The international context

2The health gains observed over the past 25 years have been driven by unprecedented global mobilization to improve health for all. This includes the action of national governments, programmes supported by United Nations agencies and by the many donors active in the health sector, which encompass non-governmental organizations (NGOs), several large private foundations, such as the Gates Foundation, partnerships like the Global Alliance for Vaccines and Immunization (GAVI), the Global Fund to Fight AIDS, Tuberculosis and Malaria, and donor countries that provide funding for development assistance for health (Germany, United Kingdom, United States, etc.) (IHME, 2016).

3The health of populations has improved in response to social progress over the past 25 years, even if gains in both areas are insufficient and vary greatly between regions. Globally, the number of people living in extreme poverty has been more than halved since 1990 (World Bank, 2016); education has improved in all countries and illiteracy has fallen (UNESCO, 2014); and many health indicators have improved (immunization coverage, safe delivery, etc.). The demography of low-and middle-income countries is changing. Fertility has fallen almost everywhere, albeit at varying speeds: in middle-income countries, it decreased from an average of 3.4 children per woman in 1990 to 2.4 in 2015, and in low-income countries from 6.4 to 4.7. Population growth slowed slightly, falling in middle-income countries from an average of 1.9% per year in 1990 to 1.1% in 2015, while in low-income countries the decrease was much smaller, from 2.7% to 2.6% (United Nations, 2015).

4Those overall results, while positive, conceal large differences in trends, histories and timing between and within countries. Inequality is more than ever a top priority for programmes of action, international institutions and academic research.

5Inequality is by no means a new issue, however. In 1979, the World Health Organization (WHO) adopted “Health for All by the Year 2000”, a global strategy that included ambitious goals for reducing child and maternal mortality by the end of the twentieth century. It came shortly after the Declaration of Alma-Ata in 1978 on primary health care, which was seen as key to reducing health inequalities. In 1994, the Programme of Action adopted at the International Conference on Population and Development (ICPD) in Cairo devoted one of 13 chapters to health and mortality, with the explicit aim of reducing inequalities in death by 2015. The results have been mixed, since not all targets were achieved by 2015. [2]

6The year 2015 was also decisive for the Millennium Development Goals (MDGs), a global partnership and development-funding programme of unprecedented scope, to which the UN member states committed in 2000. Of the eight goals to be reached by 2015, three were directly related to health: reducing child mortality (Goal 4), improving maternal health (Goal 5), and combating HIV/AIDS, malaria and other diseases (Goal 6). [3] Major progress has been achieved, but it varies by goal and region (WHO, 2015a; Stuckler et al., 2010). For example, Goal 6 has been reached because the incidence of HIV infection, tuberculosis and malaria has fallen since 2000. However, the targets on under-five mortality (reduce by two-thirds between 1990 and 2015), and maternal mortality (reduce by three-quarters) were probably over-ambitious, sub-Saharan Africa, South-East Asia, the Caucasus and Central Asia fall far short of those goals. Although the MDG programme succeeded in mobilizing the international community, it has been criticized for using aggregate targets and indicators and neglecting internal inequalities within countries.

7The issue of inequality in health has returned to the forefront since the work of the Commission on Social Determinants of Health (2005-2008) and, more recently, the 2030 Agenda for Sustainable Development adopted by the United Nations in September 2015. The 2030 Agenda comprises 17 Sustainable Development Goals (SDGs). The health goal (Goal 3) seeks “to ensure healthy lives and promote well-being for all at all ages” and is associated with 13 targets, nine of which are quantified. These include maternal mortality, under-five mortality (with a new interest in neonatal mortality), communicable diseases such as AIDS and tuberculosis, and a new focus on mortality resulting from non-communicable diseases, substance abuse, road accidents and pollution. The post-2015 global agenda puts more emphasis on reducing inequalities and ensuring that “no one is left behind”. [4] The push for more equality in health can be seen in the promotion of the concept of universal health coverage, which aims to ensure that everyone has access to affordable, high-quality essential health-care services (WHO, 2015a).

8The preparation and monitoring of these programmes, the international mobilization against AIDS since the 1980s, the resurgence of diseases like tuberculosis and cholera, as well as considerable improvements in data sources in the past 30 years have led to an expansion of research on health and mortality and their determinants. Growing resources are now devoted to measuring inequalities in death and identifying the mechanisms behind them. A large share of the scientific literature on mortality inequality focuses on child mortality, which is well documented in the available surveys. Until recently, relatively few studies looked at adult mortality, beyond AIDS and maternal mortality.

Scope of analysis

9Drawing upon the literature and the most recent estimates, and on more detailed studies of ten selected countries, this article reviews mortality trends and mortality inequalities in low-and middle-income countries between 1990 and 2015. How has the mortality decline in the past 25 years affected mortality inequalities? Have disparities between countries increased, or on the contrary, are life expectancies converging? Have inequalities within countries narrowed or widened? Which sub-populations – by age, sex, social group and place of residence – have benefited the most from recent progress?

10The first section of this article defines the geographical scope of the review and describes the conventional sources of child and adult mortality data, measurement difficulties and relative data quality, as well as the key variables used to analyse the individual determinants. The second section looks at changes in life expectancies by sex between 1990 and 2015 and the contribution of the different age groups to the progress achieved. The third section deals with the changing pattern of child mortality and the determinants of inequalities within countries. The fourth section is concerned with adult mortality, with a particular focus on maternal mortality and HIV/AIDS. The fifth section discusses mortality inequalities by cause and the new forms of the epidemiological transition. The article concludes with some suggestions for further research.

Civil registration and vital statistics systems

20When they provide death statistics by age, sex and cause, certified and classified in accordance with the WHO’s International Classification of Diseases, civil registration systems are the only source, combined with a census, that allow continuous monitoring of mortality by age and cause of death. Of the 109 countries studied here, only 50 supply cause-of-death statistics to the World Health Organization (WHO, 2016). The data are only fully useable for 15 of those countries, where more than 90% of deaths are registered with an underlying cause. According to the WHO, in our sample of ten selected countries, only South Africa and Egypt register more than 90% of deaths and their causes, compared with less than 25% in China and India (for 2007-2013). [7]

Censuses

21Mortality – and consequently life expectancy – are estimated from answers to census questions about deaths by age that have occurred in the household in the previous 12 months, or about the survival of children and, in some cases, the survival of adults. Indirect demographic methods have been developed to compensate for the frequent under-reporting of deaths or to convert the percentage of surviving close relatives into survival probabilities. However, these methods are not ideal for measuring social inequalities because they rely on numerous assumptions, such as homogeneous quality of death reporting across the different social categories (Moultrie et al., 2013).

