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Background:
Systematic Review

Association of Low Back Pain with Shift Work: A Meta-Analysis

by
Ho-Ming Chen
1,
Po-Yao Huang
2,
Hung-Yi Chuang
3,4,
Chao-Ling Wang
3,
Chen-Cheng Yang
1,3,4,*,
Peng-Ju Huang
5 and
Chi-Kung Ho
3
1
Department of Occupational and Environmental Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung City 812, Taiwan
2
Pharmacy Department, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung City 812, Taiwan
3
Department of Occupational and Environmental Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City 807, Taiwan
4
Department of Public Health and Environmental Medicine, and Research Center for Precision Environmental Medicine, Kaohsiung Medical University, Kaohsiung City 807, Taiwan
5
Department of Orthopaedics, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung City 812, Taiwan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2023, 20(2), 918; https://doi.org/10.3390/ijerph20020918
Submission received: 24 November 2022 / Revised: 22 December 2022 / Accepted: 26 December 2022 / Published: 4 January 2023
(This article belongs to the Special Issue Second Edition: Low Back Pain (LBP))
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Versions Notes

Abstract

:
Shift work (SW) is the main working schedule worldwide, and it may cause sleep disorders, breast cancer, and cardiovascular disease. Low back pain (LBP) is a common problem in the workplace; however, the association between LBP and SW remains unclear. Therefore, we conducted a meta-analysis to determine the association between SW and LBP. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The PubMed, Embase, and Web of Science databases using a set of associated keywords were queried. The inclusion criteria were as follows: (1) adult employees hired by a company or organization; (2) SW exposure; and (3) the outcome of LBP according to examination or assessment. A total of 40 studies were included that met the inclusion criteria for the meta-analysis. SW was significantly associated with LBP (odds ratio [OR]: 1.31, 95% confidence interval [CI]: 1.18–1.47, p < 0.00001). Furthermore, it was observed that LBP was significantly associated with night shift (NS) (OR: 1.49, 95% CI: 1.24–1.82, p < 0.0001) but not with rotating shift (RS) (OR: 0.96, 95% CI: 0.76–1.22, p = 0.49). Moreover, LBP was significantly associated with SW in health care workers (HCWs) (OR: 1.40, 95% CI: 1.20–1.63, p < 0.0001) but not in non-HCWs (OR: 1.19, 95% CI: 0.94–1.50, p = 0.14). SW was significantly associated with LBP. Furthermore, the subgroup analysis showed that NS, but not RS, was associated with LBP. Compared with SW in non-HCWs, SW in HCWs was significantly associated with LBP.

1. Introduction

To date, shift work (SW) is an important issue in occupational medicine. Approximately 20% of the full-time workforce in Taiwan comprises shift workers [1]; the rate is around 30% in the United States [2], while it is 21% in Europe. According to the International Labour Organization, SW is defined as “a method of organization of working time in which workers succeed one another at the workplace.” Torquati et al. showed that SW increases the risk of poor mental health by 30% [3]. Furthermore, fatigue, insomnia, and various somatic diseases are common SW disorders [4].
Several cohort studies showed that SW at night was associated with the risk of coronary heart disease and incident atrial fibrillation [5], type 2 diabetes [5], ischemic stroke [6], breast cancer in females [7], non-alcoholic fatty liver disease [8], decreased brain functional connectivity [9], and obesity [10]. However, there was no significant association between SW and heart failure [11] or obstructive sleep apnea [12]. Additionally, quitting SW decreased coronary heart disease risk among women [13].
Low back pain (LBP) is a common disorder in humans. Globally, the age-standardized point prevalence of LBP in 21 regions was investigated and found to be around 5.6%, 13%, 9%, and 12% in Central Latin America, Australasia, Asia, and Europe, respectively, in 2017 [14]. Poor general health, physical and psychological stress, and characteristics of the person increase the risk of future episodes of LBP or sciatica [15].
Several studies have shown that SW is significantly associated with LBP. The rotating shift (RS), irregular shift, longer night shift (NS), and SW over 16 h were positively correlated to LBP [16,17]. However, NS over 16 h was associated with LBP, which was elevated when participants had sleep problems [16]. Many factors, such as SW, sleep disorders [18], poor mental health [3], and breast cancer [19], may cause LBP [17]. In contrast, other studies showed no significant association between SW and LBP [20,21]. Kawaguchi et al. showed no significant association between irregular SW and LBP (odds ratio [OR]: 1.1, 95% confidence interval [CI]: 0.6–1.9) [20]. A retrospective analysis using 13 years of occupational data from the National Longitudinal Survey of Youth, comprising approximately 11,000 American workers, showed no elevated risk of injury due to evening RS, night RS, or long-term working [21]. Given the inconsistent reports on the correlation between SW and LBP, this study aimed to investigate the relationship between SW and LBP.

2. Materials and Methods

2.1. Protocol and Registration

A systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were conducted. This review protocol was registered at PROSPERO (registration number, CRD42022356707) and the Kaohsiung Medical University Hospital Institutional Review Board (KMUHIRB-EXEMPT(I)-20220009).

