Produção Nacional
Habitual short sleepers with pre-existing medical conditions are at higher risk of Long COVID
2023; American Academy of Sleep Medicine; Volume: 20; Issue: 1 Linguagem: Inglês
10.5664/jcsm.10818
ISSN1550-9397
AutoresLinor Berezin, Rida Waseem, Ilona Merikanto, Christian Benedict, Brigitte Holzinger, Luigi De Gennaro, Yun Kwok Wing, Bjørn Bjorvatn, Maria Korman, Charles M. Morin, Colin A. Espie, Anne‐Marie Landtblom, Thomas Penzel, Kentaro Matsui, Harald Hrubos‐Strøm, Sérgio Mota‐Rolim, Michael R. Nadorff, Giuseppe Plazzi, Cátia Reis, Ngan Yin Chan, Ana Suely Cunha, Juliana Yordanova, Adrijana Koščeć Bjelajac, Yuichi Inoue, Yves Dauvilliers, Markku Partinen, Frances Chung,
Tópico(s)Sleep and Wakefulness Research
ResumoFree AccessScientific InvestigationsHabitual short sleepers with pre-existing medical conditions are at higher risk of Long COVID Linor Berezin, MD, Rida Waseem, MA, Ilona Merikanto, PhD, Christian Benedict, PhD, Brigitte Holzinger, PhD, Luigi De Gennaro, PhD, Yun Kwok Wing, FRCPsych, Bjørn Bjorvatn, MD, PhD, Maria Korman, PhD, Charles M. Morin, PhD, Colin Espie, PhD, Anne-Marie Landtblom, MD, PhD, Thomas Penzel, PhD, Kentaro Matsui, MD, PhD, Harald Hrubos-Strøm, MD, PhD, Sérgio Mota-Rolim, MD, PhD, Michael R. Nadorff, PhD, Giuseppe Plazzi, MD, PhD, Catia Reis, PhD, Rachel Ngan Yin Chan, PhD, Ana Suely Cunha, MD-St, Juliana Yordanova, MD, PhD, Adrijana Koscec Bjelajac, PhD, Yuichi Inoue, MD, PhD, Yves Dauvilliers, MD, PhD, Markku Partinen, MD, PhD, Frances Chung, MD Linor Berezin, MD Department of Anesthesia and Pain Management, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada Search for more papers by this author , Rida Waseem, MA Department of Anesthesia and Pain Management, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada Search for more papers by this author , Ilona Merikanto, PhD SleepWell Research Program, Faculty of Medicine, University of Helsinki, Orton Orthopaedics Hospital, Helsinki, Finland Search for more papers by this author , Christian Benedict, PhD Department of Pharmaceutical Biosciences, Molecular Neuropharmacology, Uppsala University, Uppsala, Sweden Search for more papers by this author , Brigitte Holzinger, PhD Institute for Consciousness and Dream Research, Vienna, Austria Medical University Vienna, Postgraduate Master Program Medical Sleep Coaching, Vienna, Austria Search for more papers by this author , Luigi De Gennaro, PhD Department of Psychology, Sapienza University of Rome, Rome, Italy IRCCS Fondazione Santa Lucia, Rome, Italy Search for more papers by this author , Yun Kwok Wing, FRCPsych Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China Search for more papers by this author , Bjørn Bjorvatn, MD, PhD Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway Search for more papers by this author , Maria Korman, PhD Department of Occupational Therapy, Faculty of Health Sciences, Ariel University, Ariel, Israel Search for more papers by this author , Charles M. Morin, PhD Centre de Recherche CERVO/Brain Research Center, École de Psychologie, Université Laval, Quebec City, Quebec, Canada Search for more papers by this author , Colin Espie, PhD Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom Search for more papers by this author , Anne-Marie Landtblom, MD, PhD Department of Medical Sciences, Neurology, Uppsala University, Uppsala, Sweden Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden Search for more papers by this author , Thomas Penzel, PhD Sleep Medicine Center, Charite University Hospital Berlin, Berlin, Germany Search for more papers by this author , Kentaro Matsui, MD, PhD Department of Clinical Laboratory, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Japan Search for more papers by this author , Harald Hrubos-Strøm, MD, PhD Department of Otorhinolaryngology, Akershus University Hospital, Lørenskog, Norway Institute of Clinical Medicine, University of Oslo, Oslo, Norway Search for more papers by this author , Sérgio Mota-Rolim, MD, PhD Brain Institute, Physiology and Behavior Department, and Onofre Lopes University Hospital Federal University of Rio Grande do Norte, Natal, Brazil Search for more papers by this author , Michael R. Nadorff, PhD Department of