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논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국보건정보통계학회 보건정보통계학회지 보건정보통계학회지 제45권 제2호
발행연도
2020.1
수록면
181 - 190 (10page)

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Objectives: This study aimed to estimate the risk of disease- and death-causing obesity and to calculate direct and indirect costs using national health insurance big data. Methods: We constructed cohort data for 10,091,251 participants who underwent a national health screening between 2003 and 2004. Cox’s proportional hazard models were adopted to analyze the relative risk (RR) of related diseases and causes of death, adjusted for age, smoking, alcohol consumption, and exercise. Population attributable risk (PAR) of obesity was calculated considering prevalence of obesity and RR of incidence and death of obesity related diseases. Socioeconomic costs were estimated including direct and indirect costs. Results: The risk of diabetes increased with increasing body mass index (BMI). In severely obese males, the risk of diabetes was 4.83 times higher than in normal weight males. In severely obese females, the risk of diabetes was 4.01 times higher than in normal weight females. In case of the socioeconomic cost of obesity, the direct and indirect costs differed by sex: the direct cost of male and female obesity was 50.8 % and 85.9 % in 2015, respectively. Conclusions: This study identified that obesity is not only a significant risk factor of diseases and death but also the cause of economic loss for the health insurance sector. Therefore, it is considered that it is necessary to develop an intervention program to manage examinees who are determined to be obese.

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