2.2. Data Sources and Search Terms

MEDLINE (PubMed), Embase, and Web of Science databases were queried on 1 September 2022, for related studies. There were no limitations to the publication dates and target keywords used to identify all articles. Two researchers (C-C Yang and H-M Chen) performed rudimentary searches using different keywords. The researchers separately proposed a set of key search words as follows for low back pain:
“Low Back Pain” [All Fields] OR “back pain low” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“back” [All Fields] AND “pains” [All Fields] AND “low” [All Fields])) OR “Low Back Pains” [All Fields] OR “pain low back” [All Fields] OR “pains low back” [All Fields] OR “Lumbago” [All Fields] OR “Lower Back Pain” [All Fields] OR “back pain lower” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“back” [All Fields] AND “pains” [All Fields] AND “lower” [All Fields])) OR “Lower Back Pains” [All Fields] OR “pain lower back” [All Fields] OR “pains lower back” [All Fields] OR “Low Back Ache” [All Fields] OR “ache low back” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“aches” [All Fields] AND “low” [All Fields] AND “back” [All Fields])) OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“back” [All Fields] AND “ache” [All Fields] AND “low” [All Fields])) OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“back” [All Fields] AND “aches” [All Fields] AND “low” [All Fields])) OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“low” [All Fields] AND “back” [All Fields] AND “aches” [All Fields])) OR “Low Backache” [All Fields] OR “backache low” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“backaches” [All Fields] AND “low” [All Fields])) OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“low” [All Fields] AND “backaches” [All Fields])) OR “low back pain postural” [All Fields] OR “Postural Low Back Pain” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields] AND “posterior” [All Fields] AND “compartment” [All Fields])) OR “low back pain recurrent” [All Fields] OR “Recurrent Low Back Pain” [All Fields] OR “low back pain mechanical” [All Fields] OR “Mechanical Low Back Pain” [All Fields] OR (“Low Back Pain” [MeSH Terms] OR (“low” [All Fields] AND “back” [All Fields] AND “pain” [All Fields]) OR “Low Back Pain” [All Fields]))
And the mesh term is as follows for shift work:
(“Shift Work” [All Fields] OR “Schedule Shift Work” [All Fields] OR “Schedules Shift Work” [All Fields] OR “Work Schedule Shift” [All Fields] OR “Night Shift Work” [All Fields] OR “Shift Work Night” [All Fields] OR “Rotating Shift Work” [All Fields] OR “Shift Work Rotating” [All Fields] OR “Evening Shift Work” [All Fields] OR “Evening Shift” [All Fields] OR ((“shift” [All Fields] OR “shifted” [All Fields] OR “shifting” [All Fields] OR “shiftings” [All Fields] OR “shifts” [All Fields]) AND (“work” [MeSH Terms] OR “work” [All Fields]) AND (“evening” [All Fields] OR “evenings” [All Fields])) OR “Shift Worker” [All Fields] OR “Work Shift” [All Fields] OR ((“shift” [All Fields] OR “shifted” [All Fields] OR “shifting” [All Fields] OR “shiftings” [All Fields] OR “shifts” [All Fields]) AND (“work” [MeSH Terms] OR “work” [All Fields] )) AND “Shift Work” [All Fields] OR “schedule shift work” [All Fields] OR “schedules shift work” [All Fields] OR “work schedule shift” [All Fields] OR “Night Shift Work” [All Fields] OR “shift work night” [All Fields] OR “Rotating Shift Work” [All Fields] OR “shift work rotating” [All Fields] OR “Evening Shift Work” [All Fields] OR “Evening Shift” [All Fields] OR ((“shift” [All Fields] OR “shifted” [All Fields] OR “shifting” [All Fields] OR “shiftings” [All Fields] OR “shifts” [All Fields]) AND (“work” [MeSH Terms] OR “work” [All Fields]) AND (“evening” [All Fields] OR “evenings” [All Fields])) OR “Shift Worker” [All Fields] OR “Work Shift” [All Fields] OR ((“shift” [All Fields] OR “shifted” [All Fields] OR “shifting” [All Fields] OR “shiftings” [All Fields] OR “shifts” [All Fields]) AND (“work” [MeSH Terms] OR “work” [All Fields])).
Appropriate modified search methods were used for EMBASE and the Web of Science databases.

2.3. Eligibility Criteria

The inclusion criteria were as follows: (1) SW exposure; (2) LBP, based on questionnaire assessment, lumbar spine computed tomography, or magnetic resonance imaging examination.

2.4. Study Selection Process

In the first screening, three investigators (H–M Chen, H–Y Chuang, and C–C Yang) individually assessed the abstracts of the preliminary articles included. Subsequently, in the second screening, two investigators (H–M Chen and P–Y Huang) performed full-text screening to identify articles that met the eligibility criteria and exclude those that were not eligible. The disagreements between H–M Chen and P–Y Huang regarding the eligibility of a study were resolved by three researchers (C–C Yang, C–L Wang, and P–J Huang) following a comprehensive evaluation.

2.5. Data Collection

In each eligible study, information regarding the study characteristics, SW and LBP cases, and the association between SW and LBP was obtained. Several attempts were made to contact the relevant authors to provide details in the event that the information was missing or inaccurate.

2.6. Study Characteristics

The study data was recorded with respect to the following variables: the country where the study was conducted; publication year; sampling framework (clinical- or community-based); sample size; characteristics of participants; and the number of outcome events (i.e., the number of LBP events), as appropriate.

2.7. Shift Work

The definition of SW is “work beyond regular working daytime hours”, including evening shift, NS, fixed shift, on-call shift, or RS [22,23,24,25].

2.8. Low Back Pain

The classification of LBP was as follows: questionnaires for LBP assessment. LBP was defined based on the individual study criteria.

2.9. Statistical Analysis

A calculation of the overall pooled prevalence ORs for LBP was made according to SW and non-SW exposures. A standard error (SE) of 95% CI was used for the OR. In this meta-analysis, the prevalence of OR and SE was reported. The main prevalence ORs and SEs were combined using a random-effects model meta-analysis to calculate the pooled prevalence OR and 95% CI for the primary outcome. A random-effects model was used to assess the possibility of heterogeneity regarding whether the ORs of the included studies originated from their characteristics [26], while I2 was used to report the heterogeneity among the enrolled studies. Moreover, separate subgroup meta-analyses for shift styles (NS and RS) and worker types (health care worker (HCW) and non-HCW) were performed. The Review Manager version 5.4 and R version 3.6.2 were used for all statistical analyses.