Psychology, Mississippi State University, Starkville, Mississippi, Mississippi Search for more papers by this author , Giuseppe Plazzi, MD, PhD IRCCS Istituto Delle Scienze Neurologiche di Bologna, Bologna, Italy Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy Search for more papers by this author , Catia Reis, PhD Universidade Católica Portuguesa, Católica Research Centre for Psychological Family and Social Wellbeing, Lisbon, Portugal Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal Search for more papers by this author , Rachel Ngan Yin Chan, PhD Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China Search for more papers by this author , Ana Suely Cunha, MD-St Medical College, Potiguar University, Natal, Brazil Search for more papers by this author , Juliana Yordanova, MD, PhD Institute of Neurobiology, Bulgarian Academy of Sciences, Sofia, Bulgaria Search for more papers by this author , Adrijana Koscec Bjelajac, PhD Institute for Medical Research and Occupational Health, Zagreb, Croatia Search for more papers by this author , Yuichi Inoue, MD, PhD Department of Somnology, Tokyo Medical University, Tokyo, Japan Japan Somnology Center, Institute of Neuropsychiatry, Tokyo, Japan Search for more papers by this author , Yves Dauvilliers, MD, PhD Sleep-Wake Disorders Center, Department of Neurology, Guide Chauliac Hospital, Institute for Neurosciences of Montpellier INM, INSERM, University of Montpellier, Montpellier, France Search for more papers by this author , Markku Partinen, MD, PhD Department of Clinical Neurosciences, University of Helsinki Clinicum Unit, Helsinki, Finland Helsinki Sleep Clinic, Terveystalo Healthcare Services, Helsinki, Finland Search for more papers by this author , Frances Chung, MD Address correspondence to: Frances Chung, MBBS, MD, FRCPC, Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto. 399 Bathurst St, Toronto, ON M5T 2S8, Canada; Email: E-mail Address: [email protected] Department of Anesthesia and Pain Management, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada Search for more papers by this author Published Online:January 1, 2024https://doi.org/10.5664/jcsm.10818SectionsAbstractEpubPDFSupplemental Material ShareShare onFacebookTwitterLinkedInRedditEmail ToolsAdd to favoritesDownload CitationsTrack Citations AboutABSTRACTStudy Objectives:Preliminary evidence suggests that the risk of Long COVID is higher among people with pre-existing medical conditions. Based on its proven adjuvant role in immunity, habitual sleep duration may alter the risk of developing Long COVID. The objective of this study was to determine whether the odds of Long COVID are higher among those with pre-existing medical conditions, and whether the strength of this association varies by habitual sleep duration.Methods:Using data from 13,461 respondents from 16 countries who participated in the 2021 survey-based International COVID Sleep Study II (ICOSS II), we studied the associations between habitual sleep duration, pre-existing medical conditions, and Long COVID.Results:Of 2,508 individuals who had COVID-19, 61% reported at least 1 Long COVID symptom. Multivariable logistic regression analysis showed that the risk of having Long COVID was 1.8-fold higher for average-length sleepers (6-9 h/night) with pre-existing medical conditions compared with those without pre-existing medical conditions (adjusted odds ratio [aOR] 1.84 [1.18–2.90]; P = .008). The risk of Long COVID was 3-fold higher for short sleepers with pre-existing medical conditions (aOR 2.95 [1.04–8.4]; P = .043) and not significantly higher for long sleepers with pre-existing conditions (aOR 2.11 [0.93–4.77]; P = .073) compared with average-length sleepers without pre-existing conditions.Conclusions:Habitual short nighttime sleep duration exacerbated the risk of Long COVID in individuals with pre-existing conditions. Restoring nighttime sleep to average duration represents a potentially modifiable behavioral factor to lower the odds of Long COVID for at-risk patients.Citation:Berezin L, Waseem R, Merikanto I, et al. Habitual short sleepers with pre-existing medical conditions are at higher risk of long COVID. J Clin Sleep Med. 2024;20(1):111–119.BRIEF SUMMARYCurrent