SUMMARY
OBJECTIVE:
Musculoskeletal disorders are highly prevalent among healthcare workers due to physically demanding tasks and stressful work conditions. These disorders contribute to decreased work performance, pain, and impaired quality of life. Sleep quality is an essential factor in overall health and has been linked to pain perception and musculoskeletal health. However, the relationship between musculoskeletal disorders and sleep quality remains unclear. The aim of this study was to investigate the prevalence of musculoskeletal disorders among healthcare workers, identify associated risk factors, and examine the relationship between musculoskeletal disorders and sleep quality.
METHODS:
This cross-sectional study was conducted in a state hospital in Kırşehir, Turkey, with 249 healthcare workers. Participants completed a sociodemographic questionnaire, the Cornell Musculoskeletal Disorders Questionnaire to assess musculoskeletal disorders, and the Pittsburgh Sleep Quality Index to evaluate sleep quality. Statistical analyses included Pearson's correlation test, t-test, and analysis of variance to examine associations between musculoskeletal disorders, sleep quality, and other risk factors.
RESULTS:
A significant relationship was found between musculoskeletal disorders and sleep quality (p<0.001). Healthcare workers with poor sleep quality reported higher Cornell Musculoskeletal Disorders Questionnaire scores. Additionally, musculoskeletal disorder prevalence was significantly associated with working hours (p=0.018) and income level (p=0.047). Nurses had the highest musculoskeletal disorder scores among occupational groups.
CONCLUSION:
Musculoskeletal disorders in healthcare workers are influenced by sleep quality, working hours, and income level. Ergonomic interventions and policies to improve sleep quality may help reduce musculoskeletal disorder prevalence and enhance overall well-being in this workforce.
KEYWORDS: Musculoskeletal diseases, Risk factors, Sleep quality, Healthcare workers
INTRODUCTION
Research in the field of occupational health has identified various physical and psychosocial risk factors that cause occupational musculoskeletal disorders (MSDs). These studies show that physically demanding work practices such as lifting or carrying heavy loads, tiring positions, awkward postures, and repetitive movements, as well as stressful working conditions, directly lead to MSDs 1 .
Healthcare workers such as nurses, midwives, surgeons, physiotherapists, and dentists are at a high risk of musculoskeletal problems due to their intense work tempo, repetitive movements, standing for long periods, lifting heavy loads, and non-ergonomic working positions. Studies show that the prevalence of MSDs exceeds 80% in these groups 2,3 . Pain, especially in the low back, neck, shoulder, and knee areas, can lead to loss of work power, decreased professional performance, and deterioration of quality of life 4 .
Sleep is a universal function in all living species, accounting for approximately one-third of human life. Insufficient or poor-quality sleep can cause significant disorders across multiple systems, including the endocrine system, metabolism, cognitive functions, and the nervous system 5,6 .
It is observed that pain and sleep disorders often occur together 7 . However, the causal relationship between these two conditions has not yet been clearly defined 8 . Prospective studies examining the relationship between sleep and pain show that sleep disorders can increase the severity of pain and that pain can negatively affect sleep quality 9 .
Factors such as intense work, ergonomic inadequacy, and shift work create both pain and discomfort in the musculoskeletal system and disrupt sleep patterns, reducing the quality of rest. This situation can negatively affect the general health and work efficiency of healthcare workers. The aim of this research was to determine MSDs and risk factors in healthcare workers and to reveal their relationship with sleep quality.
METHODS
This study was conducted with hospital staff in a state hospital in Kırşehir province. It was determined by the decision of the local ethics committee that there was no ethical problem in conducting the study (139-17.09.2024). After the participants read, understood, and approved the informed consent form, those who met the inclusion criteria were assessed for sociodemographic information, musculoskeletal symptoms, and sleep quality.
The sociodemographic information of the participants was evaluated with the survey prepared by the researchers, musculoskeletal symptoms were evaluated using the "Cornell Musculoskeletal Disorders Questionnaire," (CMDQ) and sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI).
The sample size was calculated to be 10 times the number of questions in the survey with the highest number of questions among the surveys used in the study, as suggested by Bryman and Cramer 10 . The survey with the highest number of questions in our study was the "CMDQ" and the number of questions was 20. Accordingly, the minimum sample size was found to be 200, based on 10 times the 20 survey questions. By including additional reserve recruitments, 249 people were recruited for our research.
