EMRO Technical Publications Series
40
Health inequities in the Eastern Mediterranean Region Selected country case studies
EMRO Technical Publications Series
40
Health inequities in the Eastern Mediterranean Region Selected country case studies
WHO Library Cataloguing in Publication Data
World Health Organization. Regional Office for the Eastern Mediterranean Health inequities in the Eastern Mediterranean Region: selected country case studies/World Health Organization. Regional Office for the Eastern Mediterranean p..- (EMRO Technical Publications Series; 40) ISBN: 978–92–9021–876–0 ISBN: 978–92–9021–942–2 (online) ISSN: 1020–0428 1. Health Services Accessibility – statistics & numerical data – Eastern Mediterranean Region 2. Health Status Indicators 3. Delivery of Health Care – statistics & numerical data 4. Socioeconomic Factors 5. Statistics I. Title II. Regional Office for the Eastern Mediterranean III. Series (NLM Classification: WA 900)
©World Health Organization 2014 All rights reserved. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by the World Health Organization to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall the World Health Organization be liable for damages arising from its use. Publications of the World Health Organization can be obtained from Knowledge Sharing and Production, World Health Organization, Regional Office for the Eastern Mediterranean, PO Box 7608, Nasr City, Cairo 11371, Egypt (tel: +202 2670 2535, fax: +202 2670 2492; email: emrgoksp@who.int). Requests for permission to reproduce, in part or in whole, or to translate publications of WHO Regional Office for the Eastern Mediterranean – whether for sale or for noncommercial distribution – should be addressed to WHO Regional Office for the Eastern Mediterranean, at the above address; email: emrgogap@who.int.
Contents Acknowledgements................................................................................................................. 4 Executive summary.................................................................................................................. 5 1. Introduction.......................................................................................................................... 7 2. Health inequities: concepts and measurement............................................................10 3. Methods...............................................................................................................................12 4. Health inequities: magnitude and trends.......................................................................15 5. Identifying determinants of health inequities...............................................................22 6. Discussion............................................................................................................................24 Annex 1. Technical notes and concepts.............................................................................26 Annex 2. Country reports...................................................................................................28 Annex 3. Statistical annex: inequities in health determinants and outcomes by equity stratifier..................................................................................................................54 References...............................................................................................................................65
Health inequities in the Eastern Mediterranean Region
Acknowledgements This publication was written and revised by Angela Baschieri, University of Southampton, in close collaboration with the WHO Regional Office for the Eastern Mediterranean.
4
Executive summary
Executive summary This report focuses on the available evidence on inequities in health and inequities in socioeconomic determinants that exist both within and across countries in the WHO Eastern Mediterranean Region. It uses data from the Pan-Arab Project for Child Development (PAPCHILD) and Pan-Arab Project Family Health Survey (PAPFAM). The report aims to assess the extent of health inequality in the Region and identify what contributed to the changing levels of inequalities in the 1990s. The study analyses the role of changing socioeconomic and behavioural characteristics of the population and the changes in health system in contributing to widening or narrowing health inequalities. The analysis is limited to six countries in the Region for which we have data on health outcomes in two points in time (early 1990s and early 2000). Three main research questions were asked as follows. 1. What is the extent of health inequities within and across the countries in the Region? A child born in Djibouti is five and a half times more likely not to live until its fifth birthday compared to a child born in the Syrian Arab Republic. Within Yemen, children born to the poorest 20% of households are more than twice as likely to die before their fifth birthday compared to children in the richest 20% of households. Within countries health inequalities are quite strong. For maternal health-related indicators the inequalities have widened over time in all the countries surveyed except Lebanon. The health status of the poorest has generally improved but the gap between the richest and the poorest has widened with the richest gaining the most from the positive economic performance and investment in health over time.
Coverage of diphtheria-pertussis-tetanus vaccination has improved, and the gap between the richest and the poorest has narrowed over time, except in Yemen, where a major gap still exists, with children from richer backgrounds being twice as likely to be vaccinated than children from poorer backgrounds. 2. What are the major factors contributing to health inequities within countries? Three main domains were identified: health system factors, socioeconomic factors and behavioural and biological factors. We analysed in depth the factors that contributed to the inequalities in skilled birth attendance. We were able to perform this analysis of inequalities for Yemen, Syrian Arab Republic, Tunisia and Morocco. We could not run the same analysis for Lebanon or for Djibouti. In Lebanon, this analysis was not done because the analysis of inequalities showed little difference in skilled birth attendance between the rich and the poor. As far as Djibouti is concerned, the PAPFAM data for Djibouti did not contain information on asset ownership, so it was not possible to estimate the wealth index and perform the analysis of decomposition of inequalities. Results of the analysis indicate that inequities in health system factors contribute between 20% and 33% among the countries considered. In the Syrian Arab Republic and Yemen the contribution of health system factors to the overall inequality in skilled birth attendance were above 30%, whereas in Tunisia and Morocco these proportions were much lower. Both in Yemen and the Syrian Arab Republic the contribution of behavioural and biological factors to the overall inequalities is minimal (less than 1%), whereas for Tunisia and Morocco around 10% of the inequalities could be attributed to behavioural and biological factors.
5
Health inequities in the Eastern Mediterranean Region
The main determinants of inequalities for all the countries studied were the contribution of socioeconomic factors, explaining more than 60% of the inequalities in all countries. 3. What are the major policy implications or actions that countries should consider given the results of the analysis? The result of the decomposition analysis highlights the contribution to health inequities
of factors outside the health sector. This indicates that to lower the inequalities in these selected health outcomes and health system factors effective intersectoral action is needed. Results clearly show that improvement in health can only be achieved through investments in the social and economic sector, via an increase in women’s education, reducing poverty and improving well-being across the whole of society with particular focus on the worst off.
