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Social and Proximate Determinants of the Frequency of Condom Use Among African, Caribbean, and Other Black People in a Canadian City: Results from the BLACCH Study

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Abstract

African, Caribbean, and other Black (ACB) people are a priority group for HIV prevention in Canada, but little is known about condom use in this population. This exploratory community-based research project addresses this gap in knowledge. 125 sexually active ACB people completed a questionnaire covering condom use and social determinants of health. The data were analyzed using ordinal logistic regression and mediation analyses. 20.5 % of sexually active ACB adults used condoms consistently. Male gender, wealth, unstable immigration classes, and unsecure employment statuses were independently associated with more frequent condom use. Proximate determinants mediating these relationships included: not having a cohabiting regular partner, not disliking condoms, and having a history of unwanted sex. The proximate determinants mediated 85.7–97.6 % of the effects of the social determinants. These results link social context and proximate factors with condom use. They can be used to design evidence-informed interventions for ACB people.

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References

  1. Statistics Canada Canada (table). National Household Survey (NHS) Profile. 2011 National Household Survey. [Internet]. Ottawa, Canada: Statistics Canada; 2011 [cited 13 Oct 2013]. http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/index.cfm?Lang=E.

  2. Public Health Agency of Canada. At a Glance—HIV and AIDS in Canada: surveillance report to 31 Dec 2011—Public Health Agency of Canada. Ottawa, Canada: Public Health Agency of Canada; 2012.

  3. Public Health Agency of Canada. Summary: estimates of HIV prevalence and incidence in Canada, 2011—Public Health Agency of Canada. Ottawa: Public Health Agency of Canada; 2012.

    Google Scholar 

  4. Public Health Agency of Canada. Population-specific HIV/AIDS status report: people from countries where HIV is endemic: Black people of African and Caribbean descent living in Canada. Ottawa, Canada: Surveillance and Risk Assessment Division, Centre for Infectious Disease Prevention and Control, Public Health Agency of Canada; 2009.

  5. Statistics Canada, London, Ontario (table). 2006 Community profiles. 2006 Census. [Internet]. Ottawa, Canada: Statistics Canada; 2007 [cited 16 Jan 2010]. http://www12.statcan.ca/census-recensement/2006/dp-pd/prof/92-591/index.cfm?Lang=E.

  6. Remis RS, Swantee C, Liu J. HIV/AIDS in Ontario: preliminary report, 2009. Toronto: Ontario HIV Epidemiologic Monitoring Unit; 2011.

    Google Scholar 

  7. Liu J, Remis RS. Race/ethnicity among persons with HIV/AIDS in Ontario, 1981–2004. Toronto: Ontario HIV Epidemiologic Monitoring Unit; 2007.

    Google Scholar 

  8. Feldblum PJ, Welsh MJ, Steiner MJ. Don’t overlook condoms for HIV prevention. Sex Transm Infect. 2003;79(4):268–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Weller S, Davis K. Condom effectiveness in reducing heterosexual HIV transmission. Cochrane Database Syst Rev. 2002;1:CD003255.

    PubMed  Google Scholar 

  10. Chatterjee N, Hosain GMM, Williams S. Condom use with steady and casual partners in inner city African-American communities. Sex Transm Infect. 2006;82(3):238–42.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Holmes L, Ogungbade GO, Ward DD, Garrison O, Peters RJ, Kalichman SC, et al. Potential markers of female condom use among inner city African-American Women. AIDS Care. 2008;20(4):470–7.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wingood GM, DiClemente RJ. Gender-related correlates and predictors of consistent condom use among young adult African-American women: a prospective analysis. Int J STD AIDS. 1998;9(3):139–45.

    Article  PubMed  CAS  Google Scholar 

  13. Essien EJ, Mgbere O, Monjok E, Ekong E, Abughosh S, Holstad MM. Predictors of frequency of condom use and attitudes among sexually active female military personnel in Nigeria. HIV/AIDS. 2010;2:77–88.

    PubMed  PubMed Central  Google Scholar 

  14. Richards JE, Risser JM, Padgett PM, Rehman HU, Wolverton ML, Arafat RR. Condom use among high-risk heterosexual women with concurrent sexual partnerships, Houston, Texas, USA. Int J STD AIDS. 2008;19(11):768–71.

    Article  PubMed  CAS  Google Scholar 

  15. Calzavara LM, Burchell AN, Myers T, Bullock SL, Escobar M, Cockerill R. Condom use among aboriginal people in Ontario, Canada. Int J STD AIDS. 1998;9(5):272–9.

    Article  PubMed  CAS  Google Scholar 

  16. Poundstone KE, Strathdee SA, Celentano DD. The social epidemiology of human immunodeficiency virus/acquired immunodeficiency syndrome. Epidemiol Rev. 2004;26(1):22–35.

