EARLY CHILDHOOD MORTALITY ESTIMATES FOR 7 PROVINCES IN AFGHANISTAN
MSc. Rogelio Eduardo Fernandez Menjivar (Cedeplar) PhD. Rogelio Eduardo Fernandez Castilla (UNCa) PhD. Ricardo Neupert (Independent Consultant)
Abstract
As pointed out in an earlier SDES report on early childhood mortality (CSO and UNFPA), after about three decades of war that devastated the institutions and infrastructure, the Afghanistan’s health system went through a remarkable reconstruction process since 2001. Sustained Government efforts, supported by the international community, brought about relevant improvements in health care indicators, clearly documented in the results of successive data collection surveys like the Multiple Indicator Cluster Survey (Central Statistics Organization (CSO) and UNICEF, 2012), the Afghanistan Mortality Survey (APHI/MoPH, Central Statistics Organization, ICF Macro, Indian Institute of Health Management Research, World Health Organization Regional Office for the Eastern Mediterranean (WHO/EMRO), 2011), the National Risk and Vulnerability Assessment Survey (Central Statistics Organization, 2014), The Afghanistan Demographic and Health Survey 2015 (Central Statistics Organization (CSO) Ministry of Public Health (MoPH), and ICF), and also the estimates from the United Nations Population Division (2017). The evidence emanating from the SDES programme confirmed the declining trend in infant and child mortality, and further enriched the knowledge base by providing more detail evidence for lower level geographic disaggregation, as showed in the results of this report as well as the previous one.
INFANT AND UNDER-FIVE MORTATILITY LEVELS AND TRENDS:
After about three decades of war that devastated the institutions and infrastructure, Afghanistan’s health system went through a remarkable reconstruction process since 2001. Sustained Government efforts, supported by the international community, brought about relevant improvements in the health care indicators, clearly documented in the results of successive data collection surveys like the Multiple Indicator Cluster Survey (Central Statistics Organization (CSO) and UNICEF, 2012), the Afghanistan Mortality Survey (APHI/MoPH, Central Statistics Organization, ICF Macro, Indian Institute of Health Management Research, World Health Organization Regional Office for the Eastern Mediterranean (WHO/EMRO), 2011), the National Risk and Vulnerability Assessment Survey (Central Statistics Organization, 2014), The Afghanistan Demographic and Health Survey 2015 (Central Statistics Organization (CSO) Ministry of Public Health (MoPH), and ICF), and also the estimates from the (United Nations Population Division). The evidence emanating from the Socio Demographic and Economic Survey (SDES) programme confirmed the declining trend in infant and child mortality, and further enriched the knowledge base by providing more detailed evidence for lower level geographic disaggregation, as showed in the results of this report. The Basic Package of Health Services (BPHS) and the Essential Package of Hospital Services (EPHS) are some of the Government of the Islamic Republic of Afghanistan (GoIRA) efforts which have contributed to expand access to health services. These policy instruments contributed to reduce infant and child mortality, a progress that was documented in the MDG1 review process in Afghanistan (Ministry of Economy - GoIRA) and (Government of the Islamic Republic of Afghanistan). One of the main health targets stated in MDG four, was reducing the level of under-five mortality by two thirds by year 2015 as compared to the 1990´s level. Under-five mortality remains the focus of the post-2015 MDG agenda, particularly in the newly adopted Sustainable Development Goals (SDGs) (United Ntions Department
1In September 2000, world leaders met at the United Nations Headquarters in New York for the United Nations Millennium Declaration. The main outcome of this meeting was the Millennium Development Goals (MDGs), a document containing a set of eight time-bound anti-poverty targets which countries pledged to achieve by 2015.
of Economic and Social Affairs)2. Two indicators are used to monitor the MDGs and SDGs targets: a) the infant mortality rate (or probability of dying before the first birthday) and the under-five mortality rate (or probability of dying before the fifth birthday). These two indicators constitute the specific subject of this thematic report: Since under-five mortality rate incorporates infant mortality, most of the analysis done here will focus on the first one.
The level of early childhood mortality and infant mortality are
essentially health indicators. Moreover, they also express the quality of life
and the level of social development of a country. Therefore, national governments and the international community consider as a high priority to estimating their level and monitoring its changes.
Echoing the high priority given to measuring and reporting on the level of early childhood mortality and infant mortality, as well as their trends over time, a number of statistical operations in Afghanistan have included instruments to collect information to calculate infant mortality (1q0) and under-five mortality (5q0). On this basis the GoIRA reported consistent progress in mortality reduction, as registered by these two indicators.
In fact, the GoIRA considered 2003 as a base year, with an under-five mortality rate of 257 deaths per 1,000 live births; the rate recorded for 2012 was 102 deaths per 1,000 live births, revealing a 60% reduction. The targets set for 2015 of 85, and 65 for 2020, are considered achievable. Regarding infant mortality rate, it was estimated to be 165 deaths per 1,000 live births during the base year (2003) and it was reduced to 74 per 1,000 live births by 2012. The targets set for 2015 of 60 and 45 for 2020 are also regarded as attainable (Government of the Islamic Republic of Afghanistan) It is important to mention that according to the Afghanistan Demographic and Health Survey, conducted in 2015, for the period 2011-2015, under-five mortality was 55 deaths per 1,000 live births and infant mortality was 45 deaths per 1,000 live births (Central Statistics Organization (CSO) Ministry of Public Health (MoPH), and ICF). If these rates are deemed as reliable, there is no doubt
2 The target in this new agenda regarding under-five, mortality is to reduce it at least 25 per 1,000 live births by 2030.
that the GoIRA is achieving the planned under-five and infant mortality reduction targets.
As suggested above, for a long period of time, up to the first years of the previous decade, conflict and instability prevented a systematic statistical data collection in Afghanistan. Several surveys were conducted as statistical operations resumed. Table 1 shows infant mortality estimates, 1q0, and under-five mortality estimates, 5q0, according to different sources and for different periods. Although estimates differ according to the source, all of them show a clear declining trend. Figure 1 presents the under-five mortality rates according to the sources shown in Table 1. As expected, although the level estimated by each survey differs, all of them, independently, show a declining trend. Differences are likely to be the result of different sampling and data collection methods, but also due to limitations of the sample’s representativeness imposed by access restrictions in some areas because of security issues. However, notice that the entire set of estimates indicates a declining trend. Figure 1 shows a scatter plot that includes all the estimates. A straight line was fitted by minimum squares to this complete set of 5q0 estimates, which clearly shows a declining trend. The respective equation of the straight line is y = -0.92x+1932. The slope of this equation (or “b” parameter) indicates an annual decline of 0.92 in the under-five mortality level.
