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. 2024 Oct 29:5:100197.
doi: 10.1016/j.dialog.2024.100197. eCollection 2024 Dec.

The association of combinations of social factors and SARs-CoV-2 infection: A retrospective population-based cohort study in Ontario, 2020-2021

Sydney Persaud  1 , Michael Fitzgerald  1 , Steven Hawken  2   3   4 , Peter Tanuseputro  1   2   5 , Lisa Boucher  1 , William Petrcich  2 , Martin Wellman  2   3 , Colleen Webber  1   2   3 , Esther Shoemaker  1 , Robin Ducharme  3 , Simone Dahrouge  1   2   5 , Daniel Myran  1   2   3   5 , Ahmed M Bayoumi  6   7   8   9   10 , Susitha Wanigaratne  2   11 , Gary Bloch  12   13 , David Ponka  1   5 , Brendan T Smith  12   14 , Aisha Lofters  2   7   12   15 , Austin Zygmunt  5   14 , Krystal Kehoe MacLeod  1   3   5 , Luke A Turcotte  16 , Beate Sander  2   6   14   17 , Michelle Howard  18 , Sarah Funnell  19   20 , Jennifer Rayner  6   15   21 , Kurtis Kitagawa  1 , Sureya Ibrahim  22 , Claire E Kendall  1   2   4   5   7
Affiliations

The association of combinations of social factors and SARs-CoV-2 infection: A retrospective population-based cohort study in Ontario, 2020-2021

Sydney Persaud et al. Dialogues Health. .

Abstract

Objective: The COVID-19 pandemic highlighted and exacerbated health inequities worldwide. While several studies have examined the impact of individual social factors on COVID infection, our objective was to examine how interactions of social factors were associated with the risk of testing positive for SARS-CoV-2 during the first two years of the pandemic.

Study design and setting: We conducted an observational cohort study using linked health administrative data for Ontarians tested for SARS-CoV-2 between January 1st, 2020, and December 31st, 2021. We constructed multivariable models to examine the association between SARS-CoV-2 positivity and key variables including immigration status (immigrants vs. other Ontarians), and neighbourhood variables for household size, income, essential worker status, and visible minority status. We report main and interaction effects using odds ratios and predicted probabilities, with age and sex controlled in all models.

Results: Of 6,575,523 Ontarians in the cohort, 88.5 % tested negative, and 11.5 % tested positive for SARS-CoV-2. In all models, immigrants and those living in neighbourhoods with large average household sizes had greater odds of testing positive for SARS-CoV-2. The strength of these associations increased with increasing levels of neighbourhood marginalization for income, essential worker proportion and visible minority proportion. We observed little change in the probability of testing positive across neighbourhood income quintiles among other Ontarians who live in neighbourhoods with smaller households, but a large change in probability among other Ontarians who live in neighbourhoods with larger households.

Conclusion: Our study found that SARS-CoV-2 positivity was greater among people with certain combinations of social factors, but in all cases the probability of testing positive was consistently greater for immigrants than for other Ontarians. Examining interactions of social factors can provide a more nuanced and more comprehensive understanding of health inequity than examining factors separately.

Keywords: COVID-19 positivity; Health equity; SARS-CoV-2; Social determinants of health.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Claire E. Kendall reports financial support was provided by Canadian Institutes of Health Research. Dr. Bayoumi was supported by the 10.13039/100004702Baxter and Alma Ricard Chair in Inner City Health at Unity Health Toronto and the 10.13039/501100003579University of Toronto. Dr. Claire Kendall was supported by a Clinical Research Chair in Strengthening Primary Care for Integrated Health Equity and the 10.13039/100008572University of Ottawa. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Flow chart of inclusion and exclusion for cohort construction.
Fig. 2
Fig. 2
Forest plots of predicted probabilities and 95 % confidence intervals for three models for SARS-CoV-2 test positivity, presented from lowest to highest predicted probabilities compared to the reference group. All models adjusted for age and sex with baseline values of 40 years and female and all listed covariates. Exact predicted probability values and confidence intervals can be found in Supplemental Table 2. a. Income quintile model. b. Essential worker quintile model. c. Visible minority quintile.
Fig. 2
Fig. 2
Forest plots of predicted probabilities and 95 % confidence intervals for three models for SARS-CoV-2 test positivity, presented from lowest to highest predicted probabilities compared to the reference group. All models adjusted for age and sex with baseline values of 40 years and female and all listed covariates. Exact predicted probability values and confidence intervals can be found in Supplemental Table 2. a. Income quintile model. b. Essential worker quintile model. c. Visible minority quintile.
Fig. 3
Fig. 3
Scatter plot of predicted probability of SARS-CoV-2 infection for each of the three models (a. income quintile, b. essential worker quintile, c. visible minority quintile), including average neighbourhood household size and immigration status. All models adjusted for age and sex with baseline values of 40 years and female.
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