Consequences of social distancing during the COVID-19 pandemic on the increase in perceived pain of students and professors from higher education institutions: A cross-sectional study
Abstract
BACKGROUND:
Social distancing was implemented worldwide due to the coronavirus (COVID-19) pandemic. This impacted physical activity levels and increased the time spent in sedentary behaviors which may contributed to the emergence of increased musculoskeletal complaints.
OBJECTIVE:
To assess the consequences of social distancing for the increase in perceived pain of students and professors from higher education institutions.
METHODS:
One thousand two hundred and fifty-four participants responded to an online survey containing sociodemographic information and questions related to daily habits, physical activity profile, and musculoskeletal pain before and during the pandemic. Levels of concentration, nervousness, productivity, and visual fatigue were also assessed. The primary outcome was presence of perceived pain before and during the pandemic, dichotomized between those with and without increased pain during the pandemic.
RESULTS:
Perceived pain increased during the pandemic (p < 0.001) and was associated with females (p = 0.023; PR = 1.16; 95% CI = 1.02–1.32), income up to one minimum wage (p = 0.039; PR = 1.20; 95% CI = 1.01–1.42), no physical activity practice (p = 0.006; PR = 1.22; 95% CI = 1.06–1.40), long time in sedentary behavior (p = 0.013; PR = 3.07; 95% CI = 1.27–7.43), and electronic device usage for > 6 hours (p = 0.041; PR = 1.44; 95% CI = 1.02–2.06). Nervousness (p = 0.001) and visual fatigue (p = 0.001) increased, whereas concentration (p = 0.001) and productivity (p = 0.001) reduced during the pandemic.
CONCLUSIONS:
Reduced physical activity practice and increased time in sedentary behavior and electronic device usage during the pandemic were associated with increased musculoskeletal pain in students and professors from higher education institutions. Decreased concentration and productivity and increased nervousness and visual fatigue were also observed during the pandemic.
1Introduction
The novel coronavirus (SARS-CoV-2) causing the COVID-19 disease was first detected at the end of 2019 in Wuhan, China. A pandemic was declared on March 11, 2020, by the World Health Organization [1], and the first case registered in Brazil was observed on February 25, 2020, in São Paulo [2, 3]. Direct or indirect repercussions of the disease were observed on health and will probably impact the population in the long-term [4, 5].
Person-to-person transmission stimulated non-pharmacological preventive measures as the most important preventive resource to cope with the virus [1, 6]. Among these, social distancing was implemented worldwide and effectively reduced the contamination curve [7, 8]. Several establishments (e.g., public places, gyms, businesses, restaurants, schools, colleges, and universities) were temporarily closed or reduced working hours to facilitate implementation and adherence to social distancing [9]. This reduced social interaction and limited physical space, impacting physical activity levels and increasing the time spent in sedentary behaviors, such as using cell phones, computers, and online games [10–12].
In this context, higher education institutions had to continue all activities remotely; some maintained current academic classes, and others performed only extracurricular academic and administrative activities. Thus, telework, which is also considered a home office modality [13], has suddenly been practiced by professors, and students strived to accompany remote activities. These activities may contribute to the emergence of increased screen time, musculoskeletal complaints, fatigue, and other health-related conditions.
Accordingly, this study aimed to assess the consequences of social distancing for the increase in perceived pain of students and professors from higher education institutions. It is hypothesized that students and professors from higher education institutions, who changed work and study routines due to social distancing, would present more physical inactivity and musculoskeletal pain than their usual routine before the COVID-19 pandemic.
2Methods
This cross-sectional study was approved by the research ethics committee of the local university (number 4.101.008) and conducted following the Declaration of Helsinki. Data were collected between June 25 and September 30, 2020. All volunteers were electronically informed about study objectives and signed the consent form.
E-mails and disclosures on social media were used to recruit professors and students aged > 18 years and regularly enrolled in higher education courses throughout the Brazilian territory. Exclusion criterion was the incompleteness of the survey.
The assessment was performed using an online survey developed on Google® Forms platform. Authors LBM and CGS (physiotherapists, doctors, and experts in musculoskeletal physiotherapy) elaborated a survey with 27 questions related to the topic investigated. The first version of this survey was analyzed by a third author (ROC), who suggested some changes. Then, a modified version was sent back to the first and second authors, who adjusted and performed a pilot test with five pre-defined volunteers. The final version of the survey was elaborated after the pilot test and comprised short and self-explanatory objective questions structured in four sub-items: personal data, daily habits, physical activity, and musculoskeletal pain. The survey was sent via e-mail and disclosed on social media.