This data indicates that children were benefiting from improved health care and access to vaccinations for diseases such as measles, polio and tetanus, which had been expanding in the country since 2001. It is also relevant to repeat the importance of the Basic Package of Health Services (BPHS) and the Essential Package of Hospital Services (EPHS) implemented by the GoIRA), which have contributed to expand access to health services.
Although it is encouraging to see that indicators reveal significant progress, mortality levels are still very high in the country. Program efforts must be maintained and strengthened. In addition, considering that survey data currently constitute the source that can provide most reliable and complete estimates, further analysis of existing data, with more detailed exploration of differentials by relevant socio economic and ethnic classifications should be encouraged.
These analysis can reveal valuable information for targeting priority groups and guiding more focused interventions to accelerate mortality reduction. The main objective of this report is to contribute in this regard by exploring differentials according to level of education, place of residence (urban/rural) and socio-economic status as expressed through quintiles of wealth indexes (constructed on the basis of household assets as reported in the SDES surveys for the seven provinces studied in the present thematic report).
SDES MORTALITY DATA AND ESTIMATION METHODOLOGY:
The indirect estimation method utilized in this report was developed by William Brass (Brass). It requires information of women’s age within five-year age groups, the number of live-born children they have ever had, and the number of those children who have died. The SDES provides this data. The proportion of children dead by age of their mother is clearly a mortality indicator, while not a conventional life table one. Hence, Brass’ method consists in transforming this proportion into a conventional life table indicator. Also, these procedures allow estimating the time location corresponding to the age specific probabilities of dying; this is done by setting up time series that give the evolution of the mortality levels in a period of time preceding the survey or census.
This indirect estimation method has been used for more than five decades. Results are usually accurate if attention is paid to the formal demographic structure of the data and to the logic of the estimation procedure (Statistical Institute for Asia and the Pacific). The method is based on a set of assumptions, which must be taken into account to avoid erroneous interpretations of the results that are obtained. Indeed, estimates obtained in this report through this method, are subject to important assumptions the most relevant of which are: a) changes in early childhood mortality in the recent past have been gradual and unidirectional (no ups and downs in mortality levels have occurred); b) there is no relationship between mother´s age and the mortality risks of children; c) there is no correlation between the survival of mothers and the mortality risks of children, and d) the age pattern of fertility
and the age pattern of child mortality are adequately described by the models utilized in the application of the method (Moultrie, Dorrington and Hill).
RESEARCH FINDINGS:
The results of the application of the Brass indirect method to the SDES data are shown in Table 2 and in the first graph in Figure 2. As mentioned above, this method translates the proportion of children dead among all those ever born alive to women by five-year age groups from 15-19 to 45-49 into probabilities of dying from birth to an exact age n, or nq0. The initial nq0 results (with n=1, 2, 3, 5, 10, 15 and 20) have been translated, by using model life tables, into a common indicator of under-five mortality (5q0 x 1000), in order to facilitate the analysis of trends over time.
Table 2 and Graph A in Figure 2 shows certain traits, which are characteristic for this methodology. The first issue is that the estimates for the two most recent years show higher probabilities of death than the estimates for previous years. The same trend can be observed among the other provinces (see Table 1 and Figure 1, Graph A). This is not due to any recent increase in the level of mortality. The problem is that the estimates of nq0 derived from information about children ever born to women 15-19 and to a less extent, 20-24 (that is 1q0 and 2q0) represent selective groups. They correspond to children born to very young women who have a high proportion of first order births. Moreover, all higher order births within these two groups are associated with short birth intervals and repeated deliveries from very young women. These factors considerably increase the risks of dying both to mothers and children in these categories. Therefore, the higher child mortality levels related to mothers in the two youngest groups do not represent the average child mortality in the provinces. Reports on survivorship of children born to women at ages after 25 years, include a broader combination of birth orders and mother's ages. Consequently, reports from groups older than 25 years are a more adequate representation of the overall risks prevailing in the population, thus providing acceptable estimates of the overall under-five mortality affecting children in these provinces.
A second issue often affecting estimates calculated with this method is underestimation of the mortality level (nq0) obtained from reports of older
mothers (age group 45-49, and sometimes 40-44). This is usually the result of underreporting of dead children, which is likely to be caused by memory failure in older groups, that is, not declaring children who had died several years before the interview.
The distortions affecting the estimates obtained from mothers in groups 15-19 and 20-24 are of a different nature as compared to the errors affecting information from the age group 45-49. The estimates obtained from the 15-19 and 20-24 age groups are measuring actual risks, prevailing in a selected
group, which is that of children born to very young mothers. If these mothers
have born more than one child, those children are substantially affected by considerably higher risks. Thus, it is expected that the first two points in the time series estimates (which correspond to the younger mothers) systematically show higher mortality level than the overall trend. On the other hand, underreported infant and child mortality are often observed in estimates obtained from reports of the oldest groups, especially in the last one, 45-49 years.
Due to the factors affecting estimates from group 15-19 and 20-24 on the one hand and 45-49 on the other hand, the estimates calculated from these reports were adjusted, using minimum squares line fitted to the rest of the point estimates. This procedure was done to assess the annual decline in the under-five mortality values. Such a decline is given by the slope of the adjusted lineal trend. In Table 2, this value is indicated by the “b” parameter. The adjusted under-five mortality rates (5q0) calculated using this approach are also presented in Table 2. Graph B in Figure 2 shows the straight lines corresponding to the adjusted rates. Hence, the adjusted lineal trend was used to estimate the most probable value for the 5q0 in the most recent dates as well as in the initial dates of the time interval covered by the set of 5q0 estimated from this methodology.
Taking into account the previous considerations, it is apparent that the results of six out of the seven provinces observed in Graph B of Figure 2 show higher levels of 5q0 at the beginning of the period analysed (around 2002 or a little earlier), and that mortality has been consistently declining during the last 10 to 15 years, reaching lower levels by the end of this period (around 2015). The only exception is Badghis, where under-five mortality has
increase from 98 in 2003 to 112 in 2016. The annual increase has been approximately one percent.
