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BMC Musculoskeletal Disorders

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Prevalence and its risk factors for low back pain among operation and maintenance personnel in wind farms

  • Ning Jia1,
  • Tao Li1,
  • Shuangqiu Hu2,
  • Xinhe Zhu2,
  • Kang Sun2,
  • Long Yi3,
  • Qiong Zhang3,
  • Guilian Luo4,
  • Yuzhen Li1,
  • Xueyan Zhang1,
  • Yongen Gu1 and
  • Zhongxu Wang1Email author
BMC Musculoskeletal DisordersBMC series – open, inclusive and trusted201617:314

https://doi.org/10.1186/s12891-016-1180-y

Received: 11 November 2015

Accepted: 21 July 2016

Published: 26 July 2016

Abstract

Background

With the increasingly severe energy shortage and climate change problems, developing wind power has become a key energy development strategy and an inevitable choice to protect the ecological environment worldwide. The purpose of this study was to investigate the prevalence of low back pain (LBP) and analyze its risk factors among operation and maintenance personnel in wind farms (OMPWF).

Methods

A cross-sectional survey of 151 OMPWF was performed, and a comprehensive questionnaire, which was modified and combined from Nordic Musculoskeletal Questionnaires (NMQ), Washington State Ergonomics Tool (WSET) and Syndrome Checklist-90(SCL-90) was used to assess the prevalence and risk factors of LBP among OMPWF.

Results

The prevalence of LBP was 88.74 % (134/151) among OMPWF. The multivariable model highlighted four related factors: backrest, somatization, squatting and lifting objects weighing more than 10 lb more than twice per minute.

Conclusions

The prevalence of LBP among OMPWF appears to be high and highlights a major occupational health concern.

Keywords

Wind farmsLow back painRisk factorsErgonomic

Background

With the increasing scarcity of the world’s energy, wind energy is viewed as a low-carbon, clean, and abundant source of renewable energy, which is especially popular and has become an important measure to improve energy structure, reduce environmental pollution, and protect the ecological environment all over the world. However, the wind farm industry may also lead to serious health threats to operation and maintenance personnel in wind farms (OMPWF) whilst bringing many benefits in energy conservation.

Regularly OMPWF need to carry out the inspection, maintenance, and fault solutions of various equipment in wind turbine nacelle. They are required to climb the wind turbine tower several times every day, which is up to about 80 m high from the ground, causing great physical exertion. Since the wind turbine nacelle is narrow and small, and almost all operation activity is manual, workers are forced to spend long periods of time in awkward postures. This may lead to many adverse ergonomic issues, such as heavy physical labor, repetitive tasks, lifting and excessive force. In addition, wind farms are generally built in remote areas with abundant wind energy resources, which include the ridge, grassland, Gobi Desert, and island, etc. Enterprises have a regulation of holidays by rotational schedule, that is, OMPWF would go home to rest after work in wind farms for 2-3 months continuously. The environment of their resident is relatively isolated, less time for recreation, and a long time of being away from family and friends. All these factors lead to social isolation which is harmful for OMPWF’s psychosocial health.

Preliminary investigations and related research have confirmed that adverse ergonomic, psychosocial, and individual and lifestyle factors mentioned above might be associated with the risk of low back pain (LBP) [1, 2]. LBP is the most common musculoskeletal disorders, which not only seriously influences the health, working capacity and professional life of workers, but also brings heavy burden to their families and society. LBP has been included in the list of compensation diseases in many industrialized countries. It is estimated that LBP has resulted in a loss of 149 million working days and has caused direct and indirect economic losses of up to one hundred to two hundred billion dollars [3]. It has cost Germany more than 7,000 Euros annually owing to LBP [4]. The global burden of disease research showed that workplace adverse ergonomics caused by LBP gave rise to 21.7 million disability-adjusted life years [5].

So far, there are few studies on the occupational health issues caused by new energy industries despite programs of clean energy developing quickly in China. The purpose of this study was to explore the occurrence of LBP and identify the risk factors of LBP among OMPWF. The occurrence of LBP influenced by adverse ergonomic issues, psychosocial problems, and lifestyle factors are discuss in this study, which provided useful information for strategies and measures to prevent and reduce the occurrence of LBP, therefore offering scientific basis for healthy and sustainable development of the clean energy industry.