6
Introduction
1. Introduction 1.1 Objectives This report uses available data from the PanArab Project for Child Development Survey (PAPCHILD) and Pan-Arab Project Family Health Survey (PAPFAM) to analyse the magnitude of health inequalities in the WHO Eastern Mediterranean Region. The report will provide a quantitative analysis of main health and system indicators and will analyse the factors contributing to the inequities.
is due to health system factors, whereas for the other countries this factor was less important (3:269). For example, the result for Malawi suggests that in order to address inequalities in child malnutrition, multisectoral policies need to be developed to address both socioeconomic disadvantages in families as well as improving the delivery of health services for the poor.
1.2 Country context The countries included in this report represent a wide range of social and economic status. Yemen and Djibouti are classified as having a low human development according to ranking of the Human Development Index (HDI), whereas the Syrian Arab Republic and Morocco are classified as having a medium HDI. Tunisia and Lebanon are classified as having a high HDI (4). Life expectancy at birth ranges from 55 years in Djibouti to 74 years in the Syrian Arab Republic, whereas adult female literacy ranges from 43% in Morocco to above 80% in Lebanon and Morocco. Data on the level of poverty measured in terms of consumption are available only for a few countries (see Table 1) and the data show a huge diversity in poverty levels. Poverty levels range from above 40% in Djibouti and Yemen to around 15% in the Syrian Arab Republic and Morocco (see Table 1). All the countries included in this report experienced a positive per capita income growth between 2000 and 2009 with some fluctuation in positive growth for most of the countries (see Fig. 1). In addition, the six countries included in this report have a substantially high level of income inequalities with a GINI coefficient above 35% for the countries for which data on income distribution are available.
Describing the magnitude of health inequities National averages often mask inequalities at subnational level and across population subgroups (1, 2). This report will analyse the inequalities in a series of health outcomes in six selected countries in the Region. Similar analysis done using data from 30 countries in the Africa region found huge variation within and between countries in the level of under-five mortalities with the poorest in some countries being as much as 10 times more likely to die before their fifth birthday (3:256). Identifying the determinants of health inequities This report also aims to help the formulation of policies to address the inequalities in the Region by analysing the determinants of health inequalities. Decomposition analysis, for instance, demonstrates pathways of health determinants and highlights the factors that need attention in order to reduce the overall inequality. Similar decomposition analysis done in the Africa region show that more than 10% of the inequalities in child stunting in Malawi
7
Health inequities in the Eastern Mediterranean Region
Table 1. Socioeconomic indicators for the countries included in this report HDR rank GDP per capita, PPP (constant 2005 int $) 2242 4295 7511 11868 4081 2106 GINI index Average Life Poverty GDP per expectancy headcount capita at birth ratio at $2 a growth day PPP (% of population) 3.5 4.6 4.9 6.6 5.2 5.2 63.9 74.4 74.5 72.2 71.6 55.7 46.6 16.8 – – 13.9 41.2 Unemployment, (% of labour force) Adult literacy rate (%) of females aged 15 and above 44.7 77.9 70.9 85.9 43.9 –
Yemen Syrian Arab Republic Tunisia Lebanon Morocco Djibouti
133 111 81 – 114 147
37.69 35.78 – – 40.8 39.8
15.0 8.4 14.2 8.9 10.0 59.5
Source: references (4) and (5), most recent data available.
14 12 10 GDP per capita growth (%) 8 6 4 2 0 -2 -4 -6 2001 2002 2003 2004 2005 2006 2007 2008 2009 Djibouti Lebanon Morocco Syrian Arab Republic Tunisia Yemen
Fig. 1. Trends in GDP per capita growth rates (%), 2001–2009 Source: reference (5).
1.3 Health situation in countries Health outcomes range widely, with Yemen and Djibouti having the worst health indicators. Under-five mortality rate ranges from 120 per 1000 live births for Djibouti to 17 per 1000 live births in the Syrian Arab Republic. Stunting prevalence (height for age) among children under five years of age are among the highest in the world in Yemen. According to the PAPFAM data, 48% of children under five years have a lower height for their age,
showing a chronic state of undernutrition. For the other countries included in the report the level of stunting is still relatively high in the Syrian Arab Republic and Djibouti with a quarter of the population in each country showing low growth. In terms of system coverage indicators Morocco, Syrian Arab Republic, Lebanon and Tunisia are performing much better than Yemen and Djibouti. The coverage of DPT3 vaccination is almost universal in Morocco and Lebanon and around 70% in Djibouti. Almost
8
Introduction
all children born in the five years prior to the survey date were assisted by a skilled birth attendant in Lebanon whereas only one third of births were assisted by a health professional in Yemen. Only 7% of births were delivered in health facilities in Djibouti, and over three quarters of births were delivered in health facilities in Lebanon. The use of modern methods of contraception is very low in some countries, with 6% and 16% of women aged 15-49 using a modern method in Djibouti and Yemen, respectively. In other countries, the percentage of women using a modern method of contraception is much higher with more than half of women using a modern method in Morocco and Tunisia.
The data on health expenditure reveal a huge variation in the importance that those countries attribute to health. Djibouti and Yemen have one of the worst health indicators in the Region; however the government of Djibouti is responding with more government investment in the health sector than Yemen. Djibouti dedicates more than 10% of the national budget to health, whereas in Yemen the government spends only 6% of the national budget on health (see Fig. 2).
