BMJ Open
Volume 7, Issue 12, 2017

Our Health Counts Toronto: Using respondent-driven sampling to unmask census undercounts of an urban indigenous population in Toronto, Canada (Article) (Open Access)

Rotondi M.A.* , O'Campo P. , O'Brien K. , Firestone M. , Wolfe S.H. , Bourgeois C. , Smylie J.K.
  • a School of Kinesiology and Health Science, York University, Toronto, ON, Canada
  • b Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
  • c Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
  • d Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
  • e Seventh Generation Midwives Toronto, Toronto, ON, Canada
  • f Seventh Generation Midwives Toronto, Toronto, ON, Canada
  • g Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

Abstract

Objectives: To provide evidence of the magnitude of census undercounts of 'hard-to-reach' subpopulations and to improve estimation of the size of the urban indigenous population in Toronto, Canada, using respondent-driven sampling (RDS). Design: Respondent-driven sampling. Setting: The study took place in the urban indigenous community in Toronto, Canada. Three locations within the city were used to recruit study participants. Participants: 908 adult participants (15+) who self-identified as indigenous (First Nation, Inuit or Métis) and lived in the city of Toronto. Study participants were generally young with over 60% of indigenous adults under the age of 45 years. Household income was low with approximately two-thirds of the sample living in households which earned less than $C20 000 last year. Primary and secondary outcome measures We collected baseline data on demographic characteristics, including indigenous identity, age, gender, income, household type and household size. Our primary outcome asked: 'Did you complete the 2011 Census Canada questionnaire?' Results Using RDS and our large-scale survey of the urban indigenous population in Toronto, Canada, we have shown that the most recent Canadian census underestimated the size of the indigenous population in Toronto by a factor of 2 to 4. Specifically, under conservative assumptions, there are approximately 55 000 (95% CI 45 000 to 73 000) indigenous people living in Toronto, at least double the current estimate of 19 270. Conclusions: Our indigenous enumeration methods, including RDS and census completion information will have broad impacts across governmental and health policy, potentially improving healthcare access for this community. These novel applications of RDS may be relevant for the enumeration of other 'hard-to-reach' populations, such as illegal immigrants or homeless individuals in Canada and beyond. © 2017 Article author(s). All rights reserved.

Author Keywords

marginalized populations Indigenous population estimation of population size Community-based research Respondent-driven sampling census undercount

Index Keywords

urban population health care policy sampling homeless person Sampling Studies human epidemiology middle aged population group statistics and numerical data Population Groups Aged Surveys and Questionnaires Young Adult population size undocumented immigrant Humans Adolescent male Canada female Cities questionnaire population research identity Article city major clinical study household income gender human experiment adult health care access Inuit First Nation Censuses outcome assessment
Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051309262&doi=10.1136%2fbmjopen-2017-018936&partnerID=40&md5=dcf1f9ec9558e97be19cc854d943d471
DOI: 10.1136/bmjopen-2017-018936
ISSN: 20446055
Cited by: 6
Original Language: English