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 first two rounds of the Ghana Living Standards Survey, held in 1987/88 (GLSS-I) and 1988/89 (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 significantly positive relation with the various socio-economic indicators of living standard, though the correlation coefficients indicate a poor fit. However, at the level of population groups, The relationship between BMI and other characteristics of socio-economic development is strong with a correlation coefficient 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. Result 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.
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 first two rounds of the Ghana Living Standards Survey, held in 1987/88 (GLSS-I) and 1988/89 (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 significantly positive relation with the various socio-economic indicators of living standard, though the correlation coefficients indicate a poor fit. However, at the level of population groups, The relationship between BMI and other characteristics of socio-economic development is strong with a correlation coefficient 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. Result 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.
Authors: Antònia Flaquer; Clemens Baumbach; Jennifer Kriebel; Thomas Meitinger; Annette Peters; Melanie Waldenberger; Harald Grallert; Konstantin Strauch Journal: PLoS One Date: 2014-08-25 Impact factor: 3.240