Respiratory Medicine xxx (xxxx) xxx Please cite this article as: Andie MacNeil, Respiratory Medicine, https://doi.org/10.1016/j.rmed.2022.107003 0954-6111/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). Original Research Incident and recurrent depression among older adults with asthma during the COVID-19 pandemic: Findings from the Canadian Longitudinal Study on Aging Andie MacNeil a,b, Grace Li c, Ying Jiang d, Margaret de Groh d, Esme Fuller-Thomson a,b,* a Factor-Inwentash Faculty of Social Work, University of Toronto, Canada b Institute for Life Course and Aging, University of Toronto, Canada c Department of Sociology, University of Victoria, Canada d Applied Research Division, Center for Surveillance and Applied Research, Public Health Agency of Canada, Canada A R T I C L E I N F O Keywords: Asthma Depression Older adults COVID-19 CLSA A B S T R A C T Objectives: (1) In a subsample of older adults with asthma without a history of depression, to determine the factors associated with developing depression during the COVID-19 pandemic; (2) in a subsample of older adults with asthma with a history of depression, to identify factors associated with recurrent depression during the pandemic. Methods: Data came from four waves (Baseline [2011–2015], Follow-up 1 [2015–2018]; COVID Spring 2020, COVID Autumn 2020) of the Canadian Longitudinal Study on Aging’s comprehensive cohort (n = 2,047 with asthma). The outcome of interest was a positive screen for depression based on the CES-D-10 during the autumn of 2020. Bivariate and multivariate logistic regression analyses were conducted. Results: Among older adults with asthma without a history of depression (n = 1,247), approximately 1 in 7 (13.5%) developed depression for the first time during the COVID-19 pandemic. Among those with a history of depression (n = 770), approximately 1 in 2 (48.6%) experienced a recurrence of depression. The risk of incident depression and recurrent depression was higher among those who were lonely, those experiencing family conflict during the pandemic, and those who had difficulty accessing healthcare resources during the pandemic. The risk of incident depression only was higher among those who had difficulty accessing resources and/or loss of income during the pandemic. The risk of recurrent depression only was higher among those with functional limitations. Conclusions: There is a need for targeted interventions to support the mental health of older adults with asthma who have the above identified vulnerabilities during the pandemic. 1. Introduction COVID-19 is a respiratory illness caused by SARS-CoV-2 that can lead to lung damage, respiratory failure, and death. Individuals with asthma typically have an increased susceptibility to respiratory viral infections [1]. Consequently, individuals with asthma were labelled early in the COVID-19 pandemic as “high risk” for COVID-19 infection and severe COVID-19 related outcomes, resulting in this population being strongly urged to strictly adhere to physical distancing and lockdown measures. However, more recent evidence suggests that asthma does not increase one’s likelihood of COVID-19 infection [2], and further that asthma is not associated with heightened disease severity [3]. There is concern that the earlier emphasis that people with asthma should rigidly adhere to distancing guidelines combined with the stress of being labelled “high risk” may have led to worsening mental health outcomes, such as in- creases in depressive symptoms, within this population [4]. Research conducted prior to the pandemic has indicated a high co- morbidity between asthma and depression [5,6]. A recent meta-analysis of prospective studies on the temporal association between these two conditions found depression to be strongly associated with adult-onset asthma [7]. While the authors found no association between asthma and subsequent depression, they suggested this may be due to the limited number of prospective studies examining this relationship [7]. Although some cross-sectional research has found asthma to be * Corresponding author. Institute for Life Course & Aging, Factor-Inwentash Faculty of Social Work, Cross-appointed to Faculties of Medicine & Nursing, University of Toronto, 246 Bloor St. West, Toronto, ON, M5S 1V4, Canada. E-mail address: esme.fuller.Thomson@utoronto.ca (E. Fuller-Thomson). Contents lists available at ScienceDirect Respiratory Medicine journal homepage: www.elsevier.com/locate/rmed https://doi.org/10.1016/j.rmed.2022.107003 Received 2 July 2022; Received in revised form 17 September 2022; Accepted 24 September 2022 mailto:esme.fuller.Thomson@utoronto.ca www.sciencedirect.com/science/journal/09546111 https://www.elsevier.com/locate/rmed https://doi.org/10.1016/j.rmed.2022.107003 https://doi.org/10.1016/j.rmed.2022.107003 https://doi.org/10.1016/j.rmed.2022.107003 http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ Respiratory Medicine xxx (xxxx) xxx 2 associated with current depressive symptoms and lifetime depression, the cross-sectional nature of these findings prohibits determining the temporal relationship of these conditions [8], emphasizing the need for further longitudinal research to examine this relationship. When considering the high comorbidity between asthma and depression prior to the pandemic, combined with the unprecedented challenges of the COVID-19 pandemic and associated lockdowns for people with asthma, it is evident that there is a need for longitudinal research to examine the relationship between asthma and depression during the pandemic. In order to address this gap in the literature, the current study uses a large Canadian longitudinal panel study of older adults to achieve the following objectives: (1) in a subsample of older adults with asthma without a history of depression, to determine the factors associated with developing incident depression during the COVID-19 pandemic; (2) in a subsample of older adults with asthma with a history of depression, to identify factors associated with recur- rence of depression during the pandemic. We hypothesize that older adults with asthma are vulnerable to incident and recurrent depression during the COVID-19 pandemic. We also hypothesize those with low socioeconomic status are more vulnerable to depression than their peers with higher socioeconomic status due to the financial strain that COVID- 19 has placed on many low-income individuals. 