Prevalence and risk factors for self-reported work- related musculoskeletal disorder symptoms among nurses in a tertiary public hospital in Botswana

ORIGINAL RESEARCH

PEER REVIEWED

K Kgakge,1 PK Chelule,1 LI Zungu2


1School of Public Health, Sefako Makgatho University, Garankuwa, South Africa
2Department of Health Studies, University of South Africa, Pretoria, South Africa

Correspondence: Prof. Paul Chelule, Department of Public Health, Sefako Makgatho University, PO Box 215, Medunsa, 0204, South Africa. e-mail: paul.chelule@smu.ac.za

ABSTRACT
Background: Globally, work-related musculoskeletal disorders (WMSDs) have emerged as a major public health problem among healthcare workers; particularly among the nursing personnel who are at the forefront of the healthcare delivery system. 
Objective: This cross-sectional survey was conducted to determine the prevalence of WMSD symptoms among nurses in a tertiary public hospital in Botswana, and their associated risk factors.
Methods: A self-administered questionnaire was used to collect data from 220 nurses. The data were analysed using Stata version 13. Results regarding prevalence and risk factors were presented as frequencies and percentages. The risk factors (independent variables) were evaluated for associations with reported work-related musculoskeletal (WMS) pain (dependent variable), using univariate and multivariable linear regression analyses.
Results: The prevalence of WMS pain was 90.9%, with the lower back being most commonly affected (reported by 68.6% of nurses). Work experience (AOR = 0.53, 95%CI 0.3 to 0.95, p = 0.033) and working while bending (AOR = 3.3, 95%CI 1.03 to 10.55, p = 0.043) were significant risk factors for WMS pain.
Conclusion: There is a need for education and training programmes to help prevent WMSDs among nurses and hence increase efficiency in patient care.

Keywords: work-related MSDs, prevalence, risk factors, nurses, hospital, wellness.

INTRODUCTION
Work-related musculoskeletal disorders (WMSDs) are defined as occupational injuries or episodes of pain that involve muscles, tendons, and nerves.1 These painful episodes include carpal tunnel syndrome, tendonitis, sprains, strains, tears and tension neck syndromes.1 WMSDs are regarded as one of the leading occupational problems and are associated with increasing compensation and health costs, reduced productivity due to sick leaves, and reduced quality of life. They have an economic toll on the individuals, organisation and society as a whole.2 

Nursing professionals are ranked as the group most affected by WMSDs because they comprise the majority of employees in the healthcare profession, and undertake labour-intensive work that involves manual handling of patients on a daily basis.3-7  For example, in 2017, the prevalence of WMSDs in public hospital nurses in South Africa was around 84%.8  Among nurses, the prevalence of WMSDs in different body regions ranges from 16.5% to 66% and includes, in increasing order of prevalence, hips, neck, knee, shoulder, upper back, ankle and foot, and lower back.9-11 The global prevalence of WMSDs in nurses is higher than 60% but varies between countries, from 60% in the United States to 93% in Brazil.10

The high prevalence of WMSDs among nurses is attributed to the physical nature of their work, particularly that requiring intensive labour and repetitive manual handling of heavy loads,9  including lifting of patients; and moving, pushing and carrying heavy objects such as  beds. These activities involve repetitive movements and prolonged standing.6 Other factors aggravating this condition include organisational structures such as poor work ergonomics and long work shifts.5 Psychosocial and personal factors such as stress, anxiety, depression, low social support, and low moods, are also important predictors of WMSDs.6,12,13  Work demands and time pressures, physical exhaustion, poor administrative support, and inadequate job satisfaction are some of the factors that pre-dispose nurses to WMSDs. Increasing age has also been linked to high prevalence of WMSDs.11 For example, employees over the age of 40 years are likely to be weaker and less agile than those younger than 24 years old, and thus at higher risk of developing WMSDs. Other studies also report that the prevalence of WMSDs is higher in men than in women.9,11

Health planning to address WMSDs requires a sound and evidence-based knowledge of the current WMSD prevalence. In Botswana, the prevalence, reporting and statistics relevant to WMSDs among nurses are largely unknown. It was envisaged that this study would inform healthcare planners and hospital managers about the risks for WMSDs and how best to prevent them. The objectives were to estimate the prevalence of WMSDs and, to determine the association between work-related factors and WMSD symptoms among nurses.

METHODS
This was a cross-sectional quantitative study conducted among nurses employed at a tertiary hospital in Gaborone, Botswana. The hospital is the largest referral and teaching hospital in the country and has more than 500 beds.

