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Spatial Density of Gay Men In Metro Vancouver

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Spatial Density of Gay Men In Metro Vancouver

  1. 1. CAN GEOSOCIAL NETWORKING APPLICATIONS AID IN HEALTH SERVICE DELIVERY EFFORTS? KG. Card, J. Gibbs, NJ. Lachowksy, BW. Hawkins, M. Compton, J. Edward, D. Ho., T. Salway, M. Gislason, R. Hogg
  2. 2. 0.50 1.00 2.00 Recruited Online 14 Studies | Yang et al., 20141.35 (1.13-1.62) Sought Sex Online 15 Studies | Liau et al., 20061.68 (1.18-2.40) Online-Initiated Events 11 Studies | Lewnard et al., 20141.24 (1.01-1.52) Meta-Analytic Odds for CAS, by Online Sex Seeking
  3. 3. Fig 4. Increasing Prevalence of Online Sex Seeking 2.1% per year R² = 0.339 0 10 20 30 40 50 60 70 80 90 100 2000 2002 2004 2006 2008 2010 2012 2014 North America
  4. 4. Delaney et al. (2014) “Using a Geosocial Networking Application to Calculate the Population Density of Sex-Seeking Gay Men for Research and Prevention Services.” - Atlanta Sampled Locations Sampling Areas Relative User Density, By Race More Black Users More White Users
  5. 5. OBJECTIVES • Use a popular geosocial networking application to describe the spatial density of app-using gbMSM in Metro Vancouver. • Use 2016 Canadian Census data to identify factors associated with increasing app-user density.
  6. 6. >1 Mile App-User User 1 User 2 User 3 User 4 User 5 User 6 User 7 User 8 User 9 User 10 User 11 User 12 • Distance set to feet to maximize sampling radius. • Counted Number of users within <1-mile of sampling location. • No data collected from profiles and only record of counts was maintained.
  7. 7. Time & Day NumberofRadiiSampled
  8. 8. Explanatory Variables • Dissemination Area Characteristics • Male Population Density • Percent of population that is male. • Percent of male population that is not married. • Average age of males, in years from Census. • Median income of males, per $1000 CAD. • Percent of male income provided by government transfers. • Percent of males that are unemployed. • Percent of males that are immigrants to Canada. • Percent of males who identify as a visible minority. • Percent of males with a postsecondary education.
  9. 9. 𝑾 = 𝒙 ∗ 𝑷𝒊 𝑷 𝒕 ∗ 𝑨𝒊 𝑨 𝒕 𝒙 = Unweighted Census Value for a Given Dissemination Area. 𝑷𝒊 = The Population of the Given Census Dissemination Area 𝑷 𝒕 = The Total Population for all Census Dissemination Areas captured by the sampling radius. 𝑨𝒊 = The area of the Given Census Dissemination area captured by the sampling radius. 𝑨𝒕 = The total area of the sampling radius. Population-Area Weighted Value for a Given Sampling Radius (W) Prop. of Sampling Area in DA Proportion of Sampled Population in DA
  10. 10. User Density (Users/km2) Frequency(Count,byCensusDisseminationArea) Overdispersal p-value = 0.2804
  11. 11. App User Density = Population Density(1000*x) + Time*Day McFadden’s Pseudo-r2 0.64 β(se) 1.81 (0.02) P-value <.0001
  12. 12. Variable β SE Z-score P-value Male Population Density (per 1000) 1.494 0.025 16.351 <0.0001 % Receiving Government Transfers 0.799 0.024 -9.523 <0.0001 % of Males Not Married 1.139 0.010 12.457 <0.0001 % of Males who are Immigrants 1.068 0.012 5.290 <0.0001 % of Males who are Visible Minorities 0.977 0.006 -3.643 <0.0001 *Controlling for Interaction Between Time of Day and Day of Week McFadden’s Pseudo-r2: 0.75 Census-Level Factors Associated with App-User Density*
  13. 13. Implications • Understanding the spatial density of app users can potentially… • Ensure that existing services are appropriately tailored to gbMSM and those who seek sex online, • Advocate for the equitable distribution of health care services, • Empower community-based organizations to better deploy public service announcement and health service advertising within communities and municipalities. • Empower community- and municipal- health organizations to better leverage geosocial networking apps for the improvement of gbMSM health.
  14. 14. Limitations and Future Research Future research should: • Study the acceptability of data collection techniques that examine user characteristics and not just user counts. • Compare densities of using a variety of apps. • Explore how user densities vary over the course of the day and week. • Examine app-user densities in more rural regions and other cities. • Asses whether modifiable areal unites impact study estimates by comparing results across multiple geographic levels (e.g., census dissemination areas and other relevant administrative units, such as health service delivery areas).
  15. 15. Conclusions
  16. 16. Acknowledgements

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