Table 2. Selected health outcomes, health systems and health determinant indicators for surveyed countries Yemen 1991–2 2003 73 97 48
Syrian Arab Republic 1993 34 42 25 2001 17 19 25
Tunisia 1994–5 35 44 22 2001 23 29 –
Lebanon 1996 27 31 12 2001 18 19 13
Morocco 1992 44 52 21
Djibouti 2001 40 47 18
2004 96 120 21
Health outcomes IMR per 1000 live births U5MR per 1000 live births Stunting in children under 5 years (%) Health systems Coverage of DPT3 vaccinations (%) Coverage of skilled birth attendance (%) Number of antenatal care visits Place of delivery Current use of modern method of contraception (%) 21 14 73 35 24 50 80 89 22 46 – 91 8 45 88 98 – 16 99 65 68 75 81 116 43
7 10 8
13 20 16
21 11 34
42 55 39
20 45 55
63 90 57
34 43 42
79 97 36
7 15 56
30 64 60
7
6
Note: IMR = infant mortality rate; U5MR = under-five mortality rate. Source: based on calculation of PAPFAM and PAPCHILD surveys; – = data not available.
9
Health inequities in the Eastern Mediterranean Region
14 Government health expenditure as % of total government expenditure 12 10 8 6 4 2 0 1999 2000 2001 2002 2003 Djibouti Lebanon Morocco Syrian Arab Republic Tunisia Yemen
Fig. 2. Trends in government expenditure on health as a percentage of total government expenditure, 1999– 2003 Source: (2).
2. Health inequities: concepts and measurement 2.1 Health inequities, inequalities and social justice There are dramatic differences in health attainment across population groups within countries. These differences occur because of several social stratification factors, including socioeconomic, political and cultural factors. Such inequalities are seen in both rich and poor countries. In general, evidence shows that the lower an individual’s socioeconomic position the worse their health. There is a social gradient in health that runs from top to bottom of the socioeconomic spectrum. Health inequities are unjust, unfair and avoidable in health achievement. Not all inequalities can, therefore, be considered to be inequitable. This can be illustrated by the difference between men’s and women’s health. Women, in general, live longer than men. 10
This could be a consequence of biological sex differences in which case this inequality may not be classified as an inequity. On the other hand, if somewhere women’s life expectancy is lower than men’s it is likely that adverse social conditions act to reduce the natural longevity advantage of women. Such a scenario would be considered an inequity. To make a fundamental improvement in health equity, technical and medical solutions such as disease control and medical care are critical and necessary though not sufficient. Given that inequities in health arise due to differential distributions of economic and social resources in society, addressing the social and economic determinants of health will yield greater and sustainable returns to existing efforts to improve health.
2.2 Measurement of health inequities For several decades, studies have consistently shown inequalities in health among socioeconomic groups and by sex, race or ethnicity, geographical area and other categories. Because health inequalities
Health inequities: concepts and measurement
generally reflect imbalances in power and wealth in society, addressing them requires strategic action. Better information alone is not sufficient to resolve the problems; political will and continuous action in the monitoring of inequities, as well as country-level capacity to use this information for effective planning, are also required for progress towards health equity and movement towards social justice in health to take place. In order to measure the magnitude of health inequalities we need data on both measures of health and measures of social positioning that define strata in a social hierarchy.
groups. In this report ratios of the average in the two extreme quintiles (poorest versus richest) are used to assess the degree of inequalities in selected health indicators. The poorest to the richest ratio is used for infant mortality rate, under-five mortality rate and stunting in children under five years of age. The richest to the poorest ratio is used for all the other health systems indicators.
Health measures This report will consider the following health indicators: • infant mortality rate; under-five mortality rate • percentage of stunting among children under five years • coverage of DPT3 vaccination • coverage of skilled birth attendance • percentage of women who had four or more antenatal visits • percentage using a modern method of contraception.
Concentration index In addition to the simple measure of inequalities, the more complex measure of concentration index is adopted. The concentration index is a summary measure of the distribution of health across the spectrum of socioeconomic stratifiers, such as wealth, where there is a social hierarchy. It allows quantifying the degree of income-related inequality in a specific health indicator. The concentration curve plots the cumulative percentage of the health indicator against the cumulative percentage of the sample, ranked by their socioeconomic status, beginning with the most disadvantaged and ending with the least disadvantaged (see Annex 1: technical notes and concepts).
Equity stratifiers We will consider the following equity stratifiers: • household wealth quintile. • mother’s education • place of residence (urban/rural)
Measures of inequity/inequality The report will use two main measures of inequities: the range and the concentration index. Range Simple range measures, including ratio and difference, are the most frequently used in the literature to describe inequalities between 11
Health inequities in the Eastern Mediterranean Region
3. Methods 3.1 Conceptual framework The conceptual framework is largely a synthesis of models used by the Commission on Social Determinants of Health (7). This conceptual model illustrates the pathways by which social determinants of health affect health outcomes, makes explicit the linkages among different types of health determinant and makes visible the ways social determinants contribute to health inequities among groups in society, given the increasing evidence of significant social stratification in health status. This conceptual framework served as the departure point on how to “operationalize” or make concrete monitoring and assessment, with the initial purpose of describing levels and potential links across components within national settings. The four key components of the model are summarized here. Geographical, socioeconomic context. What are the main characteristics of a country
that influence the form and magnitude of social stratification as well as the implications of stratification for the circumstances in which people live and work? Social stratification or socioeconomic position. What are the key dimensions of social stratification? How extensive is the social stratification? Differential exposures, vulnerabilities, and consequences. What is the extent of differential vulnerabilities, differential exposures and differential consequences? These include behavioural and biological factors, and health system factors. Differential outcomes in health. What are the main resulting health inequities that emerge in a given society and what is the extent of these health inequities? This framework guided the approach to the analysis and interpretation of the results, and is based on the one adopted by the Commission on Social Determinants of Health noted in Fig. 3.