The online survey was available for participants after accepting to participate in the study. Questions regarding type of institution (private or public), country region, sex, age, profession, family income, type of residence, number of people living in the same residence, COVID-19 symptoms, and previous diagnosis of COVID-19 were included. Items related to daily habits, physical activity, and musculoskeletal complaints were directed to the period before and during social distancing. Daily habits sub-item was composed of questions regarding mean time spent sitting/lying (sedentary behavior) and using electronic devices, social distancing measures, and work/study at home. Physical activity items comprised questions related to practice, level (sedentary or active), and time spent in physical activity. Presence of pain [14], region, and level [15] (the latter using the numerical rating pain scale [0–10]) composed the musculoskeletal pain sub-item. Level of concentration, nervousness, productivity, and visual fatigue was also assessed using a seven-point Likert scale. Primary outcome was perceived pain before and during the pandemic, which was dichotomized between those with and without increased pain during the pandemic.
Sample size was calculated (Open Epi® program version 3.01) using the number of professors (397,893) and students (6,934,244) registered in Brazilian higher education institutions until 2018, according to the Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP). Given an expected frequency of 60%, significance level of 95%, and sampling error of 5%, an optimal number of 1024 participants was estimated. Considering a non-response ratio of 20%, total sample size of 1,229 individuals was obtained.
Statistical analysis was performed using the Statistical Package for the Social Sciences version 20.0 (IBM Corp, USA). Descriptive analysis was performed using mean and standard deviation for continuous variables and absolute and relative frequencies for categorical variables. Associations between increased perceived pain during the pandemic and independent variables were performed using Chi-squared test. Prevalence ratio (PR) and 95% confidence intervals (95% CI) were also calculated in the unadjusted model. Independent variables presenting p≤0.20 in the Chi-squared test were included in the multivariate regression model. Adjusted PR and 95% CI were obtained using Poisson regression model. Wilcoxon test compared continuous variables before and during social distancing. A significance level of 5% (α< 0.05) was adopted.
3Results
One thousand two hundred and sixty-one individuals accessed the online survey, and 1,254 met inclusion criteria. From these, 76.6% (n = 961) were students and 23.4% (n = 293) professors. The greatest number of individuals were from Northeast (80.4%), followed by Southeast (10.8%), Midwest (3.8%), South (3.0%), and North regions (2.1%). Musculoskeletal pain increased during the pandemic (z = 15.112; p < 0.001), with prevalence of 49.7% (n = 623) of respondents. Spine (62.78%) was the most painful body region indicated by participants, followed by lower (21.96%) and upper limbs (24.15%). Table 1 shows absolute and relative frequencies for each independent variable analyzed.
Table 1
Variable | n (%) |
Sex | |
Male | 362 (28.9) |
Female | 892 (71.1) |
Age | |
18 to 29 years | 789 (62.9) |
30 to 39 years | 286 (22.8) |
Over 39 years | 179 (14.3) |
Occupation | |
Student | 961 (76.6) |
Professor | 293 (23.4) |
Institution | |
Public | 799 (63.7) |
Private | 455 (36.3) |
Income | |
Over R$ 5.196 | 448 (35.7) |
Between R$ 3.118 –5.195 | 230 (18.3) |
Between R$ 1.040 –3.117 | 424 (33.8) |
Up to R$ 1.039 | 152 (12.1) |
Obeyed quarantine | |
Yes | 837 (66.7) |
No | 417 (33.3) |
COVID-19 diagnosis | |
Yes | 111 (8.9) |
No | 1143 (91.1) |
Physical activity level | |
Active | 279 (22.2) |
Sedentary | 975 (77.8) |
Physical activity before the pandemic | |
Yes | 873 (69.6) |
No | 381 (30.4) |
Physical activity during the pandemic | |
Yes | 539 (43.0) |
No | 715 (57.0) |
Sedentary behavior before the pandemic | |
Less than 1 hour | 121 (9.6) |
Between 1 –3 hours | 338 (27.0 |
Between > 3 –≤6 hours | 442 (35.2) |
Between > 6 – < 9 hours | 284 (22.6) |
Over 10 hours | 69 (5.5) |
Sedentary behavior during the pandemic | |
Less than 1 hour | 26 (2.1) |
Between 1 –3 hours | 103 (8.2) |
Between > 3 –≤6 hours | 263 (21.0) |
Between > 6 – < 9 hours | 394 (31.4) |
Over 10 hours | 468 (37.3) |
Electronic device usage before the pandemic | |
Up to 3 hours | 401 (32.0) |
Between > 3 –6 hours | 510 (40.7) |
Over 6 hours | 343 (27.4) |
Electronic device usage during the pandemic | |
Up to 3 hours | 68 (5.4) |
Between > 3 –6 hours | 237 (18.9) |
Over 6 hours | 949 (75.7) |
Most participants were female (71.1%) aged between 18 and 29 years (62.9%). A prevalence of 8.9% of individuals was infected by the SARS-CoV-2, and most (57.0%) reported no physical activity practice during the pandemic (Table 1).
