Micronutrient deficiencies and new-onset atrial fibrillation in a community-based cohort:data from PREVEND

Aim: Malnutrition has been linked to cardiovascular diseases. Both selenium and iron deficiency have been associated with worse prognosis in patients with heart failure (HF). Yet, little is known about the role of micronutrients in the development of atrial fibrillation (AFib). In this study, we aimed to elucidate the association of micronutrient deficiencies with new-onset AFib. Methods: Selenium, magnesium, and iron parameters were measured in a well-characterized prospective cohort study (N = 5452). Selenium deficiency was defined as serum selenium &lt; 70 μg/L, iron deficiency as serum ferritin &lt; 30 μg/L, and magnesium deficiency as plasma magnesium &lt; 0.85 mmol/L. New-onset AFib was the primary outcome. Additionally, we tested for previously reported effect-modifiers where applicable. Results: Selenium, iron, and magnesium deficiency was observed in 1155 (21.2%), 797 (14.6%), and 3600 (66.0%) participants, respectively. During a mean follow-up of 6.2 years, 136 (2.5%) participants developed new-onset AFib. Smoking status significantly interacted with selenium deficiency on outcome (p = 0.079). After multivariable adjustment for components of the CHARGE-AF model, selenium deficiency was associated with new-onset AFib in non-smokers (HR 1.69, 95% CI 1.09–2.64, p = 0.020), but not in smokers (HR 0.78, 95% CI 0.29–2.08, p = 0.619). Magnesium deficiency (HR 1.40, 95% CI 0.93–2.10, p = 0.110) and iron deficiency (HR 0.62, 95% CI 0.25–1.54, p = 0.307) were not significantly associated with new-onset AFib. Conclusion: Selenium deficiency was associated with new-onset AFib in non-smoking participants. Interventional studies that investigate the effects of optimizing micronutrients status in a population at risk are needed to assess causality, especially in those with selenium deficiency. Graphical abstract: Micronutrients deficiencies (selenium, iron, and magnesium) have been associated with cardiovascular diseases and mitochondrial dysfunction in human cardiomyocytes. However, it is not known whether these deficiencies are associated with atrial fibrillation. To investigate this question, we measured all three micronutrients in 5452 apparently healthy individuals. After a mean follow-up of 6.2 years, there were 136 participants who developed atrial fibrillation. Participants with selenium deficiency had a significant increased risk to develop atrial fibrillation, as did the participants with two or more deficiencies. [Figure not available: see fulltext.]</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Relative fat mass and prediction of incident atrial fibrillation, heart failure and coronary artery disease in the general population

Background: Relative fat mass (RFM) is an emerging marker of obesity that estimates body fat percentage using a sex-specific formula containing height and waist circumference (WC). We studied the association of RFM with incident atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD) and explored RFM cutoffs for cardiovascular disease (CVD) prediction. Methods: We studied 95,003 participants (age 45 ± 13 years, 59% women) without prevalent AF, HF or CAD from the population-based Lifelines study. Outcomes were ascertained using electrocardiography and self-reported questionnaire data. We used logistic regression to study the association of RFM with individual outcomes and a composite outcome (incident AF, HF, and/or CAD). Multivariable models were adjusted for components of the SCORE risk model (age, sex, systolic blood pressure, cholesterol, and smoking). Optimal cutoffs were determined using the Youden index. Results: During a median follow-up of 3.8 (3.0–4.6) years, 224 (0.2%) participants developed AF, 1003 (1.1%) HF and 657 (0.7%) CAD. After multivariable adjustment, RFM was significantly associated with all outcomes (standardised OR 1.26, 95% CI 1.18–1.34 for the composite outcome). Optimal RFM cutoffs (≥26 for men, ≥38 for women) were lower than previously proposed RFM cutoffs (≥30 for men, ≥40 for women). In general, overall discriminative ability of RFM and its cutoffs was at least similar (in women) or better (in men) compared to BMI and WC. Since RFM was substantially correlated with age, we additionally determined age-specific cutoffs, which ranged from 23 to 27 in men and 33 to 43 in women. Conclusions: RFM is associated with incident AF, HF, and CAD and may be used as a simple and intuitive marker of obesity and cardiovascular risk in the general population. This study provides potential RFM cutoffs for CVD prediction that may be used by future studies or preventive strategies targeting obesity and cardiovascular risk.</p