LifeStyle and Exercise Relation to Neck and Back Pain in Saudi Arabia

Background: Personal anguish, incapacity, and a decline in work and life quality are all associated with neck and low back pain, making it a significant socioeconomic burden for individuals and society. It is well known that engaging in regular physical exercise has considerable health benefits.

Objective: The purpose of this research was to investigate the factors contributing to the high rates of musculoskeletal pain experienced by the Saudi Arabian population.

Methods: This population-based, cross-sectional study was done in Saudi Arabia with 2,717 participants aged 18 to 60. A questionnaire was provided online to assess neck, shoulder, and lower back discomfort, time spent in general or aerobic physical activity, time spent sitting, sleep problems, general health, work satisfaction, and nutrition. Using logistic regression, we observed potential risk factors for musculoskeletal pain.

Results: The prevalence of neck pain, shoulder pain, and lower back pain (LBP) were found to be 48.1%, 47.6%, and 63.8%, respectively. It was found that being a female (OR=1.78 [1.41-2.25], p<0.001), married (OR=1.58 [1.34-1.86], p<0.001), and having poor general health status (OR=3.78 [2.2-6.49], p<0.001), sleep disturbances (OR=2.46 [2.04-2.97], p<0.001) and poor job satisfaction (OR=1.29 [1.05-1.60], p=0.016) were independently associated with the prevalence of musculoskeletal pain. The diet of the individuals did not significantly influence the prevalence of MSPs.

Conclusion: Good general health, good sleep, and good job satisfaction were associated with a reduced risk of experiencing neck or shoulder pain, but there was no association between physical activity and MSPs Longitudinal studies are required to acquire a better understanding of the relationship between MSP, aerobic activity, sleep, and diet.

Introduction

In many countries, neck and upper body musculoskeletal pain (MSP) is a leading source of morbidity and disability. Individuals’ physical, social, and psychological well-being can be compromised, resulting in higher healthcare expenditures [1,2]. The prevalence of neck pain in the world’s working population is estimated to range between 16.7% to 75.1%, with slightly more prevalence noted among women than men. Several factors contribute to neck and upper body MSP, including ergonomics (physical exhaustion, use of force and vibration, poor posture, repetitive movement), individual characteristics (age, BMI, genetics, history of MSP), lifestyles, and psychosocial characteristics [3,4]. High job strain was associated with upper body pain among males but not among women [5]. Lengthy computer use was also shown to be strongly associated with MSP [6,7]. To prevent neck pain from becoming a long-term condition, it is crucial to identify risk factors and seek treatment early. The prevention, diagnosis, treatment, and management of neck pain can be guided by identifying protective or risk factors, triggers, and outcomes.

Governments face enormous expenditures due to the recurrence and increasing incidence of MSP, which necessitates the implementation of effective new preventive reforms. Numerous studies on MPS have been performed, particularly in developed nations [8-12]. However, few studies have simultaneously investigated neck, shoulder, and low back pain in the Saudi population. Although some studies have explored the pattern and prevalence of MSP in Saudi Arabia, no national-level study has ever been done yet [13,14]. There is no exact data on the prevalence of MSP in Saudi Arabia. From this standpoint, the primary objective of this study is to determine the prevalence of MSP among the Saudi population. Correspondingly, we aimed to analyze the possible risk factors associated with this condition, and we will draw a conclusion by analyzing the impact this condition has on both a person’s peoples’ physical and social life.

Materials & Methods

A population-based, cross-sectional study was an online survey conducted involving participants from different provinces in Saudi Arabia. The study population included adults aged between 18 years and 60 years (considering the age of retirement in Saudi Arabia). Any individual that is younger than 18 years or older than 60 years of age was excluded. A non-probability sampling technique that used a mixture of convenience and snowball sampling was used to collect responses from the participants based on the eligibility criteria. Twenty-two data collectors, who are medical students at Taif University, helped in distributing the questionnaires. An online pretested self-reported questionnaire was used to collect responses from the participants after obtaining their consent. The data were collected between the period of June to August 2022. On the basis of their relevance and prior identification in the literature as risk factors for neck and shoulder pain, several potentially important factors were assessed and identified.