Methods

Subjects

A questionnaire based cross-sectional study was carried out among OMPWF in a wind turbine manufacturing enterprise in China, which involved 17 wind farms. Subjects eligibility criteria were as follows: male, having worked no less than 1 year in the current position, no history of significant trauma, no diagnosed rheumatic or tumour, and having never had an accident involving the low back region previously. All subjects who met the eligibility criteria were selected.

The workspace of the nacelle

OMPWF’s routine work is mainly conducted in nacelle, which is roughly 4 m high, 10 m long, and 4 m wide. There are large-scale instruments, such as generator, gearbox, battery cupboard, and yaw control system located in the middle of the nacelle, which occupy the most of the interior space in nacelle. The maintenance passageway is approximately 0.8 m wide. Since all of these make the working space very narrow, OMPWF have to adopt adverse postures, such as stoop, squat, and prone position. The space of hands operation is only up to 0.1 m wide when overhauling the generator. The operating point from the nacelle wall is only 0.6 m wide when maintaining the gearbox. The battery cupboard from the nacelle wall is only 0.7 m wide, when replacing batteries in the battery cupboard. OMPWF are compelled to lie on the gearbox anointing with oil for yaw gear ring when maintaining the yaw control system, the distance between yaw gear ring and the lay flat is only 0.3 m wide.

Questionnaire

In this study, the data were obtained with a comprehensive questionnaire based on Nordic Musculoskeletal Questionnaire (NMQ) [6], Washington State Ergonomics Tool (WSET) [7], and Symptom Checklist 90(SCL-90) [8] and combined with the actual situation of the operation maintenance operation in wind farms.

Consequences of low back pain

In our study, the diagnostic procedures of LBP included questionnaires and palpation inspection. First, patients were selected by questionnaire in which they complained of any two kinds of symptoms of ache, numbness, pain, or discomfort in the low back simultaneously and which could not be relieved after 24 h of rest. Additionally, LBP-positive patients would be further diagnosed by orthopedic surgeons through palpation inspection on those complaining of LBP.

A modified version of the Nordic Musculoskeletal Questionnaire(NMQ) was used to assess the cumulative pain prevalence in the low back in the past 12 months. The validity and reliability of the NMQ has been validated in previous studies [9], and this questionnaire has later been translated into Chinese [10]. The NMQ has three sections. The first section covered demographic characteristics such as age, job tenure, height, weight, education, tobacco smoking, and alcohol consumption. The second section recorded whether operators had experienced ache, pain, or discomfort in their low back in the past 12 months. The third section of the questionnaire included items about living environment, habits: the height of desk/chair, space below the table, height of keyboard/ mouse, height of the backrest, and so on.

Ergonomic, psychosocial risk factors assessments

Ergonomic risk factors were assessed through Washington State Ergonomics Tool (WSET). The WSET uses observational checklist methodology to evaluate generic risk factors in the following six major categories: awkward posture, highly repetitive motion, high hand force, repeated impact, lifting, and hand-arm vibration. Employers could use this tool to determine whether the job activity increased the risk of employees’ low back pain.

The Chinese version of Symptom Checklist-90 (SCL-90) is a widely-used self-report symptom inventory that consists of 90 items. This version is used to assess psychosocial distress symptoms among patients with LBP during the preceding week. Multiple studies have found that the Chinese version of the SCL-90 has satisfactory reliability and validity [11]. Moreover, the following subscales are derived from the 90 items: somatization, obsessive-compulsive, interpersonal-sensitivity, depression, anxiety, hostility, phobic-anxiety, paranoid ideation, and psychoticism. Each symptom is rated on a 5-point Likert scale (0 = notatall,4 = extremely) indicating how frequently the client has experienced these symptoms in the last week. The total score is inversely related to the psychological health status, the higher the total score, the worse the psychological health status.