3. Results

3.1. Selected Studies

A summary of the literature search procedure is shown in Figure 1. Three different databases (PubMed, EMBASE, and Web of Science) were used, and additional records were identified through other sources, resulting in a total of 786 articles. In the next step, 277 articles were excluded owing to duplication; therefore, a total of 509 studies were screened for abstracts and titles. In the first phase of the screening process, 409 studies were excluded, leaving 100 for full-text screening. In the second phase of full-text screening, 53 studies did not meet the inclusion criteria owing to inappropriate study design, insufficient patient groups, and inappropriate patient group studies. Furthermore, 7 studies did not have adequate data to meet the quantitative synthesis criteria. Finally, we included 40 studies with 1,839,258 participants for meta-analysis [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].

3.2. Study Characteristics

Table 1 presents the 40 studies [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65] that met our inclusion criteria; 31 studies used cross-sectional study designs [17,27,28,29,30,31,32,35,36,37,39,40,41,44,45,46,47,48,49,50,52,56,57,58,59,60,61,62,63,64,65]. Additionally, out of the remaining 9 studies, one study applied a prospective design [55], and 8 = eight used case-control study designs [33,34,38,42,43,51,53,54]. In 35 studies, the assessment of LBP was questionnaire-based [17,27,28,29,30,31,32,35,36,37,38,39,40,41,42,45,46,47,48,49,50,51,52,53,55,56,57,58,59,60,61,62,63,64,65], while in 3 studies [34,43,44], the assessment was based on a clinical diagnosis of LBP. Moreover, one study used the Occupational Prevention and Protection Service database, consisting of all safety reports and human resources information [33], and another used self-administrated instruments [54].

3.3. Results of Individual Studies

Table 1 shows the reported measures of the association between SW exposure and LBP. A total of thirteen studies reported a significant association between SW exposure and LBP [27,29,30,31,34,37,44,45,56,58,59,63,64]. However, the remaining two studies revealed a negative association of SW exposure with LBP [47,60].

3.4. Meta-Analysis

A random-effects model meta-analysis revealed variations in the association between exposure to SW and LBP (ORs derived from 40 studies) [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65] (Table 1, Figure 2). The pooled prevalence OR was significant. The random-effects model meta-analysis indicated a significant positive association between SW and LBP (OR: 1.31, 95% CI: 1.18–1.47, p < 0.00001).
A funnel plot of the log-transformed ORs of the association of LBP with exposure to SW as well as the SEs of the 51 ORs showed that an adequate number of studies had small SEs (i.e., larger sample sizes) and smaller ORs (Figure 3).

3.5. Subgroup Analysis

A random-effects model meta-analysis revealed variations in the association between exposure to different shift styles and LBP. The associations between NS and LBP (ORs derived from 19 studies) [27,28,30,31,33,34,35,37,38,40,41,46,47,56,57,58,59,61,63] and between RS and LBP (ORs derived from 5 studies) [28,31,33,36,52] are shown in Table 2 and Figure 4. The random-effects model meta-analysis indicated a significant association between NS and LBP (OR: 1.49, 95% CI: 1.21–1.82, p = 0.0001), while no significant association was found between RS and LBP (OR: 0.96, 95% CI: 0.76–1.22, p = 0.74). Furthermore, variations in the association between exposure to SW and LBP in HCWs and non-HCWs were revealed. The associations between SW and LBP in HCWs (ORs derived from 24 studies) [17,27,28,30,33,34,36,37,38,40,41,45,46,47,48,49,50,52,55,61,62,63,64,65] and between SW and LBP in non-HCWs (ORs derived from 13 studies) [31,32,39,43,44,51,53,54,56,57,58,59,60] are shown in Table 3 and Figure 5. The random-effects model meta-analysis indicated a significant association between SW and LBP in HCWs (OR: 1.40, 95% CI: 1.20–1.63, p < 0.00001), while no significant association was found between SW and LBP in non-HCWs (OR: 1.19, 95% CI: 0.94–1.50, p = 0.14).

