Determinants of poor sleep quality in adults during the coronavirus disease pandemic: COVID-Inconfidentes, a population-based study

ABSTRACT BACKGROUND: The coronavirus disease (COVID-19) pandemic has adversely affected the health of the global population, with sleep quality being one of the affected parameters. OBJECTIVES: To evaluate sleep quality and its associated factors in adults during the COVID-19 pandemic in Brazil. DESIGN AND SETTING: A population-based cross-sectional serological survey of 1,762 adults in the Iron Quadrangle region of Brazil. METHODS: The Pittsburgh Sleep Quality Index was used to assess sleep quality. Sociodemographic variables, health conditions, health-related behaviors, anxiety, vitamin D levels, weight gain/loss, and pandemic characteristics were assessed using a structured questionnaire. Univariate and multivariate analyses using Poisson regression with robust variance were performed to identify factors associated with sleep quality. RESULTS: More than half of the participants reported poor sleep quality (52.5%). Multivariate analysis revealed that the factors associated with poor sleep quality included living alone (prevalence ratio [PR] = 1.34; 95% confidence interval [CI]: 1.04–1.73), anxiety disorder (PR = 1.32; 95% CI: 1.08–1.62), 5.0% weight loss (PR = 1.21; 95% CI: 1.02–1.44), 5.0% weight gain (PR = 1.27; 95% CI: 1.03–1.55), vitamin D deficiency (PR = 1.16; 95% CI: 1.01–1.35), and COVID-19 symptoms (PR = 1.29; 95% CI: 1.10–1.52). CONCLUSIONS: Our study revealed that more than half of the participants experienced poor sleep quality during the COVID-19 pandemic. Factors associated with poor sleep quality included vitamin D deficiency and weight changes related to the pandemic.


INTRODUCTION
Sleep is essential for maintaining physiological parameters and plays an important role in hormone release and the regulation of cardiovascular activities and glucose levels. 1 In addition, Poor sleep quality, particularly if chronic, may adversely affect the immune system components, disrupting antibody production after vaccination or previous contact with the viral agent.
This could lead to increased vulnerability to infectious diseases such as coronavirus disease . 2 From the beginning of the pandemic to almost two years later, Brazil has been one of the most affected countries. It remains in the top five countries with highest number of infected people and deaths due to  Owing to the highly contagious nature of COVID-19 and limited knowledge regarding its natural history, several control measures have been adopted, such as practice of respiratory hygiene, use of masks, and implementation of social restrictions. 4 These measures, along with the pandemic scenario, have led to drastic changes in people's lifestyle, such as reduced physical activity, changes in food intake, reduced sun exposure, 4,5 and other factors that directly affect sleep quality. 6,7 OBJECTIVE As a pandemic tends to alter the daily routine and life habits of the population, 8 this study aimed to evaluate sleep quality and its associated factors during the COVID-19 pandemic. All procedures adopted in this study were in accordance with the principles of the Declaration of Helsinki and the Brazilian guidelines and standards for human research. Written informed consent was obtained from all participants.
The survey was conducted in three stages at 21-day intervals, and different census sectors were evaluated in each city. The complex sample size calculation was based on the population estimate for each city, considering a confidence level of 95%, design effect of 1.5, and the parameters presented in a previous study. 9 A three-stage conglomerate sampling design was adopted as follows: census sector (randomly selected for each stage and without replacement), households (selected by a systematic sampling process), and residents (one resident selected randomly). The sample weight of each selected unit (census tract, household, and individual) was calculated and adjusted to compensate for the loss of interviews owing to non-response, and the weights of the household and the selected resident were calibrated. 9

Data collection
The data collection process included listing and approaching households during weekends to enhance the participation of residents who worked during the week, thus increasing the representativeness of this population group.
Face-to-face interviews were conducted by trained interviewers, using a structured questionnaire to collect data on sociode- inactivity, at least 150-300 minutes of moderate-intensity aerobic physical activity per week, or at least 75-150 minutes of vigorous-intensity aerobic physical activity per week). 10 Selfrated health was assessed as "very good," "good," "fair," "poor," and "very poor". Nutritional status was assessed based on body mass index (BMI). is an important determinant of sleep quality. 16 In addition, it has been recommended as a threshold for clinically relevant weight loss in several national and international guidelines. [17][18][19][20] The average daily sun exposure was evaluated and classified as "insufficient" if exposure was < 30 minutes/day and "sufficient" if it was ≥ 30 minutes/day. 21 We also evaluated a possible scenario Furthermore, we asked about their daily routine activities during the pandemic.

