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

TL;DR

This study explores how pre-existing chronic conditions in Canadian adults affect the severity of their first SARS-CoV-2 infection symptoms.

Contribution

It provides population-based evidence linking specific chronic conditions to increased odds of severe symptoms from SARS-CoV-2.

Findings

Chronic lung disease, high blood pressure, weakened immune system, chronic fatigue syndrome/fibromyalgia, and arthritis increased odds of severe symptoms.

Osteoporosis was associated with lower odds of severe symptoms.

Confirmed SARS-CoV-2 infection status influenced some associations in the analysis.

Abstract

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.

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.

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.

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.

Full text

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global pandemic on March 11, 2020 by the World Health Organization and by March 2023, it was conservatively estimated that around 76% of the Canadian population had been infected [1, 2]. Since the beginning of the outbreak, the daily lives of people have been affected by societal, economic, and public health preventive measures such as use of face masks, physical distancing, quarantines, and lockdowns [3–5].

In addition to the indirect effects of the pandemic, SARS-CoV-2’s acute effect varies widely with respect to the types and severity of symptoms experienced [6]. Among adults in Canada, the most reported acute symptoms are fatigue, fever, coughing, and sore throat, but their severity and impact on daily life is less clear [7]. Those living with chronic conditions (CC) are at a higher risk of more severe outcomes from infectious diseases in general, and the research is growing for SARS-CoV-2 infections specifically [8]. Multiple studies have shown that pre-existing cardiovascular disease (CVD) [9–11], diabetes [12–14], mental illness [15, 16], neurological disease [17–19], musculoskeletal disease [20], and other CCs [21–23] are associated with worse COVID-19 outcomes. Conversely, those with pre-existing respiratory diseases [24–26], fibromyalgia [27], and bowel disease (BD) [28] do not seem to be at increased risk of a more severe infection. However, most studies have only evaluated severe outcomes, like death, in clinical or hospitalized populations, leaving a knowledge gap about the relationship in the general population that experience a SARS-CoV-2 infection without seeking healthcare services. Identifying which chronic conditions put community dwelling adults at increased risk of more severe infections assists in identifying priority populations for targeted prevention strategies (e.g., masking, vaccinations) and early post-infection interventions (e.g., pharmaceuticals).

In addition, existing studies examining the association between pre-existing CCs and severity of a SARS-CoV-2 infection often fail to account for the temporality of important variables. They often are unable to distinguish whether participants had a SARS-CoV-2 infection before or after their CC diagnosis. Additionally, factors such as number of COVID-19 vaccine doses received prior to infection, time since last vaccination prior to infection, and the dominant variant at time of infection are often not considered despite their potential to greatly influence the relationship between pre-existing CCs and the severity of COVID-19.

Cycle 2 of the population-based Canadian COVID-19 Antibody and Health Survey (CCAHS-2) provides a unique opportunity to assess the impact of a SARS-CoV-2 infection on individuals with pre-existing CCs, including those with suspected infections, while accounting for the temporality of key confounders. Using date information provided by the respondents for their vaccines, first SARS-CoV-2 infection, and CC diagnoses, we are able to appropriately sequence events in time and more accurately measure the effect of pre-existing CCs, vaccination status, and dominant variant on severity of SARS-CoV-2 infections. Although other large scale COVID-19 surveys are available, we are unaware of any studies that utilize these data to explore this specific relationship [29–31]. Using CCAHS-2, we aimed to identify pre-existing CCs associated with more severe acute first SARS-CoV-2 infection symptoms in the Canadian adult population self-reporting a confirmed or suspected infection by August 2022.

Methods

Study sample and participants

CCAHS-2, a population-based cross-sectional probability survey, was conducted to characterize and estimate the burden of COVID-19 among adults (aged 18 years and older) living in private households across Canada’s 10 provinces. Self-reported information was collected from April to August 2022 using an electronic questionnaire (EQ) specifically developed for the CCAHS-2 through a collaboration between the Public Health Agency of Canada, Statistics Canada, and the COVID-19 Immunity Task Force. Of the 105,998 adults invited to participate, 32,527 (30.7%) completed at least part of the EQ, and 26,859 (25.3%) agreed to share their data with the Public Health Agency of Canada. The response rate for the data used in this study (25.3%) is better than other COVID-19-related national surveys [29–31]. Statistics Canada conducted data validation during and after data collection by comparing both the collected and derived data to comparable Canadian and international data sources to ensure consistency. To mitigate non-response bias, Statistics Canada used characteristics available for both respondents and non-respondents in logistic regression models to identify variables which explained most of the non-response. Variables highly correlated with response or non-response included age group, education, income, census metropolitan area (CMA)/non-CMA, dwelling type, and household size. Based on the modeling results, homogeneous response groups were created and non-response adjustments were applied within these groups to adjust the survey weights. The application of these adjusted weights during analyses helps to minimize non-response bias by accounting for identified differences between respondents and non-respondents. More details about the survey design and the full questionnaire are available on the Statistics Canada website [32].

We restricted our analyses to participants that self-reported a confirmed or suspected SARS-CoV-2 infection. By including suspected SARS-CoV-2 infection cases, we were able to account for the population who did not have access to testing or chose not to be tested. A sensitivity analysis was conducted using only participants that self-reported a confirmed SARS-CoV-2 infection.

Severity of infection

Our outcome of interest, severity of first infection, was captured as follows: no symptoms; mild symptoms – didn’t affect my daily life; moderate symptoms – some effect on my daily life; and severe symptoms – significant effect on my daily life. Using additional information on hospitalization due to symptoms, a trichotomous severity of infection variable was derived (no or mild symptoms, moderate symptoms, severe symptoms or hospitalized) and used as our primary outcome of interest. Respondents who were hospitalized were placed in the highest severity category regardless of their self-reported infection severity. To our knowledge, no validated self-report tool currently exists to measure the severity of SARS-CoV-2 infection symptoms. However, similar four-point scales have been used in other studies assessing COVID-19 symptom severity [33, 34].

Chronic conditions

Our primary explanatory variables of interest were pre-existing CCs. Participants were asked about 21 different CCs and their dates of diagnosis (year and month if the diagnosis was in 2020 onward and only the year if it was before 2020). CCs were defined as conditions lasting or expected to last at least six months that were diagnosed by a health professional. Rare CCs (liver disease and Alzheimer’s disease or other dementia) were not examined as their frequencies were too low. Additionally, the “other chronic conditions” variable was not examined as the conditions contributing to the category are unknown. However, all three of these CC options were included in the total number of pre-existing CCs covariate. As the survey did not capture date of diagnosis for cancer, it was excluded from the analyses as a pre-existing CC but was considered as a covariate in the regression models. For the remaining CCs, only those diagnosed before a respondent’s first confirmed or suspected SARS-CoV-2 infection were considered pre-existing in the analyses. When only the year of CC diagnosis was provided, and it was the same as the year of reported SARS-CoV-2 infection, the CC status was set to missing as its pre-existence was not establishable. If the month and year of the CC and the infection were the same, it was assumed that the condition existed prior to infection. If the month and the year of the CC were missing, it was assumed that the condition existed prior to infection. We made this assumption for two reasons. First, it is more difficult to recall dates of events occurring in the distant past, so respondents diagnosed in the distant past may not have been able to recall their diagnosis date [35]. Second, it is more likely that the chronic condition was diagnosed prior to infection because of the number of lived years prior to infection compared to the number of lived years between infection and questionnaire completion. Further analysis of our analytic sample substantiated our approach. First, among infected adults, chronic conditions with missing date of diagnosis information were reported by 65 plus-years-olds 63.2% of the time while chronic conditions with date of diagnosis information were reported by 65 plus-years-olds 34.8% of the time (p < 0.0001). Second, after excluding chronic conditions with missing date of diagnosis information from our analytic sample, we found that 96.7% of all 18 chronic conditions reported by infected adults were diagnosed prior to SARS-CoV-2 infection. Finally, the proportion of infected adults with a specific chronic condition who did not provide date of diagnosis information never exceeded 3.4% for each of the 18 chronic conditions examined separately. Consequently, the impact of any misclassification resulting from our approach would be minimal. Respondents not completing the CC section of the survey were assumed to have none of the CCs.

Other explanatory variables

Covariates considered for the regression models include sex at birth, gender, age, sexual orientation, highest household education, ethnicity, dwelling type, place of residence (urban/rural), remoteness index, national and area-based neighbourhood income quintile, Canadian Index of Multiple Deprivation dimensions, region of residence, smoking status, body mass index (BMI), cancer status, number of pre-existing CCs, pre-existing chronic health symptoms (CHSs), number of pre-existing CHSs, disability status, number of COVID-19 vaccine doses before infection, time since last vaccination prior to infection, SARS-CoV-2 testing status, time period of first infection, and household member testing positive for SARS-CoV-2 infection. When the number of respondents with an unknown or missing value for a covariate was 30 or greater with at least 5 respondents in each of the severity of infection categories, an unknown category was defined for the covariate and included in all analyses; otherwise, the missing or unknown data were excluded from all analyses. This approach maximized the number of respondents retained for modeling while ensuring confidentiality requirements were satisfied. Area-based neighbourhood income quintiles are based on a ranking of neighbourhood incomes within each census metropolitan area, census agglomeration and residual neighbourhoods within a province. National neighbourhood income quintiles are based on a ranking of neighbourhood incomes using a national distribution rather than area-based. A community’s index of remoteness is determined by its distance to all population centres defined by Statistics Canada in a given travel radius, as well as their population size [36]. The Canadian Index of Multiple Deprivation dimensions included economic dependency, ethno-cultural composition, residential instability, and situational vulnerability. More information about how these dimensions are defined can be found on the Statistics Canada website [37].

Respondents were asked about 34 CHSs. Similar to the CCs, rare CHSs (fainting, difficulty swallowing, and loss of taste or smell) and “other” CHSs were not specifically examined for reasons previously explained, but were included in the total number of CHSs covariate. As CHSs can result from a SARS-CoV-2 infection, CHSs were considered pre-existing if they first started at least two months prior to the SARS-CoV-2 infection. Otherwise, the pre-existence of each CHS was established using the same approach used for the CCs.

Analysis

Descriptive statistics include weighted proportions with 95% confidence intervals (CI) calculated using the Clopper-Pearson (exact) method. The design-based first-order Rao-Scott test of association was used to test for group differences (alpha = 0.05, two-tailed).

