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Table 1 Sample characteristics by counter-advertising condition (n = 1075)

From: Can counter-advertising exposing alcohol sponsorship and harms influence sport spectators’ support for alcohol policies? An experimental study

 

Counter-advertising condition

Total

(n = 1075)

Control ad

(n = 356)

Counter-adexposingalcohol harms

(n = 367)

Counter-adexposingalcohol sponsorship and harms

(n = 352)

%

%

%

%

Gender

 Male

52.0

51.7

53.4

50.9

 Female

48.0

48.3

46.6

49.1

Age

 18–34 years

48.7

49.2

47.7

49.4

 35–49 years

51.3

50.8

52.3

50.6

 M (SD)

34.59 (7.72)

34.24 (7.92)

35.01 (7.67)

34.50 (7.56)

Highest level of education completed

 Non-tertiary

45.8

44.7

49.3

43.2

 Tertiary

54.2

55.3

50.7

56.8

SES (area-based) #

 Low SES

23.5

24.7

22.1

23.7

 Medium SES

35.9

35.7

36.5

35.4

 High SES

40.6

39.6

41.4

40.9

Parent (any aged child)

 No

32.5

34.6

32.4

30.4

 Yes

67.5

65.4

67.6

69.6

Frequency of drinking alcohol over last 12 months

 At least weekly

66.1

66.3

66.5

65.6

 At least monthly (but less than weekly)

23.4

22.8

22.6

25.0

 Less than monthly / Never

10.4

11.0

10.9

9.4

  1. Notes: Percentages are rounded so may not sum to 100%. All sample characteristics were assessed at baseline# SES was determined according to the Australian Bureau of Statistics' Index of Relative Socio-Economic Disadvantage ranking for Australia using participants' home postcode [32]. Participants who resided in a postcode ranked in the bottom third of the index were categorised as low SES, those in the middle third of the index as medium SES and those in the upper third as high SES. SES information is missing for 2 participants as they provided invalid postcodes