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Health Promotion Perspectives. 11(4):393-410. doi: 10.34172/hpp.2021.50

Systematic Review

Association between sedentary behavior and low back pain; A systematic review and meta-analysis

Sadegh Baradaran Mahdavi 1, 2ORCID logo, Roya Riahi 2, 3, *ORCID logo, Babak Vahdatpour 4ORCID logo, Roya Kelishadi 2, *ORCID logo
1Department of Physical Medicine and Rehabilitation, School of Medicine, Student Research Committee, Isfahan University of Medical Sciences, Isfahan, Iran
2Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
3Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
4Department of Physical Medicine and Rehabilitation, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
*Corresponding Authors: Roya Riahi, Email: roya_riahi87@yahoo.com; Roya Kelishadi, Email: kelishadi@med.mui.ac.ir

Abstract

Background: Sedentariness is a substantial risk for many chronic diseases. We aimed to investigate the correlation of sedentary behavior and its indicators with low back pain (LBP) among adults and children.

Methods: Original articles published up to April 28, 2020, using PubMed, Embase, Web of Science and Scopus were evaluated. Odds ratio (OR, 95% CI) was considered the overall effect size for desired associations.

Results: We reviewed 49 English articles with analytical observational study design, of which, 27 studies with cross sectional/survey design were retained in the meta-analysis. Among adults, sedentary lifestyle was a considerable risk factor for LBP (OR=1.24, 1.02-1.5); prolonged sitting time (OR=1.42, 1.09-1.85) and driving time (OR=2.03, 1.22-3.36) were the significant risk factors. Sedentary behavior was associated with LBP in office workers (OR=1.23). Moreover, excess weight (OR=1.35, 1.14-1.59) and smoking (OR=1.28, 1.03-1.60) were associated with LBP. Among children, sedentary lifestyle was a remarkable risk factor for LBP (OR=1.41, 1.24- 1.60); prolonged TV watching (OR=1.23, 1.08-1.41) and computer/mobile using and console playing time (OR=1.63, 1.36-1.95) were significant risk factors for LBP. Consumption of coffee, however, has yield conflicting results to be considered as a risk factor. Moreover, the researches on the correlation between sedentariness and high-intensity LBP are scarce and inconclusive.

Conclusion: Sedentary behavior, whether in work or leisure time, associates with a moderate increase in the risk of LBP in adults, children and adolescents.

Keywords: Sedentary behavior, Screen time, Smoking, Obesity, Coffee, Low back pain

Copyright

© 2021 The Author(s).
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Introduction

Low back pain (LBP) is a paramount public health concern contributing to self-perceived disability and a high economic burden worldwide. 1,2 It is associated with quality of life, 3 long-term sickness, and early retirement as well. 4 It is estimated that about 80% of the population has experienced an episode of LBP in their lives. 5 LBP is more common in females and those between 40-69 years. LBP prevalence increases with aging, and the LBP in childhood associates with the corresponding figure in adulthood. 6 It is shown that musculoskeletal symptoms in the lower back are correlated with other body segments, including the neck, upper back, and shoulders. 7

Sedentary behaviors, on the other hand, are defined as activities with low energy expenditure, performed in rest positions. Sedentary behavior is a predictor of metabolic risk independent of physical inactivity. 8 The health concerns associated with sedentariness are not merely attributable to lack of movement, but also to other simulations such as leisure or work screen time activities, including computer and internet use, TV (television) watching, cell phone use, and playing videogames. 9 Besides, sedentary behavior is related with all-cause mortality concomitant with overweight and obesity, diabetes, and cardiovascular diseases. 10,11 The association of sedentary behavior with musculoskeletal conditions such as LBP has been widely investigated among the population of workers and non-workers. 12

With respect to sitting time, the findings regarding the association between sitting periods and LBP are inconsistent. One study among 704 participants demonstrated no independent association of sitting time in work time or the whole day with LBP. In this study, the body mass index moderated the mentioned association. 13 In addition, the previous reviews did not mention any association between sitting time itself and LBP in leisure time or at work. 14-16 However, a mixture of whole-body vibration, awkward postures, and prolonged sitting increased the risk of LBP. 14 On the other hand, a study among 136 teaching staff reported that physical inactivity was related to LBP; but tobacco use and level of alcohol intake did not have such association with LBP. 17 In a research among 665 blue-collar workers, a longer duration of sitting periods at work was beneficial for LBP. 18 The difference in study design, measurement methods, and participants (or occupational groups) with different sedentary tasks may contribute to inconsistency for the correlation of sitting time and LBP in previous research. 18

Excessive consumption of coffee and cigarette smoking were associated with an elevated likelihood of recurring LBP among 609 Polish residents. In this study hyperlipidemia, type 2 diabetes, and hypertension, were significantly associated with an increased likelihood of chronic LBP as well. 19 Furthermore, in a cross-sectional study among 1221 school adolescents, playing video games (≥2 hours/day) and watching television (≥12 hours/week) were proposed as independent risk factors of LBP. 20

Given the controversies in different articles, in this study, we investigated the relationship of different indicators of sedentary behavior and inactivity (including sitting time, screen time, smoking, consumption of coffee, and excess weight) with LBP, whether in leisure time or work time. We aimed to synthesize the available data to quantify the abovementioned associations to address inconsistencies in previous research. A brief systematic review has been presented in the case of a lack of required data for meta-analysis. In addition, we addressed the mentioned association among children and adolescents with a particular focus.


Methods

Search strategy

We performed a comprehensive search through electronic databases, including PubMed, Embase, Web of Science and Scopus for records published up to April 28, 2020. Based on a PEO framework (Patient/Population/Problem, Exposure, and Outcome) for the eligibility of the research question, we combined the indicators or equivalents of sedentary behavior on the one hand and the equivalents of LBP, on the other hand, for building the search strings. To facilitate the process of screening, we refined the results via the following filters wherever those were available in the search engines: article, journals, English language, full text, human studies. shows the search strings in the abovementioned databases.

Study design

All the analytical observational studies (cross-sectional, case-control, or longitudinal designs) in which the association between sedentary behavior and LBP was investigated, were favorable to be contained in our review. We did not include the experimental studies in which the effects of behavior intervention or experiment on LBP were studied.

Patient/population/problem

Studies with individuals with a specific medical condition such as scoliosis or renal failure who may spend most of their time for sedentary activities were excluded. Age range and type of occupation were not considered as limiting factors, i.e., children and adults with sedentary behavior and LBP were considered to be the subjects of our review.

Exposure

Factors contributing to sedentary behavior, including sitting time, screen time, smoking, consumption of coffee, and body mass index, were considered to be the individuals’ exposures.

Outcome

The onset or recurrence of nonspecific or mechanical LBP measured via different methods was the desired outcome in our study. We excluded the studies in which sciatica or any kind of radicular pain was investigated.

Eligibility criteria and study selection

Two independent reviewers (S.B.M and R.R) screened the relevant records using Endnote software (version 18) after removing duplicates. Thereafter, additional letters, books, review or conference papers, non-English language, and unavailable full texts that were not excluded in refining results in the search engines were excluded. Then, we reviewed the full texts of remained records entirely at the next step. We excluded the articles with topics, study design, or participants irrelevant to our review (). Any disagreement was solved via a discussion for reaching consensus in the whole process.

hpp-11-393-g001
Figure 1. Flowchart of study selection for systematic review and meta-analysis.

