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task based exposure assessment in ergonomic epidemiology: a study of upper arm elevation in the jobs of machinists, car mechanics, and house painters

by:QY Precision      2019-10-16
Safactaims: compared to direct measurement of work exposure, the accuracy of task-based upper limb elevation estimates for three occupational groups was explored.
Method: male mechanic (nu200a=u200a26)
Car mechanic (nu200a=u200a23)
And house painters (nu200a=u200a23)were studied.
For 4 consecutive working days, obtain full-day records of upper limb elevation and collect relevant task information in the diary.
For everyone, task-based job exposure estimates are calculated by adding task exposure from the collective database according to the diary\'s proportion of tasks.
The work exposure of the direct measurement was verified using linear regression.
The performance of the task-based approach is expressed by obtaining the accuracy of the average exposure of the occupational group, which can be expressed by adding subjects with task-based estimates to a design with \"validation.
Results: in all three occupations, the average exposure of tasks was different and the proportion of tasks among individuals was different.
Task-based estimates have proved inefficient, with the square correlation factor occasionally exceeding 0.
2 Relationship between job exposure based on task and measurement.
Therefore, it is not possible to significantly improve the accuracy of estimated population averages by including subjects whose work exposure is based on task information.
Conclusion: Task-based mechanical work exposure estimates may be highly inaccurate, only slightly better than career-based estimates.
It is recommended that ergonomic epidemiology researchers carefully consider the prospect of task-based exposure assessment before investing resources to obtain task information.
In many cases, it may be better to ignore the strategy of the task.
Accurate and accurate exposure data are essential in occupational epidemiology.
In the present case, \"accuracy\" and \"accuracy\" respectively refer to the absence of systematic and random errors.
Inaccurate exposure assessment hinders the determination of quantitative exposure
Reactive relationships and may lead to false negative conclusions about the significance of the cause of occupational exposure.
1, 2. there are two basic methods for estimating current exposure in the study population: a \"personal\" method in which exposure was assessed separately for each subject, and a \"group\" method, in this approach, all individuals belonging to a group are assigned an average exposure of the group.
3, 4 exposure groups can be defined according to other common features of the occupation or working environment. Exposure 5-7-
Results based on linear regression of continuous variables show that the population approach minimizes attenuation, but implies greater inaccuracy than the individual.
However, in the logical regression of the binary results of continuous exposure, even a group approach would lead to increased deviations as exposure variability between subjects increased and the accuracy of group averages decreased.
8 in large-scale epidemiology studies, feasibility considerations generally tend to favor a population-based approach in which the average exposure from sub-populations
Individual samples from specific occupational groups were assigned to subjects who did not provide any exposure information other than their group members.
By adding more individuals and/or measuring days to the measured subtasks, the accuracy of work exposure estimates can be improvedsample.
Measurement is often expensive in terms of the time required for equipment and data processing.
This leads to the method of searching for estimated exposure based on cheap descriptors.
The task composition of the position was proposed to indicate the overall job opportunity.
If this is the case, an effective way to obtain accurate group average estimates may be to assess the work exposure of individuals in the group by combining the proportion of individual tasks at work
For example, obtained through a diary
Direct measurement of task exposure from the database obtained on fewer subjects.
Several ergonomic studies use a task-based approach to estimate work exposure.
Some studies used individual task exposure to simulate individual exposure within a few days.
9-11 other studies simulated the exposure of subjects according to the collective task exposure matrix (TEMs)
Obtained from literature 12, 13 or constructed as part of the study.
14-16 task information is also used to sample exposure data within the measurement day.
17 the potential usefulness of task-based modeling has been discussed based on the relative exposure variability within and between tasks 18, 19 and the variance of task-based estimates and the variance of observed work exposure
14 The ability of task-based assessments to assess work exposure was also assessed, 9,13, 20, but no discussion was made as to whether job-based exposure assessments that ignored the task were equally effective.
In order to extend the existing mechanical exposure assessment guidelines to a mission-based strategy, such surveys are required.
1,21-23 the purpose of this study was to use collective TEM to explore the performance of task-based work exposure estimates, expressing performance as an improvement in the average exposure accuracy of occupational groups, this can be obtained by adding subjects with task-based estimates to the subject group with measurement exposure in the \"validation\" design.
24 This study is based on empirical data on upper limb elevation collected as part of the shoulder disease epidemiology study.
Job exposure based on primary information is estimated to be unsuccessful.