Associations were observed between increased perceived pain during the pandemic and females (p = 0.023; PR = 1.16; 95% CI 1.02–1.32), income up to one minimum wage (p = 0.039; PR = 1.20; 95% CI 1.01–1.42), no physical activity practice (p = 0.006; PR = 1.22; 95% CI 1.06–1.40), long time spent in sedentary behavior (p = 0.013; PR = 3.07; 95% CI 1.27–7.43), and electronic device usage for > 6 hours (p = 0.041; PR = 1.44; 95% CI 1.02–2.06) (Table 2).
Table 2
Increased perceived pain during the pandemic | Unadjusted | Adjusted | ||||
No n (%) | Yes n (%) | p-value | PR (95CI%) | p-value | PR (95CI%) | |
Sex | ||||||
Male | 199 (55.0) | 163 (45.0) | 1 | 1 | ||
Female | 432 (48.4) | 460 (51.6) | 0.042 | 1.14 (1.01–1.30) | 0.023 | 1.16 (1.02–1.32) |
Age | ||||||
18 to 29 years | 397 (50.3) | 392 (49.7) | 1 | – | – | |
30 to 39 years | 148 (51.7) | 138 (48.3) | 0.680 | 0.97 (0.84–1.17) | – | – |
Over 39 years | 86 (48.0) | 93 (52.0) | 0.578 | 1.05 (0.89–1.22) | – | – |
Occupation | ||||||
Student | 486 (50.6) | 475 (49.4) | 1 | – | – | |
Professor | 145 (49.5) | 148 (50.5) | 0.744 | 1.02 (0.90–1.16) | – | – |
Income | ||||||
Over R$ 5.196 | 238 (53.1) | 46.9 (210) | 1 | 1 | ||
Between R$ 3.118 –5.195 | 115 (50.0) | 115 (50.0) | 0.437 | 1.07 (0.91–1.25) | 0.371 | 1.07 (0.92–1.26) |
Between R$ 1.040 –3.117 | 212 (50.0) | 212 (50.0) | 0.356 | 1.07 (0.93–1.22) | 0.486 | 1.05 (0.92–1.20) |
Up to R$ 1.039 | 66 (43.4) | 86 (56.6) | 0.031 | 1.21 (1.02–1.43 | 0.039 | 1.20 (1.01–1.42) |
Obeyed quarantine | ||||||
Yes | 415 (49.6) | 422 (50.4) | 1 | – | – | |
No | 216 (51.8) | 201 (48.2) | 0.463 | 0.96 (0.85–1.08) | – | – |
COVID-19 diagnosis | ||||||
Yes | 58 (52.3) | 53 (47.7) | 1 | – | – | |
No | 573 (50.1) | 570 (49.9) | 0.675 | 0.96 (0.78–1.17) | – | – |
Physical activity level | ||||||
Active | 172 (61.6) | 107 (38.4) | 1 | 1 | ||
Sedentary | 459 (47.1) | 516 (52.9) | <0.001 | 1.38 (1.18–1.62) | 0.073 | 1.19 (0.98–1.44) |
Physical activity before the pandemic | ||||||
Yes | 412 (47.2) | 461(52.8) | 1 | 1 | ||
No | 219 (57.5) | 162 (42.5) | 0.001 | 0.80 (0.70–0.92) | <0.001 | 0.74 (0.65–0.84) |
Physical activity during the pandemic | ||||||
Yes | 311 (57.7) | 228 (42.3) | 1 | 1 | ||
No | 320 (44.8) | 395 (55.2) | <0.001 | 1.31 (1.16–1.47) | 0.006 | 1.22 (1.06–1.40) |
Sedentary behavior before the pandemic | ||||||
Less than 1 hour | 58 (47.9) | 63 (52.1) | 1 | – | – | |
Between 1 –3 hours | 173 (51.2) | 165 (48.8) | 0.534 | 0.94 (0.76–1.15) | – | – |
Between > 3 –≤6 hours | 221 (50.0) | 221 (50.0) | 0.684 | 0.96 (0.79–1.17) | – | – |
Between > 6 – < 9 hours | 144 (50.7) | 140 (49.3) | 0.606 | 0.95 (0.77–1.16) | – | – |