Socioeconomic & political context Social position Governance Education Policy (Macroeconomic, Social, Health) Occupation Income Gender Cultural and societal norms and values Ethnicity / Race Health care system
Material circumstances Social cohesion Psychosocial factors Behaviours Biological factors
Distribution of health and well-being
SOCIAL DETERMINANTS OF HEALTH AND HEALTH INEQUITIES
Fig. 3. Framework adopted by the Commission on Social Determinants of Health, August 2008, page 43 Source: adapted from reference (7).
12
Methods
3.2 Data We analysed data from 11 surveys in six countries: five surveys from the PAPCHILD and six surveys from the PAPFAM. The data from the PAPCHILD survey refer to the beginning of the 1990s, whereas the data from the PAPFAM survey refer to the beginning of 2000 (see Table 3).
Some information was not available in some surveys (see Table 4); for example, it was not possible to calculate the prevalence of stunting and the coverage of DPT vaccination in Tunisia from the data at the beginning of the 1990s. Equally, it was not possible to calculate the coverage of DPT vaccination from data for the beginning of 2000 for Morocco, as this information was not available in the PAPFAM Moroccan questionnaire.
Table 3. Countries for which we have PAPCHILD or PAPFAM data PAPCHILD Yemen Syrian Arab Republic Tunisia Lebanon Morocco Djibouti 1991–92 1993 1994–95 1996 1992 PAPFAM 2003 2001 2001 2004 2003 2002-2004
Table 4. List of indicators and stratifiers available by survey type Yemen PAPCHILD PAPFAM
Syrian Arab Republic PAPCHILD PAPFAM
Tunisia PAPCHILD PAPFAM
Lebanon PAPCHILD PAPFAM
Morocco PAPCHILD PAPFAM
Djibouti PAPFAM
Health indicator IMR/U5MR Anthropometric Health system Coverage of DPT3 Delivery in a health facility Contraceptive use Skilled birth attendance Number of antenatal care visits Social stratifiers Urban/rural Household assets Mother’s education x x x x x x x x x x x
13
Health inequities in the Eastern Mediterranean Region
3.3 Indicators Table 5 shows the eight indicators used in the health equity analysis. Table 5. Definitions of indicators analysed in the study No. Indicator 1 2 3 4 5 6 7 Infant mortality Under-five mortality Stunting in children Coverage of DPT3 vaccination Coverage of skilled birth attendance Coverage of antenatal care (4+ visits) Current use of modern contraception Definition Probability of dying before first birthday (1q0) Probability of dying between birth and fifth birthday (5q0) Percentage of children with chronic malnutrition Percentage of children aged 12–23 months receiving three doses of diphtheria-pertussis-tetanus vaccine Percentage of births attended by skilled health personnel Percentage of women who had a birth in the previous five years who attended at least four antenatal care visits Percentage of women currently using modern contraception
3.4 Analytical approach Descriptive The rates and proportions of all indicators are reported for each country at national level and by the following equity stratifiers wherever possible: • household wealth quintiles • education (categorized according to country classifications) • area of residence (urban/rural areas)
The contributions of determinants to socioeconomic inequality in “skilled birth attendance” in Yemen, Syrian Arab Republic, Tunisia and Morocco were calculated using the most recent survey data (PAPFAM).
Interpretation approach Patterns of inequality The extent and the depth of inequality vary from region to region within countries, but also between countries. At one extreme are the poorest countries where large parts of the population are deprived of care, even among the better off: only a small minority enjoys reasonable access to a reasonable range of health benefits, creating a pattern of mass deprivation. Looking at health care coverage by wealth group provides a crude illustration of these different patterns. Between the extremes of mass deprivation (typical for countries with major constraints in supply of services and lowdensity health care networks) and marginal exclusion (typical for high- and middle-income countries with dense health care networks) are countries where poor populations have to queue behind the better off, waiting to
Time trends The descriptive analysis was performed for the two surveys where data were available for two time points. Decomposition of socioeconomic inequality For policy purposes it is especially relevant to understand why unfair and avoidable inequalities (inequities) exist and what actions may be taken to improve equity. Decomposition analysis is one approach used to quantify the contribution made by different factors to inequities in health.
14
Health inequities: magnitude and trends
get access to health services and hoping that benefits will eventually trickle down. The distribution of health outcomes and health opportunities across socioeconomic groups can provide a useful tool for health policy-makers as it can easily be used to classify countries according to the above-mentioned patterns.
4.1 Inequities in health outcomes within and across countries Infant mortality Reducing Infant mortality is a key Millennium Development Goal (MDG). Infant mortality rate (IMR) is defined as the probability of dying between birth and one year of age and it is expressed as the number of infant deaths per 1000 live births. In Yemen and Djibouti the infant mortality rates exceed 80 infant deaths per 1000 live births, whereas in Morocco the rate is around 40 deaths per 1000 live births. In the Syrian Arab Republic, Tunisia and Lebanon the infant mortality rates range around 20 deaths per 1000 live births (see Fig. 4). The difference in infant mortality rates between the poorest and the richest is largest in Yemen, Morocco and Tunisia (see Fig. 5). The level of infant mortality rate has increased in Yemen between the beginning of the 1990s and the latest data from 2003, whereas it has reduced in all the other countries. The gap in infant mortality rate between the rich and the poor has considerably narrowed in Lebanon and remains the same in all the other countries included in this analysis.
