Alcohol marketing on social media: young people’s exposure, engagement and alcohol-related behaviors

Figures & data

Table 1. Description of the sample (N = 3698).

Age (N = 3424)	n	%
14	386	11.3
15	307	9.0
16	646	18.9
17	586	17.1
18	665	19.4
19	464	13.6
20	370	10.8
Gender (N = 3382)
Wahine / tamahine / girl / woman	1817	55.7
Tane / tama / boy / man	1251	38.3
Transgender, agender, non-binary, intersex, something else	195	6.0
Ethnicity (N = 3365)
Māori	851	25.6
Pākehā or New Zealand European	1552	46.7
Pasifika (Samoan, Cook Islands, Tongan, Niuean, Fijian)	215	6.5
Other	704	21.2
Perceived socioeconomic status (N = 3136)
Not well off at all	153	4.1
Not particularly well off	501	13.5
Fairly well off	1154	31.2
Rather well off	734	19.8
Very well off	192	5.2
Prefer not to say	402	10.9
Sexuality (N = 3309)
Straight (heterosexual)	2236	67.6
Gay/lesbian	117	3.6
Bisexual	440	13.3
Queer, pansexual, asexual, something else	250	7.5
Takatapui	12	0.4
Not sure yet	170	5.1
Prefer not to say	84	2.5
Place of residence (N = 3196)
Major city	1743	54.5
Other city	426	13.3
Town	525	16.4
Small town	306	9.6
In the country	196	6.1

Table 2. Binary logistic regression showing differences in engagement with alcohol product advertising on social media by age, gender, ethnicity and socioeconomic status (SES).

	Odds ratio	95% CI for odds ratio		p Value
		Lower	Upper
Age^a: 18–20 years (n = 818), 14–17 years (n = 967)				<.001
18–20 vs 14–17	2.51	2.06	3.05	<.001
Gender: female (n = 991), male (n = 672), other (n = 122)				<.001
Female vs male	1.40	1.14	1.73	.001
Female vs other	2.15	1.42	3.27	.001
Ethnicity^b: Māori (n = 409), Pākehā (n = 895), Pasifika (n = 89), other (n = 392)				<.001
Māori vs Pākehā	1.09	0.85	1.40	.478
Māori vs Pasifika	1.47	0.90	2.40	.119
Māori vs Other	1.76	1.31	2.38	<.001
Pākehā vs Pasifika	1.35	0.84	2.13	.217
Pakeha vs Other	1.63	1.26	2.12	<.001
Pasifika vs Other	1.21	0.74	2.00	.440
Socioeconomic status (SES): low (n = 395), middle (n = 752), high (n = 638)				.490
Low vs middle SES	1.17	0.90	1.52	.233
Low vs high SES	1.10	0.84	1.44	.491

Note: Model χ² (8, N = 1785) = 137.32, p < .001.

^a Coding: Engagement with alcohol advertising 1 = yes, 0 = no. For all category contrasts in the predictor variables the left hand category = 1 and the right hand category = 0. This coding favors odds ratios greater than 1 for ease of interpretation.

^b To obtain all ethnicity contrasts the same model was run several times each with a different reference category for ethnicity. These contrasts are shown in the same table for ease of reporting.

Table 3. Binary logistic regression showing differences in purchasing alcohol on line by age, gender, ethnicity and socioeconomic status (SES) (Step 1); and by recall of exposure to and engagement with alcohol advertising (Step 2).

	Odds ratio	95% CI for odds ratio		p Value
		Lower	Upper
Step 1
Age^a 18–20 years (n = 801), 14–17 years (n = 942)
18–20 vs 14–17	5.56	3.76	8.20	<.001
Gender: female (n = 976), male (n = 651), other (n = 116)				.386
Female vs male	0.87	0.61	1.23	.418
Female vs other	1.43	0.69	2.96	.340
Ethnicity^b: Māori (n = 402), Pākehā (n = 871), Pasifika (n = 86), other (n = 384)				.005
Māori vs Pākehā	1.24	0.85	1.82	.270
Māori vs Pasifika	1.70	0.73	3.97	.222
Māori vs Other	2.71	1.55	4.75	<.001
Pākehā vs Pasifika	0.73	0.32	1.67	.456
Pakeha vs Other	2.19	1.30	3.68	.003
Pasifika vs Other	1.60	0.64	4.02	.318
Socioeconomic status (SES): low (n = 386), middle (n = 737), high (n = 620)				.587
Low vs middle SES	1.03	0.68	1.54	.904
Low vs high SES	1.23	0.79	1.92	.369
Step 2	2.55	1.38	4.69	.003
Exposure to advertising: yes (n = 1245); no (n = 498)
Engagement with advertising: yes (n = 724); no (n = 1019)	6.49	4.12	10.31	<.001

Note: Model χ² (10, N = 1743) = 239.68, p < .001.