Assessment of study quality

Two of the researchers (S.B.M and B.V) performed the study quality assessment independently. The STROBE scale, which consists of 22 items (combined version, 2007), was used for this purpose. 21 One score to each item was given by each reviewer separately, if the criteria were fulfilled. For each paper, a mean STROBE scores ≥16.5, in the range 11 to 16.5 and lower than 11 were considered as high, moderate and low with respect to study quality, respectively. 22 The agreement coefficient between researcher’s scores was more than 0.5.

Statistical analysis

The desired effect size was considered as an odds ratio with 95% confidence interval (OR, 95% CI). Cochran’s Q and inconsistency index (I2) were used to explore the heterogeneity of the included articles. The random-effects model with DerSimonian and Liard method 23 was used when data accumulated from studies, differed in ways that would have impacted on the results (e.g. subjects, exposure), otherwise the fixed effect model with inverse variance method was conducted. Then, the effect of each study on the pooled OR was assessed using sensitivity analysis. We performed subgroup analyses to evaluate the source of heterogeneity based on the following possible variables; type of sedentary behaviors and occupation type. The Begg’s and Egger’s tests were performed to explore publication bias. P value < 0.05 from both tests indicated remarkable publication bias. All analyses were conducted in the Stata, version 11.2 (STATA Corp, College Station, TX, USA).

Review writing style

The items included in the current review have been written according to the checklist and flow diagram of the PRISMA version 2009. 24


Results

Characteristics of included studies

Overall, 3406 records were recognized via a comprehensive search through biomedical sources. With excluding duplicates, books, letters, conference papers, review articles, non-English records, and unavailable full texts, 2255 records remained to be screened via title, abstract or whole text. Finally, we included 49 studies in this review, of which 27 were retained in the meta-analysis for different purposes, 19,20,25-49 18 were excluded due to undesirable effect sizes 1,5,13,50-64 and 4 were excluded due to cohort/case-control designs. 65-68 shows the process of study selection through a schematic flowchart.

With respect to study design of included articles in the review, 8 have been conducted in cohort/prospective design, 51,52,54,56,58,65-67 1 in case-control design, 55 1 in retrospective nested case-control design 68 and the rest in cross-sectional/survey design. Among all studies, 15 were conducted in children or under graduated students. 20,26,29,31,35,38,40,46,47,51,53,55,61,62,66 Only four studies investigated the association of coffee drinking with LBP. 19,32,57,62 Complete information of these 49 articles has been presented in Table 1 and ordered chronologically from old studies to new ones.

Table 1. Summary of included studies in the systematic review
First author;
(year) a
Study design; Study participant Sample size Age
(years)
Sedentary behavior Outcome Assessment of low back pain Main finding Adjustment factors Study quality b Ref.
A. Burdorf
(1993)c
Cross-sectional
Sedentary worker in Rotterdam
27541.5Prolong sedentary posture belong work LBPNordic musculoskeletal questionnaireThe adjusted risk for LBP among carne operator and straddle-carrier was significantly higher than office workers who spent lower sedentary daily work time.Age, Physical activity, whole-body vibration, prolonged sitting, cold and draught in current work, working under severe pressure, and job satisfaction. Moderate50
T. Skov
(1996)
Cross-sectional
Danish salespeople
130639.3 Sedentary work (proportion of
work time)
Chronic LBP Self-reported Nordic questionnaire Driving and sedentary work were related to neck and low back pain. -Moderate25
R. Gunzburg
(1999)c
Cohort
Belgian students
3929Watching TV and playing video game (> 2 hours/day)LBPQuestionnaire More LBP in children who reported playing video games (> 2 hours/day).-High51
P. R. Croft
(1999)c
Cohort
UK general population
450146.5Watching TV more than 3h/dayOverall LBPQuestionnaire There is no significant link between watching TV more than 3 hour with risk of overall LBP.Self-related health and psychological distress High52
C. Thorbjörnsson
(1999) c
Nested case-control
Swedish general population
48426Sedentary work LBPInterview Sedentary work was associated with an excess risk of LBP.AgeHigh68
D. K. Shehab
(2003)c
Cross-sectional
Schoolchildren in Kuwait
40014.4Watching TV time.LBPInterviewback pain is associated with TV watching time.-Moderate53
A. N. Sjolie
(2004)
Cross-sectional
Norwegian adolescents
8814.7television or computer use LBPSelf-reported QuestionnaireLBP was associated with the use of television or computer (>15 hours/week). Gender, distances to school and physical activityHigh26
V. ­Yip
(2004)c
Cohort
Hong Kong nurses
14431.1Sedentary leisure time activity and prolong setting and standing New LBPFace-to-face interview leisure time sedentariness was not associated with new low back pain.-High54
S. Andrusaitis
(2006)c
Cross-sectional
Brazilian truck drivers
41040.2Number of working hours LBPQuestionnaireWorking hours were associated with LBP.Weight, height, number of working hours, ethnic group, age and body mass index.Moderate5
V.M. Mattila
(2007)
Survey;
Finland Military
704019No leisure-time physical activitylifetime LBPVisit to a physician use of smokeless tobacco (OR 1.4) was a risk factor for LBP. AgeHigh27
P. Spyropoulos
(2007)
Cross-sectional
Greek office workers
64844.5Sitting time Point, one year, two year, and lifetime LBPSelf-reported QuestionnaireSitting time (>6 hours) is a significant determinant for lifetime LBP. Gender, age, BMI, Body distance from
computer screen, psychosocial factors
High28
J. Auvinen
(2008)
Cross-sectional
Finland adolescents
599916TV viewing, playing or working on a computer, reading books and other sitting activitiesLBPOne-item questionAmong girls, high amount of sitting associated with consultation or reporting LBP.Smoking, levels of physical activity and BMIHigh29
A. Karahan
(2008)
Cross-sectional
Turkish hospital staff
160028Standing and sitting in a working dayLBPQuestionnaire Overall standing time in a work day was significantly associated with LBP in univariate analysis.Occupation, gender, working year, Smoking, exercise, Perceived stress level in work environment, performing risky activities as belowHigh30
B. Skoffer
(2008)
Cross-sectional
Danish schoolchildren
54615.5Standing talking during school break, hours of watching TV or videoLBP, function-limiting LBPSelf-reported QuestionnaireHomework and TV watching time were associated with LBP. Age, gender, inactivity indicators, weight, BMI and smokingModerate31
S. Ahn
(2009)
Cross-sectional Korean postmenopausal
women
14359Being inactive during leisure timeLBPOne-item questionleisure time inactivity was a risk for back pain. health factors related to BMI, parity, osteoarthritis,
BMD, drinking coffee and inactivity
High32
F. Tissot
(2009)
Population survey
Canadian worker
773041.5Standing at work without freedomLBP Standardized Nordic
questionnaire
Standing at work is associated with low back pain.-High33
W. Yao
(2012)c
Case-control
Chinese adolescents
121415.1 Prolong TV watching, computer using, and homework timeLBP-There was no significant association between sedentary activity and LBP.-High55
N. Aggarwal
(2013)c
Cross-sectional
Indian undergraduate medical students
16020.6Regular watching TV, and working on PC/laptopLBPQuestionnaireNo associations between watching television or computer use with LBP.-High62
M. Mohseni Bandpei
(2014)
Cross-sectional
Iranian teacher
58637.9Standing or sitting time, computer working hours Lifetime LBPOswestry LBP and disability questionnaireGreater risk of LBP was observed in participants with prolonged sitting and standing, higher computer working hours and correcting examination.General health, years of teaching, do exercise, pain intensifiers, sex, age, BMI, and job satisfactionHigh34
P. Mikkonen
(2015)c
Cohort
Finland Students
162516 working on a
computer,
watching television, reading books,
and other sedentary activities
Chronic LBPSelf-reported or consultation-reportedNo association between the sedentary behavior and LBP -High66
J. Fernandes
(2015)
Cross-sectional
Brazilian schoolchildren
146112.6Watching TV/ weekChronic LBPNordic QuestionnaireLow back pain was associated with watching TV (>3 times/week and 3 hours/day)Age, gender High35
G. Inoue
(2015)
Cross-sectional
Japanese sitting worker
132940Routine standing workLBPRDQstanding was not a significant risk factor for LBP.working status, height, age, gender, BMI, smoking habit, and frequency of exercise High36
N. Gupta
(2015)c
Cross-sectional
Danish blue-collar workers
20144.7Total sitting time (hour per day)Intensity of LBPStandardized Nordic questionnairePositive association between total sitting time and high LBP intensity (OR = 1.43) was found.Age, gender, smoking, BMI, occupational time, sitting time in the opposite domain High63
J. Stričević
(2015)
Cross-sectional
Nursing personnel in Slovenia
659- Working with computer or watching TV ≥ 2 h
per day
LBPQuestionnaireWork with the computer reduced the risk for LBP (OR = 0.6)Preventive exercises, Duration of employment, Frequent manual liftingModerate37
M. Dolphens
(2016)
Cross-sectional
Belgian adolescents
84211.6screen time, homework time and reading outside of school.LBPQuestionnaireSedentary behaviors were not associated with LBP.-High38
S. Hussain
(2016)c
Cohort
Australian adults
5058-Total time spent watching Television ≥ 2h/day disability of LBP
LBP intensity
Self-administered Chronic Pain Grade Questionnaire≥ 2 hours/day TV watching was associated with greater prevalence of LBP in women Age, smoking status, dietary index score, BMI, education,High65
M. Ardahan
(2016)
Cross-sectional
Turkish computer-using office workers
39545Daily working hours at computer LB disorderTurkish-Cornell Musculoskeletal Discomfort QuestionnaireUsing a computer (> 7 hours/day) was associated with LB disorder.-High39
L. Lunde
(2017)c
Cohort
Norwegian construction
and healthcare workers
12442.2sitting and standing during work LBP intensity -The duration of sitting during work and leisure time was associated with LBP intensity. Age, gender, smoking, BMI, heavy lifting, and sitting or standing timeHigh56
S. Şimşek
(2017)
Cross-sectional
healthcare workers (Turkey)
1682 37.9 Prolong standing & siting at work & using computer for more than
4 hours
Lifetime; Recent
and
previous year LBP
SNMA Questionnaire

