The Indian Enigma revisited.

This paper re-enters the contested discussion surrounding the Indian Enigma, the high prevalence of chronic undernutrition in India relative to sub-Saharan Africa. Jayachandran & Pande (JP) argue that the key to the Indian Enigma lies in the worse treatment of higher birth order children, particularly girls. Analyzing new data, and taking into account issues relating to robustness to model specification, weighting and existing critiques of JP., we find: (1) Parameter estimates are sensitive to sampling design and model specification; (2) The gap between the heights of pre-school African and Indian children is closing; (3) The gap does not appear to be driven by differential associations by birth order and child sex; (4) The remaining gap is associated with differences in maternal heights. If Indian women had the heights of their African counterparts, pre-school Indian children would be taller than pre-school African children; and (5) Once we account for survey design, sibling size and maternal height, the coefficient associated with being an Indian girl is no longer statistically significant.

Gender Segregation in Education: Evidence From Higher Secondary Stream Choice in India.

This paper investigates gender-based segregation across different fields of study at the senior secondary level of schooling in a large developing country. We use a nationally representative longitudinal data set from India to analyze the extent and determinants of gender gap in higher secondary stream choice. Using fixed-effects regressions that control for unobserved heterogeneity at the regional and household levels, we find that girls are about 20 percentage points less likely than boys to study in science (STEM) and commerce streams as compared with humanities. This gender disparity is unlikely to be driven by gender-specific differences in cognitive ability, given that the gap remains large and significant even after we control for individuals' past test scores. We establish the robustness of these estimates through various sensitivity analyses: including sibling fixed effects, considering intrahousehold relationships among individuals, and addressing sample selection issues. Disaggregating the effect on separate streams, we find that girls are most underrepresented in the study of science. Our findings indicate that gender inequality in economic outcomes, such as occupational segregation and gender pay gaps, is determined by gendered trajectories set much earlier in the life course, especially at the school level.

The effect of bigger human bodies on the future global calorie requirements.

Existing studies show how population growth and rising incomes will cause a massive increase in the future global demand for food. We add to the literature by estimating the potential effect of increases in human weight, caused by rising BMI and height, on future calorie requirements. Instead of using a market based approach, the estimations are solely based on human energy requirements for maintenance of weight. We develop four different scenarios to show the effect of increases in human height and BMI. In a world where the weight per age-sex group would stay stable, we project calorie requirements to increases by 61.05 percent between 2010 and 2100. Increases in BMI and height could add another 18.73 percentage points to this. This additional increase amounts to more than the combined calorie requirements of India and Nigeria in 2010. These increases would particularly affect Sub-Saharan African countries, which will already face massively rising calorie requirements due to the high population growth. The stark regional differences call for policies that increase food access in currently economically weak regions. Such policies should shift consumption away from energy dense foods that promote overweight and obesity, to avoid the direct burden associated with these conditions and reduce the increases in required calories. Supplying insufficient calories would not solve the problem but cause malnutrition in populations with weak access to food. As malnutrition is not reducing but promoting rises in BMI levels, this might even aggravate the situation.

Reconsidering the income-health relationship using distributional regression.

We reconsider the relationship between income and health taking a distributional perspective rather than one centered on conditional expectation. Using structured additive distributional regression, we find that the association between income and health is larger than generally estimated because aspects of the conditional health distribution that go beyond the expectation imply worse outcomes for those with lower incomes. Looking at German data from the Socio-Economic Panel, we find that the risk of bad health is roughly halved when doubling the net equivalent income from 15,000 to 30,000€. This is more than tenfold of the magnitude of change found when considering expected health measures. A distributional perspective thus highlights another dimension of the income-health relation-that the poor are in particular faced with greater health risk at the lower end of the health distribution. We therefore argue that when studying health outcomes, a distributional approach that considers stochastic variation among observationally equivalent individuals is warranted.

Supermarket purchase contributes to nutrition-related non-communicable diseases in urban Kenya.

