Adult BMI as a health and nutritional inequality measure: applications at macro and micro-level Vasco Molini, Maarten Nubé and Bart van den Boom Centre for World Food Studies (SOW), Vrije Universiteit Amsterdam

Outline 1.Introduction 2.Health and nutritional inequalities: a macro analysis 3.Health and nutritional inequalities: a micro analysis 4. Dataset and tools 5.Results 6.Conclusions

Introduction 1.Among non- monetary measures in recent year the anthropometric ones have become a key tool for assessing poverty 2.The Body mass index (BMI) measures the joint outcomes of nutrition and health functioning. 3.A feature of anthropometric indicators of well-being such as BMI, is the direct measurement at the level of individuals. 4.The BMI can be used to analyze the intra-households allocations of food and health care and the presence of gender discrimination.

Health and nutritional inequalities: a macro analysis 1.Recent evidence on health inequality in developing countries has indicated an increase over the last 10 years. Yet this result might not be robust to the change of indicator 2.Using the BMI as indicator, we expect to find an analogue of the Kuznets curve measuring the BMI inequality as a function of stages of development: a)At very early stages, low BMI affects the lion’s share of the population. Low correlation between income and the probability of having a BMI below a certain cut-off point b)At advanced stages of development, low BMI becomes a specific feature of poorest strata of the population. The correlation might start to become negative c)At a certain level of well-being, this process reaches a turning point as the prevalence of low BMI’s also starts to fall among the poorer strata. Gradually, the correlation is likely to become weaker

Health and nutritional inequalities: a micro analysis (I) 1.In the standard neoclassical model, the household maximizes a common utility function 2.Recent evidence shows that intra- household allocation patterns are determined by bargaining between different parties and power relations inside the household condition them. 3.The nutritional status of children has been identified as a good proxy of the male female disparity in malnutrition

Health and nutritional inequalities: a micro analysis (II) 4.The evidence in this regard is not univocal. According to various studies (Doak et al., 2005 inter alia), child malnutrition is present in households where both parents are well nourished and where the female condition is not known to be particularly disfavoured. 5.Against this background, we argue that a “ceteris paribus” direct comparison between adult males’ and adult females’ BMI provides more reliable results.

Dataset and tools (macro) 1.Cross sectional country data on inequality in females’ BMI (i.e. shares of females under the 18.5 cut-off point by quintiles) and on the UNDP’s Human Development Index 2.We made use of two inequality measures directly calculated from this dataset: a.Concentration index (CI) of women below the 18.5 cut-off point. b.The quintile ratio (QR) of women undernourished in the poorest and richest quintile 3.Both measures are expected to have a peak of inequality in the form of an absolute minimum (and U-shaped instead of an inverted U-shaped curve)

The concentration index

Dataset and tools (micro) and 1998 Vietnamese Living Standard Surveys unified both in a panel of households and then of individuals 2.The households panel: Predicted percentage of undernourished (BMI<18.5) among males and females by expenditures centiles 3.The individual panel: transition matrix of male and females in 1993 and The individual panel: econometric regression on the determinants of different BMI’s growth between males and females.

Transition matrix (I) MalesFemales BMI≤ (1,151) (922) 33.4 (1,122) (1,084) 18.5<BMI ≤ (994) (991) (978) (901)

Transition matrix (II) MalesFemales BMI≤ <BMI, BMI≤20 BMI≤ <BMI, BMI≤20 BMI≤ (730) (312) (781) (257) 18.5<BMI, ≤ (166) (519) (254) (425)

Econometric regressions 1.Using the information of the same 6500 individuals collected in the two periods we tried to explain the presence of this gender bias against females through econometric analysis. 2.The BMI variation in the two periods is regressed on the expenditures variation between the two years plus other individual and household characteristics 3.To correct for endogeneity, we instrumented the expenditures variation with some exogenous variables such as assets in 1993 and education (Garret and Ruel, 1999).

Econometric regressions 1.The model was tested for the whole sample and then separately for male and females. In this latter case, the models show substantially different elasticities to income growth: that of males is almost double as compared to the females’ one 2.Females tended to benefit less from the economic improvements, in particular those belonging to more disadvantaged groups. 3.The females’ nutritional status improves less not only because the socio-economic improvements of the whole group are limited but also because, within the group (i.e. inside the ethnic minority or in the rural household) females tend to be worse-off.

Conclusions (I) 1.The present study shows how the BMI is a suitable measure for assessing the presence of health and income inequalities in developing countries both at aggregate country level and at micro household level. 2.On the macro side, we found a negative correlation between the well-being inequality based on child measures and adult females’s BMI. 3.We show that the adult females’ BMI inequality when regressed against the Human Development Index produces an U-shaped curve similar to the inverted U-shaped Kuznets curve.

Conclusions (II) 5.These results confirm our expectation on the possibility to substitute in a Kuznets-type framework the inequality in income terms with some non-monetary inequality measures without loosing significance and keeping the same pattern. 6.In micro-type analysis we show how, by means of a comparison between males and females, it can be unravelled the presence of gender discrimination inside the household 7.Vietnamese data show that males tend to benefit more than females from economic improvements. 8.The validity of present research goes beyond the specific case of Vietnam, but calls for further analysis in other developing countries where presumably gender discrimination in the access to basic households goods is similar or even more accentuated than in Vietnam