4. Discussion

This study is a meta-analysis based on the original studies. In the meta-analysis of the 40 original studies, we found that SW was significantly associated with LBP (OR: 1.31, 95% CI: 1.18–1.47, p < 0.00001). Another meta-analysis conducted by Gohar et al. showed a statistically significant association between nursing in SW and sickness absence between 1990 and 2019 (OR: 1.47, 95% CI: 1.23–1.77, p < 0.01) [66]. Sun et al. showed that non-specific chronic LBP was significantly associated with working NSs in nurses [67]. Further, Jegnie et al. showed that working hours and SW had a statistically significant association with LBP in Ethiopia [68]. On the contrary, Moscato et al. [47] and Yang et al. [60] showed no significant association between SW and LBP. It was observed that the population in the former one had lower body mass index and the latter one obese worker only take 26.9% in total worker much less than the average in their country based on the journal named Our World in Data [69]. Hence, obesity may be probably one of the risk factors of SW. However, how the body weight influence on the association between SW and LBP requires further investigation.
In addition, although we know that different job descriptions and surroundings lead to different risks of LBP [59,70], the focus of the study was on SW styles without restrictions on occupation and area. In our meta-analysis, some original studies showed a significant association [27,29,30,31,34,37,44,45,56,58,59,63,64], whereas some studies revealed no significant association between SW and LBP. The reason for this difference may be the different study designs, study populations, and careers. Moreover, we found that some studies used different definitions for shift style, such as NS only, three-shift system, or occasionally SW. Similar to the study by Arsalani et al. [28], who categorized SW into morning shift, circulatory shift, NS, and others in their cross-sectional study of the Asian population. Beyen et al. used day shift, NS, and both as SW in a case-control study conducted in Europe [31]. Further, El-Soud et al. categorized SW into day shift and RS in a longitudinal study. The definition of SW seemed to vary between the West and East. Indeed, different work styles are required depending on the type of work. In this meta-analysis, we applied a broad definition of SW. It is difficult to collect information, which sometimes leads to less data, and a non-significant result is expected. Although a different study would have led to difficulty in collecting data, we still selected the most related data for analysis. In contrast, LBP results were not objective if only the questionnaire was used without professional identification. Work-related LBP [33], chronic LBP [63], and others have been reported. A more rigorous evaluation is needed in the future to understand the timing of SW that leads to LBP. Then, the result will be more convincing and allow employers to pay attention to the SW issue.
SW can cause many sleep problems, including reduced sleep quality, insomnia, and reduced sleep duration [71]. A previous study showed disruption of the circadian clock, especially due to NS and RS, leading to changes in melatonin and cortisol levels [72]. Morris et al. studied tissue physiology concerning circadian rhythms in the intervertebral disc and showed that changes in circadian rhythms cause harm to the intervertebral disc. [73]. In a mouse model, Dudek et al. showed that circadian rhythm disruptions lead to degenerative intervertebral disc disease [74]. These animal studies imply that SW leads to sleep interruption, which may cause circadian rhythm disruptions and LBP.
In the subgroup analysis, we found that LBP was significantly associated with NS (OR: 1.49, 95% CI: 1.24–1.82) but not with RS (OR: 0.96, 95% CI: 0.76–1.22). The exposure to NS may cause an increase in the body mass index (BMI) [75], which may be associated with LBP. However, Grundy et al. revealed that both permanent evening shift/NS and RS cause obesity [10]. Häuser et al. proved that increased BMI is associated with chronic LBP (OR: 1.09, 95% CI: 1.06–1.12, p < 0.0001) [10,76].
In some studies, we found that NS and RS led to health problems. According to a review by Feskanich et al., long-term NS increased the risk of hip and wrist fractures (OR: 1.37, 95% CI: 1.04–1.80) [77]. Additionally, Bukowska-Damska et al. revealed that NS workers had a lower mineral density of lumbar vertebral bones [78], while Quevedo et al. revealed that RS workers had a lower mineral density of lumbar vertebral bones [79]. According to these two studies, NS may be associated with a risk of fracture and low bone density, which may lead to LBP. However, how these potential confounding factors influence the association between SW and LBP require more study in the future.
In the subgroup analysis, we found that LBP was significantly associated with HCWs (OR: 1.40, 95% CI: 1.20–1.63). Stereotypically, HCWs are assumed to have more health information and knowledge, and fewer health problems than individuals in other occupations. However, a study by Kyle et al. study revealed that 69% (95% CI: 64.6–73.6) of Scottish nurses had obesity problems, especially in nurse groups, and non-health-related occupations (68.9%, 95% CI: 68.1–69.7) [80]. The reason for this result may be that HCWs need to shift patients, resulting in bend postures [81].
In this study, a positive relationship between SW and LBP is shown, resulting in many possible adverse health effects of SW, such as sleep disorder [18], poor mental health [3], and breast cancer [19]. The government and business organizations need to realize their responsibility concerning ways to decrease the occupational injury. Although some workers’ tasks may be demanding, employers can modify the task content as well as provide reasonable break time and regular health check-ups to develop a comfortable environment for the employee. Healthy employees would create more worker power and decrease the burden of social welfare.

5. Conclusions

In conclusion, SW was significantly associated with LBP according to the meta-analysis of 40 studies. Compared with non-SW, NS showed a significant association with LBP, while RS was not significantly associated with LBP. Furthermore, HCWs showed a significant association with LBP. The possible mechanisms require further investigation.

Author Contributions

C.-C.Y., H.-Y.C. and C.-K.H. contributed to the conceptualization and design of the study; H.-M.C., P.-Y.H., C.-C.Y., and C.-L.W. contributed to data acquisition; C.-C.Y. and H.-Y.C. contributed to analysis; P.-J.H. and C.-K.H. contributed to interpretation of data; H.-M.C. and C.-C.Y. drafted and revised the article. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported partially by the Research Center for Precision Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan and by Kaohsiung Medical University Research Center Grant (KMU-TC111A01 and KMUTC111IFSP01), and Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University (S-111-03).