Multivariable ordinal logistic regression employing complete case analysis was used to determine which CCs were independently associated with severity of infection symptoms. The resulting odds ratio is an estimate of the odds of more severe infection and is assumed to be constant over cumulated lower levels of severity. Considering the large number of variables to be assessed combined with the increased sampling error associated with the analysis of complex survey data, a stepwise selection process was implemented. Briefly, sex at birth, age group at infection, and all CCs were always retained in the model. All other covariates associated with the outcome of interest at an alpha level of 0.10 (two-tailed) during univariable modeling were added one at a time based on the rankings of univariable p-values. If the added covariate was significant at an alpha level of 0.05 (two-tailed) after adjusting for previously selected variables, it was retained, otherwise it was excluded from further consideration. If the addition of a covariate resulted in a previously selected covariate becoming non-significant (p > 0.05), the non-significant covariate was permanently removed from the model. This process continued until all initially eligible covariates were assessed. When the main effects model was established, interactions between each retained variable and sex were tested (alpha = 0.05, two-tailed), one at a time, using product terms. Significant interactions were addressed by adding product terms to the final model. Four sensitivity analyses were conducted, repeating the multivariable modelling approach with severity of the first infection as the outcome. The first limited the analytic sample to those reporting a positive polymerase chain reaction or rapid antigen test. The second considered the duration of pre-existing CCs by creating trichotomous CC variables as follows: no CC, CC diagnosed less than 10 years prior to infection, and CC diagnosed 10 or more years prior to infection. The third redefined severity of first infection as a binary variable, distinguishing between adults with severe symptoms or hospitalized and those with moderate, mild, or no symptoms. The last excluded those with missing chronic condition diagnosis dates from the analytic sample to assess any potential bias introduced by our approach to handling missing data. All analyses used sampling and bootstrap weights to account for the complex survey design.

Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC).

Ethics approval and consent to participate

This study was exempt from research ethics board review under article 2.2 of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – TCPS 2 (2022) [38]. Our study involved analysis of previously collected anonymized survey data; did not involve linkage to additional data sources; did not include direct follow-up or contact of respondents; and, adhered to the data providers terms and conditions of access, use, and dissemination.

All processes of the CCAHS-2 were reviewed and approved by the Health Canada and Public Health Agency of Canada Research Ethics Board to ensure that internationally recognized ethical standards for human research were met. During the conduct of the survey, adults received invitations by mail that detailed the purpose of the survey and all its components, as well as their right to withdraw from any part of the survey at any time. Completion of the online questionnaire implied consent and captured the respondent’s consent to share their data with specific third parties.

Results

Table 1 displays the characteristics of adults in Canada self-reporting a first confirmed or suspected infection overall and by severity of infection. Of note, 13 of 18 CCs and nearly all covariates examined were significantly associated with severity of infection. Covariates associated with adults being disproportionately distributed in more severe infection categories included: female sex, female gender, obesity, having a disability, having a suspected infection, being infected prior to the Omicron wave, being unvaccinated or less recently vaccinated prior to infection, reporting any of the specific pre-existing CHSs, and having a greater number of pre-existing chronic conditions or symptoms. Contrarily, having a household member with a confirmed SARS-CoV-2 infection was associated with a less severe infection.

