Body mass index as indicator of standard of living in developing countries

Abstract

Objective: To assess the suitability of the body mass index (BMI) as an indicator of standard of living in developing countries. Design, setting and subjects: The analysis is based on data collected in the ®rst two rounds of the Ghana Living Standards Survey, held in 1987a88 (GLSS-I) and 1988a89 (GLSS-II). The dataset provides information on a wide range of socio-economic variables, at the individual, the household and the community level, including the height and weight data of approximately 9000 adults in the 20±65 y age bracket. Method: Bivariate analysis was used to assess, at the individual level and at the level of population groups, the relationships between adult Body Mass Index and selected household characteristics such as income and expenditure, years of schooling of head of household, access to services, quality of housing, and nutritional status of children. Through multiple regression, indicative estimates have been derived of the effects of these variables on adult BMI. For comparison, the same relationships were investigated for weight and height. Results and conclusion: At the individual level, BMI shows a signi®cantly positive relation with the various socio-economic indicators of living standard, though the correlation coef®cients indicate a poor ®t. However, at the level of population groups, the relationship between BMI and other characteristics of socio-economic development is strong, with a correlation coef®cient of 0.86 between mean BMI and mean per capita expenditures of 12 population groups in Ghana, presumed to be at different levels of standard of living. The relationships between weight and the various socioeconomic characteristics were comparable to those for BMI, while height was poorly correlated with the selected household variables. Results suggest that in low-income countries, information on adult BMI (mean and distribution) can be used for assessing differences in standards of living between population groups or for monitoring changes over time. Sponsorship: The project is co-®nanced by the Netherlands' Ministry of Development Cooperation, within the context of the Re Âseau SADAOC-Programme (Food Security and Sustainable Development in West-Africa). Descriptors: body mass index (BMI); standards of living; developing countries

Epidemiology of undernutrition in adults in Dhaka slum households, Bangladesh

“…Other studies have found that BMI was worse in low-income households (Pryer, 1990;Nube et al, 1998;Sarlio-Lahteenkorva and Lahelma, 1999;Delpeuch et al, 2000;Hakeem, 2001). Households where the head of household's occupational group was casual wage worker (unskilled) or dependent self-employed had the worse BMI compared with other occupational groups.…”

“…Earlier work by Pryer (1993) indicated that BMI was associated with livelihood groups, where the poorest groups (female-headed households and casual unskilled labour) had the lowest BMI for men and women, compared with the richest groups (traders and landlords) who had the highest BMI for men and women. Several studies have demonstrated that BMI is associated with low income (Pryer, 1990;Nube et al, 1998;Sarlio-Lahteenkorva and Lahelma, 1999;Delpeuch et al, 2000;Hakeem, 2001), low assets (Pryer, 1990(Pryer, , 1993, expenditure (Pryer, 1990;Nube et al, 1998), years of schooling (Sen, 1991), quality of housing and access to services (Nube et al, 1998), occupational groups (Pryer, 1993) and loans (Pryer, 1990;2003).…”

Body Mass Index and Chronic Energy Deficiency among Adults of Tharu Population, Uttarakhand, India

“…[8] The prevalence of Chronic Energy Deficiency (CED) measured through BMI is generally considered a good indicator of not only the nutritional status but also the poor demographic, socio-economic and environmental conditions of the population, especially adult population of developing countries. [9][10][11][12][13][14][15] Hitherto, majority of studies on body composition from India have been restricted to nontribal populations. [16] There is urgent need to evaluate the nutritional status of various tribes of India.…”

Relationships between undernutrition prevalence among children and adult women at national and subnational level

“…Probably, partially in response to these problems with respect to the various indicators of human development and poverty, over recent years anthropometric information is increasingly being used and accepted as an indicator of overall human well being (Nubé et al, 1998;Srinivasan, 2000;Nubé, 2001;Carter & Maluccio, 2003). In comparison with income or expenditure data, there is no need for information on prices or on purchasing power, and also no need for inflation correction factors when analyzing trends over time.…”