The province with the most substantial under-five mortality decline is Samangan, followed by Herat. The decline was significant but little slower in Takhar and Balkh, compared to the two previous provinces. In two provinces the decline can be considered only moderate: Baghlan and Nimroz. Finally, in Badghis mortality rates have experienced an increase.
It is possible to find three different patterns of under-five mortality decline among these seven provinces. There is rapid decline (over -3), in Samangan (-5.2), Takhar (-3.9) and Balkh (-3.4); a moderate decline (around -2) in Baghlan (-2.2) and Nimroz (-1.9); and an increase in mortality trends was observed in Badghis (1.1).
Note that the most rapid decline corresponds to those provinces with the highest rates at the beginning of the period. Thus, all those with the largest decline (over -3) are those with the highest starting 5q0: Samangan (163), Herat (146) Takhar (119) and Balkh (101). Those with moderate decline have a starting rate below 100: Baghlan (81) and Nimroz (83). In places where mortality is high, a rapid initial decline can be expected mainly as the result of increased access of health technology. Programs for the control of infectious diseases, mainly trough vaccines and expanded access to hospital services, as it was the case in Afghanistan since 2001, may have dramatic results. However at lower mortality level, further declines depend not only of access to the health system but also to socioeconomic progress such as, food security, proper sanitation, adequate housing, basic knowledge of personal hygiene, availability of potable water and also the capacity of the health systems and programs to reach the entire population. It is likely that the under-five mortality level reached by Baghlan and Nimroz requires not only health interventions to continue declining, but also social and economic improvements. The case of Badghis is discussed later on.
It is also interesting to examine Figure 3, where all the provinces included in the previous SDES surveys are also considered. The prevalent trend is of declining mortality. In general, the highest the rate, the more rapid the decline has been. It is interesting to note the case of Kabul. It is a typical case. It is the province with the lowest initial rate and also the province that
experienced the slowest decline. There are some exceptions to the general trend such as Bamiyan that had one of the highest rates at the beginning of the period but, contrary to the general trend, improvements were limited.
It is relevant to clarify that the explanation of the past and current mortality level and pace of decline in the provinces depend not only on the initial level of under-five mortality, but also other factors. For example, heavy in-migration is a possible factor associated with the slower mortality decline in Kabul. The method used here relies on retrospective mortality information. Hence, the probable high under-five mortality of in-migrants to Kabul tends to increase the overall mortality in the province. In addition the very intense in-migration into Kabul has increased demand on health infrastructure and despite its expansion, the overall improvement per inhabitant may be less significant than it would have been without migration. Probable overcrowding in some urban sectors may also play a role in deteriorating health and living conditions.
It is also important to examine the overall decline among all the provinces. Figure 4 shows a scattergraph considering the data of all 13 provinces. A straight line was fitted by minimum squares to this complete set of 5q0 estimates; a clear declining trend emerges visibly. The respective equation is at the bottom of the graph. The slope of this equation (or b parameter) indicates an annual under-five mortality decline of -3.04, which indicates an important under-five mortality reduction during the period under study.
In order to provide additional insights to this analysis, Table 3 shows selected indicators of socioeconomic development against the most recent estimate of under-five mortality (around 2016) and the pace of its annual decline during the past 10 to 15 years. Figures 5 and 6 show the respective graphs.
According to the set of graphs in Figure 4 all the indicators of socioeconomic level in the provinces are somewhat related to the level of under-five mortality rate. All the relationships are in the expected direction. Evidently, the trend is far from being a perfect linear one. In some cases the relationship is clearly identifiable such as percentage employment in agriculture, literacy rate and access to skilled antenatal care. As measured by
the correlation coefficient, the relationship of these variables with under-five mortality rate in the seven provinces under consideration is around ±0.80. The respective correlation coefficient corresponding to the other variables is about ±0.70, except for poverty rate which is +0.40. Although the number of cases is limited and the strength of the relationship is not very high, there are little doubts that the level of socioeconomic development of the provinces is a factor that has affected child survival.
Regarding the graphs in Figure 5, the relationships between the socioeconomic variables and annual under-five mortality decline is less evident. First of all, as Badghis is the only province with an under-five mortality increase, it affects the identification of any trend. However, even if Badghis is left out of the scattergraph, trends are too loose or too anomalous to suggest an interpretation. For example, there are three cases where, if Badghis is excluded, some trends can be identified: percentage employment in agriculture, percentage literate and access to skilled antenatal care. One may expect that provinces with high employment in agriculture have experienced a slower decline in under-five mortality rate (rural areas are usually associated to higher mortality than urban areas). However, the respective scattergraph shows the opposite. A similar unexpected trend occurs with regard to access to skilled antenatal care. Provinces with higher percentage of provision of skilled antenatal care have experience a slower decline than provinces with a lower percentage. The same unexpected trend occurs with regard to literacy: provinces with higher literacy rates have experienced a slower decline than provinces with lower rates. It is important to repeat that, in any case, these trends are quite weak.
A detailed analysis of the previous trends goes beyond the aim of this study. However, it is now clearer why Badghis is such as an anomalous case (it is the only province with an increasing under five mortality rate). Table 3 and Figures 5 and 6 indicate that this province has quite poor indicators of socioeconomic development. For example, it has only a 4% of female literacy rate, 9% of births attended by skilled health personnel and only 34% of mothers have access to skilled antenatal care. Calories deficiency is the highest among the seven provinces and also the overall literacy rate. It seems that the low level of development prevalent in this province has prevented it to
benefit from the expansion of health programs and services that benefitted other provinces.
Still, in all provinces there is ample room for under-five mortality reductions. In spite of the recent progress additional efforts are needed to continue improving child survival in the years to come. It is important, however, to point out that substantial child mortality reductions cannot be obtained only through the implementation of health campaigns and the expansion of the health structure (although they are very important). Major improvement can only be reached with improvements in the standard of living of the population throughout social and economic development. The experience of most countries indicates that medical interventions and expansion of health services have not been enough. Only by improving the living standards of large proportions of the population who live in an environment in which major diseases flourish, such as diarrhoea and infections of the respiratory system, substantial progress can be achieved. Technological medical interventions have not been enough (Weeks; Central Statistics Organization); (Rowland; Ministry of Economy - GoIRA).