4. Health inequities: magnitude and trends Results in this section show that there is a substantial health-related inequity among the countries selected for this report. We analysed three health outcome indicators: infant mortality rate, under-five mortality rate and prevalence of stunting among children under five years of age. The health system indicators studied were coverage of DPT3 vaccination, coverage of skilled birth attendance, antenatal care visits and current use of modern methods of contraception, difference in health outcomes and health system indicators stratified by urban/rural, mother’s educational attainment, wealth and child’s sex where possible. We used two rounds of data from the PAPCHILD and PAPFAM surveys. 120 100 80 60 40 20 0 17 23 81
Infant mortality rate per 1000 live births
94
40 18
Yemen Syrian Arab Republic Tunisia Lebanon Morocco Djibouti 2003 2001 2001 2001 2001 2004
Fig. 4. Infant mortality rate in the countries surveyed (PAPFAM published results) 15
Health inequities in the Eastern Mediterranean Region
Average 120 Infant mortality rate per 1000 live births 100 80 60 40 20 0
Poorest
Richest
Yemen Yemen Syrian Syrian Tunisia Tunisia Lebanon Lebanon Morocco Morocco 1991–92 2003 Arab Arab 1994–95 2001 1996 2001 1992 2001 Republic Republic 1993 2001
Fig. 5. Inequities in infant mortality rates between the poorest and the richest by country and survey year
No assessment of inequities in infant mortality by income level could be made for Djibouti due to unavailability of appropriate data. The gap in infant mortality rate by mother’s education fell significantly in Yemen and the Syrian Arab Republic but increased in Lebanon and Morocco (see Fig. A3.1 in Annex 3). The gap in IMR by place of residence has narrowed in all the countries except Morocco (see Fig. A3.2).
for Lebanon and Morocco, where the gap in under-five mortality rate for children of mothers with higher education and children of mothers with lower education has increased over time (see Fig. A3.3). The gap in underfive mortality rate by place of residence has remained the same in all countries except for Tunisia, where the gap in under-five mortality rate for urban and rural areas has reduced over time (see Fig. A3.4).
The level of under-five mortality is high in Djibouti and Yemen with 120 and 97 deaths per 1000 births, respectively (see Fig. 6). Morocco’s under-five mortality rate is around 46 deaths per 1000 births, whereas in Tunisia it is around 29 deaths and in the Syrian Arab Republic and Lebanon just under 20 deaths per 1000 births. The gap in under-five mortality rate between the rich and the poor has narrowed in Lebanon and Morocco but has remained the same or has increased slightly in all the other countries (see Fig. 7). The gap in the under-five mortality rate has decreased in all the countries except
Under-five mortality rate per 1000 live births
Under-five mortality
140 120 100 80 60 40 20 0 Yemen Syrian Tunisia Lebanon Morocco Djibouti 2003 Arab 2001 2001 2001 2004 Republic 2001 19 29 46 19 97 120
Fig. 6. Under-five mortality rate in the countries surveyed (PAPFAM published results)
16
Health inequities: magnitude and trends
Average 140 Under-five mortality rate per 1000 live births 120 100 80 60 40 20 0
Poorest
Richest
Yemen Yemen Syrian Syrian Tunisia Tunisia Lebanon Lebanon Morocco Morocco 1991–92 2003 Arab Arab 1994–95 2001 1996 2001 1992 2001 Republic Republic 1993 2001
Fig. 7. Inequities in under-five mortality rates between the poorest and the richest by country and survey year
Prevalence of stunting in children under five Stunting in children, defined by low height for age, is a marker of chronic undernutrition, and its reduction is a key MDG objective. Yemen has a high level of children stunting with almost half of the children with a low height for their age (see Fig. 8). 60 50 40 % Stunting 30 20 10 0 Yemen Syrian Lebanon Morocco Djibouti 2003 Arab 2001 2001 2004 Republic 2001
Fig. 8. Prevalence of stunting in the countries surveyed (PAPFAM published results)
The level of stunting slightly increased in Yemen and remained at the same level in the other countries for the two time periods. The gap in the level of stunting between the rich and the poor increased in Yemen and the Syrian Arab Republic and decreased in Tunisia, Lebanon and Morocco (see Fig. 9). It was not possible to analyse the gap in stunting by mother’s education in the latest PAPFAM data because it was not possible to link the mothers’ ID for each child resident in the household for which we had anthropometric information. In the PAPCHILD data the information was collected differently and it was possible to link these two pieces of information. At the time of the PAPCHILD survey in the early 1990s, Yemen had the highest gap in stunting by mother’s education, with almost 35 percentage points difference in the level of stunting for children of mothers with no education compared with children of mothers with higher education (see Fig. A3.5). The gap in percentage of children stunting by place of residence did not change much between the two survey rounds, except for a slight increase in gap in Yemen (see Fig. A3.6). 17
Health inequities in the Eastern Mediterranean Region
Average 60 Prevalence of stunting % 50 40 30 20 10 0
Poorest
Richest
Yemen Yemen Syrian Syrian Tunisia Lebanon Lebanon Morocco Morocco 1991–92 2003 Arab Arab 1994–95 1996 2001 1992 2001 Republic Republic 1993 2001
Fig. 9. Prevalence of stunting between the poorest and the richest by country and survey year
4.2 Inequities in health systems variables within and across countries Coverage of DPT3 vaccination The World Health Organization recommends that all children receive three doses of the DPT (diphtheria, pertussis and tetanus) vaccine to obtain immunity against these diseases. Coverage of DPT vaccination is almost universal in Morocco and varies greatly in the other countries. It is around 70% in Yemen and Djibouti (see Fig. 10). Yemen has the largest gap between the receipt of all three DPT doses among children in the poorest quintile (44%) and children in the richest quintile (91%). In the Syrian Arab Republic, Tunisia, Morocco and Lebanon, however, the gap between the rich and the poor is small (see Fig. 11). Differences in DPT vaccination by mother’s education are higher in the Syrian Arab Republic and Yemen. In these two countries, children of mothers with higher
education have 1.4 times higher probability of having been vaccinated than children born to a mother with no education (see Fig. A3.7). As far as the difference in DPT3 vaccination by place of residence is concerned, the biggest gap is found in Yemen and Djibouti where children living in urban areas were 1.4 times more likely to have been vaccinated than children living in rural areas (see Fig. A3.8 ).