The accuracy of the average exposure of occupational groups obtained by direct measurements of some subjects is difficult to improve by adding subjects who can only obtain task-based work exposure estimates.
The subjects include mechanics, car mechanics and house painters.
Within the geographical area identified, all the companies concerned were identified in the central business register of Denmark.
Companies that do not include less than five workers are included only when they have computer operated CNC tools (CNC tools).
The final corporate base consists of 29 machine shops, 110 home car garages and 119 painter workshops, with a total of 942 mechanics, 692 car mechanics and 1579 house painters.
13 pairs of colleagues were randomly selected from each professional group.
The pairing sampling was for logistical reasons.
For each topic, a work week was selected for data collection.
The inclusion criteria are at least one year of work in the prescribed week, male, aged 30-65, with at least four scheduled working days.
If the subject has a shoulder complaint that interferes with his or her work performance, it is excluded.
When a subject is excluded (nu200a=u200a1)
Or do not want to participate (nu200a=u200a6)
, He was replaced by another randomly sampled subject, preferably from the same company.
The project was approved by the scientific ethics committee system.
The data collection survey was conducted from August 1999 to February 2000.
All three career categories are represented throughout the data collection process to cover seasonal changes.
During the selected week, all working days are measured throughout the day, usually starting on Monday.
If the recording is lost, the subject is required to attend for an additional day.
In six 15 ° intervals from 0 ° to 90 °, the upper arm height is measured relative to gravity, and the coverage angle of one interval is greater than 90 °.
Measurement at a frequency of 1Hz using a inclination meter (abduflex)
Continuous registration is allowed for 8 hours.
27-29 the present study focused on the right arm, not the dominant arm, as the working conditions of the mechanics and car mechanics forced the right and left-handed subjects to adopt a similar working method.
For each occupational group, work with professional ergonomics and experienced businessmen to build a diary with 10-12 pre-printed tasks.
These tasks are designed to cover all processes in the job and represent meaningful and common job elements.
Initially, a pragmatic task definition was selected based on the list of tasks prepared by the merchant who helped build the diary.
In order to ensure the exposure contrast between tasks, the tasks are then grouped according to the typical degree of arm elevation judged (
0 ° to 30 °, 30 ° to 90 ° or above).
Finally, under control, the diaries cover all of the tasks mentioned in the description of the Danish mechanic apprenticeship training, some of which come from a large garage for home car invoices, as well as a list of tasks prepared by employee health services for Danish painters to help businesses conduct workplace assessments in accordance with Danish legislation.
During the measurement, the Subject fills in the diary each time a new task is started.
The clock time report in the diary is synchronized with the abduflex recording.
Policy implications in ergonomics epidemiology suggest that researchers carefully consider the prospect of task-based exposure assessment before investing resources to obtain task information.
In many cases, it may be better to ignore the strategy of the task.
The processing of the data set source data set is defined for each business group (fig 1).
Processing abduflex data to give the percentage of time when the right upper arm is lifted (a)
More than 90 degrees, and (b)
More than 90 ° for 5 seconds or more in a row.
These two exposure variables were selected based on a general hypothesis regarding the pathogenesis of shoulder disease, aged 30-32, in order to reflect the underlying dimensions of exposure
That is the length of time, level and frequency. 1 variable (b)
Determined after exposure change Analysis 33 and expressed cycle length-
In several tested alternatives
This gives the best contrast between careers.
Calculate exposure variables for each task that occurs throughout the working day and during the day.
If the subject performs a given task more than once in the day, the recording in the task is brought together.
Download the new tabDownload figureOpen powerpointFigure 1 Source data set (bottom boxes)
For mechanics, car mechanics and house painters.
Ns, nd, nh: number of subjects, number of days and number of hours using arm elevation data.
Summary statistics are derived by calculating the arithmetic mean of days per subject and then averaging specific average exposure of these individuals to obtain the occupational group average.
A set of task exposure means for the formation of estimated TEM (below).
In a one-way stochastic effect model, exposure differences between subjects and subjects were estimated using a restricted maximum likelihood algorithm (SAS 6. Month Proc Varcomp).
Task-based exposure assessment and regression calibration for each participant, a specific TEM was constructed using exposure data from all other subjects in the occupational group to simulate cases where the subject himself did not contribute to the TEM.
If a task is performed by only one subject, the measured average work exposure of the group is used instead of the missing task exposure, again omitting the subjects considered.
For each diary day, job exposure is modeled by the weighted average of task exposure in the TEM, using the proportion of tasks in the diary as the weight.