It is important to finish this section with a methodological clarification. As previously explained, because of the selectivity effect discussed in previous paragraphs, the 5q0 quoted in this text for the most recent dates are not the values from the original estimates, but those 5q0 derived from the linearly adjusted trend. Note also that the lineal adjusted trends render 5q0 values always above those derived from proportions of children dead declared by women in the age groups 45-49. It should be stressed that the set of adjusted 5q0 values in Table 2 represent the most probable level of under-five mortality for each of the dates covered by the time series estimates.
DISCUSSION:
Table 4 and Figure 6 shows sex differentials in under-five mortality levels in each of the seven provinces considered in this report. Taking into account that the purpose here is to show mainly differentials and not trends, the estimates were not adjusted as in previous analyses.
The seven patterns shown in Figure 6 are consistent with the typical patterns of sex differences in mortality observed in most populations: under-five mortality rates are greater among male children than female children. Note also that in each province the trend corresponding to each sex follow approximately parallel lines. Sex differentials do not appear very important in the set of graphs in Figure 7. The reason is the scale that was used. In Table 4 differentials are more visible. Consider for example Baghlan. In the graph, the curves are very close, but differentials are important. For example, in years 2013, 2011, and 2008 the under-five mortality rates among males was 65, 69, and 72, deaths per 1,000 births, respectively while among females 56, 58, and 61 deaths per 1,000 births, respectively. The differentials are more important than what the graph shows, due to the scale used n the axis; in Samangan. Herat, and Nimroz differences are even larger.
Lower female mortality consistently prevails over the whole period, except for some odd results associated with dates corresponding to extreme age groups (particularly 20-24 and 15-19 years), which are not representative of the overall mortality risks in the population, and additionally, they are affected by larger random sampling variations because of the smaller numbers involved. This also tends to be the case of years corresponding to the age group 45-49 years.
In the previous SDES report on child mortality (CSO and UNFPA), where six provinces were included (Bamiyan, Daykundi, Ghor, Kabul, Kapisa and Parwan), results were quite similar: female under-five mortality rates were consistently lower than male rates. The only exception was Ghor, and to some extent Bamiyan, where sex differentials were small, with very close trends lines, sometimes overlapping. Larger sex differences were observed in Kapisa and Parwan, which together with Kabul, register overall parallel mortality trends by sex, with consistently lower female mortality. It is likely that there are potential gender issues in Ghor and Bamiyan that are reducing the usual mortality differentials which benefit women.
In conclusion, the estimated under-five mortality rates by sex present overall reliable patterns, showing some exceptions that should be the subject of more detail analyses, which is beyond the scope of the present and previous reports.
Table 5 show the indirect estimates of under-five mortality rates by urban-rural differences in the seven provinces under study during a period from approximately 2001 to 2016. Figure 8 shows the respective graphs. It is quite clear that Samangan exhibit the largest difference between urban and rural child survival. For example, in years 2012 and 2010 under-five mortality rates in urban areas was 68 and 86 deaths per 1,000 births, respectively, while in rural areas these rates were 122 and 133 deaths per 1,000 births, respectively. Important differences between urban and rural rates can also be observed in Balk, Herat and Takhar, although not as large as in Samangan. Small urban-rural differences are seen in Baghlan, Badghis and Nimroz.
It is interesting to examine whether or not some of the socio-economic variables presented in Table 3 is related to the magnitude of the differential. An obvious starting point would be the variables percentage rural population and percentage employment in agriculture. However, there is no perceptible relationship between the magnitude of the urban-rural differential and those two variables, or any other variable in Table 3. Yet, there is a clear relationship between the annual decline in under-five mortality rate and the magnitude of the differential. Samangan, which has the largest urban-rural differential, also has the most rapid annual decline in under-five mortality rate. Balk, Herat and Takhar also exhibit a rapid annual decline in under-five mortality and a relatively large differential between rural and urban child survival. On the other hand, Baghlan, Nimroz and Badghis show small differentials and the decline of under-five mortality during the period under consideration is quite slow. In Badghis there is even an increase in under-five mortality.
A possible explanation is that in those provinces that have experienced a more rapid and substantial under-five mortality decline, the urban population benefited more than the rural population and that is why the difference between the two areas became larger. Notice, however that the rural and urban curves do not suggest an increase in differences through time. The distances between the lines, except for those corresponding to the youngest ages (which are not reliable) remain relatively constant. Other explanations are also possible, en particular methodological issues or sample variation problems.
In the previous report where six provinces were analyze (Bamiyan, Daykundi, Ghor, Kabul, Kapisa and Parwan) (CSO and UNFPA) three distinct patterns were found. Bamiyan, Ghor and Daykundi presented large differences favouring urban areas. In Kapisa and Parwan differences are small but urban mortality is also lower. Finally, in Kabul urban mortality is higher; the difference is relatively small, but consistently under-five mortality rates in rural areas are slightly below those in Kabul’s urban areas. In this case the relationship between the magnitude of annual under-five mortality decline and the extent of urban-rural difference is not evident. For example Kapisa exhibits the larger annual under-five mortality decline and urban-rural difference is small. In Bamiyan differential is large but the annual decline is relatively modest. A more in-depth analysis should be necessary to provide a convincing explanation of these differences in levels en trends.
In the case of Kabul migration is a possible factor associated to the relative slower mortality decline observed (-0.80). This may also be relevant with respect to the unexpected higher urban under-five mortality. The indirect methods used here rely on retrospective information; it registers the deaths that affected all children born to each informant. When a woman migrates, if she has children she would carry the survivorship experience of all children, declaring them in the place of enumeration, regardless of the place where they might have died. Thus two factors may push under-five mortality up for urban Kabul. First, migrants would settle in urban areas more frequently than in rural; so urban areas would be more affected by past mortality that would be declared in, and attributed to, the present area of residence. Second, the very intense in-migration into Kabul has increased demand on the health infrastructure; hence, in spite of infrastructure expansion, the overall improvement per inhabitant would be less significant than would have happened without migration. Additionally, probable overcrowding in some urban sectors may also play a role in deteriorating the urban health and living conditions.
The analysis for this section is done on the basis of Tables 6 and 7 and Figures 9 and 10, which present the estimated 5q0 time series for three education level groups: “no schooling”, “1 to 6 years” of schooling and “7 or
more years”. The educational level refers to the highest educational level
attainment in the household.