Data analysis

Analysis of the data was performed with IBM SPSS software version 20. Descriptive statistics were conducted for demographic characteristics, psychosocial distress status, and LBP prevalence rates. Chi-square test was used to determine differences between categorical variables. The stepwise logistic regression was used to identify the associations between the ergonomic, psychosocial, and other related factors possibly related to low back pain. The associations were estimated by calculating the ORs and their 95 % CI. P-value thresholds for entry to and removal from the multivariate model was set at P <0.05 and 0.10 respectively.

Results

Study population characteristics

The questionnaires were completed by 151 male OMPWF. The overall response rate was 100 %. Demographic characteristics of the participants are shown in Table 1. In total, the mean age was 25.96 years, and the mean working hours per week were 44.70 h. The average height and weight was 171.89 ± 5.41 cm and 66.87 ± 9.26 kg, respectively. The average working-age was 3.60 ± 2.19 years. Educational level of the participants was high, as 99.34 % of the participants had at least a Bachelor’s degree.
Table 1

Demographic characteristics of the participants (n = 151)

Characteristics

 

N (%)

Mean (SD)

Age (yr)

<25

48 (31.79)

25.96 (2.26)

 

25~

90 (59.60)

 

30~

13 (8.61)

Height (cm)

<170

53 (35.10)

171.89 (5.41)

 

170~

49 (32.45)

 

175~

49 (32.45)

Weight (kg)

<60

31 (20.53)

66.87 (9.26)

 

60~

60 (39.74)

 

70~

60 (39.74)

Working-age (yr)

<1

27 (17.88)

3.60 (2.19)

 

1~

22 (14.57)

 

2~

102 (67.55)

Working hours per week (h)

<40

13 (8.61)

44.70 (1.86)

 

40~

79 (52.32)

 

45~

59 (39.07)

Education

High school

1 (0.66)

 
 

Bachelor’s degree

136 (90.07)

 
 

Higher than Bachelor’s degree

14 (9.27)

 

Prevalence of LBP

According to questionnaire and palpation, the prevalence of LBP was 88.74 % (134/151).

Adverse ergonomic factors exposures

Table 2 shows the association between adverse ergonomic factors and the prevalence of LBP in the univariate analysis. LBP was significantly associated with awkward posture (squatting more than 4 h total per day) (OR = 8.80, 95 % CI1.15–67.10, P < 0.05); heavy, frequent, or awkward lifting (lifting objects weighing more than 10 lb if done more than twice per minute, more than 2 h total per day) (OR = 3.77, 95 % CI1.29–11.01, P < 0.05); repeated impact (using the knee as a hammer more than once per minute, more than 2 h total per day) (OR = 2.83, 95 % CI1.01–7.92, P < 0.05); high hand force (gripping an unsupported object(s) weighing 10 lbs or more per hand, or gripping with a force of 10lbs or more per hand, meanwhile no other risk factors more than 4 h total per day) (OR = 1.14, 95 % CI1.07–1.21, P < 0.05).
Table 2

Adverse ergonomic factors of LBP among OMPWF with univariate analysis

Adverse ergonomic risk factors

Low back pain

Number of workers

Case

OR

(95 % CI)

Awkward posture

    

Working with the hand(s) above the head, or the elbows above the shoulders, more than 4 h total per day

    

 No

6

4

1

 

 Yes

145

130

4.33

(0.73–25.68)

Repeatedly raising the hand(s) above the head, or the elbow(s) above the shouder(s) more than once per minute, more than 4 h total per day

    

 No

12

10

1

 

 Yes

139

124

1.65

(0.33–8.27)

Working with the neck bent more than 45° (without support or the ability to vary posture), more than 4 h total per day

    

 No

14

11

1

 

 Yes

137

123

2.40

(0.60–9.63)

Working with the back bent forward more than 30° (without support or the ability to vary posture), more than 4 h total per day

    

 No

10

8

1

 

 Yes

141

126

2.10

(0.41–10.82)

Working with the back bent forward more than 45° (without support or the ability to vary posture), more than 2 h total per day

21

17

1

 

 No

130

117

2.12

(0.620–7.25)

 Yes

    

Squatting more than 4 h total per day

    

 No

4

2

1

 

 Yes

147

132

8.80

(1.15–67.10)*

Kneeling more than 4 h total per day

    

 No

32

27

1

 

