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Table 2 Effect estimates for non-interacting variables from the logistic regression model

From: Increased demand for amphetamine treatment in rural Australia

 

Odds Ratio

95% Wald CI

p value

Indigenous

Yes

0.920

(0.808, 1.047)

0.207

No

Ref

–

–

Living arrangement

Alone

0.923

(0.785, 1.085)

0.330

With spouse/partner and/or child(ren)

1.000

(0.850, 1.176)

0.999

Unknown/others

0.892

(0.628, 1.267)

0.522

With parents or friends or relatives

Ref

–

–

Usual accommodation

Temporary accommodation or homeless

1.815

(1.473, 2.237)

< 0.001

Unknown/others

0.683

(0.464, 1.006)

0.053

Owned or rented

Ref

–

–

Source of referral

Legal

0.859

(0.734, 1.005)

0.057

Health care

0.777

(0.632, 0.955)

0.017

Other AOD

1.067

(0.879, 1.294)

0.512

Others

0.806

(0.652, 0.996)

0.046

Self

Ref

–

–

Source of income

Through employment

0.357

(0.276, 0.463)

< 0.001

No income

1.128

(0.801, 1.589)

0.490

Unknown

0.513

(0.372, 0.709)

< 0.001

Not through employment

Ref

–

–

  1. Residual deviance: 7073.1 on 8778 df. See also Additional file 2 for coefficient estimates for variables that interact with other variables. The p values were calculated based on z test