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Poor Sleep during the First Peak of the SARS-CoV-2 Pandemic: A Cross-Sectional Study Abstract The restrictions enacted during lockdown to limit the spread of the novel coronavirus (SARS-CoV-2) have led to changes in people’s lifestyle habits. In Italy, these restrictions have dramatically changed the way people work and spend their leisure time, also with repercussions on diet and physical activity. An anonymous survey was disseminated via websites and social media to a convenience sample of the Italian population during and immediately after the first lockdown (10 March–18 May 2020). Data collected on 1826 individuals show that lockdown might have worsened the quality of sleep of almost half of the participants in this cross-sectional study. This worsening was associated with a deterioration in crucial determinants of health, such as physical activity and diet (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), with symptoms of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52) and loneliness (OR 3.27; 95% CI 2.23–4.79), and with the presence of financial problems (some OR 1.86; 95% CI 1.27–2.72; many OR 7.27; 95% CI 3.59–14.73). The multivariate regression analysis models confirmed these associations. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems. 1. Introduction The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed the world population under enormous stress. Large geographical areas and the resident populations have been forced to undergo periods of lockdown to halt the spread of the virus and to limit the impact on healthcare systems. In March 2020, the Italian Government imposed two months of emergency lockdown, with containment measures unheard of in the national territory, sometimes characterized by mandatory quarantine [1]. These measures included the closing of businesses, schools and universities, and the banning of all recreational outdoor activities; the only exceptions were the provision of essential services for health and basic needs (i.e., food, municipal services, etc.). The lockdown radically altered the population’s lifestyle, and several containment measures lasted for weeks beyond the end of the full lockdown period: many people saw their work temporarily suspended, others were forced to work or study from home, and everybody was subjected to mobility restrictions and were obliged to cease any non-essential activity. While these measures were essential to reducing outbreaks, they may have led to the adoption of unhealthy behaviours (e.g., more sedentary lifestyle, changes in diet) [2]. Further, these strong limitations on personal freedom could have led to increased levels of psychological distress in the population [3] caused by the fear of getting sick, the fear of experiencing financial problems, the increased tension in households, as well as the isolation from elderly family members, who are at greater risk of death. All these factors could have worsened the quality of sleep, defined as one’s satisfaction with the sleep experience, which integrates aspects of sleep initiation, sleep maintenance, sleep quantity, and refreshment upon awakening [4]. Unsatisfactory sleep can lead to short and long-term harmful psychological and psychosocial effects on health [5,6]. Thus, this observational study aimed to investigate the quality of sleep in a convenience sample of Italians under lockdown during the first epidemic peak of the COVID-19 pandemic. We also investigated the associations between the quality of sleep and sociodemographic characteristics, changes in lifestyle, and the presence of psychological distress. 2. Materials and Methods This cross-sectional study was endorsed by the Local Health Authority (LHA) of the Province of Reggio Emilia (Italy), with a population of 533,158; 66% of the population is between the ages of 18 and 70. This province was one of the most affected by the first epidemic peak of COVID-19 in Italy, with a daily incidence rate of about 8/1000 inhabitants during lockdown (10 March–18 May 2020) [7]. An online survey investigating lifestyle habits and any changes that occurred during lockdown was developed by two epidemiologists, two physiotherapists, and one occupational therapist. The survey did not collect personal data and was completely anonymous as to the source, which is why the consulted Local Ethics Committee deemed approval unnecessary. However, the survey underwent an ethics review conducted by an expert in the field; after approval, it was disseminated online to individuals living in the Province of Reggio Emilia. The survey was advertised through the websites and social media of the LHA, the major municipalities of the province, the network of the municipal pharmacies, and the local patient associations that joined the initiative. Citizens could access the survey without restrictions and in complete anonymity from 4 May 2020 until 15 June 2020. The survey (Supplementary Material File S1) explored the following areas: (a) sociodemographic data (14 questions); (b) work-related data (5 questions); (c) use of digital devices (3 questions); (d) lifestyle and general health (23 questions); (e) use of local social support services (3 questions); and (f) symptoms of psychological distress, i.e., the sense of tension, upset, worry, fear, loneliness, and/ or uncertainty (one question). Apart from two open-ended questions, the answers were multiple-choice. In some cases, more than one choice was possible. The survey took an average of 15 min to complete. The main outcome of this cross-sectional study was to describe the quality of sleep during and immediately after lockdown, investigated through the following two questions: “Have your sleep habits changed since the beginning of lockdown (amount and/or regularity of sleep)?” and “How do you rate your sleep quality now”? We also searched for associations between sleep quality categories and sociodemographic and occupational characteristics, changes in lifestyle (physical activity, eating habits, smoking, and alcohol consumption), and psychological distress. 2.1. Data Privacy and Consent for Participation During the informed consent process, participants were informed that all data would be anonymized at the source and would be used exclusively for research purposes. By completing the survey, participants voluntarily consented to participate in this study. As response would be saved only by clicking the “submit” button, that participant could stop participating in the study at any stage before submission, and their responses would not be saved. As the survey was disseminated to the local community, participants were not asked to provide name, date of birth, residency, and/or job to ensure complete anonymity. 2.2. Statistical Analysis Participants who completed the survey were categorized based on the dependent variable, i.e., their self-reported quality of sleep. They were grouped by sex, age class, education level, household composition, any financial problems, occupational status, lifestyle habits, and psychological distress. We report both the number and proportion of missing values. We looked for associations (crude odds ratio—OR—and its 95% confidence interval—95% CI) between the sociodemographic and occupational characteristics, changes in lifestyle, and the presence of psychological distress as independent variables and the quality of sleep categories. Separate models of multivariate regression analysis, all adjusted for age, sex, and education level, were built for any of the independent variables which, based on the crude OR and its 95% CI, proved to be strongly associated with quality of sleep. Missing values were not included in the analyses. Statistical analyses were performed using jamovi 1.2.27 (Jamovi Project, Sydney, Australia) [8]. 3. Results Overall, 1826 citizens in the Province of Reggio Emilia participated in the study. Most were female (76.5%), aged 18 to 64 years (88.7%), with medium-high education level (92.8%), and with no financial problems (72.3%). Most lived with one or more individuals (88.6%) and continued to work (in person or remote) during lockdown (69.8%) (Table 1). At the time of the survey, most participants reported good sleep quality (n = 1026; 56.2%), with 39.5% (n = 721) reporting poor sleep quality. However, 53.7% of participants experienced a change in their sleep habits since the beginning of lockdown, more frequently represented by a decrease in the amount and/or regularity of sleep (OR 3.68; 95% CI 2.32–5.82; p < 0.001). About one third of participants reported that their physical activity habits worsened (35.1%), while far fewer reported an improvement (5.3%). Most participants reported that their eating habits had changed: about one third reported an improvement (33.5%), i.e., all the self-reported changes went in the direction of a healthier diet (e.g., eating more fruit and vegetables, regular meals, etc.); others reported a worsening (17.6%), i.e., all changes went in the direction of a less healthy diet (e.g., more prepackaged foods, carbonated drinks), and 18.5% of participants had both changes in the direction of healthier and less healthy diet. Alcohol consumption changed for an overlapping number of participants (increased or decreased, 12.5% and 12.7%, respectively), and lower proportions of participants reported that their smoking habits had increased or decreased (7.7% and 4.1%, respectively). More than half of participants experienced feelings of uncertainty (54.5%). Moreover, a considerable proportion of individuals experienced emotions of worry (44.4%), upset (20.4), tension (19.7%), fear (16.6%) and loneliness (13.6%). Male sex seemed to be associated with better sleep quality (OR 0.47; 95% CI 0.29–0.76), as was a high education level compared to low (OR 0.44; 95% CI 0.23–0.81). Factors more strongly associated with poor sleep quality were the presence of some or many financial problems (OR 1.86; 95% CI 1.27–2.72 and OR 7.27; 95% CI 3.59–14.73, respectively), a change toward less physical activity or worse eating habits (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), and perceiving feelings of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52), loneliness (OR 3.27; 95% CI 2.23–4.79), upset (OR 3.26; 95% CI 2.29–4.64) uncertainty (OR 2.89; 95% CI 1.93–4.31), fear (OR 2.74; 95% CI 1.89–3.97), and/or worry (OR 2.50; 95% CI 1.75–3.58). A change toward mixed behaviour in eating habits was also associated with poor sleep quality. The multivariate regression analysis models confirmed the association between poor sleep quality and the presence of some or many financial problems (OR 1.74; 95% CI 1.17–2.57 and OR 6.96; 95% CI 3.32–14.55, respectively) and less physical activity or worse eating habits (OR 1.62; 95% CI 1.13–2.32 and OR 3.7; 95% CI 2.2–6.24, respectively). Again, the association between a change toward mixed behaviour in eating habits and poor sleep quality was confirmed in the adjusted model of multivariate regression analyses. The regression models also confirmed the association between poor sleep quality and the presence of a sense of tension (OR 3.51; 95% CI 2.44–5.03), loneliness (OR 3.07; 95% CI 2.07–4.53) upset (OR 3.01; 95% CI 2.10–4.32), uncertainty (OR 2.71; 95% CI 1.81–4.06) fear (OR 2.42; 95% CI 1.65–3.54) and/ or worry (OR 2.30; 95% CI 1.60–3.32) (Appendix A). 4. Discussion The results of this study highlight the association between lockdown and poor sleep quality in the Italian population. These results suggest that lockdown might impact sleep quality and that this association could be mediated by crucial determinants of health, such as physical activity and diet, and to a lesser extent, smoking and alcohol consumption, the presence of financial problems, and symptoms of psychological distress. Indeed, anxiety was widespread among the Italian population during lockdown, as were feelings of uncertainty, fear, and loneliness [9,10]. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems. Since the beginning of the pandemic, observational, mostly cross-sectional, studies have been conducted around the world to study lifestyle changes in populations subjected to restrictions. While sleep quality has been frequently investigated, results have not always been consistent. In China, Wang and colleagues found that 75% of 2289 individuals isolated at home rated their sleep as very good [11], but a smaller prospective study found that 37% of a sample of young Chinese adults reported a worsening of their sleep quality during the pandemic [12]. Studies conducted in other countries have demonstrated that lockdown could either lead to an increase in the amount of time spent in bed [13,14], with good sleep efficiency [13] or associated with sleep disorders [15,16] and disruption of one’s habitual circadian rhythm [14]. This topic has also been investigated in Europe, where 55% of Spanish adults changed their sleep pattern after the beginning of the lockdown [17], and individuals who were physically active prior to the SARS-CoV-2 spread reported major sleep problems [18]. In Italy, cross-sectional investigations have suggested that while the number of hours spent in bed might have increased during lockdown [2], many individuals reported insomnia (43%) [19] and poor sleep quality (57%) [9]. Similar percentages of sleep deterioration (48%) were also shown in the UK [20], and a longitudinal study conducted in Italy confirmed the detrimental effects of the 40-day lockdown on all the parameters of the Sleep Quality Index [21], except for sleep duration [22]. Our cohort seems to confirm that sleep quality deteriorated during lockdown, as among those individuals who experienced a change in their sleep quality, 85.8% defined their sleep as poor. This proportion of individuals accounted for 46% of the entire cohort investigated, which is strikingly similar to the proportion of those who reported a worsening of sleep quality in the above-mentioned Italian studies. Our results corroborate the findings of previous research that the worsening of sleep quality during lockdown was more pronounced among females [9,23,24]. Poor sleep quality was strongly associated with the presence of many financial problems, although this group in our cohort accounted for a very small proportion of participants (2.1%). However, poor sleep quality was not associated with the interruption of work. One possible explanation for these apparently inconsistent data could be because of the economic measures promptly introduced by the Italian Government to counter the economic effects of the forced closure of most businesses. Similarly, a large survey conducted in the UK found that poor sleep quality during lockdown was associated with perceived financial problems, but not with unemployment [23]. In this study, 35.1% of individuals reported a worsening of their level of physical activity, which proved to be a determinant of poor sleep quality in the multivariate analysis. This result was not surprising, as a moderate effect of regular exercise on overall sleep quality is well documented [25,26,27], and the association between less exercise and sleep disorders was confirmed during lockdown in a sample of German individuals [16]. In addition, 17.6% of individuals declared a change for the worse in their eating habits, which was associated with poor sleep quality. This proportion of individuals who adopted a less healthy diet is lower than the 35.8% estimated by Di Renzo and colleagues in a cross-sectional survey, which involved 3533 Italians throughout the country [2]. In this regard, it should be noted that 18.5% of our sample introduced changes in their diet that we categorized as mixed, because they were neither completely positive nor completely negative. It is plausible that some of these mixed changes, upon further investigation, could be reclassified as worse. In fact, the association between sleep quality and this type of mixed change in eating habits went in the same direction as that shown by the worsening of one’s diet. Still, regardless of the accuracy of the categorization for this predictive variable, it seems certain that several individuals’ diets worsened and that this was associated with poorer sleep. This also seems to be true outside of Italy, as data collected from more than 1000 individuals in three different continents, including Europe, which found that unhealthy diet increased by 10% during the period of social isolation, and that worse eating habits were significantly associated with a worsening in sleep quality [15]. Finally, our results confirm the association between poor sleep quality and symptoms of psychological distress. The positive relationship between anxiety and poor sleep quality has been extensively investigated and was confirmed during lockdown [9,20,26]. While the cross-sectional design of our study does not allow us to verify whether the symptoms of psychological distress that we documented were related to the restrictions imposed to curtail the spread of the SARS-CoV-2 virus, a causal relationship is plausible, as also suggested by the literature [9,10,15,16,20,28]. The convenience sample investigated was recruited in the Province of Reggio Emilia, one of the most affected Italian provinces during the early phase of the pandemic. Considering that, at the time of the survey, little or nothing was known about the disease and its prognosis, it is plausible that feelings of fear and uncertainty were more widespread in the populations living in areas with a high prevalence of infection [9,29]. Added to this were the concerns arising from the forced temporary closure of many business and industries in one of the most productive areas of Italy and of Europe. The COVID-19 pandemic has called into question the stability of the Italian National Health Service, also triggering uncertainties regarding the continuity of care for thousands of individuals, often elderly and with comorbidities, in one of the longest-lived countries in the world. Therefore, the association between poor sleep quality and feelings of fear and uncertainty was expected. Less obvious was the relationship between poor quality sleep and feelings of loneliness as, based on the univariate analysis conducted, living alone was not a predictor of poor sleep quality. Thus, loneliness was perceived regardless of the presence of other household members; the reasons underlying this feeling must be sought in other causalities. We have no explanation for this, but it is possible that forced living with others in close quarters for an extended period may have worn down the quality of relationships between individuals, or loneliness may have been due to the forced separation from important, vulnerable family members. Moreover, the sense of loneliness could also have derived from the need to limit interpersonal contact to a minimum, a measure that, while necessary to reduce the contagion, is in stark contrast with Italian culture. Limitations and Strengths The results of this study should be interpreted with caution as they derive from a cross-sectional design, which makes causal inferencing challenging. Moreover, the survey sampling was based on an online invitation, which does not allow for generalization because the population that does not use the Internet was not explored. Indeed, a recruitment bias emerged in our sample, as females and working-age individuals with a high education level are overrepresented compared to the general Italian population. While the overrepresentation of females is a feature common to other similar studies [2,9,16,20,28,30], it is likely that the biases observed in age and education reflect a high level of adhesion of participants who are also healthcare professionals or administrative staff of the LHA or of the major municipalities of the Province of Reggio Emilia, which disseminated the survey through their social media and websites. Moreover, the outcome of interest and data related to predictive variables were collected through self-reporting rather than through a valid survey or clinical assessment. This was because, as we wanted to capture the changes that occurred during lockdown through a cross-sectional design, we chose specific questions to comply with this purpose. Finally, we decided to observe the association between each change occurring during the lockdown, adjusting only for those variables that certainly could not change during the study period and cannot be intermediate effectors of the other putative exposure. However, this approach does not allow us to rule out that some of the observed associations were not independent and could have been due to confounding or could have been mediated by other putative exposures. Despite these limitations, this study had a relatively high acceptance in our community. The sampling strategy allowed us to collect data from quite a large sample, which in fact numerically mirrors that investigated by other similar study designs conducted to explore the same theme [9,15,28,30]. Further, this was the only sampling method feasible during lockdown. 