Pain level with
visual analogue scale
Working for more than 4 hours (standing or sitting at desk) and using computer for more than 4 hours were associated with low back pain.-High49
Y. Yabe
(2017)
Cross-sectional
Japanese school-aged athletes
644111Video playing and TV viewing time LBPSelf-reported questionnaireLong video playing time/day was associated with low back pain. Gender, age, BMI, TV-viewing time per day, and video playing time per dayHigh40
S. Ganesan
(2017)c
Cross-sectional
Indian young adult
135524.5Study time more than 5h/day LBP scoreQuestionnaireLBP is triggered by >5 hours studying.-Moderate57
M. Balling
(2017)c
Cohort
Danish adults
7643847.6Total sitting time 6h/day or more LBPNational Patient RegisterNo statistically significant association between total sitting time and low back pain was found.Sex, age, smoking, BMI and physical activity at workHigh58
S. Ye
(2017)c
Cross-sectional
Chicness office workers
41729.1Computer use ≥8 hours/day LBPOswestry Low Back Pain Disability IndexComputer use (>8 hours/day) was not associated with high LBP.-High64
H. Yang
(2018)
Cross-sectional
USA adult population
122,33751.5 Leisure time
physical activity
Chronic LBPSelf-reported LBPHigher prevalence of LBP among inactive people in leisure time.Gender, age, ethnicity, socioeconomic status, and serious psychological distressHigh41
Sh. Sen Sribastav
(2018)
Cross-sectional;
Patient with LBP
(Chi
na)
104637.2 Long time driving Non-specific LBP and pain levelSelf-assessment question­naireSmoking, long driving time, and higher BMI were associated with LBP pain.Gender, age, BMI, smoking habits, duration of driving or riding, drinking habitsHigh42
S. Park
(2018)
Cross-sectional
General Korean population
536465.4sitting time Chronic LBPSelf-reported LBPSitting time more than 7 hours/day was notably associated with LBP. Age, socioeconomic factors, sex, BMI, smoking history, alcohol consumption, and physical activity High43
M. Korshøj
(2018)c
Cross-sectional70445Sitting at workIntensity of LBPNordic QuestionnaireNo significant associations were found between total duration and temporal patterns of sitting with LBP.Interaction between sitting and BMIHigh13
A. Citko
(2018)
Survey
Poland medical personnel
60941Sedentary lifestyle Recurrent and chronic LBPNordic musculoskeletal questionnaire Sedentary lifestyle associated with a 3.5-fold increase in the incidence of LBP.-High19
S. Çelik
(2018)c
Cross-sectional
Office worker
52838.6Time spent standing and continuously sitting in workplace LBPQuestionnaire There is no significant association time spent standing and sitting with risk of LBP.-High59
R. Shiri
(2018)c
Cohort
Finnish population
3505-Sitting hours/dayLBPQuestionnaireNo significant associations between sitting time/day and LBP for more than 7 or 30 days.Age, sexHigh67
S. Kulandaivelan
(2018)

Cross-sectional
HISAR urban population
154048.2Long sitting or watching TV time (> 2h/day)LBPModified Nordic musculoskeletal questionnaireNo statistically significant association between long sitting and sleeping time and LBP-High44
C. Tavares
(2018)c
Cross-sectional
Brazilian medical students
62923Sitting hours per dayLBPQuestionnaire The number of sitting hours was not associated with LBP.-High60
Q. Zhang
(2019)
Cross-sectional
Emergency ambulance workers (driver).
(China)
1560
(543 drivers)
38.4Sitting timeChronic LBPNordic Musculoskeletal QuestionnaireBMI and sitting time were associated with chronic LBP study sample. Age, BMI, sex, Psychosocial factorsHigh45
B. Minghelli
(2019)
Cross-sectional
Portuguese students
30413.7Sedentary habits (Watching television, Mobile phones use, Console/computer games)Lifetime and 6- and 12-month LBPSelf-QuestionnaireMobile use more than 10 hours/week is associated with LBP in adolescents. Sex, sedentary
habits, physical activity
High46
T. Bento
(2019)
Cross-sectional
Brazilian students
162815Daily use time of TV/day, cell phone, tablet more than 3 hChronic LBPNordic QuestionnaireDaily TV use, cell phone use and tablet use (>3 hours) were significantly associated with LBP.Sex, TV watching hours, daily use time of cell-phone and tabletHigh47
H. Ayed
(2019)
Cross-sectional
Tunisia schoolchildren
122115.6Watching TV more than 12h/week and playing video game for more than 2h/weekLBPNordic QuestionnairePlaying videogames (≥2 hours/day), and watching TV (≥12 hours/week) were significant risk factors for LBP.-High20
F. Hanna
(2019)
Cross-sectional
Qatari University Employees
479-Prolong sitting hour LBPALBPSQToo much sitting was significantly associated with LBP or UBPAge, gender, and profession.High48
D. Schwertner
(2019)c
Cross-sectional
Brazilian young
33016TV watching time and computer useLBPOliveira Questionnaire on Low Back Pain in Youths No association of LBP with sedentary lifestyle was found.Sex, age and BMIHigh61
C. Bontrup
(2019)c
Cross-sectional
Swedish call-center employees
7043Occupational sitting habits LBP CPG questionnaire and BPISmall association between general sitting behavior and chronic LBP was found.-High1

Abbreviations: STROBE; STrengthening the Reporting of OBservational studies in Epidemiology; BMI, body mass index; BMD, bone mass density; LBP, low back pain; RDQ, Roland-Morris Disability Questionnaire; CPG, Chronic Pain Grade;

BPI, Brief Pain Inventory; ALBPSQ, Acute Low Back Pain Screening Questionnaire.

aArranged chronologically.

b Mean STROBE score ≥ 16.5 (from two reviewers) was considered as high quality and 11 to 16.5 was considered as moderate quality.

c Not included in metanalyses.

