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    Socio-economic determinants of childhood mortality in Navrongo DSS
    (2011-03-24) Ndiath, Mahamadou Mansoor
    Background Improving the health of the poor and reducing health inequalities between the poor and non-poor has become central goals of international organizations like the World Bank and WHO as well as, national governments in the contexts of their domestic policies and development assistance programmes. There are also unquantified and poorly understood inequalities in access to health services within and between various population groups. Little is known about the factors that determine these inequalities and the mechanisms through which they operate in various sub-groups. Objectives The aim of the study was first to describe under-five mortality trend according to wealth index; second to describe risk factors for under five mortality; and finally to investigate the relationship between socio-economic and demographic factors and under five mortality during the period 2001 to 2006. Methods The study involved all children born in 2001-2006. A total of 22,422 children younger than 5 years were found in 21,494 households yielding 36603.13 Person-Years Observed (PYOs) up to 31st December 2006. Household wealth index was constructed by use of Principal Component Analysis (PCA), as a proxy measure of each household SES. From this index households were categorized into five quintiles (i.e., poorest, poorer, poor, less poor and least poor). Life table estimates were used to estimate mortality rates per 1000 PYO for infants (0-1), childhood (1-5) and underfives children. Health inequality was measured by poorest to least poor mortality rate ratio and by computing mortality concentration indices. Trend test chi-square was used to determine significance in gradient of mortality rates across wealth index quintiles. Risk factors of child mortality were assessed by the use of Cox proportional hazard regression taking into account potential confounders. v Results The result indicates unexpected low mortality rate for infant (33.4 per 1,000 PYO, 95% CI (30.4 – 35.6)) and childhood (15.0 per 1,000 PYO, 95% CI (13.9 – 16.3)). Under-five mortality rate was 18.2 per 1,000 PYO (95% CI (75.6 – 108.0)). The poorest to least poor ratios were 1.1, 1.5 and 1.5 for infants, childhood, and under-five year olds respectively, indicating that children in the poorest quintile were more likely to die as compared to those in the least poor household. Computed values for concentration indices were negative (infant C= -0.02, children C= -0.09 and underfive C= -0.04) indicating a disproportionate concentration of under-five mortality among the poor. The mortality rates trend test chi-square across wealth index quintiles were significant for both childhood (P=0.004) and under-five year old children (P<0.005) but not for infants (P=0.134). In univariate Cox proportional hazard regression, children in the least poor households were shown to have a 35% reduced risks of dying as compared to children in the poorest category [crude H.R =0.65, P=0.001, 95% C.I (0.50 – 0.84)]. The results showed that for under five children, a boy is 1.15 times more likely to die as compared to a girl [crude H.R =1.14, P=0.038, 95% C.I (1.00 - 1.31)]. Second born had a 18% reduced risk of dying as compared to first born [crude H.R =0.82, P=0.048, 95% C.I (0.67 – 0.99)]. After controlling for potential confounders, the adjusted hazard ratio for wealth index decreased slightly. The estimated hazard for wealth index in the univariate was 0.65 while in the multivariate modeling the estimated hazard ratio is 0.60 in the first model. Conclusion The study shows that household socio-economic inequality is associated with underfive mortality in the Navrongo DSS area. The findings suggest that reductions in infant, childhood, and under five mortalities are mainly conditional in health and education interventions as well as socioeconomic position of households. The findings further call for more pragmatic strategies or approaches for reducing health inequalities. These could include reforms in the health sector to provide more equitable resource allocation. Improvement in the quality of the health services offered to the poor and redesigning interventions and their delivery to ensure they are more inclined to the poor.