Over 10 hours | 35 (50.7) | 34 (49.3) | 0.714 | 0.95 (0.70–1.27) | – | – |
Sedentary behavior during the pandemic | ||||||
Less than 1 hour | 22 (84.6) | 4 (15.4) | 1 | 1 | ||
Between 1 –3 hours | 63 (61.2) | 40 (38.8) | 0.052 | 2.52 (0.99–6.42) | 0.056 | 2.41 (0.98–5.93) |
Between > 3 –≤6 hours | 143 (54.4) | 120(45.6) | 0.019 | 2.97 (1.19–7.38) | 0.033 | 2.61 (1.08–6.30) |
Between > 6 – < 9 hours | 198 (50.3) | 196(49.7) | 0.011 | 3.23 (1.30–8.01) | 0.028 | 2.68 (1.11–6.49) |
Over 10 hours | 205 (43.8) | 263 (56.2) | 0.005 | 3.65 (1.48–9.03) | 0.013 | 3.07 (1.27–7.43) |
Electronic device usage before the pandemic | ||||||
Up to 3 hours | 195 (48.6) | 206 (51.4) | 1 | 1 | ||
Between > 3 –6 hours | 248 (48.6) | 262 (51.4) | 1.00 | 1.00 (0.88–1.14) | 0.090 | 0.89 (0.78–1.02) |
Over 6 hours | 188 (54.8) | 155 (45.2) | 0.095 | 0.88 (0.76–1.02) | <0.001 | 0.75 (0.65–0.88) |
Electronic device usage during the pandemic | ||||||
Up to 3 hours | 45 (66.2) | 23 (33.8) | 1 | 1 | ||
Between > 3 –6 hours | 139 (58.6) | 98 (41.4) | 0.281 | 1.22 (0.85–1.76) | 0.406 | 1.16 (0.81–1.67) |
Over 6 hours | 447 (47.1) | 502 (52.9) | 0.010 | 1.56 (1.11–2.19) | 0.041 | 1.44 (1.02–2.06) |
PR: Prevalence Ratio; CI: Confidence Interval.
The amount of physical activity (z = 17.186; p < 0.05), concentration (z = 21.653; p < 0.05), and productivity (z = 22.367; p < 0.05) were reduced, whereas nervousness (z = 14.958; p < 0.05) and visual fatigue (z = 16.302; p < 0.05) increased during the pandemic (Table 3).
Table 3
Before the pandemic | During the pandemic | ||||||
Variable | n | mean | SD | mean | SD | Z-score | p-value |
Physical activity practice (min/week) | 1254 | 155.03 | 166.28 | 76.43 | 108.14 | 17.186 | 0.001 |
Level of nervousness (1 to 7) | 1254 | 3.64 | 1.55 | 4.66 | 1.76 | 14.958 | 0.001 |
Level of visual fatigue (1 to 7) | 1254 | 3.75 | 1.80 | 5.11 | 1.90 | 16.302 | 0.001 |
Concentration difficulty (1 to 7) | 1254 | 3.18 | 1.66 | 5.12 | 1.83 | 21.653 | 0.001 |
Commitment to productivity (1 to 7) | 1254 | 2.80 | 1.64 | 4.90 | 1.87 | 22.367 | 0.001 |
4Discussion
The present study investigated the consequences of social distancing on the increase in perceived pain of students and professors from higher education institutions. Increased musculoskeletal pain was associated with females, low family income, reduced physical activity practice, and greater time spent in sedentary behavior and using electronic devices. The pandemic also affected productivity, concentration, visual fatigue, nervousness, and time spent practicing physical activity.
