Economic Growth and Childhood Malnutrition in Low- and Middle-Income Countries.

Importance: Economic growth may reduce childhood malnutrition through improvements of several contributing factors, but the empirical evidence is mixed. Identifying the most important factors that contribute to child malnutrition and their associations with economic growth can inform decision-making about targeted investments to improve children's health. Objective: To assess the associations between economic growth and malnutrition, contributing factors and malnutrition, and economic growth and contributing factors of malnutrition in low- and middle-income countries (LMICs). Design, Setting, and Participants: This cross-sectional study used data from 239 Demographic and Health Surveys from January 1, 1990, to December 31, 2021. Observations included 1 138 568 children aged 0 to 35 months with valid anthropometric measures and information on contributing factors of malnutrition from 58 LMICs. Data were analyzed from May 20, 2022, to February 16, 2023. Exposure: National per-capita gross domestic product (GDP) was used as a proxy for economic growth. Main Outcomes and Measures: Six measures of childhood malnutrition were constructed: stunting (height-for-age z score <-2), underweight (weight-for-age z score <-2), wasting (weight-for-height z score <-2), overweight (weight-for-height z score >2), obesity (weight-for-height z score >3), and dietary diversity failure (consumption of less than 5 of 8 different food groups in the past 24 hours). Eighteen contributing factors of malnutrition were constructed, of which 10 were underlying determinants (eg, access to improved sanitation) and 8 were immediate determinants (eg, breastfeeding initiation). Results: A total of 1 138 568 children (mean [SD] age, 17.14 [10.26] months; 579 589 [50.9%] boys and 558 979 [49.1%] girls) were included in the analysis. Of these, 27.3% (95% CI, 27.2%-27.4%) had stunting; 25.7% (95% CI, 25.6%-25.8%), underweight; 11.2% (95% CI, 11.1%-11.2%), wasting; 3.8% (95% CI, 3.7%-3.8%), overweight; 1.1% (95% CI, 1.1%-1.1%), obesity; and 79.8% (95% CI, 79.7%-79.9%), dietary diversity failure. Per-capita GDP was weakly associated with childhood malnutrition. The odds ratios associated with a 5% increase in per-capita GDP were 0.99 (95% CI, 0.99-1.00) for stunting, 1.01 (95% CI, 1.00-1.01) for wasting, 1.00 (95% CI, 1.00-1.00) for underweight, 0.98 (95% CI, 0.98-0.98) for overweight, 0.98 (95% CI, 0.97-0.98) for obesity, and 1.03 (95% CI, 1.01-1.04) for dietary diversity failure. Although strong associations were found between many contributing factors and most outcomes for malnutrition, associations identified between per-capita GDP and these contributing factors themselves were ambiguous. Conclusions and Relevance: In this multicountry cross-sectional study, economic growth was weakly associated with childhood malnutrition and several contributing factors. To reduce child malnutrition, economic growth may need to be accompanied by more targeted investments to improve contributing factors that are strongly associated with child malnutrition, such as maternal health and education.

Joint distribution of child mortality and wealth across 30 sub-Saharan African countries over 2000-2019.

Background: While reductions in child mortality have been observed across sub-Saharan African countries in the last 30 years, narrowing the gaps in under-five mortality across socioeconomic groups also requires an understanding of the multiple associations between health and welfare and socioeconomic drivers. We examined the probability density distributions in under-five mortality within countries and joint pathways of under-five mortality and wealth over time. Methods: We used 69 Demographic and Health Surveys and 19 Malaria Indicator Surveys from 30 sub-Saharan African countries, with each country having at least two surveys conducted since 2000. We constructed a cross-country wealth index and estimated under-five death prevalence. We examined the pure distribution in under-five mortality prevalence and the joint probability distribution of wealth and under-five mortality prevalence over time, including the area of confidence ellipse which spanned the two dimensions of mortality and wealth and covered 75% of the mass of the joint distribution. Results: Most countries experienced decreases in under-five mortality along with increases in wealth over time. However, we observed great variations in the evolution of the joint distributions across countries over time. For instance, the areas of confidence ellipse ranged from 0.178 in Ethiopia (2000) to 1.119 in Angola (2006). The change (over time) in the area of confidence ellipses ranged from 0.010 in Tanzania to 0.844 in Angola between the 2000s and 2010s. The ranking of country performance on under-five mortality varied greatly, depending on whether performance summary indicators were based on disaggregation by wealth or on full non-disaggregated distributions. Conclusions: Our analysis points to the relevance of full distributions of health and joint distributions of health and wealth as complementary indicators of distributions of health across socioeconomic status, in assessing country performance on health.

