Abstract：
BACKGROUND: There is a noticeable lack of information on the levels of both non-essential and essential trace elements in women aged over 50. The main objective of this study is to investigate trace element concentrations and explore the influence of sociodemographic factors and dietary sources of exposure in this demographic.
METHODS: We analyzed 19 trace elements, including manganese, cobalt, copper, zinc, molybdenum, chromium, nickel, arsenic, strontium, cadmium, tin, antimony, cesium, barium, tungsten, mercury, thallium, lead, and uranium, using ICP-MS and mercury analyzer. Urine samples were obtained from a cohort of 851 women aged over 50 who participated in the 8th KoGES-Ansung study (2017-2018). Multiple linear models were employed to explore associations between urinary trace element concentrations and sociodemographic factors and dietary sources of exposure. We used K-means clustering to discern patterns of exposure to trace elements and identify contributing factors and sources.
RESULTS: Our findings indicate higher concentrations of molybdenum (Mo), arsenic (As), cadmium (Cd), and lead (Pb) in our study population compared to women in previous studies. The study population were clustered into two distinct groups, characterized by lower or higher urinary concentrations. Significant correlations between age and urinary concentrations were observed in Ni. Smoking exhibited positive associations with urinary Cd and As. Associations with dietary sources of trace elements were more distinct in women in the high-exposure group. Urinary antimony (Sb) was positively linked to mushroom and egg intake, As to mushroom and fish, and Hg to egg, dairy products, fish, seaweed, and shellfish.
CONCLUSIONS: Our study underscores the significant gap in understanding urinary concentrations of trace elements in women aged over 50. With higher concentrations of certain elements compared to previous studies and significant correlations between age, smoking, and specific food sources, it is imperative to address this gap through targeted dietary source-specific risk management.
METHODS: We analyzed 19 trace elements, including manganese, cobalt, copper, zinc, molybdenum, chromium, nickel, arsenic, strontium, cadmium, tin, antimony, cesium, barium, tungsten, mercury, thallium, lead, and uranium, using ICP-MS and mercury analyzer. Urine samples were obtained from a cohort of 851 women aged over 50 who participated in the 8th KoGES-Ansung study (2017-2018). Multiple linear models were employed to explore associations between urinary trace element concentrations and sociodemographic factors and dietary sources of exposure. We used K-means clustering to discern patterns of exposure to trace elements and identify contributing factors and sources.
RESULTS: Our findings indicate higher concentrations of molybdenum (Mo), arsenic (As), cadmium (Cd), and lead (Pb) in our study population compared to women in previous studies. The study population were clustered into two distinct groups, characterized by lower or higher urinary concentrations. Significant correlations between age and urinary concentrations were observed in Ni. Smoking exhibited positive associations with urinary Cd and As. Associations with dietary sources of trace elements were more distinct in women in the high-exposure group. Urinary antimony (Sb) was positively linked to mushroom and egg intake, As to mushroom and fish, and Hg to egg, dairy products, fish, seaweed, and shellfish.
CONCLUSIONS: Our study underscores the significant gap in understanding urinary concentrations of trace elements in women aged over 50. With higher concentrations of certain elements compared to previous studies and significant correlations between age, smoking, and specific food sources, it is imperative to address this gap through targeted dietary source-specific risk management.
摘要：
背景：关于50岁以上女性的非必需和必需微量元素水平的信息明显缺乏。这项研究的主要目的是调查微量元素浓度，并探讨社会人口统计学因素和饮食来源对该人口统计学的影响。
方法：我们分析了19种微量元素，包括锰，钴,铜，锌，钼,铬,镍,砷,锶,镉,锡，锑,铯,钡,钨,水银,铊,铅,还有铀,使用ICP-MS。尿液样本来自851名50岁以上的女性队列，这些女性参与了第八届KoGES-Ansung研究（2015-2016）。采用多个线性模型来探索尿微量元素浓度与社会人口统计学因素和饮食暴露来源之间的关联。我们使用K均值聚类来辨别微量元素的暴露模式，并确定我们研究人群中的促成因素和来源。
结果：我们的发现表明钼（Mo）的浓度较高，砷（As），镉(Cd),与以前研究中的女性相比，我们研究人群中的铅（Pb）。研究人群分为两个不同的群体，以更低或更高的尿浓度为特征。在Mo和Ni中观察到年龄与尿液浓度之间的显着相关性。吸烟与尿Cd和As呈正相关。在高暴露组的女性中，与微量元素饮食来源的关联更为明显。尿锑（Sb）与蘑菇和鸡蛋的摄入量呈正相关，至于蘑菇和鱼，汞和鸡蛋，乳制品,鱼,海藻,还有贝类.
结论：我们的研究强调了50岁以上女性在了解尿微量元素浓度方面的显著差距。与以前的研究相比，某些元素的浓度更高，并且年龄之间存在显着相关性，吸烟,和特定的食物来源，必须通过有针对性的饮食来源特异性风险管理来解决这一差距.
方法：我们分析了19种微量元素，包括锰，钴,铜，锌，钼,铬,镍,砷,锶,镉,锡，锑,铯,钡,钨,水银,铊,铅,还有铀,使用ICP-MS。尿液样本来自851名50岁以上的女性队列，这些女性参与了第八届KoGES-Ansung研究（2015-2016）。采用多个线性模型来探索尿微量元素浓度与社会人口统计学因素和饮食暴露来源之间的关联。我们使用K均值聚类来辨别微量元素的暴露模式，并确定我们研究人群中的促成因素和来源。
结果：我们的发现表明钼（Mo）的浓度较高，砷（As），镉(Cd),与以前研究中的女性相比，我们研究人群中的铅（Pb）。研究人群分为两个不同的群体，以更低或更高的尿浓度为特征。在Mo和Ni中观察到年龄与尿液浓度之间的显着相关性。吸烟与尿Cd和As呈正相关。在高暴露组的女性中，与微量元素饮食来源的关联更为明显。尿锑（Sb）与蘑菇和鸡蛋的摄入量呈正相关，至于蘑菇和鱼，汞和鸡蛋，乳制品,鱼,海藻,还有贝类.
结论：我们的研究强调了50岁以上女性在了解尿微量元素浓度方面的显著差距。与以前的研究相比，某些元素的浓度更高，并且年龄之间存在显着相关性，吸烟,和特定的食物来源，必须通过有针对性的饮食来源特异性风险管理来解决这一差距.
