• Users Online: 190
  • Print this page
  • Email this page


 
 
Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 53  |  Issue : 3  |  Page : 99-103

Lifestyle behaviors and their influence on work-related musculoskeletal discomfort: A web-based survey during coronavirus disease 2019 pandemic


1 Department of Occupational Therapy and Ergonomics, Body Dynamics, Bengaluru, Karnataka, India
2 Department of Physiotherapy, SDM College of Physiotherapy, SDM University, Dharwad, Karnataka, India

Date of Submission31-Jan-2021
Date of Acceptance04-Sep-2021
Date of Web Publication12-Oct-2021

Correspondence Address:
Bharati Jajoo
Body Dynamics, 129, Prestige Ozone Whitefield, Main Road, Bengaluru - 560 066, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijoth.ijoth_30_21

Rights and Permissions
  Abstract 


Background: Healthy lifestyle choices have a great impact on individuals' health. Coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented work from home (WFH) situation. This recent trend has led to computer users in WFH having limited access to health-care options, ergonomic workstations and social participation like a visit to a gym or walking in the park, or any other meaningful engagements which people adopt to improve their health and well-being. Objectives: This study aimed to identify the health and lifestyle behaviors and work-related discomfort reported by employees in WFH situations due to COVID-19 lockdown through a self-reported survey and to study if there is an association between reported discomfort and lifestyle behaviors. Study Design: This was a cross-sectional survey. Methods: A web-based, E-mail, cross-sectional survey was designed having three sections: demographic characteristics; work-related discomfort and its rating on the Visual Analog Scale (VAS); and scoring on the Simple Lifestyle Indicator Questionnaire (SLIQ). Completed questionnaires and the responses from employees in WFH were analyzed using SPSS version 20. Results: Demographic data showed that the majority of the respondents were male (n = 190 [78%]). One hundred and ninety-five (80%) respondents reported symptoms of musculoskeletal discomfort. The SLIQ score showed 1 (1%) of the studied population in the healthy category, 70 (29%) in the intermediate healthy category, and 173 (70%) in the unhealthy category. The Spearman's rank correlation coefficient was calculated for the individual scores in each category with the VAS score. Exercise and VAS score showed a significant negative correlation (ρ = −0.146; P = 0.001; 95% confidence interval [CI]: −0.261 [LL], −0.005 [UL]) while the VAS score with smoking (ρ = 0.362; P = 0.000; 95% CI: 0.227 LL, 0.466 UL) and stress level (ρ = −0.140; P = 0.029; 95% CI: −0.286 LL, −0.003 UL) showed a significant positive correlation. Conclusion: WFH has led to an overall reduction of participation in healthy lifestyle behaviors, with a substantial percentage of people classified in the unhealthy category. Survey also elicits a significant association where higher levels of exercise in people correlated with a lower reported work-related musculoskeletal discomfort. Similarly, smoking and higher stress levels correlated positively with reported musculoskeletal discomfort symptoms. Thus, awareness measures to promote healthy lifestyle behaviors and stress management should be incorporated among computer users working from home settings.

Keywords: Coronavirus Disease 2019, Exercise, Lifestyle Behaviors, Work from Home, Work-Related Musculoskeletal Discomfort


How to cite this article:
Jajoo B, Bhatbolan S, Bhatbolan S. Lifestyle behaviors and their influence on work-related musculoskeletal discomfort: A web-based survey during coronavirus disease 2019 pandemic. Indian J Occup Ther 2021;53:99-103

How to cite this URL:
Jajoo B, Bhatbolan S, Bhatbolan S. Lifestyle behaviors and their influence on work-related musculoskeletal discomfort: A web-based survey during coronavirus disease 2019 pandemic. Indian J Occup Ther [serial online] 2021 [cited 2021 Dec 2];53:99-103. Available from: http://www.ijotonweb.org/text.asp?2021/53/3/99/328128




