key: cord-0281876-z3uwjhme
authors: Blacutt, M.; Filgueiras, A. J.; Stults-Kolehmainen, M. A.
title: Prevalence and Incidence of Stress, Depression and Anxiety Symptoms among Brazilians in Quarantine across the early phases of the COVID-19 Crisis
date: 2021-09-12
journal: nan
DOI: 10.1101/2021.09.07.21263246
sha: 335067ed7aeefa96b5eab1ad9f2975f94c9ebb6a
doc_id: 281876
cord_uid: z3uwjhme

Objective: The aim of this study was to measure the prevalence and incidence of stress, depression, and anxiety symptoms in Brazilians during the COVID-19 pandemic. Method: We assessed 103 (54 women, 49 men) participants online in three periods of the epidemic curve: time 1 (T1; first cases of community transmission; March 20 to 25, 2020), time 2 (T2; acceleration; April 15 to 20, 2020) and time 3 (T3; continued acceleration; June 25 to 30, 2020). The criteria adopted for calculating prevalence and incidence was identifying participants with scores two standard deviations above the mean compared to normative data. Stress was measured using the Perceived Stress Scale (PSS-10), depression was measured using the Filgueiras Depression Index (FDI), and anxiety was measured using the State-Trait Anxiety Inventory - State Subscale (STAI-S). Results: Initially, 89% of individuals were free of severe stress, anxiety, and depression, which dropped to 35% by T3. Prevalence of stress increased from 1.9% (95% CI [0.5, 6.8]) at T1 to 7.8% (95% CI [4.0, 14.6]) at T2, and 28.2% (95% CI [20.4, 37.5]) at T3. Depression prevalence increased from 0% (95% CI [0, 3.6]) at T1 to 23.3% (95% CI [16.2, 32.3]) at T2 and 25.2% (95% CI [17.8, 34.4]) at T3. The prevalence of severe anxiety-state symptoms increased from 10.7% (95% CI [6.1, 18.1]) at T1 to 11.7% (95% CI [6.8, 19.3]) at T2 and 45.6% (95% CI [36.3, 55.2]) at T3. Stress incidence increased by 7.8% (95% CI = [4, 14.6]) from time 1 to time 2, 23.3% (95% CI [16.2, 32.3]) from time 2 to time 3, and 26.2% (95% CI [18.7, 35.5]) from time 1 to time 3. Depression incidence increased by 23.3% (95% CI [16.2, 32.3]) from T1 to T2, 15.5 (95% CI [9.8, 23.8]) T2 to T3, and 25.2% (95% CI [17.8, 34.4]) from T1 to T3. Anxiety incidence increased by 9.7% (95% CI [5.4, 17]) from T1 to T2, 39.8% (95%CI [30.9, 49.5]) from T2 to T3, and 35.9% (95% CI [27.3, 45.5]) from T1 to T3. The severity of stress significantly increased from 16.1{+/-}8.7 at T1 to 23.5{+/-}8.4 at T2, and 30.3{+/-}6.0 at T3. Depression severity significantly increased from 48.5{+/-}20.5 at T1 to 64.7{+/-}30.2 at T2, and 75.9{+/-}26.1 at T3. Anxiety increased from 49.0{+/-}13.4 at T1 to 53.5{+/-}12.5 at T2 and 62.3{+/-}13.4 at T3. Females and individuals without comorbidities that increased COVID-19 lethality had higher anxiety scores than males and individuals with comorbidities. Age was inversely associated with mental health outcomes at baseline. Conclusion: The prevalence and severity of stress, depression, and anxiety significantly increased throughout the course of the pandemic. Anxiety seems to be sensitive to gender and risk status, where females and individuals without pre-existing comorbidities had higher anxiety by the final collection point. Depression and stress increased throughout time but were not different between genders or risk status.

to 53.5±12.5 at T2 and 62.3±13.4 at T3. Females and individuals without comorbidities that 48 increased COVID-19 lethality had higher anxiety scores than males and individuals with 49 comorbidities. Age was inversely associated with mental health outcomes at baseline. 50

Conclusion: The prevalence and severity of stress, depression, and anxiety significantly increased 51 throughout the course of the pandemic. Anxiety seems to be sensitive to gender and risk status, 52

where females and individuals without pre-existing comorbidities had higher anxiety by the final 53 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.07.21263246 doi: medRxiv preprint PREVALENCE OF MENTAL HEALTH COVID-19 3 collection point. Depression and stress increased throughout time but were not different between 54 genders or risk status. 55 56 57 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Behaviors such as engaging in exercise and physical activity, eating healthy and engaging in tele-76 psychotherapy are associated with less mental health problems during quarantine. Those 77 participants who reported the need to leave their houses to go to work, regardless of the nature of 78 their jobs, showed more severe symptoms ( April 2020. They adopted the criteria of two standard deviations above the mean (2 SD) from the 113 normative data of validated psychometric instruments. Results showed that 9.7% of the sample 114 showed psychological distress above the clinical cut-off criteria, while 8.0% and 9.4% of 115 participants were also above for depression and anxiety, respectively. The World Health 116

