Predictive model and determinants of under-five child mortality: evidence from the 2014 Ghana demographic and health survey

The effect of the implementation of the international code of marketing of breast-milk substitutes on child mortality in Ghana and Tanzania

OBJECTIVE

The International Code of Marketing of Breast-Milk Substitutes is an important instrument to protect and promote appropriate infant and young child feeding and the safe use of commercial milk formulas. Ghana and Tanzania implemented the Code into national legislation in 2000 and 1994, respectively. We aimed to estimate the effects of the Code implementation on child mortality (CM) in both countries.

SETTING

The countries analysed were Ghana and Tanzania.

PARTICIPANTS

For CM and HIV rates, data from the Institute for Health Metrics and Evaluation from up to 2019 were used. Data for income and skilled birth rates were retrieved from the World Bank, for fertility from the World Population Prospects, for vaccination from the Global Health Observatory and for employment from the International Labour Organization.

DESIGN

We used the synthetic control group method and performed placebo tests to assess statistical inference. The primary outcomes were CM by lower respiratory infections, mainly pneumonia, and diarrhoea and the secondary outcome was overall CM.

RESULTS

One-sided inference tests showed statistically significant treatment effects for child deaths by lower respiratory infections in Ghana (P = 0·0476) and Tanzania (P = 0·0476) and for diarrhoea in Tanzania (P = 0·0476). More restrictive two-sided inference tests showed a statistically significant treatment effect for child deaths by lower respiratory infections in Ghana (P = 0·0476). No statistically significant results were found for overall CM.

CONCLUSION

The results suggest that the implementation of the Code in both countries had a potentially beneficial effect on CM due to infectious diseases; however, further research is needed to corroborate these findings.

Factors associated with under-five mortality in Rwanda: An analysis of the Rwanda Demographic and Health Survey 2020

Despite global and Rwandan progress in reducing under-five mortality, the risk of children dying before their fifth birthday persists, necessitating intensified research on determinants. Thus, this study analyzed the birth history data to shed light on the underlying causes of under-five mortality in Rwanda. The study is a secondary analysis of data sourced from the 2020 Rwanda Demographic and Health Survey (RDHS) cross-sectional design. Using SPSS, the data was cleaned, recoded, and weighted, with descriptive and inferential statistics applied. The dependent variable was the child's living status, while independent variables included socio-demographic, media exposure status of mothers, child, and environmental factors. A total of 10267 under-five children of all interviewed mothers were included in the final analysis, of which 12.3% (1260) died. Maternal age (25-34 years: AOR = 1.514, 95% CI = 1.130-2.029, p = 0.005; 45+: AOR = 13.226, 95% CI = 9.253-18.905, p<0.001), occupational status (agricultural workers and other services), and three or more births within five years (AOR = 1.895, 95% CI = 1.433-2.508, p<0.001) significantly increase the risk of under-five mortality. Conversely, maternal education (primary: AOR = 0.821, p = 0.023; secondary: AOR = 0.533, p<0.001; higher: AOR = 0.365, p = 0.010) and higher wealth indexes (middle: AOR = 0.743, p = 0.001; rich: AOR = 0.612, p<0.001), as well as current breastfeeding (AOR = 0.524, 95% CI = 0.455-0.603, p-value <0.001), are associated with lower under-five mortality. Child sex significantly impacts under-five mortality (AOR = 0.873, 95% CI = 0.770-0.991, p = 0.035), favoring females over males. Conversely, multiple birth type children face higher under-five mortality (AOR = 3.541, 95% CI = 2.727-4.599, p<0.001) compared to singletons. Children in the northern (AOR = 1.478, 95% CI = 1.086-2.011, p = 0.013) and eastern (AOR = 1.470, 95% CI = 1.097-1.971, p = 0.010) regions are more susceptible to mortality compared to those in the central (Kigali) region. Additionally, under-five mortality is higher when using water from tanks and other sources (AOR = 2.240, 95% CI = 1.471-3.411, p<0.001) than piped water. This study identifies crucial factors linked to under-five mortality, underscoring the importance of prioritizing them in interventions to enhance Rwandan under-five survival rates.

Assessment of Neonatal Mortality and Associated Hospital-Related Factors in Healthcare Facilities Within Sunyani and Sunyani West Municipal Assemblies in Bono Region, Ghana

Objectives

Ghana's quest to reduce neonatal mortality, in hospital facilities and communities, continues to be a nightmare. The pursuit of achieving healthy lives and well-being for neonates as enshrined in Sustainable Development Goal three lingered in challenging hospital facilities and communities. Notwithstanding that, there have been increasing efforts in that direction. This study examines the contributing factors that hinder the fight against neonatal mortality in all hospital facilities in the Sunyani and Sunyani West Municipal Assemblies in Bono Region, Ghana.

Methods

The study utilized neonatal mortality data consisting of neonatal deaths, structural facility related variables, medical human resources, types of hospital facilities and natal care. The data was collected longitudinally from 2014 to 2019. These variables were analysed using the negative binomial hurdle regression (NBH) model to determine factors that contribute to this menace at the facility level. Cause-specific deaths were obtained to determine the leading causes of neonatal deaths within health facilities in the two municipal assemblies.

Results

The study established that the leading causes of neonatal mortality in these districts are birth asphyxia (46%), premature birth (33%), neonatal sepsis (11%) and neonatal jaundice (7%). The NBH showed that neonatal mortality in hospital facilities depend on the number of incubators, monitoring equipment, hand washing facilities, CPAPb machines, radiant warmers, physiotherapy machines, midwives, paediatric doctors and paediatric nurses in the hospital facility.

Conclusions

Early management of neonatal sepsis, birth asphyxia, premature birth and neonatal infections is required to reduce neonatal deaths. The government and all stakeholders in the health sector should provide all hospital facilities with the essential equipment and the medical human resources necessary to eradicate the menace. This will make the realization of Sustainable Development Goal three, which calls for healthy lives and well-being for all, a reality.

Investigation of Factors Influencing Infant Mortality at Greater Accra Regional Hospital, Ghana

Background

Annually, 5.4 million children under five face mortality, with 2.5 million deaths in the first month, 1.6 million between one and eleven months, and 1.3 million aged one to four. Despite global strides, sub-Saharan Africa, including Ghana, grapples with persistent high child mortality. This study employs statistical methods to pinpoint factors driving under-five mortality in the Greater Accra Regional Hospital.

Methods

The data was acquired from Greater Accra Regional Hospital, Ghana, spanning January to December 2020. The data comprised all under-five deaths recorded in the hospital in 2020. The statistical tools employed were the chi-square test of association and the multinomial logistic regression model.

Results

In 2020, there were 238 cases of under-five mortality recorded in the hospital, with males constituting the majority (55%). About 85% of these cases occurred within the first month of birth, primarily attributed to respiratory distress, prematurity, and sepsis. Notably, meconium aspiration was the least common among grouped diagnoses. The test of association and multinomial logistic model emphasised the child's age, birth type, and weight at birth as significant factors influencing child mortality. Conversely, attributes like sex, marital status, and mother's age displayed no notable association with the diagnosis of death.

Conclusion

The study on child mortality at the Greater Accra Regional Hospital unveils key factors shaping child health outcomes, emphasising the role of age, birth type, and weight. While specific demographics show no significant association, identified predictors are vital for targeted interventions. Proposed strategies encompass education programs, improved care, birthing practices, and data-driven policies.

Application of machine learning methods for predicting under-five mortality: analysis of Nigerian demographic health survey 2018 dataset

BACKGROUND

Under-five mortality remains a significant public health issue in developing countries. This study aimed to assess the effectiveness of various machine learning algorithms in predicting under-five mortality in Nigeria and identify the most relevant predictors.

METHODS

The study used nationally representative data from the 2018 Nigeria Demographic and Health Survey. The study evaluated the performance of the machine learning models such as the artificial neural network, k-nearest neighbourhood, Support Vector Machine, Naïve Bayes, Random Forest, and Logistic Regression using the true positive rate, false positive rate, accuracy, precision, F-measure, Matthew's correlation coefficient, and the Area Under the Receiver Operating Characteristics.

RESULTS

The study found that machine learning models can accurately predict under-five mortality, with the Random Forest and Artificial Neural Network algorithms emerging as the best models, both achieving an accuracy of 89.47% and an AUROC of 96%. The results show that under-five mortality rates vary significantly across different characteristics, with wealth index, maternal education, antenatal visits, place of delivery, employment status of the woman, number of children ever born, and region found to be the top determinants of under-five mortality in Nigeria.

CONCLUSIONS

The findings suggest that machine learning models can be useful in predicting U5M in Nigeria with high accuracy. The study emphasizes the importance of addressing social, economic, and demographic disparities among the population in Nigeria. The study's findings can inform policymakers and health workers about developing targeted interventions to reduce under-five mortality in Nigeria.

Time to death and its determinants of under-five children in rural Ethiopia by using shared frailty

Under-five (U5M) is one of the most significant and sensitive measures of the community's health. Children who live in rural areas are more likely than those who live in urban areas to die before the age of five. Therefore, the study aimed to assess the Survival status of under-five mortality and its determinants in rural Ethiopia. The 2019 Ethiopia Mini Demographic and Health Survey was used in this study as a secondary source (EMDHS). A total of 4426 weighted under-five children were included in the study. To determine survival time and identify predictors of death among children under the age of five, the Cox's gamma shared frailty model and the Kaplan Meier model, respectively, were used. An adjusted Hazard Ratio (AHR) along with a 95% Confidence Interval (CI) were used to measure the size and direction of the association. The Study showed that in rural Ethiopia, 6.03% of children died before celebrating their first birthday. The median age of under-five mortality in rural Ethiopia was estimated to be 29 Months. The hazard of death among under-five children and those who had given birth to two children in the last five years was 4.99 times less likely to be at risk of dying than those who had given birth to one Child in the previous five years (AHR 4.99, 95% CI 2.97, 8.83). The Study Concluded that under-five mortality remained high in rural Ethiopia. In the final model, the Age of Mothers, Sex of Household, Breastfeeding, Types of Birth, Sex of Child, Educational Level of Mothers, Wealth Index, Child ever born, Marital Status, and Water Source were significant predictors of under-five mortality. Twins and children who are not breastfed should receive additional attention, along with improving water resources for households and mothers income.

Prevalence and predictors of infant and young child feeding practices in sub-Saharan Africa

BACKGROUND

This study assessed the prevalence and predictors of minimum dietary diversity (MDD), minimum meal frequency (MMF), and minimum acceptable diet (MAD) in sub-Saharan Africa (SSA).