The questionnaire consisted of three parts (Appendix A). The first part included sociodemographic details (age, gender, province of residence, employment status, occupation type, height, and weight). Part B, the second one, had items that measured the prevalence of neck and shoulder pain, general health status, general state of health, sleep disturbances, aerobic physical activity, time spent sitting, job satisfaction, and time spent working in a week). Responses to the question “Have you suffered any pain in your (body area) within the previous 12 months?” were used to determine the prevalence of lower back pain and neck and shoulder pain. Using a scale from 0 (no pain) to 9 (the greatest pain conceivable) as a reference point. We classified people with back pain into two groups: those with “pain” and “no pain.” In the third part, the dietary intake of each participant was recorded on a dietary chart. This chart had items that recorded the consumption of various food items such as beef, mutton/lamb, chicken, fish, vegetables, fruits, ice cream, chocolates, soft drinks, fruit juice, milk, tea, and coffee. The response options were: (a) Never, (b) 1-2 times/month, (c) once a week, (d) 2-4 times/week, (e) 5-6 times/week, (f) once daily, (g) 2-3 times/day, and (h) ≥ four times/day.

Ethical consideration

Ethical approval for the study was obtained from the research ethics committee of Taif University, Saudi Arabia (IRB No.: 44-069).

A pilot study was done on 20 participants to test the questionnaire for validity and reliability. Expert review and focused group discussion were utilized to evaluate the questionnaire’s content and face validity. We did not include the items that had a correlation coefficient of more than 0.70. The test’s internal consistency was evaluated (Chronbach’s α= 0.714), but the test’s test-retest reliability could not be determined due to a lack of available time. Online consent was taken after explaining the purpose and benefits of the study (mentioned as a statement of anonymity and confidentiality at the beginning of the questionnaire).

Statistical analysis and data management

All the collected information was tabulated on a Microsoft Excel sheet and then transferred to IBM Statistical Package for Social Sciences, Version 23 (SPSS Inc., Chicago, IL, USA) for data analysis. Descriptive statistics in the form of frequencies and percentages using suitable tables and figures were used to represent categorical data. Continuous variables were presented using mean and standard deviation. Comparison of continuous variables between categorical variables was evaluated using the Students’ “t” test and/or Analysis of variance. Any possible association between categorical variables was measured using Pearson’s chi-square test. Multivariate logistic regression was used to analyze key predictive factors for neck and shoulder pain. A p-value <0.05 was considered statistically significant.

Results

We received around 2,798 responses, of which 2,717 gave consent to participate and completed the total items in the survey. The socio-demographic analysis showed that 2,069 (76.2%) were females, 1,417 (52.2%) belonged to the age group of 18-25 years, 1,621 (59.7%) were single (unmarried), 989 (36.4%) were from the Western Province, 780 (28.7%) were employed, 1,716 (63.2%) had an executive, administrative or clerical duties type of job and 473 (17.4%) were obese (Table 1).

  N %
Gender Female 2069 76.2
Male 648 23.8
Age (years) 18-25 1417 52.2
26-35 547 20.1
36-45 420 15.5
46-55 239 8.8
56-60 58 2.1
>60 36 1.3
Marital status Single 1621 59.7
Married 1010 37.2
Divorced‎/Widow 86 3.2
Province Central province 652 24.0
Eastern province 224 8.2
Northern province 441 16.2
Southern province 411 15.1
Western province 989 36.4
Employment status Employed 780 28.7
Employed but currently on long leave 24 .9
Self-employed 115 4.2
Unemployed 532 19.6
Retired 95 3.5
Student 1171 43.1
Job type/nature Executive, administrative or clerical duties 1716 63.2
Manual labor or heavy machinery hazardous conditions 163 6.0
Manual labor or heavy machinery or exposure to certain hazardous conditions 184 6.8
Skilled or semi-skilled work and not exposed to hazardous conditions 654 24.1
Body Mass Index Underweight 309 11.4
Normal 1248 45.9
Overweight 687 25.3
Obese 473 17.4

The prevalence of neck pain (NP), shoulder pain (SP), and lower back pain (LBP) were found to be 48.1%, 47.6%, and 63.8%, respectively (Figure 1). 

Prevalence-of-MSPs-in-study-population-

The self-reported physical activities and personal habits are given in Table 2.

