ArticleEuropean journal of clinical nutrition2020
Differences in magnitude and rates of change in BMI distributions by socioeconomic and geographic factors in Mexico, Colombia, and Peru, 2005-2010.
Article in European journal of clinical nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Predictive Models of Atherogenic Risk in Citizens of Trujillo (Peru) Based on Associated Factors.Nutrients · 2024Article
- Brazilian Reference Percentiles for Bioimpedance Phase Angle of Healthy Individuals.Frontiers in nutrition · 2022Article
- Longitudinal changes in the retail food environment in Mexico and their association with diabetes.Health & place · 2020Article
- Shift in body fat distribution from lower body to upper body among urban Colombian women, 1988-1989 to 2007-2008.Public health nutrition · 2020Article
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Authors and funding
4 authors.
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Abstract
BACKGROUND/
objectivesPrevious studies about obesity and its associated factors in low- and middle-income countries have been based mostly on women of reproductive age. Furthermore, disproportionally changing BMI distributions have been a challenge for its appropriate modeling. In this context, we assessed the magnitude and rate of change in BMI distribution by socioeconomic and geographic factors in both sexes in Latin American countries, modeling the shape of BMI distributions. SUBJECTS/
methodsWe used data from national surveys conducted in Mexico, Colombia, and Peru at two time points between 2005 and 2013 (N = 57,414, 13,5403, and 30,811, respectively). We estimated shapes of BMI distributions for 2005 and 2010, and assessed their changes, using the generalized additive model for location, scale, and shape (GAMLSS), in which BMI was assumed to follow a Box-Cox Power Exponential (BCPE) distribution.
resultsIn all the three countries, higher education was negatively associated with BMI in women but somewhat positive in men; and household wealth was positively associated in men but not in women. Lower household wealth was associated with higher rates of change in BMI distributions in women.
conclusionEducation and household wealth were associated with BMI distributions and their change over time. Observed sex differences in these associations have implications for designing relevant policies and programs to approach target populations effectively. The BCPE-GAMLSS method can provide a useful visual assessment of time-varying measures.
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