Knowledge/Study Rationale: Preliminary evidence suggests that the risk of Long COVID is higher among people with pre-existing medical conditions. Based on its proven adjuvant role in immunity, habitual sleep duration may also alter the risk of Long COVID. We aimed to study the associations between habitual sleep duration, pre-existing conditions, and the risk of Long COVID.Study Impact: This study found that habitual short nighttime sleep duration exacerbated the risk of Long COVID in individuals with pre-existing conditions. Restoring nighttime sleep to average duration represents a potentially modifiable behavioral factor to lower the odds of Long COVID for at-risk patients.INTRODUCTIONAs of August 9, 2023, there have been more than 769 million laboratory-confirmed coronavirus disease 2019 (COVID-19) cases and 6.9 million deaths documented globally.1 While there has been significant emphasis on the acute phase of COVID-19, less attention has been given to the persisting symptoms. Individuals with COVID-19 are considered recovered after 2 weeks or after a negative COVID-19 test, but emerging data suggest that many continue to experience long-term sequelae. This constellation of persisting symptoms is known as post–COVID-19 condition, postacute sequelae of COVID-19 or “Long COVID”. Long COVID is defined by the World Health Organization (WHO) as the condition that occurs in people who have a history of probable or confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, usually within 3 months from the onset of COVID-19, with symptoms and effects that last for at least 2 months.2,3While most individuals fully recover, the global prevalence of Long COVID is estimated to be approximately 40%.4,5 Long COVID consists of diverse symptoms that include, but are not limited to, fatigue, dysgeusia, dyspnea, asthenia, persistent cough, muscle aches, depression, anxiety, cognitive dysfunction, and sleep problems.2,6–10 Long COVID is also associated with greater sleep alterations (sleep quality, daytime sleepiness, sleep inertia, naps, insomnia, sleep apnea, and nightmares).6 There is a greater incidence of Long COVID in individuals with greater body mass index (BMI), older age, female sex, pre-existing medical conditions, and severe COVID-19.8,11,12 The most frequent pre-existing conditions that have been linked to Long COVID include chronic obstructive pulmonary disease, fibromyalgia, anxiety, depression, migraine, multiple sclerosis, heart disease, hypertension, and diabetes.11–13Habitual sleep duration has been shown to impact health outcomes, all-cause mortality, and immunity in adults. There exists a clear U-shaped relationship between sleep duration and mortality, whereby both individuals with short (< 6 h/night) and long (> 9 h/night) habitual sleep duration have an increased risk of adverse outcomes.14–16 Long habitual sleep duration is associated with increased cardiovascular-related mortality, diabetes, all-cause mortality, and poorer mental health.17 It is also associated with increased levels of systemic inflammation and proinflammatory biomarkers, including C-reactive protein and interleukin-6.17 Similarly, individuals with short habitual sleep duration are at increased risk of mortality, diabetes, hypertension, cardiovascular disease, obesity, and respiratory infections.15 Habitual sleep duration is known to play a large role in adaptive immunity.18–20 These associations suggest that habitual sleep duration may play an important role in the development and pathogenesis of Long COVID, but whether the risk of developing Long COVID varies by nighttime sleep duration is unknown. It is possible that patients with pre-existing medical conditions and habitual short or long sleep duration are more prone to developing persisting COVID-19 symptoms compared with those with average sleep duration.To date, most research on Long COVID has focused on previously hospitalized patients with severe illness, but little is known about Long COVID in the general population and its association with habitual sleep duration and pre-existing medical conditions. Using a large, diverse multinational sample, the objective of our study was to examine whether habitual sleep duration alters the