1 Four task-based job exposure estimates were received per participant-
That is, the simulated work exposure on the first day, the mean for the first and second days, the mean for the first and third days, and the mean for all four-day data collection.
Using this data set, we investigate the performance of \"double sampling\", 34 \"direct and indirect binding\", 35 or \"validated\" designs, among them, a large number of exposure data were collected from a limited subject \"validation\" sample and used to estimate exposure to other subjects who only had limited information available.
It was suggested that the validation design be used as a tool to maximize the accuracy of the estimated population means associated with the input resources.
In our case, subjects in the validation sample were able to obtain measured work exposure and task-based estimates.
In this sample, linear least squares regression is used to determine the relationship between the average work exposure of individuals based on tasks and measurements in one to four days of data collection (SAS 6. 12 Proc Reg; fig 2).
Virtual subjects outside 34, 35 places were subsequently considered included in the diary --only sample.
For these subjects, only task-based work exposure estimates are available, which assume calibration using validation sample regression.
34, 35 download a regression analysis example of the average working exposure measured by figureOpen in the new tabDownload powerpoint figure 2, which is based on the task to estimate the upper arm height above 90 °.
Painter (nu200a=u200a23)
Collect data for four days per topic.
For combination groups of verification and diary-
Only the subjects, the standard error s μ of the average exposure of the group was determined according to: 34, 35, where sS2 was the difference between the average work exposure of the individual measured in the validation sample, ρ 2 is the square correlation between the measurements obtained from linear regression in the validation sample and the estimated individual average work exposure, NV is the number of subjects in the validation sample, nD is the number of subjects in the diary-only sample.
So if the task-based estimate is perfect-
That is to say, 22 = formul1, the first term in equation 1 disappears, and s μ is a direct inverse function of the total number of subjects (nV+nD).
If the task-based estimate is very inaccurate-
That is, 2 2 is close to 0, the second term disappears, and s μ is close to the variance of the average exposure measured in the validation sample, which means adding a diary-
Only subjects did not improve the accuracy of the combined group average.
We explore the accuracy of combined group averages by solving validation of different sizes and equation 1 of diary
Only samples were used to obtain sS2 square correlation coefficients and empirical values for one to four days per subject using the source dataset.
For comparison, we only estimate the accuracy of the group mean obtained by direct measurement.
The standard error of the mean is calculated based on: Where ns is the number of subjects.
The equation solved 1 to 100 subjects and used sS2 experience values for 1 to 4 Measurement days per subject to study the effect of increasing the number of days.
Results source data set 1 shows the features of subjects in three source data sets.
Table 2-4 provides data materials, mean exposure, and exposure variability at work and task levels for mechanics, car mechanics, and house painters, respectively.
For the two exposure variables, the average exposure of the house painter was the highest and the average exposure of the mechanic was the lowest.
At the level of work, we found considerable exposure variability between subjects and between days within subjects, and the relative size of these two variance components varies between groups.
In each occupational group, the tasks of average contact are different.
The distribution of tasks between individuals varies greatly, as shown in the wide range of the percentage of daily measurement time spent by each task.
The only task that happens on a daily basis for all subjects in the profession is a \"break\" between mechanics \".
A few days later, no breaks were found in house painters and car mechanics, but in most cases the diary contained periods without a task specification.
In general, internal
Compared with the variability of the work level, the variability of task exposure is quite large.
View this table: view the features of topics in the source data view this table: view inline View pop-up table 2 data material, average exposure and machinistview work and task level exposure of this table View inline View pop-up table 3 data material of work and task level of car machinery View, average exposure and exposure variability this table: view the pop-up table 4 data material in inline View, the average exposure and exposure variability of work and task levels in the exposure assessment form 5-7 based on family paintersTask showed the measured group average exposure and related overall differences between subjects, ss
As expected, sS2 tends to decrease when more days are included in the individual\'s average work exposure estimates.
These tables also show the linear regression results of the task-based individual average work exposure measurement (cf fig 2).
There are only four square correlation coefficients p 2 more than 0.
50, they can all be attributed to outliers with high measurement risk.
When he was removed from the analysis, the 2 2 value was reduced to about 0. 10.
His deviation results cannot be attributed to errors in the diary and measurement data.
The same is true of a peripheral car repairman.
