Distribution of urinary trace element exposure and dietary sources in women over 50 in an agricultural region- A community-based KoGES cohort study

Abstract

BackgroundThere 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. MethodsWe 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. ResultsOur 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. ConclusionsOur 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.