The sampling frame comprised nurses working in different wards of the hospital. A self-administered, structured questionnaire in English was used to collect data from participants over three months, from June to August 2017. It was adapted from the Nordic musculoskeletal questionnaire which is widely used to measure the prevalence of WMSDs,14 and included questions adapted from the Dutch Musculoskeletal Questionnaire.15 The first section of the questionnaire collected socio-demographic data including age, sex, marital status and work experience. The second part comprised questions relating to WMSDs, such as having had pain in the past 12 months, the anatomical location of the pain, and the duration of the pain. The third part comprised questions on perceived work-related risk factors for WMSDs, such as performing the same task repeatedly, bending while working, and lifting patients from beds.

 An outline of the study was presented to the nurses during their morning report, after which they were approached individually and requested to participate. The inclusion criterion was having worked at the hospital for at least 12 months. The total number of nurses who met the inclusion criterion was 529. An online sample size calculator (Raosoft) was used to calculate the sample size at 5% margin of error, 95% confidence level and 50% response distribution. A sample size of 223 was calculated; this figure was inflated by 10% to 245 to make allowances for non-response and refusal to participate.

The data were analysed using Stata version 13. Results regarding prevalence and risk factors were presented as frequencies and percentages. The risk factors (independent variables) were evaluated for associations with self-reported WMS pain (dependent variable). Factors that were significant or marginally significant (p ≤ 0.06) were evaluated using multivariable logistic regression analyses. Risks were estimated using odds ratios and 95% confidence intervals. A probability value of less than 0.05 indicated statistical significance.

Ethical clearance was obtained from Sefako Makgatho Health Science University Research Ethics Committee (SMUREC):  certificate clearance number SMUREC/H/59/2017:PG.

RESULTS
Socio-demographic characteristics
Two hundred and twenty nurses participated in the study, giving a response rate of 89.8%. As shown in Table 1, most of the nurses (75.0%) were female. Age ranged from 18 to 59 years, with a mean of 35.2 years. More than half (n = 126; 57.3%) had worked for less than five years.
 


Table 1. Demographic characteristics of participants (N = 220)

Prevalence of WMS pain and affected body part
Two hundred (90.9%) nurses reported WMS pain in the previous 12 months that lasted three days or more (n = 200; 90.9%), while 87 (39.5%) experienced WMS pain that lasted for at least five days (Table 2). Many participants (n = 131; 59.6%) took sick leave due to WMS pain; the majority took four days. The most commonly reported sites of pain were the low back pain (n = 151; 68.6%), followed by the shoulder (n = 81; 36.8%). Pain in the elbow was the least commonly reported (n = 8; 3.6%).
 


Table 2. Prevalence of WMS pain (N = 220)

Perceived risks associated with WMS pain  
As shown in Table 3, the majority of the nurses reported performing the same tasks manually and repeatedly (n = 207; 94.1%). More than two thirds worked night shifts (n = 158; 71.8%). When asked if they performed manual orthopaedic work, a high proportion said they did not (n = 140; 63.6%). Most of the nurses indicated that they did not take tea breaks (n = 152; 69.4%), or lunch breaks (n = 181; 82.3%). Assessment of working posture revealed that most performed their work while standing (n = 195; 88.6%). Many also reported that they manually lifted patients from beds (n = 206; 93.6%) as well as from floors (n = 147; 66.8%). Almost all perceived their work to be stressful (n = 215; 98.2%).
 


Table 3. Prevalence of perceived risk factors for WMS pain among study participants (N = 220)

Factors associated with WMS pain
The results of the univariate and multivariable logistic regression analyses are shown in Table 4. In the univariate model, significant factors were age, working experience and bending at work. These factors were included in the multivariable model. In this model, there was no association between age and WMS pain in any age group. Compared to nurses with less than five years work experience, the odds of WMS pain were 71% lower in those who had worked for five or more years (AOR = 0.29, 95%CI 0.08 to 0.99). Compared to those who did no work while bending, those who worked while bending were almost three times as likely to experience WMS pain (AOR = 3.3, 95%CI 1.03 to 10.55, p = 0.043).

DISCUSSION
The overall prevalence of self-reported WMSDs at any body site (within the previous 12-month period) was 90.9%. This finding is comparable to that from previous studies among nurses in South Africa,16 Saudi Arabia,17 Nigeria,4 Uganda,11 India,17 and Estonia,6 which all reported WMSD prevalence above 80%. Contrary to these findings, a Taiwanese study reported a WMSD prevalence of less than 60% among nurses.18 The discrepancy could have arisen from differences in the methods used. 

