Mortality Level and Predictors in a Rural Ethiopian Population: Community Based Longitudinal Study Berhe Weldearegawi 1,2 *, Mark Spigt 1,2 , Yemane Berhane 3 , GeertJan Dinant 2 1 Department of Public Health, College of Health Sciences, Mekelle University, Mekelle, Ethiopia, 2 CAPHRI, School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands, 3 Addis Continental Institute of Public Health, Addis Ababa, Ethiopia Abstract 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. Citation: Weldearegawi B, Spigt M, Berhane Y, Dinant G (2014) Mortality Level and Predictors in a Rural Ethiopian Population: Community Based Longitudinal Study. PLoS ONE 9(3): e93099. doi:10.1371/journal.pone.0093099 Editor: Pierre-Marie Preux, Institute of Neuroepidemiology and Tropical Neurology, France Received October 8, 2013; Accepted March 3, 2014; Published March 27, 2014 Copyright: ß 2014 Weldearegawi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The study was Funded by Centers for Disease Control and Prevention (CDC) through Ethiopian Public Health Association (EPHA) in accordance with the EPHA-CDC Cooperative Agreement No. 5U22/PS022179_05 and Mekelle University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript Competing Interests: The authors have declared that no competing interests exist. * E-mail: [email protected]Introduction Mortality is one of the most important indicators of the health status of a population [1,2]. Mortality statistics stratified by age, sex and the cause of death are of great value for the formulation, implementation and evaluation of public health programs [3]. The presence of well-established civil registration systems enabled developed countries to monitor changes in mortality, determine causes of death and devise appropriate interventions [4]. Yet, vital registration systems are lacking in low-income countries, especially in Sub-Saharan Africa [5]. This hampers the evaluation of the health status of populations and the impact of interventions [5]. Since it is unreasonable to expect an immediate implementation of nationwide population-based registration sys- tems in low-income countries, considering other interim options is important. One way is to select a circumscribed population from which reasonably detailed, complete, and high quality community- based data can be gathered longitudinally, the so called Health and Demographic Surveillance System (HDSS) [6,7]. Typical HDSS populations include at least 60,000 individuals, which is usually sufficient to provide adequate sample sizes to monitor trends in mortality [5]. Ethiopia, the second most populous country in Africa, has implemented an ambitious economic development plan and a twenty-year Health Sector Development Plan (HSDP) to improve access and utilization of health care services [8–10]. Moreover, Ethiopia is undergoing rapid economic growth, urbanization, and change in life-style and nutrition transition [11–13]. Monitoring the effects of these countrywide changes would not only help to understand the Ethiopian situation. It will be very informative to countries who plan to implement similar initiatives, and it will show to the world which changes in mortality we can expect if developing countries are changing. The Kilite Awlaelo HDSS (KA-HDSS) was established in September 2009 to generate population based longitudinal health and demographic informa- tion. This gave us the unique opportunity to investigate the mortality levels, patterns and the predictors of mortality in a predominantly rural low-income population. PLOS ONE | www.plosone.org 1 March 2014 | Volume 9 | Issue 3 | e93099
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Mortality Level and Predictors in a Rural EthiopianPopulation: Community Based Longitudinal StudyBerhe Weldearegawi1,2*, Mark Spigt1,2, Yemane Berhane3, GeertJan Dinant2
1 Department of Public Health, College of Health Sciences, Mekelle University, Mekelle, Ethiopia, 2 CAPHRI, School for Public Health and Primary Care, Maastricht
University, Maastricht, Netherlands, 3 Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
Abstract
Background: Over the last fifty years the world has seen enormous decline in mortality rates. However, in low-incomecountries, where vital registration systems are absent, mortality statistics are not easily available. The recent economicgrowth 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 regressionwas used to test for a linear trend in the standardized mortality rates. Cox-regression analysis was used to identify predictorsof 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 194,083person-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), whereasit 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) andamong 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 ofmajor causes of death. Certain population groups had significantly higher mortality rates and further research is warrantedto identify causes of higher mortality in those groups.
Citation: Weldearegawi B, Spigt M, Berhane Y, Dinant G (2014) Mortality Level and Predictors in a Rural Ethiopian Population: Community Based LongitudinalStudy. PLoS ONE 9(3): e93099. doi:10.1371/journal.pone.0093099
Editor: Pierre-Marie Preux, Institute of Neuroepidemiology and Tropical Neurology, France
Received October 8, 2013; Accepted March 3, 2014; Published March 27, 2014
Copyright: � 2014 Weldearegawi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was Funded by Centers for Disease Control and Prevention (CDC) through Ethiopian Public Health Association (EPHA) in accordance with theEPHA-CDC Cooperative Agreement No. 5U22/PS022179_05 and Mekelle University. The funders had no role in study design, data collection and analysis, decisionto publish, or preparation of the manuscript
Competing Interests: The authors have declared that no competing interests exist.
