Risk and Protective Factors for Alcohol Use Disorders Across the Lifespan

Abstract

Purpose of Review Losing and regaining control over alcohol intake varies as a function of individual-level predictors across the lifespan. Specifically, the interplay of protective and risk factors for losing and regaining control, particularly in real-life settings, is thus far poorly understood. Individual differences in cognition, affect, emotion regulation, social factors, and personality traits, together with individual differences in brain structure and function, and biological markers of stress exposure may have different effects on alcohol consumption in different age groups. We will review current evidence for age-specific effects for losing and regaining control over alcohol intake and propose a framework for investigation across age groups. Recent Findings We find evidence for differences in relative impact of psychosocial predictors of alcohol consumption as a function of age that varies by gender. There is theoretical reason to assume that predictors vary in the time course of their taking effect: While e.g., early trauma and personality traits may be conceptualized as more distant antecedents of alcohol consumption, cognition, affect and emotion regulation can be conceptualized as co-correlates, where variation over periods of months may go along with changes in alcohol consumption. At the same time, craving, current stressors, and priming events may serve as short-term or immediate causes of alcohol consumption. Summary We propose a combination of longitudinal age cohorts to (i) identify individual-level differences (using latent growth curve models) and profiles (using latent growth mixture models) of the psychosocial and biological variables of interest that predict regaining or losing control, and ambulatory assessments every 2 days, in order to (ii) investigate effects of triggers and risk factors on current alcohol consumption. This approach will allow us to characterize age-related differences in the interplay between these factors in real-life settings.

Polysubstance use classes and health outcomes among women attending specialist substance use treatment services

“…Thus, routine screening at treatment centres for past trauma is important. Taken together, these findings on the differences in age between classes support the need to consider how risk factors and psychosocial factors vary across the life span in treatment approaches [46].…”

How to prevent alcohol and illicit drug use among students in affluent areas: a qualitative study on motivation and attitudes towards prevention

“…The wish to be included in the social life and achieve high social status within the peer group was described as a central motive for substance use among a majority of the students, along with fear of being excluded if abstaining. Previous research show that high socioeconomic status is a protective factor for substance use disorder among adults [ 60 ], but among young people it may be the opposite. High status appears to be an important risk factor for the use of substances, at least among those striving for higher status.…”

Structural differences in adolescent brains can predict alcohol misuse

“…These phenotypes are listed in Table 2 and include each of the individual metrics, their combinations, and their longitudinal trajectories from age 14–22. The longitudinal phenotypes, ‘Binge-growth’ and ‘AUDIT-growth’, are generated using latent growth curve models ( Deeken et al, 2020 ) to capture the alcohol misuse trajectory over the four time points - BL, FU1, FU2, and FU3. To derive the AAMs group and the controls from each alcohol misuse metric, a standard procedure is followed that is similar to Seo et al, 2019 ; Ruan et al, 2019 .…”