2. Methods 2.1. Data source Data were drawn from the Baseline, Follow-up 1, and COVID Spring 2020, and COVID Autumn 2020 waves of the comprehensive cohort of Canadian Longitudinal Study on Aging (CLSA). The CLSA is a national study of Canadian residents aged 45 to 85 between 2011 and 2015 across 7 provinces [9]. The CLSA also collected data about COVID-19, either online or by telephone with all CLSA respondents who agreed to participate. The baseline comprehensive cohort recruited 30,097 community-living men and women in Canada. The study was designed to follow participants every 3 years after baseline for at least 20 years or until death [9]. In total, 27,737 participants of the comprehensive cohort completed the first Follow-up wave (hereafter Follow-up 1) by 2018. In order to investigate the impact of the COVID-19 pandemic among older Canadians, 18,530 and 15,544 of the participants in the comprehensive cohort completed the COVID-19 Spring 2020 and Autumn 2020 questionnaires (hereafter Spring 2020 and Autumn 2020, respectively). Respondents who were lost to follow-up or had missing data on key covariates were excluded from the analysis. A detailed description of the CLSA can be found elsewhere [9]. 2.2. Sample The sample consisted of respondents who had asthma in either Baseline or Follow-up 1 (n = 2,017) prior to the COVID-19 pandemic. Self-reported asthma was measured by the question, “Has a doctor ever told you that you have asthma?” (yes vs. no). Among those with asthma, 1,247 had no pre-pandemic history of depression and 770 had a history of depression. 2.3. Measures The outcome of interest, depression, was assessed by administering the short form of the Centre for Epidemiologic Studies – Depression (CES-D-10) scale [10]. Ten questions addressing, for example, feelings of depression, loneliness, hopefulness for the future, and restless sleep, are summed to generate a total score between 0 and 30 with higher scores indicating a greater number of symptoms. The positive screen for depression was coded 1 if the CES-D-10 score was 10 or more and 0 otherwise [10]. The CES-D-10 is a well-established, psychometrically sound, single-factor measure of depression with well-documented reliability and validity for screening depressive symptoms among com- munity dwelling older adults [11]. To identify pre-pandemic history of depression, four measures were used. The CES-D-10 scores at Baseline and Follow-up 1 wave of data collection were assessed. At both Baseline and Follow-up 1 the respondents were also asked: “Has a doctor ever told you that you suffer from clinical depression?“. If respondents answered no at both the Baseline and Follow-up 1 waves of data collection, and screened negative on the CES-D-10 in both waves, the respondent was classified as having no pre-pandemic history of depression. If at least one of the above four measures indicated depression, the respondent was classified as having a pre-pandemic history of depression. Demographic factors include age at the Autumn 2020 wave, sex (male vs. female), and marital status (married/common-law, separated/ divorced/widowed, single/never married or lived with a partner). Immigrant status was categorized into two groups based on country of origin (Canadian-born vs. immigrant). Visible minority status was classified as white vs. non-white. Socioeconomic status was measured by education, household in- come, home ownership, total savings, and whether income satisfies basic needs. We operationalized education as the highest level of edu- cation achieved, categorized as less than secondary school, secondary school/some post-secondary, and post-secondary degree/diploma. Household income was defined as total household income from all sources by all family members in the past 12 months (less than $50,000, $50,000–$99,999, $100,000 or more, and not answered). Home ownership had three categories (rent, own with mortgage, own without mortgage). Total saving had four categories (less than $50,000, $50,000–$99,999, $100,000 or more, and not answered). Whether in- come satisfies basic needs was measured by a dummy variable (0 = with some difficulty/not very well/totally inadequate; and 1 = very well/ adequately). Health-related variables include body mass index (BMI), chronic pain, and multimorbidity. BMI was classified into three clusters: un- derweight/normal weight (BMI <25.0); overweight (BMI = 25.0–29.9); and obese (BMI ≥30.0). Chronic pain was a dummy variable (free of chronic pain vs. have chronic pain). Multimorbidity was defined as having multiple chronic conditions (zero, one, two, three or more, missing). These chronic conditions include (1) diabetes, (2) heart dis- ease, (3) peripheral vascular disease or poor circulation in limbs, (4) dementia or Alzheimer’s disease, (5) multiple sclerosis, (6) epilepsy, (7) migraine headaches, (8) intestinal or stomach ulcers, (9) bowel disorder, (10) stroke or CVA (cerebrovascular accident), (11) glaucoma, (12) kidney disease, (13) macular degeneration, (14) ministroke or TIA (Transient Ischemic Attack), and (15) Parkinson’s Disease, and (16) cancer. Adverse childhood experiences (ACEs) were measured by childhood physical abuse, childhood sexual abuse, childhood exposure to chronic intimate partner violence, and being neglected. Childhood physical abuse was present if the respondent reported being kicked, bit or punched, or choked, burned or physically attacked in some other way one or more times. Childhood sexual abuse was present if respondents reported an adult forcing them or attempting to force them into any unwanted sexual activity by threatening them, holding them down, or hurting them in some way one or more times. Childhood exposure to chronic intimate partner violence was present if respondents reported seeing or hearing parents, step-parents or guardians hitting each other more than 10 times. Respondents being neglected were present if they reported their parents or guardians not having taken care of their basic needs such as keeping clean or providing food or clothing one or more times. Respondents were also asked: “How often do you feel that you lack companionship?“, “How often do you feel left out?“, and “How often do you feel isolated from others?“. The three variables were coded as 1 = often and 0 = hardly ever/some of the time. Religiosity was measured by two questions: “In the past 12 months, A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 3 how often did you participate in church or religious activities?” (here- after, church activities) and “In the past 12 months, how often did you engage in religious or spiritual activities including prayer, meditation taking place at home?