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Table 3 Multiple regression analyses: Prediction of inpatient service utilization by distance (minutes in public transportation between patient’s homes and the mental hospital) and by available ecological variables of the communities

From: The gravitational force of mental health services: distance decay effects in a rural Swiss service area

 

Inpatient cases per capita

Inpatient days per capita

Characteristic of the community

B (95% CI)

SE

β

p

B (95% CI)

SE

β

p

Constant

−5.515 (−18.375, 7.396)

6.493

 

.396

− 130.031 (− 608.273, 453.067)

271.087

 

.694

Distance (travel time in minutes)

−0.014 (− 0.036, 0.008)

0.011

− 0.101

.214

− 0.748 (−1.618, 0.108)

0.440

−0.120

.102

Age (mean in years)

0.018 (−0.131, 0.184)

0.081

0.014

.829

−1.342 (−9.410, 6.165)

3.936

−0.023

.731

Female (%)

14.807 (−11.975, 41.981)

13.505

0.077

.274

518.290 (−620.705, 1562.056)

554.487

0.059

.348

Immigrants (%)

7.394 (3.995, 10.828)

1.735

0.291

<.001

196.137 (52.491, 338.146)

72.500

0.169

.012

Taxes (mean per inhabitant in Swiss Francs)

−0.000 (−0.001, 0.000)

0.000

−0.015

.820

0.001 (−0.016, 0.019)

0.009

0.003

.949

  1. Inpatient cases per capita: R2 = .118, p < .001. Inpatient days per capita: R2 = .059, p = .036
  2. B = Regression weight
  3. 95% confidence intervals (CI) were estimated with bootstrap methods (based on k = 5000 samples)
  4. SE = Standard error
  5. β = Standardized regression weight