Retrospective surveys

22Retrospective surveys are the source most frequently used to estimate under-five mortality. Since the 1980s, most data have come from Demographic and Health Surveys (DHS), mainly funded by the United States, and UNICEF’s Multiple Indicator Cluster Surveys (MICS). [8] These surveys are designed to permit comparative approaches across time and space because the questionnaires are standardized and the collection methodologies are almost identical. The information gathered from women aged 15-49 can be used to estimate under-five mortality, based on their birth histories that provide information on the survival of children, and to estimate adult mortality, based on reported survival of parents and siblings (Masquelier et al., 2014a). Over the past 20 years, numerous studies on inequalities have been based on DHS data, dealing in particular with inequalities between men and women, between rural and urban areas and between ethnic groups, as well as by educational level and by standards of living. Caution is still required because some of the characteristics recorded at the time of the survey may have changed over time and thus skew the explanation for the differentials measured five to 15 years earlier (Bocquier et al., 2011; Lankoande, 2016).

Demographic surveillance systems

23There are around 40 demographic surveillance systems in 19 countries, often located in rural areas. A small population (between several hundred and several thousand households) is monitored in a targeted geographical area over a long period, so the data on mortality trends and causes of death are generally of high quality, but scope for studying mortality differentials is limited because the populations are fairly homogeneous in cultural and socioeconomic terms (INDEPTH, 2005). These systems closely monitor all changes in these communities and provide opportunities to conduct exploratory studies, on the impact of vaccination for example, or on the importance of less conventional determinants of mortality, such as the role of the family environment (Samuel and Hertrich, 2016).

4 – Relative data quality: caution still needed

30The data collected by surveys, censuses or civil registration must be of high quality to guarantee the accuracy of the levels, trends and differentials observed. This is particularly true for death, a tragic event that people generally prefer not to talk about. Reporting of deaths can therefore be distorted by inaccurate recall and time location. Caution and distance are always required for this type of data, especially when they are used to investigate inequalities, because reporting quality may vary across social groups.

31As an illustration, Figure 2 shows different estimates of the risk of dying before age 5 and at ages 15-60 for two neighbouring Western African countries, Nigeria and Cameroon. In Nigeria, the surveys and censuses lead to very different – and in some cases implausible – estimates of child mortality levels and trends. Conversely, in Cameroon, the estimates are much more consistent, and provide a fairly accurate picture. To calculate a plausible, smoothed trend, the United Nations agencies start with estimates from surveys and censuses and then apply a statistical model to derive adjusted estimates (represented in Figure 2 by a bold line), [11] and uncertainty intervals (Alkema et al., 2014a).

Figure 2

Trends in probabilities of dying at ages 0-5 (per 1,000 births) and at ages 15-60 (per 1,000 women aged 15), according to various sources in Nigeria and Cameroon

Trends in probabilities of dying at ages 0-5 (per 1,000 births) and at ages 15-60 (per 1,000 women aged 15), according to various sources in Nigeria and Cameroon

32In the absence of vital statistics, estimating adult mortality is more difficult, as Figure 2 illustrates. In Nigeria, the data on recent household deaths in the 2008 and 2013 DHS surveys produce fairly high adult mortality rates, of around 350 per 1,000 for women. The information gathered in the same surveys about the survival of sisters produces much lower rates, of around 215 per 1,000 (closer to the estimates derived from survival of parents). What is the real level of adult mortality in Nigeria? The UN Population Division gives an estimate of 340 per 1,000 in 2010, which is hard to justify and has sparked controversy (Gerland et al., 2014; Kassebaum et al., 2014). Cameroon provides another illustration of the uncertainty surrounding adult mortality. According to data on the survival of mothers and sisters collected in surveys and censuses, adult mortality was around 200 per 1,000 in the 1980s, then rose to around 300 in the early 2000s. According to the United Nations (2015), it remained steady at around 315 between 1970 and 1995, then increased to 400 in about 2003. The estimates derived from surveys and censuses are certainly distorted by under-reporting of deaths, but to what extent?

China, India and Brazil

45High excess female mortality is a longstanding phenomenon in China and India, contrary to Brazil. These three countries are among the best documented. [16]

46In the twentieth century, India and China, like other countries in Asia (such as Vietnam and Pakistan), the Middle East and Northern Africa (such as Algeria), excess female mortality was high at young and adult ages; the female advantage in life expectancy was therefore very small and there was even a male advantage in some cases. These countries have continued to make significant gains in life expectancy since 1990, albeit at different rates and at a slightly slower pace overall than in the 1970s and 1980s. In the last 25 years, female life expectancy gains have strongly outpaced male gains (Table 4), with almost 9 years for women versus 6.8 years for men in China, and 10 years and 7.5 years, respectively, in India. Chinese women can now expect to live for close to 80 years, [17] Indian women almost 70.

Table 3

Life expectancy at birth (years) by sex and female-male difference, 1990-2015, by region and income category

1990 2015 Change in difference (F-M) 1990-2015 Both sexes Females Males Difference (F-M) Both sexes Females Males Difference (F-M) Income categories High-income 74.1 77.7 70.4 7.3 79.2 82.2 76.2 6.0 – 1.3 Upper middle-income 67.9 70.3 65.8 4.5 74.3 76.5 72.3 4.2 – 0.3 Lower middle-income 59.1 60.4 57.9 2.5 66.9 68.8 65.2 3.6 +1.1 Low-income 49.0 50.5 47.5 3.0 61.4 63.0 59.8 3.2 +0.2 Regions (low- and middle-income countries only) Northern Africa (6 countries) 64.0 65.9 62.1 3.8 71.3 73.3 69.3 3.9 +0.1 Sub-Saharan Africa (42) 49.7 51.3 48.1 3.1 58.7 60.0 57.4 2.6 – 0.5 East Asia (3) 69.1 70.7 67.4 3.4 76.0 77.5 74.4 3.1 – 0.3 South-Central Asia (12) 58.8 59.5 58.1 1.4 68.7 70.2 67.2 3.0 +1.6 South-East Asia (9) 65.1 67.5 62.7 4.9 70.7 73.5 67.8 5.7 +0.8 Western Asia (10) 65.3 68.3 62.3 6.0 72.1 75.1 69.1 6.0 0 Latin America (17) 67.2 70.5 63.9 6.4 74.9 78.1 71.8 6.2 – 0.2 Europe (9) 70.0 73.9 66.0 7.9 72.8 77.0 68.7 8.4 +0.5 World 64.1 66.4 61.8 4.6 71.1 73.3 68.9 4.4 – 0.2

Life expectancy at birth (years) by sex and female-male difference, 1990-2015, by region and income category

Note: The regional averages were obtained by weighting the life expectancies by the populations of each sex.