Table 1. Characteristics of adults with a self-reported confirmed or suspected SARS-CoV-2 infection by severity of first infection symptoms, Canada, January 2020 to August 2022AllN = 9132No or Mild SymptomsN = 3508Moderate SymptomsN = 4000Severe Symptoms or HospitalizedN = 1624P valueCharacteristicsPercent95% CIPercent95% CIPercent95% CIPercent95% CISex at birth< 0.001 male48.1(47.1, 49.1)54.1(51.9, 56.2)45.2(43.3, 47.1)42.1(38.9, 45.3) female51.9(50.9, 52.9)45.9(43.8, 48.1)54.8(52.9, 56.7)57.9(54.7, 61.1)Gender< 0.001 men48.0(46.9, 49.0)53.8(51.7, 55.9)45.1(43.2, 47.1)41.9(38.7, 45.1) women51.7(50.6, 52.7)45.7(43.6, 47.8)54.7(52.7, 56.6)57.5(54.3, 60.7) other0.4(0.2, 0.6)-^a^-----Age at infection0.002 15–3436.4(35.4, 37.5)35.9(33.8, 37.9)38.2(36.4, 40.2)33.3(30.2, 36.6) 35–4930.0(29.1, 31.0)29.7(28.0, 31.6)30.3(28.6, 32.0)29.8(27.0, 32.7) 50–6422.5(21.6, 23.3)21.7(20.2, 23.3)22.0(20.6, 23.5)25.3(22.7, 28.0) 65+11.1(10.4, 11.7)12.7(11.6, 13.8)9.4(8.5, 10.4)11.6(9.8, 13.5)Sexual orientation0.548 heterosexual92.5(91.7, 93.3)93.1(91.6, 94.3)92.1(90.8, 93.3)92.4(90.5, 94.0) homosexual2.5(2.0, 3.0)1.9(1.2, 2.7)3.0(2.2, 3.9)2.5(1.6, 3.7) other (bisexual, sapiosexual, etc…)3.5(3.0, 4.1)3.6(2.7, 4.7)3.5(2.7, 4.3)3.7(2.5, 5.1) unknown1.5(1.1, 1.9)1.5(1.0, 2.2)1.4(0.9, 2.1)1.4(0.8, 2.4)Highest education completed in household0.163 less than secondary school graduation2.6(2.2, 3.0)3.0(2.4, 3.8)2.1(1.6, 2.8)2.9(2.0, 4.1) secondary school graduation10.6(9.8, 11.5)11.1(9.8, 12.5)10.0(8.9, 11.3)11.0(9.2, 13.1) post-secondary school graduation86.8(85.9, 87.7)85.9(84.4, 87.3)87.9(86.5, 89.1)86.0(83.7, 88.2)Ethnicity< 0.001 Indigenous3.1(2.6, 3.5)2.5(2.0, 3.1)3.3(2.7, 4.1)3.7(2.6, 5.0) White72.7(71.3, 74.2)70.3(67.9, 72.6)74.5(72.4, 76.5)73.9(70.5, 77.0) South Asian5.7(4.9, 6.5)5.9(4.6, 7.3)5.2(4.1, 6.5)6.4(4.5, 8.9) East/Southeast Asian8.2(7.3, 9.1)10.1(8.5, 11.9)7.7(6.4, 9.1)5.1(3.6, 6.9) Black2.6(2.1, 3.1)2.9(2.1, 3.8)2.1(1.5, 2.9)3.1(1.7, 5.0) Arab/West Asian3.1(2.6, 3.7)4.0(3.0, 5.2)2.0(1.5, 2.7)3.8(2.5, 5.4) Latin American2.2(1.7, 2.6)2.3(1.6, 3.3)2.0(1.4, 2.7)2.2(1.3, 3.5) Mixed/Other2.5(2.0, 3.0)2.0(1.4, 2.8)3.2(2.3, 4.2)1.9(1.1, 3.0)Dwelling type0.09 single detached, double, or duplex71.3(69.9, 72.7)71.1(68.9, 73.2)71.6(69.6, 73.5)70.8(67.4, 74.1) row, terrace, or low-rise apartment19.2(18.1, 20.4)19.1(17.3, 21.0)20.1(18.4, 21.7)17.2(14.5, 20.1) high-rise apartment8.1(7.2, 9.1)8.2(6.8, 9.9)7.3(6.0, 8.7)10.1(7.9, 12.7) other (institution, hotel, etc…)1.4(1.1, 1.7)1.5(1.1, 2.1)1.1(0.7, 1.5)1.9(1.0, 3.3)Urban/rural residence0.056 urban85.7(84.9, 86.5)84.5(83.1, 85.9)86.2(84.9, 87.4)87.3(85.2, 89.2) rural14.3(13.5, 15.1)15.5(14.1, 16.9)13.8(12.6, 15.1)12.7(10.8, 14.8)Remoteness index< 0.001 easily accessible area78.0(77.1, 78.8)76.9(75.3, 78.3)79.5(78.2, 80.8)76.6(74.2, 78.9) accessible area17.1(16.3, 17.8)18.0(16.7, 19.3)15.4(14.3, 16.6)19.1(17.1, 21.3) less accessible area4.0(3.6, 4.4)3.8(3.2, 4.5)4.4(3.8, 5.1)3.5(2.6, 4.5) remote or very remote area0.6(0.4, 0.8)0.9(0.6, 1.3)0.3(0.2, 0.6)-- unknown0.4(0.3, 0.5)0.5(0.3, 0.8)0.3(0.2, 0.5)--National neighbourhood income quintile before tax0.148 first (lowest)16.2(15.3, 17.1)17.8(16.2, 19.5)15.0(13.6, 16.3)15.7(13.7, 17.8) second19.4(18.3, 20.5)18.5(16.8, 20.3)20.0(18.4, 21.7)19.7(17.3, 22.3) third20.9(19.8, 22.0)21.0(19.2, 22.9)20.7(19.1, 22.4)21.0(18.3, 23.9) fourth21.6(20.4, 22.8)21.3(19.5, 23.3)21.1(19.3, 22.9)23.4(20.6, 26.5) fifth (highest)22.0(20.8, 23.1)21.4(19.5, 23.3)23.2(21.5, 25.0)20.2(17.7, 22.8)Area-based neighbourhood income quintile before tax0.041 first (lowest)16.4(15.4, 17.5)17.0(15.3, 18.9)15.7(14.3, 17.2)16.9(14.7, 19.3) second19.6(18.7, 20.9)20.4(18.6, 22.4)18.2(16.6, 19.8)21.6(18.9, 24.5) third20.7(19.5, 21.8)18.7(16.9, 20.5)22.5(20.8, 24.2)20.5(17.7, 23.5) fourth21.6(20.3, 22.6)21.8(20.1, 23.7)21.4(19.7, 23.2)21.6(18.9, 24.6) fifth (highest)21.7(20.5, 22.8)22.0(20.2, 23.9)22.2(20.6, 24.0)19.4(16.9, 22.1)Economic dependency quintile^b^0.221 first (lowest)24.3(23.1, 25.6)24.0(22.0, 26.1)24.5(22.7, 26.4)24.5(21.7, 27.6) second20.5(19.4, 21.7)19.2(17.4, 21.1)21.9(20.1, 23.8)20.1(17.3, 23.2) third17.5(16.5, 18.6)18.7(16.9, 20.6)17.3(15.7, 18.9)15.6(13.3, 18.2) fourth14.8(13.8, 15.7)15.7(14.2, 17.4)14.1(12.7, 15.6)14.3(12.2, 16.6) fifth (highest)13.7(12.8, 14.6)13.6(12.2, 15.1)13.4(12.1, 14.8)14.7(12.6, 17.0) unknown9.1(8.4, 9.9)8.8(7.6, 10.1)8.8(7.7, 10.0)10.7(8.7, 12.9)Ethno-cultural composition quintile^c^< 0.001 first (lowest)14.3(13.5, 15.1)16.3(14.9, 17.8)13.4(12.2, 14.7)12.2(10.5, 14.1) second15.3(14.4, 16.3)15.5(14.0, 17.1)14.5(13.1, 15.9)17.0(14.7, 19.5) third18.5(17.4, 19.5)18.5(16.7, 20.3)18.9(17.4, 20.6)17.3(15.0, 19.7) fourth22.1(20.9, 23.3)19.4(17.6, 21.3)24.8(22.9, 26.7)21.4(18.7, 24.4) fifth (highest)20.7(19.4, 21.9)21.5(19.4, 23.7)19.6(17.7, 21.6)21.4(18.2, 25.0) unknown9.1(8.4, 9.9)8.8(7.6, 10.1)8.8(7.7, 10.0)10.7(8.7, 12.9)Residential instability quintile^d^0.235 first (lowest)15.5(14.5, 16.5)16.5(14.9, 18.2)15.3(13.9, 16.7)13.9(11.8, 16.3) second17.9(16.9, 19.0)18.1(16.4, 19.8)18.6(17.0, 20.2)16.0(13.7, 18.6) third18.3(17.2, 19.4)18.7(16.9, 20.5)17.4(15.9, 18.9)19.8(17.0, 22.7) fourth18.0(16.9, 19.1)17.7(16.0, 19.5)18.6(17.0, 20.3)17.2(14.8, 19.9) fifth (highest)21.1(19.9, 22.4)20.2(18.3, 22.3)21.4(19.7, 23.3)22.4(19.6, 25.3) unknown9.1(8.4, 9.9)8.8(7.6, 10.1)8.8(7.7, 10.0)10.7(8.7, 12.9)Situational vulnerability quintile^e^0.04 first (lowest)24.8(23.5, 26.1)24.4(22.4, 26.4)25.1(23.2, 27.1)24.7(21.9, 27.8) second19.9(18.8, 21.0)20.0(18.2, 21.9)20.1(18.4, 21.9)19.0(16.4, 21.7) third18.7(17.7, 19.7)18.2(16.5, 20.0)19.2(17.5, 20.9)18.8(16.1, 21.6) fourth15.5(14.5, 16.5)14.5(13.0, 16.0)16.3(14.9, 17.9)15.6(13.2, 18.2) fifth (highest)12.1(11.2, 12.9)14.2(12.7, 15.8)10.5(9.3, 11.7)11.2(9.5, 13.2) unknown9.1(8.4, 9.9)8.8(7.6, 10.1)8.8(7.7, 10.0)10.7(8.7, 12.9)Province of Residence< 0.001 British Columbia14.0(13.3, 14.7)12.1(10.8, 13.4)14.7(13.5, 15.9)16.3(14.2, 18.6) Prairies19.2(18.4, 20.0)18.7(17.4, 20.1)20.0(18.7, 21.2)18.3(16.3, 20.6) Ontario37.3(36.1, 38.4)37.7(35.6, 39.9)36.0(34.1, 38.1)39.3(35.8, 42.8) Quebec23.1(22.3, 24.0)24.6(23.0, 26.2)23.3(21.8, 24.8)19.6(17.3, 22.0) Atlantic Canada6.4(5.9, 7.0)6.9(6.1, 7.8)6.0(5.3, 6.8)6.5(5.3, 7.8)Smoking status0.513 current smoker8.2(7.5, 8.9)8.3(7.1, 9.5)7.8(6.7, 8.9)9.0(7.3, 10.9) does not currently smoke91.8(91.1, 92.5)91.7(90.5, 92.9)92.2(91.1, 93.3)91.0(89.1, 92.7)Body mass index (BMI)< 0.001 underweight and normal weight (BMI < 25 kg/m2)31.3(30.0, 32.5)32.7(30.5, 34.9)31.7(29.7, 33.7)27.1(24.1, 30.2) overweight (25 kg/m2 < = BMI < 30 kg/m2)35.7(34.4, 37.0)36.4(34.3, 38.6)37.0(35.0, 39.1)30.9(27.8, 34.1) obese (BMI > = 30 kg/m2)30.9(29.7, 32.1)29.1(27.1, 31.0)28.9(27.2, 30.7)39.8(36.5, 43.3) unknown2.2(1.8, 2.6)1.9(1.3, 2.6)2.4(1.8, 3.1)2.2(1.3, 3.5)Cancer0.288 current cancer1.4(1.2, 1.8)1.2(0.9, 1.7)1.4(1.0, 2.0)1.9(1.2, 2.8) does not currently have cancer98.6(98.2, 98.8)98.8(98.3, 99.1)98.6(98.0, 99.0)98.1(97.2, 98.8)Pre-existing chronic conditions chronic lung disease1.6(1.3, 1.9)1.1(0.8, 1.5)1.4(1.0, 1.8)3.5(2.5, 4.7)< 0.001 sleep apnea5.7(5.1, 6.3)4.8(4.0, 5.7)5.6(4.7, 6.5)7.9(6.4, 9.7)0.001 asthma7.5(6.9, 8.2)6.1(5.1, 7.2)7.2(6.2, 8.3)11.6(9.6, 13.9)< 0.001 chronic heart disease2.1(1.7, 2.4)2.0(1.6, 2.6)1.8(1.4, 2.4)2.7(1.9, 3.9)0.194 diabetes5.2(4.7, 5.8)5.6(4.7, 6.8)3.8(3.2, 4.5)7.9(6.3, 9.6)< 0.001 chronic kidney disease0.6(0.4, 0.9)0.5(0.2, 0.9)0.8(0.5, 1.3)0.4(0.2, 0.9)0.176 high blood pressure11.9(11.1, 12.7)10.8(9.7, 12.1)10.8(9.8, 11.9)17.1(14.7, 19.6)< 0.001 chronic blood disorder0.8(0.6, 1.0)0.8(0.4, 1.3)0.6(0.4, 0.9)1.2(0.6, 2.0)0.158 osteoporosis1.9(1.6, 2.2)2.1(1.5, 2.7)1.3(1.0, 1.8)2.8(2.0, 3.9)0.004 back problems10.5(9.7, 11.2)8.9(7.7, 10.2)9.2(8.2, 10.2)17.3(15.0, 19.8)< 0.001 urinary incontinence1.9(1.6, 2.3)1.7(1.2, 2.2)1.9(1.5, 2.5)2.6(1.8, 3.6)0.176 bowel disorder4.1(3.6, 4.7)3.4(2.7, 4.3)3.5(2.8, 4.3)7.3(5.8, 9.0)< 0.001 weakened immune system3.7(3.2, 4.2)2.3(1.7, 3.0)3.4(2.7, 4.3)7.3(5.6, 9.2)< 0.001 chronic neurological disorder1.7(1.4, 2.0)1.4(0.9, 2.0)1.4(1.0, 1.9)3.1(2.1, 4.3)< 0.001 chronic fatigue syndrome or fibromyalgia1.4(1.2, 1.7)0.6(0.3, 0.9)1.2(0.8, 1.6)4.1(3.0, 5.5)< 0.001 effects of a stroke0.5(0.3, 0.7)0.5(0.3, 0.8)0.5(0.2, 0.8)0.6(0.3, 1.1)0.89 mental health condition11.5(10.6, 12.3)9.2(7.9, 10.7)10.9(9.6, 12.3)17.9(15.6, 20.3)< 0.001 arthritis10.8(10.1, 11.6)8.9(7.9, 10.0)9.7(8.7, 10.9)18(15.7, 20.5)< 0.001Number of pre-existing chronic conditions< 0.001 055.7(54.3, 57.0)59.0(56.8, 61.1)58.3(56.2, 60.4)41.6(38.2, 45.0) 122.6(21.5, 23.8)23.3(21.5, 25.2)22.4(20.6, 24.2)21.8(19.2, 24.6) 211.4(10.6, 12.2)9.5(8.3, 10.8)10.3(9.2, 11.4)18.4(15.9, 21.2) 35.0(4.5, 5.6)4.5(3.7, 5.4)4.4(3.7, 5.1)7.9(6.4, 9.6) > 35.2(4.7, 5.8)3.7(3.0, 4.4)4.6(3.9, 5.5)10.3(8.7, 12.1)Pre-existing chronic symptoms pain (excluding headache)12.9(12.1, 13.7)10.3(9.2, 11.6)12.2(11.0, 13.5)20.2(17.7, 22.8)< 0.001 shortness of breath or difficulty breathing4.8(4.2, 5.3)4.1(3.3, 5.0)4.2(3.3, 5.0)7.6(6.1, 9.3)< 0.001 difficulty speaking or hoarseness0.7(0.6, 0.9)0.6(0.4, 0.9)0.4(0.2, 0.6)1.9(1.2, 2.7)< 0.001 cough3.0(2.6, 3.4)2.5(1.9, 3.1)2.7(2.1, 3.3)5.0(3.8, 6.4)< 0.001 headache6.9(6.2, 7.6)4.9(4.0, 5.9)6.9(5.9, 8.0)11.2(9.3, 13.3)< 0.001 chest tightness1.8(1.5, 2.2)1.5(1.0, 2.0)1.6(1.1, 2.3)3.1(2.2, 4.3)0.003 symptoms relating to the heart (e.g., fast, pounding or irregular heartbeat)4.3(3.8, 4.8)3.0(2.4, 3.7)4.1(3.4, 5.0)7.4(6.0, 9.2)< 0.001 fatigue, tiredness or loss of energy13.5(12.6, 14.5)9.4(8.3, 10.7)13.8(12.3, 15.3)22.1(19.4, 24.9)< 0.001 general weakness3.4(2.9, 3.9)1.7(1.3, 2.3)3.7(3.0, 4.6)6.1(4.7, 7.7)< 0.001 loss of appetite1.2(0.9, 1.5)0.7(0.4, 1.0)0.9(0.6, 1.4)2.9(2.0, 4.0)< 0.001 feeling thirsty2.2(1.9, 2.6)1.9(1.3, 2.6)1.9(1.5, 2.5)3.8(2.8, 4.9)< 0.001 nausea, vomiting1.4(1.1, 1.8)1.1(0.6, 1.6)1.2(0.7, 1.9)2.6(1.8, 3.6)0.005 upset stomach, bloating, gas7.2(6.5, 7.9)5.4(4.5, 6.4)7.3(6.2, 8.5)11(9.1, 13.1)< 0.001 heartburn or indigestion7.2(6.6, 7.8)5.2(4.4, 6.1)7.7(6.7, 8.8)10.4(8.6, 12.5)< 0.001 frequent urination5.1(4.6, 5.6)4.5(3.8, 5.3)4.5(3.8, 5.3)7.7(6.2, 9.5)< 0.001 irregular bowel movements or habits7.0(6.4, 7.7)5.1(4.2, 6.1)7.3(6.2, 8.5)10.6(8.8, 12.7)< 0.001 change in body weight2.8(2.4, 3.2)2.4(1.8, 3.2)2.3(1.8, 2.9)4.6(3.4, 5.9)< 0.001 dizziness3.8(3.3, 4.3)2.7(2.0, 3.5)3.5(2.8, 4.3)6.9(5.3, 8.7)< 0.001 feeling hot or cold (body temperature changes)5(4.4, 5.5)3.4(2.8, 4.1)4.7(3.9, 5.6)9.2(7.6, 11.1)< 0.001 numbness or tingling5.1(4.6, 5.7)3.4(2.8, 4.1)5.3(4.4, 6.3)8.7(7.1, 10.5)< 0.001 swelling2.3(2.0, 2.7)1.7(1.3, 2.3)1.8(1.3, 2.3)5.2(4.0, 6.8)< 0.001 skin irritation7.2(6.5, 7.9)5.4(4.5, 6.4)7.6(6.5, 8.7)10.4(8.3, 12.7)< 0.001 joint inflammation10(9.2, 10.7)7.5(6.6, 8.6)9.2(8.1, 10.4)17.4(15.1, 19.8)< 0.001 stiffness9.4(8.7, 10.2)7.4(6.4, 8.5)9.2(8.1, 10.5)14.5(12.5, 16.7)< 0.001 difficulty falling or staying asleep12.3(11.5, 13.1)9.8(8.6, 11.1)12.5(11.3, 13.8)17.2(15.1, 19.6)< 0.001 difficulty thinking or problem solving (brain fog)5.7(5.0, 6.3)3.9(3.1, 4.9)5.9(5.0, 7.0)8.8(7.1, 10.8)< 0.001 confusion, memory loss3.2(2.7, 3.6)2.4(1.8, 3.1)2.7(2.2, 3.4)5.9(4.4, 7.6)< 0.001 loss of interest in activities5.4(4.9, 6.0)4.4(3.6, 5.3)5.1(4.3, 6.1)8.6(7.0, 10.4)< 0.001 sadness, pessimism, hopelessness, or depression9.1(8.3, 9.9)7.9(6.7, 9.2)8.2(7.1, 9.4)13.9(11.8, 16.3)< 0.001 stress or anxiety22.2(21.0, 23.4)18.8(17.0, 20.7)21.6(19.9, 23.3)31.5(28.4, 34.7)< 0.001Number of pre-existing chronic health symptoms< 0.001 049.9(48.5, 51.3)55.8(53.5, 58.0)50.1(48.1, 52.2)35.9(32.6, 39.3) 1–225.8(24.6, 27.1)25.6(23.7, 27.7)25.7(23.9, 27.6)26.4(23.5, 29.5) 36.5(5.9, 7.2)5.1(4.2, 6.2)7.2(6.2, 8.3)7.9(6.3, 9.7) > 317.8(16.9, 18.8)13.4(12.1, 14.9)17.0(15.6, 18.4)29.8(27.0, 32.7)Disability status< 0.001 identifies as having a disability6.0(5.5, 6.7)5.2(4.3, 6.3)5.2(4.4, 6.2)9.9(8.4, 11.7) does not identify as having a disability92.3(91.6, 93.0)93.7(92.5, 94.7)92.6(91.4, 93.7)88.6(86.7, 90.2) unknown1.6(1.3, 2.1)1.1(0.6, 1.8)2.2(1.5, 3.0)1.5(1.0, 2.2)Number of vaccine doses received prior to the month of infection< 0.001 024.3(22.9, 25.7)20.5(18.4, 22.7)22.1(20.2, 24.1)38.2(34.9, 41.6) 12.0(1.6, 2.4)2.0(1.4, 2.8)1.9(1.4, 2.6)2.0(1.0, 3.6) 235.1(33.8, 36.5)35.8(33.4, 38.1)35.8(33.9, 37.9)31.9(28.8, 35.1) > 236.6(35.2, 38.0)39.4(37.2, 41.8)38.3(36.3, 40.4)25.8(23.0, 28.7) unknown2.0(1.7, 2.4)2.3(1.7, 2.9)1.8(1.3, 2.5)2.1(1.2, 3.4)Months since last vaccine dose prior to the month of infection< 0.001 not vaccinated24.2(22.9, 25.7)20.5(18.4, 22.7)22.1(20.2, 24.1)38.2(34.9, 41.6) <=3 months25.3(24.1, 26.5)28.6(26.6, 30.6)25.4(23.5, 27.3)17.6(15.2, 20.3) 4–6 months33.7(32.3, 35.0)33.1(30.9, 35.4)36.7(34.7, 38.8)27.3(24.3, 30.5) > 6 months14.4(13.4, 15.3)15.1(13.4, 16.8)13.7(12.3, 15.2)14.3(12.0, 16.9) unknown2.4(2.1, 2.9)2.8(2.2, 3.5)2.1(1.5, 2.8)2.5(1.6, 3.9)SARS-CoV-2 testing status< 0.001 confirmed infection (PCR or RAT positive)76.1(74.8, 77.3)78.2(76.3, 80.1)77.3(75.5, 79.0)68.1(64.9, 71.1) suspected infection23.9(22.7, 25.2)21.8(19.9, 23.7)22.7(21.0, 23.7)31.9(28.9, 35.1)Time period of first infection< 0.001 pre-Omicron (January 1, 2020 – November 30, 2021)24.2(22.9, 25.5)20.4(18.5, 22.4)21.7(19.9, 23.6)39.0(35.7, 42.4) Omicron (December 1, 2021 – August 31, 2022)75.1(73.8, 76.4)79.0(77.0, 80.9)77.9(76.0, 79.7)59.6(56.2, 62.9) unknown0.7(0.5, 1.0)0.6(0.3, 1.1)0.4(0.2, 0.7)--Household member testing positive for a SARS-CoV-2 infection< 0.001 yes61.7(60.1, 63.1)65.3(62.9, 67.5)61.1(59.0, 63.3)54.8(51.3, 58.4) no37.4(35.9, 38.9)34.1(31.8, 36.4)37.9(35.8, 40.1)43.7(40.2, 47.3) unknown0.9(0.7, 1.3)0.7(0.4, 1.1)1.0(0.5, 1.6)--Notes: Estimates for Canada exclude the territories. All estimates are weightedAbbreviations: CI = confidence interval, PCR = polymerase chain reaction, RAT = rapid antigen test^a^ Suppressed as coefficient of variation is greater than 33.3%^b^ Economic dependency quantifies a neighbourhood’s dependence on sources of income other than employment income^c^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations^d^ Residential instability quantifies the tendency of neighbourhood inhabitants to fluctuate over time^e^ Situational vulnerability quantifies a neighbourhood’s education level, Indigenous composition, and extent of dwellings in need of major repairs