BACKGROUND: While undernutrition and related infectious diseases are still pervasive in many developing countries, the prevalence of non-communicable diseases (NCD), typically associated with high body mass index (BMI), is rapidly rising. The fast spread of supermarkets and related shifts in diets were identified as possible factors contributing to overweight and obesity in developing countries. Potential effects of supermarkets on people's health have not been analyzed up till now. OBJECTIVE: This study investigates the effects of purchasing food in supermarkets on people's BMI, as well as on health indicators such as fasting blood glucose (FBG), blood pressure (BP), and the metabolic syndrome. DESIGN: This study uses cross-section observational data from urban Kenya. Demographic, anthropometric, and bio-medical data were collected from 550 randomly selected adults. Purchasing food in supermarkets is defined as a binary variable that takes a value of one if any food was purchased in supermarkets during the last 30 days. In a robustness check, the share of food purchased in supermarkets is defined as a continuous variable. Instrumental variable regressions are applied to control for confounding factors and establish causality. RESULTS: Purchasing food in supermarkets contributes to higher BMI (+ 1.8 kg/m2) (P<0.01) and an increased probability (+ 20 percentage points) of being overweight or obese (P<0.01). Purchasing food in supermarkets also contributes to higher levels of FBG (+ 0.3 mmol/L) (P<0.01) and a higher likelihood (+ 16 percentage points) of suffering from pre-diabetes (P<0.01) and the metabolic syndrome (+ 7 percentage points) (P<0.01). Effects on BP could not be observed. CONCLUSIONS: Supermarkets and their food sales strategies seem to have direct effects on people's health. In addition to increasing overweight and obesity, supermarkets contribute to nutrition-related NCDs. Effects of supermarkets on nutrition and health can mainly be ascribed to changes in the composition of people's food choices.

A review of the ecosystem functions in oil palm plantations, using forests as a reference system.

Oil palm plantations have expanded rapidly in recent decades. This large-scale land-use change has had great ecological, economic, and social impacts on both the areas converted to oil palm and their surroundings. However, research on the impacts of oil palm cultivation is scattered and patchy, and no clear overview exists. We address this gap through a systematic and comprehensive literature review of all ecosystem functions in oil palm plantations, including several (genetic, medicinal and ornamental resources, information functions) not included in previous systematic reviews. We compare ecosystem functions in oil palm plantations to those in forests, as the conversion of forest to oil palm is prevalent in the tropics. We find that oil palm plantations generally have reduced ecosystem functioning compared to forests: 11 out of 14 ecosystem functions show a net decrease in level of function. Some functions show decreases with potentially irreversible global impacts (e.g. reductions in gas and climate regulation, habitat and nursery functions, genetic resources, medicinal resources, and information functions). The most serious impacts occur when forest is cleared to establish new plantations, and immediately afterwards, especially on peat soils. To variable degrees, specific plantation management measures can prevent or reduce losses of some ecosystem functions (e.g. avoid illegal land clearing via fire, avoid draining of peat, use of integrated pest management, use of cover crops, mulch, and compost) and we highlight synergistic mitigation measures that can improve multiple ecosystem functions simultaneously. The only ecosystem function which increases in oil palm plantations is, unsurprisingly, the production of marketable goods. Our review highlights numerous research gaps. In particular, there are significant gaps with respect to socio-cultural information functions. Further, there is a need for more empirical data on the importance of spatial and temporal scales, such as differences among plantations in different environments, of different sizes, and of different ages, as our review has identified examples where ecosystem functions vary spatially and temporally. Finally, more research is needed on developing management practices that can offset the losses of ecosystem functions. Our findings should stimulate research to address the identified gaps, and provide a foundation for more systematic research and discussion on ways to minimize the negative impacts and maximize the positive impacts of oil palm cultivation.

Do supermarkets contribute to the obesity pandemic in developing countries?

OBJECTIVE: Many developing countries are undergoing a nutrition transition with rising rates of overweight and obesity. This nutrition transition coincides with a rapid expansion of supermarkets. The objective of the present research is to study whether supermarkets directly contribute to overweight and other changes in nutritional status. DESIGN: This research builds on cross-sectional observational data. Household- and individual-level data were collected in Kenya using a quasi-experimental survey design. Instrumental variable regressions were employed to analyse the impact of supermarket purchase on nutritional status. Causal chain models were estimated to examine pathways through which supermarkets affect nutrition. SETTING: Small towns in Central Province of Kenya with and without supermarkets. SUBJECTS: A total of 615 adults and 216 children and adolescents. RESULTS: Controlling for other factors, buying in a supermarket is associated with a significantly higher BMI (P=0·018) and a higher probability of overweight (P=0·057) among adults. This effect is not observed for children and adolescents. Instead, buying in a supermarket seems to reduce child undernutrition measured by height-for-age Z-score (P=0·017). Impacts of supermarkets depend on many factors including people's initial nutritional status. For both adults and children, the nutrition effects occur through higher food energy consumption and changes in dietary composition. CONCLUSIONS: Supermarkets and their food sales strategies contribute to changing food consumption habits and nutritional outcomes. Yet the types of outcomes differ by age cohort and initial nutritional status. Simple conclusions on whether supermarkets are good or bad for nutrition and public health are not justified.