  N %
Current general state of health (self reported) Very poor 9 .3
Poor 55 2.0
Good 738 27.2
Very good 1091 40.2
Excellent 824 30.3
Sleep disturbances No 1179 43.4
Yes, Mild 1286 47.3
Yes, Severe 252 9.3
Aerobic physical activity per week Don’t do any aerobic physical activity 1015 37.4
Less than 30 min/week 749 27.6
30 to 59 min/week 521 19.2
60 to 89 min/week 179 6.6
More than 90 min/week 253 9.3
Heavy workouts [Running quickly – cycling quickly – rowing quickly – lifting weights] Don’t do 1758 64.7
Less than 30 min/week 518 19.1
30 to 59 min/week 251 9.2
60 to 89 min/week 79 2.9
More than 90 min/week 111 4.1
General physical activity per week Less than 30 min/week 1439 53.0
30 to 59 min/week 671 24.7
60 to 89 min/week 257 9.5
More than 90 min/week 350 12.9
Time spend sitting (per day) >10 hours 658 24.2
7-9 hours 806 29.7
4-6 hours 903 33.2
< 3 hours 350 12.9
Job satisfaction Very high 279 10.3
High 461 17.0
Moderate 912 33.6
Low 118 4.3
Unemployed/none 947 34.9
Time spent working /week >20 hours/week 1196 44.0
<20 hours/week 1521 56.0
Smoking status Current smoker 307 11.3
Ex-smoker 127 4.7
Never smoker 2283 84.0

We evaluated the relationship of the prevalence of various MSPs with the participants’ sociodemographic, physical activity, and other personal habits (Table 3). It was found that the prevalence of NP, SP, and LBP was significantly higher in females than in males (p<0.001). Three age groups (36-45 years, 46-55 years, and 56-60 years) showed significantly higher prevalence for NP, SP, and LBP (p<0.001). Those who were married reported significantly higher prevalence than others who were single or divorced/widowed (p<0.001). Those who were employed, but on a long-leave, self-employed and retired were found to have a significantly higher prevalence of NP, SP, and LBP (p<0.05). The employment nature didn’t show significant differences in the prevalence of NP and LBP, but the prevalence of SP was significantly higher among participants who did manual labor or heavy machinery or exposure to certain hazardous conditions (p=0.035). The prevalence of all three MSPs was significantly higher in participants who reported very poor and poor general health status (p<0.001). It was found that the prevalence of NP, SP, and LBP were significantly higher among participants who reported sleep disturbances either as mild or severe (p<0.001). Participants who had reported doing no aerobic physical activity showed significantly higher prevalence for all three MSPs than others (p<0.05). Similarly, a higher prevalence of MSPs was observed in participants who did not do any heavy workout activity than others (p<0.05). Participants who did general physical activity for <30 minutes showed a significantly higher prevalence of SP and LBP (p<0.05), but NP prevalence didn’t show any statistically significant differences (p=0.340). There were no statistically significant differences in the prevalence of all three MSPs observed for time spent sitting/day (p>0.05). The prevalence of all three types of MSPs was significantly higher in participants with lower job satisfaction than others (p<0.001). There was no statistically significant association observed for the prevalence of all three types of MSPs with time spent per week at work (p>0.05). The prevalence of SP was significantly higher in participants who were current smokers (p=0.036). Participants who were overweight and obese (BMI>25) significantly showed a higher prevalence of SP and LBP than others (p<0.05).