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    The role of birth order in infant mortality in Ifkara DSS area in rural Tanzania
    (2010-10-26) Sangber-Dery, Matthew Dery
    Introduction: Studies of factors affecting infant mortality have rarely considered the role of birth order. Despite the recent gains in child mortality in Tanzania, infant mortality rate is still high (68 per 1000 live births) according to the Tanzania Demographic Health Survey (2004-5). This study investigated the risk factors associated with infant mortality in Ifakara Health and Demographic Surveillance Systems area in rural Tanzania from January 2005 to December 2007 with specific reference to birth order, and identified causes of infant death for the study period. Materials and Methods: The study was a secondary analysis of existing data from the Ifakara Health and Demographic Surveillance Systems (HDSS). Child data for 8916 live births born from 1st January 2005 to 31st December 2007 were extracted for analysis. The binary outcome variable was infant mortality. Tables and graphs were used to describe the distribution of maternal demographic and study population characteristics. Poisson regression analyses were used to establish the association between infant mortality and exposure variables. Results: We recorded 562 infant deaths. Neonatal mortality rate was 38 per 1000 person-years while infant mortality rate was 70 per 1000 person-years. Birth order of 2nd to 5th was associated significantly with 22% reduced risk of infant mortality (IRR=0.78, 95%CI: 0.64, 0.96; p=0.02) compared with first births. The infant mortality rates per 1000 person-years for first births was 84, 2nd to 5th was 66 and sixth and higher was 71 per 1000 person-years. Male infants were 17% more at risk of infant deaths as compared to their female counterparts, but not statistically significant (IRR=1.17, 95%CI: 0.99, 1.38; p=0.06). Mothers aged 20 to 34 years had 19% reduced risk of infant death (IRR=0.81, 95%CI: 0.65, 1.00; p=0.05) as compared v to mother of less than 20 years of age. Singleton births had 71% reduced risk of infant mortality (IRR=0.29, 95%CI: 0.22, 0.37; p<0.001) compared with twin births. Mothers who did not attend antenatal care had 2% reduced risk of infant deaths (IRR=0.98, 95%CI: 0.49, 1.97) but not statistically significant compared with mothers who attended antenatal care. Mothers who delivered at home were 1.05 times more at risk of infant deaths but not statistically significant (IRR=1.05, 95%CI: 0.89, 1.24; p=0.56). Mothers who had no formal education were 1.41 times more likely to have infant deaths (IRR=1.41, 95%CI: 0.72, 2.79; p=0.32) as compared to those who had education beyond primary. When adjusted for sex, maternal age and twin births, second to fifth birth order had 20% reduced risk of infant death (IRR=0.80, 95%CI: 0.61, 1.03; p=0.08), but statistically not significant as compared to first births. Malaria (30%), Birth injury/asphyxia (16%), Pneumonia (10%), Premature and/or low birth weight (8%), Anaemia (3%) and Diarrhoeal diseases (2%) were the major causes of infant deaths from 2005 to 2007. Discussion and conclusion: First births and higher birth orders were associated with higher infant mortality. Twin birth was a risk factor for infant mortality. The health systems should be strengthened in providing care for mothers and child survival. We recommend that the high-risk group, first or sixth or higher pregnancies, need special care and the existing health management system may be strengthened to create awareness among potential mothers for seeking appropriate health care from the beginning of pregnancy. Also, antenatal care follow-up can be emphasized for high-risk mothers. Efforts to control mosquitoes must be accelerated in the Ifakara sub-district.
