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Association between alcohol screening scores and mortality in black, Hispanic, and white male veterans.

Williams EC, Bradley KA, Gupta S, Harris AH. Association between alcohol screening scores and mortality in black, Hispanic, and white male veterans. Alcoholism, clinical and experimental research. 2012 Dec 1; 36(12):2132-40.

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Abstract:

BACKGROUND: Scores on the Alcohol Use Disorders Identification Test Consumption (AUDIT-C) questionnaire are associated with mortality, but whether or how associations vary across race/ethnicity is unknown. METHODS: Self-reported black (n = 13,068), Hispanic (n = 9,466), and white (n = 182,688) male Veterans Affairs (VA) outpatients completed the AUDIT-C via mailed survey. Logistic regression models evaluated whether race/ethnicity modified the association between AUDIT-C scores (0, 1 to 4, 5 to 8, and 9 to 12) and mortality after 24 months, adjusting for demographics, smoking, and comorbidity. RESULTS: Adjusted mortality rates were 0.036, 0.033, and 0.054, for black, Hispanic, and white patients with AUDIT-C scores of 1 to 4, respectively. Race/ethnicity modified the association between AUDIT-C scores and mortality (p = 0.0022). Hispanic and white patients with scores of 0, 5 to 8, and 9 to 12 had significantly increased risk of death compared to those with scores of 1 to 4; Hispanic ORs: 1.93, 95% CI 1.50 to 2.49; 1.57, 1.07 to 2.30; 1.82, 1.04 to 3.17, respectively; white ORs: 1.34, 95% CI 1.29 to 1.40; 1.12, 1.03 to 1.21; 1.81, 1.59 to 2.07, respectively. Black patients with scores of 0 and 5 to 8 had increased risk relative to scores of 1 to 4 (ORs 1.28, 1.06 to 1.56 and 1.50, 1.13 to 1.99), but there was no significant increased risk for scores of 9 to 12 (ORs 1.27, 0.77 to 2.09). Post hoc exploratory analyses suggested an interaction between smoking and AUDIT-C scores might account for some of the observed differences across race/ethnicity. CONCLUSIONS: Among male VA outpatients, associations between alcohol screening scores and mortality varied significantly depending on race/ethnicity. Findings could be integrated into systems with automated risk calculators to provide demographically tailored feedback regarding medical consequences of drinking.





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