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Comparing Sexual Network Mean Active Degree Measurement Metrics Among Men Who Have Sex With Men
Christina Chandra1, Martina Morris2, Connor Van Meter1
1From the Department of Epidemiology, Rollin School of Public Health, Emory University, Atlanta, GA.
Background:
Mean active degree is an important proxy measure of cross-sectional network connectivity commonly used in HIV/sexually transmitted infection epidemiology research. No current studies have compared measurement methods of mean degree using a cross-sectional study design for men who have sex with men (MSM) in the United States. We compared mean degree estimates based on reported ongoing main and casual sexual partnerships (current method) against dates of first and last sex (retrospective method).
Methods:
We used data from ARTnet, a cross-sectional survey of MSM in the United States (2017-2019). ARTnet collected data on the number and types of sexual partners in the past year, limited to the 5 most recent partners (data truncation). We quantified partnerships for months 0 to 12 before the survey date (retrospective method) and compared that with ongoing partnerships on the day of survey (current method). We used linear regression to understand the impact of truncated partnership data on mean degree estimation.
Results:
The retrospective method yielded similar degree estimates to the current for months proximate to the day of survey. The retrospective method mean degree systematically decreased as the month increased from 0 to 12 months before survey date. This was driven by data truncation: among participants with >5 partners in the past year compared with those with ≤5, the average change in main partnership degree between 12 and 0 months before survey date was -0.05 (95% confidence interval, -0.08 to -0.03) after adjusting for race/ethnicity, age, and education. The adjusted average change in casual partnership degree was -0.40 (95% confidence interval, -0.45 to -0.35).
Conclusions:
The retrospective method underestimates mean degree for MSM in surveys with truncated partnership data, especially for casual partnerships. The current method is less prone to bias from partner truncation when the target population has high rate of partners per year.
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