Background: Alcohol use has been shown to accelerate disease progression in experimental studies of simian immunodeficiency virus in macaques, but the results in observational studies of HIV have been conflicting.
Methods: We conducted a prospective cohort study of the impact of unhealthy alcohol use on CD4 cell count among HIV-infected persons in southwestern Uganda not yet eligible for antiretroviral treatment (ART). Unhealthy alcohol consumption was 3-month Alcohol Use Disorders Identification Test-Consumption positive (≥3 for women, ≥4 for men) and/or phosphatidylethanol (PEth-an alcohol biomarker) ≥50 ng/mL, modeled as a time-dependent variable in a linear mixed effects model of CD4 count.
Results: At baseline, 43% of the 446 participants were drinking at unhealthy levels and the median CD4 cell count was 550 cells/mm (interquartile range 416-685). The estimated CD4 cell count decline per year was -14.5 cells/mm (95% confidence interval: -38.6 to 9.5) for unhealthy drinking vs. -24.0 cells/mm (95% confidence interval: -43.6 to -4.5) for refraining from unhealthy drinking, with no significant difference in decline by unhealthy alcohol use (P value 0.54), adjusting for age, sex, religion, time since HIV diagnosis, and HIV viral load. Additional analyses exploring alternative alcohol measures, participant subgroups, and time-dependent confounding yielded similar findings.
Conclusion: Unhealthy alcohol use had no apparent impact on the short-term rate of CD4 count decline among HIV-infected ART naive individuals in Uganda, using biological markers to augment self-report and examining disease progression before ART initiation to avoid unmeasured confounding because of misclassification of ART adherence.
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http://dx.doi.org/10.1097/QAI.0000000000001624 | DOI Listing |
BMC Public Health
January 2025
Public Health Research, DEFACTUM, Central Denmark Region, Aarhus, Denmark.
Background: Loneliness is a public health concern associated with increased morbidity and mortality. Adverse health behaviours and a higher body mass index (BMI) have been proposed as key mechanisms influencing this association. The present study aims to examine the relationship between loneliness, adverse health behaviour and a higher BMI, including daily smoking, high alcohol consumption, physical inactivity, unhealthy dietary habits, and obesity in men and women and across different life stages.
View Article and Find Full Text PDFAddict Sci Clin Pract
January 2025
Health Services Research & Development (HSR&D) Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs (VA) Puget Sound Health Care System, 1660 S. Columbian Way, Mail Stop S-152, Seattle, WA, 98108, USA.
Background: Unhealthy alcohol use is an independent, modifiable risk factor for HIV, but limited research addresses alcohol use and HIV prevention synergistically. Groups that experience chronic stigma, discrimination, and/or other marginalization, such as sexual and gender minoritized groups, may have enhanced HIV risk related to unhealthy alcohol use. We described awareness of and experiences with pre-exposure prophylaxis (PrEP) among a community sample of Veterans reporting unhealthy alcohol use (relative to those without), overall and across self-reported sexual orientation and gender identity.
View Article and Find Full Text PDFHealth Promot Int
January 2025
LLM Georgetown Law, Washington, DC, United States.
Noncommunicable diseases (NCDs) cause significant human and economic costs globally. Each year, 17 million people die from an NCD before age 70. The burden of NCDs is associated with socioenvironmental, cultural factors and social behavior, including modifiable risk factors like tobacco use, unhealthy diets, physical inactivity and alcohol consumption.
View Article and Find Full Text PDFChild Adolesc Psychiatry Ment Health
January 2025
Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
Purpose: To describe the trajectories of health-risk behaviors (HRBs) among college students through four consecutive surveys and explore the relationship between chronotype, sleep duration and different trajectories of HRBs.
Methods: We used a data sample of 1,042 college students from the College Student Behavior and Health Cohort Study. Students reported sleep parameters, including chronotype (Morningness-Eveningness Questionnaire-5, MEQ-5) and sleep duration.
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