Toward mandatory health insurance in low-income countries? An analysis of claims data in Tanzania.

Many low-income countries are in the process of scaling up health insurance with the goal of achieving universal coverage. However, little is known about the usage and financial sustainability of mandatory health insurance. This study analyzes 26 million claims submitted to the Tanzanian National Health Insurance Fund (NHIF), which covers two million public servants for whom public insurance is mandatory, to understand insurance usage patterns, cost drivers, and financial sustainability. We find that in 2016, half of policyholders used a health service within a single year, with an average annual cost of 33 US$ per policyholder. About 10% of the population was responsible for 80% of the health costs, and women, middle-age and middle-income groups had the highest costs. Out of 7390 health centers, only five health centers are responsible for 30% of total costs. Estimating the expected health expenditures for the entire population based on the NHIF cost structure, we find that for a sustainable national scale-up, policy makers will have to decide between reducing the health benefit package or increasing revenues. We also show that the cost structure of a mandatory insurance scheme in a low-income country differs substantially from high-income settings. Replication studies for other countries are warranted.

An index of access to essential infrastructure to identify where physical distancing is impossible.

To identify areas at highest risk of infectious disease transmission in Africa, we develop a physical distancing index (PDI) based on the share of households without access to private toilets, water, space, transportation, and communication technology and weight it with population density. Our results highlight that in addition to improving health systems, countries across Africa, especially in the western part of Africa, need to address the lack of essential domestic infrastructure. Missing infrastructure prevents societies from limiting the spread of communicable diseases by undermining the effectiveness of governmental regulations on physical distancing. We also provide high-resolution risk maps that show which regions are most limited in protecting themselves. We find considerable spatial heterogeneity of the PDI within countries and show that it is highly correlated with detected COVID-19 cases. Governments could pay specific attention to these areas to target limited resources more precisely to prevent disease transmission.

Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach.

BACKGROUND: The burden of child under-nutrition still remains a global challenge, with greater severity being faced by low- and middle-income countries, despite the strategies in the Sustainable Development Goals (SDGs). Globally, malnutrition is the one of the most important risk factors associated with illness and death, affecting hundreds of millions of pregnant women and young children. Sub-Saharan Africa is one of the regions in the world struggling with the burden of chronic malnutrition. The 2018 Zambia Demographic and Health Survey (ZDHS) report estimated that 35% of the children under five years of age are stunted. The objective of this study was to analyse the distribution, and associated factors of stunting in Zambia. METHODS: We analysed the relationships between socio-economic, and remote sensed characteristics and anthropometric outcomes in under five children, using Bayesian distributional regression. Georeferenced data was available for 25,852 children from two waves of the ZDHS, 31% observation were from the 2007 and 69% were from the 2013/14. We assessed the linear, non-linear and spatial effects of covariates on the height-for-age z-score. RESULTS: Stunting decreased between 2007 and 2013/14 from a mean z-score of 1.59 (credible interval (CI): -1.63; -1.55) to -1.47 (CI: -1.49; -1.44). We found a strong non-linear relationship for the education of the mother and the wealth of the household on the height-for-age z-score. Moreover, increasing levels of maternal education above the eighth grade were associated with a reduced variation of stunting. Our study finds that remote sensed covariates alone explain little of the variation of the height-for-age z-score, which highlights the importance to collect socio-economic characteristics, and to control for socio-economic characteristics of the individual and the household. CONCLUSIONS: While stunting still remains unacceptably high in Zambia with remarkable regional inequalities, the decline is lagging behind goal two of the SDGs. This emphasises the need for policies that help to reduce the share of chronic malnourished children within Zambia.

Modelling children's anthropometric status using Bayesian distributional regression merging socio-economic and remote sensed data from South Asia and sub-Saharan Africa.

