Association between heavy metal exposures and the prevalence of pelvic inflammatory disease: a cross-sectional study from the National Health and Nutrition Examination Survey 2013–2018

• Published in: Environmental science and pollution research international 2023-11, Vol.30 (52), p.112433-112444
• Main Authors: Hu, Panwei, Hu, Hui, Jiang, Xiaomei, Qi, Cong, He, Peizhi, Zhang, Qinhua
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Cadmium; Correlation; Cross-Sectional Studies; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental effects; Environmental Health; Exposure; Female; Heavy metals; Humans; Inflammatory diseases; Lead; Manganese; Mass spectrometry; Mass spectroscopy; Mercury; Mercury (metal); Metals, Heavy; Nutrition Surveys; Pelvic Inflammatory Disease; Physical tests; Prevalence; Questionnaires; Regression analysis; Research Article; Selenium; Subgroups; Surveys; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-30176-6

Pelvic inflammatory disease (PID) is a common medical condition in women. However, the correlation between exposure to heavy metals, including cadmium (Cd), lead (Pb), manganese (Mn), mercury (Hg), and selenium (Se), and PID, is unclear. Using a large sample size from the National Health and Nutrition Examination Survey, these relationships were studied and verified. PID diagnosis was acquired through a self-reported questionnaire (2013–2018). Heavy metal exposure (Cd, Pb, Mn, Hg, and Se) was measured using mass spectrometry of blood samples. Covariate data were obtained through questionnaires and physical tests. Individuals with complete covariate data were included in the study. The relationship between heavy metal exposure (Cd, Pb, Mn, Hg, and Se) and PID was demonstrated using logistic regression analysis, weighted quantile sum (WQS) regression analysis, and restricted cubic splines (RCS). Overall, 2743 participants were included. Of these, 183 were diagnosed with PID. Through weighted univariate and multivariate regression analyses, the heavy metals of Cd and Pb were positively correlated with the prevalence of PID. However, no significant relationship was observed in the heavy metals of Mn, Hg, and Se. The joint effect of heavy metals further confirmed the important role of Cd and Pb in WQS analysis. After visualizing the RCS, significant curved and linear relationships were observed for Cd and Pb, respectively. Most subgroup analyses confirmed these results. In conclusion, exposure to Cd was nonlinearly correlated with the risk of PID, whereas exposure to Pb showed a linear relationship. Our findings increase the awareness of the environmental effects of exposure to heavy metals in PID. However, further studies are needed to elucidate the causality and underlying mechanisms between heavy metal exposure and the prevalence of PID.