Organization collected prevalence data in Brazil (World Health Organization, 2017) three years 117 before the quarantine and found a lower prevalence of depression (5.8%). Nonetheless, anxiety 118 was similar (9.3%), perhaps indicating some stability during quarantine. Importantly, data from 119 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.07.21263246 doi: medRxiv preprint PREVALENCE OF MENTAL HEALTH COVID-19 7 inflate prevalence numbers. Volunteers who reported being non-binary gender (N=9) were also 151 excluded due to the low number of participants, which impaired statistical analyses; nonetheless, 152 they were considered in this paper's discussion. Respondents were asked to complete a 45-minute 153 online Google Forms questionnaire regarding demographic information and COVID-19-related 154 mental health outcomes. The informed consent document was presented before the questionnaires, 155 and the consent was a requirement for participation. The Ethics Committee at Rio de Janeiro State 156

University approved all procedures (report #2.990.087). 157 158

We adopted three validated and normalized measures to ensure good quality of data; one 160 instrument for each psychological dimension: psychological stress, depression, and anxiety. 161

Demographic information was collected through a simple one-page questionnaire containing: 162 gender (male, female and non-specific), age (in years) and risk for COVID-19 ("Do you have any 163 current disease that increases your risk for COVID-19 lethality?"-yes/no). All instruments were 164 presented in Brazilian Portuguese. Respondents link each of these words to their own feelings in the last fortnight. A Likert-type scale 179 response set contains six categories of endorsement ranging from "0-not related to me at all" to 180 "5-totally related to me". Examples of items are "sadness", "death", "displeasure" and "guilty". 181 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

The variables were normally distributed with skewness and kurtosis statistics within the 198 range of -2.0 and 2.0. Prevalence was calculated using the percentage of participants above cut-199 off points in each period (time 1, 2 and 3). We estimated three incidence percentages: (i) between 200 times 1 and 2, (ii) 2 and 3 and (iii) 1 and 3. Incidence was indicated by the percentage of 201 participants whose scores were below cut-offs in the previous period data collection but were 202 above these cut-offs in the next. A 95% confidence intervals were estimated as described by 203

Altman, Machin, Bryant, and Gardner (2000) . Furthermore, differences in PSS-10, FDI, and 204 STATI-S between data-collection (time), gender, risk (binary variable indicating whether 205 individual has a pre-existing comorbidity that increased risk of COVID-19 fatality) and their 206 interaction were evaluated using linear mixed effects models, where a random intercept was 207 generated per participant. Tukey post-hoc tests were used to find pairwise differences in main 208 effects and interactions. Regarding gender and risk for COVID-19, we adopted a one-way 209 ANOVA (with Bonferroni post-hoc) and a two-tailed t-test to compare groups; Cohen's f and d 210 were adopted, respectively, for effect-size and average (SD) for descriptive statistics. Pearson 211 correlations were performed to investigate linear associations between all mental health outcomes 212 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The results of the linear-mixed effects models for stress, anxiety, and depression are 249 displayed in Figure 2 . A main effect of time was found for PSS-10 (F(2, 198) = 103.5, p <.0001), 250 however, there was no main effect of gender or risk on PSS-10 as well as no interactions. Tukey 251 post-hoc tests revealed PSS-10 to be significantly higher at T3 compared to T2 (t(198) = -7.13, p 252 < .0001) and T1 (t(198) = -14.4, p < .0001), while T2 was found to be significantly higher than T1 253 (t(198) = -7.23, p <.0001). A main effect of time was found for FDI (F(2, 198) = 52.9, p < .0001) 254 however, there was no effect of gender or risk on PSS-10 in addition no interactions. FDI was 255 found to be significantly higher at T3 compared to T2 (t(198) = -7.43, p = .0001) and T1 (t(198) = 256 -10.3, p < .0001). Moreover, T2 was found to be significantly higher than T1 (t(198) = -6.02, p 257 <.0001). A main effect of time (F(2, 198) = 55.0, p < .0001) and risk (F(1, 99) = 5.55, p = .021) 258 was found for STAI-S. Tukey post-hoc comparisons revealed that STAI-S was significantly higher 259 at T3 compared to T2 (t(198) = -7.34, p < .0001) and T1 (t(198) = -10.2, p < .0001), while T2 was 260 found to be significantly higher than T1 (t(198) = -2.82, p = .015). Furthermore, there was a 261 significant difference between risk levels where individuals without a comorbidity had higher 262 STAI-S scores than individuals with a comorbidity (t(99) = 2.36, p < .02), as is seen in Figure 3 . Our analysis showed that gender had a significant interaction with time for anxiety, where 320 females had higher anxiety scores than males by the third collection point (66.7±11.8 vs. 321 57.4±13.5). These results are consistent with Özdin and Bayrak Özdin (2020) who investigated 322 gender-based differences in the effects of the COVID-19 pandemic on mental illness. They found 323 that female participants showed significantly higher levels of anxiety than male participants, 324 whereas depression did not differ between the genders. Liu et al. (2020) had similar findings in a 325 group of young Americans. Specifically, they found that females had higher anxiety and 326 depression throughout the COVID-19 pandemic. These findings differ slightly from ours, as we 327 found no significant difference in depression between genders. 328