METHODS

A sample of 87 672 mother-child pairs from the 2010-2020 Demographic and Health Surveys of 32 countries in SSA was used. Multilevel binary logistic regression analysis was carried out to examine the predictors of MDD, MMF, and MAD. Percentages and adjusted odds ratios (aORs) with a 95% confidence interval (CI) were used to present the findings.

RESULTS

The prevalence of MDD, MMF, and MAD in SSA were 25.3% (95% CI 21.7 to 28.9), 41.2% (95% CI 38.8 to 43.6), and 13.3% (95% CI 11.6 to 15.0), respectively. Children aged 18-23 months were more likely to have MDD and MAD but less likely to have MMF. Children of mothers with higher education levels were more likely to have MDD, MMF, and MAD. Children who were delivered in a health facility were more likely to have MDD and MAD but less likely to have MMF.

CONCLUSIONS

Following the poor state of complementary feeding practices for infants and young children, the study recommends that regional and national policies on food and nutrition security and maternal and child nutrition and health should follow the internationally recommended guidelines in promoting, protecting, and supporting age-appropriate complementary foods and feeding practices for infants and young children.

Determinants of child survival practice among caregivers in internally displaced persons' camps in Abuja Municipal Area Council, Nigeria

BACKGROUND

Child survival remains a major public health challenge in the sub-Saharan region of Africa, especially Nigeria. The Boko Haram crisis, which has aggravated this, has led to the displacement of many people in the north-eastern region, including children under five. This study investigated the determinants of child survival practice among caregivers in internally displaced persons' (IDP) camps in Abuja Municipal Area Council (AMAC), Nigeria.

METHODOLOGY

A cross-sectional design was used to collect data on determinants of child survival practice from 312 caregivers in five purposively selected IDP camps in AMAC using the snowball sampling technique. Data were analysed using univariate, bivariate, and multivariate statistics at 5% level of significance.

RESULTS

The mean age of respondents was 29.6 ± 6.72 years. There was a significant (p < 0.05) relationship between the predisposing, reinforcing, enabling and environmental factors studied and child survival practice. Findings also indicated that all factors were significant (p < 0.05) predictors of child survival practice with the reinforcing factor being the major predictor (ß = 0.38; t = 6.08).

CONCLUSION

Attention needs to be paid to all factors, particularly the reinforcing factor of social support in order to promote optimal child survival practice among caregivers in AMAC IDP camps. Collaboration with social work professionals would be an added benefit to enhance social support.

Predictors of mortality among under-five children in rural Ethiopia: a cross sectional study

BACKGROUND

Under-five child mortality (UFCM) is one of the major significant and sensitive indicators of the health status of the public. Although the world has seen a remarkable and substantial decrease in UFCM since 1990, its progression rate still remains alarmingly high in Sub-Saharan African (SSA) countries, particularly in Ethiopia. Therefore, this study aimed to assess associations between mortality and under-five children in rural Ethiopia.

METHODS

This study used a secondary data analysis of the 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) report. A total of 4,425 under-five children were included in the final analysis. The Kaplan-Meier (K-M) and Cox proportional hazard (PH) model analyses were utilized to estimate survival time and investigate the major predictors of mortality in under-five children, respectively. An adjusted hazard ratio (AHR) along with a 95% confidence interval (CI) was employed to measure the association size and direction of the association (STATA 12).

RESULTS

The study showed that 6.2% (95% CI: 5.43, 6.86) of children died beforehand celebrating their fifth birthday in rural Ethiopia. The multivariable Cox PH regression model analysis revealed associations of large spacing preceding birth interval (16-26 months) (AHR = 0.61; 95% CI: (0.402-0.920)), 27-38 months (AHR = 0.72; 95% CI: (0.496-1.03)), and ≥ 39 months, multiple births (AHR = 3.9; 95% CI: (2.77-5.62)), being breastfeeding (AHR = 0.13; 95% CI: (0.099-0.162)), and unvaccinated child (AHR = 11.6; 95% CI: (1.62-83.1)) were significant associations of under-five children mortality.

CONCLUSIONS

In this study, the UFCM rate was present, with 6.2% in the rural areas of Ethiopia. The birth type, preceding birth interval, vaccination of the child, and breastfeeding are identified as significant associations with under-five child mortality in rural Ethiopia. Therefore, public health interventions should be given attention to multiple births, unvaccinated, and non-breastfeeding children, as well as mothers' better encouragement to have a large spacing preceding the birth interval. Moreover, investigators should conduct continuous research on UFCM, which is imperative to provide current information and inform interventions in a timely manner.

Better individual-level risk models can improve the targeting and life-saving potential of early-mortality interventions

Infant mortality remains high and uneven in much of sub-Saharan Africa. Even low-cost, highly effective therapies can only save lives in proportion to how successfully they can be targeted to those children who, absent the treatment, would have died. This places great value on maximizing the accuracy of any targeting or means-testing algorithm. Yet, the interventions that countries deploy in hopes of reducing mortality are often targeted based on simple models of wealth or income or a few additional variables. Examining 22 countries in sub-Saharan Africa, we illustrate the use of flexible (machine learning) risk models employing up to 25 generally available pre-birth variables from the Demographic and Health Surveys. Using these models, we construct risk scores such that the 10 percent of the population at highest risk account for 15-30 percent of infant mortality, depending on the country. Successful targeting in these models turned on several variables other than wealth, while models that employ only wealth data perform little or no better than chance. Consequently, employing such data and models to predict high-risk births in the countries studied flexibly could substantially improve the targeting and thus the life-saving potential of existing interventions.

Geographic disparities in the time to under-five mortality in Ghana

Globally, there has been tremendous advancement in medicine and child healthcare with increased life expectancy. That notwithstanding, the risk of under-five mortality ─ children dying before their fifth birthday remains relatively high in countries in Sub-Saharan Africa such as Ghana. In Ghana, under-five mortality remains a major public health problem that requires significant policy interventions. Using data from the 2017 Maternal Health Survey (n = 4785), we examined the geographic disparities in the time to under-five mortality in Ghana. The Kaplan Meier estimator showed significant (Log-rank: p< 0.001) rural-urban differences in the time to under-five mortality in Ghana. A disaggregated cox proportional hazards analysis showed that despite wide consensus that children in urban areas have a high survival rate, children in urban areas in northern regions of Ghana, especially the Upper West (HR = 4.40, p < 0.05) and Upper East (HR = 5.37, p < 0.01) Regions were significantly at increased risk of dying before the age of five compared to children in urban areas in the Greater Accra Region. A rural-urban comparison showed that children born in rural areas in all the other regions of Ghana were at a higher risk of dying before the age of five when compared to their counterparts in the rural areas of Greater Accra Region. Other factors such as sex of child, mothers' age and use of the internet, number of household members, ethnicity and household wealth were significantly associated with the timing of under-five mortality in Ghana. Healthcare policies and programs such as immunizations and affordable child healthcare services should be prioritized especially in rural areas of regions with a high risk of child mortality. Also, there is a need to improve healthcare delivery in urban areas, particularly in northern Ghana, where deplorable healthcare service infrastructure and delivery coupled with high poverty rates put children at risk of dying before their fifth birthday.

Effects of household access to water, sanitation, and hygiene services on under-five mortality in Sub-Saharan Africa

Introduction

Sub-Saharan Africa has the highest under-five mortality rate and is among the regions where people have the least access to adequate Water, Sanitation, and Hygiene (WASH) services. The work aimed to investigate the effects of WASH conditions faced by children on under-five mortality in Sub-Saharan Africa.

Methods

We carried out secondary analyses using the Demographic and Health Survey datasets of 30 countries in Sub-Saharan Africa. The study population consisted of children born within 5 years preceding the selected surveys. The dependent variable was the child's status (1 = deceased versus 0 = alive) on the survey day. The individual WASH conditions in which children live were assessed in their immediate environment, i.e., at the level of their households of residence. The other explanatory variables were related to the child, mother, household, and environment. Following a description of the study variables, we identified the predictors of under-five mortality using a mixed logistic regression.

Results

The analyses involved 303,985 children. Overall, 6.36% (95% CI = 6.24-6.49) of children died before their fifth birthday. The percentage of children living in households with access to individual basic WASH services was 58.15% (95% CI = 57.51-58.78), 28.18% (95% CI = 27.74-28.63), and 17.06% (95% CI = 16.71-17.41), respectively. Children living in households using unimproved water facilities (aOR = 1.10; 95% CI = 1.04-1.16) or surface water (aOR = 1.11; 95% CI = 1.03-1.20) were more likely to die before five than those coming from households with basic water facilities. The risk of under-five mortality was 11% higher for children living in households with limited sanitation facilities (aOR = 1.11; 95% CI = 1.04-1.18) than for those with basic sanitation services. We found no evidence to support a relationship between household access to hygiene services and under-five mortality.

Conclusion

Interventions to reduce under-five mortality should focus on strengthening access to basic water and sanitation services. Further studies are needed to investigate the contribution of access to basic hygiene services on under-five mortality.

The Interaction Effect of Birth Spacing and Maternal Healthcare Services on Child Mortality in Pakistan

There is widespread agreement that improved health should be regarded as a means and an end in the context of the development process. The health of the populace and the equitable provision of healthcare are two indicators of a society's level of development. A variety of factors influences child mortality. This study investigated the causes of child death and the interaction effect of birth spacing (B.S.) and maternal health care services (MHCS) on child mortality. Using SPSS version 20, we used the Pakistan Demographic and Health Survey (PDHS) 2017-2018 data set to investigate the associated factors of child mortality and the moderating influence of birth spacing using binary logistic regression. The outcome variable is categorical with two categories. The findings indicated that the risk of infant death decreased with adequate B.S. between two pregnancies and access to maternal health care services. Birth spacing was found to moderate the link between access to maternal health care services (MHCS) and child mortality. Our research leads us to conclude that the amount of time between children's births significantly reduces infant mortality. When the birth spacing is at least 33 months, the relationship between maternal health care services and child mortality becomes more evident and negative.

Prevalence and risk factors associated with under-five mortality in the Solomon Islands: an investigation from the 2015 Solomon Islands demographic and health survey data

Background

Annually, over five million children die before their fifth birthday worldwide, with 98% of these deaths occurring in low-and middle-income countries. The prevalence and risks for under-five mortality are not well-established for the Solomon Islands.

Methods

We used the Solomon Islands Demographic and Health Survey 2015 data (SIDHS 2015) to estimate the prevalence and risk factors associated with under-five mortality.