47These rapid improvements in female life expectancy, which have occurred in most age groups (Zhao et al., 2016), have widened the gender gap in life expectancy at the country level (Table 4): between 1990 and 2015, the female advantage increased from 3.7 years to 5.8 years in China, while the trend in India went from equality to a three-year female advantage. However, these differentials are smaller than those observed in Europe when life expectancy was at equivalent levels, or in Latin America today. This is clearly illustrated by the example of Brazil, which has also recorded large life expectancy gains, but of the same number of years for both sexes (around 8 years). When average life expectancy was 60 years (in around 1975), Brazilian women had a 5.5 year advantage over men, which is almost the same differential as in China today, some 40 years later, where average life expectancy is 76 years.

48A comparison of the three countries confirms the gradual emergence of a female life expectancy advantage, including in India, which lagged for many years. It also shows that the gender gap at a given time is not directly linked to the overall mortality level. Each region, and even each country within each region, has its own history in this respect, which is influenced by the health gains achieved but also by the changing norms and cultures that govern gender relations.

Table 4

Life expectancy at birth (years) by sex from 1970 to the 2010s in China, India and Brazil

Country Overall Females Males Difference (F-M) China 1970 (a) 58.2 60.2 56.5 +3.7 1980 (a) 66.3 68.3 65.0 +3.3 1990 68.6 70.5 66.8 +3.7 2000 71.4 73.3 69.6 +3.7 2015 76.3 79.4 73.6 +5.8 Increase since 1990 7.7 8.9 6.8 - India 1970-1975 49.0 49.0 50.5 – 1.5 1988-1992 58.7 59.0 58.6 +0.4 2000-2004 63.9 65.2 62.8 +2.4 2006-2010 66.1 67.7 64.6 +3.1 2010-2015 (a) 67.5 69.0 66.1 +2.9 Increase since 1990 8.8 10.0 7.5 - Brazil 1970 (a) 59.1 61.5 56.5 +5.0 1980 62.6 65.7 59.6 +6.1 1991 67.0 70.9 63.2 +7.7 2000 70.4 74.3 66.7 +7.6 2013 74.9 78.6 71.3 +7.3 Increase since 1991 7.9 7.7 8.1 -

Life expectancy at birth (years) by sex from 1970 to the 2010s in China, India and Brazil

49But are the same sex differentials in life expectancy observed at a smaller geographical scale? Have all the provinces or regions of these large countries moved in the same direction, and at the same speed? Thanks to the wealth of data available in India, [18] we can review mortality trends in 17 Indian states between 1970 and 2010. Saikia (2016) highlights the diversity of situations and trends. Some 35 years ago, in all the states except Kerala and Maharashtra, women had lower life expectancy than men, with a particularly large gender gap in the east and north. By 1990, the situations were more varied. Nationally, India attained gender equality in life expectancy, but excess female mortality persisted in almost half of the states, particularly in rural areas, until around 2002 (Canudas et al., 2015; Saikia et al., 2010). By the late 2000s, the trend had reversed, and all states (bar one, in the north-east) exhibited a female life expectancy advantage. Progress was variable, however, with the female advantage in 2008 ranging from 0.7 years in Bihar to 5.4 years in Kerala. Of course, analysis at a finer district level would reveal even more heterogeneity and would identify excess female mortality in a number of localities.

50The scenario is somewhat different in China, where, by 1990, women already lived longer than men in all provinces. The female advantage [19] ranged from 2.7 years in Inner Mongolia (where life expectancy was 66 years) to 4.3 years in Shanghai (life expectancy of 75 years). Two decades later, in 2010, the female advantage had increased everywhere, but without the strong divergence between states found in India: it ranged from 3.0 years in the provinces where it was lowest to 5.4 years in those where it was highest. The female advantage in China is especially high in the cities because of the large gender gap in mortality from cancers and circulatory and respiratory diseases (Le et al., 2015).

51In Brazil, the female advantage, already high in 1991 (7.7 years at country level) remained stable until 2004 (at 7.6 years) before falling slightly in 2010 (to 7.1 years and an average life expectancy of 74 years). [20] But the slight dip at the country level is the result of two contradictory trends: a decrease in the wealthiest, most urbanized states and an increase in the three poorest ones. As in China, the lack of data on causes of death by region means that the epidemiological origin of these contrasting developments cannot be determined.

Mortality in the first five years of life

60Under-five mortality has fallen significantly everywhere, whatever the base level, which was generally very high in 1990, with reductions ranging from 55% to 65% by income group, and from 54% (sub-Saharan Africa) to 79% (East Asia) by region (Table 6). Globally, the mortality rate and the total number of deaths before age five have halved in 25 years. According to the data from UN IGME (2015), in the 109 low- and middle-income countries, 5.8 million children died before their fifth birthday in 2015, compared with 12.5 million in 1990. With mortality at young ages almost completely under control in the world’s richest nations, 98% of under-five deaths are now concentrated in these countries.

Table 6

Risks of death at ages 0-1 and 0-5 between 1990 and 2015, by region and income group

Risk of death at age 0-1 (per 1,000) Risk of death at ages 0-5 (per 1,000) 1990 2015 Relative decrease (%) 1990 2015 Relative decrease (%) By country category High-income Upper-middle-income Lower-middle-income Low-income 13 6 43 15 83 40 113 53 – 55 – 64 – 51 – 53 15 7 56 20 119 53 187 76 – 56 – 65 – 55 – 59 By region (low- and middle-income countries only) Northern Africa (6) Sub-Saharan Africa (42) East Asia (3) South-Central Asia (12) South-East Asia (9) Western Asia (10) Latin America (17) Europe (9) 60 27 109 57 42 9 88 40 53 22 54 21 46 16 22 8 –55 – 48 – 77 – 54 – 58 – 61 – 66 – 64 82 35 182 84 54 11 123 51 73 27 71 25 59 19 26 9 – 57 – 54 – 79 – 59 – 62 – 65 – 68 – 65 World 63 32 – 49 91 43 – 53

Risks of death at ages 0-1 and 0-5 between 1990 and 2015, by region and income group

Note: The regional averages or averages by income group were calculated by weighting the risks of death by the number of births in the same year (WPP 2015).

61Sub-Saharan Africa, where the majority of the poorest countries are located and where health infrastructure is the weakest, had the world’s highest base levels in 1990. It too has seen substantial improvements, with a reduction in under-five mortality from 182 deaths per 1,000 births in 1990 to 84 in 2015, and in infant mortality from 109 deaths per 1,000 births in 1990 to 57 in 2015. However, sub-Saharan Africa is still by far the region with the highest under-five mortality risk: a newborn in sub-Saharan Africa is eight times more likely to die before age five than in China, and almost twice as likely as in India.

