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Differential risks of syringe service program participants in Central Ohio: a latent class analysis. | LitMetric

Differential risks of syringe service program participants in Central Ohio: a latent class analysis.

Harm Reduct J

Center for Health Outcomes and Policy Evaluation Studies (HOPES), The Ohio State University College of Public Health, 381 Cunz Hall, 1841 Neil Avenue, Columbus, OH, 43210, USA.

Published: July 2023


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Article Abstract

Background: Significant heterogeneity exists among people who use drugs (PWUD). We identify distinct profiles of syringe service program (SSP) clients to (a) evaluate differential risk factors across subgroups and (b) inform harm reduction programming.

Methods: Latent class analysis (LCA) was applied to identify subgroups of participants (N = 3418) in a SSP in Columbus, Ohio, from 2019 to 2021. Demographics (age, sex, race/ethnicity, sexual orientation, housing status) and drug use characteristics (substance[s] used, syringe gauge, needle length, using alone, mixing drugs, sharing supplies, reducing use, self-reported perceptions on the impact of use, and treatment/support resources) were used as indicators to define latent classes. A five-class LCA model was developed, and logistic regression was then employed to compare risk factors at program initiation and at follow-up visits between latent classes.

Results: Five latent classes were identified: (1) heterosexual males using opioids/stimulants with housing instability and limited resources for treatment/support (16.1%), (2) heterosexual individuals using opioids with stable housing and resources for treatment/support (33.1%), (3) individuals using methamphetamine (12.4%), (4) young white individuals using opioids/methamphetamine (20.5%), and (5) females using opioids/cocaine (17.9%). Class 2 served as the reference group for logistic regression models, and at the time of entry, class 1 was more likely to report history of substance use treatment, overdose, HCV, sharing supplies, and mixing drugs, with persistently higher odds of sharing supplies and mixing drugs at follow-up. Class 3 was more likely to report history of overdose, sharing supplies, and mixing drugs, but outcomes at follow-up were comparable. Class 4 was the least likely to report history of overdose, HCV, and mixing drugs, but the most likely to report HIV. Class 5 was more likely to report history of substance use treatment, overdose, HCV, sharing supplies, and mixing drugs at entry, and higher reports of accessing substance use treatment and testing positive for HCV persisted at follow-up.

Conclusions: Considerable heterogeneity exists among PWUD, leading to differential risk factors that may persist throughout engagement in harm reduction services. LCA can identify distinct profiles of PWUD accessing services to tailor interventions that address risks, improve outcomes, and mitigate disparities.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10386257PMC
http://dx.doi.org/10.1186/s12954-023-00824-8DOI Listing

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