100 80 % DPT 3 60 40 20 0 Yemen Syrian Tunisia Lebanon Morocco Djibouti 2003 Arab 1994-95 2001 2001 2004 Republic 2001
Fig. 10. Percentage of DPT3 vaccination coverage in the countries surveyed (PAPFAM published results)
18
Health inequities: magnitude and trends
Average 100
Poorest
Richest
80
% DPT 3
60
40
20
0
Yemen Yemen Syrian Syrian Tunisia Lebanon Lebanon Morocco 1991–92 2003 Arab Arab 1994–95 1996 2001 2001 Republic Republic 1993 2001
Fig. 11. Inequities in DPT3 vaccination coverage between the poorest and the richest by country and survey year % attended by a skilled birth attendant
Coverage of skilled birth attendance Having a skilled birth attendant present during the birth of a child improves the likelihood of a safe delivery. A skilled birth attendant is a medical doctor, midwife or nurse who has been given appropriate training to care for mothers giving birth. The global experience and scientific evidence is very clear that skilled birth attendance and access to emergency obstetric care from adequately equipped hospitals are essential and critical to substantially reducing maternal mortality, which is one of the key health-related MDGs. The percentage of births attended by a skilled birth attendant vary greatly for the countries analysed in this report; Yemen has the lowest percentage of deliveries attended by a professional with only 35% of births being assisted, whereas in Morocco 65% of all births were attended by a professional. In Lebanon almost all births were attended by a skilled birth attendant at delivery (see Fig. 12).
100 80 60 40 20 0 Yemen Syria Tunisia Lebanon Morocco Djibouti 2003 Arab 2001 2001 2001 2004 Republic 2001
Fig. 12. Percentage of births attended by a skilled birth attendant in the countries surveyed (PAPFAM published results)
The percentage of births attended by a skilled birth attendant increased in all countries between the two surveys. On the other hand, the gap between the rich and the poor has widened in all the countries. The widest gap was reported in Morocco with a 60% point difference between the rich and the poor. 19
Health inequities in the Eastern Mediterranean Region
Average % attended by skilled birth attendant 100 80 60 40 20 0
Poorest
Richest
Yemen Yemen Syrian Syrian Tunisia Tunisia Lebanon Lebanon Morocco Morocco 1991–92 2003 Arab Arab 1994–95 2001 1996 2001 1992 2001 Republic Republic 1993 2001 Fig. 13. Inequities in percentage of women delivering in a health facility between the poorest and the richest by country and survey year
The gap in births attended by a skilled attendant narrowed in all the countries and was reduced to zero in Lebanon (see Figs. 13 and A3.9). The gap in percentage of births attended by skilled personnel between the rich and the poor decreased in all countries, however, it is still relatively wide in Yemen and Morocco (Fig. A3.9). The gap by place of residence was very high in Djibouti with 93% of births attended by a skilled birth attendant in urban areas and only 23% in rural areas (see Fig. A3.10).
malaria and distribution of insecticide-treated mosquito nets; prevention of mother-tochild transmission of HIV; micronutrient supplementation; and birth preparedness, including information about danger signs during pregnancy and childbirth. The antenatal period is also an ideal opportunity to supply information on birth spacing, which is recognized as an important factor in improving infant survival. 100
% ANC 4+
Four or more antenatal care visits The antenatal period presents important opportunities for reaching pregnant women with a number of interventions that may be vital to their health and well-being and those of their infants. Regular contact with a doctor, nurse or midwife allows health personnel to manage the pregnancy and provide a variety of services, such as treatment of hypertension to prevent eclampsia; tetanus immunization; intermittent preventive treatment for 20
80 60 40 20 0 Yemen Syrian Tunisia Lebanon Morocco Djibouti 2003 Arab 2001 2001 2001 2004 Republic 2001
Fig. 14. Percentage of women having four or more antenatal care visits in the countries surveyed (PAPFAM published results)
Health inequities: magnitude and trends
Average 100 80 % ANC 4+ 60 40 20 0 Yemen Yemen Syrian
Poorest
Richest
Syrian Tunisia
Tunisia Lebanon Lebanon Morocco Morocco
1991–92 2003 Arab Arab 1994–95 2001 1996 2001 1992 2001 Republic Republic 1993 2001 Fig. 15: Inequities in percentage of women having four or more antenatal care visits between the poorest and the richest by country and survey year
% Use of modern methods of contraception
WHO recommends a minimum of four antenatal visits. In all countries included in this report, the percentage of women who had four or more antenatal care visits increased between the two surveys (see Fig. 14). The analysis of wealth inequalities also revealed that the gap between the rich and the poor increased (see Fig. 15). The gap in the percentage of women who attended four or more antenatal care visits by women’s education increased in all countries except for Yemen that recorded a reduction in the gap between the rich and the poor (see Fig. A3.11). The gap between the rich and the poor by place of residence increased significantly in Tunisia and Morocco and remained unchanged in the other countries (see Fig. A3.12).