62It is at ages 1 to 5 (child mortality) – the ages most responsive to social and health progress (vaccination, nutrition, etc.) but also to health crises – that the sharpest decreases in mortality have been achieved, ranging from a 65% reduction in sub-Saharan and Northern Africa to an 84% reduction in East Asia. [27] In the first month of life (neonatal mortality) – a vulnerable age traditionally less responsive to interventions owing to the nature of the risks and the cost of treatments – mortality reductions have been slower and more uneven (UN IGME, 2015), ranging from a decrease of 38% in sub-Saharan Africa to 81% in East Asia, and from 45% in low-income countries to 67% in upper-middle-income countries. These differences by age have gradually led to a concentration of under-five mortality in the first few weeks or months of life. Progress is very advanced in Latin America, East and South-East Asia, where mortality between two or three months and five years is now very low.

63While overall progress has been substantial, the inequalities between world regions did not diminish between 1990 and 2015; in fact, they even increased. Across the different country income groups (excluding high-income countries), the under-five mortality ratio between the extreme groups widened from 3.3 in 1990 to 3.8 in 2015 (Table 6). Between the extreme regions it increased from 7 to 9.3. The direction of change was the same for infant mortality, and even more unfavourable for child mortality (ages 1-5).

64An encouraging development is the faster pace of change in the 2000s, especially from 2005 onwards (UN IGME, 2015). On average, under-five mortality fell by 4.3% per year in low- and middle-income countries between 2005 and 2015, compared with 3.2% per year between 1990 and 2005. In some 20 countries, including some of the poorest, among them Cambodia, Kenya, Senegal, Burkina Faso and Mexico, the pace of mortality reduction doubled between the two periods. The recent acceleration is particularly evident in sub-Saharan Africa, thanks to programmes to prevent mother-to-child transmission of HIV and the distribution of anti-retroviral drugs in the countries severely affected by AIDS (Ndirangu et al., 2012; UNAIDS, 2015). Elsewhere, the progress was achieved mainly through renewed efforts to improve immunization coverage, sanitation, access to safe drinking water, and use of insecticide-treated mosquito nets to combat malaria. For example, coverage of the first dose of the measles vaccine – an effective, inexpensive method of immunization – rose from 57% in 1990 to 73% in 2015 in sub-Saharan Africa (World Bank, 2016), a faster increase than in the other regions. Sub-Saharan Africa also recorded substantial progress in access to safe drinking water, with an increase from 47% to 68% in the percentage of the population using an improved source of drinking water in the past 25 years (World Bank, 2016). Last, it is estimated that by 2015, 68% of children under five in the region were sleeping under insecticide-treated mosquito nets, compared with only 2% in 2000 (WHO, 2015b).

Excess mortality of boys is increasing worldwide

73Most of the recent reviews of global trends in child mortality differentials by sex (Alkema et al., 2014b; United Nations, 2011; Sawyer, 2012) analyse changes in the previous 20 or 30 years, particularly in developing countries and regions, using the most reliable available estimates on as many countries as possible. Gender inequalities at the different ages (0-1, 1-4 years and 0-5 years) are often measured by the sex ratio of mortality, expressed as a percentage (number of male deaths for every 100 female deaths). A figure above 100 indicates excess male mortality, while a figure below 100 indicates excess female mortality (Figure 7). According to Hill and Upchurch’s model (1995), [31] when under-five mortality is around 50 per 1,000 live births (the current level in many Southern countries), we should observe roughly 125 male deaths at these ages per 100 female deaths in the absence of discrimination (the ratio should be around 128 below 12 months, and around 117 between one and four years). The sex ratio of mortality tends to increase as mortality rates fall, especially between the ages of one and four years.

74There have been huge changes in a majority of countries but these are not yet universal. On average, across 83 countries, excess male deaths below age five have increased, with a sex ratio of mortality that rose from 111 in the 1970s to 119 in the 2000s (United Nations, 2011). In line with Hill and Upchurch’s model (1995), the ratio increased more for child mortality (one to four years) than for infant mortality (below 12 months). However, if we weight the average sex ratios of mortality at national level by the number of births in the country, the trend is reversed: the under-five mortality sex ratio fell from 103 in the 1970s (as opposed to 111) to 99 (as opposed to 119) in the 2000s, because of the enormous impact of China and India, which were exceptions to the global trend over that period (Figure 7).

Figure 7

Under-five male mortality rates and sex ratios of mortality in seven countries, from 1990 to 2015

Under-five male mortality rates and sex ratios of mortality in seven countries, from 1990 to 2015

75Excess male infant mortality, which has increased slightly or remained stable since the 1990s, is now observed almost everywhere, with the noteworthy exception of China, even in the 2000s. Excluding China, it ranges from 16% to 24% between the major world regions.

76In most regions (excluding China and India), the female disadvantage at ages 1-4 is narrowing, although it has not reached what it should be, given the current levels of mortality and the reductions achieved. Between the 1980s and the 2000s, the average regional mortality sex ratio at ages 1-4 years increased from 94 to 102 in Northern Africa and Western Asia, from 103 to 112 in East and South-East Asia (but only from 94 to 101 if China is included), from 81 to just 99 in South Asia (but from 77 to 69 if India is included), and from 106 to 113 in Latin America.

77Here again, regional averages mask the diversity of socio-cultural situations and contexts at country level. With the possible exception of Latin America, no region in the world has been, or is, totally exempt from a preference for boys, which gives rise to discriminatory behaviours against girls that adversely affect their health. This is clearly the case in almost all countries of Northern Africa and the Middle East, where, from Morocco to Turkey, excess female mortality between one and five years is a longstanding phenomenon, [32] regardless of the wealth and overall mortality rate in each country (Tabutin et al., 2007). On average, excess mortality of girls is decreasing and, in some cases, has even disappeared (Alkema et al., 2014b), but at different speeds in different countries. The case of sub-Saharan Africa, a vast, highly diverse region long believed to be untouched by this problem, is worth a closer look. The DHS/MICS surveys in the 1980s and 1990s revealed widespread excess male infant mortality, but also found excess mortality of girls between the ages of one and five years (Tabutin et al., 2007). In the 1990s, these inequalities did not fit a precise geography; no link was found with the degree of Islamization of societies, nor with the level of social and health development of the countries concerned (Tabutin et al., 2007). According to Alkema et al. (2014b), excess male mortality between one and five years was low in sub-Saharan Africa in 2012 (2%), and practically unchanged since 1990.

The atypical histories and situations of India and China

78The social and health status of girls is a longstanding issue of concern in many countries of South and East Asia. These regions have the highest excess mortality of girls in the world, with a sex ratio of infant mortality in the 2000s of 90 in East and South East Asia (101 for child mortality) and 101 in South Asia (64 for child mortality) (United Nations, 2011). The figures of Alkema et al. (2014b) for 2012 confirm the high excess mortality of girls aged between one and five in South Asia and the lack of progress since 1990 (from 0.75 to 0.79). In 2012, excess female child mortality was still high in Pakistan and Nepal; only in Bangladesh has it disappeared. Of course, China and India weigh heavily in those regional averages.