 Yes

119

107

1.65

(0.54–5.09)

High hand force

    

Pinching an unsupported object(s) weighing 2 lbs or more per hand, or pinching with a force of 4 lbs or more per hand, meanwhile highly repetitive motion more than 3 h total per day

    

 No

22

10

1

 

 Yes

129

114

0.76

(0.16–3.58)

Pinching an unsupported object(s) weighing 2 lbs or more per hand, or pinching with a force of 4 lbs or more per hand, meanwhile hand/wrist in awkward posture more than 3 h total per day

    

 No

28

23

1

 

 Yes

123

111

2.01

(0.65–6.26)

Pinching an unsupported object(s) weighing 2 lbs or more per hand, or pinching with a force of 4 lbs or more per hand, meanwhile no other risk factors more than 4 h total per day

    

 No

22

18

1

 

 Yes

129

116

1.98

(0.58–6.76)

Gripping an unsupported object(s) weighing 10lbs or more per hand, or gripping with a force of 10 lbs or more per hand, meanwhile highly repetitive motion more than 3 h total per day

    

 No

15

12

1

 

 Yes

136

122

2.179

(0.55–8.67)

Gripping an unsupported object(s) weighing 10lbs or more per hand, or gripping with a force of 10 lbs or more per hand, meanwhile hand/wrist in awkward posture more than 3 h total per day

    

 No

27

23

1

 

 Yes

124

111

1.49

(0.44–4.97)

Gripping an unsupported object(s) weighing 10lbs or more per hand, or gripping with a force of 10 lbs or more per hand, meanwhile no other risk factors more than 4 h total per day

    

 No

10

10

1

 

 Yes

141

124

1.14

(1.07–1.21)*

Highly repetitive motion

    

Using the same motion with little or no variation every few seconds, and high, forceful exertions with the hand(s) more than 2 h total per day

    

 No

28

25

1

 

 Yes

123

109

0.93

(0.25–3.50)

Using the same motion with little or no variation every few seconds, meanwhile no other risk factors more than 6 h total per day

    

 No

32

29

1

 

 Yes

119

105

0.78

(0.21–2.88)

Intensive keying and hand / wrist in awkward posture more than 4 h total per day

    

 No

26

24

1

 

 Yes

125

110

0.61

(0.13–2.85)

Intensive keying and no other risk factors more than 7 h total per day

    

 No

31

29

1

 

 Yes

120

105

0.44

(0.10–2.23)

Repeated impact

    

Using the hand (heel/base of palm) as a hammer more than once per minute, more than 2 h total per day

    

 No

41

34

1

 

 Yes

110

100

2.06

(0.73–5.83)

Using the knee as a hammer more than once per minute, or more than 2 h total per day

    

 No

55

45

1

 

 Yes

96

89

2.83

(1.01–7.92)*

Heavy, Frequent or Awkward Lifting

    

Lifting object weighing more than 75 lb and more than 10 times per day

    

 No

115

104

1

 

 Yes

36

30

0.53

(0.18–1.55)

Lifting object weighing more than 55 lb and more than 10 times per day

    

 No

13

11

1

 

 Yes

138

123

1.49

(0.30–7.38)

Lifting objects weighing more than 10 lb if done more than twice per minute, or more than 2 h total per day

    

 No

28

21

1

 

 Yes

123

113

3.77

(1.29–11.01)*

Lifting objects weighing more than 25 lb above the shoulders, below the knees or at arms length more than 25 times per day

    

 No

27

23

1

 

 Yes

124

111

1.49

(0.44–4.97)

Moderate to high hand-arm vibration

    

Using impact wrenches, carpet strippers, chain saws, percussive tools (jack hammers, scalers, riveting or chipping hammers) or other tools that typically have high vibration levels, more than 30 min total per day

    

 No

52

44

1

 

 Yes

99

90

1.82

(0.66–5.03)

Using grinders, sanders, jigsaws or other hand tools that typically have moderate vibration levels more than 2 h total per day

    

 No

46

41

 

1

 Yes

105

93

0.95

(0.31–2.86)

LBP low back pain, OR odds ratio, CI confidence interval

*Significant at p < 0.05

Psychosocial risk factors exposures

Table 3 shows the means and standard deviation on the subscales of the SCL-90 in the LBP positive group were significantly higher than those in negative group (P < 0.05). The three items with highest scores were obsessive compulsive, somatization, and depression.
Table 3

Comparison of psychosocial health situations in the LBP positive and negative groups among OMPWF

Subscale

The LBP positive groups(n = 134)

The LBP negative groups(n = 17)

t

P

Mean

S.D.