In the fully adjusted model, 6 of the 18 pre-existing CCs remained significantly associated with severity of infection after adjusting for other important covariates. Pre-existing chronic lung disease (CLC) (adjusted odds ratio (aOR): 1.64, 95% CI: 1.09, 2.46), high blood pressure (HBP) (aOR: 1.35, 95% CI: 1.13, 1.62), weakened immune system (WIS) (aOR: 1.46, 95% CI: 1.08, 1.98), chronic fatigue syndrome (CFS) 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 higher odds of more severe infection (Table 2). Conversely, pre-existing osteoporosis was associated with lower odds of a more severe infection (aOR: 0.58, 95% CI: 0.39, 0.87).

Table 2. Odds ratios for more severe acute first infection symptoms among adults with a self-reported confirmed or suspected SARS-CoV-2 infection, Canada, January 2020 to August 2022 (n = 9086)CharacteristicsuOR95% CIaOR95% CIp valuePre-existing chronic conditions chronic lung disease2.41(1.67, 3.48)1.64(1.09, 2.46)0.017 sleep apnea1.42(1.14, 1.76)1.17(0.93, 1.49)0.186 asthma1.59(1.29, 1.95)1.22(0.98, 1.52)0.072 chronic heart disease1.17(0.83, 1.64)0.88(0.61, 1.27)0.502 diabetes1.12(0.85, 1.46)0.87(0.66, 1.17)0.360 chronic kidney disease1.13(0.71, 1.80)0.95(0.55, 1.65)0.865 high blood pressure1.36(1.16, 1.59)1.35(1.13, 1.62)< 0.001 chronic blood disorder1.18(0.59, 2.36)0.66(0.30, 1.45)0.299 osteoporosis1.08(0.72, 1.62)0.58(0.39, 0.87)0.009 back problems1.62(1.36, 1.93)1.11(0.91, 1.36)0.321 urinary incontinence1.33(0.96, 1.85)0.91(0.65, 1.27)0.563 bowel disorder1.71(1.29, 2.26)1.06(0.81, 1.40)0.658 weakened immune system2.35(1.76, 3.12)1.46(1.08, 1.98)0.015 chronic neurological disorder1.73(1.10, 2.70)0.94(0.60, 1.49)0.801 chronic fatigue syndrome or fibromyalgia4.57(3.00, 6.97)2.20(1.39, 3.50)< 0.001 stroke1.06(0.58, 1.94)0.77(0.40, 1.50)0.446 mental health condition1.64(1.39, 1.95)1.12(0.93, 1.35)0.238 arthritis1.7(1.44, 2.00)1.28(1.04, 1.56)0.019Age at infection (ref = 15–34)----< 0.001 35–491.02(0.90, 1.16)1.04(0.91, 1.19)0.540 50–641.10(0.96, 1.26)0.96(0.83, 1.12)0.632 65+0.87(0.74, 1.02)0.66(0.54, 0.81)< 0.001Sex (ref = male)----< 0.001 female1.44(1.29, 1.60)1.30(1.15, 1.46)< 0.001Ethnicity (ref = white)----0.023 Indigenous1.26(0.97, 1.64)1.10(0.84, 1.46)0.487 South Asian0.97(0.71, 1.32)0.94(0.68, 1.31)0.715 East/Southeast Asian0.64(0.51, 0.80)0.63(0.49, 0.80)< 0.001 Black0.90(0.57, 1.44)0.81(0.50, 1.31)0.387 Arab/West Asian0.73(0.48, 1.10)0.73(0.47, 1.15)0.176 Latin American0.87(0.56, 1.34)0.89(0.58, 1.38)0.604 Mixed/Other1.09(0.80, 1.47)1.09(0.79, 1.51)0.600Ethno-cultural composition (ref = first quintile)^a^----0.001 second1.27(1.07, 1.51)1.26(1.05, 1.52)0.013 third1.21(1.03, 1.42)1.19(1.00, 1.42)0.050 fourth1.40(1.19, 1.64)1.43(1.20, 1.70)< 0.001 fifth (highest)1.20(0.99, 1.44)1.38(1.12, 1.69)0.002 unknown1.37(1.11, 1.70)1.43(1.11, 1.84)0.006Situational vulnerability (ref = first quintile)^b^----< 0.001 second0.96(0.82, 1.13)0.98(0.82, 1.16)0.782 third1.02(0.87, 1.19)0.96(0.81, 1.14)0.639 fourth1.06(0.90, 1.25)0.99(0.83, 1.18)0.902 fifth (highest)0.78(0.65, 0.93)0.68(0.56, 0.83)< 0.001 unknown^c^1.09(0.89, 1.33)---Pre-existing chronic health symptoms fatigue1.98(1.70, 2.29)1.22(1.00, 1.48)0.047 loss of appetite3.08(1.94, 4.89)1.82(1.12, 2.94)0.016Number of pre-existing chronic health symptoms (ref = 0)----< 0.001 1 or 21.29(1.11, 1.47)1.21(1.06, 1.38)0.005 31.74(1.43, 2.11)1.56(1.26, 1.93)< 0.001 > 32.21(1.92, 2.54)1.47(1.20, 1.81)< 0.001Months since last vaccine dose prior to the month of infection (ref = 3 months or less)----< 0.001 not vaccinated1.96(1.67, 2.30)1.54(1.19, 2.00)0.001 4–6 months1.23(1.08, 1.40)1.31(1.15, 1.50)< 0.001 > 6 months1.22(1.02, 1.46)1.27(1.05, 1.52)0.013 unknown1.11(0.76, 1.61)1.01(0.71, 1.44)0.960Time period of first infection (ref = pre-omicron)----0.005 Omicron (December 1, 2021 – date of electronic questionnaire completion)0.57(0.50, 0.66)0.70(0.55, 0.90)0.005 unknown1.14(0.42, 3.11)1.83(0.62, 5.36)0.271Household member testing positive for SARS-CoV-2 infection (ref = no)----< 0.001 yes0.76(0.68, 0.85)0.83(0.74, 0.94)0.002 unknown1.42(0.73, 2.77)1.71(0.88, 3.34)0.116Notes: Estimates for Canada exclude the territories. All estimates are weighted. The reference category for a pre-existing chronic condition or symptom are adults without the chronic condition or symptom, respectivelyAbbreviations: aOR = adjusted odds ratio, CI = confidence interval, n = unweighted number of respondents included in the final model, ref = reference, uOR = unadjusted odds ratiop value is only for the fully adjusted model^a^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations^b^ Situational vulnerability quantifies a neighbourhood’s education level, Indigenous composition, and extent of dwellings in need of major repairs^c^ For the dimensions of deprivation, values for an individual were either known or unknown for all dimensions. Consequently, the parameter for unknown situational vulnerability has a value of 0 in the final adjusted model because it is a linear combination of the parameter for unknown ethnocultural composition