A history of insufficient nutritional intake is reflected by low anthropometric measures and can lead to growth failures, limited mental development, poor health outcomes and a higher risk of dying. Children below five years are among those most vulnerable and, while improvements in the share of children affected by insufficient nutritional intake has been observed, both sub-Saharan Africa and South Asia have a disproportionately high share of growth failures and large disparities at national and sub-national levels. In this study, we use a Bayesian distributional regression approach to develop models for the standard anthropometric measures, stunting and wasting. This approach allows us to model both the mean and the standard deviation of the underlying response distribution. Accordingly, the whole distribution of the anthropometric measures can be evaluated. This is of particular importance, considering the fact that (severe) growth failures of children are defined having a z-score below -2 (-3), emphasising the need to extend the analysis beyond the conditional mean. In addition, we merge individual data taken from the Demographic and Health Surveys with remote sensed data for a large sample of 38 countries located in sub-Saharan Africa and South Asia for the period 1990-2016, in order to combine individual and household specific characteristics with geophysical and environmental characteristics, and to allow for a comparison over time. Our results show besides gender differences across space, and strong non-linear effects of included socio-economic characteristics, in particular for maternal education and the wealth of the household that, surprisingly, in the presence of socio-economic characteristics, remote sensed data does not contribute to variations in growth failures, and including a pure spatial effect excluding remote sensed data leads to even better results. Further, while all regions showed improvements towards the target of the Sustainable Development Goals (SDGs), our analysis identifies hotspots of growth failures at sub-national levels within India, Nigeria, Niger, and Madagascar, emphasising the need to accelerate progress to reach the target set by the SDGs.

Nationally and regionally representative analysis of 1.65 million children aged under 5 years using a child-based human development index: A multi-country cross-sectional study.

BACKGROUND: Education and health are both constituents of human capital that enable people to earn higher wages and enhance people's capabilities. Human capabilities may lead to fulfilling lives by enabling people to achieve a valuable combination of human functionings-i.e., what people are able to do or be as a result of their capabilities. A better understanding of how these different human capabilities are produced together could point to opportunities to help jointly reduce the wide disparities in health and education across populations. METHODS AND FINDINGS: We use nationally and regionally representative individual-level data from Demographic and Health Surveys (DHS) for 55 low- and middle-income countries (LMICs) to examine patterns in human capabilities at the national and regional levels, between 2000 and 2017 (N = 1,657,194 children under age 5). We graphically analyze human capabilities, separately for each country, and propose a novel child-based Human Development Index (HDI) based on under-five survival, maternal educational attainment, and measures of a child's household wealth. We normalize the range of each component using data on the minimum and maximum values across countries (for national comparisons) or first-level administrative units within countries (for subnational comparisons). The scores that can be generated by the child-based HDI range from 0 to 1. We find considerable heterogeneity in child health across countries as well as within countries. At the national level, the child-based HDI ranged from 0.140 in Niger (with mean across first-level administrative units = 0.277 and standard deviation [SD] 0.114) to 0.755 in Albania (with mean across first-level administrative units = 0.603 and SD 0.089). There are improvements over time overall between the 2000s and 2010s, although this is not the case for all countries included in our study. In Cambodia, Malawi, and Nigeria, for instance, under-five survival improved over time at most levels of maternal education and wealth. In contrast, in the Philippines, we found relatively few changes in under-five survival across the development spectrum and over time. In these countries, the persistent location of geographical areas of poor child health across both the development spectrum and time may indicate within-country poverty traps. Limitations of our study include its descriptive nature, lack of information beyond first- and second-level administrative units, and limited generalizability beyond the countries analyzed. CONCLUSIONS: This study maps patterns and trends in human capabilities and is among the first, to our knowledge, to introduce a child-based HDI at the national and subnational level. Areas of chronic deprivation may indicate within-country poverty traps and require alternative policy approaches to improving child health in low-resource settings.

Individual and social predictors of smoking and obesity: A panel study in Germany.

This is a longitudinal study of changes in smoking behaviour as well as becoming overweight/obese (OW/OB) and the strength of their association with personal factors such as self-control, mental health, and socioeconomic status (SES) versus their connection with the behaviour of other household members. Furthermore, we investigate that in terms of roles within a household, who is more vulnerable towards the behaviour of others. We used a hybrid model that followed individual adults (person-level fixed-effect) who participated in a national representative panel survey in Germany, SOEP, between 2008 and 2016 and answered all SF-12 items (N = 6874). The count of members in a household showing the associated adverse health behaviour was the nested random-effect. Compared with other predictors, the likelihood of a person becoming OW/OB had the strongest association with the number of cohabits who were also OW/OB and it became worse as this number increased (OR 7.18, 95% CI: 2.10-24.54 and 12.44, 95% CI: 1.53-100.85, for men and women respectively, e.g. compared with being married 2.83, 95% CI: 2.28-3.53 and 1.82, 95% CI: 1.42-2.34). However, for smoking the same rapid trend was not observed. Particularly, becoming OW/OB in female (adult) children was strongly associated with the behaviour of others (compared with household head or partner). For smoking the strongest link with others was among women who were head of the household. For both behaviours, we found neither mental health nor self-control to be strong predictors. Our findings indicate that various factors do not play equal roles in changes in health behaviour and particularly for women, becoming OW/OB is strongly connected with the behaviour of others. We further discuss the potential importance of social norms that might be helpful in developing more effective policies incorporating social connections as well as norms.

