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Association between multiple urinary metals and visceral obesity: a large cross-sectional study in South China

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Overview

Large cross-sectional study (n=5,794 adults; 2,641 males, 3,153 females) from the baseline survey of the Prospective Cohort Study of Chronic Diseases in Ethnic Minority Natural Population in Guangxi, China (May-December 2019). Urinary concentrations of multiple metals were measured; visceral fat index (VFI) used as the outcome, defined as a measure of visceral obesity. Among participants, 1,423 (24.6%) had visceral obesity. LASSO regression, logistic regression, restricted cubic splines, quantile g-computation, WQS, and BKMR were applied.

Key numbers

n=5,794 adults; visceral obesity prevalence 24.6% (1,423/5,794). Four standard curves used for metal measurement, each with six concentration gradients spanning 0.05-20 ug/L for metals including chromium, manganese, nickel, arsenic, selenium, cadmium, cesium, barium, thallium, lead.

Single-metal associations (adjusted logistic regression, Ln-transformed urinary concentrations):

  • Antimony (Sb): OR=1.260 (95% CI: 1.149-1.383; p below 0.001); positive.
  • Zinc (Zn): OR=1.343 (95% CI: 1.134-1.591; p below 0.001); positive.
  • Rubidium (Rb): OR=0.741 (95% CI: 0.624-0.881; p below 0.001); inverse (protective).

Dose-response (restricted cubic splines):

  • Antimony: linear dose-response (P-overall below 0.001; P-nonlinear=0.244).
  • Zinc: dose-response present (P-overall=0.048; P-nonlinear=0.592).
  • Rubidium: dose-response present (P-overall=0.035; P-nonlinear=0.482).
  • Magnesium (female subgroup and 60-74 year subgroup): nonlinear dose-response.

Mixture effects: significant in both positive (p=0.003) and negative (p=0.043) directions. Interaction effects observed between antimony and rubidium, between antimony and zinc, and between each of these and the other six metals.

Evidence Fitness

Context only. Cross-sectional design. This study focuses on a relatively novel outcome (visceral fat index via VFI anthropometric measure) and includes metals not commonly studied in heavy-metal health effects literature (rubidium, antimony as outcomes). No food concentration data.

Methods (brief)

Baseline cohort survey, Guangxi, May-December 2019. Face-to-face interviews for demographics, health, lifestyle. Urine metals by ICP-MS. Creatinine calculated by enzymatic colorimetric method. VFI as visceral obesity indicator (non-invasive). LASSO for variable selection; logistic regression; RCS; Qgcomp; WQS; BKMR.

Implications

Certification: This study covers metals (antimony, rubidium, zinc) that are outside the standard HMT&C analyte panel but documents that metal mixture effects on metabolic outcomes are not limited to the conventional four toxic metals.

Courses: Useful for demonstrating the breadth of metal mixture epidemiology beyond the standard lead (Pb)/cadmium (Cd)/arsenic (As)/mercury (Hg) quartet.

App: No food concentration data.

Microbiome: Adipose tissue-gut axis potential; not primary focus.

Update history

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