Mean

S.D.

  

Somatization

1.77

0.59

1.36

0.37

8.115

0.000

Obsessive compulsive

1.83

0.59

1.56

0.51

4.405

0.000

Interpersonal sensitivity

1.57

0.62

1.39

0.41

3.404

0.001

Depression

1.64

0.61

1.46

0.44

3.463

0.001

Anxiety

1.53

0.58

1.38

0.45

3.028

0.003

Hostility

1.51

0.58

1.34

0.38

3.390

0.001

Phobic anxiety

1.27

0.45

1.17

0.28

2.433

0.016

Paranoid ideation

1.52

0.58

1.38

0.38

2.812

0.006

Psychoticism

1.52

0.53

1.29

0.36

5.079

0.000

LBP, low back pain

Body dimensions factors exposures

Figures 1 and 2 show the prevalence of LBP among participants with height less than 168 cm or higher than 176 cm was significantly higher than those with height ranging from168 to 176 cm, presenting a concave characteristic. Although the sample size of this study was small, there was a changing trend of concave, namely, the prevalence of LBP among those whose hip knee distance was less than 510 cm or longer than 570 cm was significantly higher than those with hip knee distance ranging from 510 to 570 cm.
Fig. 1

The prevalence trends of LBP by different height levels

Fig. 2

The prevalence trends of LBP by different hip knee distance levels

Individual and lifestyle factors exposures

The individual and lifestyle factors are presented in Table 4. There was a significant association between LBP and some individual and lifestyle factors (i.e. using computer during your spare time and the height of desk).
Table 4

Individual and lifestyle factors of LBP among OMPWF with univariate analysis

Variable

Number of workers

Cases

LBP (%)

χ2

P

Age

     

  < 25

48

41

85.4

0.839

0.657

 25~

90

81

90.0

 30~

13

12

92.3

Working-age

     

  < 1

27

24

88.9

0.194

0.907

 1~

64

56

87.5

 3~

60

54

90.0

Weight (kg)

     

  < 60

31

27

87.1

0.856

0.652

 60~

60

55

91.7

 70~

60

52

86.7

Height (cm)

     

  < 170

53

48

90.6

3.949

0.139

 170~

49

40

81.6

 175~

49

46

93.9

Physical exercise

     

 yes

38

34

89.5

0.027

1.000

 no

113

100

88.5

Smoking

     

 Yes

57

51

89.5

0.049

1.000

 No

94

83

88.3

Drinking

     

 Yes

130

114

87.7

1.030

0.469

 No

21

20

95.2

Using the computer time during your spare time(h)

     

  < 1

17

17

100

11.926

0.008

 1~

32

26

81.2

 2~

51

50

98.0

 3~

51

41

80.4

The height of chair(cm)

     

  < 35

17

15

88.2

0.086

0.958

  > 50

21

19

90.5

 35–50

111

98

88.3

The height of desk (cm)

     

  < 50

76

68

89.5

9.691

0.008

  > 72

50

48

96.0

 50–72

25

18

72.0

Legroom underneath the desk

 

 Yes

111

96

86.5

1.906

0.240

 No

38

36

94.7

Whether the keyboard and mouse at the same height

     

 Yes

137

120

87.6

1.681

0.362

 No

12

12

100.0

Backrest

     

 Yes

45

36

80.0

3.610

0.069

 No

46

43

93.5

LBP low back pain

Multivariable model predicting LBP

The risk factors of LBP among OMPWF predicted by multivariable logistic regression model are shown in Table 5. The multivariable model showed that after adjusting for other factors, squatting more than 4 h total per day (adjusted odds ratio (AOR) 3.10, 95 % CI 1.10 to 8.80), lifting objects weighing more than 10 lb more than twice per minute, more than 2 h in total per day (AOR 4.29, 95 % CI 1.15 to 15.94), and somatization (AOR 2.70, 95 % CI 1.48 to 4.91) were positively associated with LBP, while backrest was inversely associated with LBP(AOR 0.36, 95 % CI 0.20 to 0.67).
Table 5