  Introduction Top


Coronavirus disease 2019 (COVID-19) was identified as a highly infectious strain, and the World Health Organization (WHO) declared it as a health emergency in February 2020.[1] Worldwide lockdown necessitated work from home (WFH) scenario and led to greater likelihood of increase in the work hours using computers and adding to sedentary behavior.[2] Lockdown and quarantine measures contained everyone at home by shutting down business schools, socializing places, and all the institutions except the health-care delivery and emergency services.[1] These swift measures had a lasting impact on lifestyle behaviors which have a significant stake in deciding an individual's emotional and physical health. According to the Institute for Health Metrics and Evaluation, behavioral risks mainly comprise bad dietary habits, smoking, malnutrition, alcohol use, and low physical activity.[3] The WHO statement on healthy people, 2020, states “The non-communicable diseases have a strong link with unhealthy lifestyle behaviour, and adaptation of few healthy lifestyle behaviours can impact the expression of certain diseases in an individual and an individual can reverse a diseased health condition by making correct health choices.” The behavioral factors still provide the highest contribution over metabolic and environmental/occupational risk factors.[4]

Global reports suggest that greater and frequent consumption of comfort foods, fast foods, and snacks known to be high in sugar, salt, and fat could be associated with home quarantine and boredom.[5] A consistent body of literature identifies the negative emotional experience of self-isolation leading to dysfunctional eating behaviors where people look for physiological gratification associated with food consumption even overriding the hunger and satiety signal.[6] A recent review highlighted lifestyle behaviors such as sleep deprivation, reduced habit of physical exercise, altered dietary habits, and stress as important findings among Indian population during the COVID crisis and nationwide lockdown.[7]

Further, home quarantine, ill-designed, makeshift workstations may have a substantial impact on well-being and may be contributory in development of work-related musculoskeletal disorders.[8],[9]

Thus, it is significant to recognize various health and lifestyle behaviors and their influence on reported work-related discomfort among employees in WFH situations during COVID-19 lockdown. This study was conducted as a web-based, cross-sectional survey to study the self-reported lifestyle behaviors and also associated discomfort in employees in WFH situation.


  Methods Top


This survey is a second part of the research work done to identify the work-related discomfort in computer users working in WFH situations due to COVID-19 lockdown. The participants were identified through a web-based survey in the first part of the study through a questionnaire designed using Google Forms, which consisted of demographic characteristics and questions based on the Nordic Musculoskeletal Questionnaire to identify individuals with musculoskeletal discomfort complaints. Individuals using computers for at least 6 h/day with an age above 18 years and who were in WFH due to COVID-19 lockdown, were studied. This study was conducted in agreement with the national and international regulations, and the Declaration of Helsinki (2000). Full information about the study requirements was provided to the participants, and they required accepting the data sharing and privacy policy before participating in the study.

The individuals who reported the discomfort in the first part of the survey were recontacted and a Google Forms-based survey questionnaire was shared, with a request to fill in the questionnaire.

A specific questionnaire was designed to understand the lifestyle habits of the VDU/computer/laptop users by including questions from the Simple Lifestyle Indicator Questionnaire (SLIQ)[10] which is a short, simple-to-use instrument for measuring lifestyle behavior. It has five lifestyle risk factors and gives a score to every segment, and additionally a general lifestyle score. The scale demonstrates good-to-excellent test–retest reliability (r = 0.63–0.97) and good internal consistency measured by Cronbach's α = 0.58, 0.6 for both diet and activity questions.[10] The SLIQ is a short and self-administered well-being estimation scale and consists of five segments – diet, exercise, alcohol intake, smoking, and stress. Every segment has scores of 0, 1, or 2 which are summed to give a SLIQ score from 0 to 10 (0 = very unhealthy, 10 = very healthy). A person is viewed as “unhealthy” if they have a SLIQ score of around 0–4, “intermediate” if the SLIQ score is 5–7, and “healthy” if they have a score of 8–10.[10]

The Visual Analog Scale (VAS) and structured questionnaire of pain frequency were used to assess the pain/discomfort.[11] Further, Nordic questionnaire was used for the identification of pain/discomfort in various regions such as neck, shoulders, back, elbow, wrists/hands, lower back, hips/thighs, knees, legs, and ankles/feet. The Google Forms consisted of three sections: the first section enquired the demographic details, the second section had questions regarding musculoskeletal discomfort, and the third section enquired on health behaviors using SLIQ. Researcher contact details were shared to solve queries if any. This survey was conducted from October 05, 2020, to October 30, 2020. The questionnaires were shared using Google Forms link on Gmail. As this was the second phase of the study, the inclusion criteria were the subject identified with work-related discomfort in WFH situation in the first phase of the study.