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    Household socio-economic status as a determinant of under five mortality at Rufiji DSS Tanzania
    (2009-05-22T12:33:06Z) Nattey, Cornelius
    Background Disparities in health outcomes between the poor and the rich are increasingly attracting attention from researchers and policy-makers. However, policies aimed at reducing inequities need to be based on a sound assessment of the nature, magnitude and determinants of the problem, as policy decisions based on intuition are likely to be misguided. Objective The work investigates the relationship between household socio-economic status and under-five mortality at Rufiji DSS in year 2005. The specific objectives were; 1.To construct wealth and concentration indices for households with children under age five. 2. To measure health inequality by poorest / least poor mortality rate ratio and the use of concentration index 3. To determine significance in gradient of mortality rates across wealth index quintiles by a trend test (chi-square) 4. To assess the magnitude of association between socio-economic status of households and under-five mortality. Methods Data from Rufiji DSS, Tanzania was used for the analysis. Out of 11,189 children under five years of age from 7298 households, 251 died in the year 2005. These yielded a total of 9341.6 PYO in 2005 which was used in the analysis. Household wealth index was constructed by use of Principal Component Analysis (PCA), as a proxy measure of each household SES. From this index households were categorized into five quintiles (i.e., poorest, poorer, poor, less poor and least poor). Kaplan-Meier (K-M) survival estimates of incidence rates were used to estimate mortality rates per 1000 PYO for infants (0-1), children (1-4) and under-fives. Health inequality was measured by poorest to least poor mortality rate ratio and by computing mortality concentration indices. Trend test chi-square was used to determine significance in gradient of mortality rates across wealth index quintiles. Risk factors of child mortality were assessed by the use of Poisson regression taking into account potential confounders. Results The result indicates that the mortality rate was higher for infants (123.4 per 1000 PYO, 95% CI (104.3, 146.1)) than for children aged 1-4 years (17.3 per 1000 PYO, 95% CI (14.3, 20.9)). Under-five mortality was 26.9 per 1000 PYO (95% CI (23.7, 30.4)). The poorest to least poor ratio were 1.5, 3.8 and 2.4 for infants, children, and under-five year olds, respectively indicating that children in the poorest quintile were more likely to die as compared to those in the least poor household. Computed values for concentration indices were negative (infant C= -0.07, children C= -0.24 and under-five C= -0.16) indicating a disproportionate concentration of under-five mortality among the poor. The mortality rates trend test chi-square across wealth index quintiles were significant for both children (P<0.001) and under-five year old children (P<0.001) but not for infants (P=0.10). In univariate Poisson regression, children in the least poor households were shown to have a 58% significantly reduced risk of dying as compared to the poorest households [crude RR=0.42, P < 0.001, 95% CI (0.27 - 0.62)]. The effect of household socio-economic status attenuated after adjusting for maternal education, maternal age and occupation. Children in vi the least poor households had a 52% significantly reduced risk of dying as compared to the poorest households [adjusted RR=0.48, P = 0.002, 95% CI (0.30 - 0.80)]. Conclusion The study shows that household socio-economic inequality is associated with under-five mortality in Rufiji DSS in 2005 and that the survival advantage of under-five year old children is associated with maternal education. Reducing poverty and making essential health services more available to the poor are critical to improving overall childhood mortality in rural Tanzania.
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    Socioeconomic and bio-demographic determinants of infant mortality in Egypt
    (2009-05-06T10:21:09Z) Yasin, Shima Kamal
    Background: This study examines the socioeconomic and biodemographic determinants of infant, neonatal and post neonatal mortality in Egypt. It also tries to reach better understanding on the relative importance of these factors. Methods: Population-based cross-sectional secondary data analysis of the 2005 Egypt Demographic and Health Survey (EDHS). Cox’s proportional hazard models have been fitted to select the significant determinants of infant and post neonatal mortality, while logistic regression models were adopted for the neonatal period. Results: 13,851 live births were analyzed with 463 deaths before the first birthday; the total follow up time is 144,835 babymonths, giving an IMR of 32 per 10,000 baby-months. After adjusting for all socioeconomic and biodemographic factors, the analyses reveal strong association between infant mortality and biodemographic factors, while the only significant socioeconomic determinant is the mother’s education. Also it has been shown that mother’s education, child’s sex and place of delivery are time dependent covariates. Analyses of neonatal period indicate no association with any socioeconomic factor, while child’s sex and place of delivery are significant predictors. Exclusion of neonatal deaths shows that the risk of post neonatal mortality is inversely related to mother’s education, and not determined by sex of the child nor place of delivery. The risk of infant, neonatal and post neonatal death is consistently related to birth interval and birth size. Conclusions: Biodemographic characteristics represent the most substantial impacts on infant mortality. The only significant socioeconomic predictor (maternal education) has a modest impact, at best, on infant mortality, which appears at later stages of infancy period (namely post neonatal period); since the later proved to be a time varying covariate. Unlike neonatal period, analysis indicates lack of association between post neonatal mortality and child’s sex contradicting the biological knowledge, and supporting the hypothesis of gender discrimination and male sex preference.
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    Does place of delivery affect neonatal mortality in Rufiji Tanzania?
