We chose to survey a population of actively employed surgical device mechanics and compared them with a group of employees believed not to be exposed to repetitive hand and arm movements to such a large extent.
The overall prevalence of subjective upper extremity complaints (i.e. symptoms) was 47% (33/70). Eight of 20 (40%) grinders, 14/24 (58%) packers, and 11/26 (42%) people in the control group reported such symptoms. One or more upper extremity WMSDs (i.e. diagnoses) at the elbow, forearm and/or wrist were found in 56% (39/70), of which 12/20 (70%) grinders, 14/24 (54%) packers and 13/26 (42%) control persons. These results are consistent with previous studies showing a prevalence rate of symptoms between 21% and 71% in the study group and between 6% and 50% in the control group [34–46]. With regard to diagnoses, existing studies report a prevalence between 21% and 56% in the study group compared to 5–22% in the control group [35, 36, 38, 39, 40, 42]. Within the framework of the standardized clinical examination, we applied rather "softer" criteria, as recommended by Vikari-Juntura [47]. This might explain the higher detection of WMSDs via examination as compared to the lower number of subjective complaints reported in the questionnaire. An above average co-occurrence of medial epicondylitis (golfer’s elbow) and nerve entrapment at the medial elbow (cubital tunnel syndrome) was found in 30% of our test persons and 54% of the subjects with upper extremity complaints in this cohort [48–50].
The clinical endpoint values of our study population were largely consistent with the reference values of the general population, but in some cases (grip strength, PPB tests) also showed below average values. This is surprising and contradicts the study situation, as our cohort tends to have an above-average physical load [51]. Reasons could be mechanical support, shorter working hours and a historical shift in populations’ reference values without the first two points mentioned.
The aim of our analysis was to evaluate different clinically established endpoints representing surrogates for an actual health problem, for association with upper extremity WMSDs in terms of a technical evaluation of the survey methods. We also investigated the influence of socio-demographic, work-related and individual independent predictor variables as potential risk factors for WMSDs. The methodological approach is intended to be a proposal for a standardized procedure for future cross-sectional studies of this kind.
In the bivariate analysis we found a correlation between the DASH score and WMSDs as well as VAS under strain and WMSDs. A simple clinical explanation for this could be that pathology (WMSDs) manifests itself through pain, especially when the hand is used forcefully. This aspect is a common feature of the DASH questionnaire and also manifests itself with VAS under strain. VAS at rest, ROM, grip strength, PPB Test and the indication of subjective complaints by the study participants were not suitable to detect WMSDs in our study. However, the question of subjective complaints is a central component of many studies and the basis for their interpretation.
Regarding the upper extremity, the validity of questionnaires for WMSDs has not been clarified and it is not known how an optimal questionnaire can be constructed and what information can be obtained [52]. A purely technical investigation using measurement data without clinical examination would have the advantage of resource optimization but could not be related to WMSDs either [53]. This is also supported by the relatively weak correlation between measured clinical endpoints and WMSDs in our study. Accordingly, a clinical examination based on a predetermined set of diagnostic criteria remains the gold standard for cross-sectional investigations in order to keep well-defined disorders separate from more diffuse conditions. Although the clinical examination is time consuming and hard for both the subject and the examiner, it seems to be necessary so far to detect defined WMSDs.
Although the p-value has not quite reached the conventional significance level of 0.05 in our study (p = 0.056), the correlation we found between WMSDs and the DASH score may not therefore be considered non-existent and could be of interest for the design of future studies [54]. The validated DASH score as a self-administered, region-specific outcome instrument for upper-extremity disability and symptoms, was tested against the gold standard of WMSD detection (i.e. the clinical examination). To our knowledge, there are no studies focusing on the correlation between WMSDs and the DASH score, whereas this is the case for some upper extremity pathologies other than WMSDs [55]. According to our analysis, the DASH score has the potential to replace the resource-intensive clinical examination as a screening tool. In case of conspicuous DASH scores, the latter could be used in a focused manner for diagnosis, with therapeutic and preventive measures derived from it. In comparison, the Nordic Musculoskeletal Questionnaire (NMQ), often used in cross-sectional studies, is a simple validated questionnaire that refers to complaints in 9 body parts, including the hand/wrist/elbow [56]. Its content is in no way comparable to the detailed questions of the DASH with its focus on the upper extremity, and hardly exceeds the yes/no question on subjective complaints in our study. To what extent further questionnaires are suitable for the detection of upper extremity pathologies will be the subject of future studies.
