A Bayesian network for estimating hypertension risk due to occupational aluminum exposure

Abstract

Abstract Background The correlation between metals and hypertension, such as sodium, zinc, potassium, and magnesium, has been confirmed, while the relationship between aluminum and hypertension is not very clear. This study aimed to evaluate the correlation between plasma aluminum and hypertension in electrolytic aluminum workers by the Bayesian networks (BN). Methods In 2019, 476 male workers in an aluminum factory were investigated. The plasma aluminum concentration of workers was measured by inductively coupled plasma mass spectrometry. The influencing factors on the prevalence of hypertension were analyzed by the BN. Results The prevalence of hypertension was 23.9% in 476 male workers. The risk of hypertension from plasma aluminum in the Q2, Q3, and Q4 groups was 5.20 (1.90–14.25), 6.92 (2.51–19.08), and 7.33 (2.69–20.01), respectively, compared with that in the Q1 group. The risk of hypertension from the duration of exposure to aluminum of >10 years was 2.23 (1.09–4.57), compared without aluminum exposure. Area under the curve was 0.80 of plasma aluminum and the duration of exposure to aluminum was based on covariates, indicating that aluminum exposure had important predictive value in the prevalence of hypertension in the occupational population. The results of the study using the BN model showed that if the plasma aluminum of all participants was higher than Q4 (≥47.86 µg/L) and the participants were drinking, smoking, diabetes, central obesity, dyslipidemia, and aged >50 years, the proportion of hypertension was 71.2%. Conclusions The prevalence of hypertension increased significantly with the increase of plasma aluminum level.

Keywords

• Bayesian networks
• hypertension
• occupational aluminum exposure