5. Conclusions The quality of sleep, one of the determinants of public health, was adversely affected by the lockdown. Our study points out that nearly all individuals who experienced a change in their sleep reported poor quality of the same. This result is plausible, considering the fast disruption of routine caused by the pandemic. In fact, individuals’ well-being may have been seriously affected when both personal and public safety are no longer predictable, regardless of their resilience and their capacity for adaptation in daily life. We highlighted the effect that sociodemographic and occupational characteristics, changes in lifestyle, and psychological distress have on sleep quality. While this study design does not allow us to determine a causal relationship among potential determinants and poor sleep quality, it nevertheless highlights the presence of categories of people who suffered the most: socially fragile individuals, those reporting negative changes in physical activity and diet, and individuals with psychological distress. These categories require the attention of policy makers, who should plan strategies to promote healthy lifestyles and strategies to maintain serenity during this difficult period. Considering that the SARS-CoV-2 infections rate has been increasing since October 2020 and that several restrictions have been reintroduced to contain the spread of the virus, further investigations on this topic should be implemented. For example, studies exploring whether sleep has been affected during this second epidemic peak as well or whether individuals have adapted to the situation and have found strategies to deal with the limitations and uncertainties related to the SARS-CoV-2 spread would be of interested. Acknowledgments We thank Jacqueline M. Costa for the English language editing. We thank Ludovica De Panfilis for reviewing the survey for ethics. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Materials The following are available online at https://www.mdpi.com/1660-4601/18/1/306/s1, File S1: Survey on Lifestyle Adaptations in the General Population of the Province of Reggio Emilia Following the Emergency Quarantine COVID-19. Click here for additional data file. Author Contributions All authors contributed to the study conception and design and to interpretation of data. P.G.R., S.C., B.B., S.P., and E.M. developed the survey. S.P. and B.B. contributed to data analysis. The first draft of the manuscript was written by S.C., and all authors commented and contributed to it. All authors have read and agreed to the published version of the manuscript. Funding The Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia fully supported this study. Institutional Review Board Statement Not applicable. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The dataset generated and analyzed is retained by the Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia (Italy) and is available upon request from the corresponding author. Conflicts of Interest The authors do not have any conflicts of interest to disclose. Appendix A Table A1 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496 Sex Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724 Age class Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023 Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262 Education level High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679 Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787 Financial problems Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556 Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576 Table A2 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574 Sex Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753 Age class Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906 Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309 Education level High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550 Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737 Change in PA habits Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563 Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321 Legend PA = Physical activity. Table A3 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333 Sex Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861 Age class Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264 Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346 Education level High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671 Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843 Change in eating habits Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492 Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242 Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890 Table A4 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410 Sex Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799 Age class Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479 Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455 Education level High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662 Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885 Tension Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033 Table A5 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498 Sex Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730 Age class Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212 Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382 Education level High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580 Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782 Upset Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324 Table A6 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400 Sex Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882 Age class Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096 Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180 Education level High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666 Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883 Worry Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324 Table A7 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553 Sex Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808 Age class Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055 Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234 Education level High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623 Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814 Fear Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548 Table A8 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538 Sex Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728 Age class Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016 Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267 Education level High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650 Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838 Loneliness Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536 Table A9 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325 Sex Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856 Age class Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964 Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250 Education level High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649 Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903 Uncertainty Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069 Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”. Table 1 Odds ratio for quality of sleep during lockdown by sociodemographic characteristics, work-related factors, changes in lifestyle and psychological distress. Total Poor Sleep Good Sleep Missing n % n % n % n % 1826 100 721 39.5 1026 56.2 79 4.3 OR 95% CI p-Value Lower Upper Sociodemographic characteristics Sex Female 1397 76.5 601 43.0 732 52.4 64 4.6 1.00 Male 423 23.2 119 28.1 293 69.3 11 2.6 0.47 0.29 0.76 0.002 Missing 6 0.3 1 16.7 1 16.7 4 66.7 Age 18-44 818 44.8 327 40.0 467 57.1 24 2.9 1.00 45-64 802 43.9 336 41.9 438 54.6 28 3.5 0.95 0.67 1.34 0.771 >65 194 10.6 55 28.4 118 60.8 21 10.8 0.54 0.26 1.11 0.092 Missing 12 0.7 3 25.0 3 25.0 6 50.0 Education level Low 94 5.1 38 40.4 50 53.2 6 6.4 1.00 Medium 805 44.1 329 40.9 432 53.7 44 5.5 0.55 0.30 1.03 0.066 High 889 48.7 338 38.0 527 59.3 24 2.7 0.44 0.23 0.81 0.009 Missing 38 2.1 16 42.1 17 44.7 5 13.2 Household Alone 208 11.4 77 37.0 129 62.0 2 1.0 1.00 ≥1 person 1618 88.6 644 39.8 897 55.4 77 4.8 1.06 0.62 1.79 0.834 Financial problems No problems 1320 72.3 464 35.2 794 60.2 62 4.7 1.00 Some problems 399 21.9 204 51.1 187 46.9 8 2.0 1.86 1.27 2.72 0.001 Many problems 38 2.1 23 60.5 15 39.5 0 0.0 7.27 3.59 14.73 <0.001 Missing 69 3.8 30 43.5 30 43.5 9 13.0 Occupational status during lockdown Continue working 1275 69.8 495 38.8 726 56.9 54 4.2 1.00 Activity stopped 181 9.9 82 45.3 96 53.0 3 1.7 1.33 0.80 2.21 0.266 Retir. Stud. Housew. 240 13.1 86 35.8 143 59.6 11 4.6 0.73 0.42 1.29 0.288 Unemployed 55 3.0 28 50.9 25 45.5 2 3.6 1.09 0.42 2.81 0.848 Missing 75 4.1 30 40.0 36 48.0 9 12.0 Changes in lifestyle Change in sleep habits Unchanged 701 38.4 645 92.0 24 3.4 34 4.9 1.00 Changed 981 53.7 842 85.8 121 12.3 17 1.7 3.86 2.46 6.05 <0.001 Uncertain 80 4.4 67 83.8 3 3.8 10 12.5 1.20 0.35 4.10 0.760 Missing 64 3.5 21 32.8 25 39.1 18 28.1 Change in physical activity habits Unchanged 972 53.2 349 35.9 596 61.3 27 3 1.00 Improved 97 5.3 37 38.1 56 57.7 4 4.1 0.59 0.21 1.68 0.330 Worsen 641 35.1 288 44.9 334 52.1 19 3.0 1.68 1.18 2.40 0.004 Missing 116 6.4 47 40.5 40 34.5 29 25.0 Change in eating habits Unchanged 530 29.0 152 28.7 361 68.1 17 3.2 1.00 Improved 612 33.5 237 38.7 361 59.0 14 2.3 1.49 0.89 2.51 0.125 Worsen 321 17.6 171 53.3 128 39.9 22 6.9 4.19 2.51 6.96 <0.001 Mixed behav. 337 18.5 156 46.3 164 48.7 17 5.0 2.41 1.40 4.15 0.001 Missing 26 1.4 5 19.2 12 46.2 9 34.6 Change in alcohol consumption Unchanged 1275 69.8 496 38.9 726 56.9 53 4.2 1.00 Decreased 231 12.7 90 39.0 138 59.7 3 1.3 0.73 0.41 1.28 0.280 Increased 229 12.5 107 46.7 112 48.9 10 4.4 1.34 0.84 2.13 0.209 Missing 91 5.0 28 30.8 50 54.9 13 14.3 Change in smoking habits Unchanged 1327 72.7 519 39.1 780 58.8 28 2.1 1.00 Decreased 75 4.1 33 44.0 40 53.3 2 2.7 0.79 0.31 2.01 0.628 Increased 140 7.7 64 45.7 67 47.9 9 6.4 1.39 0.78 2.47 0.251 Missing 284 15.6 105 37.0 139 48.9 40 14.1 Psychological distress Tension No 1337 73.2 452 33.8 838 62.7 47 3.5 1.00 Yes 359 19.7 232 64.6 107 29.8 20 5.6 3.88 2.74 5.52 <0.001 Missing 130 7.1 37 28.5 81 62.3 12 9.2 Upset No 1284 70.3 444 34.6 804 62.6 36 2.8 1.00 Yes 372 20.4 230 61.8 135 36.3 7 1.9 3.26 2.29 4.64 <0.001 Missing 170 9.3 47 27.6 87 51.2 36 21.2 Worry No 914 50.1 271 29.6 614 67.2 29 3.2 1.00 Yes 810 44.4 421 52.0 366 45.2 23 2.8 2.50 1.75 3.58 <0.001 Missing 102 5.6 29 28.4 46 45.1 27 26.5 Fear No 1404 76.9 501 35.7 847 60.3 56 4.0 1.00 Yes 303 16.6 180 59.4 116 38.3 7 2.3 2.74 1.89 3.97 <0.001 Missing 119 6.5 40 33.6 63 52.9 16 13.4 Loneliness No 1439 78.8 524 36.4 869 60.4 46 3.2 1.00 Yes 249 13.6 151 60.6 94 37.8 4 1.6 3.27 2.23 4.79 <0.001 Missing 138 7.6 46 33.3 63 45.7 29 21.0 Uncertainty No 778 42.6 239 30.7 499 64.1 40 5.1 1.00 Yes 996 54.5 468 47.0 499 50.1 29 2.9 2.89 1.93 4.31 <0.001 Missing 52 2.8 14 26.9 28 53.8 10 19.2 Legend: OR = Odds ratio; CI = Confidence Interval; Retir. = retired; Stud. = student; Housew. = housewife; behav. = behaviour Note: OR and CI were not calculated for missing values.

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article-title	Poor Sleep during the First Peak of the SARS-CoV-2 Pandemic: A Cross-Sectional Study
abstract	The restrictions enacted during lockdown to limit the spread of the novel coronavirus (SARS-CoV-2) have led to changes in people’s lifestyle habits. In Italy, these restrictions have dramatically changed the way people work and spend their leisure time, also with repercussions on diet and physical activity. An anonymous survey was disseminated via websites and social media to a convenience sample of the Italian population during and immediately after the first lockdown (10 March–18 May 2020). Data collected on 1826 individuals show that lockdown might have worsened the quality of sleep of almost half of the participants in this cross-sectional study. This worsening was associated with a deterioration in crucial determinants of health, such as physical activity and diet (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), with symptoms of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52) and loneliness (OR 3.27; 95% CI 2.23–4.79), and with the presence of financial problems (some OR 1.86; 95% CI 1.27–2.72; many OR 7.27; 95% CI 3.59–14.73). The multivariate regression analysis models confirmed these associations. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems.
p	The restrictions enacted during lockdown to limit the spread of the novel coronavirus (SARS-CoV-2) have led to changes in people’s lifestyle habits. In Italy, these restrictions have dramatically changed the way people work and spend their leisure time, also with repercussions on diet and physical activity. An anonymous survey was disseminated via websites and social media to a convenience sample of the Italian population during and immediately after the first lockdown (10 March–18 May 2020). Data collected on 1826 individuals show that lockdown might have worsened the quality of sleep of almost half of the participants in this cross-sectional study. This worsening was associated with a deterioration in crucial determinants of health, such as physical activity and diet (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), with symptoms of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52) and loneliness (OR 3.27; 95% CI 2.23–4.79), and with the presence of financial problems (some OR 1.86; 95% CI 1.27–2.72; many OR 7.27; 95% CI 3.59–14.73). The multivariate regression analysis models confirmed these associations. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems.
body	1. Introduction The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed the world population under enormous stress. Large geographical areas and the resident populations have been forced to undergo periods of lockdown to halt the spread of the virus and to limit the impact on healthcare systems. In March 2020, the Italian Government imposed two months of emergency lockdown, with containment measures unheard of in the national territory, sometimes characterized by mandatory quarantine [1]. These measures included the closing of businesses, schools and universities, and the banning of all recreational outdoor activities; the only exceptions were the provision of essential services for health and basic needs (i.e., food, municipal services, etc.). The lockdown radically altered the population’s lifestyle, and several containment measures lasted for weeks beyond the end of the full lockdown period: many people saw their work temporarily suspended, others were forced to work or study from home, and everybody was subjected to mobility restrictions and were obliged to cease any non-essential activity. While these measures were essential to reducing outbreaks, they may have led to the adoption of unhealthy behaviours (e.g., more sedentary lifestyle, changes in diet) [2]. Further, these strong limitations on personal freedom could have led to increased levels of psychological distress in the population [3] caused by the fear of getting sick, the fear of experiencing financial problems, the increased tension in households, as well as the isolation from elderly family members, who are at greater risk of death. All these factors could have worsened the quality of sleep, defined as one’s satisfaction with the sleep experience, which integrates aspects of sleep initiation, sleep maintenance, sleep quantity, and refreshment upon awakening [4]. Unsatisfactory sleep can lead to short and long-term harmful psychological and psychosocial effects on health [5,6]. Thus, this observational study aimed to investigate the quality of sleep in a convenience sample of Italians under lockdown during the first epidemic peak of the COVID-19 pandemic. We also investigated the associations between the quality of sleep and sociodemographic characteristics, changes in lifestyle, and the presence of psychological distress. 2. Materials and Methods This cross-sectional study was endorsed by the Local Health Authority (LHA) of the Province of Reggio Emilia (Italy), with a population of 533,158; 66% of the population is between the ages of 18 and 70. This province was one of the most affected by the first epidemic peak of COVID-19 in Italy, with a daily incidence rate of about 8/1000 inhabitants during lockdown (10 March–18 May 2020) [7]. An online survey investigating lifestyle habits and any changes that occurred during lockdown was developed by two epidemiologists, two physiotherapists, and one occupational therapist. The survey did not collect personal data and was completely anonymous as to the source, which is why the consulted Local Ethics Committee deemed approval unnecessary. However, the survey underwent an ethics review conducted by an expert in the field; after approval, it was disseminated online to individuals living in the Province of Reggio Emilia. The survey was advertised through the websites and social media of the LHA, the major municipalities of the province, the network of the municipal pharmacies, and the local patient associations that joined the initiative. Citizens could access the survey without restrictions and in complete anonymity from 4 May 2020 until 15 June 2020. The survey (Supplementary Material File S1) explored the following areas: (a) sociodemographic data (14 questions); (b) work-related data (5 questions); (c) use of digital devices (3 questions); (d) lifestyle and general health (23 questions); (e) use of local social support services (3 questions); and (f) symptoms of psychological distress, i.e., the sense of tension, upset, worry, fear, loneliness, and/ or uncertainty (one question). Apart from two open-ended questions, the answers were multiple-choice. In some cases, more than one choice was possible. The survey took an average of 15 min to complete. The main outcome of this cross-sectional study was to describe the quality of sleep during and immediately after lockdown, investigated through the following two questions: “Have your sleep habits changed since the beginning of lockdown (amount and/or regularity of sleep)?” and “How do you rate your sleep quality now”? We also searched for associations between sleep quality categories and sociodemographic and occupational characteristics, changes in lifestyle (physical activity, eating habits, smoking, and alcohol consumption), and psychological distress. 2.1. Data Privacy and Consent for Participation During the informed consent process, participants were informed that all data would be anonymized at the source and would be used exclusively for research purposes. By completing the survey, participants voluntarily consented to participate in this study. As response would be saved only by clicking the “submit” button, that participant could stop participating in the study at any stage before submission, and their responses would not be saved. As the survey was disseminated to the local community, participants were not asked to provide name, date of birth, residency, and/or job to ensure complete anonymity. 2.2. Statistical Analysis Participants who completed the survey were categorized based on the dependent variable, i.e., their self-reported quality of sleep. They were grouped by sex, age class, education level, household composition, any financial problems, occupational status, lifestyle habits, and psychological distress. We report both the number and proportion of missing values. We looked for associations (crude odds ratio—OR—and its 95% confidence interval—95% CI) between the sociodemographic and occupational characteristics, changes in lifestyle, and the presence of psychological distress as independent variables and the quality of sleep categories. Separate models of multivariate regression analysis, all adjusted for age, sex, and education level, were built for any of the independent variables which, based on the crude OR and its 95% CI, proved to be strongly associated with quality of sleep. Missing values were not included in the analyses. Statistical analyses were performed using jamovi 1.2.27 (Jamovi Project, Sydney, Australia) [8]. 3. Results Overall, 1826 citizens in the Province of Reggio Emilia participated in the study. Most were female (76.5%), aged 18 to 64 years (88.7%), with medium-high education level (92.8%), and with no financial problems (72.3%). Most lived with one or more individuals (88.6%) and continued to work (in person or remote) during lockdown (69.8%) (Table 1). At the time of the survey, most participants reported good sleep quality (n = 1026; 56.2%), with 39.5% (n = 721) reporting poor sleep quality. However, 53.7% of participants experienced a change in their sleep habits since the beginning of lockdown, more frequently represented by a decrease in the amount and/or regularity of sleep (OR 3.68; 95% CI 2.32–5.82; p < 0.001). About one third of participants reported that their physical activity habits worsened (35.1%), while far fewer reported an improvement (5.3%). Most participants reported that their eating habits had changed: about one third reported an improvement (33.5%), i.e., all the self-reported changes went in the direction of a healthier diet (e.g., eating more fruit and vegetables, regular meals, etc.); others reported a worsening (17.6%), i.e., all changes went in the direction of a less healthy diet (e.g., more prepackaged foods, carbonated drinks), and 18.5% of participants had both changes in the direction of healthier and less healthy diet. Alcohol consumption changed for an overlapping number of participants (increased or decreased, 12.5% and 12.7%, respectively), and lower proportions of participants reported that their smoking habits had increased or decreased (7.7% and 4.1%, respectively). More than half of participants experienced feelings of uncertainty (54.5%). Moreover, a considerable proportion of individuals experienced emotions of worry (44.4%), upset (20.4), tension (19.7%), fear (16.6%) and loneliness (13.6%). Male sex seemed to be associated with better sleep quality (OR 0.47; 95% CI 0.29–0.76), as was a high education level compared to low (OR 0.44; 95% CI 0.23–0.81). Factors more strongly associated with poor sleep quality were the presence of some or many financial problems (OR 1.86; 95% CI 1.27–2.72 and OR 7.27; 95% CI 3.59–14.73, respectively), a change toward less physical activity or worse eating habits (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), and perceiving feelings of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52), loneliness (OR 3.27; 95% CI 2.23–4.79), upset (OR 3.26; 95% CI 2.29–4.64) uncertainty (OR 2.89; 95% CI 1.93–4.31), fear (OR 2.74; 95% CI 1.89–3.97), and/or worry (OR 2.50; 95% CI 1.75–3.58). A change toward mixed behaviour in eating habits was also associated with poor sleep quality. The multivariate regression analysis models confirmed the association between poor sleep quality and the presence of some or many financial problems (OR 1.74; 95% CI 1.17–2.57 and OR 6.96; 95% CI 3.32–14.55, respectively) and less physical activity or worse eating habits (OR 1.62; 95% CI 1.13–2.32 and OR 3.7; 95% CI 2.2–6.24, respectively). Again, the association between a change toward mixed behaviour in eating habits and poor sleep quality was confirmed in the adjusted model of multivariate regression analyses. The regression models also confirmed the association between poor sleep quality and the presence of a sense of tension (OR 3.51; 95% CI 2.44–5.03), loneliness (OR 3.07; 95% CI 2.07–4.53) upset (OR 3.01; 95% CI 2.10–4.32), uncertainty (OR 2.71; 95% CI 1.81–4.06) fear (OR 2.42; 95% CI 1.65–3.54) and/ or worry (OR 2.30; 95% CI 1.60–3.32) (Appendix A). 