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Introduction: COVID-19 disrupted traditional research infrastructures and processes most notably in-person community recruitment, especially in underrepresented populations like racial ethnic minorities. To find creative and effective strategies, our group implemented and tested the efficacy of a culturally tailored community outreach plan (COP) developed during the US COVID-19 pandemic. Methods: In February 2021, we developed an 11 step culturallytailored community outreach program to support the implementation of three NIH funded community-based sleep studies. The following steps include: (1) description of the situation statement, 2) definition of goals, 3) engagement of audience/stakeholders, 4) tailoring message, 5) defining incentives, 6) choice of outreach methods, 7) identification of spokesperson, 8) choice of tools to assess progress, 9) identification of media outlets, 10) creation of study timeline, and 11) implementation of the plan. The studies leveraged several recruitment channels: 1) community settings (Place of worship, “community recruiter”, health fairs, word of mouth, & healthcare providers/doctors' clinics), 2) online platforms (Facebook, Twitter, LinkedIn and Research Match), and 3) preexisting datasets in NYC. Results: All three studies successfully met recruitment goals. ESSENTIAL [n= 224, 69% females, mean age= 36], MOSAIC [n=109, 61% females;mean age= 64] and Latinx/Hispanics: DORMIR[n=260, 61.3% of female;32.4]. Among the three NYC cohorts, the most common recruitment channels were: preexisting datasets (74%), community settings (19%), & online platform (7%) for ESSENTIAL;preexisting datasets (85%) & community settings (15%) for MOSAIC, and (71.7%) online platform for DORMIR. However, the Miami cohorts came mostly from community settings 90% for Essential and 97% for MOSAIC. Conclusion: Overall, the TSCS community outreach plan seems to be an effective tool to engage minoritized populations in greater NY and Miami. Our current field experience indicates that recruitment channels must be adapted to age, and community resources. Limited access to technology, particularly among older Blacks seem to be a major barrier for field staff to successfully engage the disenfranchised communities.
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Introduction: The COVID-19 pandemic has deteriorated sleep health in the United States (U.S.) and worldwide. Most studies that have examined the association between COVID-19 and sleep outcomes have used a non-probability sampling with potential sampling bias and limited generalizability. We examined the association between diagnosed COVID-19 and sleep health in a large representative sample of civilian adults aged ≥18 years in the U.S. Methods: This study was based on data from the 2020 National Health Interview Survey (NHIS) of adults (n=17,636). Sleep health was captured by self-reported sleep quantity [(very short (≤ 4 hours), short (5-6 hours), healthy (7-8 hours), or long (≥9 hours)] and sleep complaints (trouble falling and staying asleep;with responses ranging from never to every day) in the past 30 days. To account for correlated residuals among the endogenous sleep outcomes, generalized structural equation modeling (GSEM) was conducted with COVID-19 diagnosis as the predictor of interest. Other covariates (age, sex, race/ethnicity, education, employment, poverty level, marital status, birthplace, health insurance, region of residence, metropolitan areas, number of children and adults in the household, obesity, and sleep medication) were included in the models. NHIS complex probability sampling design was accounted for in descriptive and GSEM analyses. Results: About 4.2% of adults had a positive COVID-19 diagnosis. Among them, 3.1% had very short sleep, 24.2% had short sleep, 59.9% had healthy sleep, and 12.8% had long sleep;37.0% had trouble falling some days, 10.9% most days, and 6.5% every day;and 33.7% had trouble staying asleep some days, 13.9% most days, and 6.6% every day. Findings from GSEM revealed that a history of COVID-19 almost doubled the odds of having short sleep (OR: 1.9;95% CI: 1.1-3.4;p=0.032). No significant associations were found between COVID-19 and the other sleep outcomes. Conclusion: Individuals with a COVID-19 diagnosis were more likely to report very short sleep, although they did not exhibit a greater likelihood of reporting more sleep complaints. Further research using longitudinal national data and examining environmental factors are needed to determine causality.