For the endpoint WMSD, the multivariate analysis of our study did not show any independent predictors significant at a 0.1-level. This is partially in contrast to previous studies, in which work-related and sociodemographic characteristics have been determined as predisposing upper extremity disorders [34]. The first include static postures, excessive force and strain, vibration, repeated pushing, pulling and lifting, overuse of particular anatomical structures or regions, poor posture or improper positioning, awkward movements, long duration of pressure, rapid work pace, short recovery periods, low decision latitude, years of service and job satisfaction [57–61]. Socio-demographic characteristics predicting WMSDs include factors like sex, age, marital status, work experience, body mass index and physical activities [62–67]. It is advisable to select the characteristics of personal factors, physical body functions, environmental factors and mental body functions based on the International Classification of Functioning, Disability and Health (ICF) [68]. The scatterplot matrix with prediction ellipses has proven to be a fast graphic analysis and a preliminary stage for a detailed statistical evaluation in our study.
Multivariate analyses were also used to examine the independent predictors for other clinical endpoints. Significant positive correlations between ROM and years in service, more frequent subjective complaints of the upper extremity with increasing age, higher VAS under strain with a higher BMI, and higher grip strength with the presence of a secondary occupation and/or physically demanding hobbies are particularly noteworthy. These findings are relevant for future investigations, since the relationships of independent variables to each other may disturb the identification of risk factors for WMSDs, acting as confounders. These relationships should therefore be considered when analyzing any WMSD-related outcomes.
From a statistical point of view, the study has provided good statistical pre-conditions with regard to the proportion of WMSDs in our collective of 56%. As this proportion was close to the perfect balance between WMSD-positive and WMSD-negative cases, the power for group comparison was near to maximum for the given sample size. The very low p-values for effects in the analysis of grip strength (see Table 5) probably resulted from the increase in power due to the higher number of individual measurements (2 × 3 measurements per subject, i.e. total n = 420 in 70 subjects). However, the variance analysis employed in regression models with other simply measured values, lacks such amount of information regarding the variance of the measurements.
We intentionally tried to avoid the term "significant" in regard to this analysis, in order not to refer our reported p-values to the conventional 5% significance level which may be prone to misinterpretation [54, 69]. Using the concept of hypothesis testing in the scientifically accurate way, setting a significance level would require a multiplicity correction for a number of pre-defined tests. Such explicit correction would, on the other hand, take away our flexibility to follow effects and relations in our data, which contains a complex network of endpoints and their predictors. For this reason, this secondary analysis was clearly explorative. This means that the p-values shown in the tables are not referred to any significance level. They rather provide continuous information of how effects are related or ranked according to their strengths. In this respect, Table 3 in the results section has to be considered as identification of two potential candidates for appropriate surrogate measures for WMSD prevalence. However, real evidence for the adequacy of any of these candidates for WMSD detection in clinical use has to be generated by a dedicated study.
The DASH score was considered to be the surrogate endpoint of choice for our primary analysis of WMSD prevalence among medical device manufacturing employees. The current analyses confirm that DASH still has to remain as the closer choice, when assessing the WMSD status of a population.
Regarding the limitations of our study, it should be noted that cross-sectional studies always represent a snapshot and no statement can be made about the duration of an existing WMSD. In particular, it is not possible to clearly distinguish between chronic, recurrent, or acute diseases. As in other studies, we also focused on a manageable number of potential risk factors, since an increasing number of predictors increases the probability of false positive effects, especially in smaller samples. This makes it difficult to assess these effects as a whole. Due to the single investigator approach, there is a risk of systematic error for over-sensitive detection of WMSDs, which is indicated by the higher number of diagnoses compared to symptoms in our study. On the other hand, the examination was performed by the same hand surgeon, which may have led to the diagnosis at an earlier stage than in a clinical setting. However, reducing the systematic error by a multiple investigator approach would have brought an inter-observer error into play, arising as a result of different teaching backgrounds and subjective assessments. Repeating the physical examination tests by having two investigators examine the same person was not an option for the authors A major reason for this is that most test results depend on the announcement of symptoms (pain, numbness, etc.) and subjects learn during follow-up examinations, which limits the objectivity of such study designs [53]. Even though the cross-sectional design of our study does not permit causal inference, the observed relations provide valuable evidence for further research and policy making. For further limitations with regard to the three occupational activities, we would like to refer to our previous publication [17].