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Table 4 Percent and prevalence ratio for having renounced care for time-related reasons

From: Renouncing care in French Guiana: the national health barometer survey

Variables

Have renounced for time-related reasons (%)

p*

Prevalence ratio**

p**

Gender (N = 2012)

Male

21.4

0.031

  

Female

26.5

   

Age (N = 2012)

15–24 years

20.5

0.011

  

25–34 years

26.9

   

35–44 years

29.3

   

45–54 years

25.4

   

55–64 years

15.9

   

65–75 years

16.3

   

Birth place (N = 2012)

Born in France

25.2

0.205

  

Foreign-born

21.9

   

Educational level (N = 1991)

None

19.9

< 0.001

1

0.0015

Below High school graduation

23.06

 

1.21 [0.90;1.62]

High school graduation

31.2

 

1.64 [1.23;2.18]

first college degree

26.8

 

1.36 [0.94;1.96]

Equal or above to a bachelor degree

33.7

 

1.70 [1.25;2.32]

Perceived Financial Status (N = 1997)

You are really comfortable

17.7

0.031

  

Your are comfortable

24.01

   

It is tight

25.6

   

It’s really difficult

23.8

   

You do not make ends meet without making debts

35.5

   

Language most often spoken (N = 2012)

French

26.5

0.239

  

Creole

19.3

   

Portuguese

28.7

   

English

20.4

   

Nengue tongo

19.2

   

Amerindians languages

21.5

   

Others

20.4

   

Professional Status (N = 2012)

Employed

27.9

0.013

1

0.02

Student

18.8

 

0.73 [0.53;1.00]

Unemployed

23.7

 

0.96 [0.72;1.29]

Retired

13.8

 

0.50 [0.31;0.80]

Other inactive

19.7

 

0.80 [0.51;1.26]

Living conditions (N = 2011)

Having water at home

24.6

0.238

  

No water at home

19.1

   

Residence location (N = 2012)

Coastal

24.7

0.539

  

Savanas

20.8

   

Western

25.2

   

Eastern

17.7

   

Having a religion (N = 2005)

Yes

23.9

0.834

  

No

24.4

   

Perceived health (N = 2000)

Very good

19.9

0.067

1

0.0043

Good

24

 

1.19 [0.89;1.58]

Fairly good

25.4

 

1.35 [0.99;1.84]

Poor / Very poor

34.3

 

2.06 [1.37;3.12]

Having complementary health insurance (N = 1989)

Yes

23.9

0.791

  
 

No

24.8

   
  1. *Pearson’s chi-square test in bivariate analysis
  2. **Final multivariate model