1 Rural AIDS and Development Action Research Programme, School of Public Health, University of the Witwatersrand, South Africa
2 Clinical Research Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
3 Agincourt Health and Population Unit, School of Public Health, University of the Witwatersrand, South Africa and MRC/Wits Unit in Rural Public Health and Health Transitions Research
4 Graduate Group in Demography, University of Pennsylvania, USA
5 Institute of Behavioral Science, University of Colorado at Boulder, USA
Correspondence: James Hargreaves, Clinical Research Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. E-mail: james.hargreaves{at}lshtm.ac.uk
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Abstract |
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Methods Open prospective cohort of 30 276 children (80 462 person years of follow-up) followed from 1 January 1992 to 31 October 2000 in Limpopo Province, South Africa. Exposure and outcomes data came from the Agincourt Health and Demographic Surveillance System (DSS).
Results There was no difference in infant mortality between children from former Mozambican refugee households and those from South African homes (adjusted rate ratio [RR] = 1.02, 95% CI: 0.79, 1.32), but mortality levels were higher among former Mozambican refugee children during the next 4 years (adjusted RR = 1.91, 95% CI: 1.50, 2.42). Increased mortality levels were also seen among children from larger households and whose mother died, while children born to mothers aged >40 years or with higher education were at lower risk. Measured maternal, household, and health service utilization characteristics could not explain the difference in mortality between children from former Mozambican refugee and South African households. Former Mozambican refugee children residing in refugee settlements had higher mortality rates than those residing in more established villages.
Conclusions This study demonstrates higher childhood, but not infant, mortality rates among children from former Mozambican refugee households compared with those from host South African households in rural South Africa. The lack of legal status and lower wealth of many former Mozambican refugees may partly explain this disparity.
Accepted 13 May 2004
Addressing inequities in health between advantaged and disadvantaged populations constitutes one of the great challenges of the new century.1 Research that describes such inequities and the mechanisms by which they are generated is necessary to inform policies that aim to close health gaps. Internationally displaced people may represent one such disadvantaged group. Refugees may be temporarily settled in camps and a number of studies have described the health status of camp refugees.2,3 However, many of the world's largest refugee populations have been living in host countries for more than 10 years, with significant numbers of self-settled refugees* often staying beyond conflict resolution.4 Local integration culminating in refugees once again acquiring the protection of a state is promoted as a durable solution in such cases but is often slow.5
South Africa's Limpopo Province was a key destination for refugees fleeing the civil war in Mozambique from 1983 onwards. A formal peace agreement was signed in October 1992, yet despite a variety of voluntary repatriation programmes, by 2000 it was estimated that over 220 000 former Mozambican refugees were still resident in the province.6 Our aim in this study was to compare mortality rates during 19922000 among children from former Mozambican refugee and host South African households. Secondly, we aimed to examine whether differences in levels of more proximate household, maternal, and health utilization characteristics could explain any differences in mortality levels found.7 Finally, we wished to examine whether there was a difference in the mortality rate between children from former Mozambican refugee households resident in locally recognized refugee settlements and children from former Mozambican refugee households residing in more established host villages.
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Methods |
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From 1983, Mozambicans fled into South Africa to escape the civil war. They dispersed within local settlements or settled on land allocated to them by local authorities. In 1993, group refugee status was granted to Mozambicans who had fled the conflict, yet access to water, sanitation, and legal rights remained poor for most.10 Following this, a Southern African Development Community (SADC) amnesty during 1996 encouraged Mozambican refugees to apply for permanent South African residency. While many took advantage of this, outreach to rural areas was limited and standards of living remained low in many areas. In 2000, more than a quarter of the population (29%) of the Agincourt sub-district were of Mozambican origin. We have used the term former Mozambican refugee to describe those whose nationality of origin was Mozambican. This term describes the current socio-legal status of the population group who arrived in South Africa from Mozambique before the end of the civil war and settled. However, it should be noted that it does not accurately describe the status of individual household heads during the entire study period.
Data collection and analysis
The Agincourt Demographic and Health Surveillance System (DSS) monitors demographic events and socio-economic variables in the sub-district. Since 1992 there have been eight census rounds in 10 years with each of the approximately 11 500 households visited at each census. The main variables measured annually include births, deaths, in- and out-migrations, household relationships, pattern of residency, nationality, educational attainment, and antenatal and perinatal health-seeking practices.9,11,12 The data model for household membership takes account of high levels of population mobility by including on the household roster non-resident members who retain significant links with the rural home.
