제2형 당뇨병 예측을 위한 비만지표와 위험 요인의 영향력 탐색Evaluating the Predictive Efficiency of Obesity-related Factors for Type 2 Diabetes: A Panel Study Using KoGES Data
- Other Titles
- Evaluating the Predictive Efficiency of Obesity-related Factors for Type 2 Diabetes: A Panel Study Using KoGES Data
- Authors
- 김영주; 염현이
- Issue Date
- Feb-2024
- Publisher
- 한국보건정보통계학회
- Keywords
- Obesity; Diabetes; BMI; Body fat percentage; Waist-to-hip ratio; .
- Citation
- 보건정보통계학회지, v.49, no.1, pp 54 - 61
- Pages
- 8
- Journal Title
- 보건정보통계학회지
- Volume
- 49
- Number
- 1
- Start Page
- 54
- End Page
- 61
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/32780
- ISSN
- 2465-8014
2465-8022
- Abstract
- 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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Collections - School of Economics > Economics Major > 1. Journal Articles
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