Assessment of study quality

Mean STROBE scores from two reviewers revealed 42 studies conducted in high quality and 7 studies in a moderate quality. We used all these studies in data synthesis or meta-analysis since, concerning moderate quality studies, none of those had small sample sizes or inaccurate estimates. Besides, in the sensitivity analyses, all of the studies were excluded, and the effect sizes were estimated again to ensure the accuracy of data. The quality of each selected study is presented in Table 1. More details about the assessment of study qualities are presented in .

Main findings of the meta-analysis

The forest plot for the association between sedentary behaviors and LBP among children and adolescents is shown in . The pooled odds ratio (based on cross-sectional studies) illustrated that sedentary lifestyle was a remarkable risk factor for LBP among children and adolescents (OR = 1.41, 95% CI = 1.24–1.60, P = 0.002; I2 = 66.5%, P = 0.001). No evidence of publication bias was noted (for all studies, P value of Egger’s test = 0.40, and P value of Begg’s tests = 0.19).

hpp-11-393-g002
Figure 2. The association between sedentary lifestyle and LBP among children and adolescents.

The forest plot for the correlation of sedentary behaviors and LBP among the adult population is shown in . The pooled odds ratio (based on cross-sectional studies) illustrated that the sedentary lifestyle was a considerable risk factor for LBP among the adult population (OR = 1.24, 95% CI = 1.02-1.50, P <0.001; I2 = 84.8%, P < 0.001). No evidence of publication bias was noted (for all studies, P value of Egger’s test = 0.91, and P value of Begg’s tests = 0.08).

hpp-11-393-g003
Figure 3. The association between sedentary lifestyle and LBP among adult population.

Subgroup meta-analysis according to the type of sedentary behaviors

Results of subgroup analysis based on the type of sedentary behaviors among children/adolescents and adult populations are shown in and , respectively. Among children and adolescents prolonged watching TV (OR = 1.23, 95% CI = 1.08–1.41, P = 0.003; I2 = 6.6%, P = 0.37), computer/mobile using and console playing time (OR = 1.63, 95% CI = 1.36–1.95, P = 0.001; I2 = 47.9%, P = 0.09) were significant risk factors for LBP (P value < 0.05) ().

hpp-11-393-g004
Figure 4. Subgroup analysis according to sedentary lifestyle among children and adolescents.

hpp-11-393-g005
Figure 5. Subgroup analysis according to sedentary lifestyle among adult population.

Among adult population prolonged sitting time (OR = 1.42, 95% CI = 1.09–1.85, P = 0.03; I2 = 85.5%, P < 0.001), and driving time (OR = 2.03, 95% CI = 1.22–3.36, P <0.001; I2 = 56.8%, P = 0.13) were the significant risk factors for LBP ().

Subgroup meta-analysis according to occupation type

Among office workers, sedentary lifestyle was an essential risk for LBP (OR = 1.23, 95% CI = 1.03–1.47, I2 = 0%) ().

hpp-11-393-g006
Figure 6. The association between the sedentary lifestyle and LBP according to occupation type.

Body mass index and smoking status

As shown in and , overweight or obesity (OR = 1.35, 95% CI = 1.14–1.59, P = 0.02; I2 = 90.3%, P < 0.001) and smoking (OR = 1.28, 95% CI = 1.03–1.60, P = 0.01; I2 = 86.5%, P < 0.001) were the significant risk factors for LBP among adult population. In children, excess wight (OR = 1.60, 95% CI = 1.13–2.27, P = 0.021; I2 = 0.00, P = 0.49) was associated with LBP as well.

hpp-11-393-g007
Figure 7. The association between Body Mass Index (BMI) and LBP according to the age group.

hpp-11-393-g008
Figure 8. The association between smoking and LBP among adult population.

No evidence of publication bias for BMI was found (P value of Egger’s test = 0.41, and P value of Begg’s tests = 0.68).

We found publication bias for smoking (P value of Egger’s test = 0.71, and P value of Begg’s tests = 0.03). Therefore, we conducted the Trim and Fill method to explore the effect of publication bias on the meta-analysis results. However, no significant change in the pooled OR was noted.

Leisure time inactivity

As shown in , leisure time inactivity was an essential risk factor for LBP (OR = 1.28, 95% CI = 0.92–1.77, I2 = 81%).

hpp-11-393-g009
Figure 9. The association between leisure-time inactivity and LBP.

Sensitivity analysis

We found no significant changes between the before-after sensitivity pooled OR for the association between sedentary lifestyle and LBP among children and adolescents. However, results showed a remarkable effect between before-after sensitivity pooled OR for the correlation between the sedentary lifestyle and LBP among adult population after excluding Zhang et al 45 study (OR = 1.16, 95% CI = 0.99–1.36).

Also, results showed significant changes between the before-after sensitivity pooled OR for the association between smoking and LBP among the adult population after excluding Mattila et al 27 study and Sribastav et al 42 study (OR = 1.26, 95% CI = 0.97–1.56).

Besides, no remarkable changes between the before-after sensitivity pooled OR for the association between the sedentary lifestyle and LBP among healthcare workers and office workers were noted.

Overview of studies not included in the meta-analysis

Sedentary behavior at work with non-neutral posture correlates with LBP among workers. 50 Bending postures but not sedentary leisure time itself have been proposed to be associated with new LBP in nurses. 54 However, three studies stated no association between sedentary habits and LBP. 55,61,62

Sitting behavior was associated with chronic LBP and functional disfunction among 70 call center employees. 1 Among a population of truck drivers, the only factor correlated to LBP was the number of working hours. 5 Also, the daily number of studying hours (>5 hours) precipitated the LBP in young adults. 57 On the other hand, sitting time was not considered a risk factor for LBP in 3 studies. 58-60

LBP was reported more in school children playing videogames >2 hours/day and not for television watchers in the Gunzburg et al study. 51 Similar to this finding, a cohort study by Croft et al reported that watching television > 3 hours/day did not enhanced the risk of recurrent LBP in the UK general population. 52 Similarly, in a cohort study among Finnish children, the sedentary class boys (derived from latent class analysis) did not presented with increased risk for reporting LBP or consultation for LBP. 66 More conflicting results have been reported in Shehab et al study in which the LBP correlated with female gender and TV watching time in children and adolescents. 53

In Hussain et al. study, TV watching time in women was associated with greater LBP disability. The authors suggested that targeting the time spent TV watching would be effective in reducing LBP disability in adults at the level of community. 65 A retrospective study revealed that sedentary work was associated with LBP in both genders after a 24 year period. 68 Also, in Shiri et al study, lifestyle including abdominal obesity and smoking increased the risk of LBP. Reduced risk of LBP was obtained via walking and cycling to work (OR = 0.75). 67

Regarding the intensity of LBP, Gupta et al showed a notable association between total sitting time and high LBP intensity among 201 participants (OR = 1.43). 63 The duration of sitting time both in work and leisure time was associated with LBP intensity in another study. 56 Such a relationship was investigated in Ye et al study among 417 office workers. In contrast, in this study computer use ≥ 8 hours/day was not associated with high intensity LBP. 64 In the Korshøj et al study, the sitting pattern was not correlated with the intensity of LBP. 13 Moreover, in Hussain et al. cohort study on 5058 individuals, no significant associations between < 2.5 hours/week physical activity and ≥ 2 hours/day TV watching, with LBP intensity at follow-up were reported. 65 Thus, further research is necessary to better elucidate the effect of sedentariness on the risk of high-intensity LBP.