  Neck pain P value Shoulder pain P-value Lower back pain P-value
No Yes No Yes No Yes
Gender  
Female 1008 (48.7%) 1061 (51.3%) <0.001 997 (48.2%) 1072 (51.8%) <0.001 694 (33.5%) 1375 (66.5%) <0.001
Male 402 (62%) 246 (38%) 429 (66.2%) 219 (33.8%) 290 (44.8%) 358 (55.2%)
Age  
18-25 800 (56.5%) 617 (43.5%) <0.001 841 (59.4%) 576 (40.6%) <0.001 613 (43.3%) 804 (56.7%) <0.001
26-35 289 (52.8%) 258 (47.2%) 270 (49.4%) 277 (50.6%) 179 (32.7%) 368 (67.3%)
36-45 182 (43.3%) 238 (56.7%) 173 (41.2%) 247 (58.8%) 103 (24.5%) 317 (75.5%)
46-55 98 (41%) 141 (59%) 97 (40.6%) 142 (59.4%) 67 (28%) 172 (72%)
56-60 20 (34.5%) 38 (65.5%) 21 (36.2%) 37 (63.8%) 11 (19%) 47 (81%)
>60 21 (58.3%) 15 (41.7%) 24 (66.7%) 12 (33.3%) 11 (30.6%) 25 (69.4%)
Marital status  
Single 892 (55%) 729 (45%) <0.001 933 (57.6%) 688 (42.4%) <0.001 690 (42.6%) 931 (57.4%) <0.001
Married 470 (46.5%) 540 (53.5%) 452 (44.8%) 558 (55.2%) 273 (27%) 737 (73%)
Divorced‎/Widow 48 (55.8%) 38 (44.2%) 41 (47.7%) 45 (52.3%) 21 (24.4%) 65 (75.6%)
Employment status  
Employed 397 (50.9%) 383 (49.1%) 0.004 370 (47.4%) 410 (52.6%) <0.001 250 (32.1%) 530 (67.9%) <0.001
Employed but currently on long leave 9 (37.5%) 15 (62.5%) 11 (45.8%) 13 (54.2%) 8 (33.3%) 16 (66.7%)
Self-employed 50 (43.5%) 65 (56.5%) 46 (40%) 69 (60%) 37 (32.2%) 78 (67.8%)
Student 643 54.9%) 528 45.1%) 702 59.9%) 469 40.1%) 502 42.9%) 669 57.1%)
Retired 36 (37.9%) 59 (62.1%) 43 (45.3%) 52 (54.7%) 27 (28.4%) 68 (71.6%)
Unemployed 275 (51.7%) 257 (48.3%) 907 (52.9%) 809 (47.1%) 160 (30.1%) 372 (69.9%)
Employment nature  
Executive, administrative or clerical duties 894 (52.1%) 822 (47.9%) 0.201 907 (52.9%) 809 (47.1%) 0.035 620 (36.1%) 1096 (63.9%) 0.244
Manual labor or heavy machinery hazardous conditions 94 (57.7%) 69 (42.3%) 97 (59.5%) 66 (40.5%) 63 (38.7%) 100 (61.3%)
Manual labor or heavy machinery or exposure to certain hazardous conditions 85 (46.2%) 99 (53.8%) 81 (44%) 103 (56%) 55 (29.9%) 129 (70.1%)
Skilled or semi-skilled work and not exposed to hazardous conditions 337 (51.5%) 317 (48.5%) 341 (52.1%) 313 (47.9%) 246 (37.6%) 408 (62.4%)
General health state  
Excellent 603 (73.2%) 221 (26.8%) <0.001 590 (71.6%) 234 (28.4%) <0.001 473 (57.4%) 351 (42.6%) <0.001
Very good 541 (49.6%) 550 (50.4%) 547 (50.1%) 544 (49.9%) 369 (33.8%) 722 (66.2%)
Good 251 (34%) 487 (66%) 276 (37.4%) 462 (62.6%) 138 (18.7%) 600 81.3%)
Poor 15 (27.3%) 40 (72.7%) 12 (21.8%) 43 (78.2%) 4 (7.3%) 51 (92.7%)
Very poor 0 (0%) 9 (100%) 1 (11.1%) 8 (88.9%) 0 (0%) 9 (100%)
Sleep disturbances  
No 748 (63.4%) 431 (36.6%) <0.001 736 (62.4%) 443 (37.6%) <0.001 542 (46%) 637 (54%) <0.001
Yes, Mild 590 (45.9%) 696 (54.1%) 613 (47.7%) 673 (52.3%) 392 (30.5%) 894 (69.5%)
Yes, Severe 72 (28.6%) 180 (71.4%) 77 (30.6%) 175 (69.4%) 50 (19.8%) 202 (80.2%)
Aerobic physical activity  
Don’t do any aerobic physical activity 492 (48.5%) 523 (51.5%) 0.009 505 (49.8%) 510 (50.2%) 0.004 328 (32.3%) 687 (67.7%) <0.001
