Risk Factors Of Under-five Mortality Research Articles

Correction: Investigating risk factors for under-five mortality in an HIV hyper-endemic area of rural South Africa, from 2000–2014

Correction: Investigating risk factors for under-five mortality in an HIV hyper-endemic area of rural South Africa, from 2000–2014

Spatiotemporal modeling of under-five mortality and associated risk factors in Ethiopia using 2000–2016 EDHS data

BackgroundThe under-five mortality rate serves as a key indicator of the performance of a country’s healthcare system. Despite a minor decline, Ethiopia continues to face a persistently high under-five mortality rate across different zones. Thus, this study aimed to identify the risk factors of under-five mortality and the spatiotemporal variation in Ethiopian administrative zones.MethodThis study used the 2000–2016 Ethiopian Demographic and Health Survey (EDHS) data which were collected using a two-stage sampling method. A total of 43,029 (10,873 in 2000, 9,861 in 2005, 11,654 in 2011, and 10,641 in 2016) weighted sample under-five child mortality were used. The space-time dynamic model was employed to account for spatial and time effects in 65 administrative zones in Ethiopia.ResultsFrom the result of a general nesting spatial-temporal dynamic model, there was a significant space-time interaction effect [γ = -0.1444, 95% CI(-0.6680, -0.1355)] for under-five mortality. The increase in the percentages of mothers illiteracy [β = 0.4501, 95% CI (0.2442, 0.6559)], not vaccinated[β= 0.7681, 95% CI (0.5683, 0.9678)], unimproved water[β= 0.5801, CI (0.3793, 0.7808)] were increased death rates for under five children while increased percentage of contraceptive use [β= -0.6609, 95% CI (-0.8636, -0.4582)] and antenatal care unit visit > 4 times [β= -0.1585, 95% CI(-0.1812, -0.1357)] were contributed to the decreased under-five mortality rate at the zone in Ethiopia.ConclusionsEven though the mortality rate for children under five has decreased over time, still there is higher in different zones of Ethiopia. There exists spatial and temporal variation in under-five mortality among zones. Therefore, it is very important to consider spatial neighborhood’s and temporal context when aiming to avoid under-five mortality.

Predictive Model and Risk Factors of Under-five Mortality in Nigeria: A Study Based on 2018 Nigeria Demographic and Health Survey

The death of children under-five years is one of the critical issues in public health and the need for improving child survival continues to be a matter of urgent concern. In this study, we develop a predictive model in order to examine the risk factors of under-five mortality in Nigeria. The study utilized data from 2018 Nigeria Demographic and Health survey. The demographic and mortality data of 127,545 children were extracted and univariate and multivariate logistic regression models were employed. The results revealed that under-five mortality was 143 deaths per 1,000 live births in Nigeria. The likelihood of death was higher among males compared to females children (OR = 1.893, P<0.05). First and second birth order have a lower chances of decreasing odds of under-five children (OR = 0.737, P<0.05) and (OR = 1.888, P<0.05).The under-five mortality was higher among children born to mothers who belong to other religions compared to Christians. Islam (OR = 1.689, P<0.05) and traditionalist (OR = 2.705, P<0.05) respectively. Public servant (OR = 1.881, P<0.05) and unmarried mother (OR = 1.896, P<0.05) were increased the odds of dying chances of under-five mortality in Nigeria. Children of mothers without education experienced more death compared to mothers who attended post-secondary education (OR = 3.372, P<0.05). Sex of child, birth order, religion, marital status, maternal occupation and maternal education were significant factors associated with under-five mortality in Nigeria. Thus, planning and implementing relevant strategies that focus on those identified risks factors of under-five mortality is required for improvement of child survival in Nigeria.

