Objective: To analyze the body mass index (BMI) as an indicator of metabolic alterations, including the metabolic syndrome (MetS), at both individual level and public health level. Method: We recruited 3683 undergradu...Objective: To analyze the body mass index (BMI) as an indicator of metabolic alterations, including the metabolic syndrome (MetS), at both individual level and public health level. Method: We recruited 3683 undergraduate students (17 - 24 years old) from México City identifying metabolic alterations, including the MetS, and comparing its prevalence by BMI ranges. We applied a sensitivity analysis to define BMI optimal cut-off point values. Results: We found 14.6% of MetS prevalence with a BMI average of 24.2%, and 34.5% of overweight prevalence (BMI ≥ 25). A BMI cut-off point value of 22.5 is suggested as an upper limit of a normal weight condition, only for public health purpose;while at individual level the BMI cut-off point of 25 was corroborated as the upper limit for a normal weight condition. A public health tool to estimate the MetS prevalence based on BMI percentages is proposed, and a study case is presented. Conclusion: BMI fails predicting at individual level both, healthy condition or metabolic alterations, when values are lower than 25. At population level, the BMI is a valuable public health tool to estimate MetS prevalence: based on the prevalence of MetS by BMI ranges of a sample of the population.展开更多
文摘Objective: To analyze the body mass index (BMI) as an indicator of metabolic alterations, including the metabolic syndrome (MetS), at both individual level and public health level. Method: We recruited 3683 undergraduate students (17 - 24 years old) from México City identifying metabolic alterations, including the MetS, and comparing its prevalence by BMI ranges. We applied a sensitivity analysis to define BMI optimal cut-off point values. Results: We found 14.6% of MetS prevalence with a BMI average of 24.2%, and 34.5% of overweight prevalence (BMI ≥ 25). A BMI cut-off point value of 22.5 is suggested as an upper limit of a normal weight condition, only for public health purpose;while at individual level the BMI cut-off point of 25 was corroborated as the upper limit for a normal weight condition. A public health tool to estimate the MetS prevalence based on BMI percentages is proposed, and a study case is presented. Conclusion: BMI fails predicting at individual level both, healthy condition or metabolic alterations, when values are lower than 25. At population level, the BMI is a valuable public health tool to estimate MetS prevalence: based on the prevalence of MetS by BMI ranges of a sample of the population.