“ (hereafter, pray at home). If respondents had taken part in these activities at least once a month, then they were coded as often (=1) otherwise rare (=0). At the beginning of the COVID-19 pandemic, the Spring 2020 questionnaire asked respondents whether they left home or not in the past month. Moreover, respondents’ loneliness during the Spring 2020 wave was operationalized using the question, “How often did you feel lonely?” (rarely or never/some of the time [0–2 days per week] vs. oc- casionally/all of the time [3–7 days per week]). The type of dwelling during the COVID-19 was classified as the house, apartment, and other. There was a dummy variable indicating whether respondents lived alone or not during the beginning of the COVID-19 pandemic. The functional limitation scale included three questions: “Do you have any difficulty standing up after sitting in a chair”, “Do you have any difficulty walking alone up and down a flight of stairs?“, and “Do you have any difficulty walking 2 to 3 neighborhood blocks?“. If respondents answered all three questions as no, then they were coded as 0, otherwise 1. COVID-19 related stressors were measured at the Autumn 2020 wave. They were investigated in a section of the survey which was preceded by the following instructions: “Which of the following have you experienced during the COVID-19 pandemic?” COVID-19 related stressors/experiences were categorized into five composite indicators. Experiences were grouped as “yes” if the participants responded yes to at least one experience in the specific category or no if the participant responded no to all questions in that category. Questions related to health stressors included, “You were ill”, “People close to you were ill”, and/or “Death of a person close to you”. Questions related to difficulties with accessing resources included “Loss of income” and/or “Unable to access necessary supplies or food”. Questions related to family conflict included “Increased verbal or physical conflict” and/or “Breakdown in family/marital relationships”. Questions related to other family issues included “Separation from family”, “Increased time caregiving”, and/or “Unable to care for people who require assistance due to health condi- tion or limitation”. Questions related to health care included “Unable to access my usual healthcare”. Questions related to medication included “Unable to get my usual prescription medications and treatments”. 2.4. Statistical analyses The analysis was conducted in several steps. First, the prevalence of incident and recurrent depression was generated for those with and without asthma. Descriptive statistics were used to characterize the CLSA participants with asthma, both with and without a pre-pandemic history of depression. We further compared the distribution of key risk factors among older adults with asthma with no history of pre-pandemic depression who did not develop depression and those who develop depression, and older adults with asthma with a history of pre-pandemic of depression who did not and those who did develop depression during the pandemic. In order to compare the pandemic incidence and recur- rent depression rates to pre-pandemic rates, we conducted a sensitivity analysis examining changes in depression from Baseline to Follow-up 1. Chi-square tests and independent t-tests were used to test the statistical differences at the bivariate level. Second, multivariate analyses were conducted using logistic regression to calculate odds ratios (ORs) and 95% confidence interval (95% CI). The dependent variable is based on the presence or absence of a positive screen for depression based on the CES-D-10 scores at the Autumn 2020 survey. All hypothesis tests were two-sided and p-values less than 0.05 were considered statistically sig- nificant. In order to evaluate the goodness-of-fit of logistic models, Nagelkerke R square was reported. We calculated the variance inflation factor (VIF) to assess the multicollinearity among the independent var- iables in the logistic regression. The VIF values were all below 5, which suggests multicollinearity is not problematic. Data manipulation and statistical analyses were performed using R version 4.1.3. 3. Results Among those with a history of depression, the recurrence of depressive symptoms during autumn of 2020 was significantly (p < 0.01) higher for those asthma (prevalence = 48%; 95% CI = 45%, 52%) compared to those who did not have asthma (prevalence = 43%; 95% CI = 41%, 44%). Among those without a history of depression, the prev- alence of depressive symptoms during autumn of 2020 was not statis- tically significantly different (p = 0.14) between those who had asthma (prevalence = 14%; 95% CI = 12%, 15%) compared to those without asthma (prevalence = 12%; 95% CI = 11%, 13%). In light of the sig- nificant difference found between those with and without asthma in the prevalence of recurrent depression, this paper is focused solely on the sample of those with asthma. Table 1 presents sample characteristics of individuals with asthma by pre-pandemic depression status (estimated using CES-D-10 score and clinical depression diagnosis). A larger proportion of female respondents had a pre-pandemic history of depression than male respondents. A higher proportion of separated/divorced/widowed respondents and single respondents had a pre-pandemic history of depression than those who were married or living common-law. Sociodemographic and health-related variables were different between those who were free of pre-pandemic depression and who had a history of depression. Re- spondents who had no history of pre-pandemic depression were more likely to have a higher level of education, higher household income, to own their home without mortgage, to have more savings, to have enough income to satisfy needs, to be under or normal weight, free of chronic pain, and to be without any chronic conditions when compared to those who had a history of pre-pandemic depression. A higher pro- portion of respondents who had a history of pre-pandemic depression reported they had a lack of companionship, felt left out, felt isolated from others, felt lonely during the pandemic, had functional limitations, and that they had COVID-related stressors. Table 2 displays the characteristics of