    (2009-04-29T13:33:26Z) Ajaari, Justice
    Introduction The fourth Millennium Development Goal (MDG) calls for a reduction in newborn mortality but newborn mortality is one of the world’s most neglected health problems. While there has been significant progress in reducing deaths among children under age five over the past decade, the proportion of under five mortality that occur in the neonatal period, an estimated 38% in 2000, is increasing. Therefore the Millennium Development Goal for child survival cannot be met without substantial reductions in neonatal mortality. It is therefore extremely important to make available the much needed epidemiological information regarding the time, place and causes of neonatal deaths which will enable greater attention to policies aimed at reducing levels of mortality and programme planning. Objectives The objective of this study was to investigate the relationship between neonatal mortality and place of delivery in Rufiji in rural Tanzania. The specific objectives were: 1.to measure and compare the neonatal mortality rates among neonates born in and outside health facilities, 2. to compare the maternal characteristics of those who deliver in and outside health facilities, 3. to compare cause-specific neonatal mortality among neonates born in and outside health facilities and 4.to measure the association between place of delivery and neonatal mortality. Methods Data from the Rufiji Demographic Surveillance System (RDSS), Tanzania, was used for the analysis. A total of 5124 live births and 166 neonatal deaths were recorded from 1st January, 2005 to 31st December, 2006. Place of delivery and place of death were categorized as either health facility or outside health facility. Neonatal mortality rates were calculated by dividing the number of neonatal deaths to the total number of live births and multiplied by 1000. Data on causes of death were collected using verbal autopsies. Cause specific mortality was determined by using physician coding according to a list of causes of death based on the 10th revision of International Classification of Diseases. Household characteristics and assets ownership of the mothers of the neonates were used to construct a wealth index as proposed by Filmer and Pritchett in 20011. The index was calculated using Principal Component Analysis (PCA) in Stata version 10 software. A chi-square (x2) test at 5% significant level was also used to compare the maternal characteristics by place of delivery and neonatal characteristics and place of delivery. Univariate and multivariate logistic regression models were also used to assess the association between neonatal mortality and place of delivery as well as between neonatal mortality and maternal risk factors, while adjusting for potential confounders. Results The highest number of neonatal deaths occurred during the first week of life 111(67%), the remainder occurred from the second week to the fourth weeks of life 55(33%). The overall neonatal mortality rate was 32/1000 live births. Neonatal mortality rate was higher in children born outside heath facilities 43/1000 live births compared with those born in health facilities 27/1000 live births. The two major causes of deaths in both health facility deliveries and outside health facility deliveries were birth injury or asphyxia n=29 (26%) and prematurity/low birth weight n=25 (22%). Mothers who delivered out-side a health facility were 1.6 times more likely to have experienced neonatal death [unadjusted OR=1.6, p-value = 0.002, 95% CI 1.2, 2.2] compared to mothers who delivered in health facility and this was statistically significant. After adjusting for maternal risk factors, mothers who delivered outside a health facility were 1.7 times more likely to have experienced neonatal death [adjusted OR=1.7, p-value = 0.002, 95% CI 1.2, 2.4] compared to mothers who delivered in a health facility and this was statistically significant. Maternal household socio-economic status and parity were the only other factors that were found to be statistically significantly associated with neonatal mortality in the multivariate analysis. For instance, least poor mothers were found to be 40% less likely to have experienced neonatal death [adjusted OR = 0.6, pvalue = 0.046, 95% CI 0.4, 1.1] compared to the poorest mothers and this was statistically significant. Less poor mothers were also found to be 50% less likely to experience neonatal mortality [adjusted OR =0.5, p-value = 0.002, 95% CI 0.3, 0.8] compared to the poorest mothers. Mothers who had parity of three to four (3-4) were found to be 40% less likely to have experienced neonatal death compared to mothers who had parity of one to two (1-2). Mothers who had parity of five (5) and above were also found to be 50% less likely to have experienced neonatal death compared to those who had parity of one to two (1-2). Conclusion Place of delivery has a very important role in neonatal survival in this rural setting. In order to reduce neonatal mortality, pregnant women should be encouraged and supported to give birth to their newborns in a health facility while discouraging deliveries that occurred outside health facility. Infrastructure, such as emergency transport, to facilitate health facility deliveries requires attention.
