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Background: Over the last fifty years the world has seen enormous decline in mortality rates. However, in low-income countries, where vital registration systems are absent, mortality statistics are not easily available. The recent economic growth of Ethiopia and the parallel large scale healthcare investments make investigating mortality figures worthwhile. Methods: Longitudinal health and demographic surveillance data collected from September 11, 2009 to September 10, 2012 were analysed. We computed incidence of mortality, overall and stratified by background variables. Poisson regression was used to test for a linear trend in the standardized mortality rates. Cox-regression analysis was used to identify predictors of mortality. Households located at <2300 meter and ≥2300 meter altitude were defined to be midland and highland, respectively. Results: An open cohort, with a baseline population of 66,438 individuals, was followed for three years to generate 194,083 person-years of observation. The crude mortality rate was 4.04 (95% CI: 3.77, 4.34) per 1,000 person-years. During the follow-up period, incidence of mortality significantly declined among under five (P<0.001) and 5-14 years old (P<0.001), whereas it increased among 65 years and above (P<0.001). Adjusted for other covariates, mortality was higher in males (hazard ratio (HR) = 1.42, 95% CI: 1.22, 1.66), rural population (HR = 1.74, 95% CI: 1.32, 2.31), highland (HR = 1.20, 95% CI: 1.03, 1.40) and among those widowed (HR = 2.25, 95% CI: 1.81, 2.80) and divorced (HR = 1.80, 95% CI: 1.30, 2.48). Conclusions: Overall mortality rate was low. The level and patterns of mortality indicate changes in the epidemiology of major causes of death. Certain population groups had significantly higher mortality rates and further research is warranted to identify causes of higher mortality in those groups. © 2014 Weldearegawi et al.
This study used data generated by the KA-HDSS, which is a longitudinal population-based surveillance system. The KA-HDSS, member of the INDEPTH Network [14], is located about 802 km North of Addis Ababa, the capital of Ethiopia. Nine rural and one urban Kebele (smallest administrative unit in Ethiopia with average population of 5,000) were selected using the probability proportional to size technique (Figure 1). Agro-climatic condition, rural-urban composition, geographic location (highland and midland) and disease burden considerations were made during selection of study villages. The cohort was established with baseline data from 66,438 individuals living in 14,453 households. All households in the selected Kebeles and all individuals in these households were included in the follow-up that was done twice in a year through house-to-house visit. During each visit, vital event information on pregnancy status, birth, cause of death with verbal autopsy [15], marital status change, and migrations were collected. Full time data collectors, who at least completed high school, were recruited from the surveillance kebeles. They were trained for five days on data collection tools, interviewing techniques and ethical conduct of research using standard field manual. Besides, they were provided with refresher training biannually. The data collection process was supervised by field supervisors, a field coordinator and the research team. To link event histories, a permanent unique identification number (ID) was given for each individual and household that ever entered the cohort. To avoid incorrect attribution of data, household and individual ID were neither given to another individual or household nor changed over time. The surveillance employed standard data collection tools and procedures adopted from the INDEPTH Network [14]. Geographic location data were also collected at household level. Households located at <2300 meter and ≥2300 meter altitude were defined to be a midland and highland, respectively [16]. All study households had access to primary health care facilities (with in 5 km distance), that provide free maternal and child health services. At kebele level, there are two Health Extension Workers (HEWs) who are responsible for health promotion, prevention and treatment of common illnesses. The KA-HDSS uses the Household Registration System (HRS version 2.1) FoxPro database. Data analysis was done using STATA 11. Incidence of mortality was calculated by dividing number of deaths in a given group or time period by the total sum of person-time in the specific group or time period. Person-time of observation was determined as the difference between a subject's end date and start date of follow-up. The total person-time was split by year and age-category to calculate mortality rates by age and by year. Cox proportional hazards regression model were used to estimate hazard ratios and corresponding 95% confidence intervals. Poisson regression was used to test for a linear trend in the standardized mortality rates. This paper is based on three years surveillance data, from September 11, 2009 to September 10, 2012. The KA-HDSS received ethical clearance from the Ethiopian Science and Technology Agency with identification number IERC 0030. Ethical approval, with reference number ERC 0377/2014, was also obtained from the Health Research Ethics Review Committee (HRERC) of Mekelle University. To capture occurrence of vital events to any family member, head of a family or an eligible adult among the family was interviewed. Therefore, informed verbal consent was obtained from head of the family or eligible adult among the family, rather than each subject. This consent procedure was stated in the proposal which was approved by the ethical review committee. To keep confidentiality, data containing personal identifiers of subjects were not shared to third party.
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