Findings

Neonatal, infant, child and under-five mortality prevalence were 8/1000, 17/1000, 12/1000 and 21/1000 live births, respectively. After adjustment for potential confounders, neonatal mortality was associated with no breastfeeding [aRR 34.80 (13.60, 89.03)], no postnatal check [aRR 11.36 (1.22, 106.16)], and Roman Catholic [aRR 3.99 (1.34, 11.88)] and Anglican [aRR 2.78 (0.89, 8.65); infant mortality to no breastfeeding [aRR 11.85 (6.15, 22.83)], Micronesian [aRR 5.54 (1.67, 18.35)], and higher birth order [aRR 2.00 (1.03, 3.88)]; child mortality to multiple gestation [aRR 6.15 (2.08, 18.18)], Polynesian [aRR 5.80 (2.48, 13.53)], and Micronesian [aRR 3.65 (1.46, 9.10)], cigarette and tobacco [aRR 1.77 (0.79, 3.96)] and marijuana use [aRR 1.94 (0.43, 8.73)] and rural residence [aRR 1.85 (0.88, 3.92)]; under-five mortality to no breastfeeding [aRR 8.65 (4.97, 15.05)], Polynesian [aRR 3.23 (1.09, 9.54)], Micronesian [aRR 5.60 (2.52, 12.46)], and multiple gestation [aRR 3.34 (1.26, 8.88)]. Proportions of 9% for neonatal and 8% of under-five mortality were attributable to no maternal tetanus vaccination.

Interpretation

Under-five mortality in the Solomon Islands from the SIDHS 2015 data was attributable to maternal health, behavioural, and sociodemographic risk factors. We recommended future studies to confirm these associations.

Funding

No funding was declared to support this study directly.

Social determinants of stunting in Malay children aged <5 years in Malaysia

OBJECTIVE

This study aims to assess social determinants of stunting among children aged <5 y within the Malay ethnicity in Malaysia.

METHODS

This study used data from the National Health and Morbidity Survey 2016: Maternal and Child Health. It includes a sample of 10 686 children, ages 0 to 59 mo, of Malay ethnicity. Height-for-age z score was determined based on the World Health Organization Anthro software. A binary logistic regression model was used to examine the association between the selected social determinants and the occurrence of stunting.

RESULTS

About 22.5% of children aged <5 y of Malay ethnicity were stunted. For those ages 0 to 23 mo, stunting is more prevalent in boys, in rural areas, and in those who have screen exposure, whereas a reduction of stunting was observed for those children whose mothers work in the private sector and in those who consume formula milk and meat. As for those ages 24 to 59 mo, there was a higher prevalence of stunting for those with self-employed mothers and reduced prevalence in children with hygienic waste disposal practices as well as those who play with toys.

CONCLUSIONS

The prevalence of stunting among children of Malay ethnicity aged <5 in Malaysia necessitates immediate intervention. It is pertinent to facilitate early identification of those children at risk of stunting for additional care to promote healthy growth.

How Zambia reduced inequalities in under-five mortality rates over the last two decades: a mixed-methods study

BACKGROUND

Zambia experienced a major decline in under-five mortality rates (U5MR), with one of the fastest declines in socio-economic disparities in sub-Saharan Africa in the last two decades. We aimed to understand the extent to which, and how, Zambia has reduced socio-economic inequalities in U5MR since 2000.

METHODS

Using nationally-representative data from Zambia Demographic Health Surveys (2001/2, 2007, 2013/14 and 2018), we examined trends and levels of inequalities in under-five mortality, intervention coverage, household water and sanitation, and fertility. This analysis was integrated with an in-depth review of key policy and program documents relevant to improving child survival in Zambia between 1990 and 2020.

RESULTS

The under-five mortality rate (U5MR) declined from 168 to 64 deaths per 1000 live births between 2001/2 and 2018 ZDHS rounds, particularly in the post-neonatal period. There were major reductions in U5MR inequalities between wealth, education and urban-rural residence groups. Yet reduced gaps between wealth groups in estimated absolute income or education levels did not simultaneously occur. Inequalities reduced markedly for coverage of reproductive, maternal, newborn and child health (RMNCH), malaria and human immunodeficiency virus interventions, but less so for water or sanitation and fertility levels. Several policy and health systems drivers were identified for reducing RMNCH inequalities: policy commitment to equity in RMNCH; financing with a focus on disadvantaged groups; multisectoral partnerships and horizontal programming; expansion of infrastructure and human resources for health; and involvement of community stakeholders and service providers.

CONCLUSION

Zambia's major progress in reducing inequalities in child survival between the poorest and richest people appeared to be notably driven by government policies and programs that centrally valued equity, despite ongoing gaps in absolute income and education levels. Future work should focus on sustaining these gains, while targeting families that have been left behind to achieve the sustainable development goal targets.

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

BACKGROUND

Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20,000 deaths in children annually of which 25% are those aged < 5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, the study produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities.

METHODS

This modelling and web-based mapping study utilized data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. The study produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations.

RESULTS

In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086-6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017-0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079-0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7% to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates.

CONCLUSION

The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by programme managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

Subnational variations in electricity access and infant mortality: Evidence from Ghana

Objectives

The study investigated the relationship between electricity access and infant mortality at the subnational level in Ghana, controlling for correlates such as birth interval, children living with both parents, women's education, and income distribution.

Methods

The study employed a pooled cross-section regression approach using data from the Ghana Demographic and Health Survey (GDHS) for 10 administrative regions from 1993 to 2014. The GDHS is a detailed data set that provides comprehensive information on households and their socio-economic and demographic characteristics in Ghana.

Results

The results show that in regions with low incidence of infant mortality, a 10% improvement in electricity access reduces infant death by 11.8 per 1,000 live births, whereas in high mortality regions, improvement in electricity access has no impact on infant death. Birth interval reduces the risk of infant death in low mortality regions but not in high mortality regions. Children living with both parents have a high probability of survivorship in high mortality regions. Women's median years of education lowers the likelihood of infant death in high mortality regions but increases the likelihood in low mortality regions. Wealth distribution is inconsequential for infant death in low mortality regions, but in high mortality regions, both the wealthiest and the poorest experienced significant decline in infant death.

Conclusions

The findings underscore the fruitfulness of investigating the effects of electricity access and other correlates on infant mortality at the subnational level. The study recommends that the provision of reliable access to electricity is needed to improve infant mortality rates. However, policies that seek to improve access to reliable electricity should be implemented together with health infrastructure development policies, especially in the regions with high infant mortality rates, for electricity access to have the desired effect.

Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh

BACKGROUND

Several studies have identified factors influencing infant mortality, but, to the best of knowledge, no studies assessed the factors considering unequal effects on different survival times of infant mortality in Bangladesh. In this study, it was examined how a set of covariates behaves on different quantile survival times related with the infant mortality.

METHODS

Data obtained from Bangladesh multiple indicator cluster survey (BMICS), 2019 have been used for purpose of the study. A total of 9,183 reproductive women were included in the study who gave their most recent live births within two years preceding the survey. Kaplan-Meier product limit approach has been applied to find the survival probabilities for the infant mortality, and the log-rank test has also been used to observe the unadjusted association between infant mortality and selected covariates. To examine the unequal effects of the covariates on different quantile survival time of infant mortality, the Laplace survival regression model has been fitted. The results obtained from this model have also been compared with the results obtained from the classical accelerated failure time (AFT) and Cox proportional hazard (Cox PH) models.

RESULTS

The infant mortality in Bangladesh is still high which is around 28 per 1000 live births. In all the selected survival regression models, the directions of regression coefficients were similar, but the heterogenous effects of covariates on survival time were observed in quantile survival model. Several correlates such as maternal age, education, gender of index child, previous birth interval, skilled antenatal care provider, immediate breastfeeding etc. were identified as potential factors having higher impact on initial survival times.

CONCLUSION

Infant mortality was significantly influenced by the factors more in the beginning of the infant's life period than at later stages, suggesting that receiving proper care at an early age will raise the likelihood of survival. Policy-making interventions are required to reduce the infant deaths, and the study findings may assist policy makers to revise the programs so that the sustainable development goal 3.2 can be achieved in Bangladesh.

Geographic variation and factors associated with under-five mortality in Ethiopia. A spatial and multilevel analysis of Ethiopian mini demographic and health survey 2019

BACKGROUND

The distribution of under-five mortality (U5M) worldwide is uneven and the burden is higher in Sub-Saharan African countries, which account for more than 53% of the global under-five mortality. In Ethiopia, though U5M decreased substantially between 1990 and 2019, it remains excessively high and unevenly distributed. Therefore, this study aimed to assess geographic variation and factors associated with under-five mortality (U5M) in Ethiopia.

METHODS

We sourced data from the most recent nationally representative 2019 Ethiopian Mini-Demographic and Health Survey for this study. A sample size of 5,695 total births was considered. Descriptive, analytical analysis and spatial analysis were conducted using STATA version 16. Both multilevel and spatial analyses were employed to ascertain the factors associated with U5M in Ethiopia.

RESULTS

The U5M was 5.9% with a 95% CI 5.4% to 6.6%. Based on the multivariable multilevel logistic regression model results, the following characteristics were associated with under-five mortality: family size (AOR = 0.92, 95% CI: 0.84,0.99), number of under-five children in the family (AOR = 0.17, 95% CI: 0.14, 0.21), multiple birth (AOR = 14.4, 95% CI: 8.5, 24.3), children who were breastfed for less than 6 months (AOR = 5.04, 95% CI: 3.81, 6.67), people whose main roof is palm (AOR = 0.57, 95% CI: 0.34, 0.96), under-five children who are the sixth or more child to be born (AOR = 2.46, 95% CI: 1.49, 4.06), institutional delivery (AOR = 0.57, 95% CI: 0.41, 0.81), resident of Somali and Afar region (AOR = 3.46, 95% CI: 1.58, 7.55) and (AOR = 2.54, 95% CI: 1.10, 5.85), respectively. Spatial analysis revealed that hot spot areas of under-five mortality were located in the Dire Dawa and Somali regions.

CONCLUSION

Under-five mortality in Ethiopia is high and unacceptable when compared to the 2030 sustainable development target, which aims for 25 per 1000 live births. Breastfeeding for less than 6 months, twin births, institutional delivery and high-risk areas of under-five mortality (Somali and Dire Dawa) are modifiable risk factors. Therefore, maternal and community education on the advantages of breastfeeding and institutional delivery is highly recommended. Women who deliver twins should be given special attention. An effective strategy should be designed for intervention in under-five mortality hot spot areas such as Somali and Dire Dawa.

Prioritizing Health Care Strategies to Reduce Childhood Mortality

IMPORTANCE

Although child mortality trends have decreased worldwide, deaths among children younger than 5 years of age remain high and disproportionately circumscribed to sub-Saharan Africa and Southern Asia. Tailored and innovative approaches are needed to increase access, coverage, and quality of child health care services to reduce mortality, but an understanding of health system deficiencies that may have the greatest impact on mortality among children younger than 5 years is lacking.