Less than 30 min/week 396 (52.9%) 353 (47.1%) 384 (51.3%) 365 (48.7%) 275 (36.7%) 474 (63.3%)
30 to 59 min/week 276 (53%) 245 (47%) 290 (55.7%) 231 44.3%) 206 (39.5%) 315 (60.5%)
60 to 89 min/week 92 (51.4%) 87 (48.6%) 90 (50.3%) 89 (49.7%) 61 (34.1%) 118 (65.9%)
More than 90 min/week 154 (60.9%) 99 (39.1%) 157 (62.1%) 96 (37.9%) 114 (45.1%) 139 (54.9%)
Heavy workout activity                  
Don’t do 871 (49.5%) 887 (50.5%) 0.003 880 (50.1%) 878 (49.9%) <0.001 571 (32.5%) 1187 (67.5%) <0.001
Less than 30 min/week 277 (53.5%) 241 (46.5%) 277 (53.5%) 241 (46.5%) 219 (42.3%) 299 (57.7%)
30 to 59 min/week 149 (59.4%) 102 (40.6%) 147 (58.6%) 104 (41.4%) 108 (43%) 143 (57%)
60 to 89 min/week 43 (54.4%) 36 (45.6%) 44 (55.7%) 35 (44.3%) 30 (38%) 49 (62%)
More than 90 min/week 70 (63.1%) 41 (36.9%) 78 (70.3%) 33 (29.7%) 56 (50.5%) 55 (49.5%)
General physical activity                  
Less than 30 min/week 739 (51.4%) 700 (48.6%) 0.340 739 (51.4%) 700 (48.6%) 0.049 496 (34.5%) 943 (65.5%) 0.003
30 to 59 min/week 338 (50.4%) 333 (49.6%) 348 (51.9%) 323 (48.1%) 238 (35.5%) 433 (64.5%)
60 to 89 min/week 137 (53.3%) 120 (46.7%) 131 (51%) 126 (49%) 92 (35.8%) 165 (64.2%)
More than 90 min/week 196 (56%) 154 (44%) 208 (59.4%) 142 (40.6%) 158 (45.1%) 192 (54.9%)
Time spend sitting/per day                  
>10 hours 341 (51.8%) 317 (48.2%) 0.301 340 (51.7%) 318 (48.3%) 0.863 262 (39.8%) 396 (60.2%) 0.083
7-9 hours 411 (51%) 395 (49%) 426 (52.9%) 380 (47.1%) 270 (33.5%) 536 (66.5%)
4-6 hours 460 (50.9%) 443 (49.1%) 470 (52%) 433 (48%) 321 (35.5%) 582 (64.5%)
Less than 3 hours 198 (56.6%) 152 (43.4%) 190 (54.3%) 160 (45.7%) 131 (37.4%) 219 (62.6%)
Job satisfaction                  
Very high 159 (57%) 120 (43%) <0.001 168 (60.2%) 111 (39.8%) <0.001 138 (49.5%) 141 (50.5%) <0.001
High 278 (60.3%) 183 (39.7%) 268 (58.1%) 193 (41.9%) 182 (39.5%) 279 (60.5%)
Moderate 415 (45.5%) 497 (54.5%) 425 (46.6%) 487 (53.4%) 291 (31.9%) 621 (68.1%)
Low 52 (44.1%) 66 (55.9%) 59 (50%) 59 (50%) 22 (18.6%) 96 (81.4%)
None 506 53.4%) 441 46.6%) 506 53.4%) 441 46.6%) 351 37.1%) 596 62.9%)
Time spend per week at work                  
<20 hours/week 800 52.6%) 721 47.4%) 0.907 801 52.7%) 720 47.3%) 0.834 559 36.8%) 962 63.2%) 0.512
>20 hours/week 610 51%) 586 49%) 625 52.3%) 571 47.7%) 425 35.5%) 771 64.5%)
Smoking status                  
Current smoker 143 46.6%) 164 53.4%) 0.097 140 45.6%) 167 54.4%) 0.036 106 34.5%) 201 65.5%) 0.490
Ex-smoker 62 48.8%) 65 51.2%) 69 54.3%) 58 45.7%) 41 32.3%) 86 67.7%)
Never smoker 1205 (52.8%) 1078 (47.2%) 1217 (53.3%) 1066 (46.7%) 837 (36.7%) 1446 (63.3%)
Body mass Index                  
Underweight 161 (52.1%) 148 (47.9%) 0.054 168 (54.4%) 141 (45.6%) 0.011 136 (44%) 173 (56%) <0.001
Normal 681 (54.6%) 567 (45.4%) 692 (55.4%) 556 (44.6%) 504 (40.4%) 744 (59.6%)
Overweight 339 (49.3%) 348 (50.7%) 335 (48.8%) 352 (51.2%) 217 (31.6%) 470 (68.4%)
Obese 229 (48.4%) 244 (51.6%) 231 (48.8%) 242 (51.2%) 127 (26.8%) 346 (73.2%)