With respect to retained covariates, being female, unvaccinated or vaccinated more than 3 months prior to infection, having a pre-existing CHS or specifically reporting pre-existing fatigue or loss of appetite, and living in a more ethnically diverse neighbourhood were associated with higher odds of more severe infection compared to the respective reference groups. Being 65 years old or older at infection or East or Southeast Asian, getting infected on or after December 1st, 2021, having a household member who tested positive for SARS-CoV-2 infection, and residing in a neighbourhood classified in the highest quintile of situational vulnerability were associated with a lower odds of more severe infection compared to the respective reference groups.

In the first sensitivity analysis, restricting the modelling to respondents with a confirmed SARS-CoV-2 infection resulted in some changes (Table 3). For CCs, arthritis (aOR: 1.11; 95% CI: 0.84, 1.42) was no longer significant, whereas having a pre-existing mental health condition was associated with a higher odds of more severe infection (aOR: 1.32; 95% CI: 1.05, 1.66). For covariates, ethnicity, time since last vaccination prior to infection, and pre-existing chronic fatigue were no longer significant, while body mass index, sadness/pessimism/hopelessness/depression (SPHD) (aOR: 0.71, 95% CI: 0.53, 0.95), and swelling (aOR: 1.85, 95% CI: 1.23, 2.79) became significant. Remoteness index also became significant with those living in remote or very remote communities having a significantly lower odds of more severe infection (aOR: 0.31; 95% CI: 0.13, 0.74). Sex significantly interacted with BMI: for males, excess body weight was associated with a higher odds of more severe infection while no association was noted for females. When examined by BMI category, the interaction indicated that the relationship between sex and severity of infection decreased in magnitude with increases in BMI: for underweight or normal weight (aOR: 1.64, 95% CI: 1.29, 2.10) and overweight adults (aOR: 1.24, 95% CI: 1.01, 1.54), females had a higher odds of more severe infection, but this relationship no longer existed among obese adults (aOR: 0.96, 95% CI: 0.75, 1.22).

Table 3. Odds ratios for more severe acute first infection symptoms among adults with a confirmed SARS-CoV-2 infection, Canada, January 2020 to August 2022 (n = 7092)CharacteristicsuOR95% CIaOR95% CIp valuePre-existing chronic conditions chronic lung disease2.48(1.52, 4.03)1.98(1.17, 3.34)0.011 sleep apnea1.38(1.08, 1.76)1.04(0.79, 1.37)0.768 asthma1.46(1.15, 1.84)1.13(0.89, 1.43)0.310 chronic heart disease1.26(0.88, 1.80)0.87(0.57, 1.32)0.503 diabetes0.98(0.72, 1.33)0.79(0.57, 1.11)0.177 chronic kidney disease1.29(0.76, 2.19)1.09(0.58, 2.07)0.782 high blood pressure1.3(1.09, 1.56)1.24(1.02, 1.52)0.033 chronic blood disorder1.54(0.72, 3.28)0.96(0.40, 2.33)0.929 osteoporosis1.08(0.67, 1.73)0.63(0.40, 1.00)0.050 back problems1.48(1.19, 1.83)1.05(0.82, 1.35)0.715 urinary incontinence1.24(0.84, 1.81)0.94(0.63, 1.39)0.750 bowel disorder1.45(1.06, 2.00)0.92(0.66, 1.29)0.642 weakened immune system2.34(1.66, 3.31)1.71(1.20, 2.44)0.003 chronic neurological disorder1.17(0.68, 2.02)0.72(0.41, 1.26)0.245 chronic fatigue syndrome or fibromyalgia3.75(2.20, 6.40)2.11(1.19, 3.75)0.010 stroke0.96(0.49, 1.85)0.66(0.33, 1.31)0.232 mental health condition1.68(1.37, 2.07)1.32(1.05, 1.66)0.019 arthritis1.54(1.28, 1.86)1.11(0.87, 1.42)0.396Age at infection (ref = 15–34)----< 0.001 35–490.99(0.86, 1.15)0.93(0.80, 1.08)0.331 50–641.05(0.89, 1.23)0.90(0.75, 1.08)0.265 65+0.76(0.64, 0.91)0.59(0.47, 0.74)< 0.001Sex (ref = male)----- female1.35(1.19, 1.52)Interaction--Remoteness index (ref = easily accessible area)----0.004 accessible area0.90(0.78, 1.03)0.99(0.85, 1.15)0.843 less accessible area1.05(0.83, 1.34)1.28(0.99, 1.67)0.064 remote or very remote areas0.26(0.12, 0.54)0.31(0.13, 0.74)0.008 unknown0.53(0.28, 0.99)0.47(0.24, 0.91)0.026Ethno-cultural composition (ref = first quintile)^a^----< 0.001 second1.35(1.11, 1.63)1.34(1.09, 1.64)0.005 third1.28(1.08, 1.53)1.34(1.10, 1.63)0.003 fourth1.53(1.28, 1.83)1.60(1.31, 1.96)< 0.001 fifth (highest)1.46(1.19, 1.80)1.58(1.26, 1.98)< 0.001 unknown1.49(1.18, 1.89)1.55(1.15, 2.09)0.004Situational vulnerability (ref = first quintile)^b^----0.007 second0.93(0.77, 1.12)0.97(0.80, 1.18)0.760 third0.98(0.82, 1.18)0.95(0.78, 1.15)0.599 fourth1.14(0.94, 1.38)1.07(0.87, 1.31)0.540 fifth (highest)0.75(0.61, 0.93)0.69(0.55, 0.87)0.002 unknown^c^1.08(0.86, 1.36)---Body mass index (BMI) (ref = underweight and normal weight (BMI < 25 kg/m2))----- overweight (25 kg/m2 < = BMI < 30 kg/m2)1.07(0.92, 1.24)Interaction-- obese (BMI > = 30 kg/m2)1.38(1.18, 1.61)Interaction-- unknown1.36(0.85, 2.20)Interaction--Pre-existing chronic health symptoms loss of appetite3.51(1.90, 6.47)2.03(1.07, 3.85)0.030 swelling3.21(2.13, 4.84)1.85(1.23, 2.79)0.003 sadness/pessimism/hopelessness/depression1.44(1.13, 1.83)0.71(0.53, 0.95)0.021Number of pre-existing chronic health symptoms (ref = 0)----< 0.001 1 or 21.34(1.16, 1.55)1.32(1.14, 1.53)< 0.001 31.78(1.42, 2.22)1.83(1.44, 2.33)< 0.001 > 32.29(1.93, 2.72)1.99(1.59, 2.50)< 0.001Time period of first infection (ref = pre-omicron)----0.002 Omicron (December 1, 2021 – date of electronic questionnaire completion)0.72(0.60, 0.87)0.70(0.58, 0.86)0.001 unknown0.77(0.18, 3.30)1.03(0.20, 5.20)0.972Household member testing positive for SARS-CoV-2 infection (ref = no)----0.038 yes0.92(0.80, 1.05)0.94(0.81, 1.09)0.398 unknown2.09(0.95, 4.58)2.22(1.08, 4.53)0.029Interaction between sex and BMI----0.017 male (ref = underweight or normal weight)----- overweight--1.36(1.06, 1.75)0.014 obese--1.79(1.36, 2.36)< 0.001 unknown1.62(0.06, 42.38)0.772 female (ref = underweight or normal weight)----- overweight--1.03(0.84, 1.27)0.758 obese--1.05(0.85, 1.28)0.670 unknown1.05(0.66, 1.69)0.834 female underweight or normal weight (ref = male underweight or normal weight)--1.64(1.29, 2.10)< 0.001 female overweight (ref = male overweight)--1.24(1.01, 1.54)0.045 female obese (ref = male obese)--0.96(0.75, 1.22)0.717 female unknown (ref = male unknown)--1.07(0.04, 27.51)0.969Notes: Estimates for Canada exclude the territories. All estimates are weighted. The reference category for a pre-existing chronic condition or symptom are adults without the chronic condition or symptom, respectivelyAbbreviations: aOR = adjusted odds ratio, CI = confidence interval, n = unweighted number of respondents included in the final model, ref = reference, uOR = unadjusted odds ratiop value is only for the fully adjusted model^a^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations^b^ Situational vulnerability quantifies a neighbourhood’s education level, Indigenous composition, and extent of dwellings in need of major repairs^c^ For the dimensions of deprivation, values for an individual were either known or unknown for all dimensions. Consequently, the parameter for unknown situational vulnerability has a value of 0 in the final adjusted model because it is a linear combination of the parameter for unknown ethnocultural composition

When recoding the CCs as trichotomous variables to account for duration of chronic conditions prior to infection, the majority of the model remained the same (compare Table 2 with Table 4). Among the significant CCs, CLC, HBP, osteoporosis, and WIS had significant associations when the CC was diagnosed 10 or more years prior to infection. Only HBP and CFS had significant associations when the CC was diagnosed less than 10 years prior to infection. Notably, arthritis was no longer statistically significant and an interaction between bowel disorder and sex was observed. For males, there was no significant association between bowel disorders and severity of infection, but females diagnosed 10 or more years prior to infection had higher odds of a more severe infection than females without bowel disorders (aOR: 1.78, 95% CI: 1.15, 2.74). When examined by bowel disorders category, the odds of a more severe infection were higher for females than males among adults without bowel disorders (aOR: 1.29, 95% CI: 1.14, 1.45) or with bowel disorders diagnosed 10 or more years prior to infection (aOR: 4.16, 95% CI: 1.62, 10.68), but not among adults with bowel disorders diagnosed less than 10 years prior to infection (aOR: 1.06, 95% CI: 0.51, 2.18). For covariates, only fatigue was no longer statistically significant.

