Factors Affecting Herbal Medicine Use for Weight Loss in Adult Women: Results From KNHANES 2010 to 2019

Speaker(s)

ABSTRACT WITHDRAWN

OBJECTIVES: The worldwide prevalence of obesity has increased, and its high prevalence results in a substantial socioeconomic cost. This study aims to analyze the factors affecting herbal medicine (HM) use for weight loss in adult women using a large, cross-sectional, nationwide database in Korea.

METHODS: This study included 14,179 women aged 19 years or older from the Korea National Health and Nutrition Examination Survey (KNHANES) from 2010 to 2019. Three models were constructed using multiple logistic regression analyses by adding predisposing, enabling, and need factors in sequence according to Andersen’s behavioral model to identify the factors affecting HM use for weight loss in adult women. Because KNHANES was collected using complex sampling design, the sample weights provided were used in all statistical analyses.

RESULTS: In model including predisposing, enabling, and need factors, women aged >65 years were less likely to use HM for weight loss compared to those aged 19-34 years (Odds ratio [95% CI]; 0.27 [0.12, 0.61]). Women in the fifth (highest) quintile of household income had higher tendency to use HM for weight loss than those in the first (lowest) quintile (1.83 [1.05, 3.18]). Women who perceived their health as good were more likely to use HM for weight loss than women who perceived their health as very good (2.12 [1.22, 3.69]). Women who perceived their bodies as very fat had higher tendency to use HM for weight loss compared to women who perceived their bodies as very thin/thin/moderate (3.51 [2.24, 5.5]). Women with BMI ≥30 were more likely to use HM for weight loss than those with BMI <22.9 (2.22 [1.31, 3.74]).

CONCLUSIONS: Our findings may be useful in distributing resources effectively and making decisions about medical policy. In additional, these results can help clinicians and researchers make decisions.

Code

RWD186

Topic

Real World Data & Information Systems

Topic Subcategory

Health & Insurance Records Systems

Disease

Alternative Medicine, Personalized & Precision Medicine