Table 3.
Estimates of multivariable multinomial logistic regression model of latent cluster allocation (modelling probability of being in Cluster 1).
Variable | Characteristic | Cluster 2 |
Cluster 3 |
Type III P-Value | ||
---|---|---|---|---|---|---|
Odds Ratio (95% CI) | Pairwise P-Value | Odds Ratio (95% CI) | Pairwise P-Value | |||
Age | 35–54 vs. 18–34 | 1.273 (0.720, 2.251) | 0.4059 | 1.749 (0.995, 3.073) | 0.0519 | 0.0125* |
55 + vs. 18–34 | 1.229 (0.509, 2.970) | 0.6461 | 3.180 (1.392, 7.264) | 0.0061* | ||
Gendera | Female vs. Male | 1.381 (0.815, 2.338) | 0.2303 | 2.907 (1.727, 4.891) | <0.0001* | <0.0001* |
Marital | Married or living together in a relationship vs. Never married | 1.300 (0.687, 2.460) | 0.4199 | 1.544 (0.832, 2.862) | 0.1683 | 0.1711 |
Other vs. Never married | 1.749 (0.881, 3.471) | 0.1100 | 1.146 (0.586, 2.241) | 0.6899 | ||
Education | Completed HSC vs. Some high school or less | 1.492 (0.687, 3.239) | 0.3114 | 1.590 (0.734, 3.444) | 0.2394 | 0.0446* |
TAFE certificate or diploma vs. Some high school or less | 0.952 (0.534, 1.700) | 0.8692 | 0.815 (0.461, 1.440) | 0.4804 | ||
University degree or higher vs. Some high school or less | 0.308 (0.127, 0.747) | 0.0092* | 0.392 (0.175, 0.877) | 0.0227* | ||
Employment | Other vs. Employed | 1.142 (0.524, 2.488) | 0.7385 | 1.160 (0.535, 2.514) | 0.7074 | 0.0572 |
Unable to work due to health reasons vs. Employed | 1.518 (0.769, 2.993) | 0.2287 | 2.766 (1.419, 5.391) | 0.0028* | ||
Unemployed vs. Employed | 1.293 (0.643, 2.600) | 0.4710 | 1.528 (0.758, 3.079) | 0.2360 | ||
Depression | Yes vs. No | 0.987 (0.593, 1.643) | 0.9595 | 1.536 (0.930, 2.536) | 0.0933 | 0.0703 |
Personality disorder | Yes vs. No | 0.874 (0.437, 1.747) | 0.7025 | 0.365 (0.177, 0.751) | 0.0062* | 0.0036* |
Substance use disorder | Yes vs. No | 11.953 (1.563, 91.423) | 0.0168* | 7.504 (0.954, 59.014) | 0.0555 | 0.0381* |
*Asterix denotes (P=<0.05).
Gender included male and female, where transgender or gender non-conforming was excluded from the respective logistic regression model due to low numbers (n = 2).