Selective mortality and the anthropometric status of children in low- and middle-income countries.

Despite a close relationship between the childrens' anthropometric status and mortality rates, the highest mortality rates are concentrated in sub-Saharan Africa, while the lowest anthropometric indicators, in particular the height-for-age z-scores, are concentrated in South Asia. This discrepancy should, however, be expected to decrease when one accounts for the survivorship bias, i.e. selective mortality. We analyse whether the survivorship bias can explain these observed differences in three standard anthropometric indicators (stunting, underweight and wasting) by using individual data of children from six waves of Demographic and Health Surveys for a large cross-section of 37 low- and middle-income countries between 1991 and 2016. We use both a matching approach and semi-parametric regression to estimate the values for the anthropometric status of deceased children. The results are twofold: first, both methods reveal that the imputed values for the anthropometric indicators are, on average, between 0.10 and 0.25 standard deviations lower than the observed anthropometric indicators. Second, since the share of deceased children in our sample is below ten per cent, the contribution of the anthropometric status of deceased children to overall anthropometric indicators is small and therefore only influences it marginally.

Correction to: Agricultural trade policies and child nutrition in low- and middle-income countries: a cross-national analysis.

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Agricultural trade policies and child nutrition in low- and middle-income countries: a cross-national analysis.

BACKGROUND: There has been growing interest in understanding the role of agricultural trade policies in diet and nutrition. This cross-country study examines associations between government policies on agricultural trade prices and child nutrition outcomes, particularly undernutrition. METHODS: This study links panel data on government distortions to agricultural incentives to data from 212,258 children aged 6 to 35 months participating in Demographic and Health Surveys from 22 countries between 1991 and 2010. Country fixed-effects regression models were used to examine the association between within-country changes in nominal rates of assistance to tradable agriculture (government price distortions as a percentage of original prices) and child nutritional outcomes (height-for-age, weight-for-age, and weight-for-height Z-scores) while controlling for a range of time-varying country covariates. RESULTS: Five-year average nominal rates of assistance to tradable agriculture ranged from - 72.0 to 45.5% with a mean of - 5.0% and standard deviation of 18.9 percentage points. A 10-percentage point increase in five-year average rates of assistance to tradable agriculture was associated with improved height-for-age (0.02, 95% CI: 0.00-0.05) and weight-for-age (0.05, 95% CI: 0.02-0.09) Z-scores. Improvements in nutritional status were greatest among children who had at least one parent earning wages in agriculture, and effects decreased as a country's proportion of tradable agriculture increased, particularly for weight-for-age Z-scores. CONCLUSIONS: Government assistance to tradable agriculture, such as through reduced taxation, was associated with small but significant improvements in child nutritional status, especially for children with a parent earning wages in agriculture when the share of tradable agriculture was not high.

Levels and trends of childhood undernutrition by wealth and education according to a Composite Index of Anthropometric Failure: evidence from 146 Demographic and Health Surveys from 39 countries.

BACKGROUND: Governments have endorsed global targets to reduce childhood undernutrition as part of the Sustainable Development Goals. Understanding the socioeconomic differences in childhood undernutrition has the potential to be helpful for targeting policy to reach these goals. METHODS: We specify a logistic regression model with the Composite Index of Anthropometric Failure (CIAF) as the outcome and indicator variables for wealth quartiles, maternal education categories and a set of covariates as explanatory variables. Wealth and education variables are interacted with a period indicator for 1990-2000 compared with 2001-2014 to observe differences over time. Based on these regressions we calculate predicted CIAF prevalence by wealth and education categories and over time. RESULTS: The sample included 146 surveys from 39 low-income and lower-middle-income countries with an overall sample size of 533 217 children. CIAF prevalence was 47.5% in 1990-2000, and it declined to 42.6% in 2001-2014. In 1990-2000 the CIAF prevalence of children with mothers with less than primary education was 31 percentage points higher than for mothers with secondary or higher education. This difference slightly decreased to 27 percentage points in 2001-2014. The difference in predicted CIAF prevalence of children from the highest and lowest wealth quartiles was 21 percentage points and did not change over time. CONCLUSIONS: We find evidence for persistent and even increasing socioeconomic inequalities in childhood undernutrition, which underlines the importance of previous calls for equity-driven approaches targeting the most vulnerable to reduce childhood malnutrition.

