Inequality in Human Development: An Empirical Assessment of 32 Countries

Modeling the potential impacts of improved monthly income on child stunting in India: a subnational geospatial perspective

OBJECTIVES

Approximately one-third of the world's stunted (low height-for-age) preschool-aged children live in India. The success of interventions designed to tackle stunting appears to vary by location and depth of poverty. We developed small-area estimation models to assess the potential impact of increments in household income on stunting across the country.

DESIGN

Two nationally representative cross-sectional datasets were used: India's National Family Health Survey 4 (2015-2016) and the 68th round of the National Sample Survey on consumer expenditure. The two datasets were combined with statistical matching. Gaussian process regressions were used to perform geospatial modelling of 'stunting' controlling for household wealth and other covariates.

SETTING AND PARTICIPANTS

The number of children in this sample totalled 259 627. Children with implausible height-for-age z-scores (HAZs) >5 or <-5, or missing data on drinking water, sanitation facility, mother's education, or geolocation and children not residing in mainland India were excluded, resulting in 207 695 observations for analysis.

RESULTS

A monthly transfer of ~$7 (500 Indian rupees) per capita to every household (not targeted or conditional) was estimated to reduce stunting nationally by 3.8 percentage points on average (95% credible interval: 0.14%-10%), but with substantial variation by state. Estimated reduction in stunting varied by wealth of households, with the poorest quintile being likely to benefit the most.

CONCLUSION

Improving household income, which can be supported through cash transfers, has the potential to significantly reduce stunting in parts of India where the burdens of both stunting and poverty are high. Modelling shows that for other regions, income transfers may raise incomes and contribute to improved nutrition, but there would be a need for complementary activities for alleviating stunting. While having value for the country as a whole, impact of income gained could be variable, and underlying drivers of stunting need to be tackled through supplementary interventions.

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.

The Subnational Human Development Database

In this paper we describe the Subnational Human Development Database. This database contains for the period 1990–2017 for 1625 regions within 161 countries the national and subnational values of the Subnational Human Development Index (SHDI), for the three dimension indices on the basis of which the SHDI is constructed – education, health and standard of living --, and for the four indicators needed to create the dimension indices -- expected years of schooling, mean years of schooling, life expectancy and gross national income per capita. The subnational values of the four indicators were computed using data from statistical offices and from the Area Database of the Global Data Lab, which contains indicators aggregated from household surveys and census datasets. Values for missing years were estimated by interpolation and extrapolation from real data. By normalizing the population-weighted averages of the indicators to their national levels in the UNDP-HDI database, values of the SHDI and its dimension indices were obtained that at national level equal their official versions of the UNDP.

Social factors associated with centenarian rate (CR) in 32 OECD countries

BACKGROUND

Over the last fifty years, the number of centenarians has dramatically increased. The centenarian rate (CR) is representative of the general longevity prevalent in a nation; it indicates the number of individuals aged 100 years or above at a given date divided by the size of the corresponding cohort of a given age. Two important attributes of the CR (50-54) are that it reflects both unchanged age-specific fertility and the absence of migration in populations. It can generally be used in longevity-based evaluations of the broader concept of successful ageing. As such, this retrospective analysis of the social factors that contribute to the CR (50-54) may help to identify the factors associated with successful ageing.This study estimates the CR (50-54) and elucidates the influence of social factors on successful ageing and the CR (50-54), examining 32 member countries of the Organization for Economic Co-operation and Development (OECD).

METHODS

The social indicators for this study were obtained from the United Nations database. The data for the analysis of centenarians in the 32 OECD countries were obtained from the world population prospects conducted by the United Nations. Associations between social factors and CR (50-54) were assessed using Pearson correlation coefficients and regression models.

RESULTS

Significant positive correlations were found between the CR (50-54) and the social factors of expenditure on health as a percentage of gross domestic product (HEGDP: r = 0.411, p < 0.021), general government expenditure on health as a percentage of total government expenditure (GGEH: r = 0.474, p < 0.006), the proportion of fixed-telephone subscriptions in the population (FTS: r = 0.489, p < 0.005), and the human development index (HDI: r = 0.486, p < 0.005). Finally, these CR (50-54) predictors were used to form a model of successful ageing, with higher HEGDP and GGEH as health expenditure, higher FTS as standard of living, and higher HDI as social well-being (R2 = 0.573, P < 0.025).

CONCLUSIONS

The findings suggest that an increased CR (50-54) is affected by multiple social factors involved in successful ageing. Therefore, if they wish to improve their country's CR (50-54), governments must strengthen their existing support services for the elderly through making improvements to standards of living, social well-being and through increased financing of the health sector.

Does inequality in health impede economic growth?

This paper investigates the effects of inequality in health on economic growth in low and middle income countries. The empirical part of the paper uses an original cross-national panel data set covering 62 low and middle income countries over the period 1985 to 2007. I find a substantial and relatively robust negative effect of health inequality on income levels and income growth controlling for life expectancy, country and time fixed-effects and a large number of other effects that have been shown to matter for growth. The effect also holds if health inequality is instrumented to circumvent a potential problem of reverse causality. Hence, reducing inequality in the access to health care and to health-related information can make a substantial contribution to economic growth.