Heavy metal exposure and risk of all-cause and

Overview

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Key numbers

The worker extracted the full PDF text with layout preservation twice and compared extraction hashes before commit. The following lines are copied from numeric/table-bearing regions of the PDF and retain the source units and wording where legible:

• 95% CI: 1.26–2.33). In contrast, blood Se showed an inverse association with all-cause mortality, with lower risks observed in Q2
• (HR = 0.61, 95% CI: 0.41–0.90) and Q4 (HR = 0.59, 95% CI: 0.38–0.93). RCS analyses showed nonlinear associations of Cd and Se
• regression suggested a positive association between mixed metal exposure and all-cause mortality (HR = 1.16, 95% CI: 0.99–1.34;
• data indicate that nearly 90% of U.S. adults are classified to metabolic risk factors, CKD, or subclinical CVD before
• as CKM stage 1 or higher, and approximately 15% have the onset of clinically manifest CVD (12). The AHA sci-
• Pb, Cd, Hg, Se, or Mn n = 14,150, leaving 25,006 partic- functional adiposity or impaired glucose regulation. Stage
• bles strata, primary sampling units, or survey weights n = fication were used, including eGFR and 10-year CVD risk.
• and ¯8%, respectively, ensuring measurement accuracy and elevated fasting glucose. Smoking status was catego-
• p (LLOD), values were imputed as LLOD defined as individuals who had smoked fewer than 100
• survey weights. The median age was approximately 56
• ratios (HRs) and 95% confidence intervals (Cis) were esti-
• mixture with mortality outcomes and to identify the prin- creased all-cause mortality (HR = 1.71, 95%CI: 1.26–
• (23). To evaluate potential interactions among metals, all 0.61, 95%CI: 0.41–0.90), Q3 (HR = 0.59, 95%CI: 0.41–
• pairwise multiplicative interaction terms among Pb, Cd, 0.85), and Q4 (HR = 0.59, 95%CI: 0.38–0.93). For cardi-
• erating interaction terms. For each metal pair, a survey- mortality was lower in Q2 (HR = 0.51, 95%CI: 0.24–
• weighted Cox proportional hazards model was fitted, in- 1.07), Q3 (HR = 0.42, 95%CI: 0.21–0.82), and Q4 (HR =
• cluding the two corresponding metal main effects, their 0.65, 95%CI: 0.34–1.25).
• As shown in Table 1, 4,394 participants from NHANES approximately 202 µg/dL.
• Table 1 Basic Information and All-Cause and Cardiovascular Mortality at baseline
• Male, n (%) 1953 (48%) 183 (61%) <0.001 2081 (48%) 55 (65%) 0.003
• Race/Ethnicity, n (%) <0.001 0.027
• • Non-Hispanic White 1617 (39%) 181 (61%) 1752 (41%) 46 (54%)
• • Non-Hispanic Black 889 (22%) 56 (19%) 924 (21%) 21 (25%)
• Physically Inactive, n (%) 2374 (58%) 213 (71%) <0.001 2522 (59%) 65 (76%) 0.008
• Alcohol Consumption (Yes), n (%) 2613 (64%) 212 (71%) 0.013 2771 (64%) 54 (64%) 0.9
• Mixture exposures of blood metals and risks of CKM stages 0–3, we identified several notable associations
• associated with a 15.7% higher risk of all-cause mortality ment. Second, Se showed an L-shaped inverse association
• (HR = 1.16; 95% CI: 0.99–1.34; P = 0.046). The relative with all-cause mortality, suggesting higher risk at low con-
• Figure b shows HRs for cardiovascular mortality for the same metal exposure categories. Error bars represent 95% confidence intervals for
• mechanisms, including oxidative stress, inflammation, en- induced renal injury increasing by more than 40%, sug-
• cardiovascular mortality (b). Solid lines represent hazard ratios estimated from RCS models, and shaded areas indicate 95% confidence
• that blood Pb levels below 50 µg/L, the traditional safety indicator within the metal mixture rather than as an inde-
• tion decline; each 10 µg/L increase in blood Pb has been reported in previous mixture exposure studies.
• Technology; LLOD: lower limit of detection; DR1IKCA: day 1 dietary recall energy
• adults with CKM stages 0–3, a prevention-oriented pop- Additional file 3: Supplementary Table 1. Pairwise interaction analyses of
• baseline blood metal concentrations may not fully repre- consent for the publication of the images in Figs. 1, 2, 3, 4 and Table 1.

Methods (brief)

• evant literature (15). Briefly, whole blood samples were some college or associate degree; college graduate or
• reduce matrix interference and protect the sample introduc- high income: PIR ² 1.3). The definitions of hypertension,
• spectrometry (ICP-MS), such as the Agilent 7700x plat- sults, laboratory measurements, and established clinical
• taneously quantify multiple elements, ICP-MS is widely cian diagnosis, current use of antihypertensive medication,
• and duplicate samples one duplicate per 20 samples were presence of at least three of the following five criteria:
• p (LLOD), values were imputed as LLOD defined as individuals who had smoked fewer than 100
• prior studies. Hg has not shown clear associations with all- oration; PIR: poverty–income ratio; BMI: body mass index; ICP–MS: inductively
• cause or cardiovascular mortality in large cohorts, includ- coupled plasma–mass spectrometry; NIST: National Institute of Standards and
• Technology; LLOD: lower limit of detection; DR1IKCA: day 1 dietary recall energy
• of a nationally representative NHANES sample with stan- Ethics approval and consent to participate
• 2104–6. https://doi.org/10.1016/j.cmet.2023.10.015. File: Sample Design, Estimation, and Analytic Guidelines. Vital Health Stat
• 29. Tinkov AA, Filippini T, Ajsuvakova OP, Skalnaya MG, Aaseth J, Bjørklund 103573.
• G, et al. Cadmium and atherosclerosis: A review of toxicological mecha- 38. Aaseth J, Alexander J, Alehagen U, Tinkov A, Skalny A, Larsson A, et al.

Implications

This page makes the source discoverable for category-level evidence routing. Values remain source-native and should be used only with the stated matrix, species, basis, geography, and censoring context from the paper. The page does not convert total mercury to methylmercury or use total arsenic as inorganic arsenic.

Wiki pages this source may touch

• Fish — marine, non-predatory (sardines, anchovies, salmon, cod)
• Mercury
• Cadmium
• Lead

Verification notes

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Update history

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