Lower back pain (LBP) was the most prevalent form of WMSD amongst the participants, consistent with findings from several other studies.9,10,16,19 The other frequently reported WMSDs included shoulders, upper back and ankle, as reported elsewhere among nursing populations.10,11

In this study, the high prevalence of WMSDs, was associated with shorter work experience (<5 years) and constantly working in a bended posture. According to the researchers’ knowledge, hospitals in Botswana do not have bedside lifting equipment, hence nurses perform manual lifting of patients; this has been found to be a predictor for LBP in other studies.10,20

A lower prevalence of LBP was reported in Pakistani nurses (as low as 34%). This could be attributed to shorter working shifts (6-8 hours per day) and not having to lift or transfer patients manually, as they made use of assistive devices and nursing assistants.20

More than half of the respondents took sick leave due to WMSDs. Similar findings have been reported in the literature among other nursing populations.21 Depending on the level of an individual’s pain, one can be booked off as being sick and ­needing to rest at home. If the condition becomes severe or chronic, it could result in termination of work, leading to increased staff shortages due to absenteeism among the nurses and, hence, poorer healthcare delivery.18

Almost all of the participants in this study perceived their work to be stressful. Similar findings were reported among nurses at a tertiary hospital in South Africa in 2013,16 where 97% of the participants found their work to be stressful. Occupational stress has been identified as a risk factor for development of WMSD.19 A third of the participants in our study reported work overload as their major source of stress. Most also reported that they worked night shifts. Shift work contributes to WMSD and stress.9,19 These findings concur with that of a South African study, among nurses at a tertiary hospital in 2013, which also reflected work overload as a risk factor for WMSD.16 Lack of support by management, poor working conditions, shortage of staff, high patient to nurse ratio, and lack of equipment were probably causes of stress among the respondents in our study, although the association was not investigated. In another study, occupational stress was found to be prevalent amongst the nurses on long working-hour shifts which may have led to staff shortages at healthcare facilities.23

Almost all of the participants reported that they performed the same task repeatedly. Although the odds of WMS pain were elevated among those who performed the same task compared to those who did not, this factor was not significant in the univariate analysis and therefore was not included in the multivariable analysis. Working posture was one of the tasks that contributed to WMS pain; the majority of the participants indicated that they performed their duties while standing and bending repeatedly (89% and 41%, respectively). The likelihood of WMS pain was significantly elevated among those who worked while bending compared to those who did not. Nursing tasks involve heavy physical labour and standing with the trunk in a bent or twisted position, all of which are major sources of back WMS pain.18,22 Most of the participants reportedly lifted patients manually from beds and floors, which is consistent with reports in Nigeria,5 where 51% of healthcare workers lifted and transferred patients manually. However, other studies have not reported any significant association between WMS pain and manually lifting patients.5,11,18 A systematic review of  the literature is required to fully understand this inconsistent relationship between study findings.

Although the AOR for age was significantly lower in the 45-54 years age group compared to those below 35 years in the univariate analysis, there was no association between age and WMS pain in the adjusted model. This finding was unexpected as other studies have reported a positive association between WMS and increasing age.16,18 It is hypothesised that younger nurses might lack experience in handling and lifting patients when they started working. As nurses age and become more experienced, they are often promoted to supervisory or managerial positions and no longer manually handle patients themselves. The discrepancy between our findings may be due to differences in methodologies used.

The high prevalence of WMSD among nurses, in general, is worrying as it may mean that healthcare facility control measures against the risks of acquiring WMSD are inadequate.

Limitations
Our study did not exhaustively investigate all predictors of WMSD that have been reported in the literature, e.g. the number of children in a houselhold,17 and sex.11 This calls for more studies in this niche area. Also, the findings in this study may not be generalisable to all healthcare settings as the study was conducted in one public hospital. Findings might be different to those in a private healthcare facility.

CONCLUSION
Musculoskeletal disorders affect the majority of nurses in Botswana; LBP is most commonly reported. Significant work-related risk factors for MSDs were being young and newly employed, and working posture. There is a need for periodic assessments of MSDs among nurses, along with greater advocacy of safe working environments and strategies to improve work practices and ergonomics.

LESSONS LEARNED
• Nurses have physically demanding jobs that predispose them to WMSDs.
• Stress at work can contribute to the development of WMSDs among nurses.

ACKNOWLEDGEMENTS
We acknowledge the support of the Department of Public Health, Sefako Makgatho Health Sciences University, in the undertaking of this study.

We also acknowledge and thank the nurses who participated in the study.

DECLARATION
The authors declare that this is their own work; all the sources used in this paper have been duly acknowledged and there are no conflicts of interest.

AUTHOR CONTRIBUTIONS
Conception and design of the study: PKC
Data acquisition: KK
Data analysis: KK, LIZ
Interpretation of data: KK, PKC  
Drafting of paper: PKC, LIZ
Critical revision of paper: LIZ 

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