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Table 4 Estimated results for unmet health care – macro-factors

From: Older Europeans’ experience of unmet health care during the COVID-19 pandemic (first wave)

 

Given up

Postponed

 

Denied

 
 

or

dy/dx

 

or

dy/dx

 

or

dy/dx

 

beveridge

0.750

−0.030

 

0.600

− 0.083

*

0.659

−0.020

 

high_OOP

1.432

0.041

*

0.812

−0.035

 

1.220

0.010

 

high_unmetneeds

0.691

−0.039

***

0.652

−0.072

***

0.894

−0.006

 

high_doctors

0.969

−0.003

 

0.965

−0.006

 

0.953

−0.002

 

high_nurses

1.499

0.044

**

1.186

0.030

 

1.506

0.021

**

beds

0.999

0.000

 

0.998

0.000

**

0.998

0.000

 

no_lockdown

1.100

0.010

 

0.821

−0.033

 

1.016

0.001

 

_cons

0.69

 

***

1.046

  

0.049

 

***

individual controls

yes

  

yes

  

yes

  

Number of obs

23,281

 

23,281

 

23,281

 

Wald chi2

2590.61(0.000)

 

784.10(0.000)

 

1086.90(0.000)

 

Pseudo R2

0.0318

 

0.0284

 

0.0424

 

linktest

not significant

not significant

 

significant

 

Pearson chi2

22,952.09 (0.883)

 

23,059.03 (0.755)

23,174.43 (0.561)

 

Hosmer-Lemeshow chi2

26.69 (0.000)

44.31 (0.000)

 

5.02 (0.756)

 
  1. Note: _cons (constant) estimates baseline odds; ***p-value < 0.01, ** p-value < 0.05, * p-value < 0.10; dy/dx for factor levels is the discrete change from the base level