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- Magnussen, Christina, et al.
(författare)
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Sex Differences and Similarities in Atrial Fibrillation Epidemiology, Risk Factors, and Mortality in Community Cohorts Results From the BiomarCaRE Consortium (Biomarker for Cardiovascular Risk Assessment in Europe)
- 2017
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 0009-7322 .- 1524-4539. ; 136:17, s. 1588-1597
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Tidskriftsartikel (refereegranskat)abstract
- Background: Atrial fibrillation (AF) is a common cardiac disease in aging populations with high comorbidity and mortality. Sex differences in AF epidemiology are insufficiently understood.Methods: In N=79 793 individuals without AF diagnosis at baseline (median age, 49.6 years; age range, 24.1–97.6 years; 51.7% women) from 4 community-based European studies (FINRISK, DanMONICA, Moli-sani Northern Sweden) of the BiomarCaRE consortium (Biomarker for Cardiovascular Risk Assessment in Europe), we examined AF incidence, its association with mortality, common risk factors, biomarkers, and prevalent cardiovascular disease, and their attributable risk by sex. Median follow-up time was 12.6 (to a maximum of 28.2) years.Results: Fewer AF cases were observed in women (N=1796; 4.4%), than in men (N=2465; 6.4%). Cardiovascular risk factor distribution and lipid profile at baseline were less beneficial in men than in women, and cardiovascular disease was more prevalent in men. Cumulative incidence increased markedly after the age of 50 years in men and after 60 years in women. The lifetime risk was similar (>30%) for both sexes. Subjects with incident AF had a 3.5-fold risk of death in comparison with those without AF. Multivariable-adjusted models showed sex differences for the association of body mass index and AF (hazard ratio per standard deviation increase, 1.18; 95% confidence interval [CI], 1.12–1.23 in women versus 1.31; 95% CI 1.25–1.38 in men; interaction P value of 0.001). Total cholesterol was inversely associated with incident AF with a greater risk reduction in women (hazard ratio per SD, 0.86; 95% CI, 0.81–0.90 versus 0.92; 95% CI, 0.88–0.97 in men; interaction P value of 0.023). No sex differences were seen for C-reactive protein and N-terminal pro B-type natriuretic peptide. The population-attributable risk of all risk factors combined was 41.9% in women and 46.0% in men. About 20% of the risk was observed for body mass index.Conclusions: Lifetime risk of AF was high, and AF was strongly associated with increased mortality both in women and men. Body mass index explained the largest proportion of AF risk. Observed sex differences in the association of body mass index and total cholesterol with AF need to be evaluated for underlying pathophysiology and relevance to sex-specific prevention strategies.
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| 2. |
- Paige, Ellie, et al.
(författare)
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Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction : An Individual-Participant-Data Meta-Analysis
- 2017
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Ingår i: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 186:8, s. 899-907
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Forskningsöversikt (refereegranskat)abstract
- The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.
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