Factors associated with drug checking service utilization among people who use drugs in a Canadian setting.

BACKGROUND: The United States and Canada are amidst an opioid overdose crisis, with the Canadian province of British Columbia (BC) among the hardest hit. In response, drug checking services (DCS) have been introduced in this setting as a novel pilot harm reduction intervention though little is known about usage rates. Therefore, we sought to identify factors associated with drug checking uptake among people who use drugs (PWUD) in Vancouver, BC. METHODS: Data were derived from three ongoing prospective cohort studies of PWUD in Vancouver between June and November 2018. Multivariable logistic regression was used to determine factors associated with self-reported DCS utilization in the past 6 months among participants at high risk of fentanyl exposure (i.e., those self-reporting illicit opioid use or testing positive for fentanyl via urine drug screen). RESULTS: Among 828 eligible participants, including 451 (55%) males, 176 (21%) reported recent use of DCS. In multivariable analyses, factors significantly associated with DCS utilization included: homelessness (Adjusted Odds Ratio [AOR] 1.47; 95% Confidence Interval [CI] 1.01-2.13) and involvement in drug dealing (AOR 1.59; 95% CI 1.05-2.39). CONCLUSIONS: In our sample of PWUD, uptake of DCS was low, although those who were homeless, a sub-population known to be at a heightened risk of overdose, were more likely to use the services. Those involved in drug dealing were also more likely to use the services, which may imply potential for improving drug market safety. Further evaluation of drug checking is warranted.

Testing Bioimpedance to Estimate Body Fat Percentage across Different Hip and Waist Circumferences.

Many studies have validated the use of bioimpedance analysis (BIA) to quantify body fat percentage (BF%). However, it is unknown if some model types (i.e., hand to hand, foot to foot, and hand to foot) are differing in their validity depending on hip and waist circumferences. The purpose of this study was to compare the difference in BF% between three BIA models (i.e., hand to hand, foot to foot, and hand to foot) against the Bod Pod across different hip and waist circumferences. A total of 92 people aged 19-72 years were recruited in this study. After following the pretesting procedures recommended for BIA measures, BF% was estimated using three BIA models and the Bod Pod. Hip and waist circumferences were obtained using standard procedures and tertiles were computed. The Bland-Altman was plotted and 1-sample T-test as well as correlation between the average measure and the difference between the two measures was tested. Within the entire sample, across all BIA models, the Bland-Altman analysis showed significant difference compared to 0 and a significant difference for the proportional. However, when stratified by tertiles, the two measurements were only significant for the highest tertiles of hip and waist for all BIA apparatus (all p <0.01) and the proportional bias was nonsignificant for all tertiles and across all BIA apparatus. For the highest tertile of waist and hip, the average difference was between 1.67% and 3.29% compared with the Bod Pod estimation. In conclusion, the three BIA models offer a BF% measurement agreeing with the estimation obtained with the Bod Pod with the exception of people having a greater waist or greater hip.