Table 6 |
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|
Logistic regression analyses for associations with reporting being a "lights" smoker* |
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|
Variables |
Adjusted Odds Ratio (95% CI) |
|||
|
Model 1 (demo-graphics) |
Model 2 (+ socio-demo-graphics) |
Model 3 (+ smoking behaviour) |
Model 4 (+ smoking beliefs) |
|
|
|
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|
Demographic |
||||
|
Age (years)# |
1.14 (0.99 – 1.31) |
1.13 (0.98 – 1.31) |
1.14 (0.98 – 1.32) |
1.22 (1.04 – 1.43) |
|
Gender (women vs men) |
1.78 (1.20 – 2.65) |
1.77 (1.19 – 2.63) |
1.57 (1.03 – 2.39) |
1.46 (0.96 – 2.24) |
|
Māori vs European |
0.53 (0.35 – 0.80) |
0.56 (0.37 – 0.84) |
0.57 (0.37 – 0.87) |
0.55 (0.35 – 0.84) |
|
Pacific vs European |
0.14 (0.05 – 0.40) |
0.15 (0.05 – 0.44) |
0.13 (0.04 – 0.41) |
0.11 (0.04 – 0.35) |
|
Asian vs European |
2.09 (0.78 – 5.61) |
2.15 (0.79 – 5.84) |
0.99 (0.42 – 2.35) |
0.92 (0.38 – 2.20) |
|
Socio-demographic |
||||
|
Deprivation quintiles (increasing deprivation) |
- |
0.92 (0.79 – 1.06) |
0.94 (0.81 – 1.10) |
0.93 (0.79 – 1.09) |
|
Smoking behaviour |
||||
|
RYO smoker (only) vs Others |
- |
- |
0.58 (0.38 – 0.91) |
0.57 (0.37 – 0.90) |
|
Heaviness of smoking index (alternate version)** # |
- |
- |
0.86 (0.78 – 0.96) |
0.87 (0.78 – 0.96) |
|
Smoking beliefs |
||||
|
Awareness of smoking harm (7-item scale)** |
- |
- |
- |
1.82 (1.17 – 2.83) |
|
Holding at least one of the 3 beliefs that "lights" confer health benefits** |
- |
- |
- |
1.95 (1.29 – 2.95) |
|
|
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|
* The aORs in models 2, 3 & 4 are adjusted for the demographic and key socio-demographic variables (ie, deprivation), models 3 & 4 for smoking behaviour variables and model 4 for smoking beliefs. The included variables from the univariate analyses that became not significant in the models (at p < 0.05) were subsequently omitted from the final respective models, except for those considered critical to our conceptual framework (see Methods). ** See Tables 3 and 4 for further details on these indices and α scores (for multi-item indices) and Table 5 for the three questions used for the variable in the last row of the above table. # Continuous variable and for age the actual age (years) was divided by 10 so as to interpret the OR estimates for an increment of 10 years. |
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|
Wilson et al. BMC Public Health 2009 9:126 doi:10.1186/1471-2458-9-126 |
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