Skip to main content

Table 4 Multivariate association between select characteristics and usual consumption levels (number of drinks consumed on a typical day) for Australian participants a

From: The association between exposure to social media alcohol marketing and youth alcohol use behaviors in India and Australia

 

Facebook n = 246

B (s.e.) p

YouTube n = 151

B (s.e.) p

Twitter n = 65

B (s.e.) p

Model Statistics

F(9, 237) 7.205 p < .001, AR2 .185

F(9, 143) 3.597 p < .001, AR2 .133

F(7, 63) 7.731 p < .001, AR2 .402

Model variables

 Age

−.096 (.097) .328

−.200 (.137) .146

−.128 (.180) .478

 Gender

−1.76 (.387) <.001*

−1.821 (.478) < .001*

−2.957 (.672) < .001*

 Education

.769 (.374) .041

1.220 (.512) .019

1.173 (.677) .092

 Alcohol brand logos on merchandise

−.308 (.376) .919

.312 (.486) .522

.439 (.686) .824

 Attended alcohol events advertised on SNS

.482 (.370) .194

.110 (.466) .814

−.237 (.677) .728

 Sharing own alcohol-related content on SNS

2.448 (.573) < .001*

1.453 (.854) .091

4.484 (1.320) .001*

 Suggestions on SNS to like/follow alcohol-related content

−.297 (.147) .044

−.356 (.206) .086

 Perceived increasing trends in alcohol advertising

−.133 (.388) .732

−.808 (.437) .069

 Friends sharing alcohol-related information on SNS

−.263 (.207) .205

−.231 (.265) .384

 Noticing alcohol-related content on SNS

−.032 (.192) .869

  1. AR2 adjusted r square, B unstandardized coefficient, s.e. standard error
  2. a non-drinkers coded as 0 drinks
  3. *p ≤ .008