The Diet Diversity chart of the participants is given in Table 4. The foods were then subgrouped into five categories that are a) Meat diary and products (Beef, Mutton, Chicken, Fish and milk), b) Fruits and Vegetables, c) sweetened and high carb food (Ice cream, chocolates, soft drinks, fruit juice), f) Tea, and e) Coffee. The scores were given based on the frequency of consumption, which ranges from 1 (never) to 8 (>4 times/day). The scores for each food item in each subgroup were added to get a total score for each subgroup, where a higher score indicated increased consumption. We compare the dietary diversity and the prevalence of three types of MSPs. There were no statistically significant differences in dietary scores for Meat, dairy and products, Fruits and Vegetables, and Sweetened and high carb food between participants who had MSPs and those who didn’t. At the same time, participants who had increased coffee consumption had a significantly higher prevalence of SP and LBP (P<0.05). Also, LBP prevalence was significantly higher in participants who had consumed more tea.

  Never 1-2 times/month Once/week 2-4 times/week 5-6 times/week Once/day 2-3/day >4 times/day Mean (SD)
Beef 1290 (47.5%) 735 (27.1%) 372 (13.7) 245 (9) 34 (1.3) 26 (1) 11 (04) 4 (0.1) 1.95 (1.2)
Mutton 800 (29.4) 866 (31.9) 568 (20.9) 372 (13.7) 53 (2) 38 (1.4) 15 (0.6) 5 (0.2) 2.34 (1.2)
Chicken 127 (4.7) 186 (6.8) 356 (13.1) 1236 (45.5) 375 (13.8) 317 (11.7) 95 (3.5) 25 (0.9) 4.10 (1.4)
Fish 639 (23.5) 1378 (50.7) 436 (16) 179 (6.6) 43 (1.6) 27 (1) 11 (0.4) 4 (0.1) 2.17 (1.0)
Vegetables 146 (5.4) 299 (11) 519 (19.1) 868 (31.9) 351 (12.9) 321 (11.8) 151 (5.6) 62 (2.3) 4.05 (1.6)
Fruit 151 (5.6) 484 (17.8) 649 (23.9) 754 (27.8) 247 (9.1) 262 (9.6) 109 (4) 61 (2.2) 3.73 (1.6)
Ice cream 367 (13.5) 993 (36.5) 671 (24.7) 409 (15.1) 115 (4.2) 102 (3.8) 40 (1.5) 20 (0.7) 2.81 (1.4)
Chocolates 216 (7.9) 502 (18.5) 663 (24.4) 713 (26.2) 239 (8.8) 225 (8.3) 107 (3.9) 52 (1.9) 3.6 (1.6)
Soft Drinks 588 (21.6) 585 (21.5) 545 (20.1) 524 (19.3) 180 (6.6) 154 (5.7) 97 (3.6) 44 (1.6) 3.07 (1.7)
Fruit Juice 401 (14.8) 758 (27.9) 701 (25.8) 501 (18.4) 162 (6) 114 (4.2) 47 (1.7) 33 (1.2) 2.99 (1.5)
Milk 529 (19.5) 567 (20.9) 509 (18.7) 512 (18.8) 190 (7) 271 (10) 94 (3.5) 45 (1.7) 3.25 (1.8)
Tea 357 (13.1) 366 (13.5) 421 (15.5) 600 (22.1) 273 (10) 346 (12.7) 217 (8) 137 (5) 3.98 (2)
Coffee 314 (11.6) 262 (9.6) 337 (12.4) 598 (22) 327 (12) 405 (14.9) 297 (10.9) 177 (6.5) 4.34 (2)

We compare the dietary diversity and the prevalence of three types of MSPs (Table 5). There were no statistically significant differences in dietary scores for Meat, dairy and products, Fruits and Vegetables, and Sweetened and high carb food between participants who had MSPs and those who did not. At the same time, participants who had increased coffee consumption had a significantly higher prevalence of SP and LBP (P<0.05). Also, LBP prevalence was significantly higher in participants who had consumed more tea.

  Neck pain P-value Shoulder pain P-value Lower back pain P-value
Meat diary & products No 13.9 (3.9) 0.215 13.9 (4.0) 0.297 13.8 (4.0) 0.953
Yes 13.7 (3.9) 13.7 (3.8) 13.8 (3.9)
Fruits & Vegetables No 3.5 (1.3) 0.738 3.5 (1.3) 0.537 3.5 (1.3) 0.629
Yes 3.5 (1.3) 3.5 (1.3) 3.5 (1.3)
Sweetened & high carb food No 5.8 (1.8) 0.120 5.8 (1.8) 0.421 5.7 (1.8) 0.128
Yes 5.9 (1.8) 5.8 (1.8) 5.8 (1.8)
Tea No 4.0 (2.0) 0.972 4.0 (2.0) 0.404 3.9 (2.0) 0.011
Yes 4.0 (2.0) 4.0 (2.0) 4.1 (2.0)
Coffee No 4.3 (2.0) 0.318 4.3 (2.1) 0.021 4.2 (2.1) 0.007
Yes 4.38 (2.05) 13.9 (4.0) 4.4 (2.0)