individuals with asthma with or without a history of depression who experienced depressive symp- toms during the pandemic. Among respondents with asthma with no history of pre-pandemic depression, 13.4% developed depressive symptoms for the first time during the pandemic. Among respondents with asthma with a history of pre-pandemic depression, nearly half experienced recurrent depressive symptoms (48.2%). The prevalence of recurrent depression varied by depression history. More than three quarters (78.1%) of those who screened positive for depression based on CES-D-10 scores in both the Baseline and Follow-up 1 waves experi- enced depressive symptoms during the pandemic. A little over half (57.3%) of those who screened positive for depression based on CES-D- 10 scores at Follow-up 1, but not at Baseline, experienced depressive symptoms during the pandemic. Two fifths (40.9%) of those with depression based on CES-D-10 scores at Baseline, but not at Follow-up 1, experienced depressive symptoms during the pandemic. Fewer than one-third of those (30.1%) who screened negative for depression based on CES-D-10 scores at both Baseline or Follow-up 1, but who reported that they had been diagnosed by a health professional at some point in their life experienced depressive symptoms during the pandemic. We conducted a sensitivity analysis to compare these findings on incident and recurrent depression among older adults with asthma during the COVID-19 pandemic with the incident and recurrence of depression from the Baseline to the Follow-up 1 wave. Among those who reported they had no history of depression and a CES-D-10 score less than 10 at Baseline, the incidence of new depressive symptoms at Follow-up 1 (prior to the pandemic) according to the CES-D-10 was 6.8% (95% CI: 5.4%, 8.2%). Among those who had a CES-D-10 score of 10 or more and/or a self-reported history of a medical diagnosis of depression at Baseline, the prevalence of recurrent depressive symptoms A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 4 Table 1 Characteristics of CLSA respondents with asthma (n = 2,017). Overall sample of older adults with asthma (n = 2,017) Older adults with asthma with no pre-pandemic history of depression (n = 1,247) Older adults with asthma with a pre-pandemic history of depression (n = 770) p-value Source of data Depression during CLSA COVID-19 Exit Survey 2020 <0.001 CLSA Autumn 2020 No 1,479 (73.3%) 1080 (86.6%) 399 (51.8%) Yes 538 (26.7%) 167 (13.4%) 371 (48.2%) Age (Mean, SD) 61.1 (8.9) 61.3 (9.0) 60.7 (8.8) 0.127 CLSA Autumn 2020 Sex <0.001 CLSA Baseline Female 1,207 (59.8%) 675 (54.1%) 532 (69.1%) Male 810 (40.2%) 572 (45.9%) 238 (30.9%) Marital status <0.001 CLSA Follow-up 1 Married/Common-law 1,373 (68.1%) 940 (75.4%) 433 (56.2%) Separated/Divorced/Widowed 426 (21.1%) 209 (16.8%) 217 (28.2%) Single 218 (10.8%) 98 (7.9%) 120 (15.6%) Immigrant status 0.611 CLSA Baseline No 1,688 (83.7%) 1,039 (83.3%) 649 (84.3%) Yes 329 (16.3%) 208 (16.7%) 121 (15.7%) Visible minority status 0.138 CLSA Baseline No 1,916 (95.0%) 1,177 (94.4%) 739 (96.0%) Yes 101 (5.0%) 70 (5.6%) 31 (4.0%) Education <0.001 CLSA Baseline Less than secondary school 68 (3.4%) 25 (2.0%) 43 (5.6%) Some post-secondary school 263 (13.0%) 152 (12.2%) 111 (14.4%) Post-secondary degree/diploma 1,686 (83.6%) 1,070 (85.8%) 616 (80.0%) Household income <0.001 CLSA Follow-up 1 Less than $50,000 423 (21.0%) 190 (15.2%) 233 (30.3%) $50,000–$99,999 700 (34.7%) 432 (34.6%) 268 (34.8%) $100,000 or more 789 (39.1%) 569 (45.6%) 220 (28.6%) Missing 105 (5.2%) 56 (4.5) 49 (6.4) Home ownership <0.001 CLSA Follow-up 1 Rent 264 (13.1%) 111 (8.9%) 153 (19.9%) Own with mortgage 646 (32.0%) 388 (31.1%) 258 (33.5%) Own without mortgage 1,087 (53.9%) 739 (59.3%) 348 (45.2%) Missing 20 (1.0%) 9 (0.7%) 11 (1.4%) Total savings <0.001 CLSA Follow-up 1 Less than $49,999 387 (19.2%) 164 (13.2%) 223 (29.0%) $50,000–$99,999 251 (12.4%) 146 (11.7%) 105 (13.6%) $100,000 or more 1,228 (60.9%) 843 (67.6%) 385 (50.0%) Missing 151 (7.5%) 94 (7.5%) 57 (7.4%) Whether income satisfies needs <0.001 CLSA Baseline No 173 (8.6%) 62 (5.0%) 111 (14.4%) Yes 1,844 (91.4%) 1,185 (95.0%) 659 (85.6%) BMI <0.001 CLSA Follow-up 1 Underweight or normal weight 523 (25.9%) 349 (28.0%) 174 (22.6%) Overweight 752 (37.3%) 505 (40.5%) 247 (32.1%) Obese 742 (36.8%) 393 (31.5%) 349 (45.3%) Chronic pain <0.001 CLSA Follow-up 1 No 1,252 (62.1%) 876 (70.2%) 376 (48.8) Yes 765 (37.9%) 371 (29.8%) 394 (51.2) Multimorbidity <0.001 CLSA Follow-up 1 0 667 (33.1%) 484 (38.8%) 183 (23.8%) 1 639 (31.7%) 400 (32.1%) 239 (31.0%) 2 375 (18.6%) 203 (16.3%) 172 (22.3%) 3+ 287 (14.2%) 127 (10.2%) 160 (20.8%) Missing 49 (2.4%) 33 (2.6%) 16 (2.1%) Feel they lack companionship <0.001 CLSA Follow-up 1 No 1,893 (93.9%) 1,221 (97.9%) 672 (87.3%) Yes 124 (6.1%) 26 (2.1%) 98 (12.7%) Feel left out <0.001 CLSA Follow-up 1 No 1,957 (97.0%) 1,235 (99.0%) 722 (93.8%) Yes 60 (3.0%) 12 (1.0%) 48 (6.2%) Feel isolated from others <0.001 CLSA Follow-up 1 No 1,968 (97.6%) 1,241 (99.5%) 727 (94.4%) Yes 49 (2.4%) 6 (0.5%) 43 (5.6%) Church activities 0.012 CLSA Follow-up 1 Rare 1,437 (71.2%) 863 (69.2%) 574 (74.5%) Often 580 (28.8%) 384 (30.8%) 196 (25.5%) Pray at home 0.504 CLSA Follow-up 1 Rare 987 (48.9%) 618 (49.6%) 369 (47.9%) Often 1,030 (51.1%) 629 (50.4%) 401 (52.1%) Adverse childhood experience (Mean, SD) 0.30 (0.66) 0.20 (0.52) 0.47 (0.80) <0.001 CLSA Follow-up 1 (continued on next page) A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 5 at Follow-up 1 was 33.5% (95% CI: 29.6%, 37.3%). As reported above, during COVID-19, these numbers were substantially higher than the incidence and recurrence of depressive symptoms during the pandemic, 13.4% (95% CI: 11.6%, 15.4%) and 48.2% (95% CI 44.6%, 51.6%), respectively. Both incident and recurrent depressive symptoms during the autumn of 2020 were statistically significantly higher compared to those of Follow-up 1, as indicated by the non-overlapping 95% confi- dence intervals. For older adults with asthma with no history of depression, the as- sociations between the risk factors and depression status at the Autumn 2020 wave are presented in Table 3. Respondents who felt lonely oc- casionally/all of the time (3–7 days per week) had a substantially higher odds of incident depressive symptoms than those who felt lonely rarely or never/some of the time (0–2 days per week) during the COVID-19 pandemic (OR = 4.33, 95% CI [2.72; 6.91], p < 0.001). COVID-19 related stressors, such as