View this table: View the average daily exposure, exposure variability in the inline View pop-up table 5 the number of days of data collection per subject in machinistsView, results from linear regression analysis based on task-based personal average work exposure measurements. This table: view inline View pop-up table 6 exposure variability in work and linear regression analysis results of task-based measurements personal average work exposure based on data collection days per subject in the automotive mechanical View this table: looking at the exposure variability in the work of the inline View pop-up table 7 and the results of linear regression analysis based on the task-based individual average work exposure measurement, for example, in a mechanic, data collected by each subject exceeds 90 ° Figure 3 illustrates the accuracy of the group average when validation and diary are combined
Only samples, when only subjects with direct measurement of work exposure are included.
As expected, the accuracy of the group average is improved-
That is, when more subjects with measurement work exposure are included, the standard error is reduced.
The effect of increasing the number of measured days per subject was far less obvious.
Therefore, s mu of 0.
By monitoring 15 subjects per day or 13 subjects per day, 5% of the time can be obtained.
Subjects with task-based exposure estimates were included, improving the accuracy of the group average, only slightly higher than the accuracy of the subjects directly measured in the validation sample.
Download figureOpen in the new tabDownload powerpoint figure 3, and evaluate the performance in the mechanic based on the exposure of the task\'s arm height of more than 90 °.
For a fully measurement-based work-based strategy, the relationship between the group mean, s μ, and the standard error studying the group size is shown, strategies for combining the subject\'s \"validation sample\" with the measured work exposure and \"Diary\"
Only sample of subjects with a calibrated task-based estimate \".
NV, verify the number of subjects in the sample;
Number of topics in the diary-only sample.
The present study examined the performance of task-based arm elevation assessment above 90 ° in three occupational groups.
The survey method combines the proportion of individual tasks in the diary with the exposure data of the collective TEM.
Task-based job exposure estimates proved unsuccessful.
Therefore, only by adding subjects with a task-based exposure estimate to a directly monitored sample of subjects can a negligible gain of the group\'s average exposure accuracy be obtained, which in the validation design is
The present study represents most of the exposure spectrum in a wide range of occupational groups, and it is reported that direct measurement data of upper arm heights above 90 ° for these occupational groups include construction workers, 36-38 industrial workers, there are 36 office workers.
28 when considering the differences in the survey design, our results are consistent with previous abduflex measurements for house painters.
36 many ergonomic studies classify tasks from the perspective of bioengineering, such as the proportion of daily working hours of the hand above the shoulder.
29,39-41 however, it turns out that it is difficult to obtain accurate and accurate information about the duration of such \"tasks\" through cheap methods such as self-assessment
Report or expert judgment
42,43 as an alternative, tasks can be classified according to the natural elements of the work.
Tasks such as 9, 10, 14, 18 are more easily identified by subjects, indicating that the self can obtain a reasonable and correct task duration
Report, at least 44,45 in work where the task has not changed rapidly.
However, nature task categories may not have much contrast in exposure.
17, 46 we have developed a program to build diaries that aims to synthesize the best features of the classification based on the biological mechanics and the \"nature\" criteria.
Diary is very effective in practice.
Cycles that do not have a task specification rarely occur, and rarely use the option to insert supplementary tasks in a diary.
In addition, compared with other studies that split the work into its constituent tasks, the comparison between task exposures is significant.
The facial validity of 14, 17, 46,47 TEM was good, as the merchants who helped build the diary arranged the task exposure in the order expected.
The proportion of tasks between individuals is also different (cf tables 2–4)
As a further indication of the possible success of task-based exposure estimates.
It turns out that the task-based estimate is very inaccurate.
If tasks with large exposure changes can be split into sub-tasks, the predictive power of task-based estimates may be bettertasks.
Another possible improvement is to perform a posterior clustering of tasks based on their empirical exposure.
In any case, quite a few interiors
As data from highly restricted tasks under controlled experimental conditions suggest, task variability of upper arm elevation may be inevitable.
48 The time point at which the task starts and ends is reported at a resolution of 5-15 minutes.
This introduces errors in the estimated work exposure, not only because the task duration is inaccurate, but also because the task exposure is extracted according to the diary schedule.
However, an examination of the recording of abduflex indicates that the exposure level did not change suddenly at the beginning of the new task.
In addition, the task sequence is relatively long, which further reduces the importance of this error source.
46 more accurate task schedule information can be obtained by observing subjects, but in this study indirect exposure assessment is more expensive than direct measurement.
Information about the occurrence of a single task can also be tracked in production records.
However, the quality of these data may not be better than diary information, and there are no similar records for the three occupational groups.
Due to the continuous measurement schedule, the amount of data for a particular task is proportional to its occurrence in the occupation.