Direct link to the Google Forms was shared with the participants, and they completed the questionnaire directly connected to the Google platform. Participants' personal information, including names, was anonymized using Google Forms features to create anonymous Google Forms and to maintain and protect confidentiality. Web survey does not allow tracing in any way sensitive personal data and maintains the anonymity. Once completed, each questionnaire was transmitted to the Google platform and the final database was downloaded as a Microsoft Excel sheet.

The completed questionnaires were analyzed using IBM SPSS Statistics for windows, version 20.0 Armonk, NY: IBM Corp. for descriptive statistics and Spearman's rho correlational statistics to see the correlation of SLIQ raw score in each category with the VAS score for discomfort. The confidence interval was set at 95%.


  Results Top


A total of 244 (N = 244) participants identified and contacted from the first phase of the studied and the completed questionnaires were considered for the analysis. Out of 244 respondents, 54 (22%) were female and 190 (78%) were male, with age distribution 22–45 years and mean age being mean ± standard deviation (SD): 35 ± 4 years. The prevalence of pain and discomfort in the respondents was found to be 83%. The frequent areas of pain and discomfort reported were hand, arm, shoulder, neck, low back, and upper back. Out of the respondents who reported symptoms of pain and discomfort, percentages were the lower back 122 (50%), neck 115 (47%), leg 88 (36%), shoulder 81 (33%), upper back 49 (20%) and hands 41 (17%), forearm 37 (15%), and fingers 37 (15%).

The general characteristics and anthropometrics of the participants are reported in [Table 1].
Table 1: Demographic Characteristics

Click here to view


[Table 1] reports the mean age ± SD of the participants as: 35 ± 4 years, with the mean height ± SD 169 ± 8.48 cm. The mean weight ± SD was 72 ± 13.49 kg. The gender-wise distribution of population shows that the larger proportion of the studied population was male 190 (78%) while only 54 (22%) were female. The distribution of the studied population according to body mass index (BMI) showed that only 100 (41%) belonged to normal BMI category, 106 (43%) in overweight category, 31 (13%) belonged to obese category, while 7 (3%) belonged to underweight category.

The result of SLIQ score analysis showed that the percentage of the participants under unhealthy category was 172 (70%) while 70 (29%) obtained intermediate healthy lifestyle scores and only 1 (1%) of the studied population reported healthy lifestyle score on SLIQ [Figure 1].
Figure 1: Distribution Based on the Simple Lifestyle Indicator Questionnaire

Click here to view


The Spearman rank correlation test between VAS score with the raw scores of five categories, namely diet, exercise, alcohol, smoking, and life stress, was performed. VAS score correlation with diet score (ρ = −0.018; P = 0.783; 95% confidence interval [CI]: −0.138 [LL], 0.107 [UL]) was not found significant. Alcohol consumption (ρ = −0.088; P = 0.171; 95% CI: −0.193 LL, 0.057 UL) also showed insignificant correlation with VAS score. However, exercise and VAS score showed a significant negative correlation (ρ = −0.146; P = 0.001; 95% CI: −0.261 LL, −0.005 UL), implicating that individual engaged in exercise scored less on pain and discomfort rating. Smoking and VAS score showed a highly significant positive correlation (ρ = 0.362; P = 0.000; 95% CI: 0.227 LL, 0.466 UL), implicating a higher score on VAS with increased smoking. Stress showed significant positive correlation with the VAS Score (ρ = −0.140; P = 0.029; 95% CI: −0.286 LL, −0.003 UL) [Table 2].
Table 2: Spearman's Rho Correlation Coefficient Values between the Visual Analog Scale Score and Simple Lifestyle Indicator Questionnaire Categories

Click here to view



  Discussion Top


Lifestyle orientations and behavior encompass a broad range of tangible and intangible factors and have a lasting impact on health parameters, personality, and the way an individual functions. While healthy behaviors are generally rewarding, a rapid unexpected negative change in lifestyle is often counterproductive and may lead to assuming routine unhealthy conduct of oneself and its undesirable consequences.

