국민건강영양조사(제8기 2019~2021년)를 활용한성인의 이상지질혈증 영향요인
Analyzing the Factors Influencing Dyslipidemia in Adults Using Data from the Korea National Health and Nutrition Examination Survey (2019~2021)
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Purpose: This study aimed to identify demographic, disease, health behavior, and physical factors associated withdyslipidemia in adults. Methods: A secondary analysis was conducted using data from the 8th Korea national health andnutrition examination survey [KNHANES], including 18,691 adults. dyslipidemia according to the characteristics of thesubjects was analyed using Rao-Scott x2 test. logistic regression was employed to identify risk factors for dyslipidemia. Statistical analysis was performed using the SPSS 25.0 program. Results: Factors significantly associated withdyslipidemia included age (p<.001), sex (p<.001), average monthly household income (p=.025), economic activity(p=.046), diagnosis of hypertension (p<.001), myocardial infarction or angina (p<.001), diabetes mellitus (p<.001),smoking (p=.010), moderate intensity physical activity (p=.002), and body mass index (p<.001). The explanatory powerof these variables for the occurrence of dyslipidemia was 38% (F=39.12, p<.001). Conclusion: The research results canbe used as useful basic data for developing and applying a program to prevent and manage dyslipidemia in adults. effectivemanagement strategies are essential for the prevention and treatment of dyslipidemia.
Abstract
Purpose: This study aimed to identify demographic, disease, health behavior, and physical factors associated withdyslipidemia in adults. Methods: A secondary analysis was conducted using data from the 8th Korea national health andnutrition examination survey [KNHANES], including 18,691 adults. dyslipidemia according to the characteristics of thesubjects was analyed using Rao-Scott x2 test. logistic regression was employed to identify risk factors for dyslipidemia. Statistical analysis was performed using the SPSS 25.0 program. Results: Factors significantly associated withdyslipidemia included age (p<.001), sex (p<.001), average monthly household income (p=.025), economic activity(p=.046), diagnosis of hypertension (p<.001), myocardial infarction or angina (p<.001), diabetes mellitus (p<.001),smoking (p=.010), moderate intensity physical activity (p=.002), and body mass index (p<.001). The explanatory powerof these variables for the occurrence of dyslipidemia was 38% (F=39.12, p<.001). Conclusion: The research results canbe used as useful basic data for developing and applying a program to prevent and manage dyslipidemia in adults. effectivemanagement strategies are essential for the prevention and treatment of dyslipidemia.