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    Risk factors for perinatal mortality in Nigeria: the role of place of delivery and delivery assistants
    (2009-03-24T12:32:13Z) Oji, Oti Samuel
    Background: This study examines the association between place of delivery, delivery assistants and perinatal mortality in Nigeria. Previous studies have found these factors to be associated with the risk of perinatal mortality. This study therefore aims to determine the extent to which these two factors predict perinatal mortality in the Nigerian context as this information will be useful in informing health policy decisions and actions in so far as a desirable reduction in childhood mortality in Nigeria is concerned. Methods: This study uses cross sectional design through secondary analysis of the 2003 Nigerian Demographic and Health Survey (NDHS). The variables representing place of delivery and delivery assistants have been fitted into logistic regression models to determine their association with perinatal mortality. Several other known risk factors for perinatal mortality such as maternal education and birth weight, to mention a few, have also been investigated using the logistic regression analysis. Results: 5783 live singleton births were analyzed with 194 newborns dying within the first seven days of life giving an early neonatal mortality rate (ENMR) of 33.5 per 1000 and an estimated perinatal mortality rate (PNMR) of 72.4 per 1000 live births. The results also show that place of delivery [p=0.8777] and delivery assistants [p=0.3812] are not significantly associated with perinatal mortality even after disaggregating the analysis by rural and urban areas. However being small in size at birth [AOR= 2.13, CI=1.41 – 3.21], female [AOR=0.57, CI= 0.42 – 0.77] and having a mother who practiced traditional religion [AOR= 4.37, CI= 2.31 – 8.26], were all significantly associated with perinatal mortality. Conclusions: Place of delivery and delivery assistants are not good predictors of perinatal mortality in the Nigerian context. However various limitations of the study design used such as the issue of uncontrolled confounding may have affected the findings. Nonetheless, the increased risk of perinatal deaths in small babies and the decreased risk of death among female babies are consistent with other studies and have both been attributed elsewhere to biologic mechanisms.
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    Socioeconomic determinants of infant mortality in Kenya
    (2008-10-23T10:09:47Z) Mustafa, Hisham
    Background: This study examines the socioeconomic factors associated with infant and postneonatal mortality in Kenya and tries to quantify these associations in order to put those factors in ranked order so as to prioritize them in health policy plans aiming to decrease infant and postneonatal mortality. The study has used wealth index, mother’s highest educational level, mother’s occupation and place of residence as exposures of interest. Methods: The study uses analytical cross-sectional design through secondary data analysis of the 2003 Kenyan Demographic and Health Survey (KDHS) dataset for children. Series of logistic regression models were fitted to select the significant factors both in urban and rural areas and for infant and postneonatal mortality, separately, through the use of backward stepwise technique. Then the magnitude of the significance for each variable was tested using the Wald’s test, and hence the factors were ranked ordered according to their overall P-value. Results: After excluding non-singleton births and children born less than one year before the survey, a sample size of 4 495 live births was analyzed with 458 infants died before the first year of life giving IMR of 79.6 deaths per 1000 live births. After adjusting for all biodemographic and other health outcome determining factors, the analyses show no significant association between socioeconomic factors and infant mortality in both urban and rural Kenya. The exclusion of deaths that occurred in the first month of ages shows that risk of postneonatal (OR 3.09; CI: 1.29 – 7.42) mortality, in urban Kenya, were significantly higher for women working in agricultural sector than nonworking women. While in rural Kenya, the risk of postneonatal (OR 0.42; CI: 0.20 – 0.90) mortality were significantly lower for mothers with secondary school level of education than mothers with no education. Conclusions: There is lack of socioeconomic differentials in infant mortality in both urban and rural Kenya. However, breastfeeding, ethnicity and gender of the child in urban areas on one hand and breastfeeding, ethnicity and fertility factors on the other hand are the main predictors of mortality in this age group. Furthermore, results for postneonatal mortality show that level of maternal education is the single most important socioeconomic determinant of postneonatal mortality in urban Kenya while mother’s occupation is the single most important socioeconomic determinant of postneonatal mortality in rural areas. Other determinants of postneonatal mortality are ethnicity and gender of the child in urban areas, while in rural areas; the other main predictors are ethnicity, breast feeding and fertility factors.