Background <p>Dyslipidemia poses a significant challenge to public health worldwide. Many researchers have suggested that nutritional and environmental factors contribute to dyslipidemia. This study aimed to examine the relationship between serum levels of selected essential and non-essential elements, calcium (Ca), cobalt (Co), magnesium (Mg), potassium (K), lithium (Li), boron (B), and aluminum (Al) and dyslipidemia. Additionally, we aimed to explore the interactions between these elements in various mixtures using the Bayesian Kernel Machine Regression (BKMR) model.</p> Methods <p>This cross-sectional analytical study was conducted among the Kurdish population in western Iran, using data from the Ravansar non-communicable diseases (RaNCD) study. A total of 224 participants aged between 35 and 65 years were included. Data collection included demographic information and blood samples, which were analyzed for selected elements using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). We applied logistic regression and BKMR models to analyze the effects of the studied serum elements on dyslipidemia.</p> Results <p>Among 224 participants, dyslipidemia prevalence was 54.9%, higher in cardiovascular disease (CVD) patients (61.8%) than in non-CVDs (49.2%). Individuals with dyslipidemia had significantly higher age, body mass index (BMI), and blood pressure, while no significant differences were found in sex, residence, marital status, or education level. The logistic regression analysis, after adjusting for confounding factors in the CVD subgroup, indicated that higher serum Ca concentrations were associated with higher odds of dyslipidemia compared with lower concentrations. In contrast, higher serum Co and Mg concentrations were associated with lower odds of dyslipidemia. The BKMR model revealed that the serum levels of B in all subjects, and K, Co, and Ca in the CVD group, as well as B and Co in the non-CVD group, exhibited the highest posterior inclusion probability (PIP) values.</p> Conclusion <p>This study suggests a potential association between serum levels of Ca, Co, Mg, and dyslipidemia in a representative sample of patients with CVD.</p>

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Association of serum essential and non-essential elements with dyslipidemia in patients with cardiovascular disease in Western Iran: an application of Bayesian kernel machine regression

  • Samaneh Nakhaee,
  • Zohreh Manoochehri,
  • Maryam Mahjoubian,
  • Mehdi Khodamoradi,
  • Borhan Mansouri

摘要

Background

Dyslipidemia poses a significant challenge to public health worldwide. Many researchers have suggested that nutritional and environmental factors contribute to dyslipidemia. This study aimed to examine the relationship between serum levels of selected essential and non-essential elements, calcium (Ca), cobalt (Co), magnesium (Mg), potassium (K), lithium (Li), boron (B), and aluminum (Al) and dyslipidemia. Additionally, we aimed to explore the interactions between these elements in various mixtures using the Bayesian Kernel Machine Regression (BKMR) model.

Methods

This cross-sectional analytical study was conducted among the Kurdish population in western Iran, using data from the Ravansar non-communicable diseases (RaNCD) study. A total of 224 participants aged between 35 and 65 years were included. Data collection included demographic information and blood samples, which were analyzed for selected elements using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). We applied logistic regression and BKMR models to analyze the effects of the studied serum elements on dyslipidemia.

Results

Among 224 participants, dyslipidemia prevalence was 54.9%, higher in cardiovascular disease (CVD) patients (61.8%) than in non-CVDs (49.2%). Individuals with dyslipidemia had significantly higher age, body mass index (BMI), and blood pressure, while no significant differences were found in sex, residence, marital status, or education level. The logistic regression analysis, after adjusting for confounding factors in the CVD subgroup, indicated that higher serum Ca concentrations were associated with higher odds of dyslipidemia compared with lower concentrations. In contrast, higher serum Co and Mg concentrations were associated with lower odds of dyslipidemia. The BKMR model revealed that the serum levels of B in all subjects, and K, Co, and Ca in the CVD group, as well as B and Co in the non-CVD group, exhibited the highest posterior inclusion probability (PIP) values.

Conclusion

This study suggests a potential association between serum levels of Ca, Co, Mg, and dyslipidemia in a representative sample of patients with CVD.