Cornell Musculoskeletal Disorders Questionnaire
The CMDQ is a measurement tool developed to assess MSDs. The Turkish validity and reliability study was conducted in 2008. The questionnaire evaluates the frequency, severity, and impact of pain, aches, or discomfort in the last week. A total of 20 body regions are scored separately, and the total discomfort score ranges from 0 to 90. When calculating the score, frequency, severity, and work disability are multiplied. As the CMDQ score increases, the frequency, severity, and negative impact of pain on work also increase 11 .
Pittsburgh Sleep Quality Index
The PSQI was used to assess sleep quality. This scale allows sleep to be determined as good or bad and to be evaluated quantitatively. The survey consists of a total of 24 questions, 19 of which are answered by the individual and five by the roommate, but this part is not included in the scoring. The scale evaluates seven components: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleeping pills, and daytime dysfunction. The total score ranges from 0 to 21. Scores of five and below are considered good sleep quality, and scores above five are considered poor sleep quality 12,13 .
Statistical analysis
The general characteristics of the study population were calculated as a percentage distribution. The relationship between continuous variables and MSDs was evaluated using Pearson's correlation analysis. Whether there was a significant difference in terms of MSDs in categorical variables was analyzed with analysis of variance (ANOVA) and t-test. The significance level was accepted as p<0.05.
RESULTS
A total of 249 healthcare workers, 106 males and 143 females, participated in the study. General characteristics of the study population are shown in Table 1. Among the continuous variables, only working hours were found to be significantly associated with MSDs. In addition, a significant relationship was found between MSDs and all components of sleep quality (except habitual sleep efficiency) (Table 2). When evaluating whether there was a significant difference in terms of MSDs in categorical variables, it was seen that there was a significant difference in income level and sleep quality. Accordingly, the prevalence of MSDs was significantly higher in individuals with low income levels compared to those with middle income levels. In addition, MSDs were significantly higher in participants with low sleep quality compared to those with good sleep quality (Table 3).
Table 1. General characteristics of the study population.
| Variable | Category | n | % |
|---|---|---|---|
| Gender | Male | 106 | 42.6 |
| Female | 143 | 57.4 | |
| Marital status | Single | 75 | 30.1 |
| Married | 171 | 68.7 | |
| Widowed | 3 | 1.2 | |
| Education level | Primary | 1 | 0.4 |
| Secondary | 1 | 0.4 | |
| High school | 32 | 12.9 | |
| Higher education | 204 | 81.9 | |
| M.Sc./Ph.D. | 11 | 4.4 | |
| Number of children | 0 | 100 | 40.2 |
| 1 | 43 | 17.3 | |
| 2 | 75 | 30.1 | |
| 3 | 25 | 10.0 | |
| 4 | 6 | 2.4 | |
| Occupation | Driver | 19 | 7.6 |
| Paramedic | 121 | 48.6 | |
| Doctor | 11 | 4.4 | |
| Technician | 19 | 7.6 | |
| Nurse | 44 | 17.7 | |
| Office worker | 31 | 12.4 | |
| Worker | 4 | 1.6 | |
| Employment type | Daytime | 79 | 67.9 |
| On duty | 170 | 30.9 | |
| Income level (TL) | Low | 169 | 67.9 |
| Medium | 77 | 30.9 | |
| High | 3 | 1.2 | |
| Smoking | Absent | 169 | 67.9 |
| Present | 80 | 32.1 | |
| Alcohol | Absent | 203 | 89.8 |
| Present | 23 | 10.2 | |
| Exercise habit | Absent | 180 | 72.3 |
| Present | 69 | 27.7 | |
| Exercise type | Resistive | 13 | 5.2 |
| Aerobic | 38 | 15.3 | |
| Resistive+aerobic | 4 | 1.6 | |
| Chronic disease | Diabetes | 14 | 21.9 |
| Hyperlipidemia | 3 | 4.7 | |
| Anemia | 14 | 21.9 | |
| Hypertension | 12 | 18.8 | |
| COPD | 2 | 3.1 | |
| CAD | 2 | 3.1 | |
| Others | 19 | 29 | |
| Occupational positions | Heavy liftinga | 40 | 16.1 |
| Bending forwardb | 32 | 12.9 | |
| Sitting for long periodsc | 56 | 22.5 | |
| Standing for long periodsd | 40 | 16.1 | |
| a+b | 17 | 6.8 | |
| a+b+c | 33 | 13.3 | |
| a+b+d | 31 | 12.4 |
n: number of participants; COPD: chronic obstructive pulmonary disease; CAD: coronary artery disease.
heavy lifting;
bending forward;
sitting for long periods;
standing for long periods.