Institutional Review Board Statement

This review protocol was registered at PROSPERO (registration number, CRD42022356707) and the Kaohsiung Medical University Hospital Institutional Review Board (KMUHIRB-EXEMPT(I)-20220009).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. SW, shift work; LBP, low back pain.
Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. SW, shift work; LBP, low back pain.
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Figure 2. Shift work and odds ratio of low back pain in the 40 studies: a random-effects model (CI, confidence interval; SE, standard error) [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
Figure 2. Shift work and odds ratio of low back pain in the 40 studies: a random-effects model (CI, confidence interval; SE, standard error) [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
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Figure 3. Funnel plot of log-transformed odds ratios of low back pain associated with shift work and standard errors for the 40 studies [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
Figure 3. Funnel plot of log-transformed odds ratios of low back pain associated with shift work and standard errors for the 40 studies [17,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
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Figure 4. Subgroup analysis of odds ratio of low back pain based on night shift or rotating shift. CI, confidence interval; SE, standard error [27,28,30,31,33,34,35,36,37,38,40,41,46,47,51,56,57,58,59,61,62].
Figure 4. Subgroup analysis of odds ratio of low back pain based on night shift or rotating shift. CI, confidence interval; SE, standard error [27,28,30,31,33,34,35,36,37,38,40,41,46,47,51,56,57,58,59,61,62].
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Figure 5. Subgroup analysis of odds ratio of low back pain associated with shift work based on health care worker (HCW) and non-HCW. CI, confidence interval; SE, standard error [17,27,28,30,31,32,33,34,36,37,38,39,40,41,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
Figure 5. Subgroup analysis of odds ratio of low back pain associated with shift work based on health care worker (HCW) and non-HCW. CI, confidence interval; SE, standard error [17,27,28,30,31,32,33,34,36,37,38,39,40,41,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65].
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Table
Table 1. Characteristics of studies included in the meta-analysis (N = 40).
Table 1. Characteristics of studies included in the meta-analysis (N = 40).
First Author
(Year/Journal), Country		Study DesignParticipants (Number)PopulationSexExposure
Variable		Outcome
Measures		Number of Outcome Events/CasesComparisonOR (95% CI)Source
Koda (1991) [42], JapanCase-control studyClinical nurse (947) and clerical worker (300)Community population in JapanWomen onlySW (three shifts)LBPSW: 129; non-SW: 142Questionnaire: LBP yes/no2.25 (0.91–2.59)Table 5 p. 416
Terzi (2015) [53], TurkeyCase-control studySupermarket employee (365)Community population in Çankaya, TurkeyMen and women combinedSWLBPSW: 87; non-SW: 135Questionnaire: LBP yes/no1.07 (0.6981–1.6407)Table 2 calculation
Ettorre (2019) [34], ItalyCase-control studyFemale nurse (1530)Female rotating shift registered nursesWomen onlyNSWRLBPNumber of NS:
0: 10
1–2: 84
3–6: 110		Clinical diagnosis LBP1–2 NS: 0.84 (0.39–1.81)
3–6 NS: 3.46 (1.6–7.47)		Table 2 p. 485
Tran (2016) [54], VietnamCase-control studyFemale workers of the industrial zone in VietnamFemale worker of 10 factories in VietnamWomen onlySWAfter-shift MSD syndrome in low backSW: 95; non-SW: 23Self-administrated instruments0.46 (0.2–1.1)Table 2 p. 742
Ettorre (2018) [33], ItalyCase-control studyFemale rotating shift-registered nurse (671)Female rotating shift-registered nurse in ItalyWomen onlyNS number in 7 days; RSWRALBPNumber of NS
0: 5
1–2: 42
3–6: 46
RS: 31
Control: 81		Occupational Prevention and Protection Service database for safe reports and Human Resources information1–2 NS: 1.03 (0.34–3.1)
3–6 NS: 1.7 (0.56–5.18)
RS: 0.65 (0.39–1.1)		Table 2 p. 55, Table 5 p. 57
Fujii (2019) [38], JapanCase-control studyFemale nurse (3066)Female nurse from 12 hospitals in JapanWomen onlyNSLBPNS: 155; non-SW: 33Questionnaire: LBP yes/no1.2 (0.67–2.13)Table 2 p. 6
Raeisi (2014) [50], IranCross-sectional studyNursing personnel in a large general hospital in Tehran, Iran (650)Nursing personnel with at least 1 year experienceMen and women combinedSWLow back disorderSW: 219; non-SW: 98Questionnaire: LBP yes/no1.2 (0.78–1.94)Table 2 p. 161 calculation
Seyedmed (2014) [51], IranCase-control studyIndustrial worker (511)Rubber factory worker in 2011–2013 in the city of Yazd, IranMen and women combinedSWLBPSW: 239; non-SW: 52General Health Questionnaire score1.47 (0.95–2.26)Table 2 p. 214
