Marfo Akua, Obeng-Gyasi Emmanuel
Department of Built Environment, North Carolina A&T State University, Greensboro, NC 27411, USA.
Environmental Health and Disease Laboratory, North Carolina A&T State University, Greensboro, NC 27411, USA.
Med Sci (Basel). 2024 Dec 11;12(4):71. doi: 10.3390/medsci12040071.
: Environmental exposures, such as heavy metals, can significantly affect physical activity, an important determinant of health. This study explores the effect of physical activity on combined exposure to cadmium, lead, and mercury (metals), using data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). Physical activity was measured with ActiGraph GT3X+ devices worn continuously for 7 days, while blood samples were analyzed for metal content using inductively coupled plasma mass spectrometry. Descriptive statistics and multivariable linear regression were used to assess the impact of multi-metal exposure on physical activity. Additionally, Bayesian Kernel Machine Regression (BKMR) was applied to explore nonlinear and interactive effects of metal exposures on physical activity. Using a Gaussian process with a radial basis function kernel, BKMR estimates posterior distributions via Markov Chain Monte Carlo (MCMC) sampling, allowing for robust evaluation of individual and combined exposure-response relationships. Posterior Inclusion Probabilities (PIPs) were calculated to quantify the relative importance of each metal. The linear regression analysis revealed positive associations between cadmium and lead exposure and physical activity. BKMR analysis, particularly the PIP, identified lead as the most influential metal in predicting physical activity, followed by cadmium and mercury. These PIP values provide a probabilistic measure of each metal's importance, offering deeper insights into their relative contributions to the overall exposure effect. The study also uncovered complex relationships between metal exposures and physical activity. In univariate BKMR exposure-response analysis, lead and cadmium generally showed positive associations with physical activity, while mercury exhibited a slightly negative relationship. Bivariate exposure-response analysis further illustrated how the impact of one metal could be influenced by the presence and levels of another, confirming the trends observed in univariate analyses while also demonstrating the complexity varying doses of two metals can have on either increased or decreased physical activity. Additionally, the overall exposure effect analysis across different quantiles revealed that higher levels of combined metal exposures were associated with increased physical activity, though there was greater uncertainty at higher exposure levels as the 95% credible intervals were wider. Overall, this study fills a critical gap by investigating the interactive and combined effects of multiple metals on physical activity. The findings underscore the necessity of using advanced methods such as BKMR to capture the complex dynamics of environmental exposures and their impact on human behavior and health outcomes.
环境暴露,如重金属暴露,会显著影响身体活动,而身体活动是健康的一个重要决定因素。本研究利用2013 - 2014年美国国家健康与营养检查调查(NHANES)的数据,探讨身体活动对镉、铅和汞(金属)联合暴露的影响。身体活动通过连续佩戴7天的ActiGraph GT3X +设备进行测量,同时使用电感耦合等离子体质谱法分析血样中的金属含量。描述性统计和多变量线性回归用于评估多金属暴露对身体活动的影响。此外,应用贝叶斯核机器回归(BKMR)来探索金属暴露对身体活动的非线性和交互作用。BKMR使用具有径向基函数核的高斯过程,通过马尔可夫链蒙特卡罗(MCMC)采样估计后验分布,从而能够对个体和联合暴露 - 反应关系进行稳健评估。计算后验包含概率(PIPs)以量化每种金属的相对重要性。线性回归分析揭示了镉和铅暴露与身体活动之间的正相关关系。BKMR分析,特别是PIP,确定铅是预测身体活动中最有影响力的金属,其次是镉和汞。这些PIP值提供了每种金属重要性的概率度量,更深入地洞察了它们对总体暴露效应的相对贡献。该研究还揭示了金属暴露与身体活动之间的复杂关系。在单变量BKMR暴露 - 反应分析中,铅和镉通常与身体活动呈正相关,而汞呈现出轻微的负相关关系。双变量暴露 - 反应分析进一步说明了一种金属的影响如何受到另一种金属的存在和水平的影响,证实了单变量分析中观察到的趋势,同时也展示了两种金属不同剂量对身体活动增加或减少的复杂影响。此外,不同分位数的总体暴露效应分析表明,较高水平的联合金属暴露与身体活动增加有关,尽管在较高暴露水平下不确定性更大,因为95%可信区间更宽。总体而言,本研究通过调查多种金属对身体活动的交互和联合效应填补了一个关键空白。研究结果强调了使用BKMR等先进方法来捕捉环境暴露的复杂动态及其对人类行为和健康结果影响的必要性。