Coffee drinking and LBP

In a survey, Citko et al showed that coffee drinking, 6 cups per day or more, increased the risk of non-specific LBP recurrence by 16 times compared to smaller amounts in medical personnel. 19 Also, a survey of 134 postmenopausal women reported a significant association of drinking coffee (yes/no) with LBP (OR = 3.1). 32 However, in the Aggarwal study, regular or occasional coffee intake was not associated with LBP among undergraduate students. 62 The absence of association was found in the Ganesan et al study as well. 57 Abovementioned studies were all cross-sectional in their design. The effect of coffee on back pain may be dose-dependent or through indirect mechanisms such as via affecting bone health. 32 To better clarify this issue, further exploration is necessary, with a standard measurement of coffee/caffeine intake, especially in longitudinal research.


Discussion

Our study explored the association of sedentary behavior and LBP. The results demonstrate the role of sedentary behavior as a risk factor for the increased incidence of LBP, both in adults and children (OR = 1.24 and 1.41, respectively).

A similar systematic review to ours, published in 2009, was performed on 15 observational studies up to 2006 and revealed that there was no correlation between sedentary behavior both in work or leisure time with LBP. 12 However, given that more articles have been published in recent years, we were able to obtain the pooled OR for the abovementioned association for adults and children separately. In addition, in the previous review, only prolonged sitting was considered as sedentary behavior, whereas we conducted subgroup meta-analyses according to the type of sedentary behaviors and occupation type.

The time spent in sedentary lifestyle has become a significant health concern. The sedentary behavior prevalence is high, even in developed countries. 69 One study showed that children spend 51.4% of their working time in sedentary lifestyle. These common behaviors may be established in childhood and track through later life. 70 Sedentary behavior is linked to various musculoskeletal pain conditions. 71

Despite the controversies observed in included articles in our systematic review, the pooled effects sizes obtained from meta-analysis of other studies revealed that prolonged sitting time and prolonged driving time are significant risk factors of LBP among adults (OR = 1.42, 2.03 respectively). However, prolonged screen time and standing time were not associated with LBP in adults. Also, among children, prolonged TV watching (OR = 1.23), and computer/mobile using or console playing time (OR = 1.63) were associated with LBP. A meta-analysis study indicated that excess weight is a risk factor for LBP in both genders. 72 Another study revealed that smokers have a higher incidence of LBP compared to nonsmokers; these associations were fairly modest (OR = 1.32 for former and OR = 1.31 for the current smokers). Of note, the association between current smoking and LBP was more remarkable in adolescents than in adults (OR = 1.82 vs. 1.16). 73 Similarly, we found that increased body mass index in adults and children and smoking in adults, are risk factors for LBP (OR = 1.35, 1.60 and 1.28 respectively), in whom the sedentary behavior has been investigated. These finding suggest that smoking and body mass index interact with sitting and LBP. 13 In addition, to avoid heterogeneity, we identified two main occupation categories as healthcare workers and office workers among the included studies. We found that sedentary behavior is a risk for LBP in office workers (OR = 1.23). In previous research, prolonged sitting and computer use were contributed to LBP in office workers. 48

As for underlying pathways, decreased level of water supply to the vertebral disc, which in turn leads to degenerative changes and disk herniations, reduced strength and muscular power, and developing hyperlordosis are some proposed pathophysiological mechanisms for sedentary behavior contributing to LBP. 19 Specifically, prolonged sitting is contributed to decreased postural change, as well as muscle strength and disk degenerations. 13 Obesity or overweight causes overload on the spinal tissues and contributes to disk herniation and LBP. On the other hand, obesity is associated with other disorders such as diabetes and hyperlipidemia that are also correlated to LBP by different mechanisms. 74 Smoking can alter the blood supply of vertebral disks via the processes of vasoconstriction and atherosclerosis. Impaired perfusion of vertebral structures leads to degenerative changes and LBP. Besides, smoking is a risk factor of osteoporosis or is a behavior seen only the people with massive physical works; thus, it has direct and indirect effects on the LBP. 73 Moreover, coffee consumption is proposed to be associated with flushing magnesium from the body and increased painful contractions of paraspinal muscles. 75

The data heterogeneity of included studies in our review can be explained in part by variations in study designs, study population, sample sizes, occupation type, gender, race, and age range. However, beyond those, some factors seem to be more important, as follows.

First, the definition of LBP and its measurement scales were considerably different in the studies. For instance, experiencing LBP during the current week for at least 48 hours via the Roland-Morris Disability Questionnaire was measured in the Inoue et al. study. 36 In the Ben Ayed et al study, however, participants were asked about discomfort and pain in the low back area during the prior month. 20 Some authors, though, defined recurrent LBP as pain episodes of at least three times in the last 12 months and chronic LBP as the pain persisted for at least 12 weeks based on the Nordic Musculoskeletal Questionnaire. 19 Many studies, however, did not differentiate chronic LBP from acute LBP.

Second, sedentary behavior has diverse definitions and types in various studies. While some authors explored the association of sitting time merely with LBP, 28 some others have turned their attention to the screen time or a combination of both. 49 In some other studies, sedentary habits were not categorized into any different types. 68 In addition, the common measurement tool for sedentary behavior is subjective self-reported questionnaires, which, in turn, are prone to information bias from participants. However, a few studies used objective-based tools such as an accelerometer or textile pressure mat to estimate the sitting time. 1,63 Thus, to make accurate estimations, we performed subgroup analyses for specified sedentary behavior in the papers, both for adults and children separately. For future research, focusing on objective-based measurement of sedentary behaviors is highly suggested.

The third is that LBP, as a complex multifactorial disease, is affected by psychological conditions and the tasks performed in non-sitting positions at work or leisure time. Therefore, just a part of the variation in LBP is because of sedentary-related risk factors. 33,48 Thus, the variety in the combination of these factors in different participants seems to be accounted for the data heterogeneity.

Strengths of the study

We applied different statistical methods to obtain the desired associations for adults and children separately, as the risk factors of LBP may be different in these age groups. We found new data and demonstrated significant but moderate associations between different sedentary behaviors and LBP. Regarding the large number of studies conducted in this field (which were retained in the meta-analysis), the results can be well generalized to different communities.

Health implications

A recent meta-analysis evaluating the lifestyle interventions to reduce sedentary behavior among five categories of population with a clinical condition (including musculoskeletal conditions) demonstrated that after multicomponent interventions, individuals with different medical conditions successfully reduced their sedentary behavior (by 64 minutes/day). The interventions consisted of the use of technologies, social facilitation, motivational counselling and self-monitoring. 76 As LBP is a complex disorder, health education to reduce the prevalence or occurrence of LBP should be address the risk factors as much as possible including sedentary behavior.


