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Table 2 binary logistic regression analysis

From: Prevalence and associated factors of the career plateau of primary care providers in Heilongjiang, China: a cross-sectional study

Statistical variables The assignment case Regression coefficient Standard error Wals P OR 95%CI
Gender 1 = Male 0.184 0.167 1.215 0.27 1.202 0.867–1.667
2 = Female      contrast  
Marriage status 1 = Have a spouse 0.332 0.141 5.507 0.019 1.394 1.056–1.839
2 = No spouse      contrast  
Weekly working hours 1 = 40 h      contrast  
2 = >40 h 0.387 0.128 9.166 0.002 1.473 1.146–1.893
Working fixed number of year 1 = 10 years      contrast  
2 = 11–20 years 0.474 0.171 7.707 0.006 1.607 1.150–2.246
3 = 20 years 1.036 0.191 29.45 < 0.001 2.818 1.938–4.097
Type of personnel post allocation 1 = Utilities staffing      contrast  
2 = Appointment system 0.323 0.171 3.579 0.059 1.382 0.988–1.931
3 = Equal pay for
equal
work/Temporary recruit
0.297 0.186 2.551 0.11 1.345 0.935–1.936
Average monthly income 1 = < 2000 yuan      contrast  
2 = 2001–3000 yuan 0.359 0.211 2.907 0.088 1.432 0.948–2.165
3 = 3001–4000 yuan 0.634 0.232 7.496 0.006 1.886 1.197–2.969
4 = 4001–5000 yuan 0.744 0.263 7.98 0.005 2.104 1.256–3.524
5 = >5001 yuan 0.364 0.298 1.495 0.221 1.44 0.803–2.582
The quality of sleep 1 = Very satisfied and relatively satisfied      contrast  
2 = General 0.131 0.166 0.618 0.432 1.14 0.803–2.582
3 = Relatively dissatisfied and very dissatisfied 0.609 0.17 12.77 < 0.001 1.838 1.317–2.567
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