TABLE 2.
Gender specific ANCOVAs predicting AUDIT scores by BPHSUP+/− status with age, education and income as covariates for T1, T2 and T3 (N=452)
| GENDER* | Predictors | F | df | p = | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Men’s AUDIT Scores T1 | Fixed Factor | ||||||||||
| BPHSUP+ (n=48) | BPHSUP− (n=197) | BPHSUP+/− status | 19.40 | 1, 244 | <.001 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 11.54 | (9.35, 12.92) | 7.90 | .91 | 6.55 | (5.79, 7.51) | 5.64 | .44 | Age | 3.40 | 1, 244 | .066 |
| (Observed AUDIT scores presented) | Education T1 | 3.49 | 1, 244 | .063 | |||||||
| F=8.26, df=4, 240, p<.001 | Income T1 | 0.88 | 1, 244 | .349 | |||||||
| Men’s AUDIT Scores T2 | Fixed Factor | ||||||||||
| BPHSUP+ (n=30) | BPHSUP− (n=142) | BPHSUP+/− status | 8.36 | 1, 171 | .004 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 7.93 | (5.99, 9.26) | 5.56 | .83 | 4.91 | (4.24, 5.72) | 4.27 | .38 | Age | 1.79 | 1, 171 | .183 |
| (Observed AUDIT scores presented) | Education T2 | 4.05 | 1, 171 | .046 | |||||||
| F=4.62, df=4, 167, p<.001 | Income T2 | 0.34 | 1, 171 | .560 | |||||||
| Men’s AUDIT Scores T3 | Fixed Factor | ||||||||||
| BPHSUP+ (n=48) | BPHSUP− (n=197) | BPHSUP+/− status | 17.60 | 1, 244 | <.001 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 7.60 | (6.31, 8.90) | 5.47 | .66 | 4.48 | (3.84, 5.12) | 4.32 | .33 | Age | 0.99 | 1, 244 | .320 |
| (Observed AUDIT scores presented) | Education T3 | 0.02 | 1, 244 | .881 | |||||||
| F=6.85, df=4, 240, p<.001 | Income T3 | 8.24 | 1, 244 | ..004 | |||||||
| Women’s AUDIT Scores T1 | Fixed Factor | ||||||||||
| BPHSUP+ (n=36) | BPHSUP− (n=171) | BPHSUP+/− status | 34.22 | 1, 205 | <.001 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 7.28 | (6.01, 8.91) | 6.84 | .74 | 2.76 | (2.06, 3.39) | 4.00 | .34 | Age | 4.00 | 1, 205 | .047 |
| (Observed AUDIT scores presented) | Education T1 | 3.83 | 1, 205 | .052 | |||||||
|
#F=13.92, df=4, 201,
p<.001 #1-person had missing income T1 |
Income T1 | 12.77 | 1, 205 | >.001 | |||||||
| Women’s AUDIT Scores T2 | Fixed Factor | ||||||||||
| BPHSUP+ (n=29) | BPHSUP− (n=151) | BPHSUP+/− status | 13.84 | 1, 179 | <.001 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 5.90 | (4.24, 7.55) | 5.82 | .79 | 2.79 | (2.09, 3.45) | 4.08 | .35 | Age | 3.16 | 1, 179 | .077 |
| (Observed AUDIT scores presented) | Education T2 | 2.72 | 1, 179 | .101 | |||||||
| F=7.20, df=4, 175, p<.001 | Income T2 | 8.39 | 1, 179 | .004 | |||||||
| Women’s AUDIT Scores T3 | Fixed Factor | ||||||||||
| BPHSUP+ (n=36) | BPHSUP− (n=171) | BPHSUP+/− status | 10.01 | 1, 206 | .002 | ||||||
| M | 95% CI | SD | SE | M | 95% CI | SD | SE | Covariates | |||
| 4.72 | (3.49, 5.95) | 4.65 | .62 | 2.61 | (2.05, 3.17) | 3.52 | .29 | Age | 0.62 | 1, 206 | .432 |
| (Observed AUDIT scores presented) | Education T3 | 4.34 | 1, 206 | .039 | |||||||
| F=3.77, df=4, 202, p<.006 | Income T3 | 0.38 | 1, 206 | .538 | |||||||
Note.
*
Rerun ANCOVAs combining genders yield the same results for men’s and women’s AUDIT scores with main effect of BPHSUP+/− status as shown above. As expected, a gender specific effect is significant (p<.001) with men having higher AUDIT scores across all 3-waves but all covariates become non-significant except for men’s income at T1 (which is not significant in Table 1 as shown above). Thus, disaggregating the analyses by gender may be more informative longitudinally to ensure salient socio-demographics are not overlooked in predicting outcomes by gender.