Multivariate logistic regression model predicting the risk factors of LBP among OMPWF

Variable

Coefficient

Waldχ2

AOR

95%CI

P value

Backrest

−1.010

10.800

0.36

0.20–0.67

0.001

Somatization

0.992

10.595

2.70

1.48–4.91

0.001

Squatting more than 4 h total per day

1.133

4.543

3.10

1.10–8.80

0.033

Lifting objects weighing more than 10 lb if done more than twice per minute, more than 2 h total per day

1.455

4.718

4.29

1.15–15.94

0.030

AOR adjusted odds ratio, CI confidence interval

Discussion

There have been a large number of available data on the prevalence of the LBP in traditional industries, such as manufacturing [12], automotive industry [13], health care industry [14], and steel industry [15], while there is little information about these issues in the wind power industry. This study revealed the prevalence of LBP on the OMPWF was up to 88.74 % in the past 12 months. This is higher than the yearly prevalence of LBP reported on other occupational group in the literature, which varies from 20 to 68 % [1619]. These findings suggest that OMPWF are at high-risk of suffering from LBP.

In this study, multivariable logistic regression analysis revealed a number of correlates of LBP including adverse ergonomic, psychosocial, or lifestyle factors. Of the adverse ergonomic factors, OMPWF who reported squatting more than 4 h per day were 3.10 times more likely to suffer from LBP than those who did not. Our study supports previous findings highlighting the prolonged static postures, particularly the squatting position as the most aggravating factor to be associated to LBP [20]. In addition, the strongest association in this cross-sectional survey was observed between LBP and lifting objects weighing more than 10 lb more than twice per minute for more than 2 h in total per day. In our study, heavy and awkward lifting was related to LBP with a high odds ratio of 4.29. This finding is in accordance with other research in which manual handling has previously been shown to be a common LBP risk factor. In Australia and New Zealand, manual handling in the preceding 12 months increased the likelihood of LBP among nurses and midwives [21]. Similarly, Okunribidofound manual handling increases risk for LBP among city bus drivers [22]. According to this investigation, OMPWF maintain and troubleshoot various engineering mechanical parts in the nacelle, which is a narrow and confined space for a long time. Due to the constraints of the dimension in the nacelle, OMPWF have been forced to maintain poor posture, which includes squatting, stooping, and using a straight ladder to climb. As reported previously, awkward posture was to be associated with LBP [23]. This is consistent with the findings of our study.

The present study indicated that the SCL-90 scores of LBP-positive group were higher than that of LBP-negative group, which means that mental health of the former was worse than the latter. In the subscales score of SCL-90, the obsessive compulsive score is highest followed by somatization and depression. It seems that the adverse psychosocial health among OMPWF was associated with LBP. In several studies, psychosocial factors, such as high job strain, high job dissatisfaction, obsessive compulsive, somatization, and depression have been reported to increase the LBP prevalence [1, 24, 25]. A 3-year follow-up study of the general working population in Norway showed that psychosocial factors appeared as the most consistent and important predictors of LBP [26]. In a study, Urquhart DM found a strong association between somatization and the prevalence of LBP [27]. From the view of physiology, adrenaline will be released and meanwhile blood flux accelerated when people become nervous or scared, resulting in motivated muscle activity to cope with stress [28]. However, the present study was cross-sectional in design, therefore it cannot provide any confirmatory evidence in favour of a cause-effect relationship between these two variables.

Despite the small sample size of this study, trends in the occurrence of in correlation with the body dimensions of an individual can be seen by our data. It is interesting to note that Figs. 1 and 2 show a “U-shaped” relationship between body dimensions and the prevalence of LBP. The height cut-points indicate that individuals with height less than 168 cm or higher than 176 cm have an increased risk. Therefore, it seems that the space of nacelle is more suitable for workers with a height between 168 and 176 cm in terms of ergonomics. Given that the proper range of body size is too narrow, wind turbine design engineers should consider redesigning the inner structure in nacelle based on the ergonomics to reduce the risk of LBP.