difficulties with accessing resources were associated with significantly higher odds of developing depressive symptoms (OR = 1.60, 95% CI [1.03; 2.50], p = 0.038). Moreover, older adults with asthma who had increased verbal or physical conflict during the COVID-19 pandemic had a much higher odds ratio of developing depressive symptoms (OR = 4.18, 95% CI [2.47; 7.07], p < 0.001). In- dividuals with asthma who were unable to access usual healthcare had 1.55 times higher odds of depressive symptoms (95%CI [1.03; 2.30], p = 0.035) compared to those who were able to access usual health care. The Nagelkerke R square for this model was 0.238. Table 4 shows the association of depression status at the Autumn 2020 wave and covariates among respondents with asthma with a pre- pandemic history of depression. Individuals with asthma who partici- pated in few or no religious activities such as prayer at home had a higher risk of recurrent depressive symptoms than those who often participated in religious activities at home (OR = 1.49, 95% CI [1.02; 2.19], p = 0.040). Respondents who often felt lonely during the first few months of the COVID-19 pandemic were significantly more likely to have recurrent depressive symptoms (OR = 2.28, 95% CI [1.54; 3.37], p < 0.001). Older adults with asthma with functional limitations had a higher risk for depressive symptoms compared to their counterparts without such limitations (OR = 2.58, 95% CI [1.76; 3.79], p < 0.001). Respondents who had increased verbal or physical family conflict during the pandemic had 3.82 times higher odds (95% CI [2.36, 6.18], p < 0.001) of depressive symptoms than those who did not have an increase in family conflict. The odds of depressive symptoms were 1.71 times (95% CI [1.19; 2.45], p < 0.001) higher for those who were unable to access usual healthcare than those who were able to access usual healthcare. The Nagelkerke R square for this model was 0.257. 4. Discussion This study examined the incidence and recurrence of depression Table 1 (continued ) Overall sample of older adults with asthma (n = 2,017) Older adults with asthma with no pre-pandemic history of depression (n = 1,247) Older adults with asthma with a pre-pandemic history of depression (n = 770) p-value Source of data Left home in the past one month during COVID 0.139 CLSA Spring 2020 No 147 (7.3%) 82 (6.6%) 65 (8.4%) Yes 1,870 (92.7%) 1165 (93.4%) 705 (91.6%) How often do you feel lonely during COVID <0.001 CLSA Spring 2020 Rarely or never/Some of the time 1,681 (83.3%) 1,104 (88.5%) 577 (74.9%) Occasionally/All of the time 336 (16.7%) 143 (11.5%) 193 (25.1%) Type of dwelling <0.001 CLSA Spring 2020 House 1,581 (78.4%) 1,023 (82.0%) 558 (72.5%) Apartment 376 (18.6%) 197 (15.8%) 179 (23.2%) Others 60 (3.0%) 27 (2.2%) 33 (4.3%) Living along during the COVID-19 pandemic <0.001 CLSA Spring 2020 No 1,515 (75.1%) 1,003 (80.4%) 512 (66.5%) Yes 502 (24.9%) 244 (19.6%) 258 (33.5%) Functional limitations <0.001 CLSA Autumn 2020 No 1,483 (73.5%) 993 (79.6%) 490 (63.6%) Yes 534 (26.5%) 254 (20.4%) 280 (36.4%) COVID _ Health stressors <0.001 CLSA Autumn 2020 No 1,272 (63.1%) 851 (68.2%) 421 (54.7%) Yes 745 (36.9%) 396 (31.8%) 349 (45.3%) COVID _ Difficulties with accessing resources 0.366 CLSA Autumn 2020 No 1,630 (80.8%) 1,016 (81.5%) 614 (79.7%) Yes 387 (19.2%) 231 (18.5%) 156 (20.3%) COVID _ Family conflict <0.001 CLSA Autumn 2020 No 1,796 (89.0%) 1,153 (92.5%) 643 (83.5%) Yes 221 (11.0%) 94 (7.5%) 127 (16.5%) COVID _ Other family Issues 0.198 CLSA Autumn 2020 No 789 (39.1%) 502 (40.3%) 287 (37.3%) Yes 1,228 (60.9%) 745 (59.7%) 483 (62.7%) COVID _ Health care 0.001 CLSA Autumn 2020 No 1,419 (70.4%) 910 (73.0%) 509 (66.1%) Yes 598 (29.6%) 337 (27.0%) 261 (33.9%) COVID _ Medications <0.001 CLSA Autumn 2020 No 1,883 (93.4%) 1187 (95.2%) 696 (90.4%) Yes 134 (6.6%) 60 (4.8%) 74 (9.6%) A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 6 Table 2 Cumulative incidence and recurrence of depression by Autumn 2020 among older adults with asthma in the Canadian Longitudinal Study on Aging Older adults with asthma without a pre- pandemic history of depression p-value Older adults with asthma with a pre- pandemic history of depression p-value No depression Depression in Autumn 2020 No depression Depression in Autumn 2020 (n = 1080) (n = 167) (n = 399) (n = 371) History of depression prior to pandemic <0.001 <0.001 No history of Depression 1080 (86.6%) 167 (13.4%) – – Any history of Depression Reported diagnosed by a health professional but not depressed at Baseline or Follow-up 1 – 399 (51.8%) 197 (69.9%) 371 (48.2%) 85 (30.1%) Depressed at Baseline – – 104 (59.1%) 72 (40.9%) Depressed at Follow-up 1 – – 61 (42.7%) 82 (57.3%) Depressed at Baseline and Follow-up 1 – – 37 (21.9%) 132 (78.1%) Age 61.4 (8.9) 60.9 (9.3) 0.535 60.6 (8.5) 60.8 (9.2) 0.766 Sex 0.001 0.263 Male 516 (90.2%) 56 (9.8%) 131 (55.0%) 107 (45.0%) Female 564 (83.6%) 111 (16.4%) 268 (50.4%) 264 (49.6%) Marital status 0.492 0.082 Married/Common-law 820 (87.2%) 120 (12.8%) 232 (53.6%) 201 (46.4%) Separated/Divorced/Widowed 178 (85.2%) 31 (14.8%) 99 (45.6%) 118 (54.4%) Single 82 (83.7%) 16 (16.3%) 68 (56.7%) 52 (43.3%) Immigrant status 0.555 0.405 No 903 (86.9%) 136 (13.1%) 341 (52.5%) 308 (47.5%) Yes 177 (85.1%) 31 (14.9%) 58 (47.9%) 63 (52.1%) Visible minority status 0.299 0.836 No 1,016 (86.3%) 161 (13.7%) 384 (52.0%) 355 (48.0%) Yes 64 (91.4%) 6 (8.6%) 15 (48.4%) 16 (51.6%) Education 0.677 0.866 Less than secondary school – – 21 (48.8%) 22 (51.2%) Some post-secondary school 130 (85.5%) 22 (14.5%) 56 (50.5%) 55 (49.5%) Post-secondary degree/diploma 927 (86.6%) 143 (13.4%) 322 (52.3%) 294 (47.7%) Household income 0.738 0.050 Less than $50,000 166 (87.4%) 24 (12.6%) 115 (49.4%) 118 (50.6%) $50,000–$99,999 371 (85.9%) 61 (14.1%) 144 (53.7%) 124 (46.3%) $100,000 or more 492 (86.5%) 77 (13.5%) 116 (52.7%) 104 (47.3%) Missing 51 (91.1%) 5 (8.9%) 24 (49.0%) 25 (51.0%) Home ownership 0.047 0.050 Rent 95 (85.6%) 16 (14.4%) 68 (44.4%) 85 (55.6%) Own with mortgage 340 (87.6%) 48 (12.4%) 130 (50.4%) 128 (49.6%) Own without mortgage 640 (86.6%) 99 (13.4%) 197 (56.6%) 151 (43.4%) Missing – – – 7 (63.6%) Total saving 0.188 0.169 Less than $49,999 138 (84.1%) 26 (15.9%) 102 (45.7%) 121 (54.3%) $50,000–$99,999 123 (84.2%) 23 (15.8%) 56 (53.3%) 49 (46.7%) $100,000 or more 742 (88.0%) 101 (12.0%) 212 (55.1%) 173 (44.9%) Missing 77 (81.9%) 17 (18.1%) 29 (50.9%) 28 (49.1%) Whether income satisfies needs 1.000 0.040 No 54 (87.1%) 8 (12.9%) 47 (42.3%) 64 (57.7%) Yes 1026 (86.6%) 159 (13.4%) 352 (53.4%) 307 (46.6%) BMI 0.009 0.098 Underweight or normal weight 300 (86.0%) 49 (14.0%) 90 (51.7%) 84 (48.3%) Overweight 454 (89.9%) 51 (10.1%) 141 (57.1%) 106 (42.9%) Obese 326 (83.0%) 67 (17.0%) 168 (48.1%) 181 (51.9%) Chronic pain 0.004 0.034 No 775 (88.5%) 101 (11.5%) 210 (55.9%) 166 (44.1%) Yes 305 (82.2%) 66 (17.8%) 189 (48.0%) 205 (52.0%) Multimorbidity <0.001 <0.001 0 427 (88.2%) 57 (11.8%) 92 (50.3%) 91 (49.7%) 1 352 (88.0%) 48 (12.0%) 133 (55.6%) 106 (44.4%) 2 165 (81.3%) 38 (18.7%) 96 (55.8%) 76 (44.2%) 3+ 107 (84.3%) 20 (15.7%) 70 (43.8%) 90 (56.2%) Missing 29 (87.9%) 4 (12.1%) 8 (50.0%) 8 (50.0%) Feel that lack companionship 0.019 0.008 No 1062 (87.0%) 159 (13.0%) 361 (53.7%) 311 (46.3%) Yes 18 (69.2%) 8 (30.8%) 38 (38.8%) 60 (61.2%) Feel left out 0.447 <0.001 No 1071 (86.7%) 164 (13.3%) 386 (53.5%) 336 (46.5%) Yes – – 13 (27.1%) 35 (72.9%) Feel isolated from others 0.403 <0.001 (continued on next page) A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 7 during the COVID-19 pandemic in a large longitudinal study of Cana- dian older adults with a subsample of those with asthma, both with and without a history of depression. Our results revealed that approximately 1 in 7 (13.4%) older adults with asthma with no history of depression developed depressive symptoms that met the cut-off criteria for depression based on the CES-D-10 for the first time during the COVID-19 pandemic. Among those with a history of depression, approximately 1 in 2 (48.2%) experienced a recurrence of depressive symptoms that met the cut-off criteria for depression based on the CES-D-10 during the pandemic. Even among respondents who had not been depressed during the Baseline and Follow-up 1 waves, but had a diagnosis of depression in previous decades, the prevalence of recurrent depression was high (30%). We conducted sensitivity analyses to examine the incidence and recurrence of depression of depression among older adults with asthma between the Baseline (2011–2015) and Follow-up 1 (2015–2018) waves. Our results indicate that the incidence and recurrence of depression at Follow-up 1 were 6.8% and 33.5%, respectively, which was substantially lower than the incidence and recurrence of depression during the pandemic, as described above. We also examined whether the incidence and recurrence of depression during the pandemic was higher among respondents with asthma when compared to respondents without asthma. We found that the recurrence of depression was significantly higher for respondents with asthma than those without asthma. This finding highlights the high vulnerability to depression during the COVID-19 pandemic among older adults with asthma who have a previous history of depression. The COVID-19 pandemic created substantial stressors for many older adults with asthma. When consid- ering the pressure placed upon this population to strictly adhere to physical distancing limitations, combined with the concerns over being labelled “high-risk” for severe COVID-19 morbidity and mortality, it is unsurprising that this population experienced a precipitous decline in mental health during the pandemic. Our hypothesis that older adults with low socioeconomic status would have higher levels of depression was partially supported. Although neither income nor education was associated with incident or Table 2 (continued ) Older adults with asthma without a pre- pandemic history of depression p-value Older adults with asthma with a pre- pandemic history of depression p-value No depression Depression in Autumn 2020 No depression Depression in Autumn 2020 (n = 1080) (n = 167) (n = 399) (n = 371) No 1076 (86.7%) 165 (13.3%) 389 (53.5%) 338 (46.5%) Yes – – 10 (23.3%) 33 (76.7%) Church activities 0.212 0.067 Rare 740 (85.7%) 123 (14.3%) 285 (49.7%) 289 (50.3%) Often 340 (88.5%) 44 (11.5%) 114 (58.2%) 82 (41.8%) Pray at home 0.061 0.067 Rare 547 (88.5%) 71 (11.5%) 178 (55.1%) 191 (44.9%) Often 533 (84.7%) 96 (15.3%) 221 (48.2%) 180 (51.8%) Adverse childhood experience 0.2 (0.5) 0.3 (0.7) <0.001 0.4 (0.8) 0.5 (0.9) 0.058 Left home in the past one month during COVID 1.000 0.962 No 71 (86.6%) 11 (13.4%) 33 (50.8%) 32 (49.2%) Yes 1009 (86.6%) 156 (13.4%) 366 (51.9%) 339 (48.1%) How often do you feel lonely during COVID <0.001 <0.001 Rarely or never/Some of the time 989 (89.6%) 115 (10.4%) 334 (57.9%) 243 (42.1%) Occasionally/All of the time 91 (63.6%) 52 (36.4%) 65 (33.7%) 128 (66.3%) Type of dwelling 0.228 0.447 House 891 (87.1%) 132 (12.9%) 297 (53.2%) 261 (46.8%) Apartment 164 (83.2%) 33 (16.8%) 86 (48.0%) 93 (52.0%) Others – – 16 (48.5%) 17 (51.5%) Living along during the COVID-19 pandemic 0.007 0.087 No 882 (87.9%) 121 (12.1%) 277 (54.1%) 235 (45.9%) Yes 198 (81.1%) 46 (18.9%) 122 (47.3%) 136 (52.7%) Functional limitation 0.010 <0.001 No 873 (87.9%) 120 (12.1%) 294 (60.0%) 196 (40.0%) Yes 207 (81.5%) 47 (18.5%) 105 (37.5%) 175 (62.5%) COVID _ Health stressors 0.006 0.026 No 753 (88.5%) 98 (11.5%) 234 (55.6%) 187 (44.4%) Yes 327 (82.6%) 69 (17.4%) 165 (47.3%) 184 (52.7%) COVID _ Difficulties with accessing resources <0.001 0.094 No 900 (88.6%) 116 (11.4%) 328 (53.4%) 286 (46.6%) Yes 180 (77.9%) 51 (22.1%) 71 (45.5%) 85 (54.5%) COVID _ Family conflict <0.001 <0.001 No 1021 (88.6%) 132 (11.4%) 368 (57.2%) 275 (42.8%) Yes 59 (62.8%) 35 (37.2%) 31 (24.4%) 96 (75.6%) COVID _ Other family Issues 0.001 0.005 No 455 (90.6%) 47 (9.4%) 168 (57.2%) 119 (42.8%) Yes 625 (83.9%) 120 (16.1%) 231 (24.4%) 252 (75.6%) COVID _ Health care <0.001 <0.001 No 813 (89.3%) 97 (10.7%) 293 (57.6%) 216 (42.4%) Yes 267 (79.2%) 70 (20.8%) 106 (40.6%) 155 (59.4%) COVID _ Medications 0.178 0.002 No 1032 (86.9%) 155 (13.1%) 374 (53.7%) 322 (46.3%) Yes 48 (80.0%) 12 (20.0%) 25 (33.8%) 49 (66.2%) Note: — indicates a value that could not be released due to insufficient cell size. A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 8 Table 3 Logistic regression results for incident depression by Autumn 2020 among older adults with asthma with no pre-pandemic history of depression (n = 1,247). Odds Ratio 95% Confidence Interval p-value Age 1.01 [0.99; 1.04] 0.340 Sex Male Female (ref.) 1.45 [0.97; 2.18] 0.073 Marital status Married/Common-law (ref.) Separated/Divorced/Widowed 0.75 [0.40; 1.40] 0.336 Single 1.17 [0.53; 2.59] 0.693 Immigrant status No (ref.) Yes 1.43 [0.88; 2.31] 0.148 Visible minority status No (ref.) Yes 0.47 [0.18; 1.24] 0.128 Education Less than secondary school (ref.) Secondary