The present study aimed at understanding the self-reported lifestyle behaviors of computer-users working from home during the pandemic lockdown. A greater number of participants in the study were in intermediate healthy to unhealthy category and only a meager 1 (1%) reporting healthy behaviors. Chabbra et al.[10] in their prepandemic survey on 207 medical professionals reported 131 (63.7%) in unhealthy category, 58 (28%) in intermediate healthy category, and 18 (8.7%) healthy category. Largely, unhealthy eating and binging, lack of awareness on healthy lifestyle, and exercise opportunities could be few of the reasons during imposed lockdown period for higher reported unhealthy category scores.[7]

Musculoskeletal pain and discomfort are frequently reported among computer users, and several factors may be considered inclusive. A study by Micheletti et al. explained an association of exercises with reduced risk of musculoskeletal pain while smoking was associated with higher reports of pain. In our study, we found similar associations among WFH computer users. While pain/discomfort was reported higher in smokers, respondents who practiced exercise at least 30 min/day reported less pain.[12] Similar findings were published in a study by Bohman et al. who concluded that practicing exercise was associated with lower pain scores and healthy lifestyle behavior reduces the risk of chronic low back pain. They recommended exercise to improve prognosis.[13] Exercises and physical activity help regulate pain and alter generalized pain perception and overall intensity and are therefore a useful strategy in promoting well-being. A change in central sensitization is also reported in response to physical exercise among people with chronic pain.[14] Furthermore, consistent sedentary lifestyle due to WFH could be an element for increased musculoskeletal pain/discomfort responses, and a study by Bontrup et al. also reinforces similar finding.[15]

Smoking is counterproductive to one's health and is known to reduce bone density and also reduction of blood supply to the vertebrae, which makes them prone to injury as well as pain. The mechanism behind this is formation of carboxyhemoglobin leading to decreased tissue oxygen perfusion, vasoconstriction, arthrosclerosis, and hematological impairment. Nicotine increases the concentration of calcium ions which results in muscle contractions, thus causing fatigue and pain.[16],[17]

Altered work structure, longer working hours, managing domestic chores simultaneously, and nonwork-related psychosocial stress could be very demanding, and it has shown a significant impact on pain reports. Recognizing stressors early and promptly modifying them may have a lasting impact on prevention of chronic pain conditions and is an area that should be explored further.[18]

Adapting to WFH and accepting healthy behaviors, though is desirable a rapid sudden change in the lifestyle, is surely challenging. Inaccessibility to routine practices during lockdown has limited an individual's overall activity levels, and an adaptation to the new situation is merited.[19] Measures to inculcate active healthy lifestyle behaviors and physical activity of any form and intensity[3] could be vital among computer users working from home. Amid uncertainty associated with the pandemic and WFH viewed as the new normal, lifestyle behaviors are unquestionably central in their role in maintaining well-being.

Limitation and Future Recommendations

The study had a larger number of male respondents and thus is mainly representative of male population. Convenient sampling method was used for data collection, and the statistics may not be truly representative of all the computer professional populations and may be investigated in future with more population extensive studies with similar representation of both the gender.


  Conclusion Top


The present study collated self-reported information based on an online survey. We found a greater percentage of respondents in “unhealthy” category with reduced participation in healthy lifestyle behaviors. Participants who engaged in any form of physical activity reported fewer complaints of musculoskeletal pain/discomfort, while smoking, sedentary lifestyle, and stress among respondents were associated with greater likelihood of pain/discomfort reports while working from home. Creating awareness and opportunities for adopting positive lifestyle changes could be an approach going ahead.

Acknowledgment

We thank all participants who volunteered for the survey and shared their responses through the online platform.

Financial Support and Sponsorship

The study is self-funded and was carried out using Google platform.

Conflicts of Interest

There are no conflicts of interest.



 
  References Top

1.
Maugeri G, Castrogiovanni P, Battaglia G, Pippi R, D'Agata V, Palma A, et al. The impact of physical activity on psychological health during COVID-19 pandemic in Italy. Heliyon 2020;6:e04315.  Back to cited text no. 1
    
2.
Mitta S. 'Work from Home has been 'Successful' during COVID-19 Lockdown. What Next?' Economic Times; 2020 April 30. Available from: https://economictimes.indiatimes.com/magazines/panache/work-from-home-has-been-successful-during-covid19lockdownwhatnext/articleshow/75470580.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst. [Last accessed on 2021 Jan 30].  Back to cited text no. 2
    
3.
Shaikh R, Khan J. Clustering of lifestyle risk factors among adult population in India: A cross-sectional analysis from 2005 to 2016. PLoS One 2021;16:e0244559.  Back to cited text no. 3
    