Tables 6 and Figure 9 show the estimated 5q0 indicator by education level. There is substantial fluctuation in the curves representing under-five mortality by each level of education. In most cases, the three curves intersect each other making the interpretation quite difficult. For this reason the data were adjusted by the same approach used in Table 2. The estimates corresponding to the two youngest age groups (15-19 and 20-24) and to the oldest (45-49) were excluded. A straight line was fitted to the rest of the point estimates by using minimum squares. The result of this exercise is presented in Table 7 and Figure 10. This procedure facilitates a clearer interpretation of the data as well as better assessing the annual decline in the under-five mortality level. Mortality decline is given by the slope of the adjusted lineal trend, which is symbolized by “b”. This value is also presented in Table 7. Figure 10 shows the straight lines corresponding to the adjusted rates. As in Table 2, the adjusted lineal trend was used to estimate the most probable value for the 5q0 in the most recent dates as well as in the initial dates of the time interval covered by the set of 5q0 estimated from this methodology.
In four provinces child mortality rates are lowest for the group with the higher educational level (7+ years) (Badghis, Herat, Samangan, and Takhar). In Baghlan the under-five mortality corresponding to this educational level is between no education and 1 to 6 years. In Balk under-five mortality for the group with the highest education starts as having the highest rates but then intersect the other lines and ends having the lowest mortality rates. The case of Nimroz is similar, but the highest education line intersects the other two lines very soon and become the educational group with the lowest mortality rates. In these two cases, the decline in under-five mortality among women with 7+ years schooling is more rapid than the decline among women with no
education or 1 to 6 years. It is interesting to note the case of Badghis. As it
may be remembered, it is the only province where under-five mortality has increased. The respective graph in Figure 10 indicates that, in fact, under-five mortality among women with no education and with 1 to 6 years has increased, but among women with 7+ years it has declined.
There is no consistency in the expected pattern of highest mortality in the group with lowest level of education. In fact, the intermediate education level (1 to 6 years schooling) tends to register higher mortality rates than the group with no education. Notice, however, that in Herat, Nimroz and Takhar under-five mortality rates in the group with 1 to 6 years schooling decline more rapidly than 5q0 rates among women with no education. More in-depth analyses would be necessary to explain some of those unexpected results.
The previous SDES report, where six provinces are analyzed (Bamiyan, Daykundi, Ghor, Kabul, Kapisa and Parwan) (CSO and UNFPA), shows similar results. In general, the time series shows that child mortality rates are lowest for the groups with the higher education level (7+ years). There are exceptions such as Bamiyan and Ghor where children of women in households with the highest educational level do no exhibits the lowest under-five mortality rates. Also, households with the intermediate level of education (1 to 6 years schooling) tend to be affected by higher under-five mortality rates than those in the group with no education.
The analysis of under-five mortality by the highest educational level attainment in the household and by sex of the child is quite relevant because it may reveal clearer patterns and also allows assessing what William Brass called the discipline of demographic data. This idea indicates whether the results follow a regular and expected behaviour, being similar to the usually observed socio-demographic and biological differences in diverse societies. If this is the case, the analyst is reassured that the patterns reflect actual characteristics of the population and not random variations and/or defective data. In other words, beyond the value that the information about child mortality by education level and sex represent for decision making, the disaggregation of the education groups by sex provide additional methodological value: the corroboration of consistencies at more disaggregated level would indicate reliable quality and consistency in the basic data. The level and trend of under-five mortality by education and sex, for each of the seven provinces, are presented in the several graphs in Figures A1.
Within each group of education level, female mortality is always and clearly lower than male mortality for the whole time reference period, except for the two most recent estimates which, as explained before are not reliable (corresponding to age groups 15-19 and 20-24 years). The results of this exercise are as expected and they suggest that the basic data is consistent and reliable. There are, however, two issues that are worth mentioning.
First the difference in under-five mortality has increased in some provinces for some educational levels, while in others it has decreased. For example, in Baghlan, considering the estimates corresponding to age group 45-49 years and that corresponding to 25-29 (the last and the third one) in the educational groups no education and 1-6 year of schooling the distance between the respective curves has diminish indicating a decline in male and female differential in under-five mortality. However, for the educational group
7+ years of schooling the difference has increased. In Herat the situation is
different: The differential has declined in the three educational levels although such a decline has not been substantial. In Nimroz, the differential between male and female mortality has decreased in households with no education, but has increased among those in households with 1-6 years of schooling; it has also increased among those in households with the highest educational level. In general, there are a variety of situations regarding the increase or the decrease of the sex differentials among educational level groups.
Second, the graphs in Figure A1 reveal substantial fluctuations in the lines representing the three educational levels considered. As a result, sex differences in under-five mortality increase and decrease through the time period studied. The reason of these fluctuations appears to be random factors; yet, a more in-depth analysis would be required in order to confirm this assumption. The most relevant feature is that sex differences follow the expected pattern in all provinces, when 5q0 estimates are disaggregated according to highest educational level in the household (female girls have better survival rates than male boys), even when some aspects would need further study.
Regarding the earlier SDES report, which analysed the provinces of Bamiyan, Daykundi, Ghor, Kabul, Kapisa and Parwan (CSO and UNFPA),
results were similar. In general, in all cases, under-five mortality was higher for boys than for girls. There were some exceptions, such as Bamiyan and Ghor, where children of women in households with the highest educational level do not exhibit the lowest under-five mortality rates. Also, women in households with the intermediate level of education (1 to 6 years schooling) tend to show higher under-five mortality rates than the group with no education. There were important fluctuations in the 5q0 curves, revealing changes through time in the differential by sex. As in this report, there is a variety of situations where the patterns are difficult to explain.
An important factor that contributes to child survival in most less developed countries is the household’s economic condition (Rowland, 2003). Table 8 and Figure 11 show the level and trends of under-five mortality for the seven provinces considered in this report by quintiles of wealth.
With variations in the level of 5q0 from one province to another, and from one quintile of wealth to another in the same province, the overall patterns of under-five mortality trends show a clear consistency in most provinces. This is remarkable in the cases of Balkh, Herat and Takhar. There is a clear rank order, with higher mortality in the poorest quintiles. However, in other provinces the curves fluctuate and the expected relationship is not clear. Nevertheless, in all cases the curve corresponding to quintile 5 (the better off) is below the others, indicating that the survival of under-five children is higher in households with the best economic conditions. The most remarkable province in this regard is Samangan. However, the patterns corresponding to the other four quintiles are not consistent. Nimroz exhibits substantial fluctuations among under-five mortality trends corresponding to the five quintiles.
