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Table 2 Predictors for making a claim at 6 months (n = 294, 179 [61%] made a claim)

From: Predictors of seeking financial compensation following motor vehicle trauma: inception cohort with moderate to severe musculoskeletal injuries

Variablea Unadjusted OR (95% CI) P Adjustedb OR (95% CI) P
Body Mass Index (BMI)e (kg/m2)   0.07   0.005
  < 18.50 (underweight) 1.28 (0.27, 6.02)   0.87 (0.17, 4.40)  
 18.50-24.99 (normal) 1.00   1.00  
  ≥ 25.00 (overweight) 2.14 (1.22, 3.76)   3.05 (1.63, 5.68)  
  ≥ 30.00(obese) 1.47 (0.80, 2.71)   1.63 (0.83, 3.20)  
Vehicle type   0.02   0.03
 Motor vehicle 1.00   1.00  
 Motorcycle 0.49 (0.30, 0.80)   0.47 (0.28, 0.82)  
 Bicycle 0.66 (0.20, 2.16)   0.91 (0.26, 3.21)  
Index of Relative Socioeconomic Disadvantage   0.09   0.04
 Most disadvantaged (quintile 1) 0.87 (0.42, 1.81)   0.70 (0.32, 1.55)  
 More disadvantaged (quintile 2) 1.30 (0.44, 3.89)   1.13 (0.35, 3.67)  
 Average (quintile 3) 1.00   1.00  
 Less disadvantaged (quintile 4) 0.45 (0.22, 0.93)   0.37 (0.17, 0.82)  
 Least disadvantaged (quintile 5) 0.62 (0.29, 1.33)   0.39 (0.17, 0.90)  
Male 0.56 (0.32, 0.95) 0.03   
Education skill levelc   0.11   
 Bachelor degree and above 1.00    
 Certificate and advanced diploma 0.59 (0.30, 1.16)    
 Secondary education 0.73 (0.37, 1.47)    
 Pre-primary and primary education 5.19 (0.62, 43.6)    
Work hours before injury   0.07   
 Fulltime 1.00    
 Part time 2.44 (1.13, 5.25)    
 Didn’t work 1.28 (0.72, 2.27)    
Language other than English (yes) 1.75 (1.05, 2.89) 0.03   
Risk of short term harm due to alcohol consumption (yes) 0.58 (0.36, 0.94) 0.03 0.56 (0.32, 0.97) 0.04
Pre-morbid neck pain in last 6 months (yes) 0.41 (0.14, 1.18) 0.10   
Self-assessed pre-injury health statusd   0.08   0.05
 Excellent 1.00   1.00  
 Very good 1.12 (0.63, 1.98)   1.45 (0.77, 2.74)  
 Good 1.13 (0.59, 2.14)   1.16 (0.58, 2.34)  
 Fair-Poor 0.29 (0.10, 0.84)   0.30 (0.09, 0.94)  
  1. aAll variables with p value <0.20 (unadjusted) and p value ≤0.10 (adjusted) were included in the data analysis
  2. bAdjusted for other variables in the column
  3. cThe measure for education is from the Australian Standard Classification of Education (ASCED), Cat. No. 1272.0, Australian Bureau of Statistics 2001
  4. dSelf-assessed pre-injury health status is based on Question 1 from the Short Form 36, version 2, (SF36v2)
  5. eBMI classification is from the Global Database on Body Mass Index, World Health Organisation