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Asvold, B. O., Bjorngaard, J. H., Carslake, D., Gabrielsen, M. E., Skorpen, F., Davey Smith, G., et al. (2014). Causal associations of tobacco smoking with cardiovascular risk factors: a Mendelian randomization analysis of the HUNT Study in Norway. Int J Epidemiol, 43(5), 1458–1470.
Abstract: BACKGROUND: Tobacco smoking has been associated with cardiovascular risk factors including adverse serum lipid levels, central obesity and higher resting heart rate, but lower blood pressure and body mass index (BMI). We used a Mendelian randomization approach to study whether these associations may be causal. If smoking affects cardiovascular risk factors then rs1051730 T alleles, predictors of increased smoking quantity, should be associated with cardiovascular risk factors among smokers, but not among never smokers. METHODS: Among 56 625 participants of a population-based study, we estimated associations of rs1051730 T alleles with cardiovascular risk factors and examined whether the associations differed by smoking status. RESULTS: Rs1051730 T alleles were associated with lower BMI and waist and hip circumferences and higher resting heart rate and estimated glomerular filtration rate (eGFR), and the associations were strongest among current smokers (P interaction 5 x 10(-9) to 0.01). Rs1051730 T alleles were associated with lower systolic blood pressure and pulse pressure and higher HDL cholesterol concentrations, but these associations did not robustly differ by smoking status. There were no convincing associations of rs1051730 T alleles with waist-hip ratio, diastolic blood pressure and non-fasting serum concentrations of non-HDL cholesterol, triglycerides, glucose and C-reactive protein. CONCLUSIONS: This Mendelian randomization analysis provides evidence that smoking may cause lower BMI and waist and hip circumferences and higher resting heart rate and eGFR. The findings further suggest that smoking is not a major determinant of waist-hip ratio or adverse blood pressure, serum lipid or glucose levels.
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Hauan, M., Strand, L. B., & Laugsand, L. E. (2018). Associations of Insomnia Symptoms With Blood Pressure and Resting Heart Rate: The HUNT Study in Norway. Behav Sleep Med, 16(5), 504–522.
Abstract: OBJECTIVE: Although elevated heart rate and blood pressure might represent biologically plausible links for the association of insomnia symptoms with increased risk of cardiovascular disease (CVD), few large studies have investigated the associations of insomnia symptoms with these factors. Our aim was to investigate the associations of self-reported insomnia symptoms with systolic and diastolic blood pressure and resting heart rate in a large population-based study. PARTICIPANTS: Self-reported information on insomnia symptoms, including sleep initiation problems, frequent awakening and early awakenings during night, and measurements of resting heart rate and blood pressure were collected from a total of 50,806 men and women who participated in the third wave of the Nord-Trondelag Health Study (HUNT-3) in 2006-2008. METHODS: In multivariable analyses, we adjusted for sociodemographic factors, lifestyle factors, established CVD risk factors, and snoring or breathing pauses. RESULTS: Compared to participants reporting none of the insomnia symptoms, those having all three insomnia symptoms several times a week had lower diastolic blood pressure (-0.80 [95% CI: -1.47 to -0.14] mmHg, p = 0.02), lower systolic blood (-1.69 [95% CI: -2.76 to -0.63) mmHg, p < 0.001), and higher resting heart rate (0.83 [95% CI: 0.11 to 1.55] beats/minute, p = 0.02). CONCLUSIONS: We found a modest positive association of insomnia symptoms with resting heart rate, and a modest inverse association of insomnia with blood pressure. However, the actual differences were small, and likely of less clinical importance. Prospective studies are needed to establish whether the potential link between insomnia and CVD is mediated through changes in heart rate and/or blood pressure.
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Loe, H., Nes, B. M., & Wisloff, U. (2016). Predicting VO2peak from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway. PloS one, 11(1), e0144873.