^a Coding: Purchased alcohol on line 1 = yes, 0 = no. For all category contrasts in the predictor variables the left hand category = 1 and the right hand category = 0. This coding favors odds ratios greater than 1 for ease of interpretation.

^b To obtain all ethnicity contrasts the same model was run several times each with a different reference category for ethnicity. These contrasts are shown in the same table for ease of reporting.

Table 4. Binary logistic regression showing differences in alcohol history by age, gender, ethnicity and socioeconomic status (SES) (Step 1) and recall of exposure to and engagement with alcohol advertising on line (Step 2).

	Odds ratio	95% CI for odds ratio		p Value
		Lower	Upper
Step 1^a
Age: 18–20 years (n = 786), 14–17 years (n = 908)
18–20 vs 14–17	5.84	4.51	7.56	<.001
Gender: female (n = 946), male (n = 634), other (n = 114)				.004
Female vs male	1.39	1.09	1.76	.008
Female vs other	1.79	1.13	2.83	.012
Ethnicity^b: Māori (n = 389), Pākehā (n = 847), Pasifika (n = 83), other (n = 375)				<.001
Māori vs Pākehā	1.32	0.96	1.81	.083
Māori vs Pasifika	3.34	1.94	5.78	<.001
Māori vs Other	2.95	2.09	4.17	<.001
Pākehā vs Pasifika	2.56	1.52	4.17	<.001
Pakeha vs Other	2.24	1.69	2.95	<.001
Pasifika vs Other	0.88	0.52	1.50	.640
Socioeconomic status (SES): low (n = 374), middle (n = 717), high (n = 603)				.249
Low vs middle SE	1.15	0.84	1.59	.377
Low vs high SES	1.32	0.95	1.83	.102
Step 2
Exposure to advertising: yes (n = 1220) vs no (n = 483)	1.79	1.38	2.33	<.001
Engagement with advertising: yes (n = 712) vs no (n = 991)	6.88	4.97	9.51	<.001

Note: Model χ² (10, N = 1703) = 541.64, p < .001.

^a Coding: Alcohol history 1 = yes, 0 = no. For all category contrasts in the predictor variables the left hand category = 1 and the right hand category = 0. This coding favors odds ratios greater than 1 for ease of interpretation.

^b To obtain all ethnicity contrasts the same model was run several times each with a different reference category for ethnicity. These contrasts are shown in the same table for ease of reporting.

Table 5. Mean AUDIT-C scores by age, gender, ethnicity & SES groups (n = 1285) and by recall of exposure and engagement.

	N	Mean	SD
Age
14	59	2.15	2.61
15	55	2.38	3.06
16	205	3.36	2.60
17	231	4.15	2.40
18	319	4.69	2.73
19	228	5.05	2.70
20	188	5.20	2.51
Gender
Female	758	4.16	2.57
Male	445	4.61	3.03
Other genders	82	3.90	2.81
Ethnicity
Māori	333	4.87	2.66
Pākehā	677	4.43	2.77
Pasifika	48	4.58	2.76
Other ethnicities	227	3.04	2.52
Socioeconomic status
Low	317	4.60	2.87
Middle	544	4.08	2.69
High	424	4.37	2.75
Exposure and engagement
Exposed to advertising	988	4.48	2.76
Not exposed to advertising	268	3.57	2.62
Engaged with advertising	667	5.29	2.56
Not engaged with advertising	542	3.16	2.55

Table A1. Binary logistic regression showing differences in exposure to alcohol product advertising on social media by age, gender, ethnicity and socioeconomic status (SES).

	Odds ratio	95% CI for odds ratio		p Value
		Lower	Upper
Age 18–20 vs 14–17	1.56	1.27	1.92	<.001
Gender				.334
Female vs male	1.17	.94	1.45	.151
Female vs other	1.15	.76	1.73	.506
Ethnicity				.146
Māori vs Pakeha	.88	.68	1.14	.344
Māori vs Pasifika	.90	.47	1.35	.399
Māori vs Other	1.17	.87	1.57	.310
Pasifika vs Pakeha	1.11	.67	1.84	.696
Pasifika vs Other	1.46	.86	2.48	.157
Socioeconomic status (SES)				.763
Low vs middle SES	1.02	.78	1.34	.893
Low vs high SES	1.10	.82	1.46	.527

Notes: Model chi square (8, N = 1870) = 29.40, p < .001. Coding: Alcohol advertising exposure 1 = yes, 0 = no. For all category contrasts in the predictor variables the left hand category = 1 and the right hand category = 0. This coding favors odds ratios greater than 1 for ease of interpretation.