Table 4. Odds ratios for more severe acute first infection symptoms among adults with a self-reported confirmed or suspected SARS-CoV-2 infection while adjusting for duration of pre-existing chronic conditions, Canada, January 2020 to August 2022 (n = 8991)CharacteristicsuOR95% CIaOR95% CIp valuePre-existing chronic conditions chronic lung disease0.038 diagnosed less than 10 years prior to infection1.94(1.12, 3.38)1.54(0.82, 2.88)0.181 diagnosed 10 or more years prior to infection3.01(1.82, 4.99)1.91(1.08, 3.38)0.027sleep apnea0.196 diagnosed less than 10 years prior to infection1.46(1.16, 1.84)1.27(0.98, 1.65)0.072 diagnosed 10 or more years prior to infection1.31(0.86, 2.00)1.00(0.63, 1.58)0.992asthma0.280 diagnosed less than 10 years prior to infection1.86(1.13, 3.05)1.29(0.77, 2.16)0.339 diagnosed 10 or more years prior to infection1.56(1.24, 1.96)1.17(0.92, 1.49)0.196chronic heart disease0.305 diagnosed less than 10 years prior to infection1.33(0.84, 2.11)1.04(0.62, 1.73)0.888 diagnosed 10 or more years prior to infection0.98(0.60, 1.60)0.68(0.41, 1.12)0.132diabetes0.392 diagnosed less than 10 years prior to infection1.24(0.83, 1.85)0.98(0.64, 1.50)0.920 diagnosed 10 or more years prior to infection0.94(0.65, 1.36)0.75(0.50, 1.13)0.172chronic kidney disease0.990 diagnosed less than 10 years prior to infection1.25(0.65, 2.43)1.06(0.48, 2.30)0.893 diagnosed 10 or more years prior to infection0.97(0.50, 1.91)0.98(0.40, 2.43)0.967high blood pressure0.007 diagnosed less than 10 years prior to infection1.45(1.16, 1.80)1.32(1.05, 1.67)0.018 diagnosed 10 or more years prior to infection1.27(1.03, 1.57)1.35(1.06, 1.71)0.016chronic blood disorder0.416 diagnosed less than 10 years prior to infection1.75(0.57, 5.36)0.94(0.26, 3.45)0.928 diagnosed 10 or more years prior to infection0.91(0.36, 2.33)0.50(0.18, 1.41)0.187osteoporosis0.029 diagnosed less than 10 years prior to infection1.46(0.85, 2.50)0.67(0.39, 1.15)0.144 diagnosed 10 or more years prior to infection0.81(0.45, 1.47)0.48(0.26, 0.89)0.021back problems0.246 diagnosed less than 10 years prior to infection1.37(1.02, 1.83)0.99(0.72, 1.37)0.951 diagnosed 10 or more years prior to infection1.86(1.50, 2.30)1.23(0.96, 1.56)0.097urinary incontinence0.356 diagnosed less than 10 years prior to infection1.55(1.06, 2.26)1.06(0.70, 1.60)0.792 diagnosed 10 or more years prior to infection0.94(0.50, 1.79)0.61(0.31, 1.21)0.157bowel disorder--- diagnosed less than 10 years prior to infection1.43(1.02, 2.00)Interaction-- diagnosed 10 or more years prior to infection2.05(1.32, 3.16)Interaction--weakened immune system0.037 diagnosed less than 10 years prior to infection2.03(1.37, 2.99)1.43(0.93, 2.21)0.105 diagnosed 10 or more years prior to infection2.96(1.93, 4.55)1.57(1.03, 2.38)0.034chronic neurological disorder0.732 diagnosed less than 10 years prior to infection1.45(0.75, 2.81)0.82(0.44, 1.49)0.507 diagnosed 10 or more years prior to infection2.02(1.09, 3.76)1.16(0.57, 2.34)0.689chronic fatigue syndrome or fibromyalgia0.020 diagnosed less than 10 years prior to infection4.09(2.28, 7.35)2.13(1.10, 4.12)0.024 diagnosed 10 or more years prior to infection5.05(2.83, 8.98)1.83(0.98, 3.42)0.058stroke0.858 diagnosed less than 10 years prior to infection0.97(0.49, 1.94)0.82(0.35, 1.91)0.643 diagnosed 10 or more years prior to infection1.32(0.36, 4.82)0.81(0.21, 3.13)0.763mental health condition0.276 diagnosed less than 10 years prior to infection1.44(1.12, 1.86)1.02(0.79, 1.33)0.857 diagnosed 10 or more years prior to infection1.90(1.56, 2.31)1.20(0.96, 1.50)0.109arthritis0.156 diagnosed less than 10 years prior to infection1.69(1.32, 2.17)1.22(0.91, 1.64)0.180 diagnosed 10 or more years prior to infection1.70(1.40, 2.08)1.22(0.96, 1.55)0.097Age at infection (ref = 15–34)----< 0.001 35–491.02(0.90, 1.16)1.04(0.91, 1.19)0.568 50–641.10(0.96, 1.26)0.94(0.81, 1.10)0.429 65+0.87(0.74, 1.02)0.68(0.55, 0.83)< 0.001Sex (ref = male)----- female1.44(1.29, 1.60)Interaction--Ethnicity (ref = white)----0.016 Indigenous1.26(0.97, 1.64)1.13(0.85, 1.50)0.409 South Asian0.97(0.71, 1.32)0.93(0.66, 1.30)0.653 East/Southeast Asian0.64(0.51, 0.80)0.62(0.48, 0.79)< 0.001 Black0.90(0.57, 1.44)0.81(0.50, 1.33)0.411 Arab/West Asian0.73(0.48, 1.10)0.72(0.46, 1.13)0.152 Latin American0.87(0.56, 1.34)0.87(0.57, 1.34)0.535 Mixed/Other1.09(0.80, 1.47)1.10(0.80, 1.52)0.554Ethno-cultural composition (ref = first quintile)^a^----< 0.001 second1.27(1.07, 1.51)1.23(1.02, 1.49)0.029 third1.21(1.03, 1.42)1.19(1.00, 1.42)0.051 fourth1.40(1.19, 1.64)1.43(1.20, 1.71)< 0.001 fifth (highest)1.20(0.99, 1.44)1.41(1.15, 1.73)0.001 unknown1.37(1.11, 1.70)1.46(1.13, 1.88)0.004Situational vulnerability (ref = first quintile)^b^----0.001 second0.96(0.82, 1.13)0.98(0.83, 1.17)0.825 third1.02(0.87, 1.19)0.95(0.80, 1.12)0.51 fourth1.06(0.90, 1.25)1.00(0.84, 1.20)0.996 fifth (highest)0.78(0.65, 0.93)0.68(0.56, 0.83)< 0.001 unknown^c^1.09(0.89, 1.33)---Pre-existing chronic health symptoms loss of appetite3.08(1.94, 4.89)1.96(1.21, 3.17)0.006Number of pre-existing chronic health symptoms (ref = 0)----< 0.001 1 or 21.29(1.13, 1.47)1.23(1.08, 1.41)0.003 31.74(1.43, 2.11)1.68(1.36, 2.07)< 0.001 > 32.21(1.92, 2.54)1.66(1.38, 1.99)< 0.001Months since last vaccine dose prior to the month of infection (ref = 3 months or less)----< 0.001 not vaccinated1.95(1.66, 2.29)1.47(1.13, 1.93)0.005 4–6 months1.23(1.08, 1.40)1.32(1.16, 1.51)< 0.001 > 6 months1.22(1.02, 1.46)1.28(1.06, 1.54)0.009 unknown1.11(0.76, 1.61)1.11(0.77, 1.62)0.571Time period of first infection (ref = pre-omicron)----0.007 Omicron (December 1, 2021 – date of electronic questionnaire completion)0.57(0.50, 0.66)0.67(0.52, 0.86)0.002 unknown1.14(0.42, 3.11)1.30(0.04, 47.38)0.885Household member testing positive for SARS-CoV-2 infection (ref = no)----0.001 yes0.76(0.68, 0.85)0.84(0.75, 0.95)0.005 unknown1.42(0.73, 2.77)1.79(0.91, 3.52)0.094Interaction between sex and bowel disorder----0.043 Male (ref = no bowel disorder)----- bowel disorder diagnosed less than 10 years prior to infection--1.06(0.60, 1.88)0.840 bowel disorder diagnosed 10 or more years prior to infection--0.55(0.24, 1.28)0.166 Female (ref = no bowel disorder)----- bowel disorder diagnosed less than 10 years prior to infection--0.87(0.55, 1.39)0.567 bowel disorder diagnosed 10 or more years prior to infection--1.78(1.15, 2.74)0.009 Female no bowel disorder (ref = male no bowel disorder)--1.29(1.14, 1.45)< 0.001 Female bowel disorder diagnosed less than 10 years prior to infection (ref = male bowel disorder diagnosed less than 10 years prior to infection)--1.06(0.51, 2.18)0.881 Female bowel disorder diagnosed 10 or more years prior to infection (ref = male bowel disorder diagnosed 10 or more years prior to infection)--4.16(1.62, 10.68)0.003Notes: Estimates for Canada exclude the territories. All estimates are weighted. The reference category for a pre-existing chronic condition or symptom are adults without the chronic condition or symptom, respectivelyAbbreviations: aOR = adjusted odds ratio, CI = confidence interval, n = unweighted number of respondents included in the final model, ref = reference, uOR = unadjusted odds ratiop value is only for the fully adjusted model^a^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations^b^ Situational vulnerability quantifies a neighbourhood’s education level, Indigenous composition, and extent of dwellings in need of major repairs^c^ For the dimensions of deprivation, values for an individual were either known or unknown for all dimensions. Consequently, the parameter for unknown situational vulnerability has a value of 0 in the final adjusted model because it is a linear combination of the parameter for unknown ethnocultural composition

After dichotomizing the severity of infection variable, CLC, HBP, osteoporosis, WIS, and arthritis were no longer significant. However, CFS remained significant (aOR: 2.09, 95% CI: 1.23, 3.53) and chronic kidney disease (CKD) emerged as a newly significant CC (aOR: 0.38, 95% CI: 0.15, 0.92) (Table 5). For covariates, ethnicity, situational vulnerability, household member testing positive for SARS-CoV-2 infection, and pre-existing fatigue were no longer significant. Region of residence became significant with the Prairies being the only region showing a significant difference when compared to Ontario (aOR: 0.75, 95% CI: 0.60, 0.94). Also, the number of pre-existing CCs became significant: the odds of a more severe infection were 1.72 (95% CI: 1.13, 2.61) times greater among adults with 2 CCs compared to adults with none of the CCs examined. As observed in the first sensitivity analysis, sex significantly interacted with BMI and followed the same patterns seen in Table 3.

