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KMID : 1155220240490010054
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Journal of the Korean Society of Health Information and Health Statistics
2024 Volume.49 No. 1 p.54 ~ p.61
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Evaluating the Predictive Efficiency of Obesity-related Factors for Type 2 Diabetes: A Panel Study Using KoGES Data
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Kim Young-Joo
Yeom Hyun-E
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Abstract
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Objectives: Obesity is a global health concern, widely recognized for its association with the risk of developing type 2 diabetes. This study aimed to investigate the relative predictive efficacy of obesity-related indicators, including BMI, body fat percentage, and waist-to-hip ratio, in predicting the inci- dence of type 2 diabetes in Korean middle-aged to older adults.
Methods: Using twelve years of panel data derived from the Korean Genome and Epi- demiology Study, we conducted a logit regression analysis to evaluate the predictive efficiency of three obesity-related indicators while controlling for individual characteristics and behavioral risk factors.
Results: For initial screening, we examined the variation of three obesity indexes explained by age and male indicators. Among the three obesity indexes, about 11.3% to 49% of variations in body fat percentage and waist-to-hip ratio were explained away by age and male gender, but these two factors hardly explained BMI variation. We showed that all three obesity-related indicators were significant predictors of type 2 diabetes without other controls in the model. However, once controlling for socioeconomic and behavioral factors likely associated with health, we showed that only BMI remained a significant predictor of type 2 diabetes. We further showed that older age, male gender, smoking, and sleep duration were also significant predictors of type 2 diabetes, other than BMI.
Conclusions: Our findings underscore the relatively superior predic- tive efficacy of BMI beyond the other obesity indicators for type 2 diabetes risk. The results indicate that a comprehensive assessment, combined with secure BMI monitoring, is imperative for preventing and early detecting type 2 diabetes, especially in populations with multiple risk factors.
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KEYWORD
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Obesity, Diabetes, BMI, Body fat percentage, Waist-to-hip ratio
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