ArticleBMC cardiovascular disorders2026
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.
Article in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundDyslipidemia 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.
methodsThis 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.
resultsAmong 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.
conclusionThis study suggests a potential association between serum levels of Ca, Co, Mg, and dyslipidemia in a representative sample of patients with CVD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.