Multilevel zero inflated and hurdle models for under five-child mortality in Indonesia

Introduction: Overcoming under-five mortality rate remains a great challenge for Indonesia to meet the national target despite its notable advancements and progress in reducing child mortality rate. Therefore, understanding risk factors of under-five mortality is essential to enhance the health and well-being of children. This research seeks to investigate associated factors of under-five mortality in Indonesia by using the 2017 Indonesia Demographic and Health Survey data. Methods: The multilevel zero-inflated and multilevel hurdle models are considered to handle unobserved heterogeneity that may occur at province level, and to model prevalence and risk of child death as a joint process, which are reported in terms of odds ratio (OR) and incidence ratio rate (IRR), respectively. Results: Lower number of household members (IRR = 0.803, 95% confidence interval [CI]: 0.784–0.823), older mother's age at first birth (IRR = 1.020, 95% CI: 1.007–1.032), higher number of children ever born (IRR = 1.491, 95% CI: 1.450–1.533), lower mother's education (IRR = 1.224, 95% CI: 1.013–1.479), and lower father's education (IRR = 1.232, 95% CI: 1.015–1.495) are significantly associated with higher total death numbers in children before the age of 5 years. Furthermore, the odds of no child death are significantly higher among mother who use a contraceptive method (OR = 11.088, 95% CI: 6.659–18.462) and among household in higher quantile wealth (OR = 1.133, 95% CI: 1.005–1.277). Conclusion: This evidence-based empirical highlights priority risk factors that might provide insight for policymakers, health professional, and the community in general to design appropriate intervention to help reduce the burden of under-five mortality in the country.

Risk factors of mortality among children under age five in Awi Zone, northwest Ethiopia.

BackgroundGlobally, under-five mortality rates have dropped, but in Ethiopia, the under-five mortality rate is still high. In Amhara region, the death of children under the age of five is still a public health problem. This study assessed the risk factors of mortality among children under age five in Awi Zone.MethodA community-based cross-sectional study was conducted from December 1, 2020, up to April 30, 2021. Data entry and analysis were conducted using SPSS version 26 and Stata version 16, respectively. A zero-inflated Poisson regression model was fitted to identify the risk factors of under-five mortality.ResultOut of the 1,340 mothers in the Awi zone, 11.9% of women lost at least one child. Single births (IRR = 0.598, 95% CI: 0.395, 0.906), fathers whose level of education is secondary or above(IRR = 0.223, 95% CI: 0.064, 0.782), mothers who completed their secondary and above education level(IRR = 0.116, 95% CI: 0.014, 0.971), mothers who have birth interval greater than 24 months (IRR = 0.619,95% CI: 0.417, 0.917), 8 and above family size the households (IRR = 0.543, 95% CI: 0.302, 0.976), 31 and above mother age groups (IRR = 0.296, 95% CI: 0.093, 0.943), medium households of mothers (IRR = 0.540, 95% CI: 0.316, 0.920), working mothers (IRR = 1.691, 95% CI: 1.040, 2.748) and mothers who had not antenatal visits during pregnancy (IRR = 2.060, 95% CI: 1.259, 3.371) were significant factors of under-five mortality.ConclusionMother’s age group, preceding birth interval, family size, wealth index, duration of pregnancy, antenatal visits during pregnancy, types of birth, mother’s education level, husband’s education level, and place of delivery were significant factors of under-five mortality in Awi zone. So, Awi zone public health institute, Awi zone children’s and youth office, and other relevant bodies should work to reduce under-five mortality by focusing on child mortality issues.

Risk factors of under-five mortality in Ethiopia using count data regression models, 2021.