4.
Healthy People 2020. Washington, DC: U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Available from: https://www.healthypeople.gov/sites/default/files/HP2020_brochure_with_LHI_508_FNL.pdf. [Last accessed on 2021 Jan 30].  Back to cited text no. 4
    
5.
US Department of Health and Human Services and US Department of Agriculture. Shifts Needed to Align with Healthy Eating Patterns – A Closer Look at Current Intakes and Recommended Shifts. Available from: https://health.gov/our-work/food-nutrition/previous-dietary-guidelines/2015. [Last accessed on 2021 Jan 04].  Back to cited text no. 5
    
6.
Briguglio M, Vitale JA, Galentino R, Banfi G, Zanaboni Dina C, Bona A, et al. Healthy Eating, Physical Activity, and Sleep Hygiene (HEPAS) as the winning triad for sustaining physical and mental health in patients at risk for or with neuropsychiatric disorders: Considerations for clinical practice. Neuropsychiatr Dis Treat 2020;16:55-70.  Back to cited text no. 6
    
7.
Rawat D, Dixit V, Gulati S, Gulati S, Gulati A. Impact of COVID-19 outbreak on lifestyle behaviour: A review of studies published in India. Diabetes Metab Syndr 2021;15:331-336.  Back to cited text no. 7
    
8.
9.
James C, James D, Nie V, Schumacher T, Guest M, Tessier J, et al. Musculoskeletal discomfort and use of computers in the university environment. Appl Ergon 2018;69:128-135.  Back to cited text no. 9
    
10.
Chhabra S, Bhat N, Sultane P, Sinha A, Joshi R, Sharma A, et al. Assessment of lifestyle among medical and dental practitioners of Udaipur, Rajasthan, India. Int J Oral Care Res 2017;5:42-46.  Back to cited text no. 10
    
11.
Shrivastava SR, Bobhate PS. Computer related health problems among software professionals in Mumbai: A cross-sectional study. Int J Health Allied Sci 2012; 1:74-8.  Back to cited text no. 11
  [Full text]  
12.
Kirsch Micheletti J, Bláfoss R, Sundstrup E, Bay H, Pastre CM, Andersen LL. Association between lifestyle and musculoskeletal pain: Cross-sectional study among 10,000 adults from the general working population. BMC Musculoskelet Disord 2019;20:609.  Back to cited text no. 12
    
13.
Bohman T, Alfredsson L, Jensen I, Hallqvist J, Vingård E, Skillgate E. Does a healthy lifestyle behaviour influence the prognosis of low back pain among men and women in a general population? A population-based cohort study. BMJ Open 2014;4:e005713.  Back to cited text no. 13
    
14.
Jakobsen MD, Sundstrup E, Brandt M, Andersen LL. Effect of physical exercise on musculoskeletal pain in multiple body regions among healthcare workers: Secondary analysis of a cluster randomized controlled trial. Musculoskelet Sci Pract 2018;34:89-96.  Back to cited text no. 14
    
15.
Bontrupa C, William RT, Fliesserb M, Visscher R, Green T, Wippert PM, et al. Low back pain and its relationship with sitting behaviour among sedentary office workers. Appl Ergon 2009;81:102894.  Back to cited text no. 15
    
16.
Korhonen T, Ketola R, Toivonen R, Luukkonen R, Häkkänen M, Viikari-Juntura E. Work related and individual predictors for incident neck pain among office employees working with video display units. Occup Environ Med 2003;60:475-482.  Back to cited text no. 16
    
17.
D' Silva J, Devadiga S, Dengody PK, Chalathadka M, Bhoj M, Jain V. Smoking and chronic pain. J Health Res Rev 2014;1:34-39.  Back to cited text no. 17
    
18.
Buscemi V, Chang WJ, Liston MB, McAuley JH, Schabrun S. The role of psychosocial stress in the development of chronic musculoskeletal pain disorders: Protocol for a systematic review and meta-analysis. Syst Rev 2017;6:224.  Back to cited text no. 18
    
19.
Di Renzo L, Gualtieri P, Pivari F, Soldati L, Attinà A, Cinelli G, et al. Eating habits and lifestyle changes during COVID-19 lockdown: an Italian survey. J Transl Med 2020;18:229.  Back to cited text no. 19
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
Introduction
Methods
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed744    
    Printed24    
    Emailed0    
    PDF Downloaded4    
    Comments [Add]    

Recommend this journal