Gribble Matthew O, Crainiceanu Ciprian M, Howard Barbara V, Umans Jason G, Francesconi Kevin A, Goessler Walter, Zhang Ying, Silbergeld Ellen K, Guallar Eliseo, Navas-Acien Ana
Department of Epidemiology and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 615 N, Wolfe Street Office W7513D, Baltimore MD 21205MD, USA.
Environ Health. 2013 Dec 9;12:107. doi: 10.1186/1476-069X-12-107.
The objective of this study was to evaluate the association between measures of body composition and patterns of urine arsenic metabolites in the 1989-1991 baseline visit of the Strong Heart Study, a cardiovascular disease cohort of adults recruited from rural communities in Arizona, Oklahoma, North Dakota and South Dakota.
We evaluated 3,663 Strong Heart Study participants with urine arsenic species above the limit of detection and no missing data on body mass index, % body fat and fat free mass measured by bioelectrical impedance, waist circumference and other variables. We summarized urine arsenic species patterns as the relative contribution of inorganic (iAs), methylarsonate (MMA) and dimethylarsinate (DMA) species to their sum. We modeled the associations of % arsenic species biomarkers with body mass index, % body fat, fat free mass, and waist circumference categories in unadjusted regression models and in models including all measures of body composition. We also considered adjustment for arsenic exposure and demographics.
Increasing body mass index was associated with higher mean % DMA and lower mean % MMA before and after adjustment for sociodemographic variables, arsenic exposure, and for other measures of body composition. In unadjusted linear regression models, % DMA was 2.4 (2.1, 2.6) % higher per increase in body mass index category (< 25, ≥25 & <30, ≥30 & <35, ≥35 kg/m2), and % MMA was 1.6 (1.4, 1.7) % lower. Similar patterns were observed for % body fat, fat free mass, and waist circumference measures in unadjusted models and in models adjusted for potential confounders, but the associations were largely attenuated or disappeared when adjusted for body mass index.
Measures of body size, especially body mass index, are associated with arsenic metabolism biomarkers. The association may be related to adiposity, fat free mass or body size. Future epidemiologic studies of arsenic should consider body mass index as a potential modifier for arsenic-related health effects.
本研究的目的是在“强心研究”1989 - 1991年基线访视中评估身体成分测量值与尿砷代谢物模式之间的关联，该研究是一项从亚利桑那州、俄克拉荷马州、北达科他州和南达科他州农村社区招募的成年人心血管疾病队列研究。
我们评估了3663名“强心研究”参与者，这些参与者的尿砷种类高于检测限，且在通过生物电阻抗测量的体重指数、体脂百分比、去脂体重、腰围及其他变量方面没有缺失数据。我们将尿砷种类模式总结为无机砷（iAs）、一甲基砷酸（MMA）和二甲基砷酸（DMA）种类在其总和中的相对贡献。我们在未调整的回归模型以及包含所有身体成分测量值的模型中，对砷种类生物标志物百分比与体重指数、体脂百分比、去脂体重和腰围类别之间的关联进行建模。我们还考虑了对砷暴露和人口统计学因素进行调整。
在对社会人口统计学变量、砷暴露以及其他身体成分测量值进行调整前后，体重指数增加均与较高的平均DMA百分比和较低的平均MMA百分比相关。在未调整的线性回归模型中，体重指数类别每增加一档（<25、≥25且<30、≥30且<35、≥35kg/m²），DMA百分比升高2.4（2.1，2.6）%，MMA百分比降低1.6（1.4，1.7）%。在未调整模型以及针对潜在混杂因素进行调整的模型中，体脂百分比、去脂体重和腰围测量值也观察到类似模式，但在对体重指数进行调整后，这些关联大多减弱或消失。
身体尺寸测量值，尤其是体重指数，与砷代谢生物标志物相关。这种关联可能与肥胖、去脂体重或身体尺寸有关。未来关于砷的流行病学研究应将体重指数视为砷相关健康影响的潜在调节因素。
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