Lisa Avery1,2, Raglan Maddox3,4, Robert Abtan5, Octavia Wong5, Nooshin Khobzi Rotondi3,6, Stephanie McConkey7,3, Cheryllee Bourgeois8,9, Constance McKnight10, Sara Wolfe8, Sarah Flicker5, Alison Macpherson5, Janet Smylie7,3, Michael Rotondi5. 1. Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. lisa.avery@uhnresearch.ca. 2. Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. lisa.avery@uhnresearch.ca. 3. Well Living House, Li Ka Shing Knowledge Institute, Unity Health Toronto - St. Michaels Hospital, Toronto, ON, Canada. 4. Aboriginal and Torres Strait Islander Health Group, National Centre for Epidemiology and Public Health, Research School of Population Health, The Australian National University, Canberra, Australia. 5. School of Kinesiology and Health Science, York University, Toronto, ON, Canada. 6. Ontario Tech University, Oshawa, ON, Canada. 7. Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. 8. Seventh Generation Midwives Toronto, Toronto, ON, Canada. 9. Metropolitan University, Toronto, ON, Canada. 10. De dwa da dehs nye>s Aboriginal Health Centre, Brantford, ON, Canada.
Abstract
OBJECTIVE: Studies have highlighted the inequities between the Indigenous and non-Indigenous populations with respect to the burden of cardiovascular disease and prevalence of predisposing risks resulting from historical and ongoing impacts of colonization. The objective of this study was to investigate factors associated with cardiovascular disease (CVD) within and specific to the Indigenous peoples living in Toronto, Ontario, and to evaluate the reliability and validity of the resulting model in a similar population. METHODS: The Our Health Counts Toronto study measured the baseline health of Indigenous community members living in Toronto, Canada, using respondent-driven sampling. An iterative approach, valuing information from the literature, clinical insight and Indigenous lived experiences, as well as statistical measures was used to evaluate candidate predictors of CVD (self-reported experience of discrimination, ethnic identity, health conditions, income, education, age, gender and body size) prior to multivariable modelling. The resulting model was then validated using a distinct, geographically similar sample of Indigenous people living in Hamilton, Ontario, Canada. RESULTS: The multivariable model of risk factors associated with prevalent CVD included age, diabetes, hypertension, body mass index and exposure to discrimination. The combined presence of diabetes and hypertension was associated with a greater risk of CVD relative to those with either condition and was the strongest predictor of CVD. Those who reported previous experiences of discrimination were also more likely to have CVD. Further study is needed to determine the effect of body size on risk of CVD in the urban Indigenous population. The final model had good discriminative ability and adequate calibration when applied to the Hamilton sample. CONCLUSION: Our modelling identified hypertension, diabetes and exposure to discrimination as factors associated with cardiovascular disease. Discrimination is a modifiable exposure that must be addressed to improve cardiovascular health among Indigenous populations.
OBJECTIVE: Studies have highlighted the inequities between the Indigenous and non-Indigenous populations with respect to the burden of cardiovascular disease and prevalence of predisposing risks resulting from historical and ongoing impacts of colonization. The objective of this study was to investigate factors associated with cardiovascular disease (CVD) within and specific to the Indigenous peoples living in Toronto, Ontario, and to evaluate the reliability and validity of the resulting model in a similar population. METHODS: The Our Health Counts Toronto study measured the baseline health of Indigenous community members living in Toronto, Canada, using respondent-driven sampling. An iterative approach, valuing information from the literature, clinical insight and Indigenous lived experiences, as well as statistical measures was used to evaluate candidate predictors of CVD (self-reported experience of discrimination, ethnic identity, health conditions, income, education, age, gender and body size) prior to multivariable modelling. The resulting model was then validated using a distinct, geographically similar sample of Indigenous people living in Hamilton, Ontario, Canada. RESULTS: The multivariable model of risk factors associated with prevalent CVD included age, diabetes, hypertension, body mass index and exposure to discrimination. The combined presence of diabetes and hypertension was associated with a greater risk of CVD relative to those with either condition and was the strongest predictor of CVD. Those who reported previous experiences of discrimination were also more likely to have CVD. Further study is needed to determine the effect of body size on risk of CVD in the urban Indigenous population. The final model had good discriminative ability and adequate calibration when applied to the Hamilton sample. CONCLUSION: Our modelling identified hypertension, diabetes and exposure to discrimination as factors associated with cardiovascular disease. Discrimination is a modifiable exposure that must be addressed to improve cardiovascular health among Indigenous populations.
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