Measurement of sleep quality
The Pittsburgh Sleep Quality Index (PSQI) questionnaire was indicating the worst sleep quality. An overall score of > 5 indicates major difficulties in at least two components or moderate difficulties in more than three components. 22 The Brazilian version of the PSQI has an overall reliability coefficient (Cronbach α) of 0.82, indicating a high degree of internal consistency. 23 Herein, sleep quality was classified as good (PSQI score ≤ 5) or poor (PSQI score > 5). A PSQI score of ≥ 2 indicated moderate to severe difficulty in a sleep-specific domain (C1 to C7). 22 This cutoff point was also used by Wang et al. in their study in 2020. 24

Statistical analysis
Statistical analyses were performed considering the complex design of the sample using the "svy" command of the Stata soft-

Characteristics and sleep quality of participants
Among the participants, women reported a high prevalence of abnormal PSQI scores in the subdomains of subjective sleep quality, sleep efficiency, and the use of sleep medications (P < 0.05). Furthermore, sleep medication use increased with increasing age, and daytime dysfunction was higher in the younger age group (P < 0.05) ( Table 1). The mean PSQI score was 6.32 (95% CI: 6.03-6.62), and the prevalence of poor sleep quality was 52.5%. The highest prevalence rates for the abnor- Among the participants, 51.9% were women, and the most prevalent age group was 35-59 years (45.6%). Most participants were married (53.2%), had > 9 years of schooling (68.8%), and had a family income ≤ 2 times the minimum wage (41.1%) ( Table 2).
At least 12% of the participants experienced 5.0% weight loss or gain during the pandemic (12.4% and 17.7%, respectively), 35.0% had a daily sun exposure of < 30 minutes, and 27.1% had vitamin D deficiency (Table 4).

Factors associated with poor sleep quality
In the multivariate model, the following factors were significantly associated with poor sleep quality: living alone (PR = Based on the factors associated with sleep quality obtained in the aforementioned adjusted model (Table 5), a chance modification analysis for poor sleep quality was performed, assuming the presence of combined changes in these variables (Figure 1). Overall 29 However, it should be noted that this study was conducted online, which would usually represent a more educated and higher-income group of the population and hence is different from a household survey.
During the pandemic, online tasks made the workday endless and affected sleep quality. Such a work schedule also reduced individuals' sun exposure, as most people spending more time doing online tasks no longer commuted to work or lunch. Sun exposure is an important factor because it is the main source of endogenous vitamin D. 21 We found that individuals with insufficient vitamin D levels had a higher PR for poor sleep quality than those with sufficient levels. This association may be explained by the intracellular distribution of vitamin D receptors in brain areas that regulate the sleep-wake cycle or through pro-inflammatory mediators. Vitamin D is also involved in the production of melatonin, an essential hormone in the regulation of circadian rhythm and sleep.
Melatonin synthesis is controlled by the active form of vitamin D, 1,25(OH) 2 D, that induces the expression of tryptophan hydroxylase (the initial enzyme in the melatonin synthesis pathway). 30 This suggests a possible role for vitamin D deficiency in sleep disturbances. 31,32 These results were found in a previous study on mining workers conducted in the same region as that of our study. In order to avoid the type 1 error, the Bonferroni correction for multiple [7] tests, was set at 0.007.
When evaluating sleep quality using polysomnography, the gold standard method, workers with hypovitaminosis D had more sleep disturbances than those without it. 33 The routine of these workers was similar to that of people confined during the COVID-19 pandemic, since they were off-road machinery drivers who spent most of their time on machines without access to sunlight. 34 An additional variable associated with poor sleep quality in our study was weight change during the pandemic. Individuals who reduced or gained up to 5.0% of their body weight during the pandemic had a greater PR for poor sleep quality than those who did not experience weight change. Weight loss, when intentional, particularly in obese individuals, can be beneficial in improving sleep quality. 35 However, unintentional weight loss may be related to increased physical and emotional stress or an imbalance between food supply and demand. A systematic review conducted between July 2020 and February 2021 found that during the pandemic, 11.1-32.0% of the total 469,362 participants had experienced weight loss. 36 For some people, the lockdown provided more time to cook and eat better; however, most people developed malnutrition and experienced weight loss owing to inflated food prices and food insecurity. In Brazil, more than half of the households (59.4%) experienced food insecurity during the pandemic. 37 Insufficient food consumption of adequate quantity and quality can have severe health effects, such as poor mental health and increased likelihood of diseases, 37 increasing the chances of poor sleep quality and vulnerability to COVID-19.
In addition, pandemic confinement was associated with weight gain in 7.2-72.4% of participants in a previous systematic review. 36  In order to avoid the type 1 error, the Bonferroni correction for multiple [9] tests, was set at 0.005. Weight loss is defined as a loss of 5% or more during the pandemic. Weight gain is defined as a gain of 5% or more during the pandemic (self-reported weight).  This study identified the important factors related to sleep quality during the pandemic; however, these findings should be interpreted with caution. In our study, causal relationships could not be determined because of the absence of previously available information on sleep quality. Furthermore, the variables were obtained by self-reporting, which may have caused underestimation of risk or overestimation of protective behaviors owing to differences in each individual's perception of the pandemic and associated factors. However, the assessment of sleep quality needs to be performed subjectively since it considers the factors intrinsic to individuals' perception of their sleep. Self-reported weight and height may have influenced these results; however, there are studies involving similar populations and strong methodological rigor that demonstrated high agreement with the measured values. 43,44 Therefore, BMI computed from self-reported weight and height can be considered a valid measure in men and women of different sociodemographic groups. 43,44 The strengths of this study include a representative random sample of the resident population from different socioeconomic strata, evaluation using a household survey, and face-to-face interviews during the COVID-19 pandemic, which increased the robustness of the study.

CONCLUSION
Our study revealed that more than half of the participants had poor sleep quality during the COVID-19 pandemic.
Moreover, factors associated with poor sleep quality were related to the pandemic, such as vitamin D deficiency and weight change.