In this study, we found that there was a main effect of time for stress, anxiety, and 329 depression, where the severity of each mental health condition became worse throughout time. 330 Furthermore, all conditions increased significantly at each time interval. For example, depression 331 at time 3 was significantly more severe than depression at time 2, which was more severe than 332 depression at time 1; this effect was seen for anxiety and stress as well. We did not find a significant 333 main effect of gender or fatality risk due to comorbidity on stress or depression. However, a main 334 effect of risk was found on anxiety where individuals without a comorbidity that increased risk of 335 fatality had lower anxiety than those who had a comorbidity. A time-by-gender interaction was 336 also found where females had higher scores of anxiety at time 3 compared to males. Finally, a 337 time-by-risk interaction was found where individuals with a comorbidity had anxiety scores than 338 those without a comorbidity at time 3. The comorbidities that we asked participants can all be 339 described as chronic illnesses, which include obesity, diabetes, high blood pressure and other 340 cardiac and respiratory conditions (Pinto et al., 2020). We hypothesize that the reason that these 341 individuals had anxiety scores is due to an increase in resiliency to stressful life events in this 342 population. This hypothesis is consistent with previous literature, as Ghanei Gheshlagh et al. 343 (2016) found that individuals with chronic illness have high resiliency scores, which increase with 344 the disease lethality. These authors propose that high resiliency in these samples is developed 345 adaptively, to maintain control of their own life, adapt to life changes, and remain in treatment, 346 among others. Therefore, it is plausible that this sample of people with chronic 347 illness/comorbidities was less anxious because of the COVID-19 pandemic as they had higher pre-348 existing resiliency than individuals without chronic illness. 349 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint We found that severity of all mental illness conditions was positively associated with each 350 other at time one and negatively associated with age at time 1. At time 2, the only significant 351 association was between age and depression. Subsequently, there were no significant associations 352 between any of the conditions with each other or age at time 3. We hypothesize that the start of 353 the pandemic provided a highly salient event that provoked similar difficulties across the sample. 354

This universally shared experience may have led to mental health changes that were largely 355 associated. However, as the pandemic progressed, individuals experienced different difficulties. null-hypothesis test due to the low number of non-binary participants, it seems that their scores 377 were typically higher than other genders. The matter of mental health among binary and non-binary 378 individuals is still a debatable, although researchers agree that cisgender (those whose gender is 379 the same as the assigned at birth) tend to show better psychological outcomes when compared to 380 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint to reach a more precise conclusion. 384

Our study sheds light on changes in psychological stress, depression, and anxiety 385 throughout early course of the COVID-19 pandemic curve in 2020. Prevalence and severity 386 increased for stress, anxiety, and depression. Our result suggests that as time progressed, stress 387 and depression significantly increased at similar rates in both genders and risk groups. However, 388 anxiety increased at a higher rate in females and individuals without a comorbidity that increased 389 fatality risk. Additionally, we found a substantial decrease in the proportion of people that did not 390 have a severe mental health condition. The present research had some limitations that are important 391 to highlight. Limitations include the self-reported nature of the data, as participants filled out the 392 questionnaire by filling out a 45-minute Google Form, which was used to analyze mental health 393 outcomes. Further, participants were asked if they had an illness which increased fatality risk for 394 COVID-19 and were given a few examples of such conditions (i.e., obesity, diabetes, high blood 395 pressure and other cardiac and respiratory conditions). Therefore, outside of these categories given 396 to participants, the answer to this question relies on their knowledge of comorbidities that increase 397 fatality risk for COVID-19 and their perception to the risk. For example, an individual with 398

Vitamin D deficiency may be unaware of their status and state that they do not have any condition 399 that increases risk for COVID-19 lethality, even though this condition increases fatality risk for 400 COVID-19 (World Health Organization, 2017). 401 402 403 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.07.21263246 doi: medRxiv preprint

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. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprintThe copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.07.21263246 doi: medRxiv preprint