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.

The emergence of three human development clubs.

We examine the joint distribution of levels of income per capita, life expectancy, and years of schooling across countries in 1960 and in 2000. In 1960 countries were clustered in two groups; a rich, highly educated, high longevity "developed" group and a poor, less educated, high mortality, "underdeveloped" group. By 2000 however we see the emergence of three groups; one underdeveloped group remaining near 1960 levels, a developed group with higher levels of education, income, and health than in 1960, and an intermediate group lying between these two. This finding is consistent with both the ideas of a new "middle income trap" that countries face even if they escape the "low income trap", as well as the notion that countries which escaped the poverty trap form a temporary "transition regime" along their path to the "developed" group.

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.

Gender gap in parents' financing strategy for hospitalization of their children: evidence from India.

The 'missing women' dilemma in India has sparked great interest in investigating gender discrimination in the provision of health care in the country. No studies, however, have directly examined discrimination in health-care financing strategies in the case of severe illness of sons versus daughters. In this paper, we hypothesize that households who face tight budget constraints are more likely to spend their meager resources on hospitalization of boys rather than girls. We use the 60th round of the Indian National Sample Survey (2004) and a multinomial logit model to test this hypothesis and to throw some light on this important but overlooked issue. The results reveal that boys are much more likely to be hospitalized than girls. When it comes to financing, the gap in the usage of household income and savings is relatively small, while the gender gap in the probability of hospitalization and usage of more onerous financing strategies is very high. Ceteris paribus, the probability of boys to be hospitalized by financing from borrowing, sale of assets, help from friends, etc. is much higher than that of girls. Moreover, in line with our theoretical framework, the results indicate that the gender gap intensifies as we move from the richest to poorest households.

Using graphical chain models to analyze differences in structural correlates of undernutrition in Benin and Bangladesh.

Undernutrition among children is one of the most important health problems in developing countries. In order to understand the complex pathways affecting undernutrition which is crucial for policy interventions, one needs to explicitly model the dependence chain of immediate, intermediate, and underlying factors affecting undernutrition. Graphical chain models are used here to investigate the determinants of undernutrition in Benin and Bangladesh. While the dependence chain affecting undernutrition contains many common elements, the influence of demographic, cultural, and socioeconomic factors seems to have stronger direct and indirect influences in Benin than in Bangladesh, where many socioeconomic and gender related factors have a more direct influence on undernutrition.

Analyzing infant mortality with geoadditive categorical regression models: a case study for Nigeria.

In this paper, we analyze infant mortality in Nigeria based on the data set from the 1999 Nigeria Demographic and Health Survey (NDHS). We investigate spatial patterns at a highly disaggregated level of Nigerian states and consider non-linear effects of mother's age at birth. Time to the occurrence of a child's death can intuitively be considered to be categorical in nature and the determinants of a child's death may differ in different age groups. Thus, it may be desirable to investigate separately the death of a child in the first month and in the remaining 11 months of the first year of life. To avoid selection bias, the data set used for this case study is based on information on children who were born 12 months preceding the survey. Inference is Bayesian and is based on Markov chain Monte Carlo (MCMC) techniques. We find that spatial variation and the determinants of death indeed differ considerably for the two age groups considered.

Undernutrition in Benin-an analysis based on graphical models.

Undernutrition is one of the most important health problems in developing countries. Examining its determinants implies the investigation of a complex association structure including a large number of potential influence variables and different types of influences. A recently developed statistical technique to cope with such situations are graphical chain models. In this paper, this approach is used to investigate the determinants of undernutrition in Benin (West Africa). Since this method also reveals indirect influences, interesting insight is gained into the association structure of all variables incorporated. The analysis identifies mother's education, socioeconomic status, and religion as three variables with particularly strong direct and indirect linkages to undernutrition.