Wealth and health revisited: Economic growth and wellbeing in developing countries, 1970 to 2015

Is the economic uncertainty- human health relationship nonlinear? An empirical analysis for the China

The health costs of economic uncertainty always remain a major concern among policymakers of China. The theoretical and empirical literature on the economic uncertainty-human health nexus is still in its infancy stage. This study is firmly rooted in the economic uncertainty theory advanced by Baker, Bloom, & Davis. In this study, the primary objective of the analysis is to estimate the asymmetric impact of economic uncertainty on human health in China's economy. In order to evaluate the short and long-run estimates of economic uncertainty on human health across various quantiles, we have employed the linear and nonlinear QARDL models. The linear QARDL model shows that the long-run relationship between economic uncertainty and the infant mortality rate is positive and significant at all quantiles, while the long-run relationship between economic uncertainty and the death rate is positive and significant at higher quantiles. The nonlinear QARDL model reveals that, in the long run, the relationship between the positive shock of economic uncertainty and the infant mortality rate is positive and significant at quantiles 0.30 to 0.95, while the long-run relationship between the positive shock of economic uncertainty and the death rate is positive and significant at higher quantiles. The relationship between the negative shock of economic uncertainty and the infant mortality rate is negative and significant at the highest quantiles, while the relationship between the negative shock of economic uncertainty and death rate is negative and significant at higher quantiles in the long run. The findings indicate a positive relationship between economic uncertainty in China and higher rates of infant mortality and death. Thus, adopting suitable policies for controlling economic uncertainty can help in improving human health in China.

Economic uncertainty and population health: insights from emerging markets and developing countries

This study employs a Bayesian panel vector autoregressive model to examine the impact of economic uncertainty on public health, using an annual, country-level panel dataset of 103 emerging markets and developing countries spanning the years 1995 through 2019. The results from the full sample suggest that the immediate effects of heightened economic uncertainty on health are marginal, yet it may engender prolonged life expectancy and lowered mortality rates. The analysis unveils considerable heterogeneities among various country classifications. The health-enhancing effects of economic uncertainty are predominantly discernible in emerging markets, low-income and upper-middle-income countries. Additionally, a diminution in suicide rates, attributed to escalated economic uncertainty, is uniquely detected in upper-middle-income countries. Furthermore, economic growth and healthcare expenditure emerge as paramount determinants in bolstering overall population health, particularly in lower-middle-income countries. The detrimental effect of environmental pollution on health is more pronounced in emerging markets and middle-income nations. Excluding high-income countries, it is essential to emphasize the beneficial health outcomes resulting from financial development and globalization, as well as the deleterious effects of environmental pollution. Lastly, several policy implications aligned with the findings are outlined, providing a roadmap for decision-makers in these diverse economies to promote better health outcomes.

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model

BACKGROUND

Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR).

METHOD

Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR.

RESULTS

The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan.

CONCLUSION

The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.

Spatiotemporal analysis of the effect of global development indicators on child mortality

BACKGROUND

Child mortality continue to be a major public health issue in most developing countries; albeit there has been a decline in global under-five deaths. The differences in child mortality can best be explained by socioeconomic and environmental inequalities among countries. In this study, we explore the effect of country-level development indicators on under-five mortality rates. Specifically, we examine potential spatio-temporal heterogeneity in the association between major world development indicators on under-five mortality, as well as, visualize the global differential time trend of under-five mortality rates.

METHODS

The data from 195 countries were curated from the World Bank's World Development Indicators (WDI) spanning from 2000 to 2017 and national estimates for under-five mortality from the UN Inter-agency Group for Child Mortality Estimation (UN IGME).We built parametric and non-parametric Bayesian space-time interaction models to examine the effect of development indicators on under-five mortality rates. We also used employed Bayesian spatio-temporal varying coefficient models to assess the spatial and temporal variations in the effect of development indicators on under-five mortality rates.

