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Age Specificity of Effects of Health Problems on Drinking Reduction: A Lifespan Developmental Analysis

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A Correction to this article was published on 20 December 2023

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Abstract

Older adult drinking poses a growing public health concern, especially given the ongoing aging of the United States population. As part of a larger lifespan developmental project contrasting predictors of drinking reductions across different periods of adulthood, we tested age differences in effects of health problems on drinking declines across young adulthood, midlife, and older adulthood. We predicted these effects to be developmentally specific to midlife and older adulthood. We also tested moderation by alcohol use disorder (AUD) symptomatology and by indices of sociodemographic disadvantage (sex and race/ethnicity). Analyses used data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), leveraging NESARC’s vast age range (18–90 + ; N = 43,093) and two waves of longitudinal data. Multiple-group cross-lag models tested differences across age groups in cross-lag paths between health problems and alcohol consumption. As hypothesized, health problem effects on drinking reductions were developmentally specific to midlife and older adulthood. However, models testing moderation by AUD symptomatology showed that these adaptive effects of health problems on drinking reductions did not extend to those with one or more AUD symptoms. Little evidence was found for moderation by sex or race/ethnicity. Findings support the notion of health concerns as a pathway to drinking reduction that increases in importance across the adult lifespan. However, given the moderation by AUD symptoms, findings also highlight a need to understand barriers to health-related pathways to drinking reduction among relatively severe midlife and older adult drinkers. These findings hold implications for lifespan developmental tailoring of clinical, public health, and policy interventions.

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Notes

  1. We use the term problem drinking to refer broadly to numerous inter-related phenomena involving risky, excessive, and consequential drinking (Lee et al., 2022); including but not limited to formal diagnostic conditions like alcohol use disorder (AUD; e.g., DSM-5, American Psychiatric Association (APA), 2013).

  2. Opinions vary regarding the age ranges that best represent different developmental periods, but concerns about such controversies should be tempered by an understanding that age is merely an imprecise proxy for individually varying developmental progression (Rutter, 1989).

  3. Although alcohol craving is also included among the DSM-5 AUD criteria, this criterion was assessed only at NESARC Wave 2, so we excluded it from the current study’s symptom count. The alcohol craving symptom was added at NESARC Wave 2 per changes to the diagnostic system in the DSM-5. The DSM changed from distinguishing between the two conditions of alcohol abuse and alcohol dependence in the DSM-IV (American Psychiatric Association, 1994) to having a single condition of alcohol use disorder in the DSM-5 (APA, 2013). Nevertheless, most symptoms remained across the two DSM versions except that the DSM-5 excluded a symptom assessing alcohol-related legal problems and added a symptom assessing alcohol craving.

  4. We replaced the term Latino with Latinx, which is one of the proposed gender neutral terms that signals Latin American ethnicity (de Onís, 2017). While many Hispanic and Latinx individuals identify as White (Telles, 2018), this study sought to index privileged status typically observed in non-Hispanic/non-Latinx White individuals compared to those who often do not benefit from the same privileged status (i.e., Asian, Black, Hispanic, Latinx, and Native American individuals).

  5. We also investigated moderation by sociodemographic disadvantage as indexed by sex and race/ethnicity, but no evidence was detected for such moderation. As a highly speculative post hoc interpretation, we suspect that risk associated with membership in disadvantaged groups may be counterbalanced by those of privileged groups having a lower perceived need to practice preventative health behaviors (e.g., reducing drinking in response to health concerns). This could stem from a greater confidence among privileged groups that health problems brought on by risky behaviors (e.g., heavy drinking) can be subsequently remedied through medical intervention. This notion is consistent with privileged groups’ greater trust in the medical establishment and greater opportunities to obtain/afford high-quality medical care (Marks et al., 2020). Again, this potential explanation is extremely speculative, and far more research is needed to understand sociodemographic variability in this and other behavior change processes.

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Funding

This research was supported by National Institute on Alcohol Abuse and Alcoholism (NIAAA) grants K99-AA024236 and R00-AA024236 to Matthew R. Lee (PI) and NIAAA grants K05-AA017242 and T32-AA013526 to Kenneth J. Sher (PI).

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Authors and Affiliations

  1. Department of Applied Psychology, Center of Alcohol and Substance Use Studies (CAS), Rutgers University, New Brunswick-Piscataway, NJ, USA

    Matthew R. Lee, Annabel Kady, Audrey Stephenson, Thomas Kwan, Douglas Bowlby & Willard Boyd

  2. Department of Psychology, Buffalo State College, Buffalo, NY, 14222, USA

    Michael G. MacLean

  3. Department of Psychological and Brain Sciences, The George Washington University, Washington, DC, 20052, USA

    Ellen W. Yeung

  4. Department of Psychological Sciences, University of Missouri, Columbia, MO, 65211, USA

    Kenneth J. Sher

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  1. Matthew R. Lee
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Correspondence to Matthew R. Lee.

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This study was performed in accordance with the ethical standards established in the 1964 Declaration of Helsinki and its later amendments, and it has been approved by the Institutional Review Board (IRB) of Rutgers University–New Brunswick.

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Lee, M.R., Kady, A., MacLean, M.G. et al. Age Specificity of Effects of Health Problems on Drinking Reduction: A Lifespan Developmental Analysis. Prev Sci 24, 887–900 (2023). https://doi.org/10.1007/s11121-023-01541-1

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