BackgroundDespite the global reduction in under-five mortality, still many children die before their fifth birthday in Ethiopia. The main aim of this study was to identify determinants of under-five mortality using count data regression models based on 2019 Ethiopia mini demography and health survey data.MethodsThe data source for this study was the 2019 Ethiopia mini demography and health survey data. Various count data regression models were applied to identify the determinants of under-five mortality.ResultsA total of 5,535 mothers with children aged 0–59 months were included in the study. Of the total, 1,277 (23.07%) women had lost at least one child by death before celebrating fifth birthday. Zero-Inflated Poisson model was found to be the best model, and it revealed that mother's age, marital status, mother's age at 1st birth, place of delivery, current contraceptive type used, type of cooking fuel, residence, region, religion, time to get drinking water, number of children at home, birth order, and birth type were significant factors that determine U5 mortality in Ethiopia.Mothers aged 15–24 years (IRR = 1.24, p = 0.007) and above 24 years (IRR = 1.66, p = 0.000) at their 1st births, mothers from rural area (IRR = 1.27, p = 0.000), mothers traveled for 1–30 min (IRR = 1.62, p = 0.000) and >30 min (IRR = 1.82, p = 0.000) to get drinking water, mothers used charcoal (IRR = 1.86, p = 0.009) and wood (IRR = 1.64, p = 0.033), children with birth order of 2nd-3rd (IRR = 3.91, p = 0.000), 4th -5th (IRR = 13.14, p = 0.000), 5th and above (IRR = 38.17, p = 0.000), and multiple born children (IRR = 1.5, p = 0.000) had higher risk of under-five mortality while mothers aged 25–34 years (IRR = 0.73, p = 0.000), unmarried mothers (IRR = 0.68, p = 0.004), mothers delivered in public health sectors (IRR = 0.59, p = 0.000), mothers used Pill/IUD (IRR = 0.64, p = 0.018), mothers who had 3 to 5 (IRR = 0.51, p = 0.000) and more than 5 (IRR = 0.27, p = 0.000) children at home had lower risk of under-five mortality.ConclusionsMothers should be encouraged to deliver at health institutions. Mothers also should be given awareness to use Pill/IUD contraceptive type. Moreover, facilitating rural areas to get electricity and drinking water near to homes helps to reduce the burden of U5M and to be in line with sustainable development goal.

The effects of community clustering on under-five mortality in India: a parametric shared frailty modelling approach

The study of the effect of community clustering of under-five mortality has its implications in both research and policy. Studies have shown the contribution of community factors on under-five mortality. However, these studies did not account for censoring. We examine the presence of community dependencies and determine the risk factors of under-five mortality in India and its six state-regions by employing a Weibull hazard model with gamma shared frailty. We considered every possible way to ensure that the frailty models used in the study are not merely a consequence of how the data are organized rather than representing a substantive assumption about the source of the frailty. Data from the fourth round of the National Family Health Survey has been used. The study found that except for south India, children born in the same community in India and the other five state-regions shared similar characteristics of under-five mortality. The risk of under-five mortality decreased with an increase in mother’s schooling. Except for northern region, female births were less likely to die within first five years of life. We found a U-shaped relationship between preceding birth interval and under-five mortality. History of sibling’s death, multiple births and low-birthweight significantly increases the risk of under-five mortality in all the six state-regions. The Hindu–Muslim mortality gaps and Scheduled Caste or Tribe’s mortality disadvantage is diminishing. Since the factors associated with under-five mortality were not necessarily the same across the six state-regions of India, adopting a uniform approach in dealing with under-five mortality in India may not benefit all the regions equally.

Spatial analysis of economic predictors of under-five mortality in Nigeria

AbstractGlobally, under-five mortality rates declined from 93 deaths per 1,000 live births in 1990 to 38 in 2019. Despite the remarkable progress in reducing under-five mortality globally, it is still significantly high in Nigeria with 117 deaths per 1,000 live births, meaning that 1 in 8 children die before the age of 5. The extant literature on the risk factors of under-five mortality in Nigeria have been largely limited to maternal socio-economic characteristics and environmental factors, with little known about the macroeconomic predictors within a spatial context. As a result, this study examines the macroeconomic predictors of under-five mortality in Nigeria. The data were analysed using spatial statistics. Results show that some parts of northern Nigeria are hotspots of under-five mortality. The study also discovers that inflation rate is a risk factor of under-five mortality in southern Nigeria while internally generated revenue is the predictor in the northern region. The study recommends region-specific interventions such as controlling the high rate of inflation and improving internally generated revenue to reduce under-five mortality in the country.

