Background: Unhealthy alcohol use (UAU) is known to disrupt pulmonary immune mechanisms and increase the risk of acute respiratory distress syndrome in patients with pneumonia; however, little is known about the effects of UAU on outcomes in patients with COVID-19 pneumonia. To our knowledge, this is the first observational cross-sectional study that aims to understand the effect of UAU on the severity of COVID-19.

Objective: We aim to determine if UAU is associated with more severe clinical presentation and worse health outcomes related to COVID-19 and if socioeconomic status, smoking, age, BMI, race/ethnicity, and pattern of alcohol use modify the risk.

Methods: In this observational cross-sectional study that took place between January 1, 2020, and December 31, 2020, we ran a digital machine learning classifier on the electronic health record of patients who tested positive for SARS-CoV-2 via nasopharyngeal swab or had two COVID-19 International Classification of Disease, 10th Revision (ICD-10) codes to identify patients with UAU. After controlling for age, sex, ethnicity, BMI, smoking status, insurance status, and presence of ICD-10 codes for cancer, cardiovascular disease, and diabetes, we then performed a multivariable regression to examine the relationship between UAU and COVID-19 severity as measured by hospital care level (ie, emergency department admission, emergency department admission with ventilator, or death). We used a predefined cutoff with optimal sensitivity and specificity on the digital classifier to compare disease severity in patients with and without UAU. Models were adjusted for age, sex, race/ethnicity, BMI, smoking status, and insurance status.

Results: Each incremental increase in the predicted probability from the digital alcohol classifier was associated with a greater odds risk for more severe COVID-19 disease (odds ratio 1.15, 95% CI 1.10-1.20). We found that patients in the unhealthy alcohol group had a greater odds risk to develop more severe disease (odds ratio 1.89, 95% CI 1.17-3.06), suggesting that UAU was associated with an 89% increase in the odds of being in a higher severity category.

Conclusions: In patients infected with SARS-CoV-2, UAU is an independent risk factor associated with greater disease severity and/or death.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575002PMC
http://dx.doi.org/10.2196/33022DOI Listing

Publication Analysis

Top Keywords

unhealthy alcohol
12
disease severity
12
observational cross-sectional
12
cross-sectional study
12
uau
9
independent risk
8
risk factor
8
covid-19 disease
8
uau associated
8
icd-10 codes
8

Similar Publications

Objectives: This study aims to estimate the impact of the co-occurrence of behavioural risk factors on mortality in the Spanish adult population.

Design: Population-based cohort study based on data from the 2011-2012 Spanish National Health Survey and the 2014 European Health Survey (n=35 053 participants ≥15 years of age) both linked to mortality data as of December 2022. Risk factors included tobacco use, high-risk alcohol consumption, low adherence to the Mediterranean diet, leisure time sedentary lifestyle and body mass index outside the 18.

View Article and Find Full Text PDF

Regional Variations in the Prevalence of Risk Factors and Non-Communicable Diseases in Papua New Guinea: A Scoping Review.

Int J Environ Res Public Health

January 2025

Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia.

Often referred to as 'the last unknown', Papua New Guinea's largely unexplored environments across its four distinct regions, the Highlands, New Guinea Islands, Momase, and Southern, exhibit remarkable diversity. Understanding this diversity is significant in contextualising the risk factors associated with developing non-communicable diseases. This review aims to map and summarise the literature to provide region-specific prevalence data for risk factors and non-communicable diseases.

View Article and Find Full Text PDF

Drinking is a common unhealthy behaviour among youth smokers aged 25 or below. However, the effects of drinking on smoking cessation outcomes are not well understood. This study aimed to explore the impact of drinking on smoking cessation outcomes among Hong Kong Chinese youth smokers who received smoking cessation counselling.

View Article and Find Full Text PDF

AI-generated cancer prevention influencers can target risk groups on social media at low cost.

Eur J Cancer

January 2025

Division of Digital Prevention, Diagnostics and Therapy Guidance, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address:

Background: This study explores the potential of Artificial Intelligence (AI)-generated social media influencers to disseminate cancer prevention messages. Utilizing a Generative AI (GenAI) application, we created a virtual persona, "Wanda", to promote cancer awareness on Instagram.

Methods: We created five posts, addressing the five most modifiable risk factors for cancer: tobacco consumption, unhealthy diet, sun exposure, alcohol consumption, and Human Papillomavirus (HPV) infection.

View Article and Find Full Text PDF

Background: It is estimated that 61% of deaths caused by Cardiovascular Diseases (CVDs) globally are attributed to lifestyle-related risk factors including tobacco use, alcohol abuse, poor diet, and inadequate physical activity. Meanwhile, inadequate knowledge and misperceptions about CVDs are disproportionately increasing the prevalence of CVDs in Africa. Moreover, pre-diagnosis awareness/knowledge about CVDs among patients is essential in shaping the extent and scope of education to be provided by healthcare workers.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!