. 2023 Mar 20;58(3):289–297. doi: 10.1093/alcalc/agad014

Table 5.

Hierarchical Regression Predictors of Alcohol Consumption

	Model 1			Model 2			Model 3			Model 4
	R² / Adj. R² / ∆ R²	β	95% CI	R² / Adj. R² / ∆ R²	β	95% CI	R² / Adj. R² / ∆ R²	β	95% CI	R² / Adj. R² / ∆ R²	β	95% CI
	.063			.063 / -.102 / .001			.446 / .308 / .383^^^*			.472 / .272 / .026
Block 1 – Demographics
Age		−.081	[-.177, .112]		−.083	[-.180, .114]		−.095	[-.157, .081]		−.060	[-.160, .111]
Sex		.076	[-1.936, 2.981]		.077	[-1.972, 3.022]		.014	[-1.956, 2.109]		−.004	[-1.941, 2.090]
Cigarette Smoker		.073	[-1.883, 2.867]		.071	[-1.475, 2.900]		.011	[-1.951, 2.900]		.031	[-1.941, 2.356]
Cannabis User		.177	[-1.387, 4.056]		.174	[-1.475, 4.096]		.013	[-2.223, 2.412]		.006	[-2.342, 2.436]
BMI		.229	[-.100, .436]		.228	[-.105, .440]		.227	[-.057, .390]		.231	[-.076, .415]
Block 2 – Medication
Ibudilast					.023	[-2.144, 2.454]		.000	[-1.847, 1.846]		−.029	[-2.181, 1.796]
Block 3 – Baseline Craving Severity
PACS								.269	[-.098, .372]		.232	[-.138, .375]
AUDIT								*.410^*	[-.032, .478]		*.485^*	[-.011, .539]
Block 4 – Metabolites
dACC Cr											−.106	[-.394, .226]
dACC Cho											−.137	[-.660, .285]
dACC mI											.160	[-.145, .367]