The need to implement non-pharmacological interventions to suppress COVID-19 transmission [7] may have impacted physical and mental health of the population [16, 17]. Increased musculoskeletal pain is common in studies investigating the effects of social distancing and isolation [18, 19], and pain may be attributed to incorrect and sustained postures during electronic device usage since this behavior was intensified in the pandemic during work, study, or leisure activities [16]. Home environment was probably not ergonomically adequate to allow work and study for several hours, increasing musculoskeletal complaints, especially in the spine [20]. Although pain in the spine was the greatest complaint, it was not associated with seated posture [21, 22]. This condition, especially chronic, is multifactorial and may be influenced by physical, environmental, and psychosocial factors, which have been strongly affected in this pandemic [23, 24].
Simultaneously, the effects of social restriction also reduced physical activity practice [25–27]. This was probably related to the temporary closing of gyms and sports centers and restricted use of community environments for physical practice. In a multicenter study, Ammar et al. [26] observed a reduced number of physical activity practice, corroborating with findings of the present study since weekly physical activity practice decreased from 155 to 76 minutes. These values are below recommended by the WHO [28] and the American College of Sports Medicine [29] and are associated with increased risk of cardiovascular disease and diabetes mellitus [30].
Participants also increased the time spent in sedentary behavior (i.e., 68.7% of individuals remained seated/lying down for > 6 hours daily), which agrees with Ammar et al. [26], who found a 28.6% increase in sitting time during the pandemic. Studies show that sitting time greater than 6–8 h/day increases mortality risk for several diseases [31], while 3–6 hours of continuous sitting is sufficient to deteriorate vascular function [32].
Inactivity and sedentary behavior are considered risk factors for several diseases, such as cardiovascular [33–35], cancer, diabetes [36, 37], metabolic syndrome [38], depression, and anxiety. For this reason, two pandemics are probably taking place: coronavirus and inactivity; the latter probably persisting after the end of the COVID-19 pandemic, leading to health and economic consequences [39]. Also, reduced time spent in physical activity and increased time in sedentary behavior are associated with increased musculoskeletal pain. A study conducted by Steffandottir and Gudmundsdottir [40] revealed that individuals with extended periods of sedentary behavior are more likely to develop musculoskeletal pain. In a prospective study, Nilsen et al. [41] observed that weekly physical activity was inversely associated with risk of chronic low back and neck/shoulder pain, especially if performed for at least 1 hour per week.
Musculoskeletal pain was greater in females, corroborating with findings of other studies [42–44]. Restrictive measures implemented to mitigate the risk of infection may expose females to a “double or triple shift” (i.e., dividing themselves between children, domestic chores, and work) and lead to greater exposure to risk factors, such as movement repetition, increased physical load, non-ergonomic postures, and short physical recovery time. Moreover, anatomo-physiological characteristics (e.g., short stature, high body mass index, different musculoskeletal composition, and joint fragility) may cause mental and physical overload and increase pain [45–48].
Musculoskeletal pain was also high in individuals with low family income. High socioeconomic levels are associated with better lifestyle habits, emotional stability, and greater access to healthy habits, reducing pain. Another hypothesis would be related to exposure to precarious and unhealthy work environments, increasing the risk of developing body pain [46, 47].
Severe mental health problems, high prevalence of anxiety, depressive symptoms, and poor sleep quality were also observed during the COVID-19 pandemic, probably due to the constant concern of becoming infected [49].
Changes in study and work routines brought new challenges to professors and students. Majumdar et al. [16] conducted an online survey to investigate the impact of lockdown on mental and physical health, depressive status, sleep quality, somatic complaints, and digital use in individuals from the corporate sector and university undergraduate or post-graduate students. They found sleep disturbance and depressive symptoms were present during the lockdown. Although home office may lead to several benefits to the worker (e.g., flexible working hours, increased productivity, creation of own rules, and family environment) [50–52], changes during the pandemic occurred quickly and without prior planning or training. Thus, students and professors had to completely change behaviors, despite feelings of fear, insecurity, and concern.
Aspects related to interconnection between work and family domains, logistics to separate personal and professional schedules [53], and inadequate environment [20] may impair health while working and studying at home. Kaushik and Guleria [52] emphasized that unpredictable interruptions, detachment from colleagues and bosses, lack of community feeling and attachment to the company, reduced productivity, and need for commitment, dedication, and self-motivation were negative aspects of home office. Furthermore, increased visual fatigue caused by extensive exposure to screens may lead to digital eye strain [54]. Therefore, participants of this study presented reduced productivity, increased nervousness, and difficulty concentrating.