Impact of high-risk fertility behaviours on underfive mortality in Asia and Africa: evidence from Demographic and Health Surveys

BackgroundMaternal age < 18 or > 34 years, short inter-pregnancy birth interval, and higher birth order are considered to be high-risk fertility behaviours (HRFB). Underfive mortality being disproportionately concentrated in Asia and Africa, this study analyses the association between HRFB and underfive mortality in selected Asian and African countries.MethodsThis study used Integrated Public Microdata Series-Demographic and Health Surveys (IPUMS-DHS) data from 32 countries in sub-Saharan Africa, Middle East, North Africa and South Asia from 1986 to 2017 (N = 1,467,728). Previous evidence hints at four markers of HRFB: women’s age at birth of index child < 18 or > 34 years, preceding birth interval < 24 months and child’s birth order > 3. Using logistic regression, we analysed change in the odds of underfive mortality as a result of i) exposure to HRFB individually, ii) exposure to any single HRFB risk factor, iii) exposure to multiple HRFB risk factors, and iv) exposure to specific combinations of HRFB risk factors.ResultsMother’s age at birth of index child < 18 years and preceding birth interval (PBI) < 24 months were significant risk factors of underfive mortality, while a child’s birth order > 3 was a protective factor. Presence of any single HRFB was associated with 7% higher risk of underfive mortality (OR 1.07; 95% CI 1.04–1.09). Presence of multiple HRFBs was associated with 39% higher risk of underfive mortality (OR 1.39; 95% CI 1.36–1.43). Some specific combinations of HRFB such as maternal age < 18 years and preceding birth interval < 24 month significantly increased the odds of underfive mortality (OR 2.07; 95% CI 1.88–2.28).ConclusionMaternal age < 18 years and short preceding birth interval significantly increase the risk of underfive mortality. This highlights the need for an effective legislation to curb child marriages and increased public investment in reproductive healthcare with a focus on higher contraceptive use for optimal birth spacing.

Count Models Analysis of Factors Associated with Under-Five Mortality in Ethiopia

Background. Under-five mortality has continued a key challenge to public health in Ethiopia, and other sub-Saharan Africa countries. The threat of under-five mortality is incessant and more studies are needed to generate new scientific evidence. This study aimed to model the number of under-five deaths a mother has experienced in her lifetime and factors associated with it in Ethiopia. Method. A retrospective cross-sectional study based on data obtained from the Ethiopian Demographic and Health Survey (DHS), 2016 was used. The response variable was the total number of under-five children died per mother in her lifetime. Variables such as maternal socioeconomic and demographic characteristics, health, and environmental factors were considered as risk factors of under-five mortality. Hurdle negative binomial (HNB) regression analysis was employed to determine the factors associated with under-five mortality. Results. The data showed that 27.2% (95%CI: 0263, 0.282) of women experienced under-five deaths. The study revealed the age of mother at first birth, the age of mother at the time of under-five mortality occurred, number of household members, household access to electricity, region, educational level of the mother, sex of household head, wealth index, mother residing with husband/partner at the time of under-five mortality occurred as factors associated with under-five mortality. Age of mother at first birth 18 to 24 (IRR = .663; 95%CI: 0.587, 0.749), 25 or higher years old (IRR = 0.424; 95%CI: 0.306, 0.588), access to electricity (IRR = 0.758; 95%CI: 0.588, 0.976), primary education level of the mother (IRR = 0.715; 95%CI: 0.584, 0.875) and the richer wealth index (IRR = 0.785; 95%CI: 0.624, 0.988) were associated with reduced incidence of under-five mortality controlling for other variables in the model. Whereas older age of mother 35 to 39 (IRR = 5.252; 95%CI: 2.992, 9.218), 40 to 44 (IRR = 7.429; 95%CI: 4.188, 13.177), 45 to 49 (IRR = 8.697; 95%CI: 4.853, 15.585), being a resident of the Benishangul-gumuz region (IRR = 1.781; 95%CI: 1.303, 2.434), female household head (IRR = 1.256; 95%CI: 1.034, 1.525) were associated with an increased incidence of under-five mortality. Conclusion. The findings suggested that early age of mothers’ at first birth and old ages of mothers’, female household head and being uneducated were found to increase the incidence of the under-five mortality, whereas access to electricity and living with husband was statistically associated with reduced incidence of under-five mortality. The implication of this study is that policymakers and stakeholders should provide health education for mothers not to give birth at an earlier age and improve living standards to achieve sustainable development goals.