Table 2. Correlations between continuous variables and Cornell Musculoskeletal Disorders Questionnaire scores.
| Variables | r | p | |
|---|---|---|---|
| Age | -0.06 | 0.337 | |
| Height | -0.11 | 0.109 | |
| Weight | -0.01 | 0.709 | |
| BMI | 0.03 | 0.616 | |
| Year of profession | -0.07 | 0.273 | |
| Duration of work | -0.16 | 0.018 * | |
| Smoke consumption | 0.10 | 0.125 | |
| Exercise habit duration | -0.06 | 0.638 | |
| Exercise frequency (day/week) | -0.08 | 0.564 | |
| Exercise duration (min/day) | 0.07 | 0.613 | |
| Number of steps | 0.06 | 0.372 | |
| Sleep quality | |||
| Subjective sleep quality | 0.22 | 0.001 * | |
| Sleep latency | 0.24 | 0.001 * | |
| Sleep duration | 0.20 | 0.003 * | |
| Habitual sleep efficiency | 0.02 | 0.774 | |
| Sleep disturbances | 0.373 | <0.001 * | |
| Use of sleeping medications | 0.154 | 0.028 * | |
| Daytime dysfunction | 0.22 | 0.001 * | |
| Total sleep quality | 0.33 | <0.001 * | |
p<0.05, r: correlation coefficient; BMI: body mass index. Statistically significant values are denoted in bold.
Table 3. Comparison of musculoskeletal disorders across categorical variables.
| Variable | Category | CMD score (mean±SD) | T or F statistic | p |
|---|---|---|---|---|
| Gender | Male | 21.53±50.75 | -2.316 | 0.022 * |
| Female | 51.40±128.75 | |||
| Marital status | Single | 28.57±50.52 | 0.563 | 0.570 |
| Married | 44.95±123.107 | |||
| Widowed | 16.66±15.27 | |||
| Education level | High school | 15.64±37.66 | ||
| Higher education | 43.73±115.917 | 0.509 | 0.729 | |
| M.Sc./Ph.D. | 80.80±70.51 | |||
| Number of children | 0 | 35.07±70.22 | 0.506 | 0.731 |
| 1 | 39.00±154.48 | |||
| 2 | 38.04±14.72 | |||
| 3 | 68.04±132.98 | |||
| 4 | 9.75±11.32 | |||
| Occupation | Driver | 8.00±22.06 | 1.245 | 0.285 |
| Paramedic | 33.47±113.54 | |||
| Doctor | 24.42±35.46 | |||
| Technician | 31.55±53.98 | |||
| Nurse | 76.39±145.44 | |||
| Office worker | 33.80±73.66 | |||
| Worker | 9.50±19.00 | |||
| Employment type | Daytime | 47.53±87.90 | 0.817 | 0.447 |
| On duty | 35.60±115.10 | |||
| Income level (TL) | Lowa | 28.17±79.46 | 2.970 |
0.047
*
(a and b) |
| Mediumb | 66.42±147±99 | |||
| Highc | 10.00±17.32 | |||
| Smoking | Absent | 34.82±95.43 | -0.946 | 0.345 |
| Present | 49.83±125.73 | |||
| Alcohol | Absent | 41.08±112.05 | 0.355 | 0.723 |
| Present | 32.33±39.15 | |||
| Exercise habit | Absent | 36.26±92.00 | -0.743 | 0.458 |
| Present | 48.55±136.23 | |||
| Exercise type | Resistive | 28.22±38.97 | 0.554 | 0.579 |
| Aerobic | 72.60±177.93 | |||
| Resistive+aerobic | 4.5.±6.60 | |||
| Chronic disease | Diabetes | 40.00±85.72 | 1.458 | 0.221 |
| Hyperlipidemia | 6.00±8.48 | |||
| Anemia | 127.72±268.01 | |||
| Hypertension | 151.22±215.28 | |||
| COPD | - | |||
| CAD | 300.00±424±26 | |||
| Others | 44.70±85.64 | |||
| Occupational positions | Heavy lifting | 6.89±23.35 | 1.509 | 0.215 |
| Bending forward | 45.23±60.41 | |||
| Sitting for long periods | 30.15±96.29 | |||
| Standing for long periods | 48.39±110.88 | |||
| Sleep quality | Lowa | 81.36±121.98 | 3.658 |
0.037
*
(a–c) |
| Mediumb | 46.21±118.56 | |||
| Highc | 16.50±70.57 |
p<0.05, CMD: Cornell Musculoskeletal Disorders Questionnaire; COPD: chronic obstructive pulmonary disease, CAD: coronary artery disease; SD: standard deviation; TL: Turkish liras. Statistically significant values are denoted in bold.