Strengths of the study are related to the fact that it was conducted in a period of social distancing measures, facilitating the analysis of factors generating musculoskeletal complaints during extended sedentary activity. Despite this, it is prudent to analyze some limitations, including the cross-sectional design that did not infer reverse causality. However, it is challenging to conduct longitudinal studies due to the COVID-19 pandemic. Memory bias can also be pointed out since some variables were analyzed retrospectively. Nevertheless, this was minimized because questions were related to short-term memory and an unusual condition. Results should also not be extrapolated to other populations since data was restricted to young university students and professors. We recommend future studies with different populations and analysis of specific pain regions to better characterize the complaints generated during the pandemic.
5Conclusions
Musculoskeletal pain increased significantly during social distancing, mainly in individuals with low income and females. This condition was associated with reduced physical activity practice, increased sedentary behavior, and greater use of electronic devices. Moreover, restrictive measures reduced concentration and productivity and increased nervousness and visual fatigue of professors and students from higher education institutions.
Acknowledgments
The authors thank Probatus Academic Services for providing scientific language translation, revision, and editing.
Conflict of interest
None to report.
References
[1] | World Health Organization. Available from: https://www.who.int/. Accessed May 30 2020. |
[2] | Croda JHR , Garcia LP . Immediate Health Surveillance Response to COVID-19 Epidemic, Epidemiologia e servicos de saúde: revista do Sistema Único de Saúde do Brasil (2020) ;29: (1):e2020002. |
[3] | Rodriguez-Morales AJ , Gallego V , Escalera-Antezana JP , Méndez CA , Zambrano LI , Franco-Paredes C , et al. COVID-19 in Latin America: The implications of the first confirmed case in Brazil. Travel Medicine and Infectious Disease. 2020;35. |
[4] | Rundle AG , Park Y , Herbstman JB , Kinsey EW , Wang YC . COVID-19–Related School Closings and Risk of Weight Gain Among Children, Obesity. (2020) ;28: (6):1008–9. |
[5] | Brooks SK , Webster RK , Smith LE , Woodland L , Wessely S , Greenberg N , et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence, The Lancet (2020) ;395: :912–20. |
[6] | Heymann DL , Shindo N . COVID-19: what is next for public health? The Lancet. (2020) ;395: :542–5. |
[7] | Ferguson NM , Laydon D , Nedjati-Gilani G , Imai N , Ainslie K , Baguelin M , et al.Report Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, Imperial College COVID Response Team 9: :2020. |
[8] | Garcia LP , Duarte E . Nonpharmaceutical interventions for tackling the COVID-19 epidemic in Brazil, Epidemiologia e Serviços saúde: Revista do Sistema Único Saúde do Brasil (2020) ;29: (2):e2020222. |
[9] | DECRETO N 59. 283 DE 16 DE MARÇO DE laquo Catálogo de Legislação Municipal, Available from: https://legislacao.prefeitura.sgov.br/leis/decreto-59283-de-16-de-marco-de-2020.Accessed 30 May 2020 2020 |
[10] | Owen N , Healy GN , Matthews CE , Dunstan DW . Too much sitting: The population health science of sedentary behavior, Exerc Sport Sci Rev (2010) ;38: (3):105–13. |
[11] | Proper KI , Singh AS , Van Mechelen W , Chinapaw MJM . Sedentary behaviors and health outcomes among adults: A systematic review of prospective studies, American Journal of Preventive Medicine (2011) ;40: :174–82. |
[12] | Aktug ZB , Iri R , Aktuğ Demir N , . COVID-19 immune system and exercise, J Hum Sci (2020) ;17: (2):513–20. |
[13] | Raišiene AG , Rapuano V , Varkulevičiūte K , Stachová K . Working from Home— Who Is Happy? A Survey of Lithuania’s Employees during the COVID-19 Quarantine Period., Sustainability (2020) ;12: (13):5332. |
[14] | Raja SN , Carr DB , Cohen M , Finnerup NB , Flor H , Gibson S , et al., The revised International Association for the Study of Pain definition of pain: concepts, challenges, and compromises. Pain (2020) ;161: (9):1976–82 |