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Introduction: Little has been done to examine within/between group predictors and mediators of race/ethnic differences in sleep health outcomes, due to COVID-19 exposure. We evaluated the effect of COVID-19 exposure on sleep quality in a multiracial/ethnic sample of New York residents. Methods: We conducted a cross-sectional study among adults exposed to COVID-19 across New York State from September to November of 2020. Comparisons of participant characteristics e.g., mean scores by race/ethnicity status were made using one-way ANOVA for continuous variables, and chi-square tests for categorical variables. Associations between social determinants of health (employment, location), Trauma Coping Self-Efficacy (CES-T), and sleep quality (Pittsburgh Sleep Quality Index-PSQI) were examined using multilinear regression analysis stratified by race/ethnicity. Results: Of the 541 participants, 373 (68.9%) were female;mean age was 40.9 years (SD=15), 198 (36.6%) identified as Whites, 111 (20.5%) as Black, 97 (17.9%) as Hispanics, and 135(25%) identified as either Asians, Native-Americans, Pacific-Islanders. Sex was the strongest predictor [β = 1.335;p < .05] of sleep quality, but only among Whites. Trauma Coping Self-Efficacy was negatively associated with sleep quality among Asian, Native-American, or Pacific- Islander participants [β = -.114;p < .05 ];Black [β = -.099;p < .05] and White participants [β = -0.79;p < .05] but not among Latinos/ as [β = -.058;p = 0.71]. Conclusion: Coping Self-Efficacy moderated the effect of COVID-19 on sleep quality among some, but not all, racial/ethnic groups. While CSE-T scores during the first wave of COVID-19 acted as a protective factor for sleep quality among Asians, Native-Americans, and Pacific- Islanders, White and Black participants, this was not the case for Latinos/as/Hispanics residing in New York. Clinical interventions that are tailored for racial/ethnic, community and cultural needs may help to mitigate sleep problems associated with COVID-19 exposure.
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Introduction: Long-term exposure to pandemics like COVID-19 may increase psychological distress (e.g., peri-traumatic and post-traumatic distress) and sleep problems. Little is known about the effects of COVID-19 on peritraumatic distress, a well-documented risk factor for post-traumatic stress disorders (PTSD). The aim of this study was to investigate the association between COVID-19 risk perception and peritraumatic distress, and whether this relationship is moderated by sleep quality among individuals located in NY. Methods: We examined data from 541 individuals (69% were female, mean age (SD) = 40.9 (15.3)] recruited online during summer and fall 2020 in New York for the NYU-COVID-19 Mental Health Study. Data were gathered on sociodemographic, COVID-19 risk perception (yes or no items), peri-traumatic distress measured by Peritraumatic Distress Inventory (PDI), and sleep quality measured by the Pittsburg Sleep Quality Index (PSQI). Descriptive, regression analysis and interaction terms were conducted using SPSS v. 25 to examine associations between COVID-19 risk perception with symptoms of peritraumatic distress and sleep quality. Results: Of the 541 participants, 311(57.5%) reported they felt at risk for contracting COVID-19. PSQI was positively correlated with PDI (r =.38, p =0.01). An independent sample t student test indicated, on average, that the symptoms of PDI [(mean (SD)=27.3 (7.63), t = 7.07, n =307)] and PSQI [mean(SD)=10.62(3.57), t=4.31 n=311)] of our participants who felt at risk for contracting the COVID-19 significantly exceeded those who did not [(PDI mean(SD)=22.7(7.13), n =228);PSQI (mean(SD) =9.25(3.72), n=229]. Results of multiple linear regression analysis shown that COVID-19 risk perception was the strongest predictor of PDI [B(t) = -.630(12.7);p < .001]. Furthermore, the interaction effect of PSQI scores and COVID-19 risk perception revealed that sleep quality significantly reduced the association between COVID-19 risk perception and PDI [B(t) = .319(5.71);p <.001], such that poorer sleep and feeling at risk of contracting COVID-19 resulted in more severe PDI scores. Conclusion: COVID-19 risk perception was associated with peritraumatic distress and poorer sleep quality, and sleep quality attenuated this relationship.
