 26. Unpublished document WHO/ICO/MESD.26. [ Links ]
101. Makinen M, Waters H, Rauch M, Almagambetova N, Bitran R, Gilson L, et al. Inequalities in health care use and expenditures: empirical data from eight developing countries and countries in transition. Bulletin of the World Health Organization 2000;78:55-65. [ Links ]
102. Gao J, Tang S, Tolhurst R, Rao K. Changing access to health services in urban China: implications for equity. Health Policy and Planning 2001;16:302-12. [ Links ]
103. Fabricant SJ, Kamara CW, Mills A. Why the poor pay more: household curative expenditures in rural Sierra Leone. International Journal of Health Planning and Management 1999;14:179-99. [ Links ]
104. Pannarunothai S, Mills A. The poor pay more: health-related inequality in Thailand. Social Science and Medicine 1997;44:1781-90. [ Links ]
105. Wagstaff A. Measuring equity in health care financing: reflections on and alternatives to WHO's fairness of financing index. Washington (DC): World Bank; 2000. [ Links ]Policy Research Working Paper No. 2550.
106. Parker S, Pier E. Mexico. In: Greene E, Zevallos J, Suarez R, editors. Health systems inequalities and poverty in Latin America and the Caribbean. Washington (DC): Pan American Health Organization/World Bank; 1999. [ Links ]
107. Hotchkiss DR, Rous JJ, Karmacharya K, Sangraula P. Household health expenditures in Nepal: implications for health care financing reform. Health Policy and Planning 1998;13:371-83. [ Links ]
108. Bidani B, Ravallion M. Decomposing social indicators using distributional data. Journal of Econometrics 1997;77:125-39. [ Links ]
109. Yip W, Berman P. Targeted health insurance in a low income country and its impact on access and equity in access: Egypt's school health insurance. Health Economics 2001;10:207-20. [ Links ]
110. Bhuiya A, Chowdhury M, Ahmed F, Adams A. Bangladesh: an intervention study of factors underlying increasing equity in child survival. In: Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M, editors. Challenging inequities in health: from ethics to action. Oxford: Oxford University Press; 2001. [ Links ]
111. Diop F, Yazbeck A, Bitran R. The impact of alternative cost recovery schemes on access and equity in Niger. Health Policy and Planning 1995;10:223-40. [ Links ]
* Based on: Wagstaff A. Poverty and health. (CMH Working Paper Series, Paper No. WG1: 5. Available at: URL: www.cmhealth.org/wg1_paper5.pdf).
1 Lead Economist, The World Bank, Washington, DC, USA; and Professor of Economics, School of Social Sciences, University of Sussex, Brighton, England. Correspondence should be addressed to the author at The World Bank, 1818 H Street NW, Washington, DC 20433, USA (email: email@example.com).
The findings, interpretations, and conclusions are entirely the author's and do not necessarily represent the views of the World Bank, its executive directors, or the countries they represent.
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