RT Journal Article
SR Electronic
T1 Influence of the definition of rurality on geographic differences in HIV outcomes in British Columbia: a retrospective cohort analysis
JF CMAJ Open
JO CMAJ
FD Canadian Medical Association
SP E643
OP E650
DO 10.9778/cmajo.20200066
VO 8
IS 4
A1 Denise Jaworsky
A1 Mona Loutfy
A1 Michelle Lu
A1 Monica Ye
A1 Andreea Bratu
A1 Paul Sereda
A1 Ahmed Bayoumi
A1 Lisa Richardson
A1 Ayelet Kuper
A1 Robert S. Hogg
A1 ,
YR 2020
UL http://www.cmajopen.ca/content/8/4/E643.abstract
AB Background: Improving rural health is often identified as a priority area for research and policy in Canada. We examined how findings on HIV outcomes (virologic suppression) can vary depending on the definition of rurality used.Methods: We performed retrospective cohort analyses using the Comparative Outcomes and Service Utilization Trends study population-based cohort of adults (age ≥ 19 yr) living with HIV in British Columbia between Jan. 4, 2012, and Mar. 31, 2013. We performed univariate logistic regression analyses using the following geographic variables to predict HIV virologic suppression: rurality defined by forward sortation area, by Statistical Area Classification and by health authority. We mapped suppression using geographic information systems.Results: Virologic suppression was observed in 5605 (65.2%) of 8598 participants. In univariate analysis, rurality defined by Statistical Area Classification (odds ratio [OR] 0.73, 95% confidence interval [CI] 0.65–0.82), but not by forward sortation area, was associated with lower odds of suppression. When we examined suppression by health authority, Northern Health had the lowest odds of suppression (OR 0.46, 95% CI 0.36–0.58 compared to Vancouver Coastal Health). Geographic information systems mapping showed poorer suppression in northern areas.Interpretation: Health outcome findings can vary depending on the definition of the geographic variable. When including geographic variables, researchers should carefully consider variable definitions and whether other classification systems, such as north–south, are more appropriate than rurality for their analysis.