and some post-secondary 1.21 [0.23; 6.23] 0.830 Post-secondary degree/diploma 1.02 [0.21; 5.11] 0.977 Household income Less than $50,000 (ref.) $50,000–$99,999 1.43 [0.77; 2.69] 0.260 $100,000 or more 1.81 [0.89; 3.68] 0.100 Missing 0.33 [0.10; 1.08] 0.067 Dwelling ownership Rent (ref.) Own with mortgage 0.93 [0.43; 2.00] 0.854 Own without mortgage 1.07 [0.50; 2.19] 0.895 Missing 6.37* [1.18; 30.50] 0.033 Total saving Less than $49,999 (ref.) $50,000–$99,999 0.97 [0.48; 1.97] 0.931 $100,000 or more 0.76 [0.41; 1.39] 0.366 Missing 1.77 [0.75; 4.17] 0.192 Whether income satisfies needs No 0.69 [0.28; 1.69] 0.420 Yes (ref.) BMI Underweight or normal weight (ref.) Overweight 0.68 [0.42; 1.08] 0.103 Obese 1.03 [0.64; 1.74] 0.916 Chronic pain No (ref.) Yes 1.40 [0.93; 2.10] 0.107 Multimorbidity 0 (ref.) 1 0.87 [0.55; 1.38] 0.562 2 1.29 [0.76; 2.18] 0.347 3+ 1.03 [0.54; 2.00] 0.921 Missing 0.51 [0.14; 1.82] 0.300 Feel that lack companionship No (ref.) Yes 1.59 [0.49; 5.23] 0.443 Feel left out No (ref.) Yes 0.67 [0.10; 4.31] 0.673 Feel isolated from others No (ref.) Yes 1.76 [0.20; 15.61] 0.610 Church activities Rare 1.78* [1.10; 2.89] 0.020 Often (ref.) Pray at home Rare 0.65* [0.42; 0.99] 0.050 Often (ref.) Adverse childhood experience 1.29 [0.96; 1.74] 0.094 Left home in the past one month during COVID No (ref.) Yes 1.08 [0.51; 2.31] 0.841 How often do you feel lonely during COVID Rarely or never/Some of the time (ref.) Occasionally/All of the time 4.33*** [2.72; 6.91] <0.001 Type of dwelling House (ref.) Apartment 1.16 [0.67; 2.00] 0.599 (continued on next page) A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 9 recurrent depression, older adults who experienced a loss of income or an inability to access necessary supplies or food due to the pandemic were 60% more likely to develop incident depression when compared to those who had no loss of income or inability to access necessities during the pandemic. This aligns with other emerging longitudinal research that has found increases in depressive symptoms due to income loss during the COVID-19 pandemic [12]. Previous research has also shown that subjective stress about the adequacy of income for meeting basic needs is associated with poor mental health outcomes beyond the objective ability to meet financial requirements [13]; Wilkinson, 2016). This may partially explain why the precariousness and uncertainty of income loss during COVID-19 was associated with depression, while objective measures, such as pre-pandemic household income, were not associated with depression during the pandemic. COVID-19 related factors that were associated with both incident depression and recurrent depression included disruptions to healthcare access and family conflict. Respondents who were unable to access their usual healthcare services hada 53% and a 71% higher risk of incident and recurrent depression, respectively. Even in the absence of in-person health services, it is important to find alternative care options to support the physical and mental health of older adults with asthma, such as providing remote care through telemedicine [14]. Ensuring that older adults with asthma have regular access to healthcare services is also important for monitoring medication adherence. Previous research has highlighted a negative association between depressive symptoms and treatment adherence in older adults with asthma [15,16]. There have been substantial declines in medication adherence among older adults with asthma during the pandemic [17], emphasizing the importance of increasing healthcare accessibility so that clinicians can be attuned to both adherence behaviours and mental health symptoms among asthma patients. Older adults who experienced an increase in verbal or physical conflict and/or a breakdown in family or marital relationships had approximately quadruple the risk of incident and recurrent depression in this study. The COVID-19 pandemic disrupted many traditional coping mechanisms that may buffer family conflict, such as external social support and time spent outside the household. Interpersonal conflict has been previously identified as a risk factor for depression in later life [18]. As expected, respondents who reported feeling lonely at the begin- ning of the pandemic in the spring of 2020 had approximately double the risk of recurrent depression and quadruple the risk of incident depression by autumn 2020. This finding is consistent with pre- pandemic research on loneliness and depression among middle-aged and older adults, which found that 50% of female respondents and 42% of male respondents endorsing past-week loneliness met the CES-D- 10 cut-off for depression, compared with less than 10% of female and 7% of male respondents who reported being rarely or never lonely during the past week [19]. This is of particular concern when considering that loneliness was previously identified as a major public health crisis among older adults prior to the pandemic [20], in conjunction with the high levels of loneliness among older adults during the pandemic [21]. Functional limitations were associated with an approximately doubled risk of recurrent depression, but were not associated with incident depression. Functional impairment is an important predictor of persistent depressive symptoms in older adults [22,23]. Emerging research has already indicated an increase in functional impairment and frailty among older adults during the COVID-19 pandemic, likely due to decreases in physical activity during periods of lockdown [24,25]. The physical functioning of older adults with asthma is an important determinant of quality of life including mental health within this pop- ulation [26]. The current findings highlight the importance of promot- ing physical activity among older adults with asthma to mitigate some of the potential consequences of extended periods of lockdown, and ulti- mately support the mental well-being of this population. 