The gap between the rich and the poor decreased in all the countries except Yemen, where the gap increased over time (see Fig. 17). The gap in use of contraception by women’s education reduced in all countries and is minimal in Tunisia and Lebanon (see Fig. A3.13). Similarly the gap in use of contraception between urban and rural areas is modest in all countries, with exception of Yemen, where the gap is greatest, on the order of 20 percentage points (see Fig. A3.14). 100 80 60 40 20 0 Yemen Syrian Tunisia Lebanon Morocco Djibouti 2003 Arab 2001 2001 2001 2004 Republic 2001
Use of modern contraception The use of modern methods of contraception is extremely low in the countries surveyed. In Djibouti and Yemen less than 20% of women currently use modern methods of contraception. Only in Tunisia and Morocco did the percentage of users increase to just over 50% (see Fig. 16).
Fig. 16. Percentage of women using a modern method of contraception in the countries surveyed (PAPFAM published results)
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Health inequities in the Eastern Mediterranean Region
Average 70 60 % Contraceptive use 50 40 30 20 10 0
Poorest
Richest
Yemen Yemen Syrian Syrian Tunisia Tunisia Lebanon Lebanon Morocco Morocco 1991–92 2003 Arab Arab 1994–95 2001 1996 2001 1992 2001 Republic Republic 1993 2001
Fig. 17. Inequities in use of modern contraception by wealth quintile by country
5. Identifying determinants of health inequities 5.1 Four broad domains In this section we are interested in identifying factors that contribute to the observed inequities in maternal and child health in the countries selected for this report. We will focus on analysing the determinants of inequality of births attended by a skilled birth attendant.
The framework described in section 2.1 was used to identify the pathways and determinants to inequities in these variables in the countries surveyed in this report. We considered four broad domains encapsulating the pathways to health inequities that were identified in the framework: • • • • socioeconomic, political context socioeconomic position intermediary determinants health system factors.
Table 6 highlights the major determinants that comprise the framework’s broad categories. Health systems factors Antenatal care (number of visits, quality of care, place of care) Barriers to accessing care
Table 6. Major determinants identified under broad categories of the framework Socioeconomic, political Socioeconomic context position Major factors Area of residence (urban/rural) Region (district, zone) Wealth Education (mother’s and partner’s) Intermediary determinants Water and sanitation Exposure to media
Mother’s biological characteristics (age, birth Occupation (mother’s interval, parity, height, body–mass index) and partner’s) Child’s biological characteristics (age, sex, birth Other social weight, morbidity) characteristics (sex of household Child care practices (method of stool disposal, length of time breastfed, types of food fed to head, relationship of mother to household child, vaccinations received by child) head) Competition for resources (mother currently pregnant, child is twin/triplet, number of children under five in household)
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Identifying determinants of health inequities
The analytical approach described in section 2 was used to conduct a decomposition analysis of determinants of inequalities.
100 80 60
5.2 Main contributors to inequities in skilled birth attendance We decomposed inequalities in access to skilled birth attendance at delivery in Yemen, Syrian Arab Republic, Tunisia and Morocco. We did not run the decomposition of inequalities in Djibouti as we did not have information on the wealth quintile and for Lebanon where the gap between the rich and the poor at the time of the latest survey was reduced to zero. Fig. 18 shows that socioeconomic factors together contribute to 60% to 75% in inequities in skilled birth attendance at delivery. Socioeconomic position ranges from just above 66% in the Syrian Arab Republic to above 75% in Tunisia. Health system factors account for a substantial proportion of inequalities in Yemen and the Syrian Arab Republic, where more than one third of the inequalities of attendance of a skilled birth attendant at delivery is due to health system factors. The percentage is much smaller in Tunisia and Morocco where only less than 20% of the inequalities are due to health system factors. This suggests that improving health service delivery will strongly reduce inequalities in countries such
40 20 0 Yemen Syrian Tunisia Morocco Arab Republic Health system Behavioural and biological factors Socioeconomic factors
Fig. 18. Contribution of broad factors in skilled birth attendance
as Yemen and the Syrian Arab Republic and to a lesser extent in Tunisia and Morocco. Table 7 shows the contribution of each specific factor to inequities in skilled birth attendance. Household wealth was a strong determinant in the Syrian Arab Republic and in Tunisia, where more than half of the inequity in access could be explained by a difference in wealth quintile. Other important factors are place of residence in Yemen and Morocco, where around a sixth of the inequalities can be attributed to it (18% in Yemen and 17% in Morocco). Interestingly the place of the most recent antenatal check-up and whether or not the mother had had four or more antenatal care visits explains more than 20% of inequalities in Yemen and the Syrian Arab Republic.
Table 7. Percentage contribution to inequities in skilled birth attendance of six of the most common determinants (that contribute positively to inequities) across four countries Yemen Urban (residence) Household’s wealth Women’s education Other socioeconomic characteristics Exposure to media Behavioural and biological factors Had four or more ANC visits Place of most recent ANC check-up Quality of care Distance to health facility Other socioeconomic characteristics 18 30 5 1 12 1 11 11 8 3 1 100 Syrian Arab Republic 1 51 6 – 4 1 6 21 10 – – 100 Tunisia 10 61 5 – + 8 4 2 8 2 – 100 Morocco 17 33 18 – 4 9 5 9 2 5 – 100
Note: – = factors that did not contribute to inequities; + = variable not available in survey data.
