Sedentary behavior is associated with poor sleep quality during the COVID-19 pandemic, and physical activity mitigates its adverse effects.

BACKGROUND: We aimed to evaluate the association of sedentary behavior (SB) and moderate to vigorous leisure-time physical activity (MVPA) with sleep quality during the COVID-19 pandemic. METHODS: Cross-sectional, population-based study in adults, conducted from October to December 2020 in the Iron Quadrangle region, Brazil. The outcome was sleep quality, evaluated with the Pittsburgh Sleep Quality Index. SB was assessed by self-report of total sitting time, before and during the pandemic. Individuals with ≥ 9 h of total sitting time were classified as SB. In addition, the ratio of time spent in MVPA to time in SB was analyzed. A contrasted directed acyclic graph (DAG) model was constructed to adjust logistic regression models. RESULTS: A total of 1629 individuals were evaluated, the prevalence of SB before the pandemic was 11.3% (95%CI: 8.6-14.8), and during the pandemic 15.2% (95%CI: 12.1-18.9). In multivariate analysis, the chance of poor sleep quality was 77% higher in subjects with SB ≥ 9 h per day (OR: 1.77; 95% CI: 1.02-2.97). Furthermore, a one-hour increase in SB during the pandemic, increased the chance of poor sleep quality by 8% (OR: 1.08; 95%CI 1.01-1.15). In the analysis of the ratio of MVPA per SB in individuals with SB ≥ 9 h, practicing 1 min of MVPA per hour of SB reduces the chance of poor sleep quality by 19% (OR: 0.84; 95%CI: 0.73-0.98). CONCLUSION: SB during the pandemic was a factor associated with poor sleep quality, and the practice of MVPA can reduce the effects of SB.

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

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.

The combined consumption of fresh/minimally processed food and ultra-processed food on food insecurity: COVID Inconfidentes, a population-based survey.

OBJECTIVE: To investigate whether the combined consumption of fresh/minimally processed and ultra-processed food is associated with food insecurity (FI) during the COVID-19 pandemic. DESIGN: Cross-sectional observational study was derived from a survey using a population-based search of a complex sample. FI was assessed using the validated Brazilian Food Insecurity Scale. Food consumption was assessed using a qualitative FFQ and the NOVA classification for fresh/minimally processed food and ultra-processed food. A scoring system was used to evaluate combined food consumption according to the extent and purpose of processing, considering the weekly consumption of the two groups (according to the NOVA classification). Higher punctuation reflects worse diet quality (higher consumption of ultra-processed foods and lower consumption of fresh/minimally processed foods). A theoretical causality model was constructed using a directed acyclic graph, and multivariate analysis was performed using Poisson regression to test the association between FI and food consumption. SETTING: Ouro Preto and Mariana, Brazil, between October and December 2020. PARTICIPANTS: An epidemiological household survey was conducted with 1753 individuals selected through a stratified and clustered sampling design in three stages. RESULTS: Those with food consumption scores in the fourth quartile had a 60 % higher prevalence ratio (PR) for FI (PR: 1·60 and 95 % CI: 1·06 - 2·40). Also, the increased consumption of fresh/minimally processed foods and low consumption of ultra-processed foods presented a 45 % lower prevalence ratio of FI (PR: 0·55 and 95 % CI: 0·40 - 0·80). CONCLUSION: These results indicate an inverse association between FI and diet quality.

Food consumption according to the level of processing and sleep quality during the COVID-19 pandemic.

BACKGROUND AND AIMS: Consumption of ultra-processed foods is negatively associated with health outcomes, however, the contribution to sleep quality is limited. Therefore, the objective of this study was to evaluate the association between food intake by frequency and degree of processing and sleep quality in adults during the covid-19 pandemic. METHODS: Population-based survey of adults from October to December 2020 in the Iron Quadrangle region, Brazil. The exposure variable was a food intake score that considered the frequency of consumption and food processing degree. The total score ranged from 0 (best) to 48 points (worst food quality), categorized into quartiles. Furthermore, we also evaluated whether individuals replaced their lunch and/or dinner based mostly on fresh/minimally processed foods for ultra-processed foods, for five or more days in the week. The outcome variable was sleep quality assessed with the Pittsburgh Sleep Quality Index. We constructed a contrasting directed acyclic graph (DAG) model to estimate the adjusted odds ratio of the association between score eating and sleep, by logistic regression. RESULTS: Most of the 1762 individuals evaluated had poor sleep quality (52.5%). The minimum and maximum food scores were 0 and 30 points (mean 9.16; 95% CI 8.50, 9.81). The higher values of the score corresponded to lower consumption of fresh and minimally processed foods and higher consumption of ultraprocessed foods. In multivariate analysis, individuals in the third food consumption score had 71% greater odds of poor sleep quality (OR = 1.71; 95% CI: 1.03, 2.85) and in the fourth quartile 144% greater odds (OR = 2.44; 95% CI: 1.32, 2.44). Besides, replacing the dinner meal with ultra-processed foods five days or more in the week was also associated with poor sleep quality (OR = 2.01; 95%CI: 1.14, 3.57). CONCLUSION: Higher consumption of ultra-processed foods concomitant with lower consumption of fresh and minimally processed foods is associated with a higher chance of poor sleep quality.