[15] | Ferreira-Valente MA , Pais-Ribeiro JL , Jensen MP . Validity of four pain intensity rating scales, Pain® (2011) ;152: (10):2399–404. |
[16] | Majumdar P , Biswas A , Sahu S . COVID-19 pandemic and lockdown: cause of sleep disruption, depression, somatic pain, and increased screen exposure of office workers and students of India, Chronobiol Int (2020) ;00: (8):1–10. |
[17] | Wang C , Pan R , Wan X , Tan Y , Xu L , Ho CS , et al . Immediate Psychological Responses and Associated Factors during the Initial Stage of the Coronavirus Disease (COVID-19) Epidemic among the General Population in China, Int J Environ Res Public Heal (2020) ;17: :1729. |
[18] | Toprak Celenay S , Karaaslan Y , Mete O , Ozer Kaya D . Coronaphobia, musculoskeletal pain, and sleep quality in stay-at home and continued-working persons during the 3-month Covid-19 pandemic lockdown in Turkey, Chronobiol Int (2020) ;00: (00):1–8. |
[19] | Sagát P , Bartík P , González PP , Tohanean DI , Knjaz D . Impact of COVID-19quarantine on low back pain intensity, prevalence, and associated risk factors among adult citizens residing in riyadh (Saudi Arabia): A cross-sectional study, Int J Environ Res Public Health (2020) ;17: :1–13. |
[20] | Moretti A , Menna F , Aulicino M , Paoletta M , Liguori S , Iolascon G . Characterization of home working population during covid-19 emergency: A cross-sectional analysis, Int J Environ Res Public Health (2020) ;17: (17):1–13. |
[21] | Bontrup C , Taylor WR , Fliesser M , Visscher R , Green T , Wippert PM , et al. Low back pain and its relationship with sitting behaviour among sedentary office workers. Applied Ergonomics. 2019;81. |
[22] | Sihawong R , Sitthipornvorakul E , Paksaichol A , Janwantanakul P . Predictors for chronic neck and low back pain in office workers: A 1-year prospective cohort study, J Occup Health (2016) ;58: (1):16–24. |
[23] | Maher C , Underwood M , Buchbinder R . Non-specific low back pain, Lancet (2017) ;389: :736–47. |
[24] | O’Sullivan P . Diagnosis and classification of chronic low back pain disorders: maladaptive movement and motor control impairments as underlying mechanism, Manual Therapy (2005) ;10: (4):242–55. |
[25] | Qin F , Song Y , Nassis GP , Zhao L , Dong Y , Zhao C , et al. Physical activity, screen time, and emotional well-being during the novel coronavirus outbreak in China, Int J Environ Res Public Health (2020) ;17: :1–16. |
[26] | Ammar A , Brach M , Trabelsi K , Chtourou H , Boukhris O , Masmoudi L , et al. Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey, Nutrients (2020) ;12: (6):1583. |
[27] | Gallo LA , Gallo TF , Young SL , Moritz KM , Akison LK . The impact of isolation measures due to COVID-19 on energy intake and physical activity levels in Australian university students, Nutrients (2020) ;12: (6):1–14. |
[28] | Bull FC , Al-Ansari SS , Biddle S , Borodulin K , Buman MP , Cardon G , et al. World Health Organization guidelines on physical activity and sedentary behavior, British Journal of Sports Medicine (2020) ;54: :1451–62. |
[29] | Riebe D , Ehrman J , Liguori G , Magal M ACSM’s Guidelines for Exercise Testing and Pescription. 10th ed. Philadelphia: Wolters Klumer; (2018) . |
[30] | Wahid A , Manek N , Nichols M , Kelly P , Foster C , Webster P , et al. Quantifying the Association Between Physical Activity and Cardiovascular Disease and Diabetes: A Systematic Review and Meta-Analysis, J Am Heart Assoc (2016) ;5: (9). |
[31] | Patterson R , McNamara E , Tainio M , de Sá TH , Smith AD , Sharp SJ , et al. Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis, Eur J Epidemiol (2018) ;33: (9):811–29. |
[32] | Carter S , Hartman Y , Holder S , Thijssen DH , Hopkins ND . Sedentary Behavior and Cardiovascular Disease Risk, Exerc Sport Sci Rev (2017) ;45: (2):80–6. |
[33] | Lippi G , Sanchis-Gomar F . An Estimation of the Worldwide Epidemiologic Burden of Physical Inactivity-Related Ischemic Heart Disease, Cardiovasc Drugs Ther (2020) ;34: (1):133–7. |
