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Table 3 Importance of education and employment status for pregnant women care trajectories

From: Mining care trajectories using health administrative information systems: the use of state sequence analysis to assess disparities in prenatal care consumption

Variables

OR [IC95%]

“High” level

“Absence” level

“Intermediate” level

(Clusters 1 vs 2-3)

(Clusters 2 vs 1-3)

(Clusters 3 vs 1-2)

N = 296

N = 546

N = 1676

Age

   

14-20 year/old

0.25 [0.1-0.61]**

2.17 [1.53-3.08]***

NS

21-35 year/old

1

1

1

>35 year/old

NS

1.32 [1.01-1.72]*

NS

Population type

   

Single women

NS

1.37 [1.10-1.70]**

0.82 [0.68-0.99]*

Education

   

No Diploma

0.71 [0.54-0.92]**

NS

NS

Technical Education

NS

NS

0.81 [0.67-0.97]*

Employment

   

Unemployed

NS

1.27 [1.03-1.55]*

0.76 [0.63-0.93]**

Blue-collar

NS

1.42 [1.15-1.73]***

NS

Precarious job

NS

NS

0.82 [0.69-0.98]*

Artisan

NS

NS

0.79 [0.67-0.97]*

Housing

   

House built after 1999

1.34 [1.03-1.73]*

NS

NS

  1. The results of the logistic regression models describe how each cluster membership relates to specific covariates
  2. ***p-value <0.001; **p-value <0.01; *p-value <0.05; NS: not significant
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BMC Health Services Research

ISSN: 1472-6963

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