RESULTS

In both parametric and non-parametric models, the results show indicators of good socioeconomic development were associated with a reduction in under-five mortality rates while poor indicators were associated with an increase in under-five mortality rates. For instance, the parametric model shows that gross domestic product (GDP) (β = - 1.26, [CI - 1.51; - 1.01]), current healthcare expenditure (β = - 0.40, [CI - 0.55; - 0.26]) and access to basic sanitation (β = - 0.03, [CI - 0.05; - 0.01]) were associated with a reduction under-five mortality. An increase in the proportion practising open defecation (β = 0.14, [CI 0.08; 0.20]) an increase under-five mortality rate. The result of the spatial components spatial variation in the effect of the development indicators on under-five mortality rates. The spatial patterns of the effect also change over time for some indicators, such as PM2.5.

CONCLUSION

The findings show that the burden of under-five mortality rates was considerably higher among sub-Saharan African countries and some southern Asian countries. The findings also reveal the trend in reduction in the sub-Saharan African region has been slower than the global trend.

Is Economic Growth Good for Population Health? A Critical Review

A large multidisciplinary literature discusses the relationship between economic growth and population health. The idea that economic growth is good for societies has inspired extensive academic debate, but conclusions have been mixed. To help shed light on the subject, this paper focuses on opportunities for consensus in this large literature. Much scholarship finds that the health-growth relationship varies according to (1) which aspect of "health" is under consideration, (2) shape (e.g., positive linear or logarithmic), (3) issues of timing (e.g., growth over the short or long term), (4) a focus on health inequalities as opposed to population averages, and (5) multivariable relationships with additional factors. After reflecting upon these findings, I propose that economic growth promotes health in some respects, for some countries, and in conjunction with other life-supporting priorities, but does not by itself improve population health generally speaking. I then argue there is already wide, interdisciplinary consensus to support this stance. Moreover, policies focusing exclusively on economic growth threaten harm to both population health and growth, which is to say that political dynamics are also implicated. Yet multivariable approaches can help clarify the bigger picture of how growth relates to health. For moving this literature forward, the best opportunities may involve the simultaneous analysis of multiple factors. The recognition of consensus around these issues would be welcome, and timely.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42650-023-00072-y.

Consistencies and contradictions: Revisiting the relationship between women's education and infant mortality from a distributional perspective

The connection between women's education and infant mortality is one of the most consistent and powerful relationships established in public health. A large body of cross-national research highlights the benefits of women's access to education, especially for improving population health in developing countries. However, most of this literature assumes the relationship is uniform across cases. In this study, we revisit the education-health link using a distributional approach. To do so, we conduct a series of unconditional quantile regression analyses that estimate the impact of female secondary school enrollment on infant mortality rates across 153 countries from 1970 to 2016. This technique allows for the possibility that the relationship between education and health may vary across the distribution of mortality. Indeed, results show that the education advantage is distribution-specific. We find that the expected benefits of women's education are limited to the middle of the distribution where infant mortality rates range from about 11 to 55 deaths per 1000 live births. However, we find no significant effect where mortality is comparatively low or high. Both consistent with and contradictory to prior research, these findings provide a more nuanced picture of how women's access to education relates to global health inequalities.

An Integrated Analysis of Social, Economic, and Environmental Indicators' Effects on Public Health and Health Inequality Globally: From the Perspective of Vulnerability

Public health and health inequality have been widely researched as they are essential for human development and social justice. Although factors influencing public health and health inequality have been explored, an integrated and comprehensive analysis of social, economic, and environmental indicators' effects on public health and health inequality globally is yet to be conducted. The current study addresses this gap by using a theoretical framework that integrates these three dimensions, examining their effects on public health and health inequality from the perspective of vulnerability. Considering the spatial heterogeneity across countries, spatial econometric models and geographically weighted regressions were conducted for the examination of these effects. Our findings reveal the social indicators of urbanisation ratio, social education level, and social governance capacity had positive effects on public health promotion and health inequality elimination globally. Besides these, environmental risk and economic capacity had relatively low impacts on health inequality. Further, the geographically weighted regression results indicate that vulnerability's effects on public health and health inequality varied significantly across countries. This integrated analysis provides national policymakers with a new perspective of vulnerability for public health promotion and health inequality reduction.