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Introduction: Causes of COVID-19 burden in urban, suburban, and rural counties are unclear, as early studies provide mixed results implicating high prevalence of pre-existing health risks and chronic diseases. However, poor sleep health that has been linked to infectionbased pandemics may provide additional insight for place-based burden. To address this gap, we investigated the relationship between habitual insufficient sleep (sleep <7 hrs./24 hr. period) and COVID-19 cases and deaths across urban, suburban, and rural counties in the US. Methods: County-level variables were obtained from the 2014-2018 American community survey five-year estimates and the Center for Disease Control and Prevention. These included percent with insufficient sleep, percent uninsured, percent obese, and social vulnerability index. County level COVID-19 infection and death data through September 12, 2020 were obtained from USA Facts. Cumulative COVID-19 infections and deaths for urban (n=68), suburban (n=740), and rural (n=2331) counties were modeled using separate negative binomial mixed effects regression models with logarithmic link and random state-level intercepts. Zero-inflated models were considered for deaths among suburban and rural counties to account for excess zeros. Results: Multivariate regression models indicated positive associations between cumulative COVID-19 infection rates and insufficient sleep in urban, suburban and rural counties. The incidence rate ratio (IRR) for urban counties was 1.03 (95% CI: 1.01 - 1.05), 1.04 (95% CI: 1.02 - 1.05) for suburban, and 1.02 (95% CI: 1.00 - 1.03) rural counties. Similar positive associations were observed with countylevel COVID-19 death rates, IRR = 1.11 (95% CI: 1.07 - 1.16) for urban counties, IRR = 1.04 (95% CI: 1.01 - 1.06) for suburban counties, and IRR = 1.03 (95% CI: 1.01 - 1.05) for rural counties. Level of urbanicity moderated the association between insufficient sleep and COVID deaths, but not for the association between insufficient sleep and COVID infection rates. Conclusion: Insufficient sleep was associated with COVID-19 infection cases and mortality rates in urban, suburban and rural counties. Level of urbanicity only moderated the relationship between insufficient sleep and COVID death rates. Future studies should investigate individual-level analysis to understand the role of sleep mitigating COVID-19 infection and death rates.
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Introduction: An effective response to the COVID-19 pandemic has been the decision to subject individuals residing in New York City to quarantine rules in order to reduce the spread of the virus. As might have been expected, restriction of usual daily activities would affect individuals' sleep-wake patterns. It is also known that exposure to traumatic experiences can also engender sleep disturbances, most notably in their ability to initiate sleep. This study investigated the associations between sleep onset latency (SOL), pre and peri-COVID-19 exposure and symptoms of posttraumatic stress disorder (PTSD) among New Yorkers. Methods: 541 individuals (female = 373(69%);mean age=40.9) were recruited during the summer and fall of 2020 in New York City to participate in the NYU-COVID-19 Mental Health Study. Participants provided sociodemographic data and were also asked to respond to the COVID-19 quarantine experiences, comprised of seven binary questions, the PTSD Checklist-PCL-5, and the Pittsburg Sleep Quality Index. Descriptive and linear regression analysis were performed to explore associations of scores on the COVID-19 quarantine experience with PTSD and sleep data. All analyses were performed using SPSS 25.0 Results: Regression analyses revealed that SOL emerged as the strongest independent predictor of PTSD symptoms [B(t) = -.630(12.7);p < .001];factors adjusted in the model included pre and peri-COVID-19 factors such as age, sex, job type, and quarantine experience. Analyses assessing potential interaction effect revealed that quarantine experience did not affect the relationship between SOL and PTSD [B(t) = .086(.831);p = >.005]. The other sleep factors in the model did not yield significance. sleep duration had a weak correlation with quarantine, it was not found to be a predictor of PTSD. Conclusion: We observed that SOL was the most important determinant of PTSD symptoms among individuals exposed to COVID-19. This is consistent with other findings suggesting that a sizable proportion of individuals exposed to pandemics are likely to experience sleep disturbances. It is plausible that quarantine might lead to increased daytime naps, which may impact SOL. Further research is needed to better understand the association of SOL and PTSD as a result of Covid-19.
