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Investigating the relationship between early life adversity, inflammation and alcohol use.

Jillian T BattistaDaria PiacentinoMelanie L SchwandtMary R LeeMonica L FaulknerMehdi FarokhniaLorenzo Leggio
Published in: Addiction biology (2023)
Early life adversity (ELA) has long-lasting and potentially harmful effects on adult mental and physical health, including a higher likelihood of developing psychiatric conditions such as depression, anxiety and alcohol use disorder (AUD). It has been suggested that inflammation may play a role in linking ELA to the development of AUD. Here, we evaluated a number of predictive factors of high sensitivity C-reactive protein (hsCRP), a key inflammatory marker, and the potential mediating role of hsCRP in the relationship between ELA and alcohol misuse in adulthood. Data was collected from participants who participated in NIAAA screening protocols between January 2013 and December 2019. In this secondary analysis, we first tested, via multiple linear regression, potential predictors of hsCRP levels among adults with AUD (N = 781) and non-AUD (N = 440) individuals. We subsequently conducted mediation analyses to evaluate the potential role of hsCRP in the relationship between early life stress and alcohol use. Regression analysis showed that stress in early life, but not childhood trauma, significantly predicted increased hsCRP levels in adulthood (p < 0.05). Additionally, a greater amount of alcohol drinking, but not a diagnosis of AUD, significantly predicted increased hsCRP levels (p < 0.05). Furthermore, hsCRP mediated the relationship between early life stress and alcohol consumption. Early life stress and heavier alcohol drinking both predicted increased hsCRP levels; however, an AUD diagnosis did not. Elevated inflammation, due to and/or predicted by greater early life stress, may contribute to the development of unhealthy alcohol use in adulthood.
Keyphrases
  • early life
  • alcohol use disorder
  • alcohol consumption
  • oxidative stress
  • mental health
  • healthcare
  • physical activity
  • climate change
  • deep learning
  • chronic pain
  • social media
  • trauma patients
  • data analysis