贝叶斯核机器回归模型在环境健康研究中的应用及R语言实现

doi:10.12183/j.scjpm.2025.0148

Abstract

Abstract: Objective The Bayesian kernel machine regression (BKMR) model is a new method developed rapidly in recent years. This study aims to introduce the application of the BKMR model in the study of the health effects of multi-pollutant exposure and R implementation. Methods Taking the dataset published by the National Institute of Environmental Health Sciences (NIEHS) as an example, we used BKMR model to analyze the impact of multi-pollutant on health, and introduced its implementation steps based on R language. Results Using on the "bkmr" package of R language, the BKMR model could analyze the univariate exposure-response relationship between the exposure and the health outcomes, the interactions among multiple exposures, and estimate the effect of single exposure and the joint effect of multi-pollutant exposure. Conclusion The BKMR model can analyze the exposure-response relationship and health effects of multi-pollutant exposure on health outcomes, which is a new analytical method for studying the health effect of combined environmental exposures.

Key words: Bayesian kernel machine regression (BKMR), Multi-pollutant exposure, Health effect, R language

CLC Number:

R195.1

OU Keer, ZHENG Wenyuan, LI Xing, ZENG Weilin, RONG Zuhua, GONG Dexin, XIAO Jianpeng. Application of Bayesian kernel machine regression model in environmental health research and R implementation[J].South China Journal of Preventive Medicine, 2025, 51(2): 148-153.

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Application of Bayesian kernel machine regression model in environmental health research and R implementation

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