Journal of Science and Technology, Vol. 30, No. 1 (2010), pp 45-53 45 © 2010 Kwame Nkrumah University of Science and Technology (KNUST) DETERMINANTS OF UNDER-FIVE MORTALITY IN BUILSA DISTRICT, UPPER EAST REGION, GHANA K. Osei-Kwakye,1 E. Otupiri,2 E. Owusu Dabo,2 E.N.L. Browne2, and M. Adjuik3 1 Kintampo Health Research Centre, Ghana Health Service, Kintampo, Ghana 2 Department of Community Health, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi 3 Navrongo Health Research Centre, Ghana Health Service, Navrongo ABSTRACT Under-five mortality rate is an important indicator of a community’s social development. The Upper East region, one of the most poverty-stricken regions in Ghana, has however recorded a dramatic decline in its under-five mortality rate since 1993; from 180 per 1000 live births to 79 per 1000 live births in 2003. The aim was to identify the determinants of under-five mortality in Builsa district. A case-control study was used to collect data from mothers of 60 cases and 120 controls matched for age, sex and place of residence. Even though 70% of mothers were illiter- ate, the educational level of mothers did not influence the child’s risk of death (OR 1.1). Chil- dren of mothers who had had previous child deaths were about 8 times more likely to die (OR 7.45,) while those who had not had vitamin A supplementation were about 10 times more likely to die (OR 9.57). Over 90% of mothers had an insecticide-treated bednet and more than 50% of them exclusively breastfed their children for the first 6 months of life. Protective risk factors identified included: exclusive breastfeeding (OR 0.72), use of an insecticide-treated bednet (OR 0.12), the number of live children a mother had (OR 0.54) and immunization (OR 0.53). Even in poverty, it is possible to improve the child health status of communities. Health staff should be equipped to pay special attention to mothers with previous child deaths in order to assist them to prevent further deaths. Keywords: Under-five mortality, determinants, case-control study, Builsa district INTRODUCTION (SSA) alone accounts for almost 50% of these Under-five mortality rate (U5MR) is the prob- deaths (Black et al., 2003; Claeson et al., 2003, ability that a newborn will die before reaching WHO, 2007; UNICEF, 2008). the age of five years if subjected to current age- Under-five deaths are caused by easily manage- specific mortality rates. It is usually expressed able or preventable diseases such as malaria, as a rate per 1000 live births. Nearly 10 million measles, pneumonia, diarrhoeal diseases (or a children worldwide die before their fifth birth- combination of such diseases) with malnutri- day, with almost all of such deaths occurring in tion playing a role in more than half of such developing countries; sub-Saharan Africa deaths (WHO, 2000; Bryce et al., 2003, Bryce Journal of Science and Technology © KNUST April, 2010 46 Osei-Kwakye et al. et al., 2005). Though under-five mortality rates Health Survey (GDHS) showed a regional have been declining worldwide, developing U5MR and IMR of 79 per 1000 live births and countries continue to record high values and in 33 per 1000 live births respectively which were low-income countries, one child in 11 dies be- lower than the national rates; 111 per 1000 live fore his/her fifth birthday in comparison to one births and 64 per 1000 live births respectively. in 143 in high-income countries (United Na- The study sought to determine the influence of tions, 2000; WHO, 2003). evidence-based risk factors for under-five mor- Certain factors such as socioeconomic status, tality on the under-five mortality rate in the fertility behaviour, environmental health condi- district and to describe the factors that may tions, nutritional status and infant feeding, and have led to the sharp drop in under the U5MR the use of health services have been identified in the district (and possibly also in the region). as strong risk factors for child mortality. The magnitude of each factor varies in various re- MATERIALS AND METHODS gions across the world (Mosley and Chen, Study Area 1984). The Builsa District is one of the eight districts th in the Upper East region of Ghana. It has six Ghana was ranked forty-seventh (47 ) in the world in terms of under-five mortality rate in sub-districts. The health infrastructure in the 2002, with a rate of 100 per 1000 live births district consists of a district hospital, two (2) mission clinics, four (4) health centres, two (down from 126 per 1000 live births in 1990) community-based health services and planning and an infant mortality rate (IMR) of 57 per (CHPS) compounds and eighty-one (81) out- 1000 live births (UNICEF, 2004). However, the rates increased slightly to 111 per 1000 live reach