Table 3

Results of multivariate model of best fit, derived through logistic regression, showing odds ratios (OR) with 95% confidence intervals, for the factors with significant and independent effects on the likelihood of developing asthma.

All asthma

Aged 0-1 at asthma admission

Aged 2+ at asthma admission


Characteristics

OR

95% C.I.

OR

95% C.I.

OR

95% C.I



Maternal asthma

No

1.00

-

1.00

-

1.00

-


Yes

3.11

2.67-3.63

3.89

2.71-5.57

3.07

2.61-3.60


Social class

1-2

0.81

0.74-0.89

0.76

0.58-0.98

0.81

0.74-0.89


3

1.00

-

1.00

-

1.00

-


4-5

1.07

0.96-1.20

1.09

0.82-1.47

1.04

0.94-1.16


Sex

Female

1.00

-

1.00

-

1.00

-


Male

1.82

1.66-1.99

2.08

1.64-2.65

1.53

1.41-1.66


Birth weight (g)

1000-2999

1.20

1.09-1.33

1.42

1.08-1.86

1.21

1.10-1.33


3000-3999

1.00

1.00

1.00

-


4000-5499

1.01

0.87-1.17

0.88

0.58-1.34

1.06

0.92-1.22


Gestation age (wks)

24-37

-

-

1.59

1.15-2.20

-

-


38-41

-

-

1.00

-

-

-


42-47

-

-

1.28

0.89-1.83

-

-


Smoking

No

1.00

-

1.00

-

-

-


Yes

1.13

1.02-1.25

1.35

1.04-1.74

-

-


Parity

0

-

-

1.00

-

-

-


1

1.34

1.03-1.74


2

1.38

0.99-1.93


3

2.19

1.42-3.38


4+

-

-

2.01

1.07-3.76

-

-


Caesarean

No

1.00

-

-

-

-

-


Yes

1.18

1.02-1.34

-

-

-

-


All variables that were significant (p < 0.05) in the univariate analysis (see Table 2) were included in the initial model and the variables that were not significant were removed. In further modelling, each variable that was not significant in univariate analysis was re-introduced, one at a time, into the model. The purpose of this was to test whether any variable, not significant in univariate analysis, became so when modelled with the other significant variables.

Davidson et al. BMC Pulmonary Medicine 2010 10:14   doi:10.1186/1471-2466-10-14

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