Long-run overweight levels and convergence in body mass index

Fat–fat-free index in body mass assessment in young people

The study aimed to personalize the classification of body weight using the fat–fat-free (FFF) index with the percentage of body fat and to develop classification standards for the FFF index for men aged 18–25 years. Moreover, 1,642 adolescents (1,200 ♀) were examined. Using body composition analyzers, weight was determined, as well as overall and segmental body composition. Based on the obtained values for fat mass and fat-free tissue mass, an overall FFF index was calculated. According to the BMI classification, 9% of ♀ and 6% of ♂ are underweight, 29% of ♀ and 13% of ♂ are overweight, and 5% of the subjects are obese. Women and men classified in the same group according to BMI differed statistically significantly in terms of body weight, FM%, and FFM. In contrast to BMI and FM%, the FFF used takes into account the ratio of fat mass to fat-free tissue and muscle tissue mass. The proposed classification of FFF was made taking into account the differences that arise with sexual development and physiological changes occurring in ontogeny. Assessment of body mass using the FFF index should be used as part of preventive screening for the early diagnosis and prevention of overweight and thus many chronic diseases for which overweight or obesity is a risk factor.

Inequality in body mass indices across countries: Evidence from convergence tests

This study examines the long-term inequality in body mass index (BMI) based on convergence tests applied to a database of 172 countries recently published by the NCD Risk Factor Collaboration. First, we find that countries converge in clubs, which indicates that country disparities in BMIs will persist over time. Second, there are three and six convergence clubs in BMIs for female and male individuals, respectively. That is, we would not observe a single convergence pattern in body weights as the nutrition transition theory and the dietary convergence hypothesis seem to suggest. Females have only one healthy club (18.5 ≤ BMI < 25) and two overweight clubs (BMI ≥ 25). Males have three healthy clubs and three overweight clubs. Third, the analysis of club convergence indicates that BMI inequality has increased due to the BMI growth observed in club 1 (the one with the highest average BMI and led by the US) in each gender group. Finally, potential determinants of BMI such as globalization, human capital, income, and urbanization are relevant to understand differences across clubs. We interpret the club convergence as the result of a heterogeneous integration of countries into the global economy, which is probably related to strong domestic preferences, policies designed to manage the impacts of globalization, and shifts in productive structures.