During each census a trained fieldworker checks existing individual information for every household member. Births, deaths, and migrations that have occurred since the previous census are recorded. Revisits are undertaken when appropriate respondents are not available. Duplicate visits are made to a random sample of 2% of households and a number of validation checks are built into the fieldwork and data-entry programme.
For this study an open cohort of all children in the first 5 years of life was constructed using data from the DSS. The cohort was followed from 1 January 1992 to 31 October 2000. All individuals who spent time resident in the sub-district during the first 5 years of life were captured by the DSS and were eligible for inclusion in the study. Entry into the cohort could occur at any time during the study period and was captured by entry to the DSS through birth, in-migration, or presence in the baseline census. Exit from the cohort was determined either by exit from the DSS before 5 years of age (through death or out-migration), turning 5 years during the follow-up period, or reaching the end of the follow-up period before the fifth birthday.
The major exposure under investigation was the nationality of origin of the head of the household in which the child resided. Further risk factors for childhood mortality investigated included household factors (sex of household head, number of female adults or children in the household and maternal presence in the home after delivery), maternal socio-demographic factors (age at birth of child and level of education), and health service utilization factors (mother receiving antenatal care and birth in a health facility). Risk factor data was limited to measures that could be calculated from data routinely collected through the DSS and complete data was not available for all children. In our analysis we constructed three groups on the basis of available data. Group 1 children have data available for all household factors. Group 2 children have data available on both household and maternal factors, with missing data primarily a result of inconsistencies in the DSS database that prevented linking a child to the mother. Group 3 children have data available on household and health service utilization factors. Data on health service utilization was only available for children born into the cohort.
Firstly, mortality rates were calculated as the number of deaths per 1000 person years of follow-up (PY). Following this, Poisson regression was used to estimate incidence rate ratios (RR) for mortality over the first year of life and over the next 4 years of life separately since the mortality rates during these two age bands was significantly different.
To identify factors that might explain differences in mortality between children from host and former Mozambican refugee households, the second part of the analysis was conducted with reference to a hierarchical causal framework (Figure 1). The mediating impact of variables lower in the hierarchy was assessed by including the variable nationality of origin of the household head in the regression model first, and then adding potential risk factors that are lower in the framework to the model. Changes in the incidence RR associated with nationality of the household head after inclusion of a potential mediating variable imply that some or all of the effect is due to differentials in risk profiles.13
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RR were adjusted for changes in the childhood mortality rate over the study period. Since some exposure variables were measured at the level of the household, CI have been adjusted to reflect this design effect.
Ethical clearance for the Agincourt DSS is provided by the University of the Witwatersrand Committee for Research on Human Subjects (M960720). Informed consent is obtained verbally each year.
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Results |
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Among group 1 there were 537 deaths over the follow-up period 1 January 1992 to 31 October 2000, occurring at a rate of 6.7 per 1000 PY. Mortality rates were approximately stable over the period 1 January 1992 to 1 January 1996 at 5.3 per 1000 PY. During the period 1 January 1996 to 31 October 2000 the overall mortality rate was also approximately stable at 8.0 per 1000 PY. The mortality rate was higher in the first year of life (16.2 per 1000 PY) than in the next 4 years (4.4 per 1000 PY). There was little difference in the mortality rate between male and female children. The pattern of mortality among the children in group 2 was comparable with group 1. However, the mortality rates in both periods of life was higher among children in group 3 (18.4 per 1000 PY, and 6.3 per 1000 PY respectively).
There was little difference in mortality rates during the first year of life between children from former Mozambican refugee and host South African households (RR = 1.02, from Poisson regression, adjusted for period of follow-up, 95% CI: 0.79, 1.32, Table 1). However, children from Mozambican households experienced a higher mortality rate than their South African counterparts during the next 4 years of life (adjusted RR = 1.91, 95% CI: 1.50, 2.42). The excess mortality among former Mozambican refugee children during this age range was seen during both the period 1 January 19921 January 1996 (adjusted RR = 1.80, 95% CI: 1.23, 2.62) and during the period 1 January 199631 October 2000 (adjusted RR = 1.99, 95% CI: 1.47, 2.70). A similar pattern was seen among groups 2 and 3.
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There was little evidence for a relationship between the sex of the household head and childhood mortality. However, children coming from large families were at greater mortality risk, particularly during the ages 15 years (adjusted RR = 1.90, 95% CI: 1.34, 2.68, comparing households with four or more adult females to those with one).
Almost all mothers had some contact with an antenatal clinic during their pregnancy, while being born in a health facility did not have a significant impact on a child's chance of survival after birth.