Table 5. Odds ratios for severe^a^ acute first infection symptoms among adults with a self-reported confirmed or suspected SARS-CoV-2 infection, Canada, January 2020 to August 2022 (n = 9107)CharacteristicsuOR95% CIaOR95% CIp valuePre-existing chronic conditions chronic lung disease2.92(2.02, 4.20)1.55(0.97, 2.46)0.064 sleep apnea1.57(1.21, 2.03)0.92(0.65, 1.30)0.631 asthma1.83(1.44, 2.33)1.12(0.83, 1.50)0.469 chronic heart disease1.43(0.93, 2.20)0.82(0.50, 1.35)0.441 diabetes1.75(1.34, 2.28)1.15(0.84, 1.59)0.383 chronic kidney disease0.65(0.31, 1.38)0.38(0.15, 0.92)0.032 high blood pressure1.70(1.40, 2.06)1.17(0.88, 1.55)0.275 chronic blood disorder1.74(0.87, 3.46)0.80(0.34, 1.88)0.609 osteoporosis1.68(1.13, 2.49)0.83(0.51, 1.34)0.443 back problems2.10(1.73, 2.55)1.20(0.88, 1.63)0.247 urinary incontinence1.42(0.94, 2.16)0.74(0.47, 1.18)0.211 bowel disorder2.20(1.66, 2.92)1.17(0.83, 1.64)0.374 weakened immune system2.62(1.93, 3.56)1.40(0.94, 2.10)0.098 chronic neurological disorder2.23(1.44, 3.44)1.11(0.63, 1.93)0.724 chronic fatigue syndrome or fibromyalgia4.88(3.18, 7.47)2.09(1.23, 3.53)0.006 stroke1.20(0.57, 2.50)0.56(0.25, 1.25)0.157 mental health condition1.93(1.61, 2.32)1.15(0.86, 1.53)0.343 arthritis2.13(1.77, 2.57)1.14(0.84, 1.54)0.402Age at infection (ref = 15–34)----0.481 35–491.11(0.92, 1.33)1.06(0.87, 1.29)0.593 50–641.29(1.06, 1.56)0.98(0.78, 1.23)0.842 65+1.18(0.94, 1.48)0.85(0.62, 1.15)0.280Sex (ref = male)----- female1.33(1.16, 1.56)Interaction--Number of pre-existing chronic health conditions (ref = 0)----0.013 11.35(1.11, 1.63)1.10(0.85, 1.42)0.475 22.62(2.10, 3.28)1.72(1.13, 2.61)0.011 32.50(1.92, 3.27)1.34(0.76, 2.35)0.314 > 33.48(2.74, 4.43)1.28(0.55, 2.98)0.565Ethno-cultural composition (ref = first quintile)^b^----0.014 second1.38(1.08, 1.75)1.32(1.02, 1.71)0.036 third1.12(0.89, 1.41)1.11(0.85, 1.44)0.435 fourth1.16(0.92, 1.47)1.26(0.97, 1.63)0.089 fifth (highest)1.27(0.97, 1.65)1.35(1.00, 1.82)0.047 unknown1.47(1.11, 1.95)1.71(1.25, 2.35)0.001Region of residence (ref = Ontario)----0.012 British Columbia1.14(0.92, 1.41)1.10(0.88, 1.39)0.408 Prairies0.89(0.73, 1.09)0.75(0.60, 0.94)0.011 Quebec0.77(0.63, 0.94)0.89(0.71, 1.11)0.289 Atlantic Canada0.95(0.78, 1.15)0.97(0.77, 1.21)0.768Body mass index (BMI) (ref = underweight and normal weight (BMI < 25 kg/m2))----- overweight  (25 kg/m2 < = BMI < 30 kg/m2)1.00(0.83, 1.21)Interaction-- obese (BMI > = 30 kg/m2)1.63(1.35, 1.98)Interaction-- unknown1.22(0.69, 2.18)Interaction--Pre-existing chronic health symptoms loss of appetite3.63(2.33, 5.63)2.13(1.31, 3.46)0.002Number of pre-existing chronic health symptoms (ref = 0)----< 0.001 1 or 21.51(1.25, 1.83)1.37(1.12, 1.67)0.002 31.87(1.44, 2.43)1.62(1.21, 2.16)0.001 > 32.86(2.39, 3.43)1.87(1.45, 2.39)< 0.001Months since last vaccine dose prior to the month of infection (ref= <=3 months)< 0.001 Not vaccinated2.73(2.22, 3.34)1.76(1.31, 2.37)< 0.001 4–6 months1.19(0.96, 1.47)1.29(1.04, 1.61)0.019 > 6 months1.52(1.17, 1.97)1.67(1.27, 2.19)< 0.001 Unknown1.60(0.95, 2.71)1.28(0.75, 2.19)0.362Time period of first infection (ref = pre-omicron)----< 0.001 Omicron  (December 1, 2021 – date of electronic questionnaire completion)0.41(0.35, 0.48)0.50(0.38, 0.66)< 0.001 unknown1.48(0.56, 3.87)1.95(0.68, 5.54)0.212Interaction between sex and BMI----0.003 male (ref = underweight or normal weight)----- overweight--1.27(0.89, 1.81)0.183 obese--2.21(1.54, 3.18)< 0.001 unknown2.88(0.15, 53.63)0.478female (ref = underweight or normal weight)----- overweight--0.92(0.71, 1.21)0.562 obese--1.02(0.80, 1.31)0.848 unknown0.73(0.38, 1.40)0.346 female underweight or normal weight (ref = male underweight or normal weight)--1.81(1.27, 2.56)0.001 female overweight (ref = male overweight)--1.31(1.00, 1.72)0.051 female obese (ref = male obese)--0.84(0.64, 1.09)0.180 female unknown (ref = male unknown)--0.46(0.02, 8.96)0.607Notes: Estimates for Canada exclude the territories. All estimates are weighted. The reference category for a pre-existing chronic condition or symptom are adults without the chronic condition or symptom, respectivelyAbbreviations: aOR = adjusted odds ratio, CI = confidence interval, n = unweighted number of respondents included in the final model, ref = reference, uOR = unadjusted odds ratiop value is only for the fully adjusted model^a^ Severe symptoms were defined as significantly affecting daily life or requiring hospitalization^b^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations

Excluding individuals with missing chronic condition diagnosis dates resulted in little changes when compared to Table 2 (Table 6). Only pre-existing fatigue was no longer significant, while pre-existing symptoms relating to the heart became significant.

Table 6. Odds ratios for more severe acute first infection symptoms among adults with a self-reported confirmed or suspected SARS-CoV-2 infection, Canada, January 2020 to August 2022 (excludes respondents with missing chronic condition diagnosis dates) (n = 9026)CharacteristicsuOR95% CIaOR95% CIp valuePre-existing chronic conditions chronic lung disease2.39(1.65, 3.45)1.64(1.08, 2.47)0.020 sleep apnea1.42(1.14, 1.76)1.18(0.93, 1.49)0.180 asthma1.59(1.30, 1.96)1.22(0.98, 1.52)0.075 chronic heart disease1.16(0.83, 1.64)0.76(0.52, 1.12)0.166 diabetes1.12(0.85, 1.46)0.89(0.66, 1.19)0.431 chronic kidney disease1.13(0.71, 1.80)0.96(0.54, 1.69)0.882 high blood pressure1.36(1.17, 1.60)1.32(1.11, 1.58)0.002 chronic blood disorder1.19(0.59, 2.40)0.65(0.30, 1.43)0.286 osteoporosis1.08(0.71, 1.63)0.59(0.39, 0.89)0.012 back problems1.63(1.37, 1.95)1.12(0.92, 1.38)0.266 urinary incontinence1.30(0.94, 1.80)0.90(0.63, 1.26)0.525 bowel disorder1.68(1.27, 2.23)1.08(0.82, 1.42)0.599 weakened immune system2.37(1.77, 3.16)1.48(1.08, 2.02)0.014 chronic neurological disorder1.71(1.09, 2.70)0.93(0.59, 1.48)0.760 chronic fatigue syndrome or fibromyalgia4.57(3.00, 6.97)2.12(1.34, 3.36)0.001 stroke1.06(0.58, 1.94)0.78(0.40, 1.51)0.454 mental health condition1.64(1.39, 1.94)1.10(0.91, 1.32)0.326 arthritis1.70(1.44, 2.00)1.24(1.01, 1.52)0.044Age at infection (ref = 15–34)----< 0.001 35–491.02(0.90, 1.16)1.04(0.91, 1.19)0.559 50–641.10(0.96, 1.26)0.96(0.83, 1.12)0.628 65+0.87(0.74, 1.02)0.67(0.55, 0.83)< 0.001Sex (ref = male)----< 0.001 female1.44(1.29, 1.60)1.31(1.16, 1.47)< 0.001Ethnicity (ref = white)----0.023 Indigenous1.26(0.97, 1.64)1.14(0.87, 1.50)0.338 South Asian0.97(0.71, 1.32)0.93(0.66, 1.29)0.648 East/Southeast Asian0.64(0.51, 0.80)0.62(0.49, 0.79)< 0.001 Black0.90(0.57, 1.44)0.81(0.50, 1.32)0.400 Arab/West Asian0.73(0.48, 1.10)0.72(0.46, 1.13)0.152 Latin American0.87(0.56, 1.34)0.89(0.57, 1.37)0.582 Mixed/Other1.09(0.80, 1.47)1.09(0.79, 1.51)0.597Ethno-cultural composition (ref = first quintile)^a^----0.002 second1.27(1.07, 1.51)1.25(1.04, 1.51)0.016 third1.21(1.03, 1.42)1.19(1.00, 1.42)0.052 fourth1.40(1.19, 1.64)1.43(1.20, 1.70)< 0.001 fifth (highest)1.20(0.99, 1.44)1.39(1.13, 1.71)0.002 unknown1.37(1.11, 1.70)1.44(1.12, 1.87)0.005Situational vulnerability (ref = first quintile)^b^----0.001 second0.96(0.82, 1.13)0.97(0.82, 1.15)0.716 third1.02(0.87, 1.19)0.95(0.80, 1.12)0.517 fourth1.06(0.90, 1.25)0.98(0.82, 1.17)0.851 fifth (highest)0.78(0.65, 0.93)0.68(0.56, 0.82)< 0.001 unknown^c^1.09(0.89, 1.33)---Pre-existing chronic health symptoms symptoms relating to the heart1.94(1.53, 2.47)1.33(1.01, 1.75)0.039 loss of appetite3.08(1.94, 4.89)1.80(1.11, 2.92)0.017Number of pre-existing chronic health symptoms (ref = 0)----< 0.001 1 or 21.29(1.11, 1.47)1.21(1.06, 1.39)0.005 31.74(1.43, 2.11)1.64(1.33, 2.03)< 0.001 > 32.21(1.92, 2.54)1.60(1.32, 1.93)< 0.001Months since last vaccine dose prior to the month of infection (ref = 3 months or less)----< 0.001 not vaccinated1.96(1.67, 2.30)1.49(1.14, 1.93)0.003 4–6 months1.23(1.08, 1.40)1.33(1.16, 1.51)< 0.001 > 6 months1.22(1.02, 1.46)1.28(1.06, 1.54)0.009 unknown1.11(0.76, 1.61)1.04(0.72, 1.50)0.822Time period of first infection (ref = pre-omicron)----0.004 Omicron (December 1, 2021 – date of electronic questionnaire completion)0.57(0.50, 0.66)0.67(0.53, 0.87)0.002 unknown1.14(0.42, 3.11)1.48(0.50, 4.37)0.482Household member testing positive for SARS-CoV-2 infection (ref = no)----0.001 yes0.76(0.68, 0.85)0.84(0.74, 0.94)0.004 unknown1.42(0.73, 2.77)1.77(0.90, 3.49)0.099Notes: Estimates for Canada exclude the territories. All estimates are weighted. The reference category for a pre-existing chronic condition or symptom are adults without the chronic condition or symptom, respectivelyAbbreviations: aOR = adjusted odds ratio, CI = confidence interval, n = unweighted number of respondents included in the final model, ref = reference, uOR = unadjusted odds ratiop value is only for the fully adjusted model^a^ Ethno-cultural composition quantifies a neighbourhood’s makeup of immigrant populations^b^ Situational vulnerability quantifies a neighbourhood’s education level, Indigenous composition, and extent of dwellings in need of major repairs^c^ For the dimensions of deprivation, values for an individual were either known or unknown for all dimensions. Consequently, the parameter for unknown situational vulnerability has a value of 0 in the final adjusted model because it is a linear combination of the parameter for unknown ethnocultural composition