5. Limitations These findings should be considered in light of some limitations. First, depression was based on upon the CES-D-10, which is a self-report measure. Although this is a frequently utilized measure with high reli- ability and validity, a clinical assessment would have been preferable. Second, the current study did not have any information on illness severity among respondents with asthma. It is possible that the mental health effects of the COVID-19 pandemic may vary by asthma severity. Third, the CLSA dataset excluded residents living in long-term care in- stitutions at baseline. When considering the extensive lockdown mea- sures implemented in long term care homes during the pandemic, it is Table 3 (continued ) Odds Ratio 95% Confidence Interval p-value Others 0.42 [0.08; 2.08] 0.278 Living along during the COVID-19 pandemic No (ref.) Yes 1.40 [0.78; 2.54] 0.264 Functional limitation scale No (ref.) Yes 1.29 [0.81; 2.07] 0.285 COVID _ Health stressors No (ref.) Yes 1.29 [0.88; 1.89] 0.198 COVID _ Difficulties with accessing resources No (ref.) Yes 1.60* [1.03; 2.50] 0.038 COVID _ Family conflict No (ref.) Yes 4.18*** [2.47; 7.07] <0.001 COVID _ Other family Issues No (ref.) Yes 1.26 [0.83; 1.91] 0.278 COVID _ Health care No (ref.) Yes 1.54* [1.03; 2.30] 0.035 COVID _ Medications No (ref.) Yes 1.14 [0.53; 2.45] 0.740 Likelihood ratio test statistic 173.6*** Nagelkerke R square 0.238 A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 10 Table 4 Logistic regression results for depression by Autumn 2020 among older adults with asthma with a pre-pandemic history of depression (n = 770). Odds Ratio 95% Confidence Interval p-value Age 1.01 [0.98; 1.03] 0.529 Sex Male (ref.) Female 1.26 [0.87; 1.82] 0.221 Marital status Married/Common-law (ref.) Separated/Divorced/Widowed 0.91 [0.54; 1.52] 0.709 Single 0.67 [0.37; 1.21] 0.183 Immigrant status No (ref.) Yes 1.11 [0.70; 1.76] 0.672 Visible minority status No (ref.) Yes 0.67 [0.27; 1.64] 0.374 Education Less than secondary school (ref.) Secondary and some post-secondary 1.14 [0.50; 2.61] 0.758 Post-secondary degree/diploma 1.15 [0.54; 2.44] 0.712 Household income Less than $49,999 (ref.) $50,000–$99,999 1.15 [0.72; 1.83] 0.571 $100,000 or more 1.21 [0.70; 2.15] 0.485 Missing 1.28 [0.58; 2.76] 0.559 Dwelling ownership Rent (ref.) Own with mortgage 0.91 [0.53; 1.58] 0.748 Own without mortgage 0.77 [0.44; 1.34] 0.352 Missing 1.21 [0.23; 6.37] 0.824 Total saving Less than $50,000 (ref.) $50,000–$99,999 0.81 [0.46; 1.46] 0.479 $100,000 or more 0.78 [0.49; 1.23] 0.287 Missing 1.01 [0.48; 2.09] 0.986 Whether income satisfies needs No 1.35 [0.81; 2.25] 0.248 Yes (ref.) BMI Underweight or normal weight (ref.) Overweight 0.80 [0.52; 1.25] 0.331 Obese 0.91 [0.60; 1.41] 0.711 Chronic pain No (ref.) Yes 0.92 [0.66; 1.30] 0.651 Multimorbidity 0 (ref.) 1 0.71 [0.46; 1.11] 0.135 2 0.64 [0.39; 1.05] 0.078 3+ 0.78 [0.47; 1.30] 0.346 Missing 0.62 [0.18; 2.11] 0.448 ACE 1.12 [0.90; 1.38] 0.316 Feel that lack companionship No (ref.) Yes 1.17 [0.66; 2.09] 0.589 Feel left out No (ref.) Yes 1.89 [0.80; 4.47] 0.144 Feel isolated from others No (ref.) Yes 1.84 [0.74; 4.60] 0.190 Church activities Rare 1.15 [0.74; 1.79] 0.523 Often (ref.) Pray at home Rare 1.49* [1.02; 2.19] 0.040 Often (ref.) Left home in the past one month during COVID No (ref.) Yes 1.07 [0.58; 1.94] 0.837 How often do you feel lonely during COVID Rarely or never/Some of the time (ref.) Occasionally/All of the time 2.28*** [1.54; 3.37] <0.001 Type of dwelling House (ref.) Apartment 1.08 [0.69; 1.69] 0.736 (continued on next page) A. MacNeil et al. Respiratory Medicine xxx (xxxx) xxx 11 likely that the mental health of this group may have been dispropor- tionately affected during the pandemic, resulting in the exclusion of a particularly vulnerable subset of older adults from this analysis. Finally, CLSA respondents had to be able to speak English or French, which limits the generalizability of these findings to community-dwelling older adults with fluency in English or French. 6. Conclusions Despite these limitations, the current study uses a large, longitudinal sample of Canadian older adults to provide an in-depth analysis on the mental health of older adults with asthma during the COVID-19 pandemic. As the life returns to “normal” through widespread vaccina- tion and the removal of physical distancing limitations, it is important to consider the potential longstanding mental health effects of the COVID- 19 pandemic, and to provide care to those who may be vulnerable to adverse mental health outcomes beyond the pandemic. CRediT authorship contribution statement Andie MacNeil: Conceptualization, Writing – original draft, Writing – review & editing. Grace Li: Methodology, Formal analysis, Writing – original draft, Writing – review & editing. Ying Jiang: Conceptualiza- tion, Writing – review & editing, Supervision. Margaret de Groh: Conceptualization, Writing – review & editing, Supervision. Esme Ful- ler-Thomson: Conceptualization, Writing – review & editing, Method- ology, Supervision, Project administration. Declaration of competing interest None. Acknowledgements This research was made possible using the data collected by the Canadian Longitudinal Study on Aging (CLSA). Funding for the Cana- dian Longitudinal Study on Aging (CLSA) is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 94473 and the Canada Foundation for Innovation. This research has been conducted using the Baseline Comprehensive Dataset version 6.0, Baseline Tracking Dataset version 3.7, Follow-up 1 Comprehensive Dataset version 3.0 and Follow-up 1 Tracking Dataset version 2.2, COVID-19 Questionnaire Study Dataset version 1.0 under Application ID 2104024. The CLSA is led by Drs. Parminder Raina, Christina Wolfson and Susan Kirkland. The opinions expressed in this manuscript are the author’s own and do not reflect the views of the Canadian Longitudinal Study on Aging. The authors gratefully acknowledge the support of the Canadian Institutes of Health Research (CIHR) grant #172862 (PI Esme Fuller-Thomson) and the Canadian Frailty Network. The opinions expressed in this manuscript are the authors’ own and do not reflect the views of the Canadian Longitudinal Study on Aging, the CIHR, or the Canadian Frailty Network. References [1] Y.J. Juhn, Risks for infection in patients with asthma (or other atopic conditions): is asthma more than a chronic airway disease? J. Allergy Clin. Immunol. 134 (2) (2014) 247–257. [2] N.F. Mendes, C.P. Jara, E. Mansour, E.P. Araújo, L.A. Velloso, Asthma and COVID- 19: a systematic review, Allergy Asthma Clin. Immunol. 17 (2021) 5. [3] T. Wu, P. Yu, Y. Li, J. Wang, Z. Li, J. Qiu, Y. 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Yes 1.24 [0.87; 1.76] 0.231 COVID _ Health care No (ref.) Yes 1.71** [1.19; 2.46] <0.001 COVID _ Medications No (ref.) Yes 1.57 [0.85; 2.88] 0.148 Likelihood ratio test statistic 164.7*** Nagelkerke R square 0.257 A. 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