OBJECTIVE

To investigate which health care and public health improvements could have prevented the most stillbirths and deaths in children younger than 5 years using data from the Child Health and Mortality Prevention Surveillance (CHAMPS) network.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used longitudinal, population-based, and mortality surveillance data collected by CHAMPS to understand preventable causes of death. Overall, 3390 eligible deaths across all 7 CHAMPS sites (Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa) between December 9, 2016, and December 31, 2021 (1190 stillbirths, 1340 neonatal deaths, 860 infant and child deaths), were included. Deaths were investigated using minimally invasive tissue sampling (MITS), a postmortem approach using biopsy needles for sampling key organs and fluids.

MAIN OUTCOMES AND MEASURES

For each death, an expert multidisciplinary panel reviewed case data to determine the plausible pathway and causes of death. If the death was deemed preventable, the panel identified which of 10 predetermined health system gaps could have prevented the death. The health system improvements that could have prevented the most deaths were evaluated for each age group: stillbirths, neonatal deaths (aged <28 days), and infant and child deaths (aged 1 month to <5 years).

RESULTS

Of 3390 deaths, 1505 (44.4%) were female and 1880 (55.5%) were male; sex was not recorded for 5 deaths. Of all deaths, 3045 (89.8%) occurred in a healthcare facility and 344 (11.9%) in the community. Overall, 2607 (76.9%) were deemed potentially preventable: 883 of 1190 stillbirths (74.2%), 1010 of 1340 neonatal deaths (75.4%), and 714 of 860 infant and child deaths (83.0%). Recommended measures to prevent deaths were improvements in antenatal and obstetric care (recommended for 588 of 1190 stillbirths [49.4%], 496 of 1340 neonatal deaths [37.0%]), clinical management and quality of care (stillbirths, 280 [23.5%]; neonates, 498 [37.2%]; infants and children, 393 of 860 [45.7%]), health-seeking behavior (infants and children, 237 [27.6%]), and health education (infants and children, 262 [30.5%]).

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, interventions prioritizing antenatal, intrapartum, and postnatal care could have prevented the most deaths among children younger than 5 years because 75% of deaths among children younger than 5 were stillbirths and neonatal deaths. Measures to reduce mortality in this population should prioritize improving existing systems, such as better access to antenatal care, implementation of standardized clinical protocols, and public education campaigns.

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

Background

Despite 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.

Methods

The 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.

Results

A 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.

Conclusions

Mothers 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.

•

Our study was an attempt to identify the risk factors for under-five mortality in Ethiopia.

•

We used 2019 Ethiopian Mini Demographic and health Survey data.

•

Analyses were done using Statistical sofwares R, Stata, and SPSS.

•

Count Data Regression Models were employed to identify the risk factors of under-five mortality.

•

The best model that fits the data well was selected using selection criterion like AIC, BIC.

•

Zero-Inflated Poisson model was found to fit the data well.

•

The study found that mother's age, marital status of mother, age of mother's at first birth, place of delivery, place of residence, time to get drinking water, number of children at home, birth order, type of birth were statistically significant determinants for under-five mortality in Ethiopia.

Under-Five Mortality in Sierra Leone and Possible Associated Factors: Evidence from the 2019 Demographic and Health Survey

High under-five mortality rate remains one of the public health challenges, especially in sub-Saharans Africa, accounting for more than half of all global cases. Sierra Leone was and still one of the countries with the highest under-five mortality rate. Using the latest 2019 SLDHS data, we investigated factors associated with under-five mortality in Sierra Leone. A total of 9771 mothers aged 15-49 years in the country were interviewed and included in the analysis. The dependent variable is child status (dead=1; alive=0). A total of 871 (9%) children died before their fifth birthday. Maternal age of 20-24 years (AOR=0.46; CI=0.33-0.64; P<0.001) up to 40-44 years (AOR=0.43; CI=0.27-0.7; P=0.001), currently breastfeeding (AOR=0.20; CI=0.17-0.24; P<0.001), maternal media exposure and usage of reading newspapers/magazines less than once a week (AOR=0.48; CI=0.28-0.85; P=0.011) were more likely to enhance child survivability through their fifth birthday. Also, the child sex being female (AOR=0.68; CI=0.59-0.79) was more likely to survive under-five mortality compared to their male counterpart. On the other hand, mothers who listened to radio at least once a week (AOR=1.31; CI=1.08-1.59; P=0.007) watched television less than once a week (AOR=1.48; CI=1.16-1.90), had two (AOR=3.4, CI=2.78-4.16; P<0.001) or three and above birth (AOR=8.11; CI=6.07-10.83; P<0.001) in five years, had multiple birth children (AOR=1.41; CI=1.08-1.86) and very small-sized child at birth (AOR= 1.95; CI=1.41-2.70) were more likely to lose their children below the age of five years. The factors contributing to under-five mortality in Sierra Leone are critical to ensuring child survival and improving maternal health. Breastfeeding, maternal age, media exposure, child's sex, multiple birth type, very small-sized child and the total number of births in five years were significant drivers of under-five mortality. The result affirms the need for attention to be focused on enhancing the survival rate of under-five children in Sierra Leone.

The effects of Ghana's capitation policy on hospital Under-5 mortality in the Ashanti Region

Objective

The study estimated the capitation policy's effect on the under-5 mortality (U5MR) rate in hospitals in Ashanti Region.

Design

We used an interrupted time series design to estimate the impact from secondary data obtained from the DHIMS-2 database. Monthly under-5 deaths and the number of live births per month were extracted and entered into Stata 15.0 for analyses. The U5MR was calculated by dividing the number of live deaths by the number of live births for each of the 60 months of the study.

Setting

Health facilities of the Ashanti Region with Data in the DHIMS 2.

Intervention

the level and trend of U5MR for 31 months during the Capitation Policy implementation (January 2015 to July 2017) were compared with the level and trend 29 months after the withdrawal of the capitation policy (August 2017 to December 2019).

Outcome measures

changes in trend or level of U5MR after the withdrawal of capitation.

Main Results

During the capitation policy, monthly U5MR averaged 10.71 +/-2.71 per 1000 live births. It declined to 0.03 deaths per 1000 live births (p=0.65). After the policy withdrawal, the immediate (increase of 0.01 per 1000live births) and the trend (decline of 0.13 deaths per 1000 live births per month) were still not statistically significant.

Conclusion

We conclude that the capitation policy did not appear to have influenced under-5 mortality in the Ashanti Region. The design of future healthcare payment models should target quality improvement to reduce under-5 mortalities.

Funding

None declared.

Factors associated with post-neonatal mortality in Ethiopia: Using the 2019 Ethiopia mini demographic and health survey

Background

Post-neonatal mortality is the number of deaths of infants aged 28 days through 11 months and is expressed as post-neonatal deaths per 1000 live births per year. This study aimed to identify the factors that influence post-neonatal death using the 2019 Ethiopia mini demographic and health survey (EMDHS2019).

Methods

The study included 2126 post neonates born from mothers who had been interviewed about births in the five years before the survey. The survey gathering period was carried out from March 21, 2019, to June 28, 2019. The data were first analyzed with a chi-square test of association, and then relevant factors were evaluated with binary logistic regression models and the results were interpreted using adjusted odds ratio (AOR) and confidence interval(CI) of parameters.

Results

The prevalence of post neonatal death was 16% (95% CI: 15.46, 17.78). The study also showed that not vaccinated post-neonates (AOR = 2.325, 95% CI: 1.784, 3.029), mothers who were not receiving any tetanus injection (AOR = 2.891, 95% CI: 2.254, 3.708), mothers age group 15-24(AOR = 1.836, 95% CI: 1.168, 2.886), Afar (AOR = 2.868, 95% CI: 1.264, 6.506), Somali(AOR = 2.273, 95% CI: 1.029, 5.020), Southern Nations, Nationalities, and People’s Region(SNNP) (AOR = 2.619, 95% CI: 1.096, 6.257), 2–4 birth orders (AOR = 1.936, 95% CI: 1.225, 3.060), not attend antenatal care(ANC) visit (AOR = 6.491, 95% CI: 3.928, 10.726), and preceding birth interval less than 24 months (AOR = 1.755, 95% CI: 1.363,2.261) statistically associated with a higher risk of post neonatal death. Although not given anything other than breast milk (AOR = 0.604, 95% CI 0.462, 0.789), urban residents (AOR = 0.545, 95% CI: 0.338, 0.877), single births (AOR = 0.150, 95% CI: 0.096, 0.234), less than 3 children in a family (AOR = 0.665, 95% CI 0.470, 0.939) and the head of the male household (AOR = 0.442, 95% CI: 0.270, 0.724) were statistically associated with a lower risk of post-neonatal mortality.

Conclusions

It is highly suggested that maternal and child health care services (including antenatal care visits, postnatal care visits, and immunization) be strengthened and monitored during the early stages of infancy. Mothers from Somali, Afar, and SNNP regions, as well as multiple births, rural residents, and those giving birth to a child with a birth gap of fewer than 24 months, demand special care.

Multilevel log linear model to estimate the risk factors associated with infant mortality in Ethiopia: further analysis of 2016 EDHS

BACKGROUND

Infant mortality is defined as the death of a child at any time after birth and before the child's first birthday. Sub-Saharan Africa has the highest infant and child mortality rate in the world. Infant and child mortality rates are higher in Ethiopia. A study was carried out to estimate the risk factors that affect infant mortality in Ethiopia.

METHOD

The EDHS- 2016 data set was used for this study. A total of 10,547 mothers from 11 regions were included in the study's findings. To estimate the risk factors associated with infant mortality in Ethiopia, several count models (Poisson, Negative Binomial, Zero-Infated Poisson, Zero-Infated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial) were considered.

RESULT

The average number of infant deaths was 0.526, with a variance of 0.994, indicating over-dispersion. The highest mean number of infant death occurred in Somali (0.69) and the lowest in Addis Ababa (0.089). Among the multilevel log linear models, the ZINB regression model with deviance (17,868.74), AIC (17,938.74), and BIC (1892.97) are chosen as the best model for estimating the risk factors affecting infant mortality in Ethiopia. However, the results of a multilevel ZINB model with a random intercept and slope model revealed that residence, mother's age, household size, mother's age at first birth, breast feeding, child weight, contraceptive use, birth order, wealth index, father education level, and birth interval are associated with infant mortality in Ethiopia.