Discussion

We used data from a large population-based Canadian survey to examine relationships between pre-existing CCs and severity of acute SARS-CoV-2 infection. Among adults with a confirmed or suspected SARS-CoV-2 infection, six of the 21 examined CCs were significantly associated with more severe infection as measured by their impact on daily life. When limiting the analyses to confirmed infections, we found that those with pre-existing mental health conditions also had greater odds of more severe infection.

Depending on the CC, our findings deviate from or corroborate the existing evidence, which is mainly based on populations accessing health care services following infection. A systematic review identified strong relationships between COVID-19 severity, defined as mortality or the most severe outcome such as intensive care unit (ICU) admission, and chronic obstructive lung disease (COPD), chronic kidney disease, cardiovascular diseases, hypertension, and diabetes [39]. We also found that CLCs, including COPD, and hypertension were significantly associated with more severe infection. However, we found no relationship for diabetes and chronic kidney disease. For those with a weakened immune system, our findings support the evidence that the immunocompromised subpopulation is at increased risk of severe SARS-CoV-2 infection outcomes [40, 41]. The lack of association between certain CCs and severity of infection could be caused, at least in part, by the correlations between CCs. For example, among adults with confirmed and suspected infections, those with hypertension were about six times more likely to have diabetes (19.6% vs. 3.3%, p < 0.0001) and about five times more likely to have chronic kidney disease (2.0% vs.0.4%, p < 0.0001) compared to those without hypertension.

A Swedish study found that a SARS-CoV-2 infection can be a potent trigger for reactivation of latent herpes viruses and endogenous retroviruses in those with pre-existing CFS [42]. There is a paucity of research evaluating COVID-19 severity in those with pre-existing fibromyalgia; we identified only one study, which found no association between fibromyalgia and hospitalization for COVID-19^27^. One proposed mechanism is that since fibromyalgia is triggered by mental stress and anxiety, the indirect impact of the COVID-19 pandemic could have triggered a more severe manifestation of fibromyalgia that coincided with an actual infection [43].

Potential contributors to differing results between this study and existing evidence are the source population of participants and methods of measuring severity of infection. Our study did not require a healthcare encounter for eligibility and captured a broader spectrum of severity of infection while most other studies identified participants from those seeking care for their symptoms and focussed on severe outcomes like hospitalization, ICU admission or death. Individuals who seek medical care for COVID-19 are likely having more severe symptoms or perceive their symptoms as severe enough to seek care. Additionally, individuals who have died due to COVID-19 were not captured by CCAHS-2. If this population had been captured, stronger relationships for several CCs and covariates may have been observed [44, 45]. This methodological difference could also explain some of our counterintuitive findings. Specifically, significant protective effects were associated with being male, aged 65 + years at infection, and living in a remote community and/or neighbourhood with high situational vulnerability (i.e., low education level, high Indigenous composition, and high proportion of dwellings in need of major repairs), all characteristics related to a higher risk of mortality from COVID-19 [44,46]. It can also explain why no significant relationship was found for diabetes and CKD, as those living with these CCs have a higher risk of mortality following SARS-CoV-2 infection than those without the respective CC [47, 48].

This limitation may also help explain the observed significant protective effect of osteoporosis. Ahn et al. found that individuals with a history of osteoporosis who contracted a SARS-CoV-2 infection did not experience significant differences in most clinical outcomes compared to those without such a history [49]. However, osteoporosis patients with a history of fracture had an elevated risk of severe complications, while osteoporosis patients without fractures had a lower risk compared to those without osteoporosis. Given that fractures are a common consequence of osteoporosis, and osteoporosis patients with fractures tend to experience high mortality rates regardless of COVID-19 status, excluding this high-risk subpopulation may bias the results toward a protective effect [50, 51].

For the other covariates, our findings support the literature showing more severe infections were associated with pre-Omicron infections [52] and being unvaccinated or not recently vaccinated [53]. The protective effect of having a household member testing positive for SARS-CoV-2 infection could result from being better prepared for the perceived impacts of the infection.

Limiting the modeling to adults with confirmed infections had an impact on some of the variables retained and adjusted associations. This may be due to excluding suspected infections that were unrelated to SARS-CoV-2, as well as clinical differences in patients with confirmed vs. suspected infections. Observed differences may also arise from the exclusion of adults suspecting an infection earlier in the pandemic when testing capacity was limited and health outcomes were worse [52].

Redefining the CC variables to include duration of CC (diagnosed either less than 10 years or 10 or more years prior to infection) resulted in minimal changes to the retained variables and adjusted associations. Sex and pre-existing chronic bowel disorders significantly interacted in their relationship with SARS-CoV-2 infection severity. To our knowledge, this interaction has not been previously identified and may reflect sex differences in the experiences of people with inflammatory bowel disorders. Other research indicates that females experience a worse quality of life and higher psychological distress than males, while males experience more bowel-related surgeries and higher mortality risk than females [54, 55].

When severity was redefined as a binary variable, many of the CCs loss statistical significance. This could be attributed to misclassification of moderate and severe infection symptoms biasing associations toward the null, the addition of number of pre-existing chronic conditions to the model, or the greater importance of other included covariates when examining associations with severe infections.

Excluding individuals with missing chronic condition diagnosis dates from the analytical sample resulted in minimal changes to the final model. Pre-existing fatigue was no longer significant, while pre-existing symptoms relating to the heart became significant. Most odds ratios were unaffected. These results indicate that our approach for handling adults with missing chronic condition diagnosis dates did not introduce bias.

To our knowledge, there is limited research reporting interactions between BMI and sex when examining severity of SARS-CoV-2 infections. A Brazilian study looking at mortality amongst obese individuals hospitalized with COVID-19 found that the more obese a male was, the higher were the odds of mortality, whereas the odds of death among females increased only among those with a BMI of ≥ 50 kg/m^2^ [56]. Additionally, Yamamoto et al. found that higher BMI was associated with lower SARS-CoV-2 spike antibody titers from vaccination in men, but not in females [57]. This suggests that vaccinated males with higher BMI are more at risk for severe COVID-19 outcomes than vaccinated females of comparable BMI which aligns with our findings.

Strengths and limitations

The primary strength of our study is that it is population-based and considers a wide range of individual characteristics. CCAHS-2 captured dates for SARS-CoV-2 infection, CC diagnosis, chronic health symptom occurrence, and vaccination. Using this data, we were able to determine the temporality of CCs, CHSs and vaccinations in relation to the infection. We also included individuals who suspected they had a SARS-CoV-2 infection but could not access COVID-19 testing or chose not to be tested. This approach increases the applicability of our findings to the general population.

One of the limitations of this study is that those who have died due to COVID-19-related causes were not included. Consequently, the subpopulation who had the most severe SARS-CoV-2 infections were not included in the statistical modelling which could have resulted in lower odds ratio estimates for pre-existing CCs. This effect would be greater for CCs that have established links to higher COVID-19-related mortality. Although the focus of this study was to estimate the impact on daily lives, including the subpopulation who died would have generated more universally interpretable estimates. Another limitation is that a respondent may have been unknowingly infected prior to their first reported SARS-CoV-2 infection. As a result, the severity of their first reported infection could be influenced by CHSs from long COVID. Additional limitations are inherent with survey data, such as selection bias, recall error, lack of objective measures of infection severity, and inaccurate infection status information. While the validity of self-reported data is subject to many biases, it remains a valuable and commonly used tool for assessing a respondent’s subjective experiences. Additionally, rigorous planning and quality assurance were undertaken at all stages of the survey design and conduct to mitigate the impact of these biases [32, 35]. Only 25.3% of adults invited to participate were included in the share file used for analysis. As outlined in the methodology, variables highly correlated with responding to the survey were used to adjust survey weights to minimize non-response bias arising from identified differences between respondents and non-respondents. Although weights were adjusted for non-response and calibrated to reflect the target population using auxiliary information, the potential for biased estimates remains if those who participated and agreed to share their data systematically differed from the target population in ways not corrected through weighting. The low response rate also compromised the study’s power to detect statistically significant associations. Due to limited testing capacity early in the pandemic, we included adults who reported a suspected infection in our main analyses; however, some suspected infections may have been the consequence of conditions or infections unrelated to SARS-CoV-2. Conversely, other respondents may have been unaware of a past SARS-CoV-2 infection or may have inappropriately ascribed COVID-19 symptoms to other conditions or infections. To partly address these issues, we performed sensitivity analyses that limited modeling to adults testing positive for SARS-CoV-2 infection.

Conclusion

The aim of this study was to characterize the association between pre-existing CCs and SARS-COV-2 infection severity among the Canadian adult population by measuring impacts on daily life. The findings suggest that a greater focus should be placed on those who are immunocompromised or have pre-existing CLC, hypertension, fibromyalgia or CFS, arthritis, or mental health condition. Individuals living with these CCs should be informed of the greater impact a SARS-CoV-2 infection can have on their lives so they can take measures to reduce their risk of infection. Targeted prevention strategies and early interventions in this population can help minimize the impact of infection and the burden on health resource.