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Association between pre-existing chronic conditions and severity of first SARS-CoV-2 infection symptoms among adults living in Canada: a population-based survey analysis from January 2020 to August 2022. | LitMetric

Association between pre-existing chronic conditions and severity of first SARS-CoV-2 infection symptoms among adults living in Canada: a population-based survey analysis from January 2020 to August 2022.

BMC Public Health

Lifespan Chronic Diseases and Conditions Division (LCDC), Centre for Surveillance and Applied Research (CSAR), Health Promotion and Chronic Disease Prevention Branch (HPCDP), Public Health Agency of Canada (PHAC), Ottawa, ON, Canada.

Published: March 2025

Background: Individuals living with chronic conditions (CC) typically have a higher risk of more severe outcomes when exposed to infection. Although many studies have investigated the relationship between CCs and COVID-19 severity, they are generally limited to clinical or hospitalized populations. There is a need to estimate the impact of pre-existing CCs on the severity of acute SARS-CoV-2 infection symptoms among the general population.

Methods: Data from the Canadian COVID-19 Antibody and Health Survey - Cycle 2, a population-based cross-sectional probability survey across 10 provinces capturing the COVID-19 experiences of respondents from January 2020 to August 2022, were used to assess whether pre-existing CCs increased the odds of more severe self-reported infection symptoms among adults living in Canada. Multivariable regression modelling identified which CCs were independently associated with more severe infection symptoms after adjusting for sex, age at infection, and other significant covariates.

Results: Chronic lung disease (aOR = 1.64, 95% CI: 1.09, 2.46), high blood pressure (aOR = 1.35, 95% CI: 1.13, 1.62), weakened immune system (aOR = 1.46, 95% CI: 1.08, 1.98), chronic fatigue syndrome or fibromyalgia (aOR = 2.20, 95% CI: 1.39, 3.50), and arthritis (aOR = 1.28, 95% CI: 1.04, 1.56) were associated with a higher odds of more severe infection, whereas osteoporosis (aOR = 0.58, 95% CI: 0.39, 0.87) was associated with a lower odds. Limiting modelling to adults with confirmed SARS-CoV-2 infections affected some of the variables retained and adjusted associations.

Conclusion: Our findings contribute to a growing evidence base of associations between pre-existing CCs and adverse outcomes after SARS-CoV-2 infection. Identifying factors associated with more severe infection allows for more targeted prevention strategies and early interventions that can minimize the impact of infection.

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Source
http://dx.doi.org/10.1186/s12889-025-22041-7DOI Listing

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