Multivariate logistic regression was done to predict the risk factors and protective factors for MSPs (Table 6). It was found that being a female (OR=1.78 [1.41-2.25], p<0.001), married (OR=1.58 [1.34-1.86], p<0.001), and poor general health status (OR=3.78 [2.2-6.49], p<0.001), sleep disturbances (OR=2.46 (2.04-2.97), p<0.001) and poor job satisfaction (OR=1.29 [1.05-1.60], p=0.016) were independently associated with the prevalence of MSPs.

  B Std. Error Wald P-value OR 95% Confidence Interval OR
Lower Bound Upper Bound
                 
Gender =Female -.578 .119 23.534 <0.001 1.78 1.41 2.25
Age >56 .395 .242 2.664 0.103 1.48 0.92 2.38
Marital status= Married .458 .083 30.495 <0.001 1.58 1.34 1.86
BMI >25 -.028 .120 .055 0.814 0.97 0.77 1.23
General health status = poor/very poor -1.330 .276 23.240 <0.001 3.78 2.20 6.49
Sleep disturbances = Yes .899 .096 87.669 <0.001 2.46 2.04 2.97
Aerobic physical exercise= =<30 minutes -.283 .189 2.233 0.135 0.75 0.52 1.09
Heavy workouts =<30 minutes -.253 .299 .714 0.398 0.78 0.43 1.40
Sitting hours >6 hours .119 .091 1.709 0.191 1.13 0.94 1.35
Job satisfaction = poor -.258 .107 5.794 0.016 1.29 1.05 1.60
  Smoking -.321 .191 0.635 0.172 1.42 0.87 2.92

Discussion

The findings of this study showed that female participants, being married, those with poor general health and sleep disturbances, and those with poor job satisfaction were independently associated with developing all three MSPs. Our findings are consistent with previous studies in different parts of the world. Rashid et al. [15] observed that women on medical leave who had both high levels of workplace stress and MSP were significantly less likely to return to work. Chinese researchers Xu et al. observed that those with mental illness, particularly those with depression, were more likely to suffer from chronic MSP than those without mental illness [16]. Hallman et al. found that women who regularly engaged in intense physical activity were more likely to have a worsening of their preexisting NP over time. Also, walking, running, or cycling, were associated with lowering NP severity with no major gender differences [17]. Other factors like age, obesity, limited musculoskeletal function, higher cognitive work demands, poor working atmosphere, low social support, heavy physical workload, lack of autonomy, and insufficient physical activity all have a negative impact on the work abilities of long-term MSP patients [18,19]. Keeping active and exercising for at least 150 minutes per week at a moderate intensity or 75 minutes per week at a strong intensity is one of the important things individuals can do for their health. Additional health benefits can be obtained from engaging in moderate physical activity for up to five hours per week or intense exercises for up to 2.5 hours per week [20].

It is widely acknowledged that a lack of exercise contributes to NP and poor health [20-22]. Still, it appears that there are substantial differences in the way these factors interact among different people [22]. Cardiovascular diseases, cancer, diabetes, and poor sleep are just some of the medical problems that have been found to improve with physical activity [20]. The majority of our participants reported having relatively modest levels of overall physical activity. However, it was not possible to draw any definite conclusions about cause and effect in the present investigation. For instance, those who engaged in more vigorous exercise may have experienced less NP, and those who did not may have been more willing to perform moderate to vigorous exercises. A lower incidence of NP was found in a previous study [21] when participants engaged in physical exercise for at least five hours per week; however, the intensity level of the activity was not specifically described in that study.