Abstract: PURPOSE: Peak oxygen uptake (VO2peak) is seldom assessed in health care settings although being inversely linked to cardiovascular risk and all-cause mortality. The aim of this study was to develop VO2peak prediction models for men and women based on directly measured VO2peak from a large healthy population. METHODS: VO2peak prediction models based on submaximal- and peak performance treadmill work were derived from multiple regression analysis. 4637 healthy men and women aged 20-90 years were included. Data splitting was used to generate validation and cross-validation samples. RESULTS: The accuracy for the peak performance models were 10.5% (SEE = 4.63 mLkg(-1)min(-1)) and 11.5% (SEE = 4.11 mLkg(-1)min(-1)) for men and women, respectively, with 75% and 72% of the variance explained. For the submaximal performance models accuracy were 14.1% (SEE = 6.24 mLkg(-1)min(-1)) and 14.4% (SEE = 5.17 mLkg(-1)min(-1)) for men and women, respectively, with 55% and 56% of the variance explained. The validation and cross-validation samples displayed SEE and variance explained in agreement with the total sample. Cross-classification between measured and predicted VO2peak accurately classified 91% of the participants within the correct or nearest quintile of measured VO2peak. CONCLUSION: Judicious use of the exercise prediction models presented in this study offers valuable information in providing a fairly accurate assessment of VO2peak, which may be beneficial for risk stratification in health care settings.
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Nauman, J., Aspenes, S. T., Nilsen, T. I. L., Vatten, L. J., & Wisloff, U. (2012). A prospective population study of resting heart rate and peak oxygen uptake (the HUNT Study, Norway). PLoS One, 7(9), e45021.
Abstract: OBJECTIVES: We assessed the prospective association of resting heart rate (RHR) at baseline with peak oxygen uptake (VO(2peak)) 23 years later, and evaluated whether physical activity (PA) could modify this association. BACKGROUND: Both RHR and VO(2peak) are strong and independent predictors of cardiovascular morbidity and mortality. However, the association of RHR with VO(2peak) and modifying effect of PA have not been prospectively assessed in population studies. METHODS: In 807 men and 810 women free from cardiovascular disease both at baseline (1984-86) and follow-up 23 years later, RHR was recorded at both occasions, and VO(2peak) was measured by ergospirometry at follow-up. We used Generalized Linear Models to assess the association of baseline RHR with VO(2peak), and to study combined effects of RHR and self-reported PA on later VO(2peak). RESULTS: There was an inverse association of RHR at baseline with VO(2peak) (p<0.01). Men and women with baseline RHR greater than 80 bpm had 4.6 mL.kg(-1).min(-1) (95% confidence interval [CI], 2.8 to 6.3) and 1.4 mL.kg(-1).min(-1) (95% CI, -0.4 to 3.1) lower VO(2peak) at follow-up compared with men and women with RHR below 60 bpm at baseline. We found a linear association of change in RHR with VO(2peak) (p=0.03), suggesting that a decrease in RHR over time is likely to be beneficial for cardiovascular fitness. Participants with low RHR and high PA at baseline had higher VO(2peak) than inactive people with relatively high RHR. However, among participants with relatively high RHR and high PA at baseline, VO(2peak) was similar to inactive people with relatively low RHR. CONCLUSION: RHR is an important predictor of VO(2peak), and serial assessments of RHR may provide useful and inexpensive information on cardiovascular fitness. The results suggest that high levels of PA may compensate for the lower VO(2peak) associated with a high RHR.
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Nes, B. M., Janszky, I., Wisloff, U., Stoylen, A., & Karlsen, T. (2013). Age-predicted maximal heart rate in healthy subjects: The HUNT Fitness Study. Scand J Med Sci Sports, 23(6), 697–704.
Abstract: Maximal heart rate (HRmax ) declines substantially with age, but the magnitude and possible modifying effect of gender, body composition, and physical activity are not fully established. The present study examined the relationship between HRmax and age in 3320 healthy men and women within a wide age range using data from the HUNT Fitness Study (2007-2008). Subjects were included if a maximal effort could be verified during a maximal exercise test. General linear modeling was used to determine the effect of age on HRmax . Subsequently, the effects of gender, body mass index (BMI), physical activity status, and maximal oxygen uptake were examined. Mean predicted HRmax by three former prediction formulas were compared with measured HRmax within 10-year age groups. HRmax was univariately explained by the formula 211 – 0.64.age (SEE, 10.8), and we found no evidence of interaction with gender, physical activity, VO2max level, or BMI groups. There were only minor age-adjusted differences in HRmax between these groups. Previously suggested prediction equations underestimated measured HRmax in subjects older than 30 years. HRmax predicted by age alone may be practically convenient for various groups, although a standard error of 10.8 beats/min must be taken into account. HRmax in healthy, older subjects and women were higher than previously reported.
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