CONCLUSION

Infant deaths remains high and infant deaths per mother differ across regions. An optimal fit was found to the data based on a multilevel ZINB model. We suggest fitting the ZINB model to count data with excess zeros originating from unknown sources such as infant mortality.

Assessing Individual- and Community-Level Variability in Predictors of Neonatal, Infant, and Under-Five Child Mortality in Ethiopia Using a Multilevel Modeling Approach

Background: In low-and middle-income countries, child mortality rates are basic indicators of a country’s socio-economic situation and quality of life. The Ethiopian government is currently working to reduce child mortality to accomplish its long-term development goals. Using data from the Ethiopian Mini Demographic and Health Survey, 2019, this study analyzed the determinants of child mortality in Ethiopia. Methods: A total of 4806 children were considered in the final analyses. Multivariate analysis was used to estimate the effects of the predictors simultaneously on each child mortality outcome. Results: The findings revealed that 31.6% of children died during the neonatal stage, 39.1% during the infant stage, and 48.5% during the under-five stage. Variation in child mortality was discovered between Ethiopian community clusters, with the result of heterogeneity between clusters on newborn mortality (χ2 = 202.4, p-value < 0.0001), (χ2 = 777.35, p-value < 0.0001), and (χ2 = 112.92, p-value < 0.0001). Children’s neonatal, infant, and under-five mortality intracluster correlation coefficient (ICC) were 0.35, 0.33, and 0.36, respectively, across communities. Conclusions: In Ethiopia, under-five mortality remains a serious public health issue, with wide variations and high rates among community clusters. Intervention measures focusing on lowering rates of household poverty, increasing education opportunities, and improving access to health care could assist in reducing child mortality in Ethiopia.

Trends of under-five mortality and associated risk factors in Zambia: a multi survey analysis between 2007 and 2018

BACKGROUND

Mortality at a young age is key to public health measures. This study aims to describe the burden, trend, and associated factors of under-five mortality rate (U5MR) in Zambia from 2007-to-2018.

METHOD

A sample of 29,274 children under-five were analyzed from the Zambia demographic and health survey (ZDHS). Univariate and bivariate analysis were used to identify factors influencing U5M.

RESULT

Pooled prevalence of U5MR in Zambia was 84.4/ 1000 live-births. Over 15 years, U5M has declined by 49% (from 118.7 to 60.5/1000 live-births). Compared to children of teenage (≤19 years) mothers the likelihood of U5M was lower by 24 to 37% among children of 20 to 34 years old mothers. The likelihood of U5M was lower by 23% (AOR, 0.77 95%CI, 0.58-1.04) for poorest, 27% (AOR, 0.73 95%CI, 0.55-0.98) for poorer, and 19% (AOR, 0.81 95%CI, 0.62-1.07) for middle as compared to the richest households. The likelihood of U5M was 21% (AOR, 0.79 95%CI, 0.67-0.93) lower among rural residents. Multiple-born children died 2.54 times (95%CI, 1.95-3.98) higher than the single-born. Male children (AOR, 1.28, 95% CI, 1.23-1.46), smaller than average birth size (AOR, 1.78; 95% CI, 1.52-2.09), and no ANC visit (AOR, 3.17, 95% CI, 2.74-3.67) were associated with U5M. The likelihoods of U5M were significantly higher in the Eastern, Luapula, and Muchinga regions than in the Central.

CONCLUSION

This study revealed that Zambia has made a gain on child survival. Further efforts targeting mothers, children, and provinces are needed to scale up the decline and achieve the SDG3.

Socio-economic and proximate determinants of under-five mortality in Guinea

BACKGROUND

The death of children under-five years is one of the critical issues in public health and improving child survival continues to be a matter of urgent concern. In this paper, we assessed the proximate and socio-economics determinants of child mortality in Guinea.

METHODS

Using the 2018 Guinea Demographic and Health Survey (GDHS), we extracted demographic and mortality data of 4,400 children under-five years. Both descriptive and multivariable logistic regression analyses were conducted.

RESULTS

Under-five mortality was 111 deaths per 1,000 live births in Guinea. The likelihood of death was higher among children born to mothers who belong to other religions compared to Christians (aOR = 2.86, 95% CI: 1.10-7.41), smaller than average children compared to larger than average children (aOR = 1.97, 95% CI: 1.28-3.04) and those whose mothers had no postnatal check-up visits after delivery (aOR = 1.72, 95% CI: 1.13-2.63). Conversely, the odds of death in children with 2-3 birth rank & >2 years of birth interval compared to ≥4 birth rank and ≤2 years of birth interval were low (aOR = 0.53, 95% CI: 0.34-0.83).

CONCLUSION

We found that household/individual-level socioeconomic and proximate factors predict under-five mortality in Guinea. With just about a decade left to the 2030 deadline of the Sustainable Development Goals (SDGs), concerted efforts across all key stakeholders, including government and development partners, need to be geared towards implementing interventions that target these predictors.

Time to under-five mortality and its predictors in rural Ethiopia: Cox-gamma shared frailty model

Background

Under-five mortality (U5M) is one of the most important and sensitive indicators of the health status of the community. Despite there having been a substantial reduction in U5M since 1990, its rate is still high in Sub-Saharan African countries. Thus, this study aimed to assess time to under-five mortality and its predictors in rural Ethiopia.

Methods

This study utilized a secondary analysis of the 2016 Ethiopia Demographic and Health Survey (EDHS). A total of 9,807 weighted under-five children selected at different stages were included in the analysis. The Kaplan-Meier and Cox’s-gamma shared frailty models were used to estimate survival time and to identify predictors of under-five mortality, respectively. An adjusted Hazard Ratio (AHR) along with a 95% Confidence Interval (CI) was used to measure the effect size and direction of the association.

Results

The study indicated that 6.69% (95% CI: 6.13, 7.30) of children died before celebrating their fifth birthday in rural Ethiopia. Of all the deaths, the median time to death was 27 months. After controlling the effect of cluster and other confounding factors, female sex (AHR = 0.62, 95% CI: 0.52, 0.75), ever born greater than five children (AHR = 1.40, 95% CI: 1.07, 1.83), very large size at birth (AHR = 1.33, 95% CI: 1.03 1.71), very small size at birth (AHR = 1.41, 95% CI: 1.10, 1.82), twin pregnancy (AHR = 3.5, 95% CI: 2.47, 4.88), not ever breastfeeding (AHR = 11.29, 95% CI: 9.03, 14.12), unimproved latrine (AHR = 3.44, 95% CI: 1.91, 6.17), covered by health insurance (AHR = 0.29, 95% CI: 0.12, 0.70) were predictors of under-five mortality.

Conclusions

Still under-five mortality was high in rural Ethiopia as compared to the global under-five mortality rate. In the final model, sex of a child, the total number of children ever born, children’s size at birth, type of pregnancy, breastfeeding, type of toilet, and being covered by health insurance were significant predictors of under-five mortality. Further emphasis should be given to twin and not breastfeeding children, as well as households’ better encouraging membership of community health insurance and utilization of improved latrines.

Factors contributing to household wealth inequality in under-five deaths in low- and middle-income countries: decomposition analysis

BACKGROUND

The burden of under-5 deaths is disproportionately high among poor households relative to economically viable ones in developing countries. Despite this, the factors driving this inequality has not been well explored. This study decomposed the contributions of the factors associated with wealth inequalities in under-5 deaths in low- and middle-income countries (LMICs).

METHODS

We analysed data of 856,987 children from 66,495 neighbourhoods across 59 LMICs spanning recent Demographic and Health Surveys (2010-2018). Under-5 mortality was described as deaths among live births within 0 to 59 months of birth and it was treated as a dichotomous variable (dead or alive). The prevalence of under-five deaths was stratified using household wealth status. A Fairlie decomposition analysis was utilized to investigate the relative contribution of the factors associated with household wealth inequality in under-5 deaths at p<0.05. The WHO health equity assessment toolkit Plus was used to assess the differences (D) ratios (R), population attributable risk (PAR), and population attributable fraction (PAF) in household wealth inequalities across the countries.

RESULTS

The proportion of children from poor households was 45%. The prevalence of under-5 deaths in all samples was 51 per 1000 children, with 60 per 1000 and 44 per 1000 among children from poor and non-poor households (p<0.001). The prevalence of under-5 deaths was higher among children from poor households than those from non-poor households in all countries except in Ethiopia, Tanzania, Zambia, Lesotho, Gambia and Sierra Leone, and in the Maldives. Thirty-four of the 59 countries showed significantly higher under-5 deaths in poor households than in non-poor households (pro-non-poor inequality) and no significant pro-poor inequality. Rural-urban contexts, maternal education, neighborhood socioeconomic status, sex of the child, toilet kinds, birth weight and preceding birth intervals, and sources of drinking water are the most significant drivers of pro-poor inequities in under-5 deaths in these countries.

CONCLUSIONS

Individual-level and neighbourhood-level factors were associated with a high prevalence of under-5 deaths among poor households in LMICs. Interventions in countries should focus on reducing the gap between the poor and the rich as well as improve the education and livelihood of disadvantaged people.

Potential determinant factors of under-five mortality in the Amhara region of Ethiopia

BACKGROUND

Even though child mortality decreased greatly (44%, since 1990), children in developing countries are eight times more likely to die before they attain their five years birthday. When comparing under-five mortality around the world, the African including Ethiopia and Southeast Asian regions showed an uneven child death rate. Therefore, this study was aimed to identify the potential determinant factors of under-five mortality in the Amhara regional state of Ethiopia.

METHODS

Statistics from a national representative cross-sectional survey of the Ethiopian Demographic and Health Survey (EDHS) of the year 2016 were used. Data was collected from the population of all under-five children in randomly selected enumeration areas of the Amhara region of Ethiopia. To investigate the relationship between the dependent variable (under-five mortality) and various independent factors, inferential statistics such as binary logistic regression and multiple logistic regressions were used. In multivariable analysis, statistically significant variables in binary logistic regression analysis, i.e. (p-value 0.250), were entered, and P-value 0.050 was considered significant at 95% CI.

RESULTS

The survey was included 977 children under the age of five and more than half of children in the family (68%) were ≤ 4. The findings showed that children whose mothers had no formal education were 2.59 times more likely to die than children whose mothers had formal education [AOR: 2.59(1.12-5.99)]. Similarly, children who did not receive breastfeeding from their mothers were 3.61 times more likely to die than children who received breastfeeding from their mothers [AOR: 3.61(1.83-6.19)]. CONCLUSION AND RECOMMENDATION: The number of children in the family, as well as the mother's educational status and current breastfeeding status, were all found to be important factors in under-five mortality in the study area. As a result, the potential determinants of under-five mortality should be addressed as part of a program targeted at lowering childhood mortality.