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Health inequities in the Eastern Mediterranean Region
6. Discussion 6.1 Overall magnitude and trends in health inequities Inequities in health outcomes and health services are substantial in the selected countries for this report. A child born in Djibouti is five and a half times more likely not to live until its fifth birthday compared to a child born in the Syrian Arab Republic. Within Yemen, children born to the poorest 20% households are more than twice as likely to die before their fifth birthday compared to children in the richest 20% of households. Within the countries health inequalities are quite strong. For maternal health-related indicators the inequalities have widened over time in all countries except in Lebanon. The health status of the poorest has generally improved but the gap between the richest and the poorest has widened with the richest gaining the most from the positive economic performance and investment in health over time. Coverage of DPT vaccination has improved, and the gap between the richest and the poorest has narrowed over time, except in Yemen where a major gap still exists, with children from richer backgrounds being twice more likely to be vaccinated than children from poorer backgrounds.
were identified: health system factors, socioeconomic factors, and behavioural and biological factors. Results of the analysis indicate that inequities in health system factors contribute between 20% and 33% among the countries considered. In the Syrian Arab Republic and Yemen the contribution of health system factors to the overall inequality in skilled birth attendance were above 30%, whereas in Tunisia and Morocco these proportions were much lower. Both in Yemen and the Syrian Arab Republic the contribution of behavioural and biological factors to the overall inequalities is minimal (less than 1%), whereas for Tunisia and Morocco around 10% of the inequalities could be attributed to behavioural and biological factors. The main determinants of inequalities were, for all the countries studied, the contribution of socioeconomic factors, explaining more than 60% of the inequalities in all countries.
6.3 Limitations of the analysis Some key limitations of the analysis. a) The analysis is based on cross-sectional data, and time series data are not linked to individuals but to population subgroups. b) The decomposition analysis is limited on the available information collected in the survey such as household welfare status, level of education, parity, maternal age at birth, whether or not the mother had four or more antenatal care visits, etc.
6.2 Key discussion points from the skilled birth attendance analysis Levels of skilled birth attendance were still low for some countries in the Region (i.e. Yemen, Morocco and Djibouti; 35%, 65%, 75%). Improvements in the previous 10 years benefited richer households more than poorer ones. We analysed in depth the factors that contributed to the inequalities in skilled birth attendance. Three main domains
6.4 The role of the health sector The result of the decomposition analysis highlights the contribution to health inequities of factors outside the health sector. This indicates that to lower the inequalities in health
24
Discussion
outcomes and health system factors effective intersectoral action is needed. Results clearly show that improvements in health can only be achieved through investments in the social
and economic sectors, either via an increase in women’s education or reducing poverty and raising welfare throughout all sections of society with particular focus on the worst off.
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Health inequities in the Eastern Mediterranean Region
Annex 1.Technical notes and concepts Household wealth index
where fi is the “scoring factor” for the ith asset as determined by the procedure, aji is the jth household’s value for the ith asset and ai and si are the mean and standard deviation of the ith asset variable over all households.
Very few demographic surveys in developing The crucial assumption and it is just an countries gather information on household assumption is that household long-run wealth income or consumption expenditure, despite is what causes the most common variation in the theoretical importance of these measures. asset variables (8). The scoring factor is the Furthermore income and consumption data “weight” assigned to each variable (normalized are both expensive and difficult to collect, by its mean and standard deviation) in the linear and many otherwise useful data sources lack combination of the variables that constitute the directAnnex measures of living standards (notably 1. Technical notes and concepts first principal component. the demographic and health surveys). On Household index the face of it, this wealth precludes the analysis of Decomposition analysis socioeconomic inequalities in health, Very few demographic surveysas inwell developing countries gather information on household The method proposed by Wagstaff, Van as testing of hypotheses relating to the impact income or consumption expenditure, despite the theoretical importance these measures. Doorslaer and Watanabe (9) of was used to of living standards on health and fertility. socioeconomic inequality in and Furthermore income of andliving consumption are both expensive and difficult to collect, Moreover, the exclusion standard datadecompose Decomposition analysis infant mortality into its determinants. The measures inotherwise multivariate analysis raises the many useful data sources lack Decomposition direct measures of living standards to (notably the analysis concentration index is the by preferred The method proposed Wagstaff, other Van Doorslaer an possibility that other coefficients are rendered The method proposed by Wagstaff, Van Doorslaer demographic and health surveys). On the face of it, this precludes the analysis measures inequalities in that it reflects the of and W biased, because of their correlation with living socioeconomic inequality in infant mortality into its experiences ofhypotheses the entire in population andimpact that standards measures. Consequently researchers socioeconomic inequality infant to mortality intoof its determ socioeconomic inequalities in health, as well as testing of relating the the preferred to other measures of inequalities in th it be sensitive to changes in the distribution have been forced to rely on ad hoc use of the preferred to other measures of inequalities in that tha living standards on health and fertility. Moreover, the exclusion of living standards measures of the population across socioeconomic group to change proxies for measures of living standards (8). entire population and that it be sensitive (10, 11) . other coefficients entire population and that it are be rendered sensitive to changes in in multivariate analysis allows raises deriving the possibility that biased, Principal component analysis across socioeconomic group (10, 11). an asset quintile measure that is with correlated across socioeconomic group (10, 11 ).index to have because of their correlation living standards measures.the Consequently researchers We decompose concentration with household long-run wealth. We decompose the concentration index to estim estimate how determinants proportionally been forced to rely on ad hoc use of proxies for measures of living standards (index 8). Principal We decompose the concentration to estimate contribute to inequality (for example, the gap contribute to inequality (for example, the gap betw component analysis allows deriving an contribute asset quintile measure that is correlated with between poor and rich)(for in aexample, health variable. Principal components analysis to inequality the gap between p They showed that for any linear regression model lin They showed that for any linear regression household long-run wealth. Principal components analysis is a technique They showed that for any linear regression model linking model the health variable of set linking of K health determinants, xk: interest y for extracting from a large number of variables set of K health determinants, x : k to a set of K health determinants, xk: those Principal few orthogonal linear combinations components analysisof the variables that best capture the common