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Introduction: New York City has been one of the largest epicenters of the COVID-19 pandemic. This provided a wealth of data to examine the characteristics of COVID-19 patients in this multi-ethnic city, while assessing the contributions of cardio-metabolic burden and pulmonary conditions as potential “at-risk” conditions for COVID- 19. We assessed the relative contribution of common upper and lower airway pulmonary diseases in determining the likelihood of COVID- 19-related mortality independent of other medical conditions, health risks, and sociodemographic factors. Methods: We analyzed data from one of the largest US-based case series of patients with COVID-19, captured from an academic health network in NYC. A total of 11,512 hospitalized patients (March 2-May 24, 2020) were tested with 4,446 (38.62%) receiving a positive diagnosis for COVID-19. EHR queries yielded age at time of testing, sex, race/ethnicity aggregated as non-Hispanic black, Asian and Hispanic referenced to non-Hispanic white;cardio-metabolic conditions (hypertension, hyperlipidemia, diabetes, obesity, peripheral artery disease, and coronary artery disease);pulmonary disease (e.g., COPD, sleep apnea, or asthma);autoimmune disease;and cancer. Mortality was based on the patient state (alive or deceased) at the moment of discharge. We included only patients who had been discharged alive or had expired. Anaconda Python 3.7 was used to perform all analyses. Results: Among patients testing positive, 959 (21.57%) died of COVID-19-related complications at the hospital. Multivariateadjusted Cox proportional hazards modeling showed mortality risks were strongly associated with greater age (HR=1.05;95%CI:1.04- 1.05), ethnic minority (HR=1.26;95%CI:1.10-1.44), low household income (HR=1.29;95%CI:1.11, 1.49), and male sex (HR=0.85;95%CI:0.74, 0.97). Higher mortality risks were also associated with a history of COPD (HR=1.27;95%CI:1.02-1.58), obesity (HR=1.19;95%CI:1.04-1.37) and peripheral artery disease (HR=1.33;95%CI:1.05-1.69). We observed a significantly higher rate of COVID- 19 cases (43.8% vs 39.6%, p<0.05) among patients with sleep apnea (7.72%). However, they did not have a significantly higher mortality rate (13.0% vs 11.8%, NS), although they experienced a longer hospital stay (7.1±7.7 vs 6.1±7.5, p<0.01). Conclusion: Patients with COPD had the highest odds of COVID- 19 mortality. Sociodemographic factors including increased age, male sex, low household income, ethnic minority status were also independently associated with greater mortality risks.
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Introduction: The COVID-19 pandemic has caused widespread disruption and stress for people of all ages and circumstances around the world. This study investigates the relationship between general and specific stressors and various dimensions of sleep health. Methods: A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Participants were asked whether they experienced increased general, financial, food, housing, family and relationship stress due to the COVID-19 pandemic. They were also asked whether they experienced a more regular schedule, improved sleep, worsened sleep, more early insomnia, more middle-of-the-night insomnia, more daytime sleepiness, and more naps due to the COVID-19 pandemic. Ordinal logistic regressions with sleep change as outcome and stress variable as predictor were adjusted for age, sex, and race/ethnicity. Results: COVID-19-related general, financial, food, housing, family, and relationship stress were all associated with a decreased likelihood of maintaining a more regular schedule (oOR=0.52-0.67, all p<0.001) and improved sleep (oOR=0.56-0.67, all p<0.001). They were also all associated with a greater likelihood of worsened sleep (oOR=1.48- 2.41, all p<0.001), early insomnia (oOR=1.63-1.85, all p<0.001), middle-of-the-night insomnia (oOR=1.40-2.00, all p<0.001), and daytime sleepiness (oOR=1.58-2.07, all p<0.001). Increased napping was also associated with more COVID-related financial, food, and housing stress (oOR=1.33-1.55, all p<0.005). Conclusion: Regular sleep schedules can be disrupted by stressors directly, or by the anxiety that so often accompanies stress. Stressed individuals may experience increased difficulty falling asleep, or more nighttime arousals, or find themselves waking up earlier than usual, all as a result of ruminating thoughts, stress-induced nightmares, or outside disturbances. Disruption to sleep at night often results in increased daytime sleepiness and fatigue, with a higher chance of napping. This study reports the significant association of some of these with COVID- 19 pandemic-related stress. More individuals now find themselves working from home with greater flexibility in their schedules, but this has not necessarily led to better sleep. The impact of the pandemic on various health outcomes as a result of stress is still to be revealed.