Sex inequality in under-five deaths and associated factors in low and middle-income countries: a Fairlie decomposition analysis

Background

There exist sex disparities in the burden of Under-five deaths (U5D) with a higher prevalence among male children. Factors explaining this inequality remain unexplored in Low-and Medium-Income Countries (LMIC). This study quantified the contributions of the individual- and neighborhood-level factors to sex inequalities in U5D in LMIC.

Methods

Demographic and Health Survey datasets (2010-2018) of 856,987 under-five children nested in 66,495 neighborhoods across 59 LMIC were analyzed. The outcome variable was U5D. The main group variable was the sex of the child while individual-level and neighborhood-level factors were the explanatory variables. Fairlie decomposition analysis was used to quantify the contributions of explanatory factors to the male-female inequalities in U5D at p<0.05.

Results

Overall weighted prevalence of U5D was 51/1000 children, 55 among males and 48 among females (p<0.001). Higher prevalence of U5D was recorded among male children in all countries except Liberia, Kyrgyz Republic, Bangladesh, Nepal, Armenia, Turkey and Papua New Guinea. Pro-female inequality was however not significant in any country. Of the 59 countries, 25 had statistically significant pro-male inequality. Different factors contributed to the sex inequality in U5D in different countries including birth order, birth weight, birth interval and multiple births.

Conclusions

There were sex inequalities in the U5D in LMIC with prominent pro-male-inequality in many countries. Interventions targeted towards the improvement of the health system that will, in turn, prevent preterm delivery and improve management of prematurity and early childhood infection (which are selective threats to the male child survival) are urgently required to address this inequality.

Survival time discrepancy among under-five-year children of rural parts of Ethiopia

BACKGROUND

Ethiopia is ranked as the fifth of heavy under-five death burdened countries with the highest burden in its rural areas. This study aimed to identify the determinants of under-five deaths in rural parts of Ethiopia.

STUDY DESIGN

A population-based cross-sectional study.

METHODS

The data for this study was extracted from the 2016 Ethiopian Demographic and Health Survey. Descriptive analysis, non-parametric estimation, and Cox proportional hazards regression model were used to examine the determinants of under-five mortality.

RESULTS

A total of 7301 under-five eligible children from rural areas were involved in this survey, and 6.5% of the cases were passed away before reaching their fifth birthday. Male children's death accounted for 59.7% of the death rate in the participants. An estimated median survival time was 31 months [95% CI: 30-32]. About 83% of children's death occurred among children delivered at home. Cox proportional hazard regression model revealed that gender, delivery-place, family-size, mother's education, number of children, contraceptive use, and source of drinking water had significant effects on survival time of under-five children. Under-five mortality was significantly fewer in female children (HR  =  0.728; 95% CI: 0.606-0.875, P =  0.001), children delivered at health facilities (HR  =  0.738; 95% CI: 0.572-0.951, P =  0.019), and those from secondary and above educated mothers (HR  =  0.464; 95% CI: 0.301-0.714, P =  0.001), compared to the reference category.

CONCLUSION

Significant risk factors were associated with under-five mortality in rural areas. Delivering in health facilities, uses of contraceptives, mother's education, and improvement of infrastructures should be areas of concern to decrease under-five children's deaths.

Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data

Background

Nigeria’s child health profile is quite concerning with an infant mortality rate of 67 deaths per 1000 live births and a significant slowing down in progress towards improving child health outcomes. Nigeria’s 2018 Demographic and Health Survey (DHS) suggests several bio-demographic risk factors for child death, including mother’s poor education, poverty, sex of child, age of mother, and location (rural vs urban) but studies are yet to explore the predictive power of these variables on infant survival in Nigeria.

Methods

The study extracted data for all births in the last 12 months preceding the 2018 Nigeria DHS and used the Cox proportional hazard model to predict infant survival in Nigeria. Failure in this analysis is death with two possible outcomes – dead/alive – while the survival time variable is age at death. We censored infants who were alive at the time of the study on the day of the interview. Covariates in the analysis were: age of mother, education of mother, wealth quintile, sex of child, location, region, place of delivery, and age of pregnancy.

Results

The study found that a higher education of a mother compared to no education (β = .429; p-value < 0.05); belonging to a household in the richer wealth quintile (β = .618; p-value < 0.05) or the highest quintile (β = .553; p-value < 0.05), compared to the lowest wealth quintile; and living in North West (β = 1.418; p-value < 0.05) or South East zone (β = 1.711; p-value < 0.05), significantly predict infant survival.

Conclusion

Addressing Nigeria’s infant survival problem requires interventions that give attention to the key drivers – education, socio-economic status, and socio-cultural contextual issues. We therefore recommend full implementation of the universal basic education policy, and child health education programs targeted at mothers as long- and short-term solutions to the problem of poor child health outcomes in Nigeria. We also argue in favor of better use of evidence in policy and program development in Nigeria.

Multilevel modeling, prevalence, and predictors of hypertension in Ghana: Evidence from Wave 2 of the World Health Organization's Study on global AGEing and adult health

BACKGROUND AND AIMS

Hypertension is a major public health issue, an important risk factor for cardiovascular diseases and stroke, especially in developing countries where the rates remain unacceptably high. In Africa, hypertension is the leading driver of cardiovascular disease and stroke deaths. Identification of critical risk factors of hypertension can help formulate targeted public health programs and policies aimed at reducing the prevalence and its associated morbidity, disability, and mortality. This study attempts to develop multilevel regression, an in-depth statistical model to identify critical risk factors of hypertension.

METHODS

This study used data on 4667 individuals aged ≥18 years from the nationally representative World Health Organization Study on global AGEing and adult health (SAGE) Ghana Wave 2 conducted in 2014/2015. Multilevel regression modeling was employed to identify critical risk factors for hypertension based on systolic blood pressure (SBP) (ie, SBP > 140 mmHg). Of the 4667, 27.3% were hypertensive. Final data on 4381 individuals residing in 3790 households were analyzed using multilevel models, and results were presented as adjusted odds ratios (aOR) and their associated 95% confidence intervals (CI).

RESULTS

Risk factors for hypertension identified were age (aOR) = 5.4, 95% CI: 4.11-7.09), obesity (aOR = 1.51, 95% CI: 1.19-1.91), marital status (aOR = 0.75, 95% CI: 0.64-0.89), perceived health state (moderate; aOR = 1.38, 95% CI: 1.15-1.65 and bad/very bad; aOR = 1.35, 95% CI: 1.0-1.83), and difficulty with self-care (aOR = 1.64, 95% CI: 1.1-2.44). We found unobserved significant differences in the likelihood of hypertension prevalence between different households.

CONCLUSION

Addressing the problem of obesity, targeting specific interventions to those aged over 50 years, and improvement in the general health of Ghanaians are paramount to reducing the prevalence and its associated morbidity, disability, and mortality. Lifestyle modification in the form of dietary intake, knowledge provision supported with strong public health message, and political will could be beneficial to the management and prevention of hypertension.

Incidence and predictors of under-five mortality in East Africa using multilevel Weibull regression modeling

BACKGROUND

In 2017, an estimated 5.3 million under-five children died annually in Sub-Saharan African countries, more than half of those deaths occurred in East Africa. Though East African countries share the huge burden of global under-five mortality, there is limited evidence on the incidence and predictors of under-five mortality. Therefore, this study investigated the incidence and predictors of under-five mortality in East Africa.

METHODS

A community-based cross-sectional study was done based on the Demographic and Health Survey (DHS) data of 12 East African countries conducted from 2008 to 2019. A total weighted sample of 138,803 live births within 5 years preceding the survey were included for analysis. The Kaplan-Meier curve and Log-rank test were done to assess the children's survival experience across variable categories. The Global Schoenfeld residual test was employed for checking Proportional Hazard (PH) assumptions and it was violated (p-value< 0.05). Considering the hierarchical nature of DHS data, multilevel parametric survival models were fitted. Model comparison was made by AIC, deviance, and shape of the hazard function. Variables with a p-value of less than 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multilevel Weibull regression analysis, the Adjusted Hazard Ratio (AHR) with 95% Confidence Interval (CI) was reported to declare the significant predictors of under-five mortality.

RESULTS

Under-five mortality rate in East Africa was 51.318 (95% CI: 51.311, 51.323) per 1000 live births. Babies born to mothers attained secondary education and above (AHR = 0.83, 95% CI: 0.75, 0.91), being 2nd - 4th birth order (AHR = 0.62, 95% CI: 0.56, 0.67), ≥ 5th birth order (AHR = 0.68, 95% CI: 0.61, 0.76), health facility delivery (AHR = 0.87, 95% CI: 0.82, 0.93), 1-3 ANC visit (AHR = 0.61, 95% CI: 0.54, 0.68), births interval of 24-48 months (AHR = 0.53, 95% CI: 0.50, 0.57), wanted pregnancy (AHR = 0.72, 95% CI: 0.68, 0.76), middle wealth status (AHR = 0.90, 95% CI: 0.83, 0.97), and richest wealth status (AHR = 0.81, 95% CI:0.73, 0.90) were significantly associated with lower hazards of under-five mortality. Whereas, advanced maternal age (≥35 years) (AHR = 1.13, 95% CI: 1.04, 1.24),, babies born to household who did not have media exposure (AHR = 1.13, 95% CI: 1.07, 1.20), twin births (AHR = 3.81, 95% CI: 3.52, 4.12), being male child (AHR = 1.27, 95%CI: 1.21, 1.33), small birth size at birth (AHR = 1.73, 95% CI: 1.63, 1.84), and large size at birth (AHR = 1.11, 95% CI: 1.04, 1.11) were significantly associated with higher hazards of under-five mortality.

CONCLUSION

Under-five mortality is a major public health concern in East African countries. Health facility delivery, ANC visit, higher wealth status, adequate birth spacing, wanted pregnancy, and maternal education were significantly correlated with a lower risk of under-5 mortality. Whereas, higher birth order, small or large size at birth, male birth, twin birth, advanced maternal age and mothers who didn't have media exposure were significantly correlated with a higher risk of under-five mortality. This study highlights that public health programs should enhance health facility delivery, ANC visit, media exposure, maternal education, and adequate birth spacing to decrease the incidence of under-five mortality in East Africa.

Determinant factors of under-five mortality in Southern Nations, Nationalities and People's region (SNNPR), Ethiopia

Background

Child mortality is a key indicator of the performance of the health system of a nation. Impressive progress in the reduction of under-five mortality has been made in Ethiopia. However, still there are some regions where the under-five mortality rates are high. Southern Nations, Nationalities, and Peoples’ Region (SNNPR) is among those regions in Ethiopia with high under-five mortality rates. This study aimed to identify the determinant factors of under-five mortality in SNNPR.