79China, like India, has been the focus of considerable research on the status of women, and has doubtless long been one of the most unequal countries in terms of under-five mortality, especially in rural areas (Attané and Barbieri, 2009). Despite achieving relatively low levels of under-five mortality (24 deaths before age five per 1,000 live births in 2005), China still exhibited excess female mortality in the first two years of life in the 2000s (United Nations, 2011). More surprisingly, between the 1970s and the 2000s, the situation appears to have worsened for infant mortality (below 12 months), but improved for child mortality (between one and five years). According to the life tables published in the latest revision of the UN Population Division (2015), excess mortality of girls had disappeared by 2015; indeed, excess male mortality now reportedly stands at around 11% for infants below 12 months and for children aged 1-5, [33] although it is still below the level to be expected in the absence of discrimination (Hill and Upchurch, 1995). Alkema et al. (2014b) arrive at a similar result for 2012 (15%). Those results would need to be confirmed with very recent data. Moreover, they give no indication of the likely variability within the country, between different provinces and between urban and rural areas.

80Bannister (2004), Li et al. (2004) and Das Gupta (2009), and more recently Guilmoto (2015), among others, suggest explanations for the historic discrimination against girls and preference for boys in China, including the rigidity of the patrilineal family system, the importance of a son for ensuring the survival of the lineage and for ancestor worship, and the fact that a daughter is married off early and belongs to her in-laws. The impact of these factors has been further amplified by the one-child policy and the recent context of the privatization of health services, the high cost of education, and increasing socio-economic inequalities. To tackle the problem, the Chinese government implemented a national campaign called Care for Girls in 2006 to combat the causes of excess female mortality and sex-selective abortion. We may now be witnessing the initial effects of that campaign.

81India, which for many years had much higher under-five mortality than China (UNICEF, 2015), [34] has a slightly different, well documented, history. Unlike China, where excess female mortality occurs (or occurred) early (during the first days or weeks of life), in India it occurs later (although still beginning in the post-neonatal period) and persists for longer (United Nations, 2011; Sawyer, 2012). Alkema et al. (2014b) found almost no change between 1990 and 2012 and estimate that excess mortality of girls between one and five years stands at almost 30%. Our analysis of the official life tables for the years 1995-1999 and 2006-2010, assuming they are reliable, confirms the virtual lack of change over the period: there is near equality of mortality between boys and girls under 12 months, and around 32% excess mortality of girls between one and five years (with, unexpectedly, few differences between urban and rural areas nationally). But again, these national averages mask diverse situations in different states: excess female mortality was observed in the large Indian states, particularly in the north and centre-north, in 2008 (Arokiasamy, 2007).

82As in China, excess female mortality in India has long been attributed to the rigidity of the patrilineal family systems in much of the country, especially the north, under which women and girls are subordinate to boys, represent a financial disincentive (a daughter will leave the family early), and have little independence or decision-making power (Das Gupta, 2009; Dyson and Moore, 1983). This is reflected in inequalities in terms of breastfeeding, food and access to healthcare, and in neglect of girls of high birth orders. However, based on the National Family Health Survey, Kuntla et al. (2014) identify progress between 1992 and 2006: they confirm that the excess mortality of girls decreased over that period, although it still remains high, especially in northern and central India.

The long-established and universal role of mothers’ education

85Both public health policymakers and demographers have long recognized the positive role of mothers’ education on child health and mortality. In a macro-geographical study of 175 countries, Gakidou et al. (2010) attribute 51% of the decline in under-five mortality between 1970 and 2010 to improvements in female education between the ages of 15 and 50. [36]

86All surveys and censuses show a clear link between inequalities in child survival and mothers’ educational levels: the more literate the mother, the lower her children’s mortality risk. The risk quadruples between mothers with post-secondary education and illiterate mothers. Having attended school, even only primary school, leads to better child survival almost everywhere. Inequalities by mother’s educational level are often highest for children between one and five years old, at least in contexts where overall mortality is high. The role of education probably varies by country [37] and period, but it is important, whatever the mortality level. Figure 8 illustrates the situation in the six selected countries.

87Though weaker, the impact of education persists after controlling for other variables in multivariate analyses. Fuchs et al. (2010) have already shown that the mother’s education is more important than household income for reducing under-five mortality in developing countries. In a recent study of 50 low- and middle-income countries, based on DHS data (2003-2013), Gaigbe-Togbe (2015) re-examined the determinants of child survival by focusing on educational level, income, and place of residence. The study found that after controlling for income, in most countries, mothers’ education still had a significant independent impact on the mortality risk, that this impact varied across world regions, [38] and that it increased with income.

88But how have inequalities by educational level changed since the 1990s? Where has the fastest progress occurred? Let us examine the situation in the six countries shown in Figure 8A and Table 7. Overall, we observe a diversity of patterns. Excluding Nigeria (slow progress for all groups), the fastest improvements occurred among the least educated mothers (no education or only primary schooling), whose children had high mortality in the 1990s (100 or higher per 1,000 live births). This was the case in Egypt, for example. With much lower base levels, the pace of decrease among the children of mothers with higher education was two or three times slower. [39] Inequalities have become smaller in these countries, but there is still a strong education gradient.

89Mothers’ education [40] is closely linked to the status of women, their decision-making power in the household, their contact with the outside world, their ability to talk to and negotiate with the health services, and their knowledge (Caldwell, 1979, 1986; Cleland and van Ginneken, 1988). But it is also linked to the standard of living and financial resources of their household.

Figure 8

Changes in under-five mortality rates between two DHS waves in six countries, (A) by mothers’ educational level, (B) household wealth and (C) place of residence

Changes in under-five mortality rates between two DHS waves in six countries, (A) by mothers’ educational level, (B) household wealth and (C) place of residence

Household wealth: now a key factor

90Without forgetting education, the focus of research in the 1990s and 2000s shifted to household economic status, standard of living and poverty as potential determinants of child health. New questions were included in the DHS/MICS surveys to measure the economic well-being of households as a proxy for income and new indicators were developed to compensate for the lack of data on household income or expenditure [41] It is now possible to measure inequality levels and trends by what we shall simply call household wealth.