The present research found that all three types of MSPs were associated with disrupted sleep. Our findings support the previous pieces of evidence that reported an association between sleep disturbances and MSPs. It has been previously observed by Holm et al. [23] and Finan et al. [24] that those who report poor job performance and sleep disturbances have a greater chance of acquiring neck and lower back pain. However, it is not clear whether sleep disturbances lead to MSPs or MSPs related to sleep disturbances. Evidence shows that Insomnia is a common complaint among those who live with chronic pain [25]. In light of this growing body of research, it seems reasonable to conclude that sleep deprivation may contribute to the onset of musculoskeletal discomfort. According to past research [23], shorter sitting hours are associated with less likelihood of developing neck and back discomfort. In contrast, we detected no statistically significant association between sitting time spent and the prevalence of MSPs. Pain might be the result of doing the same thing over and over again without taking sufficient sitting breaks [26] or from stress [27]. One further study found that blue-collar employees who sat more during the workday had a lower likelihood of experiencing NP [28]. Therefore, it is likely that there is a great deal of individual variation in the amount of time spent sitting and relaxing in relation to the physical demands placed on muscles.

Numerous clinical and experimental studies have demonstrated that cigarette smoking negatively impacts the musculoskeletal system and negatively impacts the outcome of a variety of orthopedic illnesses and surgical interventions [29,30]. Our findings showed that smokers had a significantly higher prevalence of SP, but there was no association observed between NP and LBP. The therapeutic importance of this secondary but crucial problem is often neglected, despite the fact that the number of smokers is still high across the world. Since smoking has been linked to an increase in negative psychological effects, it was hypothesized that people living with chronic MSP would be driven to smoke because they believe it will help them deal with the pain they are experiencing. However, some studies [31,32] have disproved this theory by showing that the relationship persists even after controlling anxiety and mood disorders. In the current research, BMI > 25 was found to have experienced more LBP and NP than others. There is some evidence to suggest that obesity has both biomechanical and meta-inflammatory impacts on the spine [33]. On the other hand, body mass index (BMI) measures of obesity are not a precise indicator of adiposity since they do not distinguish between fatty and lean mass. Furthermore, males and females have distinct body compositions [34,35], with women having a larger fat content. A meta-analysis found that being overweight or obese is associated with LBP more strongly in females than in males [36]. Although biomechanical parameters linked to spinal loading are associated with MSPs, particularly LBP, our findings suggest that a systemic metabolic mechanism associated with excess adipose tissue may potentially play a role in back pain and impairment.

Our study findings did not show a significant impact of diet on MSPs. Fruits, vegetables, and whole grains are among the foods suggested to be effective for easing MSPs [37]. Omega-3 fatty acids are found in fish oil [38], olive oil [39], turmeric [40], and green tea [41]; resveratrol is found in grapes and wine [42], capsaicin is found in pepper, and various flavonoids found in cabbage [43], cocoa [44], apple [45], and citrus fruits [46] have all been evaluated for their anti-inflammatory effects and/or their therapeutic effect on MSPs pain. Chronic inflammation and oxidative stress [47] are the primary determinants of chronic pain [37], and studies evaluating the benefits of nutritional interventions suggest that some foods may have anti-inflammatory activities, neutralizing these processes. There is evidence that some diets can modulate the immune system and pain perception, hence reducing functional loss due to musculoskeletal disorders and enhancing the quality of life [37,48]. However, the mechanisms behind these interactions are still unknown, and more research is needed [49] since various foods have distinct qualities and methods that operate to alleviate pain and other musculoskeletal problems.

Due to the cross-sectional design of our research, we were unable to establish any causative relationships between the various factors and MSPs. This is the primary limitation of our study. Self-reported estimates of exercise activity levels, general health condition, and diet have also been questioned, which is another limitation. To test these characteristics objectively in every single individual who is a participant in a large population-based cohort with many participants would be incredibly expensive and possibly not even practicable.

Conclusions

The current study found that female gender, married, poor general health status, poor sleep quality, and poor job satisfaction were associated with MSPs. However, no significant association was observed between different foods consumed and MSPs. More high-quality studies are needed to evaluate the relationship between MSP and diet. Insights into the relationship between upper body pain, physical activity, sleep, and health may be useful in developing effective ways to prevent and manage neck, shoulder, and lower back pain. Despite the negative effects of smoking on osteoarthritis, rheumatoid arthritis, intervertebral disc degeneration, reduced muscle mass and strength, muscular discomfort, tendons degeneration, and ruptures, smoking was not independently associated with MSP in our study. Some individuals may have quit smoking due to health concerns, but tobacco smoke may also have altered their pain perception threshold. Initiatives to encourage healthy habits should be an organizational policy priority to assist employees in staying healthy and coping with work, especially given the relatively high incidence of unhealthy lifestyles in the general working population. In order to fully comprehend the relationships between MSP and health, sleep difficulties, and aerobic activity, long-term longitudinal studies are warranted.