Diabetes in Latin America and the Caribbean: Assessing differences in patterns among elderly people

Purpose This study examines the population-based prevalence of diabetes among elderly people in seven countries of Latin America and the Caribbean. It also analyzes the age and sex-specific differences in patterns of diabetes prevalence as well as the effect of other socioeconomic and anthropometric covariates. Methods The study included 9,544 individuals, aged 60 and over. Diabetes was evaluated using self-reported measures. The differences in patterns of diabetes prevalence were analyzed using the Brass logit system. We used logistic regressions to assess the role of covariates. Results Diabetes prevalence reached 16.7% of the survey sample. Prevalence rates were higher in Mexico (22.2%) and Barbados (21.7%) and lowest in Argentina (12.5%), Uruguay (13.1%) and Chile (13.4%). Brazil and Cuba have intermediate levels. Argentina and Cuba have prevalence rates that are higher at younger ages than in the average of the Latin America and the Caribbean. In Brazil, Cuba and Uruguay shorter individuals are more likely to have diabetes than those who are taller. Larger concentration of central fat, captured by waist-to-hip ratio, increases the odds of reporting being diabetic. Coefficients are significant in all countries, except Chile and Cuba. Effects of central fat obesity are stronger in Mexico and Uruguay. In Barbados, Brazil and Cuba, higher values of BMI are also associated with higher prevalence of diabetes. However, BMI is only weakly associated with prevalence in any of the other countries. Elderly women have higher prevalence rates than men in most countries in the region, except Argentina and Mexico. We find that central obesity, height and BMI are important predictors of diabetes prevalence among elderly in Latin America and the Caribbean. Conclusion This study explores the differences in age patterns in an innovative way, which makes it easier to contrast countries in terms of earlier versus later onset of the disease. Policy-makers in those countries, who usually lack adequate information, can use our findings to plan interventions that might result in reductions of disease incidence.