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Introduction: The COVID-19 pandemic has affected sleep and diet for many people. The present study sought to examine potential associations between changes to sleep and eating habits during the COVID- 19 pandemic. Methods: A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Questions for diet asked, “since quarantine: I'm eating healthier, eating more processed foods, home-cooked meals and more regularly,” “I'm enjoying food in quarantine and I'm struggling with overeating in quarantine.” Sleep questions asked “since quarantine: I have managed to keep a regular sleep-wake schedule, my sleep has improved, I'm struggling to fall asleep, I'm waking up more during the night, I'm more sleepy during the day and I'm taking more naps during the day.” Answers were reported on a 4-point scale ranging from “strongly disagree to strongly agree.” Ordinal logistic regressions were used, adjusted for age and sex and examined each dietary variable as ordinal outcome and each sleep variable as predictor. Results: Those who report that they kept a more regular schedule were more likely to report eating healthier (oOR=3.13, p=0.007), eating more home-cooked meals (oOR=3.19, p=0.005), and less likely to be eating more processed foods (oOR=0.39, p=0.02), struggle with overeating (oOR=0.39, p=0.02) or undereating (oOR=0.30, p=0.004) or snacking (oOR=0.25, p=0.001). Those reporting more difficulty falling asleep were less likely to be eating healthier (oOR=0.25, p=0.002) and more likely to be eating more processed foods (oOR=3.07, p=0.009) and snacking (oOr=2.36, P=0.04). Those reporting more difficulty with awakenings were less likely to report eating healthier (oOR=0.34, p=0.03) and more likely to report eating more processed foods (oOR=4.52, p=0.001). Those with more sleepiness were less likely to report eating healthier (oOR=0.29, p=0.01) and more homecooked meals (oOR=0.40, p=0.046) and more likely to report eating more processed foods (oOR=6.42, p<0.0005), overeating (oOR=3.63, p=0.01) and snacking (oOR=5.81, p=0.001). Conclusion: Research studying psychological, behavioral and environmental factors that are contributing to changes in sleep and dietary patterns is especially important during a pandemic that has forced people into changes that they may not have been prepared for and which may result in long-term health outcomes.
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Introduction: The COVID-19 pandemic has disrupted life at the US-Mexico border in many ways, including sleep and dietary behavior. Given the potential long-term impact of worsening sleep and metabolic health due to the pandemic, the present study examines whether changes to dietary behavior were associated with changes to sleep. Methods: Participants were 155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) Study and were contacted about completing a COVID-19 sub-study (95% Hispanic/Latino). Participants reported the degree to which they experienced pandemic-related changes to sleep, including a more regular schedule, overall improvement, overall worsening, more initial insomnia, more middle-of-the-night insomnia, more daytime sleepiness, and more napping. They were also asked whether as a result of the pandemic they consumed an overall healthier diet, more homecooked meals, more processed meals, more regular meals, whether they enjoyed food more, and degree of overeating. Ordinal regressions with diet change as outcome and sleep change as predictor were adjusted for age, sex, education, and socioeconomics. Results: Those who reported more regular sleep were more likely to report a healthier overall diet (oOR=3.12,p<0.0005), more homecooked meals (oOR=2.18,p=0.001), more enjoyment of food (oOR=1.71,p=0.028), and less likelihood of overeating (oOR=0.59,p=0.033). Similarly, those who reported more “improved” sleep reported healthier overall diet (oOR=7.42,p<0.0005), more homecooked meals (oOR=2.59,p=0.001), more regular diet (oOR=2.15,p=0.006), more enjoyment of food (oOR=2.92,p<0.0005), less consumption of processed foods (oOR=0.54,p=0.039), and less overeating (0.33,p<0.0005). Those whose sleep worsened reported eating more processed foods (oOR=1.78,p=0.030) and overeating (oOR=3.90,p<0.0005). Those who reported more initial insomnia reported eating more processed foods (oOR=1.93,p=0.016), more regular diet (oOR=1.65,p=0.042), and overeating more often (oOR=4.11,p<0.0005). More middleof- the-night insomnia was associated with eating more processed foods (oOR=2.45,p=0.001), more regular diet (oOR=1.66,p=0.031), and overeating more often (oOR=3.68, <0.0005). Those with more daytime sleepiness also reported eating more processed foods (oOR=2.36,p=0.003), more regular diet (oOR=1.79, =0.019), and overeating more often (oOR=3.28,p<0.0005). More napping was associated with a more regular diet (oOR=1.90,p=0.011) and more overeating (oOR=3.53,p<0.0005). Conclusion: Overall, worse sleep led to worse dietary behavior, especially eating more processed food and overeating.
