Journal of multidisciplinary healthcare · 2025
Relative Fat Mass and Psoriasis Risk: Evidence from NHANES 2009-2014.
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Ma Tianming, Xiang Xiaoqing, Liu Guijun
Аннотация
OBJECTIVE: This study aims to investigate the relationship between Relative Fat Mass (RFM) and the risk of psoriasis based on data from the US National Health and Nutrition Examination Survey (NHANES) from 2009 to 2014.
METHODS: This cross-sectional study included 19,565 adults aged 20 years and older. Psoriasis diagnosis was determined using self-reported questionnaires, and RFM was calculated based on established formulas. Multivariable logistic regression models were used to analyze the association between RFM and psoriasis risk, adjusting for covariates such as age, gender, race, socioeconomic factors, and health behaviors. Nonlinear relationships and potential threshold effects between RFM and psoriasis were assessed using restricted cubic splines.
RESULTS: The analysis revealed a significant positive association between RFM and psoriasis risk. Each 1-unit increase in RFM was associated with a 3% higher likelihood of psoriasis (OR=1.03, 95% CI: 1.02-1.05, P<0.05). The restricted cubic spline analysis showed a nonlinear relationship between RFM and psoriasis risk (P_non-linear=0.028). Subgroup analysis further demonstrated that income level (with lower associations observed among those with a poverty-to-income ratio ≤1.3) moderated the relationship. RFM exhibited moderate predictive performance for psoriasis risk, with an area under the receiver operating characteristic curve (AUC) of 0.549.
CONCLUSION: RFM is significantly associated with increased psoriasis risk, with a dose-response relationship observed. These findings suggest that RFM may serve as a useful predictor for psoriasis risk and could be incorporated into screening strategies for early detection and prevention.
METHODS: This cross-sectional study included 19,565 adults aged 20 years and older. Psoriasis diagnosis was determined using self-reported questionnaires, and RFM was calculated based on established formulas. Multivariable logistic regression models were used to analyze the association between RFM and psoriasis risk, adjusting for covariates such as age, gender, race, socioeconomic factors, and health behaviors. Nonlinear relationships and potential threshold effects between RFM and psoriasis were assessed using restricted cubic splines.
RESULTS: The analysis revealed a significant positive association between RFM and psoriasis risk. Each 1-unit increase in RFM was associated with a 3% higher likelihood of psoriasis (OR=1.03, 95% CI: 1.02-1.05, P<0.05). The restricted cubic spline analysis showed a nonlinear relationship between RFM and psoriasis risk (P_non-linear=0.028). Subgroup analysis further demonstrated that income level (with lower associations observed among those with a poverty-to-income ratio ≤1.3) moderated the relationship. RFM exhibited moderate predictive performance for psoriasis risk, with an area under the receiver operating characteristic curve (AUC) of 0.549.
CONCLUSION: RFM is significantly associated with increased psoriasis risk, with a dose-response relationship observed. These findings suggest that RFM may serve as a useful predictor for psoriasis risk and could be incorporated into screening strategies for early detection and prevention.