4. Discussion The results of this study highlight the association between lockdown and poor sleep quality in the Italian population. These results suggest that lockdown might impact sleep quality and that this association could be mediated by crucial determinants of health, such as physical activity and diet, and to a lesser extent, smoking and alcohol consumption, the presence of financial problems, and symptoms of psychological distress. Indeed, anxiety was widespread among the Italian population during lockdown, as were feelings of uncertainty, fear, and loneliness [9,10]. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems. Since the beginning of the pandemic, observational, mostly cross-sectional, studies have been conducted around the world to study lifestyle changes in populations subjected to restrictions. While sleep quality has been frequently investigated, results have not always been consistent. In China, Wang and colleagues found that 75% of 2289 individuals isolated at home rated their sleep as very good [11], but a smaller prospective study found that 37% of a sample of young Chinese adults reported a worsening of their sleep quality during the pandemic [12]. Studies conducted in other countries have demonstrated that lockdown could either lead to an increase in the amount of time spent in bed [13,14], with good sleep efficiency [13] or associated with sleep disorders [15,16] and disruption of one’s habitual circadian rhythm [14]. This topic has also been investigated in Europe, where 55% of Spanish adults changed their sleep pattern after the beginning of the lockdown [17], and individuals who were physically active prior to the SARS-CoV-2 spread reported major sleep problems [18]. In Italy, cross-sectional investigations have suggested that while the number of hours spent in bed might have increased during lockdown [2], many individuals reported insomnia (43%) [19] and poor sleep quality (57%) [9]. Similar percentages of sleep deterioration (48%) were also shown in the UK [20], and a longitudinal study conducted in Italy confirmed the detrimental effects of the 40-day lockdown on all the parameters of the Sleep Quality Index [21], except for sleep duration [22]. Our cohort seems to confirm that sleep quality deteriorated during lockdown, as among those individuals who experienced a change in their sleep quality, 85.8% defined their sleep as poor. This proportion of individuals accounted for 46% of the entire cohort investigated, which is strikingly similar to the proportion of those who reported a worsening of sleep quality in the above-mentioned Italian studies. Our results corroborate the findings of previous research that the worsening of sleep quality during lockdown was more pronounced among females [9,23,24]. Poor sleep quality was strongly associated with the presence of many financial problems, although this group in our cohort accounted for a very small proportion of participants (2.1%). However, poor sleep quality was not associated with the interruption of work. One possible explanation for these apparently inconsistent data could be because of the economic measures promptly introduced by the Italian Government to counter the economic effects of the forced closure of most businesses. Similarly, a large survey conducted in the UK found that poor sleep quality during lockdown was associated with perceived financial problems, but not with unemployment [23]. In this study, 35.1% of individuals reported a worsening of their level of physical activity, which proved to be a determinant of poor sleep quality in the multivariate analysis. This result was not surprising, as a moderate effect of regular exercise on overall sleep quality is well documented [25,26,27], and the association between less exercise and sleep disorders was confirmed during lockdown in a sample of German individuals [16]. In addition, 17.6% of individuals declared a change for the worse in their eating habits, which was associated with poor sleep quality. This proportion of individuals who adopted a less healthy diet is lower than the 35.8% estimated by Di Renzo and colleagues in a cross-sectional survey, which involved 3533 Italians throughout the country [2]. In this regard, it should be noted that 18.5% of our sample introduced changes in their diet that we categorized as mixed, because they were neither completely positive nor completely negative. It is plausible that some of these mixed changes, upon further investigation, could be reclassified as worse. In fact, the association between sleep quality and this type of mixed change in eating habits went in the same direction as that shown by the worsening of one’s diet. Still, regardless of the accuracy of the categorization for this predictive variable, it seems certain that several individuals’ diets worsened and that this was associated with poorer sleep. This also seems to be true outside of Italy, as data collected from more than 1000 individuals in three different continents, including Europe, which found that unhealthy diet increased by 10% during the period of social isolation, and that worse eating habits were significantly associated with a worsening in sleep quality [15]. Finally, our results confirm the association between poor sleep quality and symptoms of psychological distress. The positive relationship between anxiety and poor sleep quality has been extensively investigated and was confirmed during lockdown [9,20,26]. While the cross-sectional design of our study does not allow us to verify whether the symptoms of psychological distress that we documented were related to the restrictions imposed to curtail the spread of the SARS-CoV-2 virus, a causal relationship is plausible, as also suggested by the literature [9,10,15,16,20,28]. The convenience sample investigated was recruited in the Province of Reggio Emilia, one of the most affected Italian provinces during the early phase of the pandemic. Considering that, at the time of the survey, little or nothing was known about the disease and its prognosis, it is plausible that feelings of fear and uncertainty were more widespread in the populations living in areas with a high prevalence of infection [9,29]. Added to this were the concerns arising from the forced temporary closure of many business and industries in one of the most productive areas of Italy and of Europe. The COVID-19 pandemic has called into question the stability of the Italian National Health Service, also triggering uncertainties regarding the continuity of care for thousands of individuals, often elderly and with comorbidities, in one of the longest-lived countries in the world. Therefore, the association between poor sleep quality and feelings of fear and uncertainty was expected. Less obvious was the relationship between poor quality sleep and feelings of loneliness as, based on the univariate analysis conducted, living alone was not a predictor of poor sleep quality. Thus, loneliness was perceived regardless of the presence of other household members; the reasons underlying this feeling must be sought in other causalities. We have no explanation for this, but it is possible that forced living with others in close quarters for an extended period may have worn down the quality of relationships between individuals, or loneliness may have been due to the forced separation from important, vulnerable family members. Moreover, the sense of loneliness could also have derived from the need to limit interpersonal contact to a minimum, a measure that, while necessary to reduce the contagion, is in stark contrast with Italian culture. Limitations and Strengths The results of this study should be interpreted with caution as they derive from a cross-sectional design, which makes causal inferencing challenging. Moreover, the survey sampling was based on an online invitation, which does not allow for generalization because the population that does not use the Internet was not explored. Indeed, a recruitment bias emerged in our sample, as females and working-age individuals with a high education level are overrepresented compared to the general Italian population. While the overrepresentation of females is a feature common to other similar studies [2,9,16,20,28,30], it is likely that the biases observed in age and education reflect a high level of adhesion of participants who are also healthcare professionals or administrative staff of the LHA or of the major municipalities of the Province of Reggio Emilia, which disseminated the survey through their social media and websites. Moreover, the outcome of interest and data related to predictive variables were collected through self-reporting rather than through a valid survey or clinical assessment. This was because, as we wanted to capture the changes that occurred during lockdown through a cross-sectional design, we chose specific questions to comply with this purpose. Finally, we decided to observe the association between each change occurring during the lockdown, adjusting only for those variables that certainly could not change during the study period and cannot be intermediate effectors of the other putative exposure. However, this approach does not allow us to rule out that some of the observed associations were not independent and could have been due to confounding or could have been mediated by other putative exposures. Despite these limitations, this study had a relatively high acceptance in our community. The sampling strategy allowed us to collect data from quite a large sample, which in fact numerically mirrors that investigated by other similar study designs conducted to explore the same theme [9,15,28,30]. Further, this was the only sampling method feasible during lockdown. 5. Conclusions The quality of sleep, one of the determinants of public health, was adversely affected by the lockdown. Our study points out that nearly all individuals who experienced a change in their sleep reported poor quality of the same. This result is plausible, considering the fast disruption of routine caused by the pandemic. In fact, individuals’ well-being may have been seriously affected when both personal and public safety are no longer predictable, regardless of their resilience and their capacity for adaptation in daily life. We highlighted the effect that sociodemographic and occupational characteristics, changes in lifestyle, and psychological distress have on sleep quality. While this study design does not allow us to determine a causal relationship among potential determinants and poor sleep quality, it nevertheless highlights the presence of categories of people who suffered the most: socially fragile individuals, those reporting negative changes in physical activity and diet, and individuals with psychological distress. These categories require the attention of policy makers, who should plan strategies to promote healthy lifestyles and strategies to maintain serenity during this difficult period. Considering that the SARS-CoV-2 infections rate has been increasing since October 2020 and that several restrictions have been reintroduced to contain the spread of the virus, further investigations on this topic should be implemented. For example, studies exploring whether sleep has been affected during this second epidemic peak as well or whether individuals have adapted to the situation and have found strategies to deal with the limitations and uncertainties related to the SARS-CoV-2 spread would be of interested.
sec	1. Introduction The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed the world population under enormous stress. Large geographical areas and the resident populations have been forced to undergo periods of lockdown to halt the spread of the virus and to limit the impact on healthcare systems. In March 2020, the Italian Government imposed two months of emergency lockdown, with containment measures unheard of in the national territory, sometimes characterized by mandatory quarantine [1]. These measures included the closing of businesses, schools and universities, and the banning of all recreational outdoor activities; the only exceptions were the provision of essential services for health and basic needs (i.e., food, municipal services, etc.). The lockdown radically altered the population’s lifestyle, and several containment measures lasted for weeks beyond the end of the full lockdown period: many people saw their work temporarily suspended, others were forced to work or study from home, and everybody was subjected to mobility restrictions and were obliged to cease any non-essential activity. While these measures were essential to reducing outbreaks, they may have led to the adoption of unhealthy behaviours (e.g., more sedentary lifestyle, changes in diet) [2]. Further, these strong limitations on personal freedom could have led to increased levels of psychological distress in the population [3] caused by the fear of getting sick, the fear of experiencing financial problems, the increased tension in households, as well as the isolation from elderly family members, who are at greater risk of death. All these factors could have worsened the quality of sleep, defined as one’s satisfaction with the sleep experience, which integrates aspects of sleep initiation, sleep maintenance, sleep quantity, and refreshment upon awakening [4]. Unsatisfactory sleep can lead to short and long-term harmful psychological and psychosocial effects on health [5,6]. Thus, this observational study aimed to investigate the quality of sleep in a convenience sample of Italians under lockdown during the first epidemic peak of the COVID-19 pandemic. We also investigated the associations between the quality of sleep and sociodemographic characteristics, changes in lifestyle, and the presence of psychological distress.
title	1. Introduction
p	The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed the world population under enormous stress. Large geographical areas and the resident populations have been forced to undergo periods of lockdown to halt the spread of the virus and to limit the impact on healthcare systems. In March 2020, the Italian Government imposed two months of emergency lockdown, with containment measures unheard of in the national territory, sometimes characterized by mandatory quarantine [1]. These measures included the closing of businesses, schools and universities, and the banning of all recreational outdoor activities; the only exceptions were the provision of essential services for health and basic needs (i.e., food, municipal services, etc.). The lockdown radically altered the population’s lifestyle, and several containment measures lasted for weeks beyond the end of the full lockdown period: many people saw their work temporarily suspended, others were forced to work or study from home, and everybody was subjected to mobility restrictions and were obliged to cease any non-essential activity. While these measures were essential to reducing outbreaks, they may have led to the adoption of unhealthy behaviours (e.g., more sedentary lifestyle, changes in diet) [2]. Further, these strong limitations on personal freedom could have led to increased levels of psychological distress in the population [3] caused by the fear of getting sick, the fear of experiencing financial problems, the increased tension in households, as well as the isolation from elderly family members, who are at greater risk of death.
p	All these factors could have worsened the quality of sleep, defined as one’s satisfaction with the sleep experience, which integrates aspects of sleep initiation, sleep maintenance, sleep quantity, and refreshment upon awakening [4]. Unsatisfactory sleep can lead to short and long-term harmful psychological and psychosocial effects on health [5,6]. Thus, this observational study aimed to investigate the quality of sleep in a convenience sample of Italians under lockdown during the first epidemic peak of the COVID-19 pandemic. We also investigated the associations between the quality of sleep and sociodemographic characteristics, changes in lifestyle, and the presence of psychological distress.
sec	2. Materials and Methods This cross-sectional study was endorsed by the Local Health Authority (LHA) of the Province of Reggio Emilia (Italy), with a population of 533,158; 66% of the population is between the ages of 18 and 70. This province was one of the most affected by the first epidemic peak of COVID-19 in Italy, with a daily incidence rate of about 8/1000 inhabitants during lockdown (10 March–18 May 2020) [7]. An online survey investigating lifestyle habits and any changes that occurred during lockdown was developed by two epidemiologists, two physiotherapists, and one occupational therapist. The survey did not collect personal data and was completely anonymous as to the source, which is why the consulted Local Ethics Committee deemed approval unnecessary. However, the survey underwent an ethics review conducted by an expert in the field; after approval, it was disseminated online to individuals living in the Province of Reggio Emilia. The survey was advertised through the websites and social media of the LHA, the major municipalities of the province, the network of the municipal pharmacies, and the local patient associations that joined the initiative. Citizens could access the survey without restrictions and in complete anonymity from 4 May 2020 until 15 June 2020. The survey (Supplementary Material File S1) explored the following areas: (a) sociodemographic data (14 questions); (b) work-related data (5 questions); (c) use of digital devices (3 questions); (d) lifestyle and general health (23 questions); (e) use of local social support services (3 questions); and (f) symptoms of psychological distress, i.e., the sense of tension, upset, worry, fear, loneliness, and/ or uncertainty (one question). Apart from two open-ended questions, the answers were multiple-choice. In some cases, more than one choice was possible. The survey took an average of 15 min to complete. The main outcome of this cross-sectional study was to describe the quality of sleep during and immediately after lockdown, investigated through the following two questions: “Have your sleep habits changed since the beginning of lockdown (amount and/or regularity of sleep)?” and “How do you rate your sleep quality now”? We also searched for associations between sleep quality categories and sociodemographic and occupational characteristics, changes in lifestyle (physical activity, eating habits, smoking, and alcohol consumption), and psychological distress. 2.1. Data Privacy and Consent for Participation During the informed consent process, participants were informed that all data would be anonymized at the source and would be used exclusively for research purposes. By completing the survey, participants voluntarily consented to participate in this study. As response would be saved only by clicking the “submit” button, that participant could stop participating in the study at any stage before submission, and their responses would not be saved. As the survey was disseminated to the local community, participants were not asked to provide name, date of birth, residency, and/or job to ensure complete anonymity. 2.2. Statistical Analysis Participants who completed the survey were categorized based on the dependent variable, i.e., their self-reported quality of sleep. They were grouped by sex, age class, education level, household composition, any financial problems, occupational status, lifestyle habits, and psychological distress. We report both the number and proportion of missing values. We looked for associations (crude odds ratio—OR—and its 95% confidence interval—95% CI) between the sociodemographic and occupational characteristics, changes in lifestyle, and the presence of psychological distress as independent variables and the quality of sleep categories. Separate models of multivariate regression analysis, all adjusted for age, sex, and education level, were built for any of the independent variables which, based on the crude OR and its 95% CI, proved to be strongly associated with quality of sleep. Missing values were not included in the analyses. Statistical analyses were performed using jamovi 1.2.27 (Jamovi Project, Sydney, Australia) [8].