Ethnic diversity and mortality in northwest Burkina Faso: An analysis of the Nouna health and demographic surveillance system from 2000 to 2012

Ethnic diversity has been a topic of contention across the globe, contrasted with economic development, social security, and political stability. The link between health and ethnic diversity is not yet well established especially in low-middle- income countries. Our study aims to explore the association between ethnic diversity and all-cause mortality in rural areas of Burkina Faso. We used data from the Nouna Health & Demographic Surveillance System (HDSS) collected between 2000 and 2012. To derive Standardized Mortality Ratios (SMR), the observed number of deaths was compared to the expected deaths based on the entire HDSS taking into account sex, age, rainy season, calendar year, and village. SMR were calculated for ethnic and religious diversity on a village level (using the Simpson Index), sub-region, wealth, and distance to Healthcare Facilities (HCF). Furthermore, we modeled SMR with a multilevel random intercept Poisson regression considering individual ethnic and religious groups in addition to the above-mentioned village-level information. Village wealth (poorest fifth: SMR 1.07; 95% CI: 1.02-1.13, richest fifth: SMR 0.85; 95% CI: 0.82-0.88), distance to HCF (within the village: SMR 0.88; 95% CI: 0.85-0.91, further than 5km: SMR 1.13; 95% CI: 1.10-1.16), and sub-region showed significant associations with overall mortality. Villages belonging to the third with the highest ethnic diversity had lowered SMR (0.86; 95% CI: 0.84-0.89) compared to the entire HDSS, while those belonging to the lowest diversity third yielded elevated SMR (1.13; 95% CI: 1.09-1.17). The multilevel model confirmed the association. Our study showed that historically established ethnic diversity in rural areas of Burkina Faso was associated with lower all-cause mortality. Generally, the literature suffers from a lack of standardization in defining ethnic diversity, along with measuring it. More research is needed to understand this relation and to establish it in different settings.

Empirical Analysis of Factors Influencing Healthcare Efficiency among Emerging Countries

Numerous factors, including inefficient utilization of healthcare resources have been attributed to the poor health outcome. The study aims to compare the efficiency of health expenses and its determining factors in the emerging economies based on their income levels. Data for the study is extracted from the World Bank’s World Development Indicators for 21 countries covering the period of 2000 to 2018. Analysis of the research involves two stages. Stage one computes the efficiency scores, whereas second stage examines factors affecting health efficiency by employing the Tobit regression and Simar-Wilson regression test to confirm the results. The Tobit result shows that research and development (R&D) and physicians enhanced health efficiency at the main panel, lower-middle-income, upper-middle-income, and high-income countries. Corruption remained negative with education showing mixed results. The interaction between research and development and physicians increases health efficiency in all the panels. Health research must be a policy focus if efficiency is to be achieved by the emerging economies.

Longevity and Economic Growth in China and India Using a Newly Developed Bootstrap ARDL Model

In this study, we use a recently developed Bootstrap ARDL model to examine the influence of longevity (life expectancy after giving birth) and alcohol consumption on economic progression (GDP) in both China and India during the years between 1992 and 2015. Empirical results have shown an extended link across economic development, longevity, and alcohol use in both China and India. The Granger causality test, derived from the Bootstrap ARDL model, demonstrates a unidirectional relationship between economic growth and longevity in China. However, a bidirectional causality exists between longevity and alcohol use in India. Results have important implications for Indian and Chinese governments' public health policies, focused on alcohol consumption reduction specifically, and population health generally.

The Two Faces of Diversity: The Relationships between Religious Polarization, Religious Fractionalization, and Self-rated Health

A dominant discourse in the social sciences theorizes that religious diversity puts individuals' health at risk via interreligious hostility. However, this discourse overlooks the different subtypes of religious diversity and the moderation of political institutions. To better understand the issue of diversity and health, in this study, we distinguish between two subtypes of religious diversity-polarization and fractionalization-and argue that their impacts on health are heterogeneous. Using a sample of 67,399 individuals from 51 societies drawn from the 2010-2014 wave of the World Values Survey, our multilevel analyses show that religious polarization is negatively associated with individual health, whereas the health effects of religious fractionalization are positive. Moreover, the associations between religious polarization/fractionalization and individual health are found to depend on the democratic level of the state. In more democratic countries, the negative effects of polarization on health are mitigated, and the positive effects of fractionalization are stronger.