Table 9 shows a somewhat clearer picture. It contains a summary of the results of the previous trends by showing the under-five mortality rates for just two dates (2005 and 2015) within the time reference period of these estimates. The table also presents the annual decline as estimated by the the slope of the adjusted lineal trend (represented by “b”).
As it may be remembered, Badghis is the only province where under-five mortality has increased (see Table 2 and Figure 2). In fact, the under-under-five mortality corresponding to quintiles Q1 to Q4 has increased (both sexes), but the rate corresponding to Q5 (households with the best economic conditions) has declined, but only as a result of the decline among female girls. There is another exception: in Q3, the rate corresponding to male boys has declined, but this decline was not enough as to reduce the 5q0 rate for both sexes.
In the other provinces, under-five mortality has experienced the highest decline in Q3 and, in some cases, in Q4. For example, in Herat the decline has been -6.0 per year in Q3 and Q4. In most provinces under-five mortality in lower wealth quintiles has experienced a more important decline than in the highest quintile (Q5). For example, in Samangan, Q1 has experienced an annual decline of -5.9. It is only surpassed by the rate corresponding to Q4 (-6.4). This pattern appears to be the result of the fact that basic heath interventions such as those implemented by the GoIRA have a more substantial effect in high mortality groups (lower quintiles) that in groups with lower mortality levels -where efforts should be more substantial to achieve similar impact. In other word, is easer to reduce an under-five mortality rate of 120 by 5% per year than a rate of 60 by a similar annual percentage.
Differentials by sex show very consistent patterns (Table 9) of lower mortality for girl children in all wealth quintiles and all provinces. Noticeably, this occurs in all cases without any exception, which is reassuring in terms of data reliability.
In the previous analysis of the provinces of Bamiyan, Daykundi, Ghor, Kabul, Kapisa and Parwan (CSO and UNFPA), results showed similar patterns as in this study. In general, levels and trends by wealth quintiles were consistent in all provinces, with higher mortality in the lower quintiles. There were few exceptions, but the general trend was clear. Sex differentials also favoured females, although with few exceptions. It is also relevant to mention that poorest quintiles have benefitted more for the mortality decline.
In other sections of this report reference have been made to the variation in the mortality risk of children according to the selectivity affecting
the reports of mothers in age groups 15-19 and 20-24 years. The cross tabulation of the proportion of children dead, by age of the mother and by parity of the mother (total children ever born), allow us to assess the effects of these variables on the proportion of children dead for each age group of the mother and parity order.
The information provided by mothers older than 25 years are a reasonable combination of ages and birth orders; hence they provide satisfactory estimates of the overall risk of dying for children ever born to women in those age groups. Information from the first two age groups (15-19 and 20-24) is not satisfactory to estimate the overall mortality risk of children in the entire population. Nevertheless, the examination of these proportions classified by age and parity of mothers at the time of the survey provides important evidence on the risk of dying for children born to women in the younger age groups. It also provides information on how these risks significantly increase when very young women have more than one child. Fernandez-Castilla developed a methodology that facilitates the analysis of the patterns of variation in the proportion of dead children, among the children born to mothers in age group i and parity order n at the time of the survey (represented by D(i,n)), compared to the average proportion of dead children among all children born to mothers in age group i (represented by D(i)). These comparisons show the variations in the level of mortality that affects children born to mothers of different parity order at a given age, as compared to the average mortality level for all children born to mothers in that age group (Fernandez Castilla). This is so because the average time exposure to the risk of dying for children is fairly similar within a given age group of the mother, for different parity orders (or family sizes) achieved by the women at that age.
On this basis, the relative risk for children born to women in age group
i and parity n, represented as RR(i,n), can be calculated by comparing the
risk in the combination of age group i and parity n, D(i,n), to the average risk for all children born to women in age group i, D(i); that is: RR(i,n) = D(i,n) /
The results of those calculations for the seven provinces are presented in the set of graphs that are presented in the Figure 12.
It is important to remember that the numbers represented in the vertical axis of the graphs in Figure 12 are relative risks.This means that points along the line for value “1” in the graph, represent mortality risks similar to the level of mortality that affects all children born to women in that specific age group. Points over the line of value “1” for any given age group of the mother mean that the children born to women who reported having that number of children ever born (say parity “n”)have been affected by mortality risks higher than the average risk for all children born to women in that age group. Hence, a relative risk of 2 means that the children in that parity order have mortality risks twice as high as the average risk corresponding to all children born to women in that age group. For example, in the graph corresponding to Badghis, in Figure 12, the relative risk for parity 4 in the age group 15-19 is approximately 2.7; this means that the relative risk for children of women with parity 4 in age group 15-19 is 2.7 times higher than the average risk for all children born to women 15-19 years old at the time of the survey. Note that relative risk values smaller than 1 should be interpreted with a different approach. For example, 0.5 means that the average mortality in this mother’s age group is twice as high as the mortality observed in this parity order within the age group (or the risk in this parity order is half the average level affecting all children born to women this age group). Hence, relative risks points below value 1 appear more concentrated (closer to one another) in the graphs. However the absolute difference in the risk values can be large. For example, a value of 0.25 is relatively close to 1, but represents an absolute difference four times higher for the average risk as compared to the risk on this particular parity within the age group.
The most important feature seen in graphs shown in Figures 12 is the rapid increase in the relative risks, particularly within younger age groups of the mothers, as the number of children increases. Continuing with the example of Badghis in age group 15-19 the mortality risk for children of mothers who have had only one child are lower than the average risk. Instead, children born to 15-19 year old women who have had 4 children are
affected by risks which are 2.7 times higher than the average for the group (more than 5 times higher than the children of women who have had only one child). If the age group 25-29 is considered, children born to women of parity 9 have mortality risks almost 5 times higher than the average risk for all children born to women aged 25-29, and more than 10 times higher than children born to 25-29 year old women who have had only one child.