There was little change in the RR value associated with coming from a former Mozambican refugee household with the addition to the Poisson regression model of most of the potential risk factors measured in this study (Table 2). Children from former Mozambican refugee households were much less likely to be born in a health facility (14.7% former Mozambican refugee children versus 43.8% South African children) and their mothers were much more likely to have received no formal education (59.7% versus 14.2%). However, the inclusion of the health service delivery variable into the model had almost no effect on the RR associated with coming from a former Mozambican refugee household, while the inclusion of the mothers education variable slightly increased the RR associated with coming from a former Mozambican refugee household on mortality in the next 4 years of life.
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Discussion |
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There are limitations to this analysis. We measured all exposure variables at a single point in each child's life. This approach does not fully capture the complexity of the situation. Changes in situation during childhood (for example, a change in household structure) may also be important in predicting mortality patterns. It is not clear how this might have affected the results we present. We have also measured a relatively limited number of risk factors in this study. Since it is highly unlikely that the mortality differential described in this paper is the result of intrinsic differences between former Mozambican refugee and South African children, they must be mediated by differences in proximate risk factors.7 More detailed research, including data on cause of death, anthropometric measures and nutritional factors, housing quality, or immunization rates might highlight interventions that could improve the health of children born into former Mozambican refugee households. Finally, we did not have complete data on all children which may have resulted in selection bias. Mortality rates were higher among the children on whom data for health service utilization factors were available, all of whom were born into the study cohort. However, the RR associated with coming from a former Mozambican refugee household was comparable in all three groups for both age bands, suggesting a limited impact of selection bias on the relationship under examination in this study.
The overall rate of childhood mortality seen in this study was low compared with many other DSS sites in developing country settings,15 but significantly higher than that seen in most developed country settings.16 The area is experiencing a severe HIV/AIDS epidemic. The prevalence of human immunodeficiency virus (HIV) infection among antenatal clinic attenders in the health region was 19.1% in 1998.17 Previous work from the Agincourt DSS has described the impact of HIV/AIDS on adult mortality,18 and HIV/AIDS may help explain the increased childhood mortality seen during the later period of this study. While migrant populations may be particularly vulnerable to HIV infection,19 isolated populations may also exhibit lower HIV prevalence than roadside or peri-urban areas.20,21 The excess mortality associated with coming from a former Mozambican refugee household was only present during ages 15 years. It is possible that children from host South African households experienced high infant mortality rates if there is a greater burden of HIV among this community. Prolonged breastfeeding among Mozambican mothers may also help explain this pattern. However, in the absence of additional data it is difficult to assess the extent to which HIV/AIDS or breastfeeding practices are responsible for the disparities in childhood mortality reported here.
The inequality in childhood mortality described in this paper may be closely linked to inequalities in wealth. Former Mozambican refugee households generally have a lower standard of living than host South African households. Asset data collected during the 2001 Agincourt DSS census have been used to construct a relative index of household economic status using principal components analysis. Mozambican households were approximately three times more likely to fall in the poorest quintile than South African households. Furthermore, Mozambican households in refugee settlements were over twice as likely to fall in this category than Mozambican households located in mixed villages (unpublished census data). An environmental survey conducted in 1993 also demonstrated that refugee settlements were consistently worse off than mixed villages with respect to access to water, fuel, sanitation, and waste disposal.22 In 2000, refugee settlements still generally had no schools, the quality of housing was poor and they are particularly isolated from public transport.14 Other recent analyses have pointed to child mortality disparities between ethnic groups in 11 countries of sub-Saharan Africa closely linked to economic inequity and differential use of health services.23
The economic vulnerability of many former Mozambican refugees is likely to have been influenced by tenuous legal status over much of the follow-up period. Serious deficiencies in the UNHCR-Mozambique-South Africa tripartite agreement that granted group refugee status to Mozambicans in 1993 meant that it had little effect on the situation on the ground,10 while the 1996 amnesty failed to adequately reach rural areas.6 However, some Mozambicans did get residency papers during the 1990s through a variety of means, with pre-existing social network structures influencing the progress of refugees as they fled into South Africa (personal communication, Fred Golooba-Mutebi 2002). Our analysis suggests that some Mozambican households have fared better in South Africa than others. Further research is needed to explore the link between legal status and childhood mortality among this population.
Two recent policy shifts might have a significant impact on health inequities in this population. In 1999, former Mozambican refugees were again granted the opportunity to apply for permanent residency within South Africa. This regularization process sought to address the shortcomings of previous efforts, and significant attempts at rural outreach were made.6 More recently, in March 2003, a South African High Court order paved the way for former Mozambican refugees to gain access to a range of social assistance grants. The DSS system used in this study is well placed to monitor absolute and relative changes in health status within this population over the coming years.
KEY MESSAGES
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References |
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