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Purpose of Review: Biomarkers are commonly used in epidemiological studies to assess metals and metalloid exposure and estimate internal dose, as they integrate multiple sources and routes of exposure. Researchers are increasingly using multi-metal panels and innovative statistical methods to understand how exposure to real-world metal mixtures affects human health. Metals have both common and unique sources and routes of exposure, as well as biotransformation and elimination pathways. The development of multi-element analytical technology allows researchers to examine a broad spectrum of metals in their studies; however, their interpretation is complex as they can reflect different windows of exposure and several biomarkers have critical limitations. This review elaborates on more than 500 scientific publications to discuss major sources of exposure, biotransformation and elimination, and biomarkers of exposure and internal dose for 12 metals/metalloids, including 8 non-essential elements (arsenic, barium, cadmium, lead, mercury, nickel, tin, uranium) and 4 essential elements (manganese, molybdenum, selenium, and zinc) commonly used in multi-element analyses., Recent Findings: We conclude that not all metal biomarkers are adequate measures of exposure and that understanding the metabolic biotransformation and elimination of metals is key to metal biomarker interpretation. For example, whole blood is a good biomarker of exposure to arsenic, cadmium, lead, mercury, and tin, but it is not a good indicator for barium, nickel, and uranium. For some essential metals, the interpretation of whole blood biomarkers is unclear. Urine is the most commonly used biomarker of exposure across metals but it should not be used to assess lead exposure. Essential metals such as zinc and manganese are tightly regulated by homeostatic processes; thus, elevated levels in urine may reflect body loss and metabolic processes rather than excess exposure. Total urinary arsenic may reflect exposure to both organic and inorganic arsenic, thus, arsenic speciation and adjustment for arsebonetaine are needed in populations with dietary seafood consumption. Hair and nails primarily reflect exposure to organic mercury, except in populations exposed to high levels of inorganic mercury such as in occupational and environmental settings. When selecting biomarkers, it is also critical to consider the exposure window of interest. Most populations are chronically exposed to metals in the low-to-moderate range, yet many biomarkers reflect recent exposures. Toenails are emerging biomarkers in this regard. They are reliable biomarkers of long-term exposure for arsenic, mercury, manganese, and selenium. However, more research is needed to understand the role of nails as a biomarker of exposure to other metals. Similarly, teeth are increasingly used to assess lifelong exposures to several essential and non-essential metals such as lead, including during the prenatal window. As metals epidemiology moves towards embracing a multi-metal/mixtures approach and expanding metal panels to include less commonly studied metals, it is important for researchers to have a strong knowledge base about the metal biomarkers included in their research. This review aims to aid metals researchers in their analysis planning, facilitate sound analytical decision-making, as well as appropriate understanding and interpretation of results., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Purpose of Review: Hundreds of millions of people worldwide are exposed to arsenic via contaminated water. The goal of this study was to identify whether arsenic-associated lung function deficits resemble obstructive- or restrictive-like lung disease, in order to help illuminate a mechanistic pathway and identify at-risk populations., Recent Findings: We recently published a qualitative systematic review outlining the body of research on arsenic and non-malignant respiratory outcomes. Evidence from several populations, at different life stages, and at different levels of exposure showed consistent associations of arsenic exposure with chronic lung disease mortality, respiratory symptoms, and lower lung function levels. The published review, however, only conducted a broad qualitative description of the published studies without considering specific spirometry patterns, without conducting a meta-analysis, and without evaluating the dose-response relationship. We searched PubMed and Embase for studies on environmental arsenic exposure and lung function. We performed a meta-analysis using inverse-variance-weighted random effects models to summarize adjusted effect estimates for arsenic and forced expiratory volume in one second (FEV 1 ), forced vital capacity (FVC), and FEV 1 /FVC ratio. Across nine studies, median water arsenic levels ranged from 23 to 860 μg/L. The pooled estimated mean difference (MD) comparing the highest category of arsenic exposure (ranging from > 11 to > 800 μg/L) versus the lowest (ranging from < 10 to < 100 μg/L) for each study for FEV 1 was - 42 mL (95% confidence interval (CI) - 70, - 16) and for FVC was - 50 mL (95% CI - 63, - 37). Three studies reported effect estimates for FEV 1 /FVC, for which there was no evidence of an association; the pooled estimated MD was 0.01 (95% CI - 0.005, 0.024). This review supports that arsenic is associated with restrictive impairments based on inverse associations between arsenic and FEV 1 and FVC, but not with FEV 1 /FVC. Future studies should confirm whether low-level arsenic exposure is a restrictive lung disease risk factor in order to identify at-risk populations in the USA.