Samaei (2016) [17], IranCross-sectional studyRandomly selected nursing personnel (243)Randomly selected nursing personnel, Iran Men and women combinedSWLBPSW: 145; non-SW: 24NMQ1.41 (0.68–2.91)Table 2 p. 5 calculation
Zhang (2019) [63], ChinaCross-sectional studySonographers (248)Sonographers in General Hospital Guangdong provinceMen and women combinedNSLBPNS: 118; non-SW: 24Questionnaire: LBP yes/no1.83 (0.99–3.37)Table 5 calculation
Yoshimoto (2019) [61], JapanCross-sectional studyNursing personnel (1075)Nursing personnel in Kameda Medical Centre at Chinba, JapanMen and women combinedNSLBPNRQuestionnaire: LBP yes/no1.00 (0.97–1.04)Table 2 p. 5
Ovayolu (2014) [48], TurkeyCross-sectional studyNurse in intensive care units (114)Nurse in intensive care units in the province of Gaziantep, TurkeyMen and women combinedSWLBPSW: 34; non-SW: 62Questionnaire: LBP + Visual Analogue Scale2.74 (0.74–10.14)Table 1 p. 72
calculation
Lee (2020) [43], ChinaCase-control studyManual worker (406)Workers in Henan, Hubei, Guangdong province, ChinaMen onlySWLBPSW: 59; non-SW: 81Difference-in-difference analysis1.03 (0.65–1.64)Table 2 p. 5 calculation
Widanarko (2015) [59], IndonesianCross-sectional studyIndonesian coal mining workers (1565)Coal mining workers, IndonesianMen and woman combinedSW without NS; SW with NSLBPSW no NS: 13; SW with NS: 218; non-SW: 28NMQSW without NS:
1.41 (0.66–3.02)
SW with NS: 1.97 (1.14–3.43)		Table 3 p. 164
Trinkoff (2006) [55], USThree-wave longitudinal surveyRegistered nurse (2617)Registered nurse, USMen and women combinedSWLBPNRNMQ1.27 (0.94–1.72)Table 2 p. 968
Wang (2017) [56], ChinaCross-sectional studyTaxi-driver of three major taxi companies in Jinan, China (719)Taxi-driver of three major taxi companies in Jinan, ChinaMen and women combinedNSLBPNRNMQ2.3 (1.7–3.2)Table 2 p. 3
Ibrahim (2019) [65], MalaysiaCross-sectional studyNurse aged 25–60 years working for six public hospitals of Penang, Malaysia (1292)Nurse aged 25–60 years working for six public hospitals, MalaysiaMen and women combinedSWLBPSW: 819; non-SW: 170The BACKS Tool questionnaire (self-administered)0.98 (0.69–1.37)Table 5 p. 7 of 12 calculation
Zhang (2019) [63], ChinaCross-sectional studyAmbulance workers including doctors, nurses, and drivers (1560)Ambulance workers in 38 tertiary hospitals in Shandong, ChinaMen and women combinedSWChronic LBPSW: 60; non-SW: 45NMQ2.73 (1.77–4.23)Table 4 p. 6
Yang (2016) [60], USCross-sectional study2010 National Health Interview Survey in US (13924)Database, USMen and women combinedSWLBPSW: 873; non-SW: 2175NHIS core questionnaire 0.66 (0.61–0.72)Table 3 p. 7
calculation
Weyh (2020) [57], GermanCross-sectional studyWelders from 34 companies in German steel industry (145)Steel industrial welders, GermanMen and women combinedSW no NS; SW with NSLBPSW no NS: 28; SW with NS: 27; non-SW: 46NMQSW without NS: 0.7 (0.32–1.47)
SW with NS: 0.7 (0.33–1.57) 		Table 1 p. 5
Moscato (2010) [47], ItalyCross-sectional studyOperating room nurse in nine hospitals in Room (225)Operating room nurse in nine hospitals in Room, ItalyMen and women combinedNS
diurnals/nocturnals		Intensity of LBPNS: 64; Non-SW: 89Questionnaire: LBP yes/no NMQ0.3 (0.12–0.78)Table 2 p. 457
Leino-Arjas (2004) [44], FinlandCross-sectional studyPatients hospitalized due to severe lumbar intervertebral disc disorders from the Finland Hospital Discharge Register (1783616)Database, FinlandMen and women combinedTwo SW; three SWLBPNRDiagnosis (ICD-10: M51.1–51.9)2 SW: 1.09 (0.94–1.26)
3 SW: 1.34 (1.15–1.56)		Table 3 p. 519
Katsifaraki (2020) [41], NorwayCross-sectional studyNurse with three-shift rotation, Norway (679)Nurse with three-shift rotation, NorwayMen and women combinedNSLBPNRQuestionnaire: LBP yes/no1.4 (0.83–2.34)Table 3 p. 6
Shafiezadeh (2011) [52], IranCross-sectional studyNurses in a large hospital in Ahwaz, southwestern Iran (195)Nurses in a large hospital in Ahwaz, southwestern IranMen and women combinedRSLBPRS: 46; non-SW: 15NMQ0.95 (0.44–2.03)Table 3 p. 162 calculation
Kalteh (2018) [39], IranCross-sectional studyEmployee on offshore oil and gas installations, South Iran (1157)Employee on offshore oil and gas installations, IranMen and women combinedSWLBPSW: 61; non-SW: 207NMQ1.23 (0.88–1.71)Table 3 p. 4 calculation
Widanarko (2012) [58], IndonesianCross-sectional studyCoal mining industry workers, Indonesian (1294)Coal mining industry workers, IndonesianMen and women combinedNSLBPNRQuestionnaire: LBP yes/no NMQ1.77 (1.07–2.93)p. 5735 right column, result section, line10
Christen (2021) [32], NorwayCross-sectional studyData from the Troms Study, Norway (2332)Data from Troms Study, a longitudinal population-based cohort study, NorwayMen and women combinedSWLBPNRQuestionnaire: LBP yes/no 1.03 (0.77–1.37)Table 2