title	2. Materials and Methods
p	This cross-sectional study was endorsed by the Local Health Authority (LHA) of the Province of Reggio Emilia (Italy), with a population of 533,158; 66% of the population is between the ages of 18 and 70. This province was one of the most affected by the first epidemic peak of COVID-19 in Italy, with a daily incidence rate of about 8/1000 inhabitants during lockdown (10 March–18 May 2020) [7].
p	An online survey investigating lifestyle habits and any changes that occurred during lockdown was developed by two epidemiologists, two physiotherapists, and one occupational therapist. The survey did not collect personal data and was completely anonymous as to the source, which is why the consulted Local Ethics Committee deemed approval unnecessary. However, the survey underwent an ethics review conducted by an expert in the field; after approval, it was disseminated online to individuals living in the Province of Reggio Emilia. The survey was advertised through the websites and social media of the LHA, the major municipalities of the province, the network of the municipal pharmacies, and the local patient associations that joined the initiative. Citizens could access the survey without restrictions and in complete anonymity from 4 May 2020 until 15 June 2020.
p	The survey (Supplementary Material File S1) explored the following areas: (a) sociodemographic data (14 questions); (b) work-related data (5 questions); (c) use of digital devices (3 questions); (d) lifestyle and general health (23 questions); (e) use of local social support services (3 questions); and (f) symptoms of psychological distress, i.e., the sense of tension, upset, worry, fear, loneliness, and/ or uncertainty (one question).
p	Apart from two open-ended questions, the answers were multiple-choice. In some cases, more than one choice was possible. The survey took an average of 15 min to complete.
p	The main outcome of this cross-sectional study was to describe the quality of sleep during and immediately after lockdown, investigated through the following two questions: “Have your sleep habits changed since the beginning of lockdown (amount and/or regularity of sleep)?” and “How do you rate your sleep quality now”?
p	We also searched for associations between sleep quality categories and sociodemographic and occupational characteristics, changes in lifestyle (physical activity, eating habits, smoking, and alcohol consumption), and psychological distress.
sec	2.1. Data Privacy and Consent for Participation During the informed consent process, participants were informed that all data would be anonymized at the source and would be used exclusively for research purposes. By completing the survey, participants voluntarily consented to participate in this study. As response would be saved only by clicking the “submit” button, that participant could stop participating in the study at any stage before submission, and their responses would not be saved. As the survey was disseminated to the local community, participants were not asked to provide name, date of birth, residency, and/or job to ensure complete anonymity.
title	2.1. Data Privacy and Consent for Participation
p	During the informed consent process, participants were informed that all data would be anonymized at the source and would be used exclusively for research purposes. By completing the survey, participants voluntarily consented to participate in this study. As response would be saved only by clicking the “submit” button, that participant could stop participating in the study at any stage before submission, and their responses would not be saved. As the survey was disseminated to the local community, participants were not asked to provide name, date of birth, residency, and/or job to ensure complete anonymity.
sec	2.2. Statistical Analysis Participants who completed the survey were categorized based on the dependent variable, i.e., their self-reported quality of sleep. They were grouped by sex, age class, education level, household composition, any financial problems, occupational status, lifestyle habits, and psychological distress. We report both the number and proportion of missing values. We looked for associations (crude odds ratio—OR—and its 95% confidence interval—95% CI) between the sociodemographic and occupational characteristics, changes in lifestyle, and the presence of psychological distress as independent variables and the quality of sleep categories. Separate models of multivariate regression analysis, all adjusted for age, sex, and education level, were built for any of the independent variables which, based on the crude OR and its 95% CI, proved to be strongly associated with quality of sleep. Missing values were not included in the analyses. Statistical analyses were performed using jamovi 1.2.27 (Jamovi Project, Sydney, Australia) [8].
title	2.2. Statistical Analysis
p	Participants who completed the survey were categorized based on the dependent variable, i.e., their self-reported quality of sleep. They were grouped by sex, age class, education level, household composition, any financial problems, occupational status, lifestyle habits, and psychological distress. We report both the number and proportion of missing values. We looked for associations (crude odds ratio—OR—and its 95% confidence interval—95% CI) between the sociodemographic and occupational characteristics, changes in lifestyle, and the presence of psychological distress as independent variables and the quality of sleep categories. Separate models of multivariate regression analysis, all adjusted for age, sex, and education level, were built for any of the independent variables which, based on the crude OR and its 95% CI, proved to be strongly associated with quality of sleep. Missing values were not included in the analyses. Statistical analyses were performed using jamovi 1.2.27 (Jamovi Project, Sydney, Australia) [8].
sec	3. Results Overall, 1826 citizens in the Province of Reggio Emilia participated in the study. Most were female (76.5%), aged 18 to 64 years (88.7%), with medium-high education level (92.8%), and with no financial problems (72.3%). Most lived with one or more individuals (88.6%) and continued to work (in person or remote) during lockdown (69.8%) (Table 1). At the time of the survey, most participants reported good sleep quality (n = 1026; 56.2%), with 39.5% (n = 721) reporting poor sleep quality. However, 53.7% of participants experienced a change in their sleep habits since the beginning of lockdown, more frequently represented by a decrease in the amount and/or regularity of sleep (OR 3.68; 95% CI 2.32–5.82; p < 0.001). About one third of participants reported that their physical activity habits worsened (35.1%), while far fewer reported an improvement (5.3%). Most participants reported that their eating habits had changed: about one third reported an improvement (33.5%), i.e., all the self-reported changes went in the direction of a healthier diet (e.g., eating more fruit and vegetables, regular meals, etc.); others reported a worsening (17.6%), i.e., all changes went in the direction of a less healthy diet (e.g., more prepackaged foods, carbonated drinks), and 18.5% of participants had both changes in the direction of healthier and less healthy diet. Alcohol consumption changed for an overlapping number of participants (increased or decreased, 12.5% and 12.7%, respectively), and lower proportions of participants reported that their smoking habits had increased or decreased (7.7% and 4.1%, respectively). More than half of participants experienced feelings of uncertainty (54.5%). Moreover, a considerable proportion of individuals experienced emotions of worry (44.4%), upset (20.4), tension (19.7%), fear (16.6%) and loneliness (13.6%). Male sex seemed to be associated with better sleep quality (OR 0.47; 95% CI 0.29–0.76), as was a high education level compared to low (OR 0.44; 95% CI 0.23–0.81). Factors more strongly associated with poor sleep quality were the presence of some or many financial problems (OR 1.86; 95% CI 1.27–2.72 and OR 7.27; 95% CI 3.59–14.73, respectively), a change toward less physical activity or worse eating habits (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), and perceiving feelings of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52), loneliness (OR 3.27; 95% CI 2.23–4.79), upset (OR 3.26; 95% CI 2.29–4.64) uncertainty (OR 2.89; 95% CI 1.93–4.31), fear (OR 2.74; 95% CI 1.89–3.97), and/or worry (OR 2.50; 95% CI 1.75–3.58). A change toward mixed behaviour in eating habits was also associated with poor sleep quality. The multivariate regression analysis models confirmed the association between poor sleep quality and the presence of some or many financial problems (OR 1.74; 95% CI 1.17–2.57 and OR 6.96; 95% CI 3.32–14.55, respectively) and less physical activity or worse eating habits (OR 1.62; 95% CI 1.13–2.32 and OR 3.7; 95% CI 2.2–6.24, respectively). Again, the association between a change toward mixed behaviour in eating habits and poor sleep quality was confirmed in the adjusted model of multivariate regression analyses. The regression models also confirmed the association between poor sleep quality and the presence of a sense of tension (OR 3.51; 95% CI 2.44–5.03), loneliness (OR 3.07; 95% CI 2.07–4.53) upset (OR 3.01; 95% CI 2.10–4.32), uncertainty (OR 2.71; 95% CI 1.81–4.06) fear (OR 2.42; 95% CI 1.65–3.54) and/ or worry (OR 2.30; 95% CI 1.60–3.32) (Appendix A).
title	3. Results
p	Overall, 1826 citizens in the Province of Reggio Emilia participated in the study. Most were female (76.5%), aged 18 to 64 years (88.7%), with medium-high education level (92.8%), and with no financial problems (72.3%). Most lived with one or more individuals (88.6%) and continued to work (in person or remote) during lockdown (69.8%) (Table 1).
p	At the time of the survey, most participants reported good sleep quality (n = 1026; 56.2%), with 39.5% (n = 721) reporting poor sleep quality. However, 53.7% of participants experienced a change in their sleep habits since the beginning of lockdown, more frequently represented by a decrease in the amount and/or regularity of sleep (OR 3.68; 95% CI 2.32–5.82; p < 0.001).
p	About one third of participants reported that their physical activity habits worsened (35.1%), while far fewer reported an improvement (5.3%). Most participants reported that their eating habits had changed: about one third reported an improvement (33.5%), i.e., all the self-reported changes went in the direction of a healthier diet (e.g., eating more fruit and vegetables, regular meals, etc.); others reported a worsening (17.6%), i.e., all changes went in the direction of a less healthy diet (e.g., more prepackaged foods, carbonated drinks), and 18.5% of participants had both changes in the direction of healthier and less healthy diet. Alcohol consumption changed for an overlapping number of participants (increased or decreased, 12.5% and 12.7%, respectively), and lower proportions of participants reported that their smoking habits had increased or decreased (7.7% and 4.1%, respectively).
p	More than half of participants experienced feelings of uncertainty (54.5%). Moreover, a considerable proportion of individuals experienced emotions of worry (44.4%), upset (20.4), tension (19.7%), fear (16.6%) and loneliness (13.6%).
p	Male sex seemed to be associated with better sleep quality (OR 0.47; 95% CI 0.29–0.76), as was a high education level compared to low (OR 0.44; 95% CI 0.23–0.81). Factors more strongly associated with poor sleep quality were the presence of some or many financial problems (OR 1.86; 95% CI 1.27–2.72 and OR 7.27; 95% CI 3.59–14.73, respectively), a change toward less physical activity or worse eating habits (OR 1.68; 95% CI 1.18–2.40 and OR 4.19; 95% CI 2.51–6.96, respectively), and perceiving feelings of psychological distress, such as tension (OR 3.88; 95% CI 2.74–5.52), loneliness (OR 3.27; 95% CI 2.23–4.79), upset (OR 3.26; 95% CI 2.29–4.64) uncertainty (OR 2.89; 95% CI 1.93–4.31), fear (OR 2.74; 95% CI 1.89–3.97), and/or worry (OR 2.50; 95% CI 1.75–3.58). A change toward mixed behaviour in eating habits was also associated with poor sleep quality.
p	The multivariate regression analysis models confirmed the association between poor sleep quality and the presence of some or many financial problems (OR 1.74; 95% CI 1.17–2.57 and OR 6.96; 95% CI 3.32–14.55, respectively) and less physical activity or worse eating habits (OR 1.62; 95% CI 1.13–2.32 and OR 3.7; 95% CI 2.2–6.24, respectively). Again, the association between a change toward mixed behaviour in eating habits and poor sleep quality was confirmed in the adjusted model of multivariate regression analyses. The regression models also confirmed the association between poor sleep quality and the presence of a sense of tension (OR 3.51; 95% CI 2.44–5.03), loneliness (OR 3.07; 95% CI 2.07–4.53) upset (OR 3.01; 95% CI 2.10–4.32), uncertainty (OR 2.71; 95% CI 1.81–4.06) fear (OR 2.42; 95% CI 1.65–3.54) and/ or worry (OR 2.30; 95% CI 1.60–3.32) (Appendix A).
sec	4. Discussion The results of this study highlight the association between lockdown and poor sleep quality in the Italian population. These results suggest that lockdown might impact sleep quality and that this association could be mediated by crucial determinants of health, such as physical activity and diet, and to a lesser extent, smoking and alcohol consumption, the presence of financial problems, and symptoms of psychological distress. Indeed, anxiety was widespread among the Italian population during lockdown, as were feelings of uncertainty, fear, and loneliness [9,10]. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems. Since the beginning of the pandemic, observational, mostly cross-sectional, studies have been conducted around the world to study lifestyle changes in populations subjected to restrictions. While sleep quality has been frequently investigated, results have not always been consistent. In China, Wang and colleagues found that 75% of 2289 individuals isolated at home rated their sleep as very good [11], but a smaller prospective study found that 37% of a sample of young Chinese adults reported a worsening of their sleep quality during the pandemic [12]. Studies conducted in other countries have demonstrated that lockdown could either lead to an increase in the amount of time spent in bed [13,14], with good sleep efficiency [13] or associated with sleep disorders [15,16] and disruption of one’s habitual circadian rhythm [14]. This topic has also been investigated in Europe, where 55% of Spanish adults changed their sleep pattern after the beginning of the lockdown [17], and individuals who were physically active prior to the SARS-CoV-2 spread reported major sleep problems [18]. In Italy, cross-sectional investigations have suggested that while the number of hours spent in bed might have increased during lockdown [2], many individuals reported insomnia (43%) [19] and poor sleep quality (57%) [9]. Similar percentages of sleep deterioration (48%) were also shown in the UK [20], and a longitudinal study conducted in Italy confirmed the detrimental effects of the 40-day lockdown on all the parameters of the Sleep Quality Index [21], except for sleep duration [22]. Our cohort seems to confirm that sleep quality deteriorated during lockdown, as among those individuals who experienced a change in their sleep quality, 85.8% defined their sleep as poor. This proportion of individuals accounted for 46% of the entire cohort investigated, which is strikingly similar to the proportion of those who reported a worsening of sleep quality in the above-mentioned Italian studies. Our results corroborate the findings of previous research that the worsening of sleep quality during lockdown was more pronounced among females [9,23,24]. Poor sleep quality was strongly associated with the presence of many financial problems, although this group in our cohort accounted for a very small proportion of participants (2.1%). However, poor sleep quality was not associated with the interruption of work. One possible explanation for these apparently inconsistent data could be because of the economic measures promptly introduced by the Italian Government to counter the economic effects of the forced closure of most businesses. Similarly, a large survey conducted in the UK found that poor sleep quality during lockdown was associated with perceived financial problems, but not with unemployment [23]. In this study, 35.1% of individuals reported a worsening of their level of physical activity, which proved to be a determinant of poor sleep quality in the multivariate analysis. This result was not surprising, as a moderate effect of regular exercise on overall sleep quality is well documented [25,26,27], and the association between less exercise and sleep disorders was confirmed during lockdown in a sample of German individuals [16]. In addition, 17.6% of individuals declared a change for the worse in their eating habits, which was associated with poor sleep quality. This proportion of individuals who adopted a less healthy diet is lower than the 35.8% estimated by Di Renzo and colleagues in a cross-sectional survey, which involved 3533 Italians throughout the country [2]. In this regard, it should be noted that 18.5% of our sample introduced changes in their diet that we categorized as mixed, because they were neither completely positive nor completely negative. It is plausible that some of these mixed changes, upon further investigation, could be reclassified as worse. In fact, the association between sleep quality and this type of mixed change in eating habits went in the same direction as that shown by the worsening of one’s diet. Still, regardless of the accuracy of the categorization for this predictive variable, it seems certain that several individuals’ diets worsened and that this was associated with poorer sleep. This also seems to be true outside of Italy, as data collected from more than 1000 individuals in three different continents, including Europe, which found that unhealthy diet increased by 10% during the period of social isolation, and that worse eating habits were significantly associated with a worsening in sleep quality [15]. Finally, our results confirm the association between poor sleep quality and symptoms of psychological distress. The positive relationship between anxiety and poor sleep quality has been extensively investigated and was confirmed during lockdown [9,20,26]. While the cross-sectional design of our study does not allow us to verify whether the symptoms of psychological distress that we documented were related to the restrictions imposed to curtail the spread of the SARS-CoV-2 virus, a causal relationship is plausible, as also suggested by the literature [9,10,15,16,20,28]. The convenience sample investigated was recruited in the Province of Reggio Emilia, one of the most affected Italian provinces during the early phase of the pandemic. Considering that, at the time of the survey, little or nothing was known about the disease and its prognosis, it is plausible that feelings of fear and uncertainty were more widespread in the populations living in areas with a high prevalence of infection [9,29]. Added to this were the concerns arising from the forced temporary closure of many business and industries in one of the most productive areas of Italy and of Europe. The COVID-19 pandemic has called into question the stability of the Italian National Health Service, also triggering uncertainties regarding the continuity of care for thousands of individuals, often elderly and with comorbidities, in one of the longest-lived countries in the world. Therefore, the association between poor sleep quality and feelings of fear and uncertainty was expected. Less obvious was the relationship between poor quality sleep and feelings of loneliness as, based on the univariate analysis conducted, living alone was not a predictor of poor sleep quality. Thus, loneliness was perceived regardless of the presence of other household members; the reasons underlying this feeling must be sought in other causalities. We have no explanation for this, but it is possible that forced living with others in close quarters for an extended period may have worn down the quality of relationships between individuals, or loneliness may have been due to the forced separation from important, vulnerable family members. Moreover, the sense of loneliness could also have derived from the need to limit interpersonal contact to a minimum, a measure that, while necessary to reduce the contagion, is in stark contrast with Italian culture. Limitations and Strengths The results of this study should be interpreted with caution as they derive from a cross-sectional design, which makes causal inferencing challenging. Moreover, the survey sampling was based on an online invitation, which does not allow for generalization because the population that does not use the Internet was not explored. Indeed, a recruitment bias emerged in our sample, as females and working-age individuals with a high education level are overrepresented compared to the general Italian population. While the overrepresentation of females is a feature common to other similar studies [2,9,16,20,28,30], it is likely that the biases observed in age and education reflect a high level of adhesion of participants who are also healthcare professionals or administrative staff of the LHA or of the major municipalities of the Province of Reggio Emilia, which disseminated the survey through their social media and websites. Moreover, the outcome of interest and data related to predictive variables were collected through self-reporting rather than through a valid survey or clinical assessment. This was because, as we wanted to capture the changes that occurred during lockdown through a cross-sectional design, we chose specific questions to comply with this purpose. Finally, we decided to observe the association between each change occurring during the lockdown, adjusting only for those variables that certainly could not change during the study period and cannot be intermediate effectors of the other putative exposure. However, this approach does not allow us to rule out that some of the observed associations were not independent and could have been due to confounding or could have been mediated by other putative exposures. Despite these limitations, this study had a relatively high acceptance in our community. The sampling strategy allowed us to collect data from quite a large sample, which in fact numerically mirrors that investigated by other similar study designs conducted to explore the same theme [9,15,28,30]. Further, this was the only sampling method feasible during lockdown.
