Skip to main content

Table 2 Association of the PBMC score and primary care utilization (univariate regressions)

From: Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal

 

Population

Dependent variable

Model

Type of estimate

Estimate

p-value

Predictions

At Score = 0 (“not a problem”)

At Score = 1 (“a small problem”)

At Score = 2 (“a big problem”)

Primary care utilization

All adults (n = 1,787)

Forgone medical consultation (HH level)

Logistic

OR

3.10***

(0.45)

< 0.001

0.20

(0.02)

0.43

(0.02)

0.70

(0.04)

Forgone medical treatment (HH level)

Logistic

OR

1.30

(0.18)

0.061

0.21

(0.02)

0.26

(0.02)

0.31

(0.04)

Participants with a recent episode of illness (n = 418)

Consulted in a health facility following an episode of illness

Logistic

OR

0.63*

(0.15)

0.047

0.41

(0.05)

0.30

(0.03)

0.22

(0.05)

Self-medicated following an episode of illness

Logistic

OR

2.09**

(0.47)

0.001

0.20

(0.04)

0.34

(0.03)

0.52

(0.07)

Women with a recent birth (n = 197)

Gave birth in a health facility

Logistic

OR

0.46*

(0.16)

0.023

0.68

(0.07)

0.49

(0.05)

0.31

(0.10)

Number of prenatal consultations

Poisson

IRR

0.87*

(0.06)

0.028

3.69

(0.20)

3.20

(0.12)

2.78

(0.25)

  1. Notes: *p < 0.05, **p < 0.01, ***p < 0.001. All variables measured at the individual level, unless when HH-level specified. Robust standard errors (clustered at the household level to account for intra-household correlation) in parenthesis. Regressions were weighted using sampling weights to account for choice-based stratified samples. All binary dependent variables were coded as 0 for “no” and 1 for “yes”. For logistic models, predictions are predicted probabilities of the dependent variable. For Poisson models, predictions are the predicted number of events
  2. Abbreviations: n = number of observations, HH = household, OR = odds ratio, CBHI = community-based health insurance, IRR = incidence-rate ratio