Determinants and Trends of Under-Five Child Mortality in Ethiopia: A Multi-level Logistic Modeling Approach

The burden of under-five mortality remains unevenly distributed. About 80 percent of under-five deaths occur in two regions, sub-Saharan Africa and South Asia. Ethiopia is among the six countries that account for half of the global under-five deaths. The aim of this study was to identify the significant socio-economic and demographic factors influencing under-five child mortality and evaluate the variation among the regional states of Ethiopia. In this study, the 2000, 2005, 2011 and 2016 EDHS data were used to describe the trend of under-five mortality in Ethiopia. The 2016 EDHS data have been used to analyze determinants and variation of under-five mortality by background characteristics. Single-level logistic regression and multilevel logistic regression models were used to identify the major risk factors of under-five mortality and regional variations in under-five child mortality in Ethiopia using the 2016 EDHS data. The results from single-level and multilevel logistic regression analyses showed that Sex of a child, Age of a child in month, Birth type, Birth order number, Number of Household size, Breastfeeding status, Educational level of mother’s, Place of residence and type of toilet facility had significant effects on under-five child mortality and there is variation of under-five child mortality from region to region. Conversely, preceding birth interval, wealth index Household, Source of drinking water and place of delivery were found insignificant. The results revealed variation of under-five child mortality from region to region. The multilevel logistic regression analysis result showed that the effects of breastfeeding varied across regions whereas the effects of other covariates on under-five child mortality remained fixed across regions.

Are socioeconomic status and type of residence critical risk factors of under-five mortality in Pakistan? Evidence from nationally representative survey

IntroductionPakistan had the highest mortality rate (75/1000) among under-five children in the South Asia, followed by Afghanistan (68/1000) in 2017. This paper examines whether socioeconomic status and type of residence are crucial risk factors of under-five mortality or not in Pakistan. MethodsThe bivariate and Cox Proportional Hazards regression were applied on a sample of 19,190 under-five children extracted from the Pakistan Demographic and Health Survey 2017–18 to examine the impacts of risk factors on under-five mortality. ResultsThe rich families were associated with 28% reduced risks (HR = 0.72; 95% CI: 0.64–0.81) of under-five mortality compared to the poor, and urban had 19% a lower risk (HR = 0.81; 95% CI: O.73–0.89) compared to rural (model 1). Educated mothers had 25 lower risk mothers (HR = 0.75; 95% CI:0.60–0.93), mothers aged 18 years and above at first birth had 21% lower risk (HR = 0.79; 95% CI: 0.65–0.95); mothers experiencing birth spacing of more than 3 years were associated with 44% lower risk (HR = 0.56; 95% CI: 0.45–0.69); average birth size was associated with 36% lower risk (HR = 0.64; 95% CI: 0.51–0.78), and female child with 11% reduced risk (HR = 0.64; 95% CI: 0.51–0.78), whereas socioeconomic status and type of residence were not statistically significant (model 2). ConclusionThe results call for revisiting healthcare policies and propose holistic programs for under-five mortality reduction in Pakistan.

Machine learning approach for predicting under-five mortality determinants in Ethiopia: evidence from the 2016 Ethiopian Demographic and Health Survey

There is a dearth of literature on the use of machine learning models to predict important under-five mortality risks in Ethiopia. In this study, we showed spatial variations of under-five mortality and used machine learning models to predict its important sociodemographic determinants in Ethiopia. The study data were drawn from the 2016 Ethiopian Demographic and Health Survey. We used three machine learning models such as random forests, logistic regression, and K-nearest neighbors as well as one traditional logistic regression model to predict under-five mortality determinants. For each machine learning model, measures of model accuracy and receiver operating characteristic curves were used to evaluate the predictive power of each model. The descriptive results show that there are considerable regional variations in under-five mortality rates in Ethiopia. The under-five mortality prediction ability was found to be between 46.3 and 67.2% for the models considered, with the random forest model (67.2%) showing the best performance. The best predictive model shows that household size, time to the source of water, breastfeeding status, number of births in the preceding 5 years, sex of a child, birth intervals, antenatal care, birth order, type of water source, and mother’s body mass index play an important role in under-five mortality levels in Ethiopia. The random forest machine learning model produces a better predictive power for estimating under-five mortality risk factors and may help to improve policy decision-making in this regard. Childhood survival chances can be improved considerably by using these important factors to inform relevant policies.

