# Table 2 Linear regression analysis investigating the relationship between playing sport while injured and health related quality of life

Physical Component ScoreMental Component Score
EffectEffectEffectEffect
(95% CI)(95% CI)(95% CI)(95% CI)
Played sport while injured (n = 1725, 77%)−1.53 (−2.37, −0.69), P < 0.001− 1.78 (− 2.62, − 0.93), P < 0.001−1.49 (− 2.32, − 0.66), P < 0.001− 1.40 (− 2.25, − 0.54), P < 0.001
Ageb −13.03 (− 17.16, −8.89), P < 0.001 0.79 (0.42, 1.17), P < 0.001
Agec   −5.10 (−7.55, − 2.64), P < 0.001
Gender −1.68 (−3.77, 0.41), P = 0.115 −0.09 (− 2.25, 2.21), P = 0.934
Cricket Seasons Playedd 0.46 (0.16, 0.76), P = 0.003 0.81 (0.48, 1.13), P < 0.001
Playing Status −2.52 (−3.31, −1.72), P < 0.001 −0.29 (−1.09, 0.55), P = 0.490
Joints Injured −1.60 (−2.30, − 1.00), P < 0.001 −0.77 (− 1.49, − 0.06), P = 0.035
Orthopaedic Surgeries − 2.18 (− 3.00, − 1.46), P < 0.001 0.09 (− 0.09, 1.10), P = 0.808
1. a Estimates were adjusted for age, gender (male = 0, female = 1), cricket seasons played, playing status (current = 0, former = 1), history of joint injury (no joints injured = 0, sustained a joint injury = 1), and history of orthopaedic surgery (never had an orthopaedic surgery = 0, underwent orthopaedic surgery = 1)
2. b Age was defined as (Age/100)^3 for PCS analyses and (Age/100)^1 for MCS analyses
3. c Second order fractional polynomial was not used for PCS analyses and Age was defined as (Age/100)^2 for MCS analyses
4. d Cricket seasons for PCS and MCS analyses were divided by ten (Seasons/10)
5. e SF-8: Short-Form 8 Health Survey; Physical Component Scores (PCS) were calculated using norm based scoring (population norm 50 SD 10, high scorer = better health-related quality of life); Mental Component Scores (MCS) were calculated using norm based scoring (population norm 50 SD 10, high scorer = better health-related quality of life)