1. Estimating cause of adult (15+ years) death using InterVA-4 in a rural district of southern Ghana.
- Author
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Awini E, Sarpong D, Adjei A, Manyeh AK, Amu A, Akweongo P, Adongo P, Kukula V, Odonkor G, Narh S, and Gyapong M
- Subjects
- Adolescent, Adult, Aged, Autopsy, Female, Ghana epidemiology, Humans, Male, Middle Aged, Population Surveillance, Rural Population, Software, Cause of Death, Data Collection methods, Mortality trends
- Abstract
Background: Data needed to estimate causes of death and the pattern of these deaths are scarce in sub-Saharan Africa. Such data are very important for targeting, monitoring, and evaluating health interventions., Objective: To estimate the mortality rate and determine causes of death among adults (aged 15 years and older) in a rural district of southern Ghana, using the InterVA-4 model., Design: Data used were generated from verbal autopsies conducted for registered adult members of the Dodowa Health and Demographic Surveillance System who died between 2006 and 2010. The InterVA-4 model was used to assign the cause of death., Results: Overall, the mortality rate for the period under review was 7.5/1,000 person-years (py) for the general population and 10.4/1,000 py for those aged 15 and older. The leading cause of death was communicable diseases (CDs), with a malaria-specific mortality rate of 1.06/1,000 py. Pulmonary tuberculosis (TB)-specific mortality rate was the next highest (1.01/1,000 py). HIV/AIDS attributed deaths were lower among males than females. Non-communicable diseases (NCDs) contributed to 28.3% of the deaths with cause-specific mortality rate of 2.93/1,000 py. Stroke topped the list with cause-specific mortality rate of 0.69/1,000 py. As expected, young males (15-49 years) contributed to more road traffic accident (RTA) deaths; they had a lower RTA cause-specific mortality rate than older males (50-64 years)., Conclusions: Data indicate that CDs (e.g. malaria and TB) remain the major cause of death with NCDs (e.g. stroke) following closely behind. Verbal autopsy data can provide the causes of mortality in poorly resourced settings where access to timely and accurate data is scarce.
- Published
- 2014
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