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Table 2 Logistic regression estimates after complete case analysis and multiple imputation

From: Prevalence and associated factors of COVID-19 across Italian regions: a secondary analysis from a national survey on physiotherapists

 

Complete-case analysis (N = 9164)

Multiple imputation (N = 14,607)

Coefficient

SE

P-value

Coefficient

SE

P-value

Cluster 2 versus Cluster 1

−1.26

0.19

< 0.0001

− 1.22

0.13

< 0.0001

Males versus females

0.38

0.12

0.0009

0.39

0.08

0.0202

Age, yrs

0.014

0.005

0.0026

0.009

0.004

0.0257

At least 1 comorbidities versus none

0.18

0.12

0.1205

0.12

0.08

0.1754

Professional field

  

0.0005

  

< 0.0001

(Cardio-respiratory as reference)

Geriatric

−0.43

0.32

0.3881

−0.03

0.23

0.9111

Neurologic

−0.26

0.3

0.0105

−0.29

0.23

0.2017

Orthopedic-Musculoskeletal

−0.72

0.28

0.1041

−0.75

0.22

0.0006

Urogynecologic and Oncologic

−1.68

1.04

0.7709

−0.29

0.43

0.5095

Pediatric

−0.11

0.38

0.9873

−0.25

0.29

0.3921

Mixed

−0.004

0.25

0.9158

−0.032

0.2

0.8694

Working Facilities

  

< 0.0001

  

< 0.0001

(Private/public hospitals as reference)

Residential Care Home

0.02

0.22

0.9158

0.22

0.15

0.1472

Private/public rehabilitation clinics

−0.41

0.17

0.0137

−0.35

0.12

0.0037

Home

−1.55

0.4

< 0.0001

−1.23

0.25

< 0.0001

Mixed

0.44

0.16

0.0047

0.17

0.12

0.1748

Private setting

−1.47

0.27

< 0.0001

−1.69

0.21

< 0.0001

Reallocation to a different unit (Yes versus No)

0.27

0.16

0.0862

0.26

0.16

0.1078

Changing job task (Yes versus No)

0.21

0.16

0.1794

0.29

0.16

0.0746

Constant

−3.3

0.32

< 0.0001

−2.7

0.25

< 0.0001

  1. Estimates are expressed as log odds
  2. Cluster 1 = Piedmont and Aosta Valley, Liguria, Lombardy, Veneto, Friuli-Venezia-Giulia, Trentino-Alto-Adige, Emilia-Romagna, Tuscany, Marche and Umbria; Cluster 2 = Abruzzo, Lazio, Molise, Campania, Apulia, Basilicata, Calabria, Sicily and Sardinia
  3. SE Standard Error