    Article  PubMed  CAS  Google Scholar 

  17. World Health Organization Commission on Social Determinants of Health. A conceptual framework for action on the social determinants of health. World Health Organization; 2007. http://www.who.int/social_determinants/resources/csdh_framework_action_05_07.pdf.

  18. Mikkonen J, Raphael D. Social determinants of health: the Canadian facts. Toronto: York University School of Health Policy and Management; 2010. http://www.thecanadianfacts.org/.

  19. Boerma J, Weir SS. Integrating demographic and epidemiological approaches to research on HIV/AIDS: the proximate-determinants framework. J Infect Dis. 2005;191(Suppl 1):S61–7.

    Article  PubMed  Google Scholar 

  20. Hancock A-M. When multiplication doesn’t equal quick addition: examining intersectionality as a research paradigm. Perspect Polit. 2007;5(01):63–79.

    Article  Google Scholar 

  21. Bowleg L. The problem with the phrase women and minorities: intersectionality—an important theoretical framework for public health. Am J Public Health. 2012;102(7):1267–73.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Israel BA, Schulz AJ, Parker EA, Becker AB. Review of community-based research: assessing partnership approaches to improve public health. Annu Rev Publ Health. 1998;19(1):173–202.

    Article  CAS  Google Scholar 

  23. Baidoobonso S. An exploration of the relationships between markers of social status and position and HIV risk behaviours in African, Caribbean, and Other Black populations. London, Canada: The University of Western Ontario; 2013. http://ir.lib.uwo.ca/etd/1317.

  24. Statistics Canada. London, Ontario and Ontario (table). Census profile. 2011 Census. Ottawa, Canada: Statistics Canada; 2012. Report No.: Statistics Canada Catalogue no. 98-316-XWE.

  25. Baidoobonso S, Mokanan H, Meidinger L, Pugh D, Bauer G, Nleya-Ncube M, et al. Final report from the Black, African and Caribbean Canadian Health (BLACCH) Study. London, Canada: The University of Western Ontario; 2012. http://works.bepress.com/shamara_baidoobonso/.

  26. Dillman D. Mail and internet surveys: the tailored design method. 2nd ed. Hoboken, NJ: Wiley; 2007.

    Google Scholar 

  27. Statistics Canada. Income research paper series, Low income cut-offs for 2006 and low income measures for 2005 [Internet]. Statistics Canada; 2009. http://www12.statcan.ca/census-recensement/2006/ref/dict/tables/table-tableau-18-eng.cfm.

  28. Carey MP, Schroeder KEE. Development and psychometric evaluation of the brief HIV knowledge questionnaire (HIV-KQ-18). AIDS Educ Prev. 2002;14(2):174–84.

    Article  Google Scholar 

  29. SAS Institute Inc. Version 9.3 of the SAS System for Windows. Cary, NC, USA; 2011.

  30. Grau E, Potter F, Williams S, Diaz-Tena N. Nonresponse adjustment using logistic regression: to weight or not to weight? American Statistical Association, Survey Research Methods Section. Alexandria, VA: American Statistical Association; 2003.

    Google Scholar 

  31. Geneletti S, Richardson S, Best N. Adjusting for selection bias in retrospective, case–control studies. Biostatistics. 2009;10(1):17–31.

    Article  PubMed  Google Scholar 

  32. Hahs-Vaughn DL. A primer for using and understanding weights with national datasets. J Exp Educ. 2005;73(3):221–48.

    Article  Google Scholar 

  33. Harrell F Jr. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer; 2001.

    Book  Google Scholar 

  34. Iacobucci D. Mediation analysis and categorical variables: the final frontier. J Consum Psychol. 2012;22(4):582–94.

    Article  Google Scholar 

  35. Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–82.

    Article  PubMed  CAS  Google Scholar 

  36. Zhao X, Lynch JG Jr, Chen Q. Reconsidering Baron and Kenny: myths and truths about mediation analysis. J Consum Res. 2010;37(2):197–206.

    Article  Google Scholar 

  37. Gray K, Calzavara L, Tharao W. The East African health study in Toronto (EAST): results from a survey of HIV and health-related behavior, beliefs, attitudes, and knowledge. Toronto, Canada: University of Toronton; 2008. www.hivstudiesunit.ca.

  38. Adrien A, Cox J, Leclerc P, Boivin J-F, Archibald C, Boulos D, et al. Behavioural risks for HIV infection among Quebec residents of Haitian origin. J Immigr Minor Health. 2010;12(6):894–9.

    Article  PubMed  Google Scholar 

  39. Tourangeau R, Yan T. Sensitive questions in surveys. Psychol Bull. 2007;133(5):859–83.

    Article  PubMed  Google Scholar 

  40. Teixeira C. Barriers and outcomes in the housing searches of new immigrants and refugees: a case study of “Black” Africans in Toronto’s rental market. J Hous Built Environ. 2008;23(4):253–76.

