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Sökning: WFRF:(Kronmal Richard A.)

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1.
  • Whitlock, Gary, et al. (författare)
  • Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies
  • 2009
  • Ingår i: Lancet (London, England). - 1474-547X. ; 373:9669, s. 1083-1096
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The main associations of body-mass index (BMI) with overall and cause-specific mortality can best be assessed by long-term prospective follow-up of large numbers of people. The Prospective Studies Collaboration aimed to investigate these associations by sharing data from many studies. METHODS: Collaborative analyses were undertaken of baseline BMI versus mortality in 57 prospective studies with 894 576 participants, mostly in western Europe and North America (61% [n=541 452] male, mean recruitment age 46 [SD 11] years, median recruitment year 1979 [IQR 1975-85], mean BMI 25 [SD 4] kg/m(2)). The analyses were adjusted for age, sex, smoking status, and study. To limit reverse causality, the first 5 years of follow-up were excluded, leaving 66 552 deaths of known cause during a mean of 8 (SD 6) further years of follow-up (mean age at death 67 [SD 10] years): 30 416 vascular; 2070 diabetic, renal or hepatic; 22 592 neoplastic; 3770 respiratory; 7704 other. FINDINGS: In both sexes, mortality was lowest at about 22.5-25 kg/m(2). Above this range, positive associations were recorded for several specific causes and inverse associations for none, the absolute excess risks for higher BMI and smoking were roughly additive, and each 5 kg/m(2) higher BMI was on average associated with about 30% higher overall mortality (hazard ratio per 5 kg/m(2) [HR] 1.29 [95% CI 1.27-1.32]): 40% for vascular mortality (HR 1.41 [1.37-1.45]); 60-120% for diabetic, renal, and hepatic mortality (HRs 2.16 [1.89-2.46], 1.59 [1.27-1.99], and 1.82 [1.59-2.09], respectively); 10% for neoplastic mortality (HR 1.10 [1.06-1.15]); and 20% for respiratory and for all other mortality (HRs 1.20 [1.07-1.34] and 1.20 [1.16-1.25], respectively). Below the range 22.5-25 kg/m(2), BMI was associated inversely with overall mortality, mainly because of strong inverse associations with respiratory disease and lung cancer. These inverse associations were much stronger for smokers than for non-smokers, despite cigarette consumption per smoker varying little with BMI. INTERPRETATION: Although other anthropometric measures (eg, waist circumference, waist-to-hip ratio) could well add extra information to BMI, and BMI to them, BMI is in itself a strong predictor of overall mortality both above and below the apparent optimum of about 22.5-25 kg/m(2). The progressive excess mortality above this range is due mainly to vascular disease and is probably largely causal. At 30-35 kg/m(2), median survival is reduced by 2-4 years; at 40-45 kg/m(2), it is reduced by 8-10 years (which is comparable with the effects of smoking). The definite excess mortality below 22.5 kg/m(2) is due mainly to smoking-related diseases, and is not fully explained.
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2.
  • den Hoed, Marcel, et al. (författare)
  • Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders
  • 2013
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 45:6, s. 621-
  • Tidskriftsartikel (refereegranskat)abstract
    • Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
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4.
  • Paige, Ellie, et al. (författare)
  • Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction An Individual-Participant-Data Meta-Analysis
  • 2017
  • Ingår i: American Journal of Epidemiology. - Oxford University Press. - 0002-9262. ; 186:8, s. 899-907
  • Forskningsöversikt (övrigt vetenskapligt)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.
5.
  • Paige, Ellie, et al. (författare)
  • Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction An Individual-Participant-Data Meta-Analysis.
  • 2017
  • Ingår i: American Journal of Epidemiology. - 0002-9262 .- 1476-6256. ; 186:8, s. 899-907
  • Tidskriftsartikel (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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