title: Factors affecting home-measured resting heart rate in the general population: the Ohasama study.
abstract: BACKGROUND
  We recently demonstrated that a home-measured resting heart rate (HR) can predict cardiovascular disease mortality, and it is possible that the determinants of home HR are different from casual HR. Therefore, clarifying the determinants of home HR should be useful.
  
  
  METHODS
  Home HR was obtained using a self-monitored blood pressure (BP) measuring device. The impact of factors including home-measured BP and lifestyle on home HR was examined in 1275 members of the general Japanese population aged > or =40 years.
  
  
  RESULTS
  Multivariate linear regression analysis demonstrated that younger age (beta = -0.08, P < or = .01), current smoking (beta = 3.22, P < or = .01), female gender (beta = 2.07, P < or = .01), and sedentary lifestyle (walking for < or =1 h/day) (beta = 2.43, P < or = .01) were determinants of elevated morning home HR. No significant association was observed between home HR and home systolic BP, whereas casual HR was significantly and positively associated with casual systolic BP. The difference between casual and home HR was also significantly and positively associated with the difference between casual and home systolic BP, suggesting that positive association between BP and HR obtained in clinic settings would be a reflection of the so-called white-coat effect.
  
  
  CONCLUSIONS
  We observed that, with the exception of BP, most determinants of home HR were consistent with the determinants observed in previous studies using casual HR. These results suggest that reduction of home HR through modification of smoking habit or sedentary lifestyle may have a potential to decrease cardiovascular risk in addition to decreasing in these modifiable risk factor per se.
authors.affiliation: Departments of Clinical Pharmacology and Therapeutics, Tohoku University Graduate School of Pharmaceutical Science and Medicine, 1-1 Seiryomachi, Aobaku, Sendai 980-8574, Japan.
authors.forename: Junko
authors.initials: J
authors.lastname: Yamaguchi
authors.forename: Atsushi
authors.initials: A
authors.lastname: Hozawa
authors.forename: Takayoshi
authors.initials: T
authors.lastname: Ohkubo
authors.forename: Masahiro
authors.initials: M
authors.lastname: Kikuya
authors.forename: Takashi
authors.initials: T
authors.lastname: Ugajin
authors.forename: Kaori
authors.initials: K
authors.lastname: Ohmori
authors.forename: Junichiro
authors.initials: J
authors.lastname: Hashimoto
authors.forename: Haruhisa
authors.initials: H
authors.lastname: Hoshi
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Satoh
authors.forename: Ichiro
authors.initials: I
authors.lastname: Tsuji
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Imai
mesh_terms: D000367:Age Factors; D000368:Aged; D000428:Alcohol Drinking; D000959:Antihypertensive Agents / Q000008:administration & dosage; D001794:Blood Pressure / Q000187:drug effects / Q000502:physiology; D018660:Blood Pressure Monitoring, Ambulatory / Q000379:methods*; D015992:Body Mass Index; D003069:Coffee; D003920:Diabetes Mellitus / Q000503:physiopathology; D005260:Female; D006339:Heart Rate / Q000187:drug effects / Q000502:physiology*; D006801:Humans; D006937:Hypercholesterolemia / Q000503:physiopathology; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012146:Rest / Q000502:physiology; D012307:Risk Factors; D012907:Smoking; D011795:Surveys and Questionnaires; D016138:Walking / Q000502:physiology
chemical_list: D000959:Antihypertensive Agents; D003069:Coffee