Supplement to a microsimulation of alcohol control interventions to advance health equity and reverse the current decrease in life expectancy in the US

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 3R01AA028009-03S1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2025
  • Known Financial Commitments (USD)

    $109,394
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    SCIENTIST Charlotte Probst
  • Research Location

    Canada
  • Lead Research Institution

    CENTRE FOR ADDICTION AND MENTAL HEALTH
  • Research Priority Alignment

    N/A
  • Research Category

    Secondary impacts of disease, response & control measures

  • Research Subcategory

    Indirect health impacts

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

PROJECT SUMMARY The COVID-19 pandemic has led to drastic declines in life expectancy in the United States (US), disproportionately affecting individuals with low socioeconomic status (SES) as well as Black and Hispanic populations. Mortality from non-COVID-related causes has also shown meaningful increases that contributed to the losses in life expectancy, including a striking 27% increase in age-adjusted mortality rates from alcohol- related causes from 2019 to 2020. The current application requests a supplement to the parent grant (R01AA028009) to account for the social, demographic, economic, and behavioral changes induced by the COVID-19 pandemic. Under the parent grant, a microsimulation of the adult (18+) general population is being developed to model years of potential life lost (YLL) from alcohol-attributable causes of death between 2000 and 2017 with a forward modeling time horizon until 2028. This supplement aims to augment the microsimulation model by incorporating the role and effects of the COVID-19 pandemic. Specifically, the role of alcohol use in excess mortality during the COVID-19 pandemic will be investigated among different population subgroups. Changes in psychological distress and alcohol-related policies during the pandemic will be investigated as potential drivers of changes in alcohol use. Current population-based data on alcohol use, psychological distress, alcohol-related policy changes, mortality, and population statistics will be used. Linear spline multilevel models, stratified by sex, will be used to investigate trends in alcohol use, conditional on SES and race/ethnicity. Age, individual-level psychological distress, and state-level alcohol-related policies, along with their interaction with year, will be introduced as covariates. Cause-specific contributions to changes in life expectancy will be calculated using a decomposition method. Transition probabilities between i) drinking patterns and ii) levels of education before and during the COVID-19 pandemic will be estimated using continuous-time Markov models. Findings will be integrated into an augmented microsimulation model. YLL from nine selected causes of death including alcohol use disorders, intentional and unintentional injuries, liver disease and cirrhosis, diabetes mellitus, and several cardiovascular diseases will be modeled. Counterfactual scenarios will be used to estimate i) excess alcohol-attributable YLL by population subgroup during the COVID-19 pandemic compared to a scenario without pandemic; ii) potential long-term effects on alcohol-attributable mortality assuming sustained compared to temporary changes in transition probabilities; and iii) alcohol-attributable YLL under different scenarios of long- and short-term implementation of restrictive and permissive alcohol-related policies during the pandemic and beyond. The findings will provide unique insights into the impact of the COVID-19 pandemic on alcohol use and alcohol-attributable mortality in different population subgroups. Furthermore, the augmented microsimulation model will constitute a robust foundation for policy and intervention modeling performed under the parent grant.