Abstract
A set of low-risk gambling limits were recently produced using Canadian epidemiological data on the intensity of gambling behavior and related consequences (Currie et al. Addiction 101:570–580, 2006). The empirically derived limits (gambling no more than two to three times per month, spending no more than $501–$100°CAN per year or no more than 1% of gross income spent on gambling) accurately predicted risk of gambling-related harm after controlling for other risk factors. The present study sought to replicate these limits on data collected in three independently conducted Canadian provincial gambling surveys. Dose–response curves and logistic regression analyses were applied to gambling prevalence data collected in surveys conducted in 2001–2002 within the provinces of Alberta, British Columbia, and Ontario (combined sample N = 7,675). A comparable dose–response relationship between gambling intensity and risk of harm was found in each province. The optimal thresholds for defining an upper limit of low-risk gambling were similar across the three provinces despite variations in the availability and organization of legalized gambling opportunities within each region. These results provide additional evidence supporting the validity of the low-risk gambling limits. Quantitative limits could be used to augment existing responsible gambling guidelines.
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Notes
The analysis of the CCHS-1.2 data included gambling-related interpersonal problems as an additional negative consequence. This item was included in the AB and ON surveys but not the BC survey.
Detailed results with lottery play excluded are available from the authors on request.
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Acknowledgments
This project is funded by grants from the Alberta Gaming Research Institute and Ontario Problem Gambling Research Centre (Grant# 2475). The authors wish to acknowledge the assistance of Anja Karvinen who helped in manuscript preparation.
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Currie, S.R., Hodgins, D.C., Wang, J. et al. Replication of Low-Risk Gambling Limits Using Canadian Provincial Gambling Prevalence Data. J Gambl Stud 24, 321–335 (2008). https://doi.org/10.1007/s10899-008-9091-y
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DOI: https://doi.org/10.1007/s10899-008-9091-y