title	4. Discussion
p	The results of this study highlight the association between lockdown and poor sleep quality in the Italian population. These results suggest that lockdown might impact sleep quality and that this association could be mediated by crucial determinants of health, such as physical activity and diet, and to a lesser extent, smoking and alcohol consumption, the presence of financial problems, and symptoms of psychological distress. Indeed, anxiety was widespread among the Italian population during lockdown, as were feelings of uncertainty, fear, and loneliness [9,10]. This impact on sleep quality was seen especially among females, those with low education level, and those who experienced financial problems.
p	Since the beginning of the pandemic, observational, mostly cross-sectional, studies have been conducted around the world to study lifestyle changes in populations subjected to restrictions. While sleep quality has been frequently investigated, results have not always been consistent. In China, Wang and colleagues found that 75% of 2289 individuals isolated at home rated their sleep as very good [11], but a smaller prospective study found that 37% of a sample of young Chinese adults reported a worsening of their sleep quality during the pandemic [12]. Studies conducted in other countries have demonstrated that lockdown could either lead to an increase in the amount of time spent in bed [13,14], with good sleep efficiency [13] or associated with sleep disorders [15,16] and disruption of one’s habitual circadian rhythm [14]. This topic has also been investigated in Europe, where 55% of Spanish adults changed their sleep pattern after the beginning of the lockdown [17], and individuals who were physically active prior to the SARS-CoV-2 spread reported major sleep problems [18]. In Italy, cross-sectional investigations have suggested that while the number of hours spent in bed might have increased during lockdown [2], many individuals reported insomnia (43%) [19] and poor sleep quality (57%) [9]. Similar percentages of sleep deterioration (48%) were also shown in the UK [20], and a longitudinal study conducted in Italy confirmed the detrimental effects of the 40-day lockdown on all the parameters of the Sleep Quality Index [21], except for sleep duration [22]. Our cohort seems to confirm that sleep quality deteriorated during lockdown, as among those individuals who experienced a change in their sleep quality, 85.8% defined their sleep as poor. This proportion of individuals accounted for 46% of the entire cohort investigated, which is strikingly similar to the proportion of those who reported a worsening of sleep quality in the above-mentioned Italian studies.
p	Our results corroborate the findings of previous research that the worsening of sleep quality during lockdown was more pronounced among females [9,23,24]. Poor sleep quality was strongly associated with the presence of many financial problems, although this group in our cohort accounted for a very small proportion of participants (2.1%). However, poor sleep quality was not associated with the interruption of work. One possible explanation for these apparently inconsistent data could be because of the economic measures promptly introduced by the Italian Government to counter the economic effects of the forced closure of most businesses. Similarly, a large survey conducted in the UK found that poor sleep quality during lockdown was associated with perceived financial problems, but not with unemployment [23].
p	In this study, 35.1% of individuals reported a worsening of their level of physical activity, which proved to be a determinant of poor sleep quality in the multivariate analysis. This result was not surprising, as a moderate effect of regular exercise on overall sleep quality is well documented [25,26,27], and the association between less exercise and sleep disorders was confirmed during lockdown in a sample of German individuals [16].
p	In addition, 17.6% of individuals declared a change for the worse in their eating habits, which was associated with poor sleep quality. This proportion of individuals who adopted a less healthy diet is lower than the 35.8% estimated by Di Renzo and colleagues in a cross-sectional survey, which involved 3533 Italians throughout the country [2]. In this regard, it should be noted that 18.5% of our sample introduced changes in their diet that we categorized as mixed, because they were neither completely positive nor completely negative. It is plausible that some of these mixed changes, upon further investigation, could be reclassified as worse. In fact, the association between sleep quality and this type of mixed change in eating habits went in the same direction as that shown by the worsening of one’s diet. Still, regardless of the accuracy of the categorization for this predictive variable, it seems certain that several individuals’ diets worsened and that this was associated with poorer sleep. This also seems to be true outside of Italy, as data collected from more than 1000 individuals in three different continents, including Europe, which found that unhealthy diet increased by 10% during the period of social isolation, and that worse eating habits were significantly associated with a worsening in sleep quality [15].
p	Finally, our results confirm the association between poor sleep quality and symptoms of psychological distress. The positive relationship between anxiety and poor sleep quality has been extensively investigated and was confirmed during lockdown [9,20,26]. While the cross-sectional design of our study does not allow us to verify whether the symptoms of psychological distress that we documented were related to the restrictions imposed to curtail the spread of the SARS-CoV-2 virus, a causal relationship is plausible, as also suggested by the literature [9,10,15,16,20,28]. The convenience sample investigated was recruited in the Province of Reggio Emilia, one of the most affected Italian provinces during the early phase of the pandemic. Considering that, at the time of the survey, little or nothing was known about the disease and its prognosis, it is plausible that feelings of fear and uncertainty were more widespread in the populations living in areas with a high prevalence of infection [9,29]. Added to this were the concerns arising from the forced temporary closure of many business and industries in one of the most productive areas of Italy and of Europe. The COVID-19 pandemic has called into question the stability of the Italian National Health Service, also triggering uncertainties regarding the continuity of care for thousands of individuals, often elderly and with comorbidities, in one of the longest-lived countries in the world. Therefore, the association between poor sleep quality and feelings of fear and uncertainty was expected.
p	Less obvious was the relationship between poor quality sleep and feelings of loneliness as, based on the univariate analysis conducted, living alone was not a predictor of poor sleep quality. Thus, loneliness was perceived regardless of the presence of other household members; the reasons underlying this feeling must be sought in other causalities. We have no explanation for this, but it is possible that forced living with others in close quarters for an extended period may have worn down the quality of relationships between individuals, or loneliness may have been due to the forced separation from important, vulnerable family members. Moreover, the sense of loneliness could also have derived from the need to limit interpersonal contact to a minimum, a measure that, while necessary to reduce the contagion, is in stark contrast with Italian culture.
sec	Limitations and Strengths The results of this study should be interpreted with caution as they derive from a cross-sectional design, which makes causal inferencing challenging. Moreover, the survey sampling was based on an online invitation, which does not allow for generalization because the population that does not use the Internet was not explored. Indeed, a recruitment bias emerged in our sample, as females and working-age individuals with a high education level are overrepresented compared to the general Italian population. While the overrepresentation of females is a feature common to other similar studies [2,9,16,20,28,30], it is likely that the biases observed in age and education reflect a high level of adhesion of participants who are also healthcare professionals or administrative staff of the LHA or of the major municipalities of the Province of Reggio Emilia, which disseminated the survey through their social media and websites. Moreover, the outcome of interest and data related to predictive variables were collected through self-reporting rather than through a valid survey or clinical assessment. This was because, as we wanted to capture the changes that occurred during lockdown through a cross-sectional design, we chose specific questions to comply with this purpose. Finally, we decided to observe the association between each change occurring during the lockdown, adjusting only for those variables that certainly could not change during the study period and cannot be intermediate effectors of the other putative exposure. However, this approach does not allow us to rule out that some of the observed associations were not independent and could have been due to confounding or could have been mediated by other putative exposures. Despite these limitations, this study had a relatively high acceptance in our community. The sampling strategy allowed us to collect data from quite a large sample, which in fact numerically mirrors that investigated by other similar study designs conducted to explore the same theme [9,15,28,30]. Further, this was the only sampling method feasible during lockdown.
title	Limitations and Strengths
p	The results of this study should be interpreted with caution as they derive from a cross-sectional design, which makes causal inferencing challenging. Moreover, the survey sampling was based on an online invitation, which does not allow for generalization because the population that does not use the Internet was not explored.
p	Indeed, a recruitment bias emerged in our sample, as females and working-age individuals with a high education level are overrepresented compared to the general Italian population. While the overrepresentation of females is a feature common to other similar studies [2,9,16,20,28,30], it is likely that the biases observed in age and education reflect a high level of adhesion of participants who are also healthcare professionals or administrative staff of the LHA or of the major municipalities of the Province of Reggio Emilia, which disseminated the survey through their social media and websites.
p	Moreover, the outcome of interest and data related to predictive variables were collected through self-reporting rather than through a valid survey or clinical assessment. This was because, as we wanted to capture the changes that occurred during lockdown through a cross-sectional design, we chose specific questions to comply with this purpose.
p	Finally, we decided to observe the association between each change occurring during the lockdown, adjusting only for those variables that certainly could not change during the study period and cannot be intermediate effectors of the other putative exposure. However, this approach does not allow us to rule out that some of the observed associations were not independent and could have been due to confounding or could have been mediated by other putative exposures.
p	Despite these limitations, this study had a relatively high acceptance in our community. The sampling strategy allowed us to collect data from quite a large sample, which in fact numerically mirrors that investigated by other similar study designs conducted to explore the same theme [9,15,28,30]. Further, this was the only sampling method feasible during lockdown.
sec	5. Conclusions The quality of sleep, one of the determinants of public health, was adversely affected by the lockdown. Our study points out that nearly all individuals who experienced a change in their sleep reported poor quality of the same. This result is plausible, considering the fast disruption of routine caused by the pandemic. In fact, individuals’ well-being may have been seriously affected when both personal and public safety are no longer predictable, regardless of their resilience and their capacity for adaptation in daily life. We highlighted the effect that sociodemographic and occupational characteristics, changes in lifestyle, and psychological distress have on sleep quality. While this study design does not allow us to determine a causal relationship among potential determinants and poor sleep quality, it nevertheless highlights the presence of categories of people who suffered the most: socially fragile individuals, those reporting negative changes in physical activity and diet, and individuals with psychological distress. These categories require the attention of policy makers, who should plan strategies to promote healthy lifestyles and strategies to maintain serenity during this difficult period. Considering that the SARS-CoV-2 infections rate has been increasing since October 2020 and that several restrictions have been reintroduced to contain the spread of the virus, further investigations on this topic should be implemented. For example, studies exploring whether sleep has been affected during this second epidemic peak as well or whether individuals have adapted to the situation and have found strategies to deal with the limitations and uncertainties related to the SARS-CoV-2 spread would be of interested.
title	5. Conclusions
p	The quality of sleep, one of the determinants of public health, was adversely affected by the lockdown. Our study points out that nearly all individuals who experienced a change in their sleep reported poor quality of the same. This result is plausible, considering the fast disruption of routine caused by the pandemic. In fact, individuals’ well-being may have been seriously affected when both personal and public safety are no longer predictable, regardless of their resilience and their capacity for adaptation in daily life.
p	We highlighted the effect that sociodemographic and occupational characteristics, changes in lifestyle, and psychological distress have on sleep quality. While this study design does not allow us to determine a causal relationship among potential determinants and poor sleep quality, it nevertheless highlights the presence of categories of people who suffered the most: socially fragile individuals, those reporting negative changes in physical activity and diet, and individuals with psychological distress.
p	These categories require the attention of policy makers, who should plan strategies to promote healthy lifestyles and strategies to maintain serenity during this difficult period.
p	Considering that the SARS-CoV-2 infections rate has been increasing since October 2020 and that several restrictions have been reintroduced to contain the spread of the virus, further investigations on this topic should be implemented. For example, studies exploring whether sleep has been affected during this second epidemic peak as well or whether individuals have adapted to the situation and have found strategies to deal with the limitations and uncertainties related to the SARS-CoV-2 spread would be of interested.
back	Acknowledgments We thank Jacqueline M. Costa for the English language editing. We thank Ludovica De Panfilis for reviewing the survey for ethics. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Materials The following are available online at https://www.mdpi.com/1660-4601/18/1/306/s1, File S1: Survey on Lifestyle Adaptations in the General Population of the Province of Reggio Emilia Following the Emergency Quarantine COVID-19. Click here for additional data file. Author Contributions All authors contributed to the study conception and design and to interpretation of data. P.G.R., S.C., B.B., S.P., and E.M. developed the survey. S.P. and B.B. contributed to data analysis. The first draft of the manuscript was written by S.C., and all authors commented and contributed to it. All authors have read and agreed to the published version of the manuscript. Funding The Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia fully supported this study. Institutional Review Board Statement Not applicable. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The dataset generated and analyzed is retained by the Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia (Italy) and is available upon request from the corresponding author. Conflicts of Interest The authors do not have any conflicts of interest to disclose. Appendix A Table A1 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496 Sex Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724 Age class Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023 Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262 Education level High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679 Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787 Financial problems Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556 Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576 Table A2 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574 Sex Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753 Age class Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906 Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309 Education level High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550 Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737 Change in PA habits Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563 Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321 Legend PA = Physical activity. Table A3 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333 Sex Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861 Age class Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264 Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346 Education level High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671 Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843 Change in eating habits Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492 Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242 Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890 Table A4 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410 Sex Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799 Age class Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479 Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455 Education level High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662 Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885 Tension Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033 Table A5 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498 Sex Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730 Age class Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212 Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382 Education level High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580 Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782 Upset Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324 Table A6 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400 Sex Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882 Age class Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096 Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180 Education level High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666 Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883 Worry Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324 Table A7 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553 Sex Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808 Age class Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055 Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234 Education level High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623 Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814 Fear Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548 Table A8 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538 Sex Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728 Age class Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016 Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267 Education level High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650 Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838 Loneliness Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536 Table A9 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325 Sex Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856 Age class Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964 Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250 Education level High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649 Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903 Uncertainty Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069 Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
ack	Acknowledgments We thank Jacqueline M. Costa for the English language editing. We thank Ludovica De Panfilis for reviewing the survey for ethics.
title	Acknowledgments
p	We thank Jacqueline M. Costa for the English language editing. We thank Ludovica De Panfilis for reviewing the survey for ethics.
footnote	Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
p	Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
appendix	Supplementary Materials The following are available online at https://www.mdpi.com/1660-4601/18/1/306/s1, File S1: Survey on Lifestyle Adaptations in the General Population of the Province of Reggio Emilia Following the Emergency Quarantine COVID-19. Click here for additional data file.
title	Supplementary Materials
p	The following are available online at https://www.mdpi.com/1660-4601/18/1/306/s1, File S1: Survey on Lifestyle Adaptations in the General Population of the Province of Reggio Emilia Following the Emergency Quarantine COVID-19.
caption	Click here for additional data file.
p	Click here for additional data file.
notes	Author Contributions All authors contributed to the study conception and design and to interpretation of data. P.G.R., S.C., B.B., S.P., and E.M. developed the survey. S.P. and B.B. contributed to data analysis. The first draft of the manuscript was written by S.C., and all authors commented and contributed to it. All authors have read and agreed to the published version of the manuscript.
title	Author Contributions
p	All authors contributed to the study conception and design and to interpretation of data. P.G.R., S.C., B.B., S.P., and E.M. developed the survey. S.P. and B.B. contributed to data analysis. The first draft of the manuscript was written by S.C., and all authors commented and contributed to it. All authors have read and agreed to the published version of the manuscript.
notes	Funding The Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia fully supported this study.
