Veronica L Richards1, Ruba Sajdeya1, Karina Villalba2, Yan Wang1, Vaughn Bryant1, Babette Brumback3, Kendall Bryant4, Judith A Hahn5, Robert L Cook1. 1. From the, Department of Epidemiology, (VLR, RS, YW, VB, RLC), University of Florida, Gainesville, Florida. 2. Robert Stempel College of Public Health and Social Work, (KV), Florida International University, Miami, Florida. 3. Department of Biostatistics, (BB), University of Florida, Gainesville, Florida. 4. National Institute on Alcohol Abuse and Alcoholism, (KB), Bethesda, Maryland. 5. Department of Medicine, (JAH), University of California, San Francisco, California.
Abstract
BACKGROUND: Direct biomarkers such as phosphatidylethanol (PEth) have the capability to detect heavy alcohol use, but it is unclear how strongly self-reported reduction in alcohol use correlates with reduction in PEth. We sought to explore the strength of correlation between reductions in self-reported alcohol use and change in PEth among a sample of women living with HIV (WLWH) who participated in a clinical trial to reduce heavy alcohol use. We also sought to determine whether this correlation was stronger in women with lower body mass index (BMI) and women without an alcohol use disorder (AUD). METHODS: 81 WLWH (mean age = 48.7, 80% Black) engaging in a randomized trial of naltrexone versus placebo with a positive baseline PEth (≥8 ng/ml), and alcohol use data at baseline, 2, and 7 months were included in this analysis. Spearman correlation coefficients were compared to measure the correlation between baseline PEth and number of drinks per week by demographic, biological, and alcohol use factors. Mini-International Neuropsychiatric Interview was used to screen for AUD. Further analyses were stratified by BMI and AUD. Spearman correlation coefficients were calculated for the change in PEth and the change in number of drinks per week over 7 months, including 3 time-points: baseline, 2, and 7 months. RESULTS: At baseline, the correlation between baseline PEth and the number of drinks per week was significantly stronger for those with a BMI ≤25 compared to those with a BMI > 25 (r = 0.66; r = 0.26, respectively). Similarly, the correlation between baseline PEth and number of drinks was stronger for those who did not screen positive for AUD compared with those who did (r = 0.66; r = 0.25, respectively). When stratifying by BMI, a low-to-moderate correlation (r = 0.32, p = 0.02) was present for persons with a BMI > 25; when stratifying by AUD, a moderate correlation (r = 0.50, p < 0.01) was present for persons without an AUD between 0 and 2 months only. CONCLUSIONS: In this sample of WLWH, BMI and AUD affected the strength of correlation between PEth and drinks per week. Future work examining changes in PEth over time in broader populations is needed, particularly to understand the sex differences in PEth levels.
BACKGROUND: Direct biomarkers such as phosphatidylethanol (PEth) have the capability to detect heavy alcohol use, but it is unclear how strongly self-reported reduction in alcohol use correlates with reduction in PEth. We sought to explore the strength of correlation between reductions in self-reported alcohol use and change in PEth among a sample of women living with HIV (WLWH) who participated in a clinical trial to reduce heavy alcohol use. We also sought to determine whether this correlation was stronger in women with lower body mass index (BMI) and women without an alcohol use disorder (AUD). METHODS: 81 WLWH (mean age = 48.7, 80% Black) engaging in a randomized trial of naltrexone versus placebo with a positive baseline PEth (≥8 ng/ml), and alcohol use data at baseline, 2, and 7 months were included in this analysis. Spearman correlation coefficients were compared to measure the correlation between baseline PEth and number of drinks per week by demographic, biological, and alcohol use factors. Mini-International Neuropsychiatric Interview was used to screen for AUD. Further analyses were stratified by BMI and AUD. Spearman correlation coefficients were calculated for the change in PEth and the change in number of drinks per week over 7 months, including 3 time-points: baseline, 2, and 7 months. RESULTS: At baseline, the correlation between baseline PEth and the number of drinks per week was significantly stronger for those with a BMI ≤25 compared to those with a BMI > 25 (r = 0.66; r = 0.26, respectively). Similarly, the correlation between baseline PEth and number of drinks was stronger for those who did not screen positive for AUD compared with those who did (r = 0.66; r = 0.25, respectively). When stratifying by BMI, a low-to-moderate correlation (r = 0.32, p = 0.02) was present for persons with a BMI > 25; when stratifying by AUD, a moderate correlation (r = 0.50, p < 0.01) was present for persons without an AUD between 0 and 2 months only. CONCLUSIONS: In this sample of WLWH, BMI and AUD affected the strength of correlation between PEth and drinks per week. Future work examining changes in PEth over time in broader populations is needed, particularly to understand the sex differences in PEth levels.
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