While proportional sampling may be an effective strategy for determining individual average task exposure, it also means uncertain exposure for rare tasks.
Additional data collection may be required for selected rare tasks.
However, we believe that any of the above possible improvements will not significantly change the performance of the mission-based strategy.
In the energy expenditure study using validation samples, collective TEM was explored to simulate working exposure of subjects.
13 estimates of personal job exposure were obtained by combining self
The \"usual\" task duration with task exposure was reported from the literature database.
The \"real\" work exposure was obtained through a two-working day task stratified measurement.
The square correlation coefficient is 0.
49 was found between estimates and real exposure, which was attributed to the use of task information.
However, the study included 27 subjects from 21 occupations, and the exposure levels of these subjects could vary significantly even if there were no examination tasks --
For example, the librarian is a carpenter.
The results of this study show that the work exposure matrix is equally effective for estimating the exposure of the study subjects, and the efforts invested in obtaining and using task information may not be very effective.
The possibility was not discussed by the author.
In a study of tank terminal workers, task-based modeling was performed on subjects using collective TEM constructed as part of the study. 14 The within-
The daily exposure variance based on the task estimate was less than the observed exposure.
Based on this, it is concluded that the estimation of physical load can be improved through task-based exposure assessment.
However, this interpretation does not take into account the collective average task exposure obscures variability between and within subjects performing a particular task.
Other ergonomic studies have evaluated alternative methods of using individual task exposure to estimate exposure of subjects over a few days.
In a study of cleaners and office workers, direct measurements of a full working day were performed for each subject and estimated work exposure was obtained using the average task ratio of 10 diary days per participant
9 for 10 and 90 cm of the cumulative distribution of the prone angle of the arm, 1-
Day measurement and 10-
The daily average estimate is highly correlated with a square correlation coefficient of 0. 95 and 0.
98 respectively.
The author concluded that there was no need to collect task information, as a measurement day seemed sufficient to assess the worker\'s long-term average exposure level.
However, the analysis did not take into account the variability of task exposure between different days, reducing the ability of task-based estimates to predict between different days (cf tables 2–4).
In the assessment of the task-based interview technique, the \"real\" work exposure was obtained by observation in one shift, estimated job exposure was calculated by combining task duration and individual task exposure reported during the interview.
Both the interview and observation were assumed to represent the average work exposure of the subjects.
In this regard, the results involve modeling of cross-day exposure, although daily exposure is not consideredto-Change of day.
For the four exposure variables, including \"standing above the shoulder with one hand or both hands\", The Square correlation coefficient is from 0. 53 to 0.
86 The relationship between estimates and \"real\" exposures.
However, the assessment was based on the subjects of the occupational group, who were significantly different in terms of exposure.
As noted above, this means that the study did not assess the benefits of task-based exposure assessment, exceeding the benefits that work-based exposure assessment would gain, while ignoring the task
That is, by interviewing subjects about the overall exposure in their work.
Based on the above discussion, we suspect that the lack of success of task-based estimates is not limited to the occupational environment investigated in this study.
On the other hand, studies from other areas of occupational epidemiology show that if the exposure contrast between tasks is very large and individuals at work have completely different jobs, task information may have a valuable role in the assessment of exposure in the occupational group.
49,50 this may also apply to selected ergonomic exposure variables in certain occupations (
Cf Nordander and colleagues 51).
Conclusion The accuracy of the group mean obtained by direct measurement of some subjects can only be slightly improved by adding subjects who can only obtain task-based work exposure estimates.
This is a consistent finding among the three occupational groups representing a wide range of work tasks and work exposure levels.
The results questioned the use of task-based exposure assessments in ergonomic surveys targeting precise group averages, including population-based exposure studies
Response Relationship
The discovery of weak correlation between estimated and measured work exposure also suggests that task-based work exposure estimates may not be superior to those based on exposure occupations --
Response studies using individual exposure assessment methods.
Therefore, we suggest that ergonomic epidemiology researchers carefully consider the prospect of task-based exposure assessment before investing in resources to obtain task information.
In many cases, it may be better to ignore the strategy of the task.
The project is funded by the Danish Rheumatism Association (grant no. 233-1021-21. 07. 98)
Danish Health Insurance Fund (grant no. 11/271-98)
And the research program of Aarhus University Hospital (grant no. 2-16-4-12-98).
S. W. Svendsen is supported by the School of Health Sciences at Aarhus University.
S. E. Mathiassen did part of his work as a visiting scholar at the Institute of Free mutual assistance and security in Ma hop Kinton, USA.
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