Methods

Data used for the study were drawn from the 2016 EDHS. A total of 1277 under-five children were included in the study. A multivariable logistic regression model was fitted to identify determinant factors associated with under-five mortality.

Results

Children with second or third birth order (OR = 1.316, 95% CI: (1.097, 2.343)), fourth or fifth birth order (OR = 1.934, 95% CI: (1.678, 3.822)), sixth or above birth order (OR = 3.980, 95% CI: (2.352, 6.734)) were significantly associated with increased risk of under-five mortality as compared to those with first birth order. Increased risk of under-five mortality was also significantly associated with a family size of five or more (OR = 3.397, 95% CI: (1.702, 6.782)) as compared to the family size of less than five; smaller size at birth (OR = 1.714, 95% CI: (1.120, 2.623)) as compared to larger size at birth; multiple births (OR = 1.472, 95% CI: (1.289, 2.746)) as compared to singletons. On the other hand, female children (OR = 0.552, 95% CI: (0.327, 0.932)), children born at health institutions (OR = 0.449, 95% CI: (0.228, 0.681)) and children who were breastfed (OR = 0.657, 95% CI: (0.393, 0.864)) were significantly associated with decreased risk of under-five mortality as compared to male children, those born at home and those who were not breastfed respectively.

Conclusions

Sex of a child, birth order, size of a child at birth, place of delivery, birth type, breastfeeding status, and family size were significant factors associated with under-five mortality in SNNPR, Ethiopia. Thus, planning and implementing relevant strategies that focus on those identified determinant factors of under-five mortality is required for the improvement of child survival in SNNPR, Ethiopia.

Mapping of mothers' suffering and child mortality in Sub-Saharan Africa

Child death and mothers who suffer from child death are a public health concern in Sub-Saharan Africa. The location and associated factors of child death and mothers who suffer child death were not identified. To monitor and prioritize effective interventions, it is important to identify hotspots areas and associated factors. Data from nationally representative demographic and health survey and Multiple Indicator Cluster administrated in 42 Sub-Sahara Africa countries, which comprised a total of 398,574 mothers with 1,521,312 children. Spatial heterogeneity conducted hotspot regions identified. A mixed-effect regression model was run, and the adjusted ratio with corresponding 95% confidence intervals was estimated. The prevalence of mothers who suffer child death 27% and 45-49 year of age mother 48%. In Niger, 47% of mothers were suffering child death. Women being without HIV knowledge, stunted, wasted, uneducated, not household head, poor, from rural, and from subtropical significantly increased the odds of the case (P < 0.05). The spatial analysis can support the design and prioritization of interventions. Multispectral interventions for mothers who suffer from child death are urgently needed, improve maternal health and it will reduce the future risk of cases.

Trends in under-five mortality rate disaggregated across five inequality dimensions in Ghana between 1993 and 2014

OBJECTIVES

Globally, there has been a considerable decline in under-five mortality in the past years. However, it remains a critical issue among low- and middle-income countries, especially in sub-Saharan Africa. In Ghana, under-five mortality is a critical public health issue that requires national interventions. In the present study, we examined the trends of under-five mortality in Ghana from 1993 to 2014.

METHODS

Using the World Health Organization's Health Equity Assessment Toolkit, we analyzed data from the 1993-2014 Ghana Demographic and Health surveys. We disaggregated the under-five mortality rate by five equity stratifiers: wealth index, education, sex, place, and region of residence. We measured the inequality through summary measures, namely difference, population attributable risk, ratio and population attributable fraction.

RESULTS

In 1993, under-five mortality among children in poor households (172.90, uncertainty intervals [UIs = 153.21-194.53]) was more than twice the proportion of children from the richest households who died before their 5th birthday (74.96; UI = 60.31-92.81) and this trend continued until 2008. However, in 2014, the poorest had the lowest rate (30.91, UI = 78.70-104.80). Children of women with no formal education consistently recorded the highest burden of under-five mortality. Although in 2014 the gap appeared to have narrowed, children of mothers with no formal education record the highest under-five mortality rate (91.61; UI = 79.73-105.07) compared with those with secondary or higher education (54.34; UI = 46.24-63.77). Under-five mortality was higher among rural residents throughout the years. Men repeatedly had the greatest share of under-five mortality with the highest prevalence occurring in 1993 (137.52; UI = 123.51-152.85) and the lowest occurring in 2014 (77.40; UI = 69.15-86.54). The Northern region consistently accounted for the greatest proportion of under-five mortality.

CONCLUSION

Ghana has experienced a decline in under-five mortality from 1993 to 2014. Context-specific appropriate interventions are necessary for various disadvantaged sub-populations with risks of health disparities.

Geostatistical analysis, web-based mapping, and environmental determinants of under-5 stunting: evidence from the 2014 Ghana Demographic and Health Survey

BACKGROUND

Stunting rates in children younger than 5 years are among the most important health indicators globally. At the national level, malnutrition accounts for about 40% of under-5 deaths in Ghana. Disease risk mapping provides opportunities for disease surveillance and targeted interventions. We aimed to estimate and map under-5 stunting prevalence in Ghana, with the goal of identifying communities at higher risk where interventions and further research can be targeted.

METHODS

For this modelling study, we used data from the 2014 Ghana Demographic and Health Survey. Analyses were done on 2734 children residing in 415 geographical clusters. The outcome variable was the number of stunted children younger than 5 years in each sampled cluster. We employed a Bayesian geostatistical model to investigate both measured and unmeasured spatial risk factors for child stunting, comparing the performance of non-spatial (adjusting for selected covariates without spatial correlation), spatial (including spatial correlation), and null spatial (without the selected covariates) models. We then visualised the stunting prevalence across Ghana by mapping the predicted prevalence and exceedance probabilities to resolutions as refined as 5 km × 5 km.

FINDINGS

In 2014, 535 (19·6%) of 2734 children surveyed in Ghana were stunted. Elevation (log odds mean -0·0017, 95% credible interval -0·0034 to -0·0001), precipitation (0·0403, 0·0192 to 0·0615), and aridity (-3·7013, -6·5478 to -0·8723) were environmental and climatic factors associated with stunting in the non-spatial model, but were not significant in the spatial model. Substantial geographical variations in prevalence of childhood stunting were found. The predicted mean stunting prevalence was 27·7% (SD 3·7%) with predicted prevalence ranging from 4·2% to 45·1% across Ghana. Children residing in parts of the Northern region were at highest risk of stunting, whereas parts of the Greater Accra, Brong-Ahafo, Ashanti, and Eastern regions showed some of the lowest prevalence.

INTERPRETATION

There are substantial geographical differences in childhood stunting across Ghana. Our prevalence maps can be used as an effective tool to identify communities that require targeted interventions by programme managers and implementers, as part of an overall strategy to reduce the burden of malnutrition in a country with limited public health resources.

FUNDING

None.

Does Birth Interval Matter in Under-Five Mortality? Evidence from Demographic and Health Surveys from Eight Countries in West Africa

In sub-Saharan Africa (SSA), every 1 in 12 children under five dies every year compared with 1 in 147 children in the high-income regions. Studies have shown an association between birth intervals and pregnancy outcomes such as low birth weight, preterm birth, and intrauterine growth restriction. In this study, we examined the association between birth interval and under-five mortality in eight countries in West Africa. A secondary analysis of the Demographic and Health Survey (DHS) data from eight West African countries was carried out. The sample size for this study comprised 52,877 childbearing women (15-49 years). A bivariate logistic regression analysis was carried out and the results were presented as crude odds ratio (cOR) and adjusted odds ratios (aOR) at 95% confidence interval (CI). Birth interval had a statistically significant independent association with under-five mortality, with children born to mothers who had >2 years birth interval less likely to die before their fifth birthday compared to mothers with ≤2 years birth interval [cOR = 0.56; CI = 0.51 − 0.62], and this persisted after controlling for the covariates [aOR = 0.55; CI = 0.50 − 0.61]. The country-specific results showed that children born to mothers who had >2 years birth interval were less likely to die before the age of five compared to mothers with ≤2 years birth interval in all the eight countries. In terms of the covariates, wealth quintile, mother's age, mother's age at first birth, partner's age, employment status, current pregnancy intention, sex of child, size of child at birth, birth order, type of birth, and contraceptive use also had associations with under-five mortality. We conclude that shorter birth intervals are associated with higher under-five mortality. Other maternal and child characteristics also have associations with under-five mortality. Reproductive health interventions aimed at reducing under-five mortality should focus on lengthening birth intervals. Such interventions should be implemented, taking into consideration the characteristics of women and their children.

Geospatial analysis, web-based mapping and determinants of prostate cancer incidence in Georgia counties: evidence from the 2012-2016 SEER data

Background

Prostate cancer (CaP) cases are high in the United States. According to the American Cancer Society, there are an estimated number of 174,650 CaP new cases in 2019. The estimated number of deaths from CaP in 2019 is 31,620, making CaP the second leading cause of cancer deaths among American men with lung cancer been the first. Our goal is to estimate and map prostate cancer relative risk, with the ultimate goal of identifying counties at higher risk where interventions and further research can be targeted.

Methods

The 2012–2016 Surveillance, Epidemiology, and End Results (SEER) Program data was used in this study. Analyses were conducted on 159 Georgia counties. The outcome variable is incident prostate cancer. We employed a Bayesian geospatial model to investigate both measured and unmeasured spatial risk factors for prostate cancer. We visualised the risk of prostate cancer by mapping the predicted relative risk and exceedance probabilities. We finally developed interactive web-based maps to guide optimal policy formulation and intervention strategies.

Results

Number of persons above age 65 years and below poverty, higher median family income, number of foreign born and unemployed were risk factors independently associated with prostate cancer risk in the non-spatial model. Except for the number of foreign born, all these risk factors were also significant in the spatial model with the same direction of effects. Substantial geographical variations in prostate cancer incidence were found in the study. The predicted mean relative risk was 1.20 with a range of 0.53 to 2.92. Individuals residing in Towns, Clay, Union, Putnam, Quitman, and Greene counties were at increased risk of prostate cancer incidence while those residing in Chattahoochee were at the lowest risk of prostate cancer incidence.

Conclusion

Our results can be used as an effective tool in the identification of counties that require targeted interventions and further research by program managers and policy makers as part of an overall strategy in reducing the prostate cancer burden in Georgia State and the United States as a whole.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08254-0.

