Geographical variations in infant and child mortality in West Africa: a geo-additive discrete-time survival modelling

Zero-inflated Poisson regression analysis of factors associated with under-five mortality in Ethiopia using 2019 Ethiopian mini demographic and health survey data

BACKGROUND

Remarkable reduction in global under-five mortality has been seen over the past two decades. However, Ethiopia is among the five countries which account for about half (49%) of all under-five mortality worldwide. This study aimed at identifying factors associated with under-five children mortality in Ethiopia using the 2019 Ethiopia mini demography and health survey data.

METHODS

The most recent national representative demography and health survey data of Ethiopia, 2019 Ethiopia mini demography and health survey data, were used for this study. Count data regression models were applied to identify the factors associated with under-five children mortality. Statistical significance was declared at P-value less than 0.05.

RESULTS

Zero-Inflated Poisson (ZIP) regression model was found to be the best model compared to other count regression models based on models comparison Criteria. The ZIP model revealed that decreased risk of under-five mortality was associated with mothers aged 25-34 years, unmarried mothers, mothers delivered in health facility, mothers used Pill/IUD, mothers who had larger number of children at home whereas increased risk of under-five mortality was associated with older mothers at their first births, mothers from rural areas, mothers travel for 1-30 min and >30 min to get drinking water, mothers used charcoal and wood, children with higher birth order and multiple births.

CONCLUSIONS

In this study, place of residence, region, place of delivery, religion, age of mother, mother's age at first birth, marital status, birth order, birth type, current contraceptive type used, type of cooking fuel, time to get drinking water, and number of children at home were statistically significant factors associated with under-five mortality in Ethiopia. Thus, the Ethiopian Ministry of Health and other concerned bodies are recommended to encourage mothers to deliver at health institutions, give awareness for mothers to use Pill/IUD contraceptive type, and facilitate rural areas to have electricity and drinking water near to homes so as to minimize the under-five mortality to achieve the sustainable development goal.

Copula based trivariate spatial modeling of childhood illnesses in Western African countries

Acute respiratory infections (ARI), diarrhea, and fever are three common childhood illnesses, especially in sub-Saharan Africa. This study investigates the marginal and pairwise correlated effects of these diseases across Western African countries in a single analytical framework. Using data from nationally representative cross-sectional Demographic and Health Surveys, the study analyzed specific and correlated effects of each pair of childhood morbidity from ARI, diarrhea, and fever using copula regression models in fourteen contiguous Western African countries. Data concerning childhood demographic and socio-economic conditions were used as covariates. In this cross-sectional analysis of 152,125 children aged 0-59 months, the prevalence of ARI was 6.9%, diarrhea, 13.8%, and fever 19.6%. The results showed a positive correlation and geographical variation in the prevalence of the three illnesses across the study region. The estimated correlation and 95% confidence interval between diarrhea and fever is 0.431(0.300,0.539); diarrhea and ARI is 0.270(0.096,0.422); and fever and ARI is 0.502(0.350,0.614). The marginal and correlated spatial random effects reveal within-country spatial dependence. Source of water and access to electricity was significantly associated with any of the three illnesses, while television, birth order, and gender were associated with diarrhea or fever. The place of residence and access to newspapers were associated with fever or ARI. There was an increased likelihood of childhood ARI, diarrhea, and fever, which peaked at about ten months but decreased substantially thereafter. Mother's age was associated with a reduced likelihood of the three illnesses. The maps generated could be resourceful for area-specific policy-making to speed up mitigation processes.

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.

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

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We used 2019 Ethiopian Mini Demographic and health Survey data.

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

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

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

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

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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.

