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Association of the body roundness index and sun sensitivity: insights from the NHANES data with machine learning
Zhaofu Tan1, Yanjie Chen1, Yi Ou1
1Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Background:
Sun sensitivity, an abnormal skin reaction to ultraviolet radiation, increases the risk of melanoma and impairs the quality of life. In recent times, the body roundness index (BRI) has been suggested to be associated with various health conditions. Nevertheless, the association between the BRI and sun sensitivity remains not well understood. The purpose of this research was to investigate the association between the BRI and sun sensitivity.
Methods:
This research utilized information acquired from the National Health and Nutrition Examination Survey (NHANES) conducted in the United States (2001-2006, 2009-2018; n = 9,999, including 1,085 cases of sun sensitivity). The association between the BRI and sun sensitivity was analyzed, and the Boruta algorithm was employed for feature selection. Subsequently, seven machine learning (ML) models were used to predict the risk of sun sensitivity, and the independent effect of the BRI was analyzed using Shapley additive explanations (SHAP).
Results:
After full adjustment, each one-unit increase in the BRI significantly increased the risk of sun sensitivity (OR = 1.08, 95% CI: 1.04-1.11, P < 0.001). Quartile analysis showed that participants in the highest BRI quartile (≥ 6.32) had a 47% higher risk of sun sensitivity (OR = 1.47, 95% CI: 1.17-1.83, P < 0.001) than those in the lowest quartile. RCS confirmed a linear dose-response relationship (P- nonlinear >0.05). The LightGBM model outperformed the other models (test AUC = 0.859, 95% CI: 0.847-0.871), with the BRI identified as a key predictor alongside race, the poverty-income ratio, and hypertension, as determined by SHAP analysis.
Conclusions:
This is the first study to systematically evaluate the relationship between the BRI and risk of sun sensitivity using ML methods. The study identified a significant association between the BRI and risk of sun sensitivity. These findings provide new evidence regarding the etiology of sun sensitivity and offer a scientific basis for personalized disease management and public health interventions.