risk of Long COVID and its interaction with pre-existing medical conditions. We hypothesized that individuals with pre-existing comorbidities would have a higher probability of Long COVID, with exacerbation by short and long habitual sleep duration.METHODSGlobal COVID-19 surveyThe research protocol and standardized survey questionnaire have been published previously.21 The survey was designed by the International COVID Sleep Study (ICOSS) II group.22 All countries/regions obtained ethical approval or exemptions in keeping with national research governance and regulations (Table S1 in the supplemental material). The multinational cross-sectional survey was conducted between May and December 2021 in the general adult population in 16 countries in their native language (Austria, Brazil, Bulgaria, Canada, Hong Kong/China, Croatia, Finland, France, Germany, Israel, Italy, Japan, Norway, Portugal, Sweden, United States).21 The survey was administered online by sharing a link on national newspapers, social media sites, and university or hospital webpages. Participants aged 18 years or older, anonymously, and voluntarily, took part in the self-administered online survey. The most used survey platforms for administration were Redcap (Research Electronic Data Capture, Vanderbilt University, Nashville, Tennessee) and Qualtrics (Qualtrics, Provo, Utah).The survey included sociodemographic variables (age, sex, BMI) and pre-existing medical conditions. Participants were asked if they had tested positive for COVID-19. We considered COVID-19 cases as those who responded “yes” to both having had COVID-19 and testing positive for COVID-19. We considered COVID-19–negative control cases as those who reported not having had COVID-19 and did not report positive results from a COVID-19 test. Those who responded “yes” only for either having had COVID-19 or testing positive for COVID-19 were excluded. Participants were asked whether they have persistent symptoms related to COVID-19. We used the following definition of Long COVID, defined according to a Delphi consensus by the WHO: individuals with a history of confirmed or probable SARS-CoV-2 infection with at least 1 symptom lasting for over 3 months.2This research was conducted according to the Declaration of Helsinki, and all countries obtained ethical approval or exemptions in keeping with national research governance and regulations.Pre-existing medical conditionsPre-existing medical conditions were grouped into relevant categories: (1) chronic cardiac diseases, including arterial hypertension, atrial fibrillation, heart failure, other heart conditions, and stroke; (2) chronic respiratory diseases, including chronic obstructive pulmonary disease and asthma; (3) chronic neurological conditions, including cognitive impairment and problems of movement (tremor, rigidity, bradykinesia, and gait difficulty); (4) autoimmune conditions and cancer, such as autoimmune disease, use of cytostatic medications, immunosuppressive treatment, and allergy (atopy, seasonal allergy, other allergies); (5) endocrine disorders including type 1 and 2 diabetes; (6) chronic pain, including chronic pain syndromes, and migraine or headache; and (7) psychiatric conditions, including depression, anxiety, or panic disorder. Pre-existing medical conditions were defined as medical conditions existing prior to COVID-19. Those pre-existing conditions developed during or because of COVID-19 were excluded.Nighttime sleep durationSleep duration was assessed by self-report questions, where participants were asked, “How many hours per night did you sleep on average before the pandemic” and “How many hours per night did you sleep on average during the pandemic, prior to having COVID-19?” Self-reported sleep duration was used as an indicator for habitual sleep duration. Participants were classified into the average sleep duration category if they reported sleeping an average of 6 to 9 hours per night, short-duration sleepers if they slept, on average, less than 6 hours per night, and long-duration sleepers if they slept, on average, more than 9 hours per night.Clusters of Long COVID symptomsThe Long COVID symptoms were grouped into clusters relevant to the specific symptoms