Spatial Co-Morbidity of Childhood Acute Respiratory Infection, Diarrhoea and Stunting in Nigeria

In low- and middle-income countries, children aged below 5 years frequently suffer from disease co-occurrence. This study assessed whether the co-occurrence of acute respiratory infection (ARI), diarrhoea and stunting observed at the child level could also be reflected ecologically. We considered disease data on 69,579 children (0–59 months) from the 2008, 2013, and 2018 Nigeria Demographic and Health Surveys using a hierarchical Bayesian spatial shared component model to separate the state-specific risk of each disease into an underlying disease-overall spatial pattern, common to the three diseases and a disease-specific spatial pattern. We found that ARI and stunting were more concentrated in the north-eastern and southern parts of the country, while diarrhoea was much higher in the northern parts. The disease-general spatial component was greater in the north-eastern and southern parts of the country. Identifying and reducing common risk factors to the three conditions could result in improved child health, particularly in the northeast and south of Nigeria.

A Spatial Survival Model for Risk Factors of Under-Five Child Mortality in Kenya

Child mortality is high in Sub-Saharan Africa compared to other regions in the world. In Kenya, the risk of mortality is assumed to vary from county to county due to diversity in socio-economic and even climatic factors. Recently, the country was split into 47 different administrative regions called counties, and health care was delegated to those county governments, further aggravating the spatial differences in health care from county to county. The goal of this study is to evaluate the effects of spatial variation in under-five mortality in Kenya. Data from the Kenya Demographic Health Survey (KDHS-2014) consisting the newly introduced counties was used to analyze this risk. Using a spatial Cox Proportional Hazard model, an Intrinsic Conditional Autoregressive Model (ICAR) was fitted to account for the spatial variation among the counties in the country while the Cox model was used to model the risk factors associated with the time to death of a child. Inference regarding the risk factors and the spatial variation was made in a Bayesian setup based on the Markov Chain Monte Carlo (MCMC) technique to provide posterior estimates. The paper indicate the spatial disparities that exist in the country regarding child mortality in Kenya. The specific counties have mortality rates that are county-specific, although neighboring counties have similar hazards for death of a child. Counties in the central Kenya region were shown to have the highest hazard of death, while those from the western region had the lowest hazard of death. Demographic factors such as the sex of the child and sex of the household head, as well as social economic factors, such as the level of education, accounted for the most variation when spatial differences were factored in. The spatial Cox proportional hazard frailty model performed better compared to the non-spatial non-frailty model. These findings can help the country to plan health care interventions at a subnational level and guide social and health policies by ensuring that counties with a higher risk of Under Five Child Mortality (U5CM) are considered differently from counties experiencing a lower risk of death.

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.

Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

BACKGROUND

Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities.

METHODS

In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span.

RESULTS

The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period.

CONCLUSIONS

The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

Review of How Population Change Will Transform Our World by Sarah Harper

In this book, Sarah Harper explores the relevant topic of the shift in the age structure of the world’s population. She addresses this issue by considering the entire world population. In particular, she deeply analyses causes and consequences of the age-structural change highlighting convergences and differences between populations of various geographical areas and focusing on the connections with economic and social factors. Addressed also to a wider audience, this book sheds light about the important changes of the population age structure and about the future of the world population. The author highlights differences and interconnections existing between various populations of the world, without forgetting to stress the importance to consider changes at the individual level within the society. Sarah Harper, through this book, contributes to provide instruments and knowledge to understand the populations and societies of the world.

Estimating geographic variations in the determinants of attitude towards the practice of female genital mutilation in Nigeria

Female genital mutilation (FGM) has persisted in Nigeria despite the very harmful effects on its victims. Massive inequality in the demographic and socioeconomic status of the Nigerian populace, coupled with marked differences in cultural values, have led to lopsided patterns of most health indicators based on the geographical location. The risk factors of health indicators are equally expected to vary according to location. This study aimed to explain the spatial variations in the risk factors for female cutting in Nigeria. Data were from the geo-referenced 2013 Nigeria Demographic and Health Survey. The objective was to estimate the spatially varying relationships of the factors influencing women's attitude towards female cutting in Nigeria and to identify how the variables exact influence across the states using geographically weighted logistic regression analysis - a technique that allows for spatially varying relationships among variables to be established. The results showed that women's higher educational level and higher household wealth lowered the desire for continuation of FGM everywhere in the country, but the effects of most other variables varied in direction, strength and magnitude. The findings suggest the use of local approaches to address the factors that encourage the continuation of female cutting in Nigeria.