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.

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.

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.

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.

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.

Association between economic growth and early childhood undernutrition: evidence from 121 Demographic and Health Surveys from 36 low-income and middle-income countries.

BACKGROUND: Economic growth is widely regarded as a necessary, and often sufficient, condition for the improvement of population health. We aimed to assess whether macroeconomic growth was associated with reductions in early childhood undernutrition in low-income and middle-income countries. METHODS: We analysed data from 121 Demographic and Health Surveys from 36 countries done between Jan 1, 1990, and Dec 31, 2011. The sample consisted of nationally representative cross-sectional surveys of children aged 0-35 months, and the outcome variables were stunting, underweight, and wasting. The main independent variable was per-head gross domestic product (GDP) in constant prices and adjusted for purchasing power parity. We used logistic regression models to estimate the association between changes in per-head GDP and changes in child undernutrition outcomes. Models were adjusted for country fixed effects, survey-year fixed effects, clustering, and demographic and socioeconomic covariates for the child, mother, and household. FINDINGS: Sample sizes were 462,854 for stunting, 485,152 for underweight, and 459,538 for wasting. Overall, 35·6% (95% CI 35·4-35·9) of young children were stunted (ranging from 8·7% [7·6-9·7] in Jordan to 51·1% [49·1-53·1] in Niger), 22·7% (22·5-22·9) were underweight (ranging from 1·8% [1·3-2·3] in Jordan to 41·7% [41·1-42·3] in India), and 12·8% (12·6-12·9) were wasted (ranging from 1·2% [0·6-1·8] in Peru to 28·8% [27·5-30·0] in Burkina Faso). At the country level, no association was seen between average changes in the prevalence of child undernutrition outcomes and average growth of per-head GDP. In models adjusted only for country and survey-year fixed effects, a 5% increase in per-head GDP was associated with an odds ratio (OR) of 0·993 (95% CI 0·989-0·995) for stunting, 0·986 (0·982-0·990) for underweight, and 0·984 (0·981-0·986) for wasting. ORs after adjustment for the full set of covariates were 0·996 (0·993-1·000) for stunting, 0·989 (0·985-0·992) for underweight, and 0·983 (0·979-0·986) for wasting. These findings were consistent across various subsamples and for alternative variable specifications. Notably, no association was seen between per-head GDP and undernutrition in young children from the poorest household wealth quintile. ORs for the poorest wealth quintile were 0·997 (0·990-1·004) for stunting, 0·999 (0·991-1·008) for underweight, and 0·991 (0·978-1·004) for wasting. INTERPRETATION: A quantitatively very small to null association was seen between increases in per-head GDP and reductions in early childhood undernutrition, emphasising the need for direct health investments to improve the nutritional status of children in low-income and middle-income countries. FUNDING: None.

A reversal in the relationship of human development with fertility?

Myrskylä et al. (2009) found that the relationship between the human development index (HDI) and the total fertility rate (TFR) reverses from negative (i.e., increases in HDI are associated with decreases in TFR) to positive (i.e., increases in HDI are associated with increases in TFR) at an HDI level of 0.86. In this article, we show that the reversal in the HDI-TFR relationship is robust to neither the UNDP's recent revision in the HDI calculation method nor the decomposition of the HDI into its education, standard-of-living, and health subindices.

Patterns of frailty in older adults: comparing results from higher and lower income countries using the Survey of Health, Ageing and Retirement in Europe (SHARE) and the Study on Global AGEing and Adult Health (SAGE).

We use the method of deficit accumulation to describe prevalent and incident levels of frailty in community-dwelling older persons and compare prevalence rates in higher income countries in Europe, to prevalence rates in six lower income countries. Two multi-country data collection efforts, SHARE and SAGE, provide nationally representative samples of adults aged 50 years and older. Forty items were used to construct the frailty index in each data set. Our study shows that the level of frailty was distributed along the socioeconomic gradient in both higher and lower income countries such that those individuals with less education and income were more likely to be frail. Frailty increased with age and women were more likely to be frail in most countries. Across samples we find that the level of frailty was higher in the higher income countries than in the lower income countries.

Inequality in Human Development: An Empirical Assessment of 32 Countries.

One of the most frequent critiques of the HDI is that is does not take into account inequality within countries in its three dimensions. In this paper, we apply a simply approach to compute the three components and the overall HDI for quintiles of the income distribution. This allows a comparison of the level in human development of the poor with the level of the non-poor within countries, but also across countries. This is an application of the method presented in Grimm et al. (World Development 36(12):2527-2546, 2008) to a sample of 21 low and middle income countries and 11 industrialized countries. In particular the inclusion of the industrialized countries, which were not included in the previous work, implies to deal with a number of additional challenges, which we outline in this paper. Our results show that inequality in human development within countries is high, both in developed and industrialized countries. In fact, the HDI of the lowest quintiles in industrialized countries is often below the HDI of the richest quintile in many middle income countries. We also find, however, a strong overall negative correlation between the level of human development and inequality in human development.