Table 7

Annual rate of reduction (%) in under-five mortality between two DHS surveys in six countries, by mothers’ educational level, household wealth and place of residence

Country Bolivia Burkina Faso Egypt India Indonesia Nigeria Survey 1 1994 1993 1995 1992/3 1997 1990 Survey 2 2008 2010 2014 2005/6 2007 2013 Educational level No education 2.4 1.8 5.8 2.2 1.4 0.7 Primary 4.0 2.2 5.3 1.1 2.8 1.0 Secondary 2.8 2.0 2.8 1.0 –0.3 1.2 Higher 1.4 1.0 2.0 1.7 –9.2 –0.4 Household wealth quintiles Poorest 3.0 0.8 6.6 2.1 3.5 1.0 Poor 3.8 1.6 6.6 3.4 2.7 0.9 Middle 5.1 2.8 5.7 3.0 4.5 1.7 Rich 5.8 2.5 4.6 2.7 3.7 2.0 Richest 3.8 2.8 3.8 2.5 –1.0 2.2 Place of residence Rural 3.5 1.9 6.5 2.6 2.8 1.0 Urban 4.6 2.1 5.4 1.9 2.3 1.1

Annual rate of reduction (%) in under-five mortality between two DHS surveys in six countries, by mothers’ educational level, household wealth and place of residence

91Unsurprisingly, the richer a household, the lower the child mortality: the recent literature is unanimous on that point. But this inequality results not only from the often huge gulf between rich and poor; it follows a more or less linear social gradient of decreasing mortality from the poorest to the richest quintiles (Houweling et al., 2005; Houweling and Kunst, 2010). Figure 8B illustrates this pattern for six countries. Like the impact of education, the under-five mortality differentials between wealth quintiles vary over time and between countries. In the poorest countries with the highest mortality, like Burkina Faso, the differentials between the poorest, poor and middle-income quintiles are relatively small; lower mortality is only clearly visible among the richest elite.

92Gaigbe-Togbe’s analysis (2015) of the individual risk of death in 50 countries confirms, for the recent period, the crucial role of household wealth in child survival, after controlling for educational level. In these 50 countries, the study found few differences between the poorest and the poor quintiles; a clear gap only emerged between the middle-income, rich and, especially, richest quintiles. The highest correlations between household wealth and under-5 child mortality were found in Latin America and Asia, and the lowest in Africa. Moreover, the author shows that household wealth had a bigger impact on child mortality (1-4) than on infant mortality. Wealth generally rises with education, but when education is controlled for in the models, the impact of household wealth on child mortality decreases, and in some cases becomes non-significant.

93How have these economic inequalities changed since 1990 and 2000? Bendavid (2014) recently explored the question through a macro-analysis of under-five mortality, based on the combined DHS data from 54 countries, including 29 countries with two surveys between 2002 and 2012. Working with wealth tertiles (least poor, middle-income, and poorest), but without controlling for other variables such as education or place of residence, the analysis confirmed the role of wealth (or poverty) at a specific time. The main finding was that the poorest group saw the fastest annual declines in mortality in the 2010s: annual rates ranged from 2.1% to 4.4% between the extreme tertiles (average of 29 countries). The author also observed a pattern of convergence, while noting that it is far from universal. The findings of the recent WHO report (WHO, 2015b) on child health in 86 low- and middle-income countries support this trend: the economic inequalities in under-five mortality have narrowed in a majority of countries. But this average may mask divergent patterns between countries.

94In the six selected countries (Figure 8), over the 15 years covered, the average mortality reductions are substantial across all social groups (quintiles), but occurred at different speeds and in different ways in each country. In the two most disadvantaged countries in the sample (Burkina Faso and Nigeria), but also in Bolivia, mortality fell fastest in the richest groups, two to three times faster than in the poor and poorest groups. Conversely, the poor and poorest quintiles saw the most progress in Egypt between 1995 and 2014, whereas India and Indonesia showed few significant differences in mortality trends by wealth quintile. In other words, based on these few examples, no overall trend can be identified: inequalities in under-five mortality by level of household wealth increased in some countries, especially those with the highest mortality (Bolivia, Burkina Faso, Nigeria), decreased in others (Egypt), and remained stable in yet others (India, Indonesia).

Place of residence: persistent urban-rural inequalities

95The many studies of child survival differentials by place of residence show that mortality in low- and middle-income countries has consistently been significantly higher in rural than in urban areas (Cleland et al., 1992; Cleland and Harris, 1998; Gould, 1998; Günther and Harttgen, 2012; Lalou and Legrand, 1997). [42] The urban-rural gap varies, of course, by period and country, and depends on the type and pace of urbanization, the respective socioeconomic characteristics of the two types of area (education, wealth, etc.), and on health policies. In a large literature review for the period 1975-1990, Sastry (1997) showed that child mortality differentials by place of residence persisted after controlling for education and various household characteristics, though they were often smaller. According to our calculations, based on the most recent DHS surveys (2008-2014), [43] excess rural under-five mortality is relatively independent of the national level of mortality: between 40% and 50% in countries as different as Nigeria, Bolivia, Afghanistan and Egypt, 34% in Indonesia and Burkina Faso, and only 19% in the Democratic Republic of Congo, where mortality is high in cities and countryside alike. In the neonatal period (the first 28 days of life), the rural/urban divide is of similar magnitude, but slightly lower in countries with lower child mortality and better healthcare provision in terms of infrastructure and personnel.

96Urban-rural inequalities have narrowed overall in the past 20 years (Garenne, 2010; WHO, 2015b), but again the differentials vary across countries, depending on the social and health policies implemented (particularly investment in rural areas) and on the socioeconomic situations of the cities. [44] For example, under-five mortality has fallen much faster in rural than in urban areas in Egypt, India and Indonesia (Figure 8C), at the same speed in Burkina Faso and Nigeria, and much more slowly in rural areas in Bolivia. It is therefore hard to generalize.

97For some time, a debate has been running about current and future health in cities, in particular large cities and metropolises (Brockerhoff and Brennan, 1998). Some authors (e.g. Gould, 1998), now in the minority, have maintained that rapid urbanization would spur the mortality transition; others hold that urbanization, which is often uncontrolled and accompanied by an increase in informal settlements and poverty, insufficient healthcare and environmental services (water management, waste management, pollution control, etc.), is generating huge intra-urban inequalities and a deterioration in urban health which could even lead to an increase in urban mortality rates. The concept of “urban penalty” refers to excess urban mortality such as that observed in nineteenth-century Europe, when industrial cities were characterized by poverty, a lack of personal and collective hygiene, and non-existent or deficient social and health services (on the concepts and debates, see Bocquier et al., 2011; Maïga and Bocquier, 2016; Ramiro-Fariñas and Oris, 2016).

98With increasing socio-spatial segregation in large cities, in particular the extension of peripheral neighbourhoods and slums, intra-urban inequalities have become a key theme in local health action programmes (Fink et al., 2014). According to Montgomery (2009), cities have an overall advantage, but the children from the poorest households, whose numbers are increasing, are no better off than in rural areas. The study by Kyu et al. (2013), conducted on 45 countries, reveals the strong negative impact of residence in a slum on child health (particularly stunting), [45] after controlling for other household characteristics. This is the case in Nairobi, where half of the population lives in slums, and in many other large cities in the South (e.g. Soura (2009) on Ouagadougou). Günther and Harttgen (2012), who studied ten African countries, found an average 65% excess mortality among children living in slums compared with those living in formal housing, and concluded that mortality inequalities within cities are greater than between rural areas and slums. We need to bear in mind, however, that rural areas (less well documented in terms of inequalities) are never a homogeneous whole, and also encompass a diversity of situations.