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Introduction: The COVID-19 pandemic has impacted many individuals at the vulnerable US-Mexico border region in a variety of ways. Fear, worry, and stress have increased for many, as has poor sleep. The present study evaluated the degree to which worsened sleep due to the pandemic impacted stress experiences. Methods: Participants were N=155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) and were contacted about completing a COVID sub-study (95% Hispanic/Latino). They were asked the degree to which their sleep worsened due to the pandemic. They also reported the degree to which they agreed with statements regarding various pandemic-related stress experiences. These included infection-related stresses, stresses about community impact, personal psychosocial stresses, stresses about consequences of potential infection, media and society-related stresses, feelings of safety, and how the pandemic has impacted home life. Ordinal logistic regressions were used to determine whether changes in sleep were associated with agreement with statements about pandemic-related stress experiences, adjusted for age, sex, financial status, education, and mental health (PHQ4). Results: Those who perceived that their sleep worsened were more likely to report greater endorsement of beliefs that they were infected (ordinal Odds Ratio [oOR]=2.82,p<0.0005), they could possibly be infected (oOR=1.98,p=0.003), they feared testing (oOR=1.94,p=0.006), COVID- 19 would impact their community (oOR=1.75,p=0.017) and would do so for a long time (oOR=1.90,p=0.006), they experience more general (oOR=4.10,p<0.0005), financial (oOR=3.15,p<0.0005), food-related (oOR=2.97,p<0.0005), housing-related (oOR=2.14,p=0.002), familyrelated (oOR=2.53,p<0.0005) and relationship (oOR=3.37,p<0.0005) stress, their shopping was impacted by scarcity (oOR=1.76,p=0.014), and they are at high risk for COVID (oOR=1.87,p=0.008). Furthermore, media coverage of COVID-19 had increased their stress (oOR=2.46,p<0.0005), there is too much panic about COVID-19 (oOR=1.67,p=0.032), and they themselves are scared of getting COVID-19 (oOR=1.95,p=0.005), worried about the future (oOR=1.71,p=0.022), feel less secure (oOR=0.59,p=0.028), are thriving less (oOR=0.40,p<0.0005), and their mental health is not improving (oOR=0.46,p=0.002). Conclusion: Worse sleep due to the COVID-19 pandemic was associated with increased reports of stresses across a wide range of domains. Perhaps sleep health interventions could improve social and emotional health in these domains and reduce stress experiences and better cope with the pandemic. Alternatively, mental health interventions should perhaps be targeted to this population.
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Introduction: The COVID-19 pandemic has caused major impacts to social and financial status for many people, including those living in the vulnerable US-Mexico border region. This study examined relationships between changes in sleep and perceived impacts to social and financial stability due to the pandemic. Methods: Participants were 155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) and were contacted about completing a COVID sub-study (95% Hispanic/Latino). Participants were asked if the COVID-19 pandemic was causing them to feel more socially isolated, negatively impacting their finances, causing increased worry about finances, affecting their primary job, causing a job loss, and impacting their belief life will one day return to normal. In addition, they were asked to report the degree to which they experienced pandemic-related changes to sleep, including a regularity, overall improvement/worsening, initial and middle-of-the-night insomnia, daytime sleepiness, and napping. Logistic regression analyses were adjusted for age, sex, socioeconomics, and mental health (PHQ4). Results: Those who kept a more regular schedule had lower odds of endorsing isolation (OR=0.32,p<0.0005) and higher odds of believing things will return to normal (OR=1.67,p=0.041). Those whose sleep improved also had lower odds of feeling isolated (OR=0.40,p=0.005). Those with worsened sleep had increased odds of feeling isolated (OR=2.14,p=0.023), experiencing a financial impact (OR=1.85,p=0.016) and increased financial worry (OR=1.71,p=0.033), and lower odds of believing things will return to normal (OR=0.53,p=0.012). More initial insomnia was associated with isolation (OR=3.62,p=0.001), financial impact, (OR=1.89,p=0.015), financial worry (OR=1.87,p=0.016) and job impact (OR=1.95,p=0.010). More middle-of-the-night insomnia was associated with financial worry (OR=1.82,p=0.016) and job impact (OR=1.93,p=0.009). More sleepiness was associated with job loss (OR=1.84,p=0.043). More napping was associated with financial impact (OR=1.89,p=0.017) and worry (OR=1.88,p=0.017), impact to job (OR=1.89,p=0.016) or lost job (OR=1.81,p=0.041), and decreased likelihood of believing things will return to normal (OR=0.45,p=0.003). Conclusion: Pandemic-related stress was linked with sleep disturbances. Worse sleep was indicative of increased social isolation, greater financial fears, more job-related impacts and less of a general sense that things would return to normal.