Conclusion

In brief, according to our meta-analysis, sufficient evidence exists from recent studies that indicate the association of different types of sedentary behavior with the occurrence or recurrence of LBP both in adults and children. Given the increasing trend of sedentary behavior worldwide, especially in the era of the COVID-19 pandemic, meticulous and robust preventive strategies are suggested to be applied to avoid the establishment of sedentariness early in childhood and to prevent its’ musculoskeletal consequences such as LBP.


Acknowledgments

We want to thank our colleagues in Isfahan University of medical Sciences who helped us working on this project.


Funding

This study was funded and supported by Isfahan University of Medical Sciences, Isfahan, Iran.


Competing interests

None to declare.


Ethical approval

The protocol of the current review has been qualified in the Isfahan University of Medical Sciences, Isfahan, Iran (code: 199298) and has been approved in the National regulatory ethics committee (IR.MUI.MED.REC.1399.507). The study protocol and its details have been registered in the international prospective register of systematic reviews, PROSPERO with identification code: CRD42020187175.


Authors’ contributions

SBM contributed to the conception of the work, data search, screening of records, study quality assessment, data extraction, manuscript preparation, manuscript revision, final approval of the manuscript, and agreed to be accountable for all aspects of the work. RR contributed to the screening of records, study quality assessment, data extraction, statistical analysis, interpretation of data, manuscript preparation, manuscript revision, final approval of the manuscript, and agreed to be accountable for all aspects of the work. BV contributed to study quality assessment, manuscript preparation, manuscript revision, final approval of the manuscript, and agreed to be accountable for all aspects of the work. RK contributed to the conception of the work, manuscript preparation, manuscript revision, final approval of the manuscript, and agreed to be accountable for all aspects of the work. All authors approved the final version of manuscript and took the responsibility for all aspects of the work.