Proximate determinants of mortality: immunization coverage and malnutrition

99While child mortality has fallen significantly everywhere and spatial and social inequalities are regressing overall, what about the trends in proximate determinants such as child immunization and malnutrition, two factors underlying the mortality transition at young ages? [46] Again, most studies are based on DHS/MICS data. In the abundant literature on these determinants, we focused on a WHO report (2015b) and on Rutstein et al. (2016), which both looked at changes in socioeconomic inequalities in low- and middle-income countries in the 2000s.

100Large differences in immunization are observed between countries. For example, over a 13-year period, full basic immunization [47] coverage increased from 44% to 81% in Burkina Faso and remained at around 91% in Egypt, while coverage rose only from 13% to 25% over a ten-year period in Nigeria. Regarding within-country differences, in 26 low- and middle-income countries (Rutstein et al., 2016), towns fare, on average, slightly better than cities, and much better than rural areas (coverage rates of 58%, 53% and 45%, respectively). Unlike other variables, immunization coverage in cities varies little with household wealth; today it is only among the poorest rural populations that coverage is particularly low (33%). Progress is visible everywhere. According to Rutstein et al. (2016), it is more evident in cities and in the richest population groups in all three places of residence (cities, towns and rural areas), whereas according to the WHO, on a larger, more heterogeneous sample of 86 countries, the gaps between the richest and poorest have narrowed in a majority of cases (WHO, 2015a). Almost everywhere, there is little difference in immunization coverage between boys and girls (WHO, 2015a).

101The nutritional status of children, measured by stunting, bodyweight and prevalence of anaemia, is still, as to be expected, strongly associated with place of residence, household poverty and mothers’ educational level. Children’s nutritional status is better in middle-income countries than in poor countries (WHO, 2015a) and is positively correlated everywhere with mothers’ educational level. There have been significant improvements in all population groups, but stunting in children remains linked to the place of residence (it is two to three times more frequent in rural areas than in cities) and household poverty (children in the poorest households, in both urban and rural areas, are between twice and almost three times more likely to be stunted than children from non-poor households; Rutstein et al., 2016). The same inequalities are observed for underweight children, but there was no major change in prevalence in the 2000s. Regarding anaemia, the average prevalence is very high in cities (42% of children) and in rural areas (57%), and increases significantly from wealthy households (30%) to poor households (39%) and very poor households (60%). Clear advances have been made, however, and on the whole they tend to benefit the most disadvantaged populations.

102All these elements are contributing to the rapid decline in child mortality and illustrate the progress achieved; but they also reveal the persistence of large social, economic and geographical inequalities between and within countries.

General trends

106At the global level, between 1990 and 2015, adult mortality decreased almost three times more slowly than child mortality (Table 8). While under-5 mortality fell by an average of 3% per year over the period, the annual rate of decrease for adults aged 15-60 was only 1.1% for men and 1.2% for women. Expressed as relative decreases, these changes represent a drop of between 19% in lower-middle-income countries and 30% in upper-middle-income countries for men, and around 30% for women regardless of income category. The slower decline among men in lower-middle-income countries is due to low rates of progress in Indonesia (0.2% decrease per year), Pakistan (0.8%), Nigeria (0.4%), and the Philippines (0.2%).

Table 8

Male and female probability of dying between ages 15 and 60 by region and country’s income category, in 1990 and 2015

Adult mortality 45q15 (per 1,000) Men Women 1990 2015 Relative decrease (%) 1990 2015 Relative decrease (%) By country category High-income Upper-middle-income Lower-middle-income Low-income 188 133 –29 192 134 –30 276 224 –19 392 280 –29 87 66 –25 129 88 –32 220 154 –30 334 233 –30 By region (low- and middle-income countries only) 168 114 –32 335 286 –15 116 72 –38 226 136 –40 171 128 –25 140 101 –28 149 95 –36 113 96 –15 North Africa (6) Sub-Saharan Africa (42) East Asia (3) South and central Asia (12) South-East Asia (9) Western Africa (10) Latin America (17) Europe (9) 233 172 –26 397 329 –17 155 99 –36 273 203 –26 239 212 –11 230 177 –23 257 178 –31 260 240 –8 World 230 176 –23 159 118 –26

Male and female probability of dying between ages 15 and 60 by region and country’s income category, in 1990 and 2015

Note: The regional averages were obtained by weighting the probabilities of dying by the size of the population aged 15-59; they may therefore differ from WPP 2015 estimates.

107In high-income countries, between 1990 and 2015, the risk of death between ages 15 and 60 was about twice as high for men as for women (Table 8). The sex ratio of adult mortality (ratio between men’s and women’s risks of dying) is lower in poor countries: in low-income countries in 2015 it stood at only 1.2. Overall, men’s adult mortality disadvantage has slightly increased over the years, particularly in lower-middle-income countries. We will return below to the question of the determinants of these sex inequalities in adult mortality.

108Table 8 also highlights large disparities in progress between regions. In 1990, sub-Saharan Africa stood out from other geographical regions, with a risk of death between ages 15 and 60 of nearly 400 per 1,000 for men and 330 per 1,000 for women. In contrast, adult male mortality in East Asia was the lowest among all low- and middle-income countries, while adult female mortality was slightly higher than that of European middle-income countries. This regional average was, in fact, largely determined by China, where by 1990 the risk of dying between ages 15 and 60 had already fallen to 155 per 1,000 for men and 116 per 1,000 for women. In other regions, in 2015, adult mortality in low- and middle-income countries ranged between 230 and 280 per 1,000 for men, and between 110 and 230 per 1,000 for women.

109Over the last 25 years, worldwide inequalities between countries in different income categories have persisted. Adult mortality among men living in low-income countries is double that of men in high-income countries; the ratio for women is 3.5. The disparities between broad geographical regions have widened, with faster decreases in East Asia, South and Central Asia, North Africa, and Latin America, contrasting with low rates of progress in sub-Saharan Africa and Europe. In South-East Asia (Indonesia, Philippines), progress has been slow among men, but twice as fast among women. Consequently, women’s advantage in adult survival has increased slightly in almost all regions.

110These regional averages mask relatively diverse patterns of change between 1990 and 2015, which can be seen in Figure 9. Adult mortality decreased in most countries over this period (below the diagonal), with the exception of Syria (for men) due to the recent conflicts, and a number of African countries that have been severely affected by the HIV/AIDS epidemic. A few countries show particularly rapid progress: in Iran, Lebanon, Nepal, Morocco, Cambodia, and Timor-Leste, adult mortality has fallen by more than half in the last 25 years.