according to a recent systematic review and meta-analysis.4 Cardiac cluster symptoms included fatigue, dyspnea, palpitations, cardiac arrhythmia, tachycardia, postexertional malaise referring to prolonged weakness or poor functionality after exertion, such as muscle weakness, and difficulties walking long distances. Neurological cluster symptoms included attention or concentration problems, brain fog, cognitive dysfunction, memory problems, loss of smell or taste, hallucinations, and psychotic symptoms. Pain cluster symptoms included muscle pain or ache, joint pain, migraine, or headache. Dysautonomia cluster symptoms included dizziness, hypotension, urinary symptoms, sweating problem, heat or cold intolerance, abdominal pain or colic, diarrhea, and nausea or vomiting.4 In this study, sleep-related symptoms were not considered in the definition of Long COVID to avoid collinearity, since we studied the effect of sleep duration.Statistical analysisStatistical analysis was conducted using Stata version 14.2 (StataCorp, College Station, TX). The demographic data were summarized using means and standard deviations. The categorical variables were described using frequencies and percentages. Baseline demographic characteristics of participants with no COVID, Short COVID, and Long COVID, as well as habitual average, short, and long-duration sleep were compared using 1-way analysis of variance (ANOVA) and chi-square tests. Multivariable logistic regression analyses were conducted to examine the association between Long COVID with habitual sleep duration and pre-existing medical conditions, adjusting for age, sex, BMI, vaccination status, ethnicity, marital status, type of geographic area (rural vs urban), and exercise. Variables were chosen based on clinical significance and statistical significance in unadjusted analysis. Both adjusted (adjusted odds ratio [aOR]) and unadjusted odds ratios were reported. A P value < .05 was considered statistically significant (2-sided). All analyses were weighted by joint distribution of age and sex by country.RESULTSIn total, 16,899 participants completed the survey and 13,461 answered the specific questions about COVID-19 diagnosis. There were 10,953 participants with no prior COVID-19, 2,508 who had COVID-19, including 966 who did not report Long COVID symptoms (referred to as “Short COVID”). Among 1,542 participants with Long COVID, 1,505 also reported whether they had pre-existing medical conditions and their habitual sleep duration. Among them, 945 participants reported having pre-existing medical conditions prior to the pandemic (Figure 1). The numbers of habitual average-length sleepers, short, and long sleepers with and without pre-existing medical conditions are shown in Figure 1.Figure 1: Flow diagram of the included participants.Download FigureThere were significant differences between the demographic characteristics of the participants with Long COVID with average (6–9 hours), short (< 6 hours), and long habitual sleep duration (> 9 hours) (Table 1). Long sleepers were significantly younger (36.0 ± 14.7 years, P < .001) compared with short sleepers (44.5 ± 13.8 years) and those with average sleep duration (43.9 ± 13.5 years). A greater proportion of long sleepers and average-duration sleepers were of White ethnicity (90% and 86.6%, respectively) compared with short sleepers (76.1%). There were significantly more unvaccinated participants who reported habitual long sleep duration compared with average sleepers and short sleepers (38.9% vs 30.0% vs 21.4%, P = .049). In comparison to average and long sleepers, short sleepers had a significantly greater number of individuals with asymptomatic COVID-19 (6.3% vs 6.1% vs 9.6%, P = .002) and as well as those with severe or life-threatening COVID-19 (8.5% vs 6.1% vs 12.2%).Table 1 Characteristics of participants (n = 1,425) with Long COVID based on habitual sleep duration.VariablesAverage Sleep Duration (6–9 h) (n = 1,186)Short Sleep Duration (< 6 h) (n = 131)Long Sleep Duration (> 9 h) (n = 108)PAge, y43.9 ± 13.544.5 ± 13.836.0 ± 14.7<.001Sex, female961 (81.0)101 (77.1)91 (84.3).363Geophragical region, urban717 (78.3)69 (74.2)51 (72.9).414Ethnicity White789 (86.6)70 (76.1)63 (90.0).001 Asian35 (3.8)6 (6.5)3 (4.3) Black6 (0.7)3 (3.3)0 Hispanic23 (2.5)9 (9.8)2 (2.9) Other58 (6.4)4 (4.4)2 (2.9)Marital status Single224 (24.5)19(20.4)38 (54.3)<.001 Relations609 (66.5)69 (74.2)28 (40.0) Divorce/separated66 (7.2)4 (4.3)3 (4.3) Widowed17 (1.9)1 (1.1)1 (1.4)No. of vaccinations 0356 (30.0)28 (21.4)42 (38.9).049 1412 (34.8)49 (37.4)29 (26.9) 2417 (35.2)54 (41.2)37 (34.3)COVID-19 severity No marked symptoms40 (6.3)66 (9.6)6 (6.1).002 Mild352 (55.4)322 (46.6)63 (64.3) Moderate190 (29.9)219 (31.7)23 (23.5) Severe/life threatening54 (8.5)84 (12.2)6 (6.1)No. of pre-existing conditions 0129 (28.5)13 (26.5)10 (23.3).740 ≥ 1323 (71.5)36 (73.5)33 (76.7)Pre-existing conditions Cardiac193 (18.7)39 (33.6)*7 (6.6)<.001 Respiratory150 (13.3)19 (15.3)14 (14.0).819 Endocrine41 (3.5)10 (7.8)3 (2.8).050 Neurological97 (13.9)18 (22.0)13 (21.0).069 Autoimmune and cancer154 (13.5)12 (9.5)9 (8.7).188 Chronic pain220 (30.9)30 (39.0)20 (34.5).325 Depression/anxiety222 (25.2)15 (16.0)27 (32.1).098Values are expressed as n (%) or mean ± standard deviation, as appropriate. COVID-19 = coronavirus disease 2019.There were also significantly more individuals with pre-existing cardiac conditions among habitual short sleepers compared with average and long sleepers (33.6% vs 18.7% vs 6.6%, P < .001), but no differences between other types of pre-existing conditions, including respiratory, endocrine, neurological, autoimmune, or psychiatric pre-existing comorbidities. There were no significant differences among sexes and number of pre-existing medical conditions.Multivariable logistic regression analyses on the association of Long COVID with habitual sleep duration and presence of pre-existing medical conditions are shown in Table 2. The probability of Long COVID for average, short, and long sleepers with or without pre-existing medical conditions is shown in Figure 2. The model was adjusted for significant variables including sex, age, BMI, vaccination status, ethnicity, marital status, geophragical region, and exercise. Multivariable logistic regression analysis showed that the risk of having Long COVID was 1.8- fold higher for average-length sleepers with pre-existing medical conditions than those without pre-existing medical conditions (aOR 1.84 [1.18–2.90], P = .008) (Table 2, Figure 2). The risk of Long COVID was 3-fold higher for habitual short sleepers with pre-existing medical conditions (aOR 2.95 [1.04–8.4], P = .043) but not significantly higher for habitual long sleepers with pre-existing conditions (aOR 2.11 [0.93–4.77], P = .073) than the average sleepers without pre-existing conditions (Table 2, Figure 2).Table 2 Association of Long COVID with habitual sleep duration and presence of pre-existing medical conditions.VariablesUnadjusted ORPAdjusted ORPSex, female1.84 (1.42–2.37)<.0011.62 (1.05–2.50).029Age < 30 yReference 30–39 y2.45 (1.72–3.48)<.0012.72 (1.38–5.37).004 40–49 y3.48 (2.51–4.84)<.0012.64 (1.42–4.91).002 50–59 y3.50 (2.43–3.40)<.0012.50 (1.22–5.18).012 60–69 y2.10 (1.35–3.40).0012.17 (0.77–6.13).144 ≥ 70 y3.06 (1.63–5.74)<.0011.20 (0.25–5.77).820BMI > 30 kg/m21.76 (1.2–2.57).0041.32 (0.74–2.34).029No. of vaccinations 0Reference 11.91 (1.41–-2.58)<.0011.98 (1.13–3.46).017 > 11.29 (0.94–-1.77).0111.65 (1.00–2.73).049Marital status SingleReference Married3.46 (2.56–-4.68)<.0011.76 (1.05–2.96).032 Divorced9.81 (4.23–-22.70)<.0014.35 (1.27–14.90).020 Widowed9.10 (2.94–-28.10)<.0010.46 (0.09–2.49).369Urban area0.71 (0.53–0.97).0340.96 (0.62–1.49).851Vigorous intensity exerciseReference < 1 h0.50 (0.32–0.80).0030.84 (0.44–1.61).601 1–1.5 h1.01 (0.62–1.64).9591.04 (0.55–1.97).893 2–3 h0.42 (0.27–0.67)<.0010.99 (0.55–1.78).982 > 4 h0.20 (0.12–0.36)<.0010.73 (0.35–1.51).394Ethnicity WhiteReference Asian0.38 (0.23–0.62)<.0010.27 (0.12–0.62).002 Black0.15 (0.67–0.36)<.0010.23 (0.06–0.90).035 Hispanic1.21 (0.54–2.68).6440.83 (0.25–2.71).752 Other1.03 (0.54–1.99).9191.01 (0.38–2.70).980Average sleepers and no pre-existing medical conditionsReferenceShort sleepers and no pre-existing medical conditions1.34 (0.54–3.34).530.79 (0.17–3.60).759Long sleepers and no pre-existing medical conditions1.18 (0.31–4.47).810.94 (0.30–3.00).923Average sleepers and pre-existing medical