Our study indicate that using the computer during spare time and the height of desk could also influence LBP prevalence. According to OSHA ergonomic solutions, height-adjustable desks should generally be between 20 and 28 in. (50–72 cm) high [29]. This study also confirmed that the prevalence of LBP was at the lowest level within this height range. Furthermore, the multivariable logistic regression model showed that backrest was a protective factor. Thus, it might be indicated that from an ergonomic point of view, the most basic concepts of supporting the back in order to avoid bending more than 30° have been demonstrated to reduce the occurrence of the LBP [30].

In this study, LBP was diagnosed through self-reported questionnaire in combination with rigorous palpation inspection which might lower the recall bias. Nonetheless, the study still had several limitations. First, since the present study was cross-sectional, we could not establish causal inference. In future studies, longitudinal cohort studies should be more appropriate to further elucidate the causal correlates between those factors and the LBP consequences. Second, this study used only a small sample size of OMPWF in a large wind turbine manufacturer in China, which may not represent the industry-wide working conditions of operation and maintenance personnel in wind farms. Therefore, further studies with larger sample size are needed to improve the industry representation.

Conclusions

It can be concluded that LBP appears to be a serious problem among OMPWF and highlights a major health concern. The association between some risk factors, such as adverse ergonomic factors (squatting more than 4 h total per day and lifting objects weighing more than 10 lb if done more than twice per minute, more than 2 h total per day), psychosocial factors (somatization), and individual, lifestyle factors (using the computer too long during spare time) and LBP were highlighted in this study. It is obviously essential to make intervention strategies concentrating on ergonomic factors (improving the narrow working space in the wind farms, reducing awkward or tiring positions) as well as the psychosocial factors (managing work stress, carrying out various forms of cultural and sports activities and psychological counseling and persuasion) to prevent and minimize the occurrence of LBP among OMPWF.

Abbreviations

AOR, adjusted odds ratio; LBP, low back pain; NMQ, Nordic Musculoskeletal Questionnaires; OMPWF, operation and maintenance personnel in wind farms; SCL-90, syndrome checklist-90; WSET, Washington State Ergonomics Tool

Declarations

Acknowledgements

We would like to appreciate Wind power Division of Zhuzhou Electric Locomotive Institute Corporation, China South Locomotive and Rolling Stock (CSR) which provided survey site and financial support, and Labor Health Occupational Disease Prevention and Control Center in Zhuzhou which completed the data entry and provided great contribution and kind cooperation.

Funding

This study was supported by grants from the National Natural Science Foundation of China (81172643) and National Key Technology Research and Development Program of the Ministry of Science and Technology of China(2014BAI12B03).

Availability of data and materials

Data will not be shared as consent for this was not included in the informed consent process.

Authors’ contributions

NJ conceived of the study, participated in its design, carried out the data collection, performed the statistical analyses, and drafted the manuscript. ZXW contributed to the study design, helped to revise the manuscript, and had the overall scientific responsibility. TL participated in the formulation of the study, supervised, and consulted in the drafting of the manuscript. SQH, XHZ, KS, LY, QZ and GLL participated in the description of background knowledge, the formulation of the study, and the data collection. YZL, XYZ and YEG participated in choice of statistical methods, interpreted data, and assisted with the statistical analyses. All authors read and approved the final manuscript.

Competing interest

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethics approval for the study was obtained from the Chinese Center for Disease Control and Prevention Human Ethics Committee. All participants signed informed consent for using their data for the research purposes.

Sponsorship

This study was supported by grants from the National Natural Science Foundation of China(81172643) and National Key Technology Research and Development Program of theMinistry of Science andTechnology of China(2014BAI12B03).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Occupational Protection and Ergonomics, National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention
(2)
Labor Health Occupational Disease Prevention and Control Center in Zhuzhou
(3)
Wind power Division of Zhuzhou Electric Locomotive Institute Corporation, China South Locomotive and Rolling Stock (CSR)
(4)
Hunan University of Technology

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Copyright

© The Author(s). 2016

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