title	Funding
p	The Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia fully supported this study.
notes	Institutional Review Board Statement Not applicable.
title	Institutional Review Board Statement
p	Not applicable.
notes	Informed Consent Statement Informed consent was obtained from all subjects involved in the study.
title	Informed Consent Statement
p	Informed consent was obtained from all subjects involved in the study.
notes	Data Availability Statement The dataset generated and analyzed is retained by the Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia (Italy) and is available upon request from the corresponding author.
title	Data Availability Statement
p	The dataset generated and analyzed is retained by the Azienda Unità Sanitaria Locale–IRCCS di Reggio Emilia (Italy) and is available upon request from the corresponding author.
notes	Conflicts of Interest The authors do not have any conflicts of interest to disclose.
title	Conflicts of Interest
p	The authors do not have any conflicts of interest to disclose.
appendix	Appendix A Table A1 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496 Sex Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724 Age class Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023 Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262 Education level High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679 Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787 Financial problems Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556 Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576 Table A2 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574 Sex Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753 Age class Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906 Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309 Education level High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550 Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737 Change in PA habits Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563 Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321 Legend PA = Physical activity. Table A3 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333 Sex Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861 Age class Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264 Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346 Education level High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671 Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843 Change in eating habits Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492 Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242 Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890 Table A4 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410 Sex Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799 Age class Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479 Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455 Education level High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662 Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885 Tension Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033 Table A5 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498 Sex Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730 Age class Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212 Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382 Education level High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580 Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782 Upset Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324 Table A6 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400 Sex Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882 Age class Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096 Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180 Education level High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666 Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883 Worry Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324 Table A7 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553 Sex Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808 Age class Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055 Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234 Education level High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623 Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814 Fear Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548 Table A8 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538 Sex Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728 Age class Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016 Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267 Education level High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650 Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838 Loneliness Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536 Table A9 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325 Sex Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856 Age class Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964 Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250 Education level High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649 Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903 Uncertainty Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069 Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
title	Appendix A
table-wrap	Table A1 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496 Sex Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724 Age class Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023 Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262 Education level High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679 Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787 Financial problems Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556 Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576
label	Table A1
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Financial Problems and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496 Sex Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724 Age class Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023 Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262 Education level High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679 Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787 Financial problems Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556 Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.403 0.358 −3.923 <0 .001 0.246 0.122 0.496
td	Intercept
td	−1.403
td	0.358
td	−3.923
td	<0 .001
td	0.246
td	0.122
td	0.496
td	Sex
tr	Sex
tr	Male–Female −0.840 0.264 −3.184 0.001 0.432 0.258 0.724
td	Male–Female
td	−0.840
td	0.264
td	−3.184
td	0.001
td	0.432
td	0.258
td	0.724
td	Age class
tr	Age class
tr	Aged–Adult −0.864 0.452 −1.911 0.056 0.421 0.174 1.023
td	Aged–Adult
td	−0.864
td	0.452
td	−1.911
td	0.056
td	0.421
td	0.174
td	1.023
tr	Middle-aged–Adult −0.141 0.191 −0.738 0.460 0.869 0.598 1.262
td	Middle-aged–Adult
td	−0.141
td	0.191
td	−0.738
td	0.460
td	0.869
td	0.598
td	1.262
td	Education level
tr	Education level
tr	High–Low −1.073 0.350 −3.065 0.002 0.342 0.172 0.679
td	High–Low
td	−1.073
td	0.350
td	−3.065
td	0.002
td	0.342
td	0.172
td	0.679
tr	Medium–Low −0.913 0.344 −2.656 0.008 0.401 0.205 0.787
td	Medium–Low
td	−0.913
td	0.344
td	−2.656
td	0.008
td	0.401
td	0.205
td	0.787
td	Financial problems
tr	Financial problems
tr	Many–None 1.940 0.376 5.156 <0 .001 6.962 3.329 14.556
td	Many–None
td	1.940
td	0.376
td	5.156
td	<0 .001
td	6.962
td	3.329
td	14.556
tr	Some–None 0.556 0.199 2.788 0.005 1.743 1.179 2.576
td	Some–None
td	0.556
td	0.199
td	2.788
td	0.005
td	1.743
td	1.179
td	2.576
table-wrap	Table A2 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574 Sex Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753 Age class Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906 Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309 Education level High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550 Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737 Change in PA habits Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563 Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321 Legend PA = Physical activity.
label	Table A2
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in PA Habits and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574 Sex Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753 Age class Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906 Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309 Education level High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550 Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737 Change in PA habits Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563 Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.245 0.352 −3.536 <0 .001 0.288 0.144 0.574
td	Intercept
td	−1.245
td	0.352
td	−3.536
td	<0 .001
td	0.288
td	0.144
td	0.574
td	Sex
tr	Sex
tr	Male–Female −0.788 0.258 −3.061 0.002 0.455 0.274 0.753
td	Male–Female
td	−0.788
td	0.258
td	−3.061
td	0.002
td	0.455
td	0.274
td	0.753
td	Age class
tr	Age class
tr	Aged–Adult −0.985 0.452 −2.178 0.029 0.374 0.154 0.906
td	Aged–Adult
td	−0.985
td	0.452
td	−2.178
td	0.029
td	0.374
td	0.154
td	0.906
tr	Middle-aged–Adult −0.104 0.190 −0.544 0.586 0.902 0.621 1.309
td	Middle-aged–Adult
td	−0.104
td	0.190
td	−0.544
td	0.586
td	0.902
td	0.621
td	1.309
td	Education level
tr	Education level
tr	High–Low −1.268 0.342 −3.709 <0.001 0.281 0.144 0.550
td	High–Low
td	−1.268
td	0.342
td	−3.709
td	<0.001
td	0.281
td	0.144
td	0.550
tr	Medium–Low −0.962 0.335 −2.871 0.004 0.382 0.198 0.737
td	Medium–Low
td	−0.962
td	0.335
td	−2.871
td	0.004
td	0.382
td	0.198
td	0.737
td	Change in PA habits
tr	Change in PA habits
tr	Improved–No change −0.595 0.532 −1.120 0.263 0.551 0.195 1.563
td	Improved–No change
td	−0.595
td	0.532
td	−1.120
td	0.263
td	0.551
td	0.195
td	1.563
tr	Worsened–No change 0.483 0.183 2.638 0.008 1.621 1.132 2.321
td	Worsened–No change
td	0.483
td	0.183
td	2.638
td	0.008
td	1.621
td	1.132
td	2.321
table-wrap-foot	Legend PA = Physical activity.
footnote	Legend PA = Physical activity.
p	Legend PA = Physical activity.
table-wrap	Table A3 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333 Sex Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861 Age class Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264 Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346 Education level High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671 Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843 Change in eating habits Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492 Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242 Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890
label	Table A3
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Change in Eating Habits and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333 Sex Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861 Age class Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264 Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346 Education level High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671 Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843 Change in eating habits Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492 Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242 Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.8735 0.395 −4.743 <0.001 0.154 0.0708 0.333
td	Intercept
td	−1.8735
td	0.395
td	−4.743
td	<0.001
td	0.154
td	0.0708
td	0.333
td	Sex
tr	Sex
tr	Male–Female −0.6464 0.253 −2.553 0.011 0.524 0.3190 0.861
td	Male–Female
td	−0.6464
td	0.253
td	−2.553
td	0.011
td	0.524
td	0.3190
td	0.861
td	Age class
tr	Age class
tr	Aged–Adult −0.5144 0.382 −1.347 0.178 0.598 0.2828 1.264
td	Aged–Adult
td	−0.5144
td	0.382
td	−1.347
td	0.178
td	0.598
td	0.2828
td	1.264
tr	Middle-aged adult −0.0689 0.187 −0.369 0.712 0.933 0.6476 1.346
td	Middle-aged adult
td	−0.0689
td	0.187
td	−0.369
td	0.712
td	0.933
td	0.6476
td	1.346
td	Education level
tr	Education level
tr	High–Low −1.0647 0.340 −3.132 0.002 0.345 0.1771 0.671
td	High–Low
td	−1.0647
td	0.340
td	−3.132
td	0.002
td	0.345
td	0.1771
td	0.671
tr	Medium–Low −0.8205 0.332 −2.474 0.013 0.440 0.2298 0.843
td	Medium–Low
td	−0.8205
td	0.332
td	−2.474
td	0.013
td	0.440
td	0.2298
td	0.843
td	Change in eating habits
tr	Change in eating habits
tr	Improved–No change 0.3883 0.268 1.450 0.147 1.474 0.8724 2.492
td	Improved–No change
td	0.3883
td	0.268
td	1.450
td	0.147
td	1.474
td	0.8724
td	2.492
tr	Worsened–No change 1.3103 0.266 4.930 <0.001 3.707 2.2019 6.242
td	Worsened–No change
td	1.3103
td	0.266
td	4.930
td	<0.001
td	3.707
td	2.2019
td	6.242
tr	Mixed–No change 0.8088 0.280 2.885 0.004 2.245 1.2960 3.890
td	Mixed–No change
td	0.8088
td	0.280
td	2.885
td	0.004
td	2.245
td	1.2960
td	3.890
table-wrap	Table A4 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410 Sex Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799 Age class Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479 Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455 Education level High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662 Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885 Tension Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033
label	Table A4
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Tension and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410 Sex Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799 Age class Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479 Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455 Education level High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662 Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885 Tension Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.61890 0.371 −4.3681 <0.001 0.198 0.0958 0.410
td	Intercept
td	−1.61890
td	0.371
td	−4.3681
td	<0.001
td	0.198
td	0.0958
td	0.410
td	Sex
tr	Sex
tr	Male–Female −0.74502 0.266 −2.8051 0.005 0.475 0.2821 0.799
td	Male–Female
td	−0.74502
td	0.266
td	−2.8051
td	0.005
td	0.475
td	0.2821
td	0.799
td	Age class
tr	Age class
tr	Aged–Adult −0.40416 0.406 −0.9958 0.319 0.668 0.3013 1.479
td	Aged–Adult
td	−0.40416
td	0.406
td	−0.9958
td	0.319
td	0.668
td	0.3013
td	1.479
tr	Middle-aged adult 0.00382 0.190 0.0202 0.984 1.004 0.6924 1.455
td	Middle-aged adult
td	0.00382
td	0.190
td	0.0202
td	0.984
td	1.004
td	0.6924
td	1.455
td	Education level
tr	Education level
tr	High–Low −1.11701 0.359 −3.1102 0.002 0.327 0.1619 0.662
td	High–Low
td	−1.11701
td	0.359
td	−3.1102
td	0.002
td	0.327
td	0.1619
td	0.662
tr	Medium–Low −0.81351 0.353 −2.3049 0.021 0.443 0.2220 0.885
td	Medium–Low
td	−0.81351
td	0.353
td	−2.3049
td	0.021
td	0.443
td	0.2220
td	0.885
td	Tension
tr	Tension
tr	Yes–No 1.25585 0.184 6.8324 <0.001 3.511 2.4488 5.033
td	Yes–No
td	1.25585
td	0.184
td	6.8324
td	<0.001
td	3.511
td	2.4488
td	5.033
table-wrap	Table A5 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498 Sex Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730 Age class Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212 Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382 Education level High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580 Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782 Upset Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324
label	Table A5
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Upset and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498 Sex Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730 Age class Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212 Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382 Education level High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580 Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782 Upset Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.4162 0.367 −3.863 <0.001 0.243 0.118 0.498
td	Intercept
td	−1.4162
td	0.367
td	−3.863
td	<0.001
td	0.243
td	0.118
td	0.498
td	Sex
tr	Sex
tr	Male–Female −0.8490 0.272 −3.116 0.002 0.428 0.251 0.730
td	Male–Female
td	−0.8490
td	0.272
td	−3.116
td	0.002
td	0.428
td	0.251
td	0.730
td	Age class
tr	Age class
tr	Aged–Adult −0.6390 0.424 −1.507 0.132 0.528 0.230 1.212
td	Aged–Adult
td	−0.6390
td	0.424
td	−1.507
td	0.132
td	0.528
td	0.230
td	1.212
tr	Middle-aged Adult −0.0489 0.190 −0.257 0.797 0.952 0.656 1.382
td	Middle-aged Adult
td	−0.0489
td	0.190
td	−0.257
td	0.797
td	0.952
td	0.656
td	1.382
td	Education level
tr	Education level
tr	High–Low −1.2453 0.358 −3.483 <0.001 0.288 0.143 0.580
td	High–Low
td	−1.2453
td	0.358
td	−3.483
td	<0.001
td	0.288
td	0.143
td	0.580
tr	Medium–Low −0.9358 0.352 −2.657 0.008 0.392 0.197 0.782
td	Medium–Low
td	−0.9358
td	0.352
td	−2.657
td	0.008
td	0.392
td	0.197
td	0.782
td	Upset
tr	Upset
tr	Yes–No 1.1042 0.184 6.012 <0.001 3.017 2.105 4.324
td	Yes–No
td	1.1042
td	0.184
td	6.012
td	<0.001
td	3.017
td	2.105
td	4.324
table-wrap	Table A6 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400 Sex Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882 Age class Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096 Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180 Education level High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666 Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883 Worry Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324
label	Table A6
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Worry and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400 Sex Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882 Age class Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096 Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180 Education level High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666 Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883 Worry Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.647 0.374 −4.41 <0 .001 0.193 0.0926 0.400
td	Intercept
td	−1.647
td	0.374
td	−4.41
td	<0 .001
td	0.193
td	0.0926
td	0.400
td	Sex
tr	Sex
tr	Male–Female −0.624 0.254 −2.46 0.014 0.536 0.3254 0.882
td	Male–Female
td	−0.624
td	0.254
td	−2.46
td	0.014
td	0.536
td	0.3254
td	0.882
td	Age class
tr	Age class
tr	Aged–Adult −0.653 0.380 −1.72 0.086 0.520 0.2471 1.096
td	Aged–Adult
td	−0.653
td	0.380
td	−1.72
td	0.086
td	0.520
td	0.2471
td	1.096
tr	Middle-aged adult −0.203 0.188 −1.08 0.280 0.817 0.5652 1.180
td	Middle-aged adult
td	−0.203
td	0.188
td	−1.08
td	0.280
td	0.817
td	0.5652
td	1.180
td	Education level
tr	Education level
tr	High–Low −1.093 0.350 −3.12 0.002 0.335 0.1688 0.666
td	High–Low
td	−1.093
td	0.350
td	−3.12
td	0.002
td	0.335
td	0.1688
td	0.666
tr	Medium–Low −0.796 0.343 −2.32 0.020 0.451 0.2305 0.883
td	Medium–Low
td	−0.796
td	0.343
td	−2.32
td	0.020
td	0.451
td	0.2305
td	0.883
td	Worry
tr	Worry
tr	Yes–No 0.836 0.186 4.48 <0.001 2.306 1.6003 3.324
td	Yes–No
td	0.836
td	0.186
td	4.48
td	<0.001
td	2.306
td	1.6003
td	3.324
table-wrap	Table A7 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553 Sex Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808 Age class Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055 Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234 Education level High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623 Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814 Fear Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548
label	Table A7
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Fear and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553 Sex Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808 Age class Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055 Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234 Education level High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623 Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814 Fear Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.309 0.365 −3.584 <0 .001 0.270 0.132 0.553
td	Intercept
td	−1.309
td	0.365
td	−3.584
td	<0 .001
td	0.270
td	0.132
td	0.553
td	Sex
tr	Sex
tr	Male–Female −0.735 0.266 −2.760 0.006 0.480 0.285 0.808
td	Male–Female
td	−0.735
td	0.266
td	−2.760
td	0.006
td	0.480
td	0.285
td	0.808
td	Age class
tr	Age class
tr	Aged–Adult −0.773 0.422 −1.832 0.067 0.462 0.202 1.055
td	Aged–Adult
td	−0.773
td	0.422
td	−1.832
td	0.067
td	0.462
td	0.202
td	1.055
tr	Middle-aged adult −0.160 0.189 −0.847 0.397 0.852 0.588 1.234
td	Middle-aged adult
td	−0.160
td	0.189
td	−0.847
td	0.397
td	0.852
td	0.588
td	1.234
td	Education level
tr	Education level
tr	High–Low −1.184 0.362 −3.268 0.001 0.306 0.150 0.623
td	High–Low
td	−1.184
td	0.362
td	−3.268
td	0.001
td	0.306
td	0.150
td	0.623
tr	Medium–Low −0.904 0.356 −2.537 0.011 0.405 0.201 0.814
td	Medium–Low
td	−0.904
td	0.356
td	−2.537
td	0.011
td	0.405
td	0.201
td	0.814
td	Fear
tr	Fear
tr	Yes–No 0.884 0.195 4.536 <0.001 2.421 1.652 3.548
td	Yes–No
td	0.884
td	0.195
td	4.536
td	<0.001
td	2.421
td	1.652
td	3.548
table-wrap	Table A8 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538 Sex Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728 Age class Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016 Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267 Education level High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650 Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838 Loneliness Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536
label	Table A8
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Loneliness and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538 Sex Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728 Age class Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016 Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267 Education level High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650 Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838 Loneliness Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.354 0.374 −3.620 <0.001 0.258 0.124 0.538
td	Intercept
td	−1.354
td	0.374
td	−3.620
td	<0.001
td	0.258
td	0.124
td	0.538
td	Sex
tr	Sex
tr	Male–Female −0.836 0.264 −3.161 0.002 0.434 0.258 0.728
td	Male–Female
td	−0.836
td	0.264
td	−3.161
td	0.002
td	0.434
td	0.258
td	0.728
td	Age class
tr	Age class
tr	Aged–Adult −0.815 0.424 −1.923 0.054 0.443 0.193 1.016
td	Aged–Adult
td	−0.815
td	0.424
td	−1.923
td	0.054
td	0.443
td	0.193
td	1.016
tr	Middle-aged adult −0.140 0.192 −0.730 0.466 0.869 0.596 1.267
td	Middle-aged adult
td	−0.140
td	0.192
td	−0.730
td	0.466
td	0.869
td	0.596
td	1.267
td	Education level
tr	Education level
tr	High–Low −1.153 0.368 −3.130 0.002 0.316 0.153 0.650
td	High–Low
td	−1.153
td	0.368
td	−3.130
td	0.002
td	0.316
td	0.153
td	0.650
tr	Medium–Low −0.886 0.362 −2.448 0.014 0.412 0.203 0.838
td	Medium–Low
td	−0.886
td	0.362
td	−2.448
td	0.014
td	0.412
td	0.203
td	0.838
td	Loneliness
tr	Loneliness
tr	Yes–No 1.122 0.199 5.635 <0.001 3.070 2.079 4.536
td	Yes–No
td	1.122
td	0.199
td	5.635
td	<0.001
td	3.070
td	2.079
td	4.536
table-wrap	Table A9 Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables. 95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325 Sex Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856 Age class Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964 Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250 Education level High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649 Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903 Uncertainty Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069 Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
label	Table A9
caption	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables.
