Relationship between household socio-economic status and under-five mortality in Rufiji DSS, Tanzania.
BACKGROUND
Disparities in health outcomes between the poor and the better off are increasingly attracting attention from researchers and policy makers. However, policies aimed at reducing inequity need to be based on evidence of their nature, magnitude, and determinants.


OBJECTIVE
The study aims to investigate the relationship between household socio-economic status (SES) and under-five mortality, and to measure health inequality by comparing poorest/least poor quintile mortality rate ratio and the use of a mortality concentration index. It also aims to describe the risk factors associated with under-five mortality at Rufiji Demographic Surveillance Site (RDSS), Tanzania.


METHODS
This analytical cross sectional study included 11,189 children under-five residing in 7,298 households in RDSS in 2005. Principal component analysis was used to construct household SES. Kaplan-Meier survival incidence estimates were used for mortality rates. Health inequality was measured by calculating and comparing mortality rates between the poorest and least poor wealth quintile. We also computed a mortality concentration index. Risk factors of child mortality were assessed using Poisson regression taking into account potential confounders.


RESULTS
Under-five mortality was 26.9 per 1,000 person-years [95% confidence interval (CI) (23.7-30.4)]. The poorest were 2.4 times more likely to die compared to the least poor. Our mortality concentration index [-0.16; 95% CI (-0.24, -0.08)] indicated considerable health inequality. Least poor households had a 52% reduced mortality risk [incidence rate ratio (IRR) = 0.48; 95% CI 0.30-0.80]. Furthermore, children with mothers who had attained secondary education had a 70% reduced risk of dying compared to mothers with no education [IRR = 0.30; 95% CI (0.22-0.88)].


CONCLUSIONS
Household socio-economic inequality and maternal education were associated with under-five mortality in the RDSS. Targeted interventions to address these factors may contribute towards accelerating the reduction of child mortality in rural Tanzania.
National Institute for Occupational Health, Johannesburg, South Africa.
Cornelius
C
Nattey
Honorati
H
Masanja
Kerstin
K
Klipstein-Grobusch
D000367:Age Factors; D046688:Child Mortality; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D004522:Educational Status; D005191:Family Characteristics; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D007223:Infant; D053208:Kaplan-Meier Estimate; D008297:Male; D016012:Poisson Distribution; D011203:Poverty / Q000706:statistics & numerical data; D012307:Risk Factors; D012959:Socioeconomic Factors; D013636:Tanzania / Q000453:epidemiology
inequality; mortality concentration index; principal component analysis; socio-economic status