Katsifaraki (2019) [40], NorwayCross-sectional studyShift work nurses working in public hospitals in Norway (679)Public hospitals, NorwayMen and women combinedNSLBPNRQuestionnaire: pain site: low back1.15 (0.96–1.38)Table 1
Zhao (2012) [64], Australia, NZ, and UKCross-sectional studyNurses (5280)Nurses and Midwives’ e-cohort Study (NMeS)Men and women combinedSWLBPSW: 174; non-SW: 145NMQ1.39 (1.06–1.83)Table 1 calculation
Eriksen (2004) [37], NorwayCross-sectional studyRandomly selected Norwegion nurses’ aides (4266)Norwegion nurses’ aides, NorwayMen and women combinedNS:
sometimes/
rather often/
very often		LBPNRQuestionnaire: LBP yes/noSometimes:1.52 (1.06–2.19)
Rather often: 1.39 (0.73–2.63)
Very often: 1.64 (1.09–2.49)		Table 4 p. 402
Mekonnen (2019) [45], EthiopiaCross-sectional studyNurses (422)Selected by random sampling technique, EthiopiaMen and women combinedSWLBPSW: 227; non-SW: 39NMQ2.85 (1.77–4.61)Table 2
Passali (2018) [49], GreeceCross-sectional studyNurses (394)Nurses in the capital of GreeceMen and women combinedSWLBPSW: 198; non-SW: 78NMQ1.29 (0.81–2.05)Table 3 p. 4 calculation
Beyen (2013) [31], EthiopiaCross-sectional studyPrimary, secondary, or higher institution (college or university) teacher in Gondar town, Ethiopia (662)Primary, secondary, or higher institution (college or university) teacher in Gondar town, EthiopiaMen and women combinedNS, RSLBPNS: 17; RS: 70; non-SW: 259NMQNS: 6.79 (1.55- 29.74)
RS: 1.19 (0.79- 1.80)		Table 6 calculation
Belay (2016) [30], EthiopiaCross-sectional studyNurses working in public hospitals of Addis Ababa, Ethiopia (395)Nurses working in public hospitals of Addis Ababa, EthiopiaMen and women combinedNSLBPNS: 94; non-NS: 86self-administered questionnaire1.77 (1.19–2.65)Table 6a
Mijena (2020) [46], EthiopiaCross-sectional studyNurses working in public hospitals of Harari region and Dire Dawa city administration, Ethiopia (404)Nurses working in public hospitals of Harari region and Dire Dawa city administration, EthiopiaMen and women combinedNSLBPNS: 126; non-NS: 28self-administered questionnaire1.35 (0.82–2.25)Table 6
Wang (2016) [27], ChinaCross-sectional studyNurses working in three class-A hospitals, China (909)Nurses working in hospitals, ChinaMen and women combinedNSLBPNS: 582; non-SW: 25self-administered questionnaire12.64 (6.36–25.12)Table 3 calculation
El-Soud (2016) [36], EgyptCross-sectional studyNurse working in Zagazig University Hospitals, Egypt (150)Nurse working in Zagazig University Hospitals, EgyptWomen onlyRSLBPRS: 76; non-SW: 43self-administered questionnaire1.12 (0.46–2.7)Table 5 p. 112
Arsalani (2014) [28], IranCross-sectional studyNurses working in public hospitals in Tehran, Iran (606)Nurses working in public hospitals in Tehran, IranMen and women combinedRS; NS; otherLBPDS: 39
RS: 111
NS: 26
Other: 28		self-administered questionnaireRS: 0.97 (0.61–1.55)
NS: 0.92 (0.49–1.73)
Other: 1.62 (0.84–3.15)		Table 1 calculation
Attarchi (2014) [29], IranCross-sectional studyHealth care workers in Tehran, Iran (454)Nurses working in public hospitals in Tehran, IranMen and women combinedSWLBPSW: 182; non-SW: 79NMQ1.74 (1.18–2.56)Table 1 calculation
Dlungwane (2018) [35], South AfricaCross-sectional studyNurse at a regional hospital, South Africa (373)Nurse at a regional hospital, South AfricaMen and women combinedNSLBPNRself-administered questionnaire0.94 (0.66–1.34)Table 4
CI, confidence ratio; DS, day shift; LBP, low back pain; NHIS, National Health Interview Survey; NMQ, Nordic Musculoskeletal Questionnaire; NR, NS, night shift; OR, odds ratio; RS, rotating shift; SW, shift work; MSD, musculoskeletal disorders; WRALBP, work-related acute low back pain; WRLBP, work-related low back pain; US, United States.
Table
Table 2. Subgroup analysis of odds ratios based on participants exposed to night shifts or rotating shifts.
Table 2. Subgroup analysis of odds ratios based on participants exposed to night shifts or rotating shifts.
SubgroupPooled Odds Ratio95% CI
Study Participants
 Night shift
  Ettorre (2019) [34], Italy, Number of NS 1–20.840.39–1.81
  Ettorre (2019) [34], Italy, Number of NS 3–63.461.6–7.47
  Ettorre (2018) [33], Italy, Number of NS 1–21.030.34–3.1
  Ettorre (2018) [33], Italy, Number of NS 3–61.70.56–5.18
  Fujii (2019) [38], Japan1.20.67–2.13
  Zhang (2020) [62], China1.82800.9914–3.3704
  Yoshimoto (2019) [61], Japan1.000.97–1.04
  Widanarko (2015) [59], Indonesian, SW with NS1.971.14–3.43
  Wang (2017) [56], China2.31.7–3.2
  Weyh (2020) [57], German, SW with NS0.70.33–1.57
  Moscato (2010) [47], Italy0.30.12–0.78
  Katsifaraki (2020) [40], Norway1.40.83–2.34
  Widanarko (2012) [58], Indonesian1.771.07–2.93
  Katsifaraki (2019) [40], Norway1.150.96–1.38
  Eriksen (2004) [37], Norway, sometimes1.521.06–2.19
