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Table 2 Univariate associations and multivariable regression coefficients of the predictors in the final model of the development cohort

From: Long-term sickness absence in a working population: development and validation of a risk prediction model in a large Dutch prospective cohort

   Univariate Multivariable
Predictor Level OR (95%-CI)a OR Coefficientb
Female gender   1.26 (1.05–1.51) 1.10 0.09
Age, per year   1.02 (1.00–1.03) 1.00 0.007
Educational levelc
(ref: low)
Medium 1.00 (0.84–1.19) 0.88 −0.13
High 0.75 (0.62–0.91) 0.83 −0.19
SF-12 physical healthd (ref: 1st quartile, poorest health) 2nd quartile 0.97 (0.80–1.18) 0.55 −0.59
3rd quartile 0.51 (0.41–0.65) 0.42 −0.87
4th quartile 0.46 (0.36–0.59) 0.41 −0.90
Physically fite   0.77 (0.64–0.94) 0.80 −0.22
Physical job loadf (ref: 1st-3rd quartile, less demanding) 4th quartile 1.63 (1.35–1.98) 1.33 0.29
Knowledge and skills match the job (ref: bad/mediocre) Reasonable/good 0.43 (0.30–0.59) 0.62 −0.48
Major life events previous year (ref: none) 1 1.10 (0.92–1.33) 1.12 0.11
≥2 1.62 (1.32–2.00) 1.43 0.35
Work abilityg (ref: good) Average 1.40 (1.14–1.71) 1.10 0.10
Poor 4.70 (3.50–6.30) 2.28 0.82
Sickness absence days previous year (ref: none) 1–5 0.90 (0.73–1.12) 1.39 0.33
6–10 2.25 (1.76–2.87) 2.53 0.93
11–27 4.68 (3.77–5.80) 3.84 1.35
Self-employed   0.49 (0.33–0.73) 0.57 −0.57
Intercept −2.55
  1. aPooled Odds Ratio (95% confidence interval) from the m = 30 multiple imputed datasets
  2. bPooled regression coefficients and intercept from the m = 30 multiple imputed datasets. An individuals predicted probability can be computed using the logistic regression formula P (LTSA) = 1/(1 + exp.(−LP), in which ‘exp’ denotes e-raised-to-the-power-of. The LP is the linear predictor, i.e. the linear sum of all predictor values multiplied by their regression coefficients, or − 2.55 + 0.09*gender (female = 1) + 0.007*age (years) -0.13*education (medium education = 1) -0.19*education (high education = 1) -0.59*physical health (2nd quartile = 1) -0.87*physical health (3rd quartile = 1) -0.90*physical health (4th quartile = 1) -0.22*physically fit (yes = 1) + 0.29*physical job load (4th quartile = 1) -0.48*knowledge (reasonable/good = 1) + 0.11*major life events (one event = 1) + 0.35*major life events (two or more = 1) + 0.10*work ability (average = 1) + 0.82*work ability (poor = 1) + 0.33*sickness absence (1–5 days = 1) + 0.93*sickness absence (6–10 days = 1) + 1.35*sickness absence (11–27 days = 1) -0.57*employment status (self-employed = 1)
  3. cLow: lower general secondary educational, preparatory secondary vocational education. Medium: intermediate vocational training, higher general secondary education, pre-university education. High: higher vocational education, university education
  4. dWeighted summary score (range 0–100) assessing physical health using 6 items of the 12-Item Short-Form Health Survey. Higher scores indicating better perceived physical health. 1st quartile < 46.1, 2nd quartile = 46.1–54.1, 3rd quartile = 54.2–56.5, 4th quartile > = 56.6
  5. eIntensive physical exercise ≥3 days per week for ≥20 min
  6. fAverage of five items (range: 1 = never, 5 = always) from the Dutch Musculoskeletal Questionnaire [22]. 1st-3rd quartile < 2.4, 4th quartile > = 2.4
  7. gMeasured with the first item of the Work Ability Index (WAI) [23]. Good = 8–10, average = 6/7, poor = 0–5