Determinants of under-five mortality in the high mortality regions of Ethiopia: mixed-effect logistic regression analysis

BACKGROUND

Even though the global under-five mortality rate substantially decreased over time, Sub-Saharan African (SSA) countries including Ethiopia continue to share the huge burden of under-five mortality. Ethiopia showed a substantial reduction in under-five mortality over time but the rate of reduction has varied across regions. Therefore, this study aimed to investigate determinants of under-five mortality in the high mortality regions of Ethiopia.

METHODS

A secondary data analysis was done based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 3446 live births were included for this study. For the determinants of under-five mortality, mixed-effect logistic regression was fitted. The Intra-Class Correlation Coefficient (ICC), and Median Odds Ratio (MOR) were done to assess the presence of a significant clustering effect. The standard binary logistic regression and the mixed-effect logistic regression model were fitted and deviance (-2LL) was used for model comparison as the models were nested models. Variables with a p-value less than 0.2 in the bi-variable mixed-effect binary logistic regression analysis were considered for the multivariable analysis. In the multivariable mixed-effect logistic regression analysis, the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) were reported to declare the statistical significance and strength of association of under-five mortality and the determinant factors.

RESULTS

Overall, the under-five mortality rate in the high mortality regions of Ethiopia was 74 per 1000 live births and it was highest among twin births (262 per 1000 live births). In the multivariable mixed-effect logistic regression analysis, being having 6 and above births (AOR = 3.66, 95% CI: 1.55, 8.67), preceding birth interval of 2-3 years (AOR = 0.57, 95% CI: 0.41, 0.81) and above 3 years (AOR = 0.35, 95% CI: 0.22, 0.55), being twin (AOR = 5.12, 95% CI: 2.28, 11.46), and being having antenatal care (ANC) visit during pregnancy (AOR = 0.27, 95% CI: 0.16, 0.45) were significant determinants of under-five mortality.

CONCLUSION

In this study, under-five mortality rate was highest in high mortality regions of Ethiopia. Parity, ANC visit, preceding birth interval, and multiple births were significant predictors of under-five mortality. Therefore, public health interventions that increase maternal health service utilization such as ANC and family planning service utilization to increase birth interval are needed to reduce under-five mortality among these regions of Ethiopia.

Predictive model and determinants of odds of neonates dying within 28 days of life in Ghana

BACKGROUND

One of the priorities and important current problem in public health research globally is modeling of neonatal mortality and its risk factors in using the appropriate statistical methods. It is believed that multiple risk factors interplay to increase the risk of neonatal mortality. To understand the risk factors of neonatal mortality in Ghana, the current study carefully evaluated and compared the predictive accuracy and performance of two classification models.

METHODS

This study reviewed the birth history data collected on 5884 children born in the 5 years preceding the 2014 Ghana Demographic and Health Survey (GDHS). The 2014 GDHS is a cross-sectional nationally representative household sample survey. The relevant variables were selected using leaps-and-bounds method, and the area under curves were compared to evaluate the predictive accuracy of unweighted penalized and weighted single-level multivariable logistic regression models for predicting neonatal mortality using the 2014 GDHS data.

RESULTS

The study found neonatal mortality prevalence of 2.8%. A sample of 4514 children born in the 5 years preceding the 2014 GDHS was included in the inferential analysis. The results of the current study show that for the unweighted penalized single-level multivariable logistic model, there is an increased risk of neonatal death among babies born to mothers who received prenatal care from non-skilled worker [OR: 3.79 (95% CI: 2.52, 5.72)], multiple births [OR: 3.10 (95% CI: 1.89, 15.27)], babies delivered through caesarian section [OR: 2.24 (95% CI: 1.30, 3.85)], and household with 1 to 4 members [OR: 5.74 (95% CI: 3.16, 10.43)], respectively. The predictive accuracy of the unweighted penalized and weighted single-level multivariable logistic regression models was 82% and 80%, respectively.

CONCLUSION

The study advocates that prudent and holistic interventions should be institutionalized and implemented to address the risk factors identified in order to reduce neonatal death and, by large, improve child and maternal health outcomes to achieve the SDG target 3.2.

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.

Trends and projections of under-5 mortality in Bangladesh including the effects of maternal high-risk fertility behaviours and use of healthcare services

OBJECTIVE

This study examines trends and puts forward projections of under-5 mortality (U5M) in Bangladesh and identifies the effects of maternal high-risk fertility behaviours and use of healthcare services.

METHODS

Data from seven waves of the Bangladesh Demographic and Health Survey (1994-2014) were analyzed for trends and projections of U5M and a Chi-square (χ2) test was used to identify if there was any association with maternal high-risk fertility behaviours and use of healthcare services. A multivariate logistic regression model was used to determine the effects of fertility behaviors and healthcare usage on the occurrence of U5M adjusting with confounders.

RESULTS

U5M declined from 82.5 to 41.0 per 1000 livebirths during 1994-2014 and is projected to further reduce to 17.6 per 1000 livebirths by 2030. The study identified a noticeable regional variation in U5M with maternal high-risk fertility behaviours including age at birth <18 years (aOR: 1.84, 95% CI: 1.23-2.76) and birth interval <24 months (aOR: 1.56, 95% CI: 1.02-2.37) found to be significant determinants. There was a 39-53% decline in this rate of mortality among women that had used antenatal care services at least four times (aOR, 0.51, 95% CI: 0.27-0.97), delivery care (aOR, 0.47, 95% CI: 0.24-0.95), and had received postnatal care (aOR, 0.61, 95% CI: 0.41-0.91) in their last birth. Cesarean section was found to be associated with a 51% reduction in U5M (aOR, 0.49, 95% CI: 0.29-0.82) compared to its non-use.

CONCLUSION

The Sustainable Development Goals require a U5M rate of 25 per 1000 livebirths to be achieved by 2030. This study suggests that with the current trend of reduction, Bangladesh will achieve this target before the deadline. This study also found that maternal high-risk fertility behaviours and non-use of maternal healthcare services are very prevalent in some regions of Bangladesh and have increased the occurrence of U5M in those areas. This suggests therefore, that policies and programmes designed to reduce the pregnancy rates of women that are at risk and to encourage an increase in the use of maternal healthcare services are needed.

Risk factor of neonatal mortality in Ethiopia: multilevel analysis of 2016 Demographic and Health Survey

Background

In sub-Saharan African countries, neonatal mortality rates remain unacceptably high. Ethiopia is one of the countries in Sub-Saharan Africa with the highest death rates of newborn children. Therefore, this study aimed to identify the risk factors associated with neonatal mortality in Ethiopia at the individual and community level.

Methods

The 2016 Ethiopian Demographic and Health Survey data was accessed and used for the analysis. A total of 2449 newborn children were included in the analysis. The multilevel logistic regression model was used to identify the significant factor of neonatal mortality. Adjusted odds ratio with a 95% confidence interval and p-value < 0.05 in the multilevel model was reported.

Results

A total of 2449 newborn children were included in this study. Multiple birth type (AOR = 3.18; 95% CI 2.78, 3.63), birth order of ≥ 5 (AOR = 2.15; 95% CI 1.75, 2.64), pre-term birth (AOR = 5.97; 95% CI 4.96, 7.20), no antenatal care (ANC) visit during pregnancy (AOR = 2.33; 95% CI 2.09, 2.61), not received TT injection during pregnancy (AOR = 2.28; 95% CI 1.92, 2.71), delivered at home (AOR = 1.99; 95% CI 1.48, 2.69), less than 24 months of preceding birth interval (AOR = 1.51; 95% CI 1.35,1.68), smaller birth size (AOR = 1.58; 95% CI 1.46, 1.71), never breastfeeding (AOR = 2.43; 95% CI 2.17, 2.72), poor wealth index (AOR = 1.29; 95% CI 1.17,1.41), non-educated mothers (AOR = 1.58; 95% CI 1.46, 1.71), non-educated fathers (AOR = 1.32; 95% CI 1.12, 1.54), rural residence (AOR = 2.71; 95% CI 2.23, 3.29), unprotected water source (AOR = 1.35; 95% CI 1.16, 1.58), and have no latrine facility (AOR = 1.78; 95% CI 1.50, 2.12) were associated with a higher risk of neonatal mortality. Neonates living in Amhara, Oromia, Somali, Harari, and Dire Dawa had a higher risk of neonatal mortality compared to Tigray. Moreover, the random effects result showed that about 85.57% of the variation in neonatal mortality was explained by individual- and community-level factors.

Conclusions

The findings suggest that attention be paid to education-based programs for mothers that would highlight the benefits of delivery care services, such as ANC visits, TT injections, and facility births. Meanwhile, public health initiatives should focus on expanding access to quality sanitation facilities, especially for latrines and drinking water that could improve neonatal health at the community-level as a whole.

Factors Affecting Under-Five Mortality in Ethiopia: A Multilevel Negative Binomial Model

Purpose

Even though remarkable declines in under-five mortality rates noticed globally, nearly 5.6 million children still die annually before celebrating their fifth birthday. The 2016 Ethiopian Demographic and Health Survey (EDHS) report revealed that 67 children per 1000 live births died before the fifth birthday. This study aimed at determining factors affecting under-five mortality in Ethiopia using EDHS, 2016.

Materials and Methods

The data were retrieved from the EDHS 2016, and a total weighted number of 11,023 under-five children were included. Descriptive statistics were reported using tables, graphs, and texts. A multilevel negative binomial regression model was fitted, and adjusted incidence rate (ARR) with a 95% confidence interval (CI) and a p-value <0.05 were reported. The deviance test was used to check the goodness of fit.

Results

Mother attained higher education (ARR=0.25, 95% CI: 0.10–0.66), female-headed household (ARR=1.32, 95% CI: 1.05–1.66), age of household head (AIRR=1.07, 95% CI: 1.03,1.11), preceding birth interval ≥48 months (ARR=0.51, 95% CI: 0.42–0.61), child who had history of diarrhea (ARR=1.23, 95% CI: 1.08–1.41), multiple birth type (ARR=1.80, 95% CI: 1.34–2.42), mothers who delivered in health facility (ARR=0.86, 95% CI: 0.73,0.94), residents of Addis Ababa (ARR=0.52, 95% CI: 0.28–0.98), and Amhara region (ARR=1.43, 95% CI: 1.09, 1.88) were statistically significant with the number of under-five mortality.

Conclusion

In this study, under-five mortality remains a public health problem in Ethiopia. Educational status of the mother, women delivered at health institution, preceding birth interval 24–35 and ≥48, and residents of Addis Ababa reduced the incidence of under-five mortality. On the other hand, being a female household head, age of mother at first giving birth, being employed, having multiple births, and childhood diarrhea were associated with a higher incidence of under-five mortality. This finding suggests that enhancing opportunities to female education, addressing regional disparities, and encouraging mothers to deliver at health institutions will help to reduce the burden of under-five mortality.