The lines in the graphs in Figures 12 decline as the age of the women increases. However, this should not be considered as declining mortality levels for older age group of the mothers. If the analysis of mortality trends conducted in previous sections is taken into account, it should be remembered that mortality was higher in the past. The mortality estimates for past dates were derived from reports from the older age groups, thus in absolute terms, the mortality rates derived from information pertaining older age groups are in fact higher than those corresponding to younger ages of women, which correspond to more recent dates in time. Mortality levels are higher, but relative risks by parity order are closer to the average risks. The fact that at older ages the differences in the relative risks are less remarkable is due to a broader combination of experiences among women of older ages. A very young woman can only attain a high parity order by starting reproduction earlier and having children in a close succession. A child age motherhood or early motherhood imply higher risks; if in addition there are several children delivered at short birth intervals the risks increase exponentially. And this is the only possibility for adolescents or young women who have several children. On the other hand, older women can reach high parity orders without necessarily starting too early or having too short birth intervals; additionally, the starting age at childbearing and the birth spacing may not be very different for women who by age 34 have had 4, 5 or 6 children. Hence, although the differential risks are present when higher parities are achieved at a given age, these differences are less important at older ages.
The evidence from these analyses is highly relevant for health and population policies, particularly the situation in the younger groups: 15-19 and 20-24. The consequences of very early marriage and childbearing have been
singled out as an objectionable situation from a viewpoint of human rights as well as gender equity and reproductive health (UNFPA) (WHO). As it is clear from the graphs in Figure 12, the reproductive risks by age of the mother and total children ever born repeat themselves in very similar ways in all provinces. Hence, these factors must be taken into account, to strengthen the relevance of developing culturally sensitive policies directed to increase the age at marriage, avoiding child marriages and early marriages, and encouraging the delay of childbearing to later ages as well as avoiding a rapid progression toward large number of births at young ages.
All those issues examined in the previous paragraph are consistent with a national goal to improve the human capital of the society, preparing the young generations for a transition to lower fertility levels, and encourage, at the same time, higher educational attainments. These goals are clearly incorporated in the Afghanistan National Peace and Development Framework (ANPDF) 2017-2021 (GoIRA), and constitute policy issues that are essential for setting up solid a solid foundation for human development. In due time these would create the conditions for a possible demographic bonus, as the demographic transition evolves to more advanced stages, including favourable population age structures (UNFPA Afghanistan) (UNFPA).
In general, the situation is similar in all provinces. However, in some provinces, as the number of cells increased for wider ranges of parity orders, some of the values in the cells could not be used in the classifications, as they were affected by larger random variations. In some cases probable reporting errors, in the context of few cases in the sample, may have relatively larger impact on the results. However, those random variations do not to affect the substantive conclusions and policy implications. The results obtained in the analysis of these seven provinces are totally consistent with the previous analysis and evidence obtained from earlier six SDES provincial surveys. The general patterns and trends are remarkably similar (see (CSO and UNFPA)),
CONCLUDING REMARKS AND POLICY IMPLICATIONS:
The analysis of the mortality levels affecting children in the early period of life, and of the trends observed during the past decade, conducted in the present report and in a previous one, have rendered overall consistent results. The empirical evidence derived from these studies is a major contribution to enhance the knowledge base regarding the health and socioeconomic conditions in each of the thirteen provinces that have been studied (six in the earlier report and seven in the present one), since they provided a level of disaggregation within each province, that other available sources of data cannot provide. Relevant differentials were identified, which facilitate to shape the epidemiological profile of early mortality risks by sex, urban-rural place of residence, level of education, wealth and age-parity groups within each of these provinces. Hence the data and the analyses conducted on the basis of the SDES program have a huge value for guiding policy interventions, especially by adapting them to local situations.
A variety of studies conducted by different agencies during recent years indicate a clear decline in child mortality. The results presented in this report and in a prior SDES study confirm this decline. Under-five mortality has decline in all provinces considered in the two stages of SDES thematic analyses. There is, however, one exception. Badghis is the only province where under-five mortality does not show evidence of decline, and may have increased, indeed. The main reason appears to be the limited level of socioeconomic development observed in this province. Selected indicators show a meagre situation: extremely low female literacy rate (only 4%) low percentage of births attended by skilled health personnel (9%) and a low percentage of mothers with access to skilled antenatal care (34%). Calories deficiency is the highest among the seven provinces and also the lowest overall literacy rate. It seems that the low level of development prevalent in this province has prevented it to benefit from the expansion of health programs and services that benefitted other provinces.
In spite of the fact that it is evident that a limited development explain the under-five mortality increase in Badghis, the relationship between several
indicators of socioeconomic development and child mortality is not very strong. Although the strength of the relationship is not very high, there are little doubts that the level of socioeconomic development of the provinces is a factor that has affected child survival. Note that this relationship refers to the level of under-five mortality but not to the decline. The most rapid decline corresponds to those provinces with the highest rates at the beginning of the period under consideration. Thus, all provinces with the largest decline are those with the highest starting rates and those with a more modest decline are those with lower initial rates. In countries with high child mortality levels, a rapid initial decline can be expected mainly as the result of increased access of health technology. Programs for the control of infectious diseases, mainly trough vaccines and expanded access to hospital services, as it was the case in Afghanistan since 2001, may have remarkable results. However at lower mortality level, further declines depend not only of access to the health system but also to socioeconomic progress such as, food security, proper sanitation, adequate housing, basic knowledge of personal hygiene, availability of potable water and also the capacity of the health systems and programs to reach the entire population. This evidence would suggest that to sustain a consistent further decline in infant and under five mortality, interventions would need to adjust and incorporate additional interventions to the Basic Package of Health Services (BPHS) and the Essential Package of Hospital Services (EPHS), which have been very successful during the last decade, but would need to adjust interventions to the new scenario. This relationship between the initial level of under-five mortality rates and the magnitude of its decline is also observed in the prior SDES study where six provincial surveys were analysed. Kabul, the province with the lowest initial rate of under-five mortality was the one with the less remarkable child mortality improvement.
In all provinces there is much space for further under-five mortality reductions. In spite of the recent progress stronger and extensive efforts are necessary to continue improving child survival in the years to come. Substantial child mortality reductions beyond the current level would demand adjustments to the interventions that proved very successful during this initial stage of progress. The experience of most countries shows that medical
interventions would need to be strengthened by improving the living standards of populations who are living in environments where major diseases flourish, such as diarrhoea and infections of the respiratory system. Adequate sanitation in congested urban areas would be substantial to bring further progress in such areas.
After analysing the general trends, several differentials were examined: sex, urban-rural residence, mother´s education, household socio-economic conditions and parity.