points. Endemic diseases in the district births and 64 per 1000 live births for under-five are: malaria, tuberculosis, leprosy, schistosomi- asis, respiratory tract infections, intestinal and infant mortality respectively for the year worms, sexually transmitted infections (STIs) 2003 (GSS/NMIMR/ORC Macro, 2004) and in and diarrhoea while the main epidemic-prone 2008, went down to 80 and 50 per 1000 live diseases are cerebrospinal meningitis (CSM), births respectively (GSS/GHS//ORC Macro, 2008 preliminary results). To achieve the 4th measles and yellow fever. Millennium Development Goal (MDG), Ghana Records from the Builsa District Hospital indi- has to reduce her U5MR rate to 40 per 1000 cate high proportions of deaths in the under- live births by 2015 (Bryce et al., 2008). The five age group out of all deaths occurring in the annual rate of U5MR reduction in Ghana (1990 hospital. In 2001, 27.8% of all deaths in the -2006) is 0.09%. Between 2007 and 2015, hospital were in children under-five. This in- Ghana has to achieve an annual rate of reduc- creased to 33.2% in 2002 but decreased slightly tion of 12.2% in order to achieve the MDG 4 to 31.5% in 2003 (Ghana Health Service/Builsa (Countdown Coverage Writing Group, 2008). District Health Management Team, 2004). The Upper East Region of Ghana (in which Builsa District is located), has been classified Methods as one of the worst poverty stricken regions of A comparative study with a case-control design Ghana with 40% of its population living in was used. The cases were defined as children abject poverty and nine out of ten people in the below five years who died at the Builsa District region being said to be poor (Ghana Poverty hospital or in the communities (as identified from Reduction Strategy, 2003). In spite of this, the community-based surveillance records), from region has recorded a dramatic decline in under January 2003 to June 2005. Data on the cases -five and infant mortality rates since 1993 were collected via a review of the district hospital (U5MR - 180/1000 and IMR - 105/1000 live records of deaths among children under-five ad- births). The 2003 Ghana Demographic and mitted to the hospital from January 2003 to June Journal of Science and Technology © KNUST April 2010 Builsa under-five mortality determinants 47 2005 and also from the sub-district community- search, Publications and Ethics (CHRPE), while based surveillance (CBS) records as well as administrative clearance was obtained from the through interviews with community-based volun- Builsa District Health Directorate. teers to further identify any under-five deaths that may not have been recorded in the CBS records STATISTICAL ANALYSIS at the time of the study. Informed verbal consent The sample size was calculated as follows: 60 was sought from mothers or guardians of cases cases and 120 controls based on a 60% preva- before they were interviewed. A total of 74 cases lence of infectious diseases among under-fives were identified from the Builsa District hospital in the district for the control group with 3 as the records for the period January 2003 to June 2005. odds ratio worth detecting at a 95% confidence Of the 74, 38 were eventually recruited to partici- level with a power of 80% and allowing for a pate in the study; the rest either did not consent to 10% non-response rate (Epitable Calculator, participate or had wrong addresses and could not Epi Info™ 6.04d (CDC, Atlanta). be traced or were not available at the recorded address at the time of the study or were not resi- Data were analyzed using Epi Info 2000 (© dents of Builsa District. An additional 22 cases CDC, USA; WHO, Geneva) and Stata 8 for were captured from the CBS records and from Windows (© College Station, Texas 77845 information provided by the community-based USA). Summary statistics for the variables volunteers. were determined. For categorical variables, frequencies and sometimes cross-tabulations Controls for the study were children matched for were used to describe the relationships between the same age (range: ± 2 months of age of a case as at the time of his/her death), sex, who lived in study variables. The chi-square test statistic the same communities as cases (or in nearby was used to determine the statistical signifi- communities) and who were alive at the time of cance of associations between variables. Con- the study. Mothers and or guardians of controls tinuous variables were summarized using the assisted in the identification of other potential mean with a 95% confidence interval as meas- controls. The community-based surveillance vol- ure of dispersion. For skewed variables, the unteer assisted in the location of the house of the median and the inter-quartile range were used potential control.