Geospatial variation and risk factors for under-five mortality in rural Misungwi, North-western Tanzania

This study aims to examine if, when holding socio-economic, bio-demographic and healthcare covariates constant, geospatial indicators help to explain variations in the under-five mortality rate across wards from a high focus district of Misungwi in Tanzania. Data were collected from a 2019 survey which canvassed 540 households with 471 women aged 15-49. A total of 737 live births that occurred during five years preceding the survey were analysed. Of all the children born, 46 had died before survey interviews were carried out. Under-5 mortality rates in 27 clusters were calculated. The spatial autocorrelation of under-five mortality rates was estimated by global Moran's index (I). Thematic maps were generated with these rates. The software TerraView 5.4.1 was used for spatial analysis. The results showed substantial cluster-level spatial variations in childhood mortality in the district. Among all the under-five children analysed, the mortality rate was 56 deaths per 1000 live births. The average global Moran's index (I) was I=0.05 for child mortality rate. All global Moran's indices showed p-values <0.05. Thematic maps showed clusters of villages with high rates located closer to streams and further from transport routes. The geospatial factors associated with mortality indicate variability due to exposure and transmission of infectious diseases. These results provide an improved understanding of district level under-five mortality and help in the execution of health policies. Key words: Geographic differentials, deaths, global Moran’s index, health management, Tanzania.

Under-Five Mortality and Associated Risk Factors in Rural Settings of Ethiopia: Evidences from 2016 Ethiopian Demographic and Health Survey

Background. Evidence shows that in Ethiopia, a gradual decrease of under-five mortality is observed, but it is still high in the rural settings of the country. We are motivated to investigate the socioeconomic, demographic, maternal and paternal, and child-related associated risk factors of under-five mortality given birth from rural resident mothers. Methods. Demographic and Health Survey data from Ethiopia (2016) were used for analysis. The chi-square test of association and logistic regression were used to determine the associated risk factors of under-five children mortality. Study Settings. Rural Ethiopia. Results. Secondary school and above completed fathers (AOR = 0.77; 95% CI: 0.63–0.94) and primary school completed mothers (AOR = 0.82; 95% CI: 0.72–0.93); multiple twin child (AOR = 4.50; 95% CI: 3.38–5.98); public sector delivery (AOR = 0.65; 95% CI: 0.55–0.76); had working of mother (AOR = 1.28; 95% CI: 1.16–1.42) and of father (AOR = 1.45; 95% CI: 1.25–1.69); mothers aged above 16 at first birth (AOR = 0.41; 95% CI: 0.37–0.45); breastfeeding (AOR = 0.60; 95% CI: 0.55–0.66); birth order of 2-3 (AOR = 1.18; 95% CI: 1.02–1.37); religious belief of Muslim (AOR = 1.20; 95% CI: 1.02–1.41); users of contraceptive method (AOR = 0.80; 95% CI: 0.71–0.90); vaccinated child (AOR = 0.52; 95% CI: 0.46–0.60); family size of 4–6 (AOR = 0.74; 95% CI: 0.63–0.86) and of seven and above (AOR = 0.44; 95% CI: 0.36–0.52); mother’s age group: aged 20–29 (AOR = 3.88; 95% CI: 3.08–4.90), aged 30–39 (AOR = 16.29; 95% CI: 12.66–20.96), and aged 40 and above (AOR = 55.97; 95% CI: 42.27–74.13); number of antenatal visits: 1–3 visits (AOR = 0.50; 95% CI: 0.43–0.58), and four and above visits (AOR = 0.46; 95% CI: 0.39–0.54); and preceding birth interval of 25–36 months (AOR = 0.55; 95% CI: 0.48–0.62) and above 36 months (AOR = 0.30; 95% CI: 0.26–0.34) are significant determinant factors of under-five mortality in rural settings. Conclusions. Differences in regions, educated parents, born in singleton, public sector delivery, nonavailability of occupation of parents, mothers older than 16 at first birth, breastfeeding, use of a contraceptive method, child vaccination, higher number of family size, repeated antenatal visits, and preceding birth interval play a significant role regarding the survival of under-five children. These, among other differences, should be addressed decisively as part of any upcoming strategic interventions to improve the survival of children in line with the target of 2030 Sustainable Development Goals (SDGs).