Regarding sex differentials, the expected pattern of higher male mortality was in general verified, both in the seven provinces studied in this report as well as in the six provinces covered in the previous study. The magnitude of the differentials varies substantially among provinces. These variations could be related socio-economic development in the sense that differential by sex tends to dilute in provinces with lower socio-economic conditions, suggesting that gender issues may affect the relative survival of girl children.
Under-five mortality by rural-urban residence fluctuates substantially among provinces. Samangan exhibit the largest difference between urban and rural child survival. Important differences between urban and rural rates can also be observed in Balk, Herat and Takhar, although not as large as in Samangan. Small urban-rural differences are in Baghlan, Badghis and Nimroz. In the previous SDES study a high differential favouring urban areas was found in Bamiyan and Ghor, and relative little differences in Kapisa, Parwan and Kabul. In Kabul this relative small difference is, surprisingly, in favour of rural areas. The peculiar pattern in Kabul may be related to migration, combined with the characteristics of the methodology utilized (which assign the reported mortality to the place of residence, yet it might have occurred somewhere else), but also may be related to the overcrowding in some urban areas, generated by a very fast urban growth registered during the last 15 to 20 years.
In general, the time series show that child mortality rates are lowest for the groups with the higher education level (7+ years). This is the case in both SDES studies. There are, however, exceptions where women in households
with the highest educational level do no exhibits the lowest under-five mortality rates. Also, women in households with the intermediate level of education (1 to 6 years schooling) tend to show higher under-five mortality rates than the group with no education. These departures from the expected pattern may be related to asymmetries in the distribution of population by level of education. There is high concentration in the lowest educational levels, and in these cases for some groups the low education may be associated with relative higher economic status, which may revert –in some cases- the expected association of low education with higher mortality risks. Since the patterns are very similar in different provinces, it is not likely that they would reflect random variations or misreporting.
The analysis of quintiles of wealth, as indicators of the well-being of the household, shows, variations in the level of under-five mortality from one province to another, and from one quintile of wealth to another in the same province. There is a clear rank order, with higher mortality in the poorest quintiles. This is remarkable in some provinces while in others the curves fluctuate substantially and the expected relationship is not very clear. However, in all cases the 5q0 curve, corresponding to quintile 5, is below all others, indicating that the survival of under-five children is higher in households with the best economic conditions.
Regarding the trend, under-five mortality has experienced the highest decline in Q3 and, in some cases, in Q4. In most provinces, under-five mortality in low quintiles has experienced a more important decline than in the highest quintile (Q5). This pattern seems to be associated to the fact that basic heath interventions such as those implemented by the GoIRA have a more substantial effect in high mortality groups (lower quintiles) that in groups with lower mortality levels where efforts would need incorporate more complex interventions to achieve a comparable impact. Differentials by sex show very consistent patterns (Table 9) of lower mortality for girl children in all wealth quintiles and all provinces. Noticeably, this occurs in all cases without any exception. Results in the previous analysis of six provinces are similar. In general, levels and trends by wealth quintiles are consistent in all provinces, with higher mortality in the lower quintiles. There are few exceptions, but the
general trend is very clear. Sex differentials also favour females. It is relevant to mention that the poorest quintiles have benefitted more from the mortality decline.
The last section of the report examined the variation of mortality according to the total number of children ever born by women in a given age group, using relative risks compared to the average mortality for all children of women in that age group. This type of analysis explore the variation of risks according to reproductive patterns, differentiating between patterns of early age at the onset of reproduction and rapid progression to high parity order, from patterns of moderate progression to higher orders and later starting ages of childbearing. In all provinces the patterns of variation are similar, with remarkable increases in the mortality risks of children from women who reached high parity orders at relative young ages. The implications of these findings for health and population policies are quite relevant, as they reveal the harmful effects of very early reproduction, short birth intervals and rapid progression toward large families. Again, this is a very important contribution that the SDES programme is making to strengthen the body of knowledge that is needed to guide policy formulation and program development to continue reducing child mortality, as well as fine tuning population policy interventions.
BIBLIOGRAPHY
Afghan Public Health Institute (APHI/MoPH), Central Statistics Organization (CSO), ICF Macro, Indian Institute of Health Management Research (IIHMR) [India], and World Health Organization Regional Office for the Eastern Mediterranean. Afghanistan Mortality Survey 2010. Calverton, Maryland, USA, 2011.
Brass, William and Ansley Coale. “Methods of analysis and estimation.” Brass, William, et al. The Demography of Tropical Africa. Princeton NJ: Princeton University Press, 1968. 88-139.
Brass, William. “Uses of census or survey data for the estimation of vital rates.” African Seminar on Vital Statistics,14-19 December. Addis Ababa, 1964.
Central Statistics Organization (CSO) and UNICEF. Afghanistan Multiple Indicator Cluster Survey - MICS. Kabul: Central Statistics Organization and UNICEF, 2012.
Central Statistics Organization (CSO) Ministry of Public Health (MoPH), and ICF. Afghanistan Demographic and Health Survey 2015. Kabul, Afghanistan and and Rockville, Maryland USA: Central Statistics Organization, Ministry of Public Health, and ICF
International, 2017.
Central Statistics Organization. Afghanistan Living Conditions Survey 2013-14. National Risk and Vulnerability Assessment. Kabul: CSO, 2016.
—. National Risk and Vulnerability Assessment 2011-12. Afghanistan Living Condition Survey. Kabul: CSO, 2014.
CSO and UNFPA. Socio-Demografic and Economic Survey: Child Mortality in the Provinces of Kabul, Bamiyan, Daykundi, Ghor, Kapisa and Parwan. Kabul: CSO, 2016.
European Union. National Risk and Vulnerability Assessment 2007/8 - A profile of Afghanistan. Kabul, Afghanistan: ICON-INSTITUTE GmbH & Co. KG Consulting Group, 2009.
Fernandez Castilla, Rogelio. The Influence of Differentials in Child Mortality by Age of the Mother, Birth Order, and Birth Spacing on Indirect Estimation Methods (Ph.D Thesis). London: London School of Hygiene and Tropical Medicine (Unpublished) - University of London, 1985.
GoIRA. Afghanistan National Peace and Development Framework (ANPDF) 2017-2021. Kabul: Government of the Islamic Republic of Afghanistan, 2017.
