title: Nonexercise Equations to Estimate Fitness in White European and South Asian Men.
abstract: OBJECTIVE
  Cardiorespiratory fitness is a strong, independent predictor of health, whether it is measured in an exercise test or estimated in an equation. The purpose of this study was to develop and validate equations to estimate fitness in middle-age white European and South Asian men.
  
  
  METHODS
  Multiple linear regression models (n = 168, including 83 white European and 85 South Asian men) were created using variables that are thought to be important in predicting fitness (V˙O2max, mL·kg⁻¹·min⁻¹): age (yr), body mass index (kg·m⁻²), resting HR (bpm); smoking status (0, never smoked; 1, ex or current smoker), physical activity expressed as quintiles (0, quintile 1; 1, quintile 2; 2, quintile 3; 3, quintile 4; 4, quintile 5), categories of moderate- to-vigorous intensity physical activity (MVPA) (0, <75 min·wk⁻¹; 1, 75-150 min·wk⁻¹; 2, >150-225 min·wk⁻¹; 3, >225-300 min·wk⁻¹; 4, >300 min·wk⁻¹), or minutes of MVPA (min·wk⁻¹); and, ethnicity (0, South Asian; 1, white). The leave-one-out cross-validation procedure was used to assess the generalizability, and the bootstrap and jackknife resampling techniques were used to estimate the variance and bias of the models.
  
  
  RESULTS
  Around 70% of the variance in fitness was explained in models with an ethnicity variable, such as: V˙O2max = 77.409 - (age × 0.374) - (body mass index × 0.906) - (ex or current smoker × 1.976) + (physical activity quintile coefficient) - (resting HR × 0.066) + (white ethnicity × 8.032), where physical activity quintile 1 is 0, 2 is 1.127, 3 is 1.869, 4 is 3.793, and 5 is 3.029. Only around 50% of the variance was explained in models without an ethnicity variable. All models with an ethnicity variable were generalizable and had low variance and bias.
  
  
  CONCLUSIONS
  These data demonstrate the importance of incorporating ethnicity in nonexercise equations to estimate cardiorespiratory fitness in multiethnic populations.
authors.affiliation: 1Diabetes Research Centre, Leicester Diabetes Centre, Leicester General Hospital, University of Leicester, Leicester, UNITED KINGDOM; 2BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UNITED KINGDOM; 3Department of Health Sciences, University of Leicester, Leicester, UNITED KINGDOM; 4National Centre for Sport & Exercise Medicine, East Midlands, Loughborough University, Loughborough, UNITED KINGDOM; and 5Faculty of Health Sciences, Charles Perkins Centre, University of Sydney, Sydney, AUSTRALIA.
authors.forename: Gary
authors.initials: G
authors.lastname: O'Donovan
authors.forename: Kishan
authors.initials: K
authors.lastname: Bakrania
authors.forename: Nazim
authors.initials: N
authors.lastname: Ghouri
authors.forename: Thomas
authors.initials: T
authors.lastname: Yates
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Gray
authors.forename: Mark
authors.initials: M
authors.lastname: Hamer
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Stamatakis
authors.forename: Kamlesh
authors.initials: K
authors.lastname: Khunti
authors.forename: Melanie
authors.initials: M
authors.lastname: Davies
authors.forename: Naveed
authors.initials: N
authors.lastname: Sattar
authors.forename: Jason M R
authors.initials: JM
authors.lastname: Gill
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People; D015992:Body Mass Index; D000072599:Cardiorespiratory Fitness; D015444:Exercise; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D010101:Oxygen Consumption; D010809:Physical Fitness; D044465:White People