A NuGenia Logics publication · Free to read

Substance Use Linked to Accelerated Biological Aging

Recent research has examined the relationship between substance use and biological aging, specifically focusing on alcohol, tobacco, and illicit drugs. The study analyzed data from 2,276 adults participating in the Person-to-Person Health Interview Study in Indiana, utilizing validated assessments of substance use disorder (SUD) severity and DNA methylation profiling to measure biological aging.

Key Findings

The findings revealed significant associations between various forms of substance use and accelerated biological aging, as measured by AgeAccelGrim2 and DunedinPACE. Notably, illicit opioid use and non-prescription opioid use were positively correlated with both measures of biological aging. Specifically, illicit opioid use showed a strong association (β=0.417, p=5.913e-11 for AgeAccelGrim2), indicating that individuals using these substances may experience accelerated aging processes.

Additionally, clinically significant alcohol use was positively associated with AgeAccelGrim2 (β=0.177, p=2.111e-08), although it did not show a similar association with DunedinPACE. Cigarette smoking also demonstrated a positive correlation with both biological aging measures across all levels of use, suggesting that tobacco consumption may contribute significantly to accelerated aging.

Interestingly, the study found that vaping was not associated with accelerated biological aging when analyzed alongside cigarette smoking, indicating a potential difference in the impact of these substances on biological aging.

What this study does not show

This study does not establish a causal relationship between substance use and biological aging, nor does it explore the underlying mechanisms that may link these factors.

Evidence scorecard

  • Analytic validity: Established
  • Clinical validity: Partial
  • Clinical utility: Not established

The evidence is based on primary research involving human participants.

Sponsored
Article slot — 728×90

Evidence classes are taken from source metadata — publication type and trial registration — never from opinion. How we classify · Corrections