Measuring Socioeconomic Inequalities With Predicted Absolute Incomes Rather Than Wealth Quintiles: A Comparative Assessment Using Child Stunting Data From National Surveys.

OBJECTIVES: To compare the predictive power of synthetic absolute income measures with that of asset-based wealth quintiles in low- and middle-income countries (LMICs) using child stunting as an outcome. METHODS: We pooled data from 239 nationally representative household surveys from LMICs and computed absolute incomes in US dollars based on households' asset rank as well as data on national consumption and inequality levels. We used multivariable regression models to compare the predictive power of the created income measure with the predictive power of existing asset indicator measures. RESULTS: In cross-country analysis, log absolute income predicted 54.5% of stunting variation observed, compared with 20% of variation explained by wealth quintiles. For within-survey analysis, we also found absolute income gaps to be predictive of the gaps between stunting in the wealthiest and poorest households (P < .001). CONCLUSIONS: Our results suggest that absolute income levels can greatly improve the prediction of stunting levels across and within countries over time, compared with models that rely solely on relative wealth quintiles.

The association of parental education with childhood undernutrition in low- and middle-income countries: comparing the role of paternal and maternal education.

Background: Most existing research on the association of parental education with childhood undernutrition focuses on maternal education and often ignores paternal education. We systematically investigate differences in maternal and paternal education and their association with childhood undernutrition. Methods: One hundred and eighty Demographic and Health Surveys from 62 countries performed between 1990 and 2014 were analysed. We used linear-probability models to predict childhood undernutrition prevalences, measured as stunting, underweight and wasting, for all combinations of maternal and paternal attainment in school. Models were adjusted for demographic and socio-economic covariates for the child, mother and household, country-level fixed effects and clustering. Additional specifications adjust for local area characteristics instead of country fixed effects. Results: Both higher maternal and paternal education levels are associated with lower childhood undernutrition. In regressions adjusted for child age and sex as well as country-level fixed effects, the association is stronger for maternal education than for paternal education when their combined level of education is held constant. In the fully adjusted models, the observed differences in predicted undernutrition prevalences are strongly attenuated, suggesting a similar importance of maternal and paternal education. These findings are confirmed by the analysis of composite schooling indicators. Conclusions: We find that paternal education is similarly important for reducing childhood undernutrition as maternal education and should therefore receive increased attention in the literature.

The HIV Epidemic in Sub-Saharan Africa is Aging: Evidence from the Demographic and Health Surveys in Sub-Saharan Africa.

We use the individual-level data from all available Demographic and Health Surveys (DHS) from 27 sub-Saharan African countries conducted between 2003 and 2012 (40 population-based and nationally representative surveys in total) to calculate HIV testing consent rates and HIV prevalence for each country separately, as well as for the pooled sample. The pooled sample comprised of 427,130 individuals. In most countries HIV prevalence in adults aged 45 years and above is higher than in the total population. We further show that over the past decade HIV prevalence has increased in older age groups, while it has decreased in younger ones. While the age patterns of HIV consent rates vary across the 27 countries included in our sample, analysis of the pooled sample across all countries reveals a u-shaped relationship with lowest consent rates around age 35 years and higher consent rates among younger and older people. We argue that future DHS and other population-based HIV surveys should offer HIV testing to all adults without age limits.

Desired Fertility and Number of Children Born Across Time and Space.

Economists have often argued that high fertility rates are mainly driven by women's demand for children (and not by family planning efforts) with low levels of unwanted fertility across countries (and hence with little room for family planning efforts to reduce population growth). We study the relationship between wanted fertility and number of children born in a panel of 200 country-years controlling for country fixed effects and global time trends. In general, we find a close relationship between wanted and actual fertility, with one desired child leading to one additional birth. However, our results also indicate that in the last 20 years, the level of unwanted births has stayed at 2 across African countries but has, on average, decreased from 1 to close to 0 in other developing countries. Hence, women in African countries are less able to translate child preferences into birth outcomes than women in other developing countries, and forces other than fertility demand have been important for previous fertility declines in many developing countries. Family planning efforts only partially explain the observed temporal and spatial differences in achieving desired fertility levels.