A comparison of all-cause and cause-specific mortality by household socioeconomic status across seven INDEPTH network health and demographic surveillance systems in sub-Saharan Africa.

BACKGROUND: Understanding socioeconomic disparities in all-cause and cause-specific mortality can help inform prevention and treatment strategies. OBJECTIVES: To quantify cause-specific mortality rates by socioeconomic status across seven health and demographic surveillance systems (HDSS) in five countries (Ethiopia, Kenya, Malawi, Mozambique, and Nigeria) in the INDEPTH Network in sub-Saharan Africa. METHODS: We linked demographic residence data with household survey data containing living standards and education information we used to create a poverty index. Person-years lived and deaths between 2003 and 2016 (periods varied by HDSS) were stratified in each HDSS by age, sex, year, and number of deprivations on the poverty index (0-8). Causes of death were assigned to each death using the InterVA-4 model based on responses to verbal autopsy questionnaires. We estimated rate ratios between socioeconomic groups (2-4 and 5-8 deprivations on our poverty index compared to 0-2 deprivations) for specific causes of death and calculated life expectancy for the deprivation groups. RESULTS: Our pooled data contained almost 3.5 million person-years of observation and 25,038 deaths. All-cause mortality rates were higher among people in households with 5-8 deprivations on our poverty index compared to 0-2 deprivations, controlling for age, sex, and year (rate ratios ranged 1.42 to 2.06 across HDSS sites). The poorest group had consistently higher death rates in communicable, maternal, neonatal, and nutritional conditions (rate ratios ranged 1.34-4.05) and for non-communicable diseases in several sites (1.14-1.93). The disparities in mortality between 5-8 deprivation groups and 0-2 deprivation groups led to lower life expectancy in the higher-deprivation groups by six years in all sites and more than 10 years in five sites. CONCLUSIONS: We show large disparities in mortality on the basis of socioeconomic status across seven HDSS in sub-Saharan Africa due to disparities in communicable disease mortality and from non-communicable diseases in some sites. Life expectancy gaps between socioeconomic groups within sites were similar to the gaps between high-income and lower-middle-income countries. Prevention and treatment efforts can benefit from understanding subpopulations facing higher mortality from specific conditions.

A 10 year study of the cause of death in children under 15 years in Manhiça, Mozambique.

BACKGROUND: Approximately 46 million of the estimated 60 million deaths that occur in the world each year take place in developing countries. Further, this mortality is highest in Sub-Saharan Africa, although causes of mortality in this region are not well documented. The objective of this study is to describe the most frequent causes of mortality in children under 15 years of age in the demographic surveillance area of the Manhiça Health Research Centre, between 1997 and 2006, using the verbal autopsy tool. METHODS: Verbal autopsy interviews for causes of death in children began in 1997. Each questionnaire was reviewed independently by three physicians with experience in tropical paediatrics, who assigned the cause of death according to the International Classification of Diseases (ICD-10). Each medical doctor attributed a minimum of one and a maximum of 2 causes. A final diagnosis is reached when at least two physicians agreed on the cause of death. RESULTS: From January 1997 to December 2006, 568,499 person-year at risk (pyrs) and 10,037 deaths were recorded in the Manhiça DSS. 3,730 deaths with 246,658 pyrs were recorded for children under 15 years of age. Verbal autopsy interviews were conducted on 3,002 (80.4%) of these deaths. 73.6% of deaths were attributed to communicable diseases, non-communicable diseases accounted for 9.5% of the defined causes of death, and injuries for 3.9% of causes of deaths. Malaria was the single largest cause, accounting for 21.8% of cases. Pneumonia with 9.8% was the second leading cause of death, followed by HIV/AIDS (8.3%) and diarrhoeal diseases with 8%. CONCLUSION: The results of this study stand out the big challenges that lie ahead in the fight against infectious diseases in the study area. The pattern of childhood mortality in Manhiça area is typical of developing countries where malaria, pneumonia and HIV/AIDS are important causes of death.

Levels and trends of demographic indices in southern rural Mozambique: evidence from demographic surveillance in Manhiça district.

BACKGROUND: In Mozambique most of demographic data are obtained using census or sample survey including indirect estimations. A method of collecting longitudinal demographic data was introduced in southern Mozambique since 1996 (DSS -Demographic Surveillance System in Manhiça district, Maputo province), but the extent to which it yields demographic measures that are typical of southern rural Mozambique has not been evaluated yet. METHODS: Data from the DSS were used to estimate the levels and trends of fertility, mortality and migration in Manhiça, between 1998 and 2005. The estimates from Manhiça were compared with estimates from Maputo province using the 1997 National census and 1997 Demographic and Health Survey (DHS). The DHS data were used to estimate levels and trends of adult mortality using the siblings' histories and the orphanhood methods. RESULTS: The populations in Manhiça and in Maputo province are young (44% <15 years in Manhiça and 42% in Maputo); with reduced adult males when compared to females (all ages sex ratio of 78.7 in Manhiça and 89 in Maputo). Fertility in Manhiça is at a similar level as in Maputo province and has remained around 5 children per woman, during the eight years of surveillance in Manhiça. Although the infant mortality rate (IMR) in Mozambique has decreased during the last two decades (from 148 deaths per 1000 live births in 1980 to 101 in 2003), it has remained stable around 80 in Manhiça during the surveillance period. Adult mortality has increased both in Manhiça (probability of dying from ages 15 to 60 increased from 0.4 in 1998 to 0.6 in 2005 in Manhiça, from 0.3 in 1992 to 0.4 in 1997 in Maputo province and from 0.1 in 1980 to 0.6 in 2000 in Mozambique). Consequently, the life expectancy decreased from 53 to 46 in Manhiça and from 42 years in 1997 to 38 in 2004 in Mozambique. Migration is high in Manhiça but tends to stabilise after the movements of resettlement that followed the end of the civil war in 1992. CONCLUSION: The population under demographic surveillance in Manhiça district presents characteristics that are typical of southern rural Mozambique, with predominance of young people and reduction of adult males. Labour migration and excess adult male mortality are the major factors for the reduction of adult males. Mortality is high and only infant mortality has started to stabilise while adult mortality has increased, and as consequence, life expectancy has decreased. The Manhiça DSS is an adequate tool to report demographic measures for southern rural Mozambique.