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Table 3 Binary logistic regressions predicting alcohol–related harms and severity levels of alcohol use disorder in Thai adolescents (n = 1187)

From: Association of supply sources of alcohol and alcohol-related harms in adolescent drinkers: the baseline characteristics of a high school cohort across Thailand

Variables

Adjusted Odds Ratio: AOR

(95% CI)

Any alcohol–related harms

(1)

Alcohol use disorder

(2)

Supply of alcohol

 Parental supply only (=1)

1.066 (0.521–2.181)

P = 0.861

1.178 (0.606–2.294)

P = 0.629

 Friend/siblings supply only (=1)

2.888 (1.636–5.098)

P <  0.001

2.664 (1.533–4.630)

P <  0.001

 Relatives supply only (=1)

2.148 (1.061–4.350)

P = 0.034

0.775 (0.322–1.865)

P = 0.569

 Both parental and friend/siblings supply (=1)

4.332 (2.211–8.488)

P <  0.001

4.356 (2.259–8.400)

P <  0.001

 Both parental and relatives supply (=1)

1.552 (0.641–3.759)

P = 0.330

3.184 (1.513–6.703)

P = 0.002

 Both friend/siblings and relatives supply (=1)

5.425 (3.094–9.511)

P <  0.001

3.443 (1.963–6.038)

P <  0.001

 All parental, friend/siblings, and relatives supply (=1)

6.357 (3.764–10.735)

P <  0.001

5.494 (3.294–9.163)

P <  0.001

Alcohol-drinking behavior

 Binge-drinking 2–3 times per month (=1)

12.115 (3.881–37.823)

P < 0.001

16.907 (4.817–59.345)

P < 0.001

Social media exposure to alcohol advertisements

 Picture (=1)

1.120 (0.626–2.006)

P = 0.702

1.117 (0.626–1.990)

P = 0.708

 Video clip (=1)

1.407 (0.748–2.648)

P = 0.290

1.001 (0.542–1.846)

P = 0.998

Alcohol reaction

 Have alcohol flushing reaction (=1)

3.915 (2.423–6.327)

P < 0.001

3.292 (2.034–5.329)

P < 0.001

Other sociodemographic factors

 Female students (= 1)

0.991 (0.714–1.376)

P = 0.957

1.069 (0.768–1.487)

P = 0.694

 Family economic status (total income less than average national expenditures =1)

2.029 (1.470–2.802)

P < 0.001

2.196 (1.592–3.029)

P < 0.001

 Do not live with parents (=1)

1.921 (1.305–2.828)

P < 0.001

2.185 (1.488–3.209)

P < 0.001

 Academic performance

(GPA less than 2.5 = 1)

1.447 (0.921–2.273)

P = 0.109

1.887 (1.208–2.947)

P = 0.005

 Live in Greater Bangkok (=1)

1.397 (0.973–2.008)

P = 0.070

1.164 (0.805–1.684)

P = 0.420

  1. (1) using binary logistic regression model (Enter method), Nagelkerke R square = 0.269. The reference group is never facing any alcohol–related harm within 12 months prior
  2. (2) using binary logistic regression model (Enter method), Nagelkerke R square = 0.268. The reference group is never having any symptoms of Alcohol Use Disorder within past 12 months
  3. CI Confidence interval, GPA Grade point average