References

  1. Bontrup C, Taylor WR, Fliesser M, Visscher R, Green T, Wippert PM. Low back pain and its relationship with sitting behaviour among sedentary office workers. Appl Ergon 2019; 81:102894. doi: 10.1016/j.apergo.2019.102894 [Crossref]
  2. Amorim AB, Levy GM, Pérez-Riquelme F, Simic M, Pappas E, Dario AB. Does sedentary behavior increase the risk of low back pain? a population-based co-twin study of Spanish twins. Spine J 2017; 17(7):933-42. doi: 10.1016/j.spinee.2017.02.004 [Crossref]
  3. Jonsdottir S, Ahmed H, Tómasson K, Carter B. Factors associated with chronic and acute back pain in Wales, a cross-sectional study. BMC Musculoskelet Disord 2019; 20(1):215. doi: 10.1186/s12891-019-2477-4 [Crossref]
  4. Lötters F, Burdorf A. Prognostic factors for duration of sickness absence due to musculoskeletal disorders. Clin J Pain 2006; 22(2):212-21. doi: 10.1097/01.ajp.0000154047.30155.72 [Crossref]
  5. Andrusaitis SF, Oliveira RP, Barros Filho TE. Study of the prevalence and risk factors for low back pain in truck drivers in the state of São Paulo, Brazil. Clinics (Sao Paulo) 2006; 61(6):503-10. doi: 10.1590/s1807-59322006000600003 [Crossref]
  6. Maher C, Underwood M, Buchbinder R. Non-specific low back pain. Lancet 2017; 389(10070):736-47. doi: 10.1016/s0140-6736(16)30970-9 [Crossref]
  7. Daraiseh NM, Cronin SN, Davis LS, Shell RL, Karwowski W. Low back symptoms among hospital nurses, associations to individual factors and pain in multiple body regions. Int J Ind Ergon 2010; 40(1):19-24. doi: 10.1016/j.ergon.2009.11.004 [Crossref]
  8. Booth FW, Lees SJ. Fundamental questions about genes, inactivity, and chronic diseases. Physiol Genomics 2007; 28(2):146-57. doi: 10.1152/physiolgenomics.00174.2006 [Crossref]
  9. Panahi S, Tremblay A. Sedentariness and health: is sedentary behavior more than just physical inactivity?. Front Public Health 2018; 6:258. doi: 10.3389/fpubh.2018.00258 [Crossref]
  10. Chau JY, Grunseit AC, Chey T, Stamatakis E, Brown WJ, Matthews CE. Daily sitting time and all-cause mortality: a meta-analysis. PLoS One 2013; 8(11):e80000. doi: 10.1371/journal.pone.0080000 [Crossref]
  11. Bjørk Petersen C, Bauman A, Grønbæk M, Wulff Helge J, Thygesen LC, Tolstrup JS. Total sitting time and risk of myocardial infarction, coronary heart disease and all-cause mortality in a prospective cohort of Danish adults. Int J Behav Nutr Phys Act 2014; 11:13. doi: 10.1186/1479-5868-11-13 [Crossref]
  12. Chen SM, Liu MF, Cook J, Bass S, Lo SK. Sedentary lifestyle as a risk factor for low back pain: a systematic review. Int Arch Occup Environ Health 2009; 82(7):797-806. doi: 10.1007/s00420-009-0410-0 [Crossref]
  13. Korshøj M, Hallman DM, Mathiassen SE, Aadahl M, Holtermann A, Jørgensen MB. Is objectively measured sitting at work associated with low-back pain? a cross sectional study in the DPhacto cohort. Scand J Work Environ Health 2018; 44(1):96-105. doi: 10.5271/sjweh.3680 [Crossref]
  14. Lis AM, Black KM, Korn H, Nordin M. Association between sitting and occupational LBP. Eur Spine J 2007; 16(2):283-98. doi: 10.1007/s00586-006-0143-7 [Crossref]
  15. Bakker EW, Verhagen AP, van Trijffel E, Lucas C, Koes BW. Spinal mechanical load as a risk factor for low back pain: a systematic review of prospective cohort studies. Spine (Phila Pa 1976) 2009; 34(8):E281-93. doi: 10.1097/BRS.0b013e318195b257 [Crossref]
  16. Hartvigsen J, Leboeuf-Yde C, Lings S, Corder EH. Is sitting-while-at-work associated with low back pain? a systematic, critical literature review. Scand J Public Health 2000; 28(3):230-9.
  17. Diallo SYK, Mweu MM, Mbuya SO, Mwanthi MA. Prevalence and risk factors for low back pain among university teaching staff in Nairobi, Kenya: a cross-sectional study. F1000Res 2019; 8:808. doi: 10.12688/f1000research.19384.1 [Crossref]
  18. Korshøj M, Jørgensen MB, Hallman DM, Lagersted-Olsen J, Holtermann A, Gupta N. Prolonged sitting at work is associated with a favorable time course of low-back pain among blue-collar workers: a prospective study in the DPhacto cohort. Scand J Work Environ Health 2018; 44(5):530-8. doi: 10.5271/sjweh.3726 [Crossref]
  19. Citko A, Górski S, Marcinowicz L, Górska A. Sedentary lifestyle and nonspecific low back pain in medical personnel in North-East Poland. Biomed Res Int 2018; 2018:1965807. doi: 10.1155/2018/1965807 [Crossref]
  20. Ben Ayed H, Yaich S, Trigui M, Ben Hmida M, Ben Jemaa M, Ammar A. Prevalence, risk factors and outcomes of neck, shoulders and low-back pain in secondary-school children. J Res Health Sci 2019; 19(1):e00440.
  21. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61(4):344-9. doi: 10.1016/j.jclinepi.2007.11.008 [Crossref]
  22. Baradaran Mahdavi S, Daniali SS, Farajzadegan Z, Bahreynian M, Riahi R, Kelishadi R. Association between maternal smoking and child bone mineral density: a systematic review and meta-analysis. Environ Sci Pollut Res Int 2020; 27(19):23538-49. doi: 10.1007/s11356-020-08740-1 [Crossref]
  23. Higgins JP, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Version 5.1. 0 (Updated March 2011). The Cochrane Collaboration; 2011. Available from: https://handbook-5-1.cochrane.org/.
  24. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009; 6(7):e1000097. doi: 10.1371/journal.pmed.1000097 [Crossref]
  25. Skov T, Borg V, Orhede E. Psychosocial and physical risk factors for musculoskeletal disorders of the neck, shoulders, and lower back in salespeople. Occup Environ Med 1996; 53(5):351-6. doi: 10.1136/oem.53.5.351 [Crossref]
  26. Sjolie AN. Associations between activities and low back pain in adolescents. Scand J Med Sci Sports 2004; 14(6):352-9. doi: 10.1111/j.1600-0838.2004.377.x [Crossref]
  27. Mattila VM, Sahi T, Jormanainen V, Pihlajamäki H. Low back pain and its risk indicators: a survey of 7,040 Finnish male conscripts. Eur Spine J 2008; 17(1):64-9. doi: 10.1007/s00586-007-0493-9 [Crossref]
  28. Spyropoulos P, Papathanasiou G, Georgoudis G, Chronopoulos E, Koutis H, Koumoutsou F. Prevalence of low back pain in Greek public office workers. Pain Physician 2007; 10(5):651-9.
  29. Auvinen J, Tammelin T, Taimela S, Zitting P, Karppinen J. Associations of physical activity and inactivity with low back pain in adolescents. Scand J Med Sci Sports 2008; 18(2):188-94. doi: 10.1111/j.1600-0838.2007.00672.x [Crossref]
  30. Karahan A, Kav S, Abbasoglu A, Dogan N. Low back pain: prevalence and associated risk factors among hospital staff. J Adv Nurs 2009; 65(3):516-24. doi: 10.1111/j.1365-2648.2008.04905.x [Crossref]
  31. Skoffer B, Foldspang A. Physical activity and low-back pain in schoolchildren. Eur Spine J 2008; 17(3):373-9. doi: 10.1007/s00586-007-0583-8 [Crossref]
  32. Ahn S, Song R. Bone mineral density and perceived menopausal symptoms: factors influencing low back pain in postmenopausal women. J Adv Nurs 2009; 65(6):1228-36. doi: 10.1111/j.1365-2648.2009.04983.x [Crossref]
  33. Tissot F, Messing K, Stock S. Studying the relationship between low back pain and working postures among those who stand and those who sit most of the working day. Ergonomics 2009; 52(11):1402-18. doi: 10.1080/00140130903141204 [Crossref]
  34. Mohseni Bandpei MA, Ehsani F, Behtash H, Ghanipour M. Occupational low back pain in primary and high school teachers: prevalence and associated factors. J Manipulative Physiol Ther 2014; 37(9):702-8. doi: 10.1016/j.jmpt.2014.09.006 [Crossref]
  35. Fernandes JA, Dos Santos Genebra CV, Maciel NM, Fiorelli A, de Conti MH, De Vitta A. Low back pain in schoolchildren: a cross-sectional study in a western city of São Paulo State, Brazil. Acta Ortop Bras 2015; 23(5):235-8. doi: 10.1590/1413-785220152305148842 [Crossref]
  36. Inoue G, Miyagi M, Uchida K, Ishikawa T, Kamoda H, Eguchi Y. The prevalence and characteristics of low back pain among sitting workers in a Japanese manufacturing company. J Orthop Sci 2015; 20(1):23-30. doi: 10.1007/s00776-014-0644-x [Crossref]
  37. Stričević J, Papež BJ. Non-specific low back pain: occupational or lifestyle consequences?. Wien Klin Wochenschr 2015; 127 Suppl 5:S277-81. doi: 10.1007/s00508-015-0770-2 [Crossref]
  38. Dolphens M, Vansteelandt S, Cagnie B, Vleeming A, Nijs J, Vanderstraeten G. Multivariable modeling of factors associated with spinal pain in young adolescence. Eur Spine J 2016; 25(9):2809-21. doi: 10.1007/s00586-016-4629-7 [Crossref]
  39. Ardahan M, Simsek H. Analyzing musculoskeletal system discomforts and risk factors in computer-using office workers. Pak J Med Sci 2016; 32(6):1425-9. doi: 10.12669/pjms.326.11436 [Crossref]
  40. Yabe Y, Hagiwara Y, Sekiguchi T, Momma H, Tsuchiya M, Kuroki K. Late bedtimes, short sleeping time, and longtime video-game playing are associated with low back pain in school-aged athletes. Eur Spine J 2018; 27(5):1112-8. doi: 10.1007/s00586-017-5177-5 [Crossref]