Injury- and Non-Injury-Related Factors Associated with Under Five Mortality in Iran: A Multilevel Study

Background: Unintentional and intentional injuries are the most important factors that cause disability and death among children throughout the world, especially in Iran. Objectives: This study aimed to assess injury- and non-injury-related factors associated with under five mortality (U5M) at individual and community levels in Iran. Methods: This population-based case-control study recruited a total of 2,228 mothers in Iran in 2017. Subjects were divided into three groups (428 as the case group, 664 as the control group 1, and 1,136 as the control group 2). Data were extracted from health records of mothers and interviews through a researcher-made checklist in the health center of eight provinces of Iran. The multilevel logistic regression model was used to evaluate risk factors of under-five mortality at individual and community levels. Data were analyzed using R V. 3.5.0 software. Results: Analysis showed gestational age (post-term and pre-term) (OR = 4.20, CI: 3.14 - 5.61 , P < 0.001), pregnancy interval (between 1 to 3 years) (OR = 3.05, CI: 2.15 - 4.13, P < 0.001), history of mother’s diseases (OR = 3.14, CI: 2.41 - 4.10, P < 0.001), living in urban area (OR = 1.51, CI: 1.16 - 1.97, P < 0.01) and worst life events among mothers (OR = 1.91, CI: 1.46 - 2.49, P < 0.001) were risk factors associated with under-five injury-related mortality. Moreover, women’s literacy (OR = 0.72, CI: 0.54 - 0.97, P < 0.05), mothers being housewife (OR = 0.76, CI: 0.61 - 0.93, P < 0.01) were protective factor at the community level (P < 0.05). Conclusions: This study revealed factors related to under-five mortality at individual and community levels, which most of them are preventable. Therefore, child mortality can be controlled by improving family health, mothers’ education, as well as conducting interventions at the community level.

Crucial predicting factors of under-five mortality in Sierra Leone

IntroductionSierra Leone includes in countries which exhibit the highest prevalence of under-five mortality in the world. A range of factors are known to have challenged the under-five survival in the country; some comprise outbreak of epidemics, socioeconomic inequalities, regional disparities, and unsuccessful implementation of healthcare initiatives. The present study aims to identify crucial predictors of under-five survival. MethodsThis paper used the Sierra Leone Demographic and Health Survey (SLDH, 2013). A Cox Proportional Hazards Model was applied to the sample of 24,742 children to analyze the adjusted and unadjusted hazards ratio of crucial risk factors of under-five mortality. ResultsThe results show that birth interval and birth size are leading risk factors of under-five mortality in Sierra Leone. A birth spacing exceeding three years is associated with the lowest risk compared to 2–3 years and lesser than two years. The average or larger birth size has the lowest hazards followed by smaller than average, and the magnitude of the effect remains the same in adjusted and unadjusted models. The wealth status is a crucial predictor only in the unadjusted model. Mother's age, sex of the child, and a number of children in the household are significant covariates. ConclusionGiven the research findings, this study recommends for re-orientation of reproductive healthcare strategies to target the younger mother and birth-spacing, and integration of nutrition-related interventions with the maternal healthcare initiatives to influence the child birth-size.

Proximate Determinants of Under-Five Mortality in Ethiopia: Using 2016 Nationwide Survey Data.

IntroductionAlthough there has been a remarkable decline in under-five mortality through the decades, it is still highest in socio-economically disadvantaged countries, including Ethiopia. The benefits of reducing under-five mortality have been highly emphasized in the ambitious target of Sustainable Development Goals. The risk factors of under-five mortality have not been exhaustively researched in Ethiopia using recent nationwide survey data.ObjectiveThis study aimed to determine the risk factors of under-five mortality using the recent nationwide survey data.MethodThe data source for this study was the 2016 Ethiopian Demographic and Health Survey. Bivariate and multivariable logistic regression analysis was conducted and statistical significance was declared at p value < 0.05.ResultsThe data for a total of 10,641 under-five children were analyzed and the under-five mortality rate was 67 per 1000 live births in this study. In the final model, rural residence (AOR=2.0, [1.20, 3.30], P=0.008), mothers who gave birth with preceding birth intervals of shorter than 24 months (AOR=2.12, CI=[1.72, 2.61], P<0.000), multiple births (AOR=4.74, CI=[3.34, 6.69], P<0.000), very small size of child at birth (AOR=1.43, CI= [1.10, 1.85], P=0.007), and being male (AOR=1.30, CI=[1.07, 1.57], P<0.008) showed significant association with under-five mortality compared to their counterparts.ConclusionUnder-five mortality was significantly associated with place of residence, preceding birth interval, plurality, size of child at birth, and sex of the child. Thus, special emphasis should be placed on children with rural residence, preceding birth interval of shorter than 24 months, very small size of the child at birth, and male children.