[34] | Li J , Siegrist J . Physical Activity and Risk of Cardiovascular Disease— A Meta-Analysis of Prospective Cohort Studies, Int J Environ Res Public Health (2012) ;9: (2):391–407. |
[35] | Wijndaele K , Brage S , Besson H , Khaw K-T , Sharp SJ , Luben R , et al. Television viewing time independently predicts all-cause and cardiovascular mortality: the EPIC Norfolk Study, Int J Epidemiol (2011) ;40: (1):150–9. |
[36] | Hamasaki H . Daily physical activity and type 2 diabetes: A review, World J Diabetes (2016) ;7: (12):243. |
[37] | Sanchis-Gomar F , Lucia A , Yvert T , Ruiz-Casado A , Pareja-Galeano H , Santos-Lozano A , et al. Physical inactivity and low fitness deserve more attention to alter cancer risk and prognosis, Cancer Prev Res (2015) ;8: (2):105–10. |
[38] | Ford ES , Kohl HW , Mokdad AH , Ajani UA . Sedentary behavior, physical activity, and the metabolic syndrome among U, S. adults. Obes Res (2005) ;13: (3):608–14. |
[39] | Hall G , Laddu DR , Phillips SA , Lavie CJ , Arena R . A tale of two pandemics: How will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another? Prog Cardiovasc Dis. 2020. |
[40] | Stefansdottir R , Gudmundsdottir SL , Sedentary behavior and musculoskeletal pain: a five-year longitudinal Icelandic study. Public Health (2017) ;149: :71–3. |
[41] | Nilsen TIL , Holtermann A , Mork PJ . Physical exercise, body mass index, and risk of chronic pain in the low back and neck/shoulders: Longitudinal data from the nord-trøndelag health study, Am J Epidemiol (2011) ;174: (3):267–73. |
[42] | Cimas M , Ayala A , Sanz B , Agulló-Tomás MS , Escobar A , Forjaz MJ . Chronic musculoskeletal pain in European older adults: Cross-national and gender differences, Eur J Pain (2018) ;22: (2):333–45. |
[43] | Fillingim RB , King CD , Ribeiro-Dasilva MC , Rahim-Williams B , Riley JL , Sex, Gender, and Pain: A Review of Recent Clinical and Experimental Findings. J Pain (2009) ;10: (5):447–85 . |
[44] | Reitsma M , Tranmer JE , Buchanan DM , VanDenKerkhof EG . The epidemiology of chronic pain in Canadian men and women between and longitudinal results of the National Population Health Survey, Pain Res Manag (2012) ;17: (3):166–72. |
[45] | Harris ML , Loxton D , Sibbritt DW , Byles JE . The influence of perceived stress on the onset of arthritis in women: Findings from the australian longitudinal study on women’s health, Ann Behav Med (2013) ;46: (1):9–18. |
[46] | Chun MY , Cho B-J , Yoo SH , Oh B , Kang J-S , Yeon C . Association between sleep duration and musculoskeletal pain, Medicine (Baltimore) (2018) ;97: (50):e13656. |
[47] | Bingefors K , Isacson D . Epidemiology, co-morbidity, and impact on health-related quality of life of self-reported headache and musculoskeletal pain - A gender perspective, Eur J Pain (2004) ;8: (5):435–50. |
[48] | del Campo MT , Romo PE , de la Hoz RE , Villamor JM , Mahíllo-Fernández I . Anxiety and depression predict musculoskeletal disorders in health care workers, Arch Environ Occup Heal (2017) ;72: (1):39–44. |
[49] | Huang Y , Zhao N . Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey, Psychiatry Res (2020) ;288: :112954. |
[50] | De Macêdo TAM , Cabral ELDS , Silva Castro WR , De Souza Junior CC , Da Costa Junior JF , Pedrosa FM , et al. Ergonomics and telework: A systematic review, Work (2020) ;66: (4):777–88. |
[51] | Shepherd-Banigan M , Bell JF , Basu A , Booth-LaForce C , Harris . JR Workplace Stress and Working from Home Influence Depressive Symptoms Among Employed Women with Young Children, Int J Behav Med (2016) ;23: (1):102–11. |
[52] | Kaushik M , Guleria N . The Impact of Pandemic COVID -19 in Workplace, Eur J Bus Manag (2020) ;12: (15):9–18. |
[53] | Lopez-Leon S , Forero Dia , Ruiz-Diáz P . Recommendations for working from home during the COVID-19 pandemic (and beyond), Work (2020) ;66: (2):371–5. |
[54] | Bahkir F , Grandee S . Impact of the COVID-19 lockdown on digital device-related ocular health, Indian J Ophthalmol (2020) ;68: (11):2378. |