p	Results of Multivariate Regression Analysis Models, with Quality of Sleep as Dependent Variable and Feeling of Uncertainty and Sociodemographic Characteristics as Independent Variables.
table	95% Confidence Interval Predictor Estimate SE Z p Odds Ratio Lower Upper Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325 Sex Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856 Age class Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964 Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250 Education level High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649 Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903 Uncertainty Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069
tr	95% Confidence Interval
th	95% Confidence Interval
tr	Predictor Estimate SE Z p Odds Ratio Lower Upper
th	Predictor
th	Estimate
th	SE
th	Z
th	p
th	Odds Ratio
th	Lower
th	Upper
tr	Intercept −1.874 0.383 −4.893 <0.001 0.154 0.0725 0.325
td	Intercept
td	−1.874
td	0.383
td	−4.893
td	<0.001
td	0.154
td	0.0725
td	0.325
td	Sex
tr	Sex
tr	Male–Female −0.651 0.252 −2.577 0.010 0.522 0.3181 0.856
td	Male–Female
td	−0.651
td	0.252
td	−2.577
td	0.010
td	0.522
td	0.3181
td	0.856
td	Age class
tr	Age class
tr	Aged–Adult −0.816 0.398 −2.051 0.040 0.442 0.2028 0.964
td	Aged–Adult
td	−0.816
td	0.398
td	−2.051
td	0.040
td	0.442
td	0.2028
td	0.964
tr	Middle-aged adult −0.144 0.188 −0.769 0.442 0.866 0.5994 1.250
td	Middle-aged adult
td	−0.144
td	0.188
td	−0.769
td	0.442
td	0.866
td	0.5994
td	1.250
td	Education level
tr	Education level
tr	High–Low −1.119 0.351 −3.191 0.001 0.327 0.1643 0.649
td	High–Low
td	−1.119
td	0.351
td	−3.191
td	0.001
td	0.327
td	0.1643
td	0.649
tr	Medium–Low −0.770 0.341 −2.259 0.024 0.463 0.2375 0.903
td	Medium–Low
td	−0.770
td	0.341
td	−2.259
td	0.024
td	0.463
td	0.2375
td	0.903
td	Uncertainty
tr	Uncertainty
tr	Yes–No 1.000 0.206 4.853 <0.001 2.717 1.8146 4.069
td	Yes–No
td	1.000
td	0.206
td	4.853
td	<0.001
td	2.717
td	1.8146
td	4.069
table-wrap-foot	Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
footnote	Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
p	Note. Estimates represent the log odds of “good sleep quality category” versus “poor sleep quality category”.
table-wrap	Table 1 Odds ratio for quality of sleep during lockdown by sociodemographic characteristics, work-related factors, changes in lifestyle and psychological distress. Total Poor Sleep Good Sleep Missing n % n % n % n % 1826 100 721 39.5 1026 56.2 79 4.3 OR 95% CI p-Value Lower Upper Sociodemographic characteristics Sex Female 1397 76.5 601 43.0 732 52.4 64 4.6 1.00 Male 423 23.2 119 28.1 293 69.3 11 2.6 0.47 0.29 0.76 0.002 Missing 6 0.3 1 16.7 1 16.7 4 66.7 Age 18-44 818 44.8 327 40.0 467 57.1 24 2.9 1.00 45-64 802 43.9 336 41.9 438 54.6 28 3.5 0.95 0.67 1.34 0.771 >65 194 10.6 55 28.4 118 60.8 21 10.8 0.54 0.26 1.11 0.092 Missing 12 0.7 3 25.0 3 25.0 6 50.0 Education level Low 94 5.1 38 40.4 50 53.2 6 6.4 1.00 Medium 805 44.1 329 40.9 432 53.7 44 5.5 0.55 0.30 1.03 0.066 High 889 48.7 338 38.0 527 59.3 24 2.7 0.44 0.23 0.81 0.009 Missing 38 2.1 16 42.1 17 44.7 5 13.2 Household Alone 208 11.4 77 37.0 129 62.0 2 1.0 1.00 ≥1 person 1618 88.6 644 39.8 897 55.4 77 4.8 1.06 0.62 1.79 0.834 Financial problems No problems 1320 72.3 464 35.2 794 60.2 62 4.7 1.00 Some problems 399 21.9 204 51.1 187 46.9 8 2.0 1.86 1.27 2.72 0.001 Many problems 38 2.1 23 60.5 15 39.5 0 0.0 7.27 3.59 14.73 <0.001 Missing 69 3.8 30 43.5 30 43.5 9 13.0 Occupational status during lockdown Continue working 1275 69.8 495 38.8 726 56.9 54 4.2 1.00 Activity stopped 181 9.9 82 45.3 96 53.0 3 1.7 1.33 0.80 2.21 0.266 Retir. Stud. Housew. 240 13.1 86 35.8 143 59.6 11 4.6 0.73 0.42 1.29 0.288 Unemployed 55 3.0 28 50.9 25 45.5 2 3.6 1.09 0.42 2.81 0.848 Missing 75 4.1 30 40.0 36 48.0 9 12.0 Changes in lifestyle Change in sleep habits Unchanged 701 38.4 645 92.0 24 3.4 34 4.9 1.00 Changed 981 53.7 842 85.8 121 12.3 17 1.7 3.86 2.46 6.05 <0.001 Uncertain 80 4.4 67 83.8 3 3.8 10 12.5 1.20 0.35 4.10 0.760 Missing 64 3.5 21 32.8 25 39.1 18 28.1 Change in physical activity habits Unchanged 972 53.2 349 35.9 596 61.3 27 3 1.00 Improved 97 5.3 37 38.1 56 57.7 4 4.1 0.59 0.21 1.68 0.330 Worsen 641 35.1 288 44.9 334 52.1 19 3.0 1.68 1.18 2.40 0.004 Missing 116 6.4 47 40.5 40 34.5 29 25.0 Change in eating habits Unchanged 530 29.0 152 28.7 361 68.1 17 3.2 1.00 Improved 612 33.5 237 38.7 361 59.0 14 2.3 1.49 0.89 2.51 0.125 Worsen 321 17.6 171 53.3 128 39.9 22 6.9 4.19 2.51 6.96 <0.001 Mixed behav. 337 18.5 156 46.3 164 48.7 17 5.0 2.41 1.40 4.15 0.001 Missing 26 1.4 5 19.2 12 46.2 9 34.6 Change in alcohol consumption Unchanged 1275 69.8 496 38.9 726 56.9 53 4.2 1.00 Decreased 231 12.7 90 39.0 138 59.7 3 1.3 0.73 0.41 1.28 0.280 Increased 229 12.5 107 46.7 112 48.9 10 4.4 1.34 0.84 2.13 0.209 Missing 91 5.0 28 30.8 50 54.9 13 14.3 Change in smoking habits Unchanged 1327 72.7 519 39.1 780 58.8 28 2.1 1.00 Decreased 75 4.1 33 44.0 40 53.3 2 2.7 0.79 0.31 2.01 0.628 Increased 140 7.7 64 45.7 67 47.9 9 6.4 1.39 0.78 2.47 0.251 Missing 284 15.6 105 37.0 139 48.9 40 14.1 Psychological distress Tension No 1337 73.2 452 33.8 838 62.7 47 3.5 1.00 Yes 359 19.7 232 64.6 107 29.8 20 5.6 3.88 2.74 5.52 <0.001 Missing 130 7.1 37 28.5 81 62.3 12 9.2 Upset No 1284 70.3 444 34.6 804 62.6 36 2.8 1.00 Yes 372 20.4 230 61.8 135 36.3 7 1.9 3.26 2.29 4.64 <0.001 Missing 170 9.3 47 27.6 87 51.2 36 21.2 Worry No 914 50.1 271 29.6 614 67.2 29 3.2 1.00 Yes 810 44.4 421 52.0 366 45.2 23 2.8 2.50 1.75 3.58 <0.001 Missing 102 5.6 29 28.4 46 45.1 27 26.5 Fear No 1404 76.9 501 35.7 847 60.3 56 4.0 1.00 Yes 303 16.6 180 59.4 116 38.3 7 2.3 2.74 1.89 3.97 <0.001 Missing 119 6.5 40 33.6 63 52.9 16 13.4 Loneliness No 1439 78.8 524 36.4 869 60.4 46 3.2 1.00 Yes 249 13.6 151 60.6 94 37.8 4 1.6 3.27 2.23 4.79 <0.001 Missing 138 7.6 46 33.3 63 45.7 29 21.0 Uncertainty No 778 42.6 239 30.7 499 64.1 40 5.1 1.00 Yes 996 54.5 468 47.0 499 50.1 29 2.9 2.89 1.93 4.31 <0.001 Missing 52 2.8 14 26.9 28 53.8 10 19.2 Legend: OR = Odds ratio; CI = Confidence Interval; Retir. = retired; Stud. = student; Housew. = housewife; behav. = behaviour Note: OR and CI were not calculated for missing values.
label	Table 1
caption	Odds ratio for quality of sleep during lockdown by sociodemographic characteristics, work-related factors, changes in lifestyle and psychological distress.
p	Odds ratio for quality of sleep during lockdown by sociodemographic characteristics, work-related factors, changes in lifestyle and psychological distress.
table	Total Poor Sleep Good Sleep Missing n % n % n % n % 1826 100 721 39.5 1026 56.2 79 4.3 OR 95% CI p-Value Lower Upper Sociodemographic characteristics Sex Female 1397 76.5 601 43.0 732 52.4 64 4.6 1.00 Male 423 23.2 119 28.1 293 69.3 11 2.6 0.47 0.29 0.76 0.002 Missing 6 0.3 1 16.7 1 16.7 4 66.7 Age 18-44 818 44.8 327 40.0 467 57.1 24 2.9 1.00 45-64 802 43.9 336 41.9 438 54.6 28 3.5 0.95 0.67 1.34 0.771 >65 194 10.6 55 28.4 118 60.8 21 10.8 0.54 0.26 1.11 0.092 Missing 12 0.7 3 25.0 3 25.0 6 50.0 Education level Low 94 5.1 38 40.4 50 53.2 6 6.4 1.00 Medium 805 44.1 329 40.9 432 53.7 44 5.5 0.55 0.30 1.03 0.066 High 889 48.7 338 38.0 527 59.3 24 2.7 0.44 0.23 0.81 0.009 Missing 38 2.1 16 42.1 17 44.7 5 13.2 Household Alone 208 11.4 77 37.0 129 62.0 2 1.0 1.00 ≥1 person 1618 88.6 644 39.8 897 55.4 77 4.8 1.06 0.62 1.79 0.834 Financial problems No problems 1320 72.3 464 35.2 794 60.2 62 4.7 1.00 Some problems 399 21.9 204 51.1 187 46.9 8 2.0 1.86 1.27 2.72 0.001 Many problems 38 2.1 23 60.5 15 39.5 0 0.0 7.27 3.59 14.73 <0.001 Missing 69 3.8 30 43.5 30 43.5 9 13.0 Occupational status during lockdown Continue working 1275 69.8 495 38.8 726 56.9 54 4.2 1.00 Activity stopped 181 9.9 82 45.3 96 53.0 3 1.7 1.33 0.80 2.21 0.266 Retir. Stud. Housew. 240 13.1 86 35.8 143 59.6 11 4.6 0.73 0.42 1.29 0.288 Unemployed 55 3.0 28 50.9 25 45.5 2 3.6 1.09 0.42 2.81 0.848 Missing 75 4.1 30 40.0 36 48.0 9 12.0 Changes in lifestyle Change in sleep habits Unchanged 701 38.4 645 92.0 24 3.4 34 4.9 1.00 Changed 981 53.7 842 85.8 121 12.3 17 1.7 3.86 2.46 6.05 <0.001 Uncertain 80 4.4 67 83.8 3 3.8 10 12.5 1.20 0.35 4.10 0.760 Missing 64 3.5 21 32.8 25 39.1 18 28.1 Change in physical activity habits Unchanged 972 53.2 349 35.9 596 61.3 27 3 1.00 Improved 97 5.3 37 38.1 56 57.7 4 4.1 0.59 0.21 1.68 0.330 Worsen 641 35.1 288 44.9 334 52.1 19 3.0 1.68 1.18 2.40 0.004 Missing 116 6.4 47 40.5 40 34.5 29 25.0 Change in eating habits Unchanged 530 29.0 152 28.7 361 68.1 17 3.2 1.00 Improved 612 33.5 237 38.7 361 59.0 14 2.3 1.49 0.89 2.51 0.125 Worsen 321 17.6 171 53.3 128 39.9 22 6.9 4.19 2.51 6.96 <0.001 Mixed behav. 337 18.5 156 46.3 164 48.7 17 5.0 2.41 1.40 4.15 0.001 Missing 26 1.4 5 19.2 12 46.2 9 34.6 Change in alcohol consumption Unchanged 1275 69.8 496 38.9 726 56.9 53 4.2 1.00 Decreased 231 12.7 90 39.0 138 59.7 3 1.3 0.73 0.41 1.28 0.280 Increased 229 12.5 107 46.7 112 48.9 10 4.4 1.34 0.84 2.13 0.209 Missing 91 5.0 28 30.8 50 54.9 13 14.3 Change in smoking habits Unchanged 1327 72.7 519 39.1 780 58.8 28 2.1 1.00 Decreased 75 4.1 33 44.0 40 53.3 2 2.7 0.79 0.31 2.01 0.628 Increased 140 7.7 64 45.7 67 47.9 9 6.4 1.39 0.78 2.47 0.251 Missing 284 15.6 105 37.0 139 48.9 40 14.1 Psychological distress Tension No 1337 73.2 452 33.8 838 62.7 47 3.5 1.00 Yes 359 19.7 232 64.6 107 29.8 20 5.6 3.88 2.74 5.52 <0.001 Missing 130 7.1 37 28.5 81 62.3 12 9.2 Upset No 1284 70.3 444 34.6 804 62.6 36 2.8 1.00 Yes 372 20.4 230 61.8 135 36.3 7 1.9 3.26 2.29 4.64 <0.001 Missing 170 9.3 47 27.6 87 51.2 36 21.2 Worry No 914 50.1 271 29.6 614 67.2 29 3.2 1.00 Yes 810 44.4 421 52.0 366 45.2 23 2.8 2.50 1.75 3.58 <0.001 Missing 102 5.6 29 28.4 46 45.1 27 26.5 Fear No 1404 76.9 501 35.7 847 60.3 56 4.0 1.00 Yes 303 16.6 180 59.4 116 38.3 7 2.3 2.74 1.89 3.97 <0.001 Missing 119 6.5 40 33.6 63 52.9 16 13.4 Loneliness No 1439 78.8 524 36.4 869 60.4 46 3.2 1.00 Yes 249 13.6 151 60.6 94 37.8 4 1.6 3.27 2.23 4.79 <0.001 Missing 138 7.6 46 33.3 63 45.7 29 21.0 Uncertainty No 778 42.6 239 30.7 499 64.1 40 5.1 1.00 Yes 996 54.5 468 47.0 499 50.1 29 2.9 2.89 1.93 4.31 <0.001 Missing 52 2.8 14 26.9 28 53.8 10 19.2
tr	Total Poor Sleep Good Sleep Missing