Risk factors for under-five mortality in Ethiopia: Evidence from the 2016 Ethiopian Demographic and Health Survey

Background. The under-five child mortality (U5CM) rate is the most important sensitive indicator of the socioeconomic and health status of a community, and the overall development of a nation. Despite the world having made substantial progress in reducing child mortality since 1990, the global U5CM rate was 41 per 1 000 in 2016. The rate is higher in Ethiopia than in several other low- and middle-income countries. Objectives. To estimate the effects of socioeconomic and demographic factors on U5CM in Ethiopia. Methods. A community-based cross-sectional study was conducted on 10 641 under-five children. The 2016 Ethiopian Demographic and Health Survey data were used for this research. Binary logistic regression was employed to identify factors affecting the U5CM rate. Results. The U5CM rate was 60 deaths per 1 000 live births. Children who were delivered at home (adjusted odds ratio ( aOR) 1.30; 95% CI 1.04 - 1.63) and male (aOR 1.36; 95% CI 1.15 - 1.60) were at an increased risk of death. Children whose family size was between 1 and 3 (aOR 5.54; 95% CI 4.08 - 7.54), and 4 and 6 (aOR 1.94; 95% CI 1.55 - 2.43) were more likely to die before age 5 than those whose family size was ≥6. First-born (aOR 0.49; 95% CI 0.36 - 0.67), second- or third-born (aOR 0.51; 95% CI 0.39 - 0.67) and fourth- or fifth-born (aOR 0.71; 95% CI 0.56 - 0.91) children were less likely to die than those who were sixth-born and above. Similarly, singleton children (aOR 0.20; 95% CI 0.15 - 0.28), children residing in urban communities (aOR 0.55; 95% CI 0.40 - 0.76) and children whose families had protected sources of water (aOR 0.84; 95% CI 0.71 - 0.99) had reduced risks of death compared with their respective counterparts. Conclusions. The present study identified risk factors for under-five mortality in Ethiopia. Programmes to reduce under-five mortality in Ethiopia must focus on the place of delivery, households with unprotected sources of drinking water and families residing in rural areas.

Socioeconomic factors contributing to under-five mortality in sub-Saharan Africa: a decomposition analysis

BackgroundIn sub-Saharan Africa, socioeconomic factors such as place of residence, mother’s educational level, or household wealth, are strongly associated with risk factors of under-five mortality (U5M) such as health behavior or exposure to diseases and injuries. The aim of the study was to assess the relative contribution of four known socioeconomic factors to the variability in U5M in sub-Saharan countries.MethodsThe study was based on birth histories from the Demographic and Health Surveys conducted in 32 sub-Saharan countries in 2010–2016. The relative contribution of sex of the child, place of residence, mother’s educational level, and household wealth to the variability in U5M was assessed using a regression-based decomposition of a Gini-type index.ResultsThe Gini index – measuring the variability in U5M related to the four socioeconomic factors – varied from 0.006 (95%CI: 0.001–0.010) in Liberia 2013 to 0.034 (95%CI: 0.029–0.039) in Côte d’Ivoire 2011/12. The main contributors to the Gini index (with a relative contribution higher than 25%) were different across countries: mother’s educational level in 13 countries, sex of the child in 12 countries, household wealth in 11 countries, and place of residence in 8 countries (in some countries, more than one main contributor was identified).ConclusionsFactors related to socioeconomic status exert varied effects on the variability in U5M in sub-Saharan African countries. The findings provide evidence in support of prioritizing intersectoral interventions aiming at improving child survival in all subgroups of a population.