conditions2.03 (1.39–3.00)<.0011.84 (1.18–2.90).008Short sleepers and pre-existing medical conditions2.60 (1.21–5.60).0142.95 (1.04–8.40).043Long sleepers and pre-existing medical conditions2.55 (1.16–5.59).0202.11 (0.93–4.77).073The model was adjusted for significant variables including sex, age, BMI, vaccination status, ethnicity, marital status, geographical region, and exercise. BMI = body mass index, OR = odds ratio.Figure 2: Probability of Long COVID based on habitual sleep duration stratified by the presence of pre-existing medical conditions.Normal sleepers refer to average-length sleepers.Download FigureThere was no significant increase in the risk of Long COVID for both long and short sleepers without pre-existing conditions. When average-length sleepers with pre-existing medical conditions are used as the reference group, the risk of Long COVID is significantly reduced for average sleepers with no pre-existing medical conditions (aOR 0.54 [0.35–0.90], P = .008) (Table 2, Figure 2). There were no significant differences in the risk of Long COVID for short and long sleepers with or without pre-existing medical conditions when compared with average sleepers with pre-existing medical conditions (Table S1). Female sex, age between 30 and 59 years, BMI over 30 kg/m2, COVID-19 vaccination, and married or divorced marital status were all significantly associated with an increased risk of developing Long COVID. Asian and Black ethnicity and male sex were found to decrease the risk of developing Long COVID.DISCUSSIONWe studied the associations between Long COVID, habitual sleep duration, and pre-existing medical conditions based on a multinational, cross-sectional survey. We found that prior-infection habitual short sleepers with pre-existing medical conditions had a higher likelihood of Long COVID. Notably, the risk of Long COVID was 3-fold higher for short sleepers with pre-existing medical conditions than average-duration sleepers without pre-existing conditions. Average-duration sleepers with pre-existing medical conditions had a 1.8-fold higher risk of developing Long COVID compared with those without pre-existing medical conditions. Long-duration sleepers were not found to have a significantly higher risk of developing Long COVID compared with those with or without pre-existing medical conditions. Thus, our results suggest that pre-existing medical conditions play a greater role in the development of Long COVID than habitual sleep duration. These associations persisted even after adjustment for demographic and socioeconomic covariates, as well as BMI and vaccination status.Our findings suggest that habitual short sleep duration may modulate the relationship between Long COVID and pre-existing medical conditions, and the interplay between sleep duration and pre-existing medical conditions may play an important role in the pathogenesis of Long COVID. Prior studies have shown that, among individuals double-vaccinated for COVID-19, those with habitual short duration sleep before the pandemic, but not long sleep duration, had a higher risk of Long COVID (aOR 1.56 [1.29–1.88] vs 1.18 [0.70–1.97]).23A study of over 400,000 participants using genetic variants associated with short and long sleep durations showed that genetically predicted short sleep duration had causal associations with 5 of 12 cardiovascular diseases, while genetically predicted long sleep duration lacked associations with any cardiovascular diseases.24 A genetic predisposition to short sleep duration may influence cardiovascular health through common pathophysiological mechanisms identified in insomnia, including sympathetic nervous system dysfunction, accelerated atherosclerosis, increased inflammation, and cardiovascular dysfunction.24 These same pathophysiological pathways may exacerbate the risk of Long COVID in short sleepers with pre-existing medical conditions.Our finding of increased Long COVID risk among habitual short sleepers with pre-existing medical conditions adds to the growing literature suggesting that short sleep duration impairs immune function. Associations have previously been found between habitual short sleep duration
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