Login / Signup

Alcohol use severity among recent Latino immigrants: Associations of acculturation, family history of alcohol use and alcohol outcome expectancies.

Ashly C WestrickMariana SanchezWeize WangMiguel Ángel CanoPatria RojasMario R De La Rosa
Published in: Journal of ethnicity in substance abuse (2021)
Having a family history of alcohol (FH+) use is a well-documented risk factor for alcohol use and alcohol related problems. However, there are limited studies examining the impact of FH + on current alcohol use among Latino immigrants. This study aimed to determine the influence of having a FH + on current alcohol use among Latino immigrants and the influence of alcohol outcome expectancies (AOEs) and acculturation on this relationship. This is a longitudinal secondary data analysis of data from the Recent Latino Immigrant Study (RLIS), the first community-based cohort study to examine pre- to post-immigration alcohol use trajectories of young adult Latino immigrants. Linear mixed models were performed to assess the association between various pre- and post-immigration factors and alcohol use among Latino immigrants. There were 518 young adult Latino immigrants with 18.7% reporting a FH + with those with a FH + having higher mean AUDIT score compared to those without (4.74 vs. 3.81; p = 0.028). Positive AOEs were associated with increase AUDIT scores. FH + individuals with greater positive AOEs experienced higher AUDIT scores compared to FH- individuals. Family cohesion was protective against alcohol use while endorsement of Americansism was associated with increased alcohol use. Theses results provide the framework for more in-depth exploration regarding the influences of FH+, AOEs, and acculturation have on the alcohol use among Latino immigrants. Future longitudinal research studies should account for whether traditional cultural values mediate or moderate the relationship between a FH+, AOE, and alcohol use of Latino immigrants.
Keyphrases
  • african american
  • alcohol consumption
  • young adults
  • mental health
  • emergency department
  • machine learning
  • case control