  41. Yang H, Haldeman S. Behavior-related factors associated with low back pain in the US adult population. Spine (Phila Pa 1976) 2018; 43(1):28-34. doi: 10.1097/brs.0000000000001665 [Crossref]
  42. Sribastav SS, Long J, He P, He W, Ye F, Li Z. Risk factors associated with pain severity in patients with non-specific low back pain in Southern China. Asian Spine J 2018; 12(3):533-43. doi: 10.4184/asj.2018.12.3.533 [Crossref]
  43. Park SM, Kim HJ, Jeong H, Kim H, Chang BS, Lee CK. Longer sitting time and low physical activity are closely associated with chronic low back pain in population over 50 years of age: a cross-sectional study using the sixth Korea National Health and Nutrition Examination Survey. Spine J 2018; 18(11):2051-8. doi: 10.1016/j.spinee.2018.04.003 [Crossref]
  44. Kulandaivelan S, Ateef M, Singh V, Chaturvedi R, Joshi S. One-year prevalence of low back pain and its correlates in Hisar urban population. J Musculoskelet Res 2018; 21(2):1850011. doi: 10.1142/s0218957718500112 [Crossref]
  45. Zhang Q, Dong H, Zhu C, Liu G. Low back pain in emergency ambulance workers in tertiary hospitals in China and its risk factors among ambulance nurses: a cross-sectional study. BMJ Open 2019; 9(9):e029264. doi: 10.1136/bmjopen-2019-029264 [Crossref]
  46. Minghelli B. Musculoskeletal spine pain in adolescents: epidemiology of non-specific neck and low back pain and risk factors. J Orthop Sci 2020; 25(5):776-80. doi: 10.1016/j.jos.2019.10.008 [Crossref]
  47. Bento TPF, Cornelio GP, de Oliveira Perrucini P, Simeão S, de Conti MHS, de Vitta A. Low back pain in adolescents and association with sociodemographic factors, electronic devices, physical activity and mental health. J Pediatr (Rio J) 2020; 96(6):717-24. doi: 10.1016/j.jped.2019.07.008 [Crossref]
  48. Hanna F, Daas RN, El-Shareif TJ, Al-Marridi HH, Al-Rojoub ZM, Adegboye OA. The relationship between sedentary behavior, back pain, and psychosocial correlates among university employees. Front Public Health 2019; 7:80. doi: 10.3389/fpubh.2019.00080 [Crossref]
  49. Şimşek Ş, Yağcı N, Şenol H. Prevalence of and risk factors for low back pain among healthcare workers in Denizli. Agri 2017; 29(2):71-8. doi: 10.5505/agri.2017.32549 [Crossref]
  50. Burdorf A, Naaktgeboren B, de Groot HC. Occupational risk factors for low back pain among sedentary workers. J Occup Med 1993; 35(12):1213-20.
  51. Gunzburg R, Balagué F, Nordin M, Szpalski M, Duyck D, Bull D. Low back pain in a population of school children. Eur Spine J 1999; 8(6):439-43. doi: 10.1007/s005860050202 [Crossref]
  52. Croft PR, Papageorgiou AC, Thomas E, Macfarlane GJ, Silman AJ. Short-term physical risk factors for new episodes of low back pain. Prospective evidence from the South Manchester Back Pain Study. Spine (Phila Pa 1976) 1999; 24(15):1556-61. doi: 10.1097/00007632-199908010-00009 [Crossref]
  53. Shehab DK, Al-Jarallah KF. Nonspecific low-back pain in Kuwaiti children and adolescents: associated factors. J Adolesc Health 2005; 36(1):32-5. doi: 10.1016/j.jadohealth.2003.12.011 [Crossref]
  54. Yip VY. New low back pain in nurses: work activities, work stress and sedentary lifestyle. J Adv Nurs 2004; 46(4):430-40. doi: 10.1111/j.1365-2648.2004.03009.x [Crossref]
  55. Yao W, Luo C, Ai F, Chen Q. Risk factors for nonspecific low-back pain in Chinese adolescents: a case-control study. Pain Med 2012; 13(5):658-64. doi: 10.1111/j.1526-4637.2012.01369.x [Crossref]
  56. Lunde LK, Koch M, Knardahl S, Veiersted KB. Associations of objectively measured sitting and standing with low-back pain intensity: a 6-month follow-up of construction and healthcare workers. Scand J Work Environ Health 2017; 43(3):269-78. doi: 10.5271/sjweh.3628 [Crossref]
  57. Ganesan S, Acharya AS, Chauhan R, Acharya S. Prevalence and risk factors for low back pain in 1,355 young adults: a cross-sectional study. Asian Spine J 2017; 11(4):610-7. doi: 10.4184/asj.2017.11.4.610 [Crossref]
  58. Balling M, Holmberg T, Petersen CB, Aadahl M, Meyrowitsch DW, Tolstrup JS. Total sitting time, leisure time physical activity and risk of hospitalization due to low back pain: The Danish Health Examination Survey cohort 2007-2008. Scand J Public Health 2019; 47(1):45-52. doi: 10.1177/1403494818758843 [Crossref]
  59. Celik S, Celik K, Dirimese E, Taşdemir N, Arik T, Büyükkara İ. Determination of pain in musculoskeletal system reported by office workers and the pain risk factors. Int J Occup Med Environ Health 2018; 31(1):91-111. doi: 10.13075/ijomeh.1896.00901 [Crossref]
  60. Tavares C, Salvi CS, Nisihara R, Skare T. Low back pain in Brazilian medical students: a cross-sectional study in 629 individuals. Clin Rheumatol 2019; 38(3):939-42. doi: 10.1007/s10067-018-4323-8 [Crossref]
  61. Schwertner DS, Oliveira R, Koerich M, Motta AF, Pimenta AL, Gioda FR. Prevalence of low back pain in young Brazilians and associated factors: sex, physical activity, sedentary behavior, sleep and body mass index. J Back Musculoskelet Rehabil 2020; 33(2):233-44. doi: 10.3233/bmr-170821 [Crossref]
  62. Aggarwal N, Anand T, Kishore J, Ingle GK. Low back pain and associated risk factors among undergraduate students of a medical college in Delhi. Educ Health (Abingdon) 2013; 26(2):103-8. doi: 10.4103/1357-6283.120702 [Crossref]
  63. Gupta N, Christiansen CS, Hallman DM, Korshøj M, Carneiro IG, Holtermann A. Is objectively measured sitting time associated with low back pain? a cross-sectional investigation in the NOMAD study. PLoS One 2015; 10(3):e0121159. doi: 10.1371/journal.pone.0121159 [Crossref]
  64. Ye S, Jing Q, Wei C, Lu J. Risk factors of non-specific neck pain and low back pain in computer-using office workers in China: a cross-sectional study. BMJ Open 2017; 7(4):e014914. doi: 10.1136/bmjopen-2016-014914 [Crossref]
  65. Hussain SM, Urquhart DM, Wang Y, Dunstan D, Shaw JE, Magliano DJ. Associations between television viewing and physical activity and low back pain in community-based adults: a cohort study. Medicine (Baltimore) 2016; 95(25):e3963. doi: 10.1097/md.0000000000003963 [Crossref]
  66. Mikkonen P, Heikkala E, Paananen M, Remes J, Taimela S, Auvinen J. Accumulation of psychosocial and lifestyle factors and risk of low back pain in adolescence: a cohort study. Eur Spine J 2016; 25(2):635-42. doi: 10.1007/s00586-015-4065-0 [Crossref]
  67. Shiri R, Falah-Hassani K, Heliövaara M, Solovieva S, Amiri S, Lallukka T. Risk factors for low back pain: a population-based longitudinal study. Arthritis Care Res (Hoboken) 2019; 71(2):290-9. doi: 10.1002/acr.23710 [Crossref]
  68. Thorbjörnsson CB, Alfredsson L, Fredriksson K, Michélsen H, Punnett L, Vingård E. Physical and psychosocial factors related to low back pain during a 24-year period. A nested case-control analysis. Spine (Phila Pa 1976) 2000; 25(3):369-75. doi: 10.1097/00007632-200002010-00019 [Crossref]
  69. Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol 2008; 167(7):875-81. doi: 10.1093/aje/kwm390 [Crossref]
  70. Pereira JR, Cliff DP, Sousa-Sá E, Zhang Z, Santos R. Prevalence of objectively measured sedentary behavior in early years: systematic review and meta-analysis. Scand J Med Sci Sports 2019; 29(3):308-28. doi: 10.1111/sms.13339 [Crossref]
  71. Baradaran Mahdavi S, Kelishadi R. Impact of sedentary behavior on bodily pain while staying at home in COVID-19 pandemic and potential preventive strategies. Asian J Sports Med 2020; 11(2):e103511. doi: 10.5812/asjsm.103511 [Crossref]
  72. Zhang TT, Liu Z, Liu YL, Zhao JJ, Liu DW, Tian QB. Obesity as a risk factor for low back pain: a meta-analysis. Clin Spine Surg 2018; 31(1):22-7. doi: 10.1097/bsd.0000000000000468 [Crossref]
  73. Shiri R, Karppinen J, Leino-Arjas P, Solovieva S, Viikari-Juntura E. The association between smoking and low back pain: a meta-analysis. Am J Med 2010; 123(1):87.e7-87. doi: 10.1016/j.amjmed.2009.05.028 [Crossref]
  74. Ha JY. Evaluation of metabolic syndrome in patients with chronic low back pain: using the fourth Korea national health and nutrition examination survey data. Chonnam Med J 2011; 47(3):160-4. doi: 10.4068/cmj.2011.47.3.160 [Crossref]
  75. Alghadir AH, Gabr SA, Al-Eisa ES. Mechanical factors and vitamin D deficiency in schoolchildren with low back pain: biochemical and cross-sectional survey analysis. J Pain Res 2017; 10:855-65. doi: 10.2147/jpr.s124859 [Crossref]
  76. Nieste I, Franssen WMA, Spaas J, Bruckers L, Savelberg H, Eijnde BO. Lifestyle interventions to reduce sedentary behaviour in clinical populations: a systematic review and meta-analysis of different strategies and effects on cardiometabolic health. Prev Med 2021; 148:106593. doi: 10.1016/j.ypmed.2021.106593 [Crossref]
Submitted: 29 Sep 2021
Accepted: 29 Oct 2021
First published online: 19 Dec 2021
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