    Article  Google Scholar 

  41. Creese G, Wiebe B. “Survival employment”: gender and deskilling among African immigrants in Canada. Int Migr. 2012;50(5):56–76.

    Article  Google Scholar 

  42. Nerad S, Janczur A. Primary health care with immigrant and refugee populations: issues and challenges. Aust J Prim Health. 2000;6(4):222–9.

    Article  Google Scholar 

  43. Gushulak BD, Pottie K, Roberts JH, Torres S, DesMeules M. Migration and health in Canada: health in the global village. CMAJ. 2011;183(12):E952–8.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Dhalla S, Poole G. Determinants of condom use: results of the Canadian community health survey 3.1. Can J Public Health. 2009;100(4):299–303.

    PubMed  Google Scholar 

  45. Hankivsky O, Christoffersen A. Intersectionality and the determinants of health: a Canadian perspective. Crit Public Health. 2008;18(3):271–83.

    Article  Google Scholar 

  46. Hankivsky O. Women’s health, men’s health, and gender and health: implications of intersectionality. Soc Sci Med. 2012;74(11):1712–20.

    Article  PubMed  Google Scholar 

  47. Villanueva L, Darrow W, Uribe C, Sánchez-Braña E, Obiaja K, Gladwin H. Ethnic differences in HIV risk perceptions and behaviors among Black 18–39 year-old residents of Broward County, Florida. AIDS Educ Prev. 2010;22(2):160–71.

    Article  PubMed  Google Scholar 

  48. Davidoff-Gore A, Luke N, Wawire S. Dimensions of poverty and inconsistent condom use among youth in urban Kenya. AIDS Care. 2011;23(10):1282–90.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Lewis JJC, Donnelly CA, Mare P, Mupambireyi Z, Garnett GP, Gregson S. Evaluating the proximate determinants framework for HIV infection in rural Zimbabwe. Sex Transm Infect. 2007;83(suppl 1):i61–9.

    Article  PubMed  Google Scholar 

  50. Newman PA, Williams CC, Massaquoi N, Brown M, Logie C. HIV prevention for Black women: structural barriers and opportunities. J Health Care Poor Underserved. 2008;19(3):829–41.

    Article  PubMed  Google Scholar 

  51. Baidoobonso S, Bauer GR, Speechley KN, Lawson E, The BLACCH Study Team. HIV risk perception and distribution of HIV risk among African, Caribbean and other Black people in a Canadian city: mixed methods results from the BLACCH study. BMC Public Health. 2013;13(1):184.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Noar S. Sexual partnerships, risk behaviors, and condom use among low-income heterosexual African Americans: a qualitative study. Arch Sex Behav. 2012;41(4):959–70.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Copas AJ, Johnson AM, Wadsworth J. Assessing participation bias in a sexual behaviour survey: implications for measuring HIV risk. AIDS. 1997;11(6):783–90.

    Article  PubMed  CAS  Google Scholar 

  54. Fox RJ. Mail survey response rate: a meta-analysis of selected techniques for inducing response. Public Opin Q. 1988;52(4):467–91.

    Article  Google Scholar 

  55. Hopkins K, Gullickson A. Response rates in survey research: a meta-analysis of the effects of monetary gratuities. J Exp Educ. 1992;61(1):52–62.

    Article  Google Scholar 

  56. Nemes S, Miao Jonasson J, Genell A, Steineck G. Bias in odds ratios by logistic regression modelling and sample size. BMC Med Res Methodol. 2009;9(56). http://www.biomedcentral.com/1471-2288/9/56.

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Acknowledgments

The authors would like to thank the Ontario HIV Treatment Network Community-Based Research Capacity-Building Fund and The University of Western Ontario for funding this project. Likewise, we would like to thank the Canadian Association for HIV Research, the Ontario Graduate Scholarship, and the Centre for REACH in HIV/AIDS for funding the lead author’s work on this project. This study was also supported by the BLACCH Study Team: Monica Abdelkader, Michael Antwi, Greta Bauer, Shamara Baidoobonso, Julius Ehiemua, Rob Haile, Sherin Hussien, Jan Jasnos, Sila Joshua, Erica Lawson, Roxanne Longman Marcellin, Leah Meidinger, Harina Mokanan, Mercy Nleya-Ncube and Daniel Pugh.

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Correspondence to Shamara Baidoobonso.

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Baidoobonso, S., Bauer, G.R., Speechley, K.N. et al. Social and Proximate Determinants of the Frequency of Condom Use Among African, Caribbean, and Other Black People in a Canadian City: Results from the BLACCH Study. J Immigrant Minority Health 18, 67–85 (2016). https://doi.org/10.1007/s10903-014-9984-z

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