111Figure 10 presents the probability of dying between the ages of 15 and 60 years (₄₅q₁₅) from 1990 to 2015 by five-year periods, for the 10 selected countries chosen for analysis here. There have generally been steady decreases over the period, with the exception of the three sub-Saharan African countries affected by HIV/AIDS, and of Indonesia, where the last 15 years have not seen clear progress. [48]

Figure 9

Change between 1990 and 2015 in the risk of dying (per 1,000) between ages 15 and 60, in 108 countries classified by 2015 income level, by sex

Change between 1990 and 2015 in the risk of dying (per 1,000) between ages 15 and 60, in 108 countries classified by 2015 income level, by sex

Figure 10

Risk of death between ages 15 and 60 (per 1,000, both sexes combined) in 10 countries by five-year periods

Risk of death between ages 15 and 60 (per 1,000, both sexes combined) in 10 countries by five-year periods

Impact of the HIV/AIDS epidemic on adult mortality trends

112The countries where adult mortality trends have been most disrupted over the past 25 years are those most severely affected by the AIDS epidemic. As most HIV infections are sexually transmitted, deaths due to AIDS are mainly concentrated among adults. According to the latest estimates from the Joint United Nations Programme on HIV/AIDS, out of the 1.1 million persons who died of AIDS in 2015, 91% were 15 years old or above. [49]

113Detectable increases in adult mortality due to the epidemic were observed in the late 1980s in several East African countries, such as Uganda, Zambia, and Malawi (Blacker, 2004; Timæus and Jasseh, 2004). The epidemic then developed and expanded into other countries, particularly in southern Africa, where HIV prevalence reached its highest levels. In Zimbabwe, for example, according to UNAIDS data, up to 26% of the adult population aged 15-49 years was HIV-positive in 1997. According to DHS data, the probability of dying between ages 15 and 60 years tripled in that country, rising from 21% among men in 1985 to 65% in 2000 (Masquelier et al., 2014a). HIV prevalence subsequently decreased, falling to 15% in 2015, [50] and adult mortality likewise (from around 2005), although it has not returned to pre-epidemic levels. Zimbabwe is one of the countries where adult mortality has been most affected by the epidemic, due to extremely high HIV prevalence (Feeney, 2001). Only in seven other countries, all located in or close to southern Africa, [51] did prevalence exceed 15% among adults aged 15-49 years. In South Africa, HIV prevalence increased steadily to 21% in 2004, before declining very slowly to 19% in 2015. Today it is the country with the largest population of infected persons, estimated at 7 million. Up to the early 1990s, adult mortality in the country decreased steadily, but then surged to more than 500 deaths before age 60 per 1,000 individuals aged 15 (Figure 10). The continued spread of the epidemic in southern Africa until recent years explains why some countries in the region have still not returned to their 1990 levels of adult mortality (Figure 9). In East Africa, prevalence in a number of countries also rose above 5% (Kenya, Mozambique, Rwanda, Tanzania, Uganda), but these countries controlled the epidemic more rapidly. Uganda, for example, reached its peak prevalence in 1991 (13%) but the probability of dying between ages 15 and 60 in the country has decreased by more than a third since 1990 (United Nations, 2015). This is also the case in Ethiopia, Rwanda, Tanzania and Zambia. Overall, prevalence has already peaked in almost all countries, but it remains high in southern Africa. With the increasing use of antiretroviral treatments, a growing proportion of the HIV-positive population survives for longer, which partly explains this persistence.

114Although the proportion of AIDS deaths has been smaller in West and Central Africa, the disease has also disrupted mortality trends in a number of countries in these regions, such as Burkina Faso, Cameroon, Côte d’Ivoire and Nigeria. Figure 10 presents the cases of Nigeria and Burkina Faso. In Nigeria, around 3.4 million individuals are currently infected with the virus; this is the second-largest HIV-positive population in the world, after South Africa. [52] The prevalence of the virus in the country reached 4% of the adult population around 2001, its highest level, and has subsequently remained above 3% (Mahy et al., 2014). According to United Nations estimates, adult mortality in the country increased slowly up to the period 2000-2005, before dropping off slightly. In Burkina Faso, HIV prevalence among adults peaked at 3.8% in 1993, and since 2012 it has fallen to below 1%. Between 1998 and 2001, AIDS caused more than 14,000 deaths in the country each year, i.e. around one in 12, whereas today it causes only one in 50. [53] As in other countries, this improvement can be attributed to a combination of favourable factors, principally a decrease in high-risk sexual behaviours following prevention campaigns, and the scale-up of antiretroviral treatments beginning in 2005.

115In 2000, only around 200,000 persons infected by the virus had access to these treatments in low- and middle-income countries, most of them outside sub-Saharan Africa (Brazil, Thailand). But the resources devoted to persons living with HIV in those countries were subsequently increased more than four-fold – from 4.8 billion dollars in 2000 to 20.2 billion in 2014 – notably thanks to international initiatives such as the PEPFAR programme [54] (Bendavid et al., 2012) and the Global Fund to Fight AIDS, Tuberculosis and Malaria (UNAIDS, 2015). In 2014, antiretroviral coverage in low- and middle-income countries was 40%, with a total of 13.6 million persons receiving treatment. The latest WHO treatment recommendations, from 2015, stipulate that all HIV-infected individuals should begin treatment as quickly as possible following diagnosis. It is thus more crucial than ever not only to ensure universal treatment, but also to expand HIV testing. According to UNAIDS, in 2014 only 54% of infected persons knew that they were HIV-positive (UNAIDS, 2015), and knowledge varied by age, sex, and level of poverty. A recent survey in Mozambique showed that 61% of HIV-positive individuals were unaware of their status, and that this proportion was highest among men and members of poorer households (Dokubo et al., 2014). These persons cannot be reached or treated by the healthcare services, and expose their partners to the risk of infection.

Spatial inequalities in adult mortality in countries affected by HIV/AIDS

124The AIDS epidemic has redefined spatial inequalities in mortality in countries where prevalence is high. It was determined at an early stage that HIV does not evolve at the same rate in different residential environments, due to the greater frequency of risk behaviours in the city. For this reason, the monitoring of these epidemics, initially structured around HIV tests in prenatal clinics, now distinguishes between rural and urban settings. The inclusion of HIV tests in general population surveys has confirmed that HIV prevalence is higher in urban areas. For example, García-Calleja and colleagues (2006) analysed 20 surveys carried out in sub-Saharan Africa, and showed that in half of them, the urban-rural prevalence ratio was above 1.7. More recently, it has been shown that in some countries, such as Namibia, there are few differences between residential environments, but large inequalities between regions (Mahy et al., 2014). In recent years, a number of countries, such as Mozambique and Nigeria, have monitored the epidemic at the sub-national level, revealing wide spatial heterogeneity. In 12 countries of sub-Saharan Africa where provincial-level data on HIV prevalence are available, the ratio between the highest and lowest prevalences is above 5 (UNAIDS, 2013).