th	Total
th	Poor Sleep
th	Good Sleep
th	Missing
tr	n % n % n % n %
th	n
th	%
th	n
th	%
th	n
th	%
th	n
th	%
tr	1826 100 721 39.5 1026 56.2 79 4.3
th	1826
th	100
th	721
th	39.5
th	1026
th	56.2
th	79
th	4.3
tr	OR 95% CI p-Value
th	OR
th	95% CI
th	p-Value
tr	Lower Upper
th	Lower
th	Upper
tr	Sociodemographic characteristics Sex Female 1397 76.5 601 43.0 732 52.4 64 4.6 1.00
td	Sociodemographic characteristics
td	Sex
td	Female
td	1397
td	76.5
td	601
td	43.0
td	732
td	52.4
td	64
td	4.6
td	1.00
tr	Male 423 23.2 119 28.1 293 69.3 11 2.6 0.47 0.29 0.76 0.002
td	Male
td	423
td	23.2
td	119
td	28.1
td	293
td	69.3
td	11
td	2.6
td	0.47
td	0.29
td	0.76
td	0.002
tr	Missing 6 0.3 1 16.7 1 16.7 4 66.7
td	Missing
td	6
td	0.3
td	1
td	16.7
td	1
td	16.7
td	4
td	66.7
tr	Age 18-44 818 44.8 327 40.0 467 57.1 24 2.9 1.00
td	Age
td	18-44
td	818
td	44.8
td	327
td	40.0
td	467
td	57.1
td	24
td	2.9
td	1.00
tr	45-64 802 43.9 336 41.9 438 54.6 28 3.5 0.95 0.67 1.34 0.771
td	45-64
td	802
td	43.9
td	336
td	41.9
td	438
td	54.6
td	28
td	3.5
td	0.95
td	0.67
td	1.34
td	0.771
tr	>65 194 10.6 55 28.4 118 60.8 21 10.8 0.54 0.26 1.11 0.092
td	>65
td	194
td	10.6
td	55
td	28.4
td	118
td	60.8
td	21
td	10.8
td	0.54
td	0.26
td	1.11
td	0.092
tr	Missing 12 0.7 3 25.0 3 25.0 6 50.0
td	Missing
td	12
td	0.7
td	3
td	25.0
td	3
td	25.0
td	6
td	50.0
tr	Education level Low 94 5.1 38 40.4 50 53.2 6 6.4 1.00
td	Education level
td	Low
td	94
td	5.1
td	38
td	40.4
td	50
td	53.2
td	6
td	6.4
td	1.00
tr	Medium 805 44.1 329 40.9 432 53.7 44 5.5 0.55 0.30 1.03 0.066
td	Medium
td	805
td	44.1
td	329
td	40.9
td	432
td	53.7
td	44
td	5.5
td	0.55
td	0.30
td	1.03
td	0.066
tr	High 889 48.7 338 38.0 527 59.3 24 2.7 0.44 0.23 0.81 0.009
td	High
td	889
td	48.7
td	338
td	38.0
td	527
td	59.3
td	24
td	2.7
td	0.44
td	0.23
td	0.81
td	0.009
tr	Missing 38 2.1 16 42.1 17 44.7 5 13.2
td	Missing
td	38
td	2.1
td	16
td	42.1
td	17
td	44.7
td	5
td	13.2
tr	Household Alone 208 11.4 77 37.0 129 62.0 2 1.0 1.00
td	Household
td	Alone
td	208
td	11.4
td	77
td	37.0
td	129
td	62.0
td	2
td	1.0
td	1.00
tr	≥1 person 1618 88.6 644 39.8 897 55.4 77 4.8 1.06 0.62 1.79 0.834
td	≥1 person
td	1618
td	88.6
td	644
td	39.8
td	897
td	55.4
td	77
td	4.8
td	1.06
td	0.62
td	1.79
td	0.834
tr	Financial problems No problems 1320 72.3 464 35.2 794 60.2 62 4.7 1.00
td	Financial problems
td	No problems
td	1320
td	72.3
td	464
td	35.2
td	794
td	60.2
td	62
td	4.7
td	1.00
tr	Some problems 399 21.9 204 51.1 187 46.9 8 2.0 1.86 1.27 2.72 0.001
td	Some problems
td	399
td	21.9
td	204
td	51.1
td	187
td	46.9
td	8
td	2.0
td	1.86
td	1.27
td	2.72
td	0.001
tr	Many problems 38 2.1 23 60.5 15 39.5 0 0.0 7.27 3.59 14.73 <0.001
td	Many problems
td	38
td	2.1
td	23
td	60.5
td	15
td	39.5
td	0
td	0.0
td	7.27
td	3.59
td	14.73
td	<0.001
tr	Missing 69 3.8 30 43.5 30 43.5 9 13.0
td	Missing
td	69
td	3.8
td	30
td	43.5
td	30
td	43.5
td	9
td	13.0
tr	Occupational status during lockdown Continue working 1275 69.8 495 38.8 726 56.9 54 4.2 1.00
td	Occupational status during lockdown
td	Continue working
td	1275
td	69.8
td	495
td	38.8
td	726
td	56.9
td	54
td	4.2
td	1.00
tr	Activity stopped 181 9.9 82 45.3 96 53.0 3 1.7 1.33 0.80 2.21 0.266
td	Activity stopped
td	181
td	9.9
td	82
td	45.3
td	96
td	53.0
td	3
td	1.7
td	1.33
td	0.80
td	2.21
td	0.266
tr	Retir. Stud. Housew. 240 13.1 86 35.8 143 59.6 11 4.6 0.73 0.42 1.29 0.288
td	Retir. Stud. Housew.
td	240
td	13.1
td	86
td	35.8
td	143
td	59.6
td	11
td	4.6
td	0.73
td	0.42
td	1.29
td	0.288
tr	Unemployed 55 3.0 28 50.9 25 45.5 2 3.6 1.09 0.42 2.81 0.848
td	Unemployed
td	55
td	3.0
td	28
td	50.9
td	25
td	45.5
td	2
td	3.6
td	1.09
td	0.42
td	2.81
td	0.848
tr	Missing 75 4.1 30 40.0 36 48.0 9 12.0
td	Missing
td	75
td	4.1
td	30
td	40.0
td	36
td	48.0
td	9
td	12.0
tr	Changes in lifestyle Change in sleep habits Unchanged 701 38.4 645 92.0 24 3.4 34 4.9 1.00
td	Changes in lifestyle
td	Change in sleep habits
td	Unchanged
td	701
td	38.4
td	645
td	92.0
td	24
td	3.4
td	34
td	4.9
td	1.00
tr	Changed 981 53.7 842 85.8 121 12.3 17 1.7 3.86 2.46 6.05 <0.001
td	Changed
td	981
td	53.7
td	842
td	85.8
td	121
td	12.3
td	17
td	1.7
td	3.86
td	2.46
td	6.05
td	<0.001
tr	Uncertain 80 4.4 67 83.8 3 3.8 10 12.5 1.20 0.35 4.10 0.760
td	Uncertain
td	80
td	4.4
td	67
td	83.8
td	3
td	3.8
td	10
td	12.5
td	1.20
td	0.35
td	4.10
td	0.760
tr	Missing 64 3.5 21 32.8 25 39.1 18 28.1
td	Missing
td	64
td	3.5
td	21
td	32.8
td	25
td	39.1
td	18
td	28.1
tr	Change in physical activity habits Unchanged 972 53.2 349 35.9 596 61.3 27 3 1.00
td	Change in physical activity habits
td	Unchanged
td	972
td	53.2
td	349
td	35.9
td	596
td	61.3
td	27
td	3
td	1.00
tr	Improved 97 5.3 37 38.1 56 57.7 4 4.1 0.59 0.21 1.68 0.330
td	Improved
td	97
td	5.3
td	37
td	38.1
td	56
td	57.7
td	4
td	4.1
td	0.59
td	0.21
td	1.68
td	0.330
tr	Worsen 641 35.1 288 44.9 334 52.1 19 3.0 1.68 1.18 2.40 0.004
td	Worsen
td	641
td	35.1
td	288
td	44.9
td	334
td	52.1
td	19
td	3.0
td	1.68
td	1.18
td	2.40
td	0.004
tr	Missing 116 6.4 47 40.5 40 34.5 29 25.0
td	Missing
td	116
td	6.4
td	47
td	40.5
td	40
td	34.5
td	29
td	25.0
tr	Change in eating habits Unchanged 530 29.0 152 28.7 361 68.1 17 3.2 1.00
td	Change in eating habits
td	Unchanged
td	530
td	29.0
td	152
td	28.7
td	361
td	68.1
td	17
td	3.2
td	1.00
tr	Improved 612 33.5 237 38.7 361 59.0 14 2.3 1.49 0.89 2.51 0.125
td	Improved
td	612
td	33.5
td	237
td	38.7
td	361
td	59.0
td	14
td	2.3
td	1.49
td	0.89
td	2.51
td	0.125
tr	Worsen 321 17.6 171 53.3 128 39.9 22 6.9 4.19 2.51 6.96 <0.001
td	Worsen
td	321
td	17.6
td	171
td	53.3
td	128
td	39.9
td	22
td	6.9
td	4.19
td	2.51
td	6.96
td	<0.001
tr	Mixed behav. 337 18.5 156 46.3 164 48.7 17 5.0 2.41 1.40 4.15 0.001
td	Mixed behav.
td	337
td	18.5
td	156
td	46.3
td	164
td	48.7
td	17
td	5.0
td	2.41
td	1.40
td	4.15
td	0.001
tr	Missing 26 1.4 5 19.2 12 46.2 9 34.6
td	Missing
td	26
td	1.4
td	5
td	19.2
td	12
td	46.2
td	9
td	34.6
tr	Change in alcohol consumption Unchanged 1275 69.8 496 38.9 726 56.9 53 4.2 1.00
td	Change in alcohol consumption
td	Unchanged
td	1275
td	69.8
td	496
td	38.9
td	726
td	56.9
td	53
td	4.2
td	1.00
tr	Decreased 231 12.7 90 39.0 138 59.7 3 1.3 0.73 0.41 1.28 0.280
td	Decreased
td	231
td	12.7
td	90
td	39.0
td	138
td	59.7
td	3
td	1.3
td	0.73
td	0.41
td	1.28
td	0.280
tr	Increased 229 12.5 107 46.7 112 48.9 10 4.4 1.34 0.84 2.13 0.209
td	Increased
td	229
td	12.5
td	107
td	46.7
td	112
td	48.9
td	10
td	4.4
td	1.34
td	0.84
td	2.13
td	0.209
tr	Missing 91 5.0 28 30.8 50 54.9 13 14.3
td	Missing
td	91
td	5.0
td	28
td	30.8
td	50
td	54.9
td	13
td	14.3
tr	Change in smoking habits Unchanged 1327 72.7 519 39.1 780 58.8 28 2.1 1.00
td	Change in smoking habits
td	Unchanged
td	1327
td	72.7
td	519
td	39.1
td	780
td	58.8
td	28
td	2.1
td	1.00
tr	Decreased 75 4.1 33 44.0 40 53.3 2 2.7 0.79 0.31 2.01 0.628
td	Decreased
td	75
td	4.1
td	33
td	44.0
td	40
td	53.3
td	2
td	2.7
td	0.79
td	0.31
td	2.01
td	0.628
tr	Increased 140 7.7 64 45.7 67 47.9 9 6.4 1.39 0.78 2.47 0.251
td	Increased
td	140
td	7.7
td	64
td	45.7
td	67
td	47.9
td	9
td	6.4
td	1.39
td	0.78
td	2.47
td	0.251
tr	Missing 284 15.6 105 37.0 139 48.9 40 14.1
td	Missing
td	284
td	15.6
td	105
td	37.0
td	139
td	48.9
td	40
td	14.1
tr	Psychological distress Tension No 1337 73.2 452 33.8 838 62.7 47 3.5 1.00
td	Psychological distress
td	Tension
td	No
td	1337
td	73.2
td	452
td	33.8
td	838
td	62.7
td	47
td	3.5
td	1.00
tr	Yes 359 19.7 232 64.6 107 29.8 20 5.6 3.88 2.74 5.52 <0.001
td	Yes
td	359
td	19.7
td	232
td	64.6
td	107
td	29.8
td	20
td	5.6
td	3.88
td	2.74
td	5.52
td	<0.001
tr	Missing 130 7.1 37 28.5 81 62.3 12 9.2
td	Missing
td	130
td	7.1
td	37
td	28.5
td	81
td	62.3
td	12
td	9.2
tr	Upset No 1284 70.3 444 34.6 804 62.6 36 2.8 1.00
td	Upset
td	No
td	1284
td	70.3
td	444
td	34.6
td	804
td	62.6
td	36
td	2.8
td	1.00
tr	Yes 372 20.4 230 61.8 135 36.3 7 1.9 3.26 2.29 4.64 <0.001
td	Yes
td	372
td	20.4
td	230
td	61.8
td	135
td	36.3
td	7
td	1.9
td	3.26
td	2.29
td	4.64
td	<0.001
tr	Missing 170 9.3 47 27.6 87 51.2 36 21.2
td	Missing
td	170
td	9.3
td	47
td	27.6
td	87
td	51.2
td	36
td	21.2
tr	Worry No 914 50.1 271 29.6 614 67.2 29 3.2 1.00
td	Worry
td	No
td	914
td	50.1
td	271
td	29.6
td	614
td	67.2
td	29
td	3.2
td	1.00
tr	Yes 810 44.4 421 52.0 366 45.2 23 2.8 2.50 1.75 3.58 <0.001
td	Yes
td	810
td	44.4
td	421
td	52.0
td	366
td	45.2
td	23
td	2.8
td	2.50
td	1.75
td	3.58
td	<0.001
tr	Missing 102 5.6 29 28.4 46 45.1 27 26.5
td	Missing
td	102
td	5.6
td	29
td	28.4
td	46
td	45.1
td	27
td	26.5
tr	Fear No 1404 76.9 501 35.7 847 60.3 56 4.0 1.00
td	Fear
td	No
td	1404
td	76.9
td	501
td	35.7
td	847
td	60.3
td	56
td	4.0
td	1.00
tr	Yes 303 16.6 180 59.4 116 38.3 7 2.3 2.74 1.89 3.97 <0.001
td	Yes
td	303
td	16.6
td	180
td	59.4
td	116
td	38.3
td	7
td	2.3
td	2.74
td	1.89
td	3.97
td	<0.001
tr	Missing 119 6.5 40 33.6 63 52.9 16 13.4
td	Missing
td	119
td	6.5
td	40
td	33.6
td	63
td	52.9
td	16
td	13.4
tr	Loneliness No 1439 78.8 524 36.4 869 60.4 46 3.2 1.00
td	Loneliness
td	No
td	1439
td	78.8
td	524
td	36.4
td	869
td	60.4
td	46
td	3.2
td	1.00
tr	Yes 249 13.6 151 60.6 94 37.8 4 1.6 3.27 2.23 4.79 <0.001
td	Yes
td	249
td	13.6
td	151
td	60.6
td	94
td	37.8
td	4
td	1.6
td	3.27
td	2.23
td	4.79
td	<0.001
tr	Missing 138 7.6 46 33.3 63 45.7 29 21.0
td	Missing
td	138
td	7.6
td	46
td	33.3
td	63
td	45.7
td	29
td	21.0
tr	Uncertainty No 778 42.6 239 30.7 499 64.1 40 5.1 1.00
td	Uncertainty
td	No
td	778
td	42.6
td	239
td	30.7
td	499
td	64.1
td	40
td	5.1
td	1.00
tr	Yes 996 54.5 468 47.0 499 50.1 29 2.9 2.89 1.93 4.31 <0.001
td	Yes
td	996
td	54.5
td	468
td	47.0
td	499
td	50.1
td	29
td	2.9
td	2.89
td	1.93
td	4.31
td	<0.001
tr	Missing 52 2.8 14 26.9 28 53.8 10 19.2
td	Missing
td	52
td	2.8
td	14
td	26.9
td	28
td	53.8
td	10
td	19.2
table-wrap-foot	Legend: OR = Odds ratio; CI = Confidence Interval; Retir. = retired; Stud. = student; Housew. = housewife; behav. = behaviour Note: OR and CI were not calculated for missing values.
footnote	Legend: OR = Odds ratio; CI = Confidence Interval; Retir. = retired; Stud. = student; Housew. = housewife; behav. = behaviour Note: OR and CI were not calculated for missing values.
p	Legend: OR = Odds ratio; CI = Confidence Interval; Retir. = retired; Stud. = student; Housew. = housewife; behav. = behaviour Note: OR and CI were not calculated for missing values.

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