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IntroductionSedentary behavior (SB) has been associated with adverse health outcomes, however, it is not completely clear whether total time in SB during the day or prolonged uninterrupted SB are interrelated. The aim of the current study was to describe the different patterns of SB of adults, their relationships, and associated factors.MethodsThe sample included 184 adults aged ranging from 18 to 59 years old. SB was objectively measured by an accelerometer and the following SB pattern parameters were obtained: total time in sedentary bouts, mean time of sedentary bouts, and total time in sedentary breaks. Demographic data (age and sex), anthropometry [weight, height, body mass index (BMI)], blood pressure (BP), medical history (self-reported comorbid conditions), and cardiac autonomic modulation, were assessed to identify factors associated with SB. Multiple linear regressions were used to analyze the relationship between SB parameters and the associated factors.ResultsThe parameters of SB indicated 2.4 (0.9) h/day for total time in sedentary bouts, 36.4 (7.9) min for the mean time of sedentary bouts, and 9.1 (1.9) h/day for the total time in sedentary breaks. Multiple adjusted regression indicated that age was the only factor associated with SB patterns (p

Objective: This study analyzed the association of high blood pressure (HBP) with physical activity, sedentary behavior, and sedentary breaks in 2-year follow-up.Methods: A sample of 331 middle-aged and older adults (mean age of 59.6 ± 17.3 years) was randomly selected and assessed at baseline and after 2 years of follow-up. HBP was considered as ≥140/90 mmHg values of systolic and diastolic blood pressure. Physical activity, sedentary behavior, and sedentary breaks were assessed by questionnaire. Age, sex, socioeconomic status, and body mass index were covariates.Results: Continuous HBP was observed in 26.3% of sample between baseline and follow-up. Adults who reported continuously high sedentary breaks at leisure activities were less likely to have HBP (OR = 0.34, p = 0.011), as well as those who remained high physically active (OR = 0.41, p = 0.016), even after mutual adjustment. No association was observed between high sedentary behavior and HBP at follow-up.Conclusion: Community dwelling adults who were high active and performed frequent sedentary breaks were less likely to have HBP in 2-year follow-up. Strategies for HBP control should considered both physical activities and leisure sedentary breaks in adult population.

The aim of this study was to analyze the association between physical activity and eating habits during the COVID-19 pandemic among Brazilian adults. A sample of 1,929 participants answered an online survey, however 1,874 were included in the analysis. The impact of the COVID-19 pandemic on eating habits was assessed inquiring about participants' intake of fruits, vegetables, fried foods, and sweets during the pandemic. Physical activity was assessed by asking participants about their weekly frequency, intensity and number of minutes/hours engaging in structured physical activities per week. Participants were then stratified into categories based on moderate-to-vigorous intensity (0–30; 31–90; 91–150; 151–300; and >300 min/week) and into active (≥150 min) or inactive (

Background: Elevated screen time has been associated with addictive behaviors, such as alcohol and sugar intake and smoking. Considering the substantial increase in screen time caused by social isolation policies, this study aimed to analyze the association of increased screen time in different devices during the COVID-19 pandemic with consumption and increased desire of alcohol, smoking, and sweetened foods in adults.Methods: A sample of 1,897 adults with a mean age of 37.9 (13.3) years was assessed by an online survey, being composed by 58% of women. Participants were asked whether screen time in television, cell phone, and computer increased during the pandemic, as well as how much time is spent in each device. Closed questions assessed the frequency of alcohol and sweetened food consumption, smoking, and an increased desire to drink and smoke during the pandemic. Educational level, age, sex, feeling of stress, anxiety, depression, and use of a screen device for physical activity were covariates. Binary logistic regression models considered adjustment for covariates and for mutual habits.Results: Increased television time was associated with increased desire to drink (OR = 1.46, 95% CI: 1.12; 1.89) and increased sweetened food consumption (OR = 1.53, 95% CI: 1.18; 1.99), while an increase in computer use was negatively associated with consumption of alcohol (OR = 0.68, 95% CI: 0.53; 0.86) and sweetened foods (OR = 0.78, 95% CI: 0.62; 0.98). Increased cell phone time was associated with increased sweetened food consumption during the pandemic (OR = 1.78, 95% CI: 1.18; 2.67). Participants with increased time in the three devices were less likely to consume sweetened foods for ≥5 days per week (OR = 0.63, 95% CI: 0.39; 0.99) but were twice as likely to have sweetened food consumption increased during pandemic (OR = 2.04, 95% CI: 1.07; 3.88).Conclusion: Increased screen time was differently associated with consumption and desire for alcohol and sweets according to screen devices. Increased time in television and cell phones need to be considered for further investigations of behavioral impairments caused by the pandemic.

BackgroundThe outbreak of novel coronavirus disease 2019 (COVID-19) has caused a global panic and public concern due to its mortality ratio and lack of treatments/vaccines. Reduced levels of physical activity have been reported during the outbreak, affecting the normal daily pattern.ObjectiveTo investigate (i) the relationship of physical activity level with sleep quality and (ii) the effects of reduction physical activity levels on sleep quality.MethodsA Google form was used to address personal information, COVID-19 personal care, physical activity, and mental health of 1,907 adult volunteers. Binary logistic regression was used to verify the association of physical activity parameters and sleep quality.ResultsInsufficient physical activity levels were a risk factor to have disturbed sleep pattern [OR: 1.28, 95% CI (1.01–1.62)]; however, when the BMI was added to the analysis, there was no more statistical difference [OR: 1.23, 95% CI (0.96–1.57)]. On the other hand, we found that the reduction of physical activity levels was associated with negative changes in sleep quality [OR: 1.73, 95% CI (1.37–2.18)], regardless all the confounders [OR: 1.30, 95% CI (1.01–1.68)], unless when feeling of depression was added in Model 6 [OR: 1.28, 95% CI (0.99–1.66)].ConclusionDisruption in daily physical activity routine, rather than physical activity level, negatively influences sleep quality during the COVID-19 quarantine.