Health care expenditure and child mortality in Nigeria

Adeosun, Oluyemi Theophilus; Faboya, Omolara Morounkeji

doi:10.1108/ijhcqa-10-2019-0172

Cited by 7 publications

(13 citation statements)

References 18 publications

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“…The health premium effect of DAH has been corroborated by a substantial number of studies on the effectiveness of health development assistance (Yogo & Mallaye, 2015). In the same vein, the pro-health impacts of education and government expenditure have been documented by Adeosun and Faboya (2020), Andriano and Monden (2019), and Sunkanmi and Olufunsho (2013).…”

Section: Discussionmentioning

confidence: 84%

Urbanization and Child Health Outcomes in Nigeria

Jemiluyi

2021

JPSS

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Against the rising trend of urbanization in Nigeria and the accompanying dramatic changes in the urbanization process, this study explores the health advantage of urbanization in Nigeria. The study specifically examines the relationship between various child health outcomes. Secondary data on neonatal, infant, and under-5 mortalities were used to measure child health outcomes. By obtaining cointegration among the collected data, the study investigates the long-run relationships between the degree of urbanization and the various child health outcomes using the Fully Modified Ordinary Least Squares(FM-OLS) estimator. The results suggest the existence of positive relationships between urbanization and child health indicators. In particular, the results show that there exist child health advantages of urbanization, with urbanization having reducing impacts on the mortality indicators. Also, public health expenditure, literacy rate, and health aids are negatively correlated with measures of children mortality. In all the estimated models, the economic growth proxy by Gross Domestic Product (GDP) has an insignificant effect on all the measures of child health outcomes. The result implies the need to pay attention to the urbanization process for an effective health plan.

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Section: Discussionmentioning

confidence: 84%

Urbanization and Child Health Outcomes in Nigeria

Jemiluyi

2021

JPSS

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“…Similarly, South Asia also has a fragile public healthcare system, which cannot effectively satisfy a massive population's health needs. Therefore, the disease burden can translate into substantial out-ofpocket expenses in many households and lead to child undernutrition [78].…”

Section: Discussionmentioning

confidence: 99%

Nutritional inequalities among under-five children: a geospatial analysis of hotspots and cold spots in 73 low- and middle-income countries

Amir-ud-Din

Fawad

Naz

et al. 2022

Int J Equity Health

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Background Child undernutrition is a severe health problem in the developing world, which affects children’s development in the long term. This study analyses the extent and patterns of under-five child undernutrition using Demographic and Health Surveys (DHS) for 73 low- and middle-income countries (LMICs). Methods First, we mapped the prevalence of undernutrition in the developing world. Second, using the LISA (a local indicator of spatial association) technique, we analyzed the geographical patterns in undernutrition to highlight the localized hotspots (regions with high undernutrition prevalence surrounded by similar other regions), cold spots (regions with low undernutrition prevalence surrounded by similar other regions), and outliers (regions with high undernutrition surrounded by low undernutrition and vice versa). Third, we used Moran’s I to find global patterns in child undernutrition. Results We find that South Asia has the highest under-five child undernutrition rates. The intra-country nutritional inequalities are highest in Burundi (stunting), Kenya (wasting), and Madagascar (underweight). The local indicator of spatial association (LISA) analysis suggests that South Asia, Middle East and North Africa (MENA) region, and Sub-Saharan Africa are undernutrition hotspots and Europe and Central Asia and Latin America, and the Caribbean are undernutrition cold spots (regions with low undernutrition surrounded by similar other regions). Getis Ord-Gi* estimates generally support LISA analysis. Moran’s I and Geary’s C gave similar results about the global patterns of undernutrition. Geographically weighted regressions suggest that several socioeconomic indicators significantly explain child undernutrition. Conclusions We found a significant within and across country variation in stunting, wasting and underweight rates among the under-five children’s population. The geospatial analysis also suggested that stunting, wasting, and underweight patterns exhibit clear regional patterns, underscoring the need for coordinated interventions at the regional level.

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“…Similarly, South Asia also has a fragile public healthcare system, which cannot effectively satisfy a massive population size's health need. Therefore, the disease burden can translate into disastrous out-of-pocket investment in many households and lead to child malnutrition as a result (Adeosun & Faboya, 2020).…”

Section: Discussionmentioning

confidence: 99%

Nutritional inequalities among under-5 children: An analysis of cross-country and within-country hotspots and cold spots in the developing world

Amir-ud-Din

Fawad

Naz

2021

Preprint

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Undernutrition of under-five children is a severe public health issue of the developing world. Around 45% of deaths among children under five years are linked to undernutrition. According to 2019 global estimates, 21% of under-five children were stunted, 7% were wasted, and 13% were underweight in 2019. However, there are wide disparities in the distribution of undernutrition within countries and across countries. As an illustration, 38% of under-five children in Pakistan are stunted. However, the stunting rate in Islamabad Capital Territory is 24% but 52% in FATA, according to Demographic and Health Surveys (DHS) data. Such disparities in undernutrition may reflect policy failures or the genetic vulnerabilities of population subgroups. To the best of our knowledge, very few studies have analyzed the geography of the undernutrition inequalities among under-five children. We analyzed the geographical patterns in child undernutrition in developing countries. First, we mapped the prevalence of undernutrition in the developing world. Secondly, using the LISA (local indicator of spatial association) technique, we analyzed the geographical patterns in the distribution of undernutrition to highlight the localized hotspots (regions with high undernutrition prevalence surrounded by similar other regions), cold spots (regions with low undernutrition prevalence surrounded by similar other regions), and outliers (regions with high undernutrition surrounded by low undernutrition and vice versa showing inequalities in the distribution in undernutrition). Additionally, we used Moran’s I to find global patterns in malnutrition.We used data from Demographic and Health Surveys (DHS) data from 73 developing countries for our study.The Global Moran’s I and LISA techniques used to estimate the global and within-country malnutrition patterns, respectively, confirm significant spatial clustering of malnutrition among under-five children. South Asia and Sub-Saharan Africa are global hotspots of child malnutrition, and Latin America and the Caribbean, and Europe and Central Asia are global cold spots of child malnutrition. There are few outliers: areas of low child malnutrition surrounded by high malnutrition and vice versa. One important policy implication of this study is that it will help identify the areas with i) high undernutrition and ii) high nutritional inequalities and help targeted health interventions in the geographical areas with a high need population.

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Health care expenditure and child mortality in Nigeria

Cited by 7 publications

References 18 publications

Urbanization and Child Health Outcomes in Nigeria

Urbanization and Child Health Outcomes in Nigeria

Nutritional inequalities among under-five children: a geospatial analysis of hotspots and cold spots in 73 low- and middle-income countries

Nutritional inequalities among under-5 children: An analysis of cross-country and within-country hotspots and cold spots in the developing world

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