* P-value represents test for linear trend in stand.ardized rates.Year I: September 11, 2009–september 10, 2010.Year II: September 11, 2010–september 10, 2011.Year III: September 11, 2011–september 10, 2012.doi:10.1371/journal.pone.0093099.t004
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23. Berhane Y, Wall S, Fantahun M, Emmelin A, Mekonnen W, et al. (2008) A
rural Ethiopian population undergoing epidemiological transition over ageneration: Butajira from 1987 to 2004. SJPH 36: 436–441.
24. Preston SH (1980). Causes and Consequences of Mortality Declines in Less
Developed Countries during the Twentieth Century. In: Easterlin RA, (eds)Population and Economic Change in Developing Countries. University of
Chicago Press. p. 289–360.25. Bradley E, Taylor L, Skonieczny M, Curry L (2011) Grand Strategy and Global
Health: The Case of Ethiopia. Global Health Governance, Volume, No. 1 (Fall
2011).26. Central Statistical Agency [Ethiopia] and ICF International (2012) Ethiopia
Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton,Maryland, USA: Central Statistical Agency and ICF International.
27. Tigray Regional Health Bureau (2013) Annual profile 2012/13. Tigray,Ethiopia.
28. Hill K, Amouzou A (2006) Trends in Child Mortality, 1960 to 2000. In: Jamison
DT, Feachem RG, Makgoba MW (eds). Disease and Mortality in Sub-SaharanAfrica. 2nd edn. Washington (DC): World Bank Chapter 3.
29. Bradshow D, Timaues I (2006) Levels and trends of adult mortality, 1960 to2000. In: Jamison DT, Feachem RG, Makgoba MW (eds). Disease and
Mortality in Sub-Saharan Africa. 2nd edn. Washington (DC): World Bank
Chapter 4.30. Fantahun M, Berhane Y, Hogberg U, Wall S, Byass P (2008) Young adult and
middle age mortality in Butajira demographic surveillance site, Ethiopia:lifestyle, gender and household economy. BMC public Health 8(1): 268.
31. Berhane Y, Wall S, Kebede D, Emmelin A, Enquselassie F, et al. (1999)Establishing an epidemiological field laboratory in rural areas -potentials for
public health research and interventions: The Butajira Rural Health Programme
1987–1999. Ethiop J Health Dev 13:1–47.32. Hu Y, Goldman N (1990) Mortality Differentials By Marital Status: An
International Comparison. Demography 27:2.
33. Berhane Y, Hogberg U, Byass P, Wall S (2002) Gender, Literacy, and survival
among Ethiopian adults, 1987–1996. Bull World Health Organ 80(9).34. Singh-Manoux A, Gue’guen A, Ferrie J, Shipley M, Martikainen P, et al. (2008)
Gender Differences in the Association Between Morbidity and Mortality Among
Middle-Aged Men and Women. Am J Public Health 98:2251–2257.35. Weldearegawi B, Ashebir Y, Gebeye E, Gebregziabiher T, Yohannes M, et al.
(2013) Emerging chronic non-communicable diseases in rural communities ofNorthern Ethiopia: evidence using population-based verbal autopsy method in
Kilite Awlaelo surveillance site. Health Policy Plan 28(8): 891–8.
36. De Poel E, O’donnell O, Doorslaer E (2009) What explains the rural-urban gapin infant mortality: household or community characteristics? Demography 46(4):
827–850.37. Kalediene R, Petrauskiene J, Starkuviene S (2007) Inequalities in mortality by
marital status during socio-economic transition in Lithuania. Public Health121(5):385–392.
38. Fantahun M, Berhane Y, Hogberg U, Wall S, Byass P (2009) Ageing of a rural
Ethiopian Population: Who are the survivors? Public Health 123(4):326–30.39. Liu H (2009) Till Death do us part: Marital status and U.S. Mortality trends
1986–2000. Journal of Marriage and Family 71: 1158–1173.40. Ikeda A, Iso H, Toyoshima H (2007) Marital status and mortality among
Japanese men and women: the Japan Collaborative Cohort Study. BMC Public
Health 7:73.41. Molla M, Byass P, Berhane Y, Lindtjorn B (2008) Mortality Decreases among
Young Adults in Southern Central Ethiopia. Ethiop.J.Health Dev 22;(3):218–225.
42. Kamugisha ML, Gesase S, Mlwilo TD, Mmbando BP, Segeja MD, et al. (2007)Malaria specific mortality in lowlands and highlands of Muheza district, North-
eastern Tanzania. Tanzan Health Res Bull 9(1):32–7.
43. Fotrell E, Byass P, Berhane Y (2008) Demonstrating the robustness of populationsurveillance data: implications of error rates on demographic and mortality
estimates. BMC Medical Research Methodology 8:13.
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