low;
medium;
high.
DISCUSSION
This study, which was conducted to examine the factors affecting MSDs in healthcare workers and the relationship between MSDs and sleep quality, found that MSDs in healthcare workers were related to working hours and sleep quality. It was also found that healthcare workers showed significant differences in terms of MSDs according to their income levels and sleep quality levels. Numerous studies in the literature have examined MSDs among healthcare workers. For example, according to the study conducted by Zaheer et al., the highest prevalence of work-related musculoskeletal problems was found among medical technologists, followed by nurses 14 . Another study found that nurses and doctors have higher rates of MSDs than other healthcare professions 15 . Similarly, our study found that nurses are prone to musculoskeletal problems. According to the findings of the study, it was determined that musculoskeletal problems differ between occupational groups. This situation can be explained by the fact that these occupational groups are physically more strained. In addition, a significant relationship was found between working hours and musculoskeletal problems in our study. This is an expected result considering the working hours and increasing workload.
A 7-year cross-sectional study by Pan et al. found that low-income individuals had poorer musculoskeletal health than high-income individuals 16 . In another study, the primary sociodemographic factors affecting MSDs of homemakers were found to be household income and body mass index. In this study, a significant difference was observed between income level and MSDs. It was determined that individuals with low income levels had more MSDs. This situation may be related to the fact that individuals with low income levels work under more challenging physical conditions and benefit less from ergonomic conditions. However, more research is needed to explain the causal relationship between MSDs and income level.
One of the most striking findings of this study is the relationship between MSDs and sleep quality. The findings showed that individuals with poor sleep quality were significantly more likely to have MSDs. The findings of a systematic review and meta-analysis covering 16 articles and 11 different study populations provide evidence, albeit with very low certainty, that baseline sleep problems/disorders are a risk factor for chronic musculoskeletal problems in both the short and long term 17 . Another study showed that nurses’ sleep duration, time to fall asleep, and sleep quality significantly contributed to the development of neck and upper back pain 18 . Although sleep quality is largely assessed subjectively, it is known that sleep disorders are more common, especially in individuals who work shifts. It can be said that a significant portion of healthcare professionals also work shifts. The fact that sleep disorders are associated with MSDs can be attributed to the body's regeneration and repair processes being affected. Sleep has a critical role in the repair of muscle tissue and general well-being. In addition, it is thought that sleep disorders cause an increase in inflammatory markers, which in turn affects chronic pain mechanisms. It is known that sleep insufficiency lowers the pain threshold and increases the perception of MSDs 9 .
The findings of this study reveal the necessity of ergonomic arrangements and improvements in the work environment to reduce MSDs in healthcare workers. Workload adjustments and the use of appropriate supportive equipment are recommended, especially for high-risk groups such as nurses and paramedics.
In addition, work order improvements that will increase sleep quality are also of great importance. Rearranging shift hours can help healthcare workers optimize their sleep cycles.
In conclusion, it has been shown that MSDs in healthcare workers are affected by both individual and environmental factors and that sleep quality plays an important role in these disorders. Therefore, strategies to improve these two factors are critical to improving the overall health and work performance of healthcare workers.
Footnotes
Funding: none.
DATA AVAILABILITY STATEMENT
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.