  Eriksen (2004) [37], Norway, rather often1.390.73–2.63
  Eriksen (2004) [37], Norway, very often1.641.09–2.49
  Beyen (2013) [31], Ethiopia, NS6.79341.5518–29.7393
  Belay (2016) [30], Ethiopia1.771.19–2.65
  Mijena (2020) [46], Ethiopia1.350.82–2.25
  Wang (2016) [27], China12.63776.3568–25.1247
  Arsalani (2014) [28], Iran, NS0.92420.4924–1.7349
  Dlungwane (2018) [35], South Africa0.940.66–1.34
 Subtotal1.491.21–1.82
 Rotating shift
  57. Ettorre (2018) [33], Italy, RS0.650.39–1.1
  342. Shafiezadeh (2011) [52], Iran0.94710.4425–2.0270
  504. Beyen (2013) [31], Ethiopia, RS1.19030.7881–1.7978
  508. El-Soud (2016) [36], Egypt1.120.46–2.7
  509. Arsalani (2014) [28], Iran, RS0.97000.6084–1.5465
 Subtotal0.960.76–1.22
CI, confidence interval; NS, night shift; RS, rotating shift.
Table
Table 3. Subgroup analysis of odds ratio for healthcare workers (HCWs) and non-HCWs exposed to shift work.
Table 3. Subgroup analysis of odds ratio for healthcare workers (HCWs) and non-HCWs exposed to shift work.
SubgroupPooled Odds Ratio95% CI
Study Participants
 Healthcare worker
  38. Ettorre (2019) [34], Italy, number of NS 1–20.840.39–1.81
  38. Ettorre (2019) [34], Italy, number of NS 3–63.461.6–7.47
  57. Ettorre (2018) [33], Italy, number of NS 1–21.030.34–3.1
  57. Ettorre (2018) [33], Italy, number of NS 3–61.70.56–5.18
  57. Ettorre (2018) [33], Italy, RS0.650.39–1.1
  67. Fujii (2019) [38], Japan1.20.67–2.13
  110. Raeisi (2014) [50], Iran1.20.78–1.94
  160. Samaei (2016) [17], Iran1.40970.6831–2.9094
  176. Zhang (2019) [62], China1.82800.9914–3.3704
  189. Yoshimoto (2019) [61], Japan1.000.97–1.04
  195. Ovayolu (2014) [48], Turkey2.74190.7411–10.1444
  241. Trinkoff (2006) [55], US1.270.94–1.72
  248. Ibrahim (2019) [65], Malaysia0.97500.6917–1.3743
  250. Zhang (2019) [63], China2.7321.765–4.229
  278. Moscato (2010) [47], Italy0.30.12–0.78
  312. Katsifaraki (2020) [41], Norway1.40.83–2.34
  342. Shafiezadeh (2011) [52], Iran0.94710.4425–2.0270
  406. Katsifaraki (2019) [40], Norway1.150.96–1.38
  438. Zhao (2012) [64], Australia, NZ, and UK1.39151.0602–1.8263
  481. Eriksen (2004) [37], Norway, sometimes1.521.06–2.19
  481. Eriksen (2004) [37], Norway, rather often1.390.73–2.63
  481. Eriksen (2004) [37], Norway, very often1.641.09–2.49
  493. Mekonnen (2019) [45], Ethiopia2.8531.766–4.609
  496. Passali (2018) [49], Greece1.28570.8069–2.0487
  505. Belay (2016) [30], Ethiopia1.771.19–2.65
  506. Mijena (2020) [46], Ethiopia1.350.82–2.25
  507. Wang (2016) [27], China12.63776.3568–25.1247
  508. El-Soud (2016) [36], Egypt1.120.46–2.7
  509. Arsalani (2014) [28], Iran, RS0.97000.6084–1.5465
  509. Arsalani (2014) [28], Iran, NS0.92420.4924–1.7349
  509. Arsalani (2014) [28], Iran, other shift1.620.84–3.15
 Subtotal1.401.20–1.63
 Non-healthcare worker
  12. Terzi (2015) [53], Turkey1.07020.6981–1.6407
  41. Tran (2016) [54], Vietnam0.460.2–1.1
  150. Seyedmed (2014) [51], Iran1.470.95–2.26
  218. Lee (2020) [43], China1.02900.6460–1.6390
  232. Widanarko (2015) [59], Indonesian, SW no NS1.410.66–3.02
  232. Widanarko (2015) [59], Indonesian, SW with NS1.971.14–3.43
  247. Wang (2017) [56], China2.31.7–3.2
  253. Yang (2016) [60], US0.66210.6061–0.7233
  276. Weyh (2020) [57], German, SW no NS0.70.32–1.47
  276. Weyh (2020) [57], German, SW with NS0.70.33–1.57
  300. Leino-Arjas (2004) [44], Finland, two SW1.090.94–1.26
  300. Leino-Arjas (2004) [44], Finland, three SW1.341.15–1.56
  344. Kalteh (2018) [39], Iran1.22840.8827–1.7095
  367. Widanarko (2012) [58], Indonesian1.771.07–2.93
  399. Christen (2021) [32], Norway1.030.77–1.37
  504. Beyen (2013) [31], Ethiopia, NS6.79341.5518–29.7393
  504. Beyen (2013) [31], Ethiopia, RS1.19030.7881–1.7978
 Subtotal1.090.94–1.50
CI, confidence interval; NS, night shift; RS, rotating shift; SW, shift work; UK, United Kingdom; NZ, New Zealand.
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Chen, H.-M.; Huang, P.-Y.; Chuang, H.-Y.; Wang, C.-L.; Yang, C.-C.; Huang, P.-J.; Ho, C.-K. Association of Low Back Pain with Shift Work: A Meta-Analysis. Int. J. Environ. Res. Public Health 2023, 20, 918. https://doi.org/10.3390/ijerph20020918

AMA Style

Chen H-M, Huang P-Y, Chuang H-Y, Wang C-L, Yang C-C, Huang P-J, Ho C-K. Association of Low Back Pain with Shift Work: A Meta-Analysis. International Journal of Environmental Research and Public Health. 2023; 20(2):918. https://doi.org/10.3390/ijerph20020918

Chicago/Turabian Style

Chen, Ho-Ming, Po-Yao Huang, Hung-Yi Chuang, Chao-Ling Wang, Chen-Cheng Yang, Peng-Ju Huang, and Chi-Kung Ho. 2023. "Association of Low Back Pain with Shift Work: A Meta-Analysis" International Journal of Environmental Research and Public Health 20, no. 2: 918. https://doi.org/10.3390/ijerph20020918

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