Describe how to calculate the incidence rate for musculoskeletal disorders (MSDs) and cumulative trauma disorders (CTDs) in a workplace. What do you bel

International Journal of

Environmental Research

and Public Health

Article

Quantitative Models for Prediction of Cumulative Trauma Disorders Applied to the Maquiladora Industry

Melissa Airem Cázares-Manríquez 1 , Claudia Camargo-Wilson 1, Ricardo Vardasca 2,3,4 , Jorge Luis García-Alcaraz 5,* , Jesús Everardo Olguín-Tiznado 1 , Juan Andrés López-Barreras 6

and Blanca Rosa García-Rivera 7

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Citation: Cázares-Manríquez, M.A.;

Camargo-Wilson, C.; Vardasca, R.;

García-Alcaraz, J.L.; Olguín-Tiznado,

J.E.; López-Barreras, J.A.;

García-Rivera, B.R. Quantitative

Models for Prediction of Cumulative

Trauma Disorders Applied to the

Maquiladora Industry. Int. J. Environ.

Res. Public Health 2021, 18, 3830.

https://doi.org/10.3390/ijerph18073830

Academic Editor: Wing-Keung Wong

Received: 23 January 2021

Accepted: 1 April 2021

Published: 6 April 2021

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4.0/).

1 Faculty of Engineering, Arquitecture and Design, Autonomous University of Baja California, Ensenada BC 22860, Mexico; [email protected] (M.A.C.-M.); [email protected] (C.C.-W.); [email protected] (J.E.O.-T.)

2 Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal; [email protected] or [email protected]

3 INEGI, Universidade do Porto, 4200-465 Porto, Portugal 4 ISLA Santarém, 2000-241 Santarém, Portugal 5 Department of Industrial Engineering and Manufacturing, Autonomous University of Ciudad Juarez,

Ciudad Juárez CHIH 32310, Mexico 6 Faculty of Chemical Sciences and Engineering, Autonomous University of Baja California,

Tijuana BC 22390, Mexico; [email protected] 7 Faculty of Administrative and Social Sciences, Autonomous University of Baja California,

Tijuana BC 22390, Mexico; [email protected] * Correspondence: [email protected]

Abstract: Temperature gradient changes on the surface of the skin or in the middle of the body are signs of a disease. The aim of this study is to develop quantitative models for the prediction of cumulative trauma disorders (CTDs) arising from highly repetitive activities, considering risk factors, such as age, gender, body mass index (BMI), blood pressure (BP), respiratory rate (RR), and heart rate, to prevent injuries in manufacturing factory operators. This research involved 19 individuals from the area of sanding and 14 individuals from the area of tolex in manufacturing factories who had their vital signs and somatometry taken, as well as thermal images of their hands in the dorsal and palmar areas; an evaluation by the OCRA method was also applied. Factors such as BP and heart rate were determined to significantly influence the injuries, but no strong association with BMI was found. Quadratic regression models were developed, the estimates of which were adequately adjusted to the variable (R2 and R2 adjusted > 0.70). When integrating the factors of the OCRA method to the generated models, a better fit was obtained (R2 and adjusted R2 > 0.80). In conclusion, the participants who present levels out of the normal range in at least one of the factors have high probabilities of developing injuries in their wrists.

Keywords: age; blood pressure; body mass index; carpal tunnel syndrome; cumulative trauma disorder; heart rate; infrared thermography; respiratory rate; gender

1. Introduction

Musculoskeletal system disorders (MSDs) refer to health problems in the locomotive system; that is, muscles, tendons, skeleton, cartilage, joints, ligaments, blood vessels, and tendons [1,2]. MSDs are a set of symptoms and injuries (inflammatory or degenerative) of the musculoskeletal system, and are related to the neck, back, and upper and lower extremities of the body [3]. MSDs are the most common occupational diseases in industry. They derive from various causes, and are divided into two categories: those caused by acute trauma, such as slips or falls, and those due to repetitive exposure to a type of physical activity, known as cumulative trauma disorders (CTDs), meaning that these injuries develop over time, which can be as long as weeks, months, or even years of

Int. J. Environ. Res. Public Health 2021, 18, 3830. https://doi.org/10.3390/ijerph18073830 https://www.mdpi.com/journal/ijerph

Int. J. Environ. Res. Public Health 2021, 18, 3830 2 of 19

propensity to repetitive stress, so that they are not due to a single temporary event, as is the case of the first category, but to various micro-traumas [1,2].

When MSDs are caused by work-related issues, they are called work-related mus- culoskeletal disorders (WMSDs) [4]. For years, studies have focused on ways to reduce WMSDs. General knowledge of the mechanisms and factors that cause the given ailments, among others, has enabled the development of a series of methods for risk occurrence and identification. WMSDs can be prevented through ergonomic interventions, including optimization of posture and working conditions, muscle and movement training, periodic work breaks, and load-dependent work management, through which the load on the musculoskeletal system can be reduced, thus providing workers with a longer working life [5].

Workers who suffer from this disorder may experience severe pain, which is reflected in a decrease in productivity and quality of work, and can even cause disability, which causes absenteeism from work and leads to increased costs for businesses and for the public health system [2]. Pain caused by musculoskeletal disorders is the second leading cause of disability [6], and, according to the International Labour Organization (ILO), it is estimated that occupational accidents and diseases cause the loss of 4% of the gross domestic product (GDP), or about $2.8 billion in direct and indirect costs.

MSDs occur in different areas of the body, caused by a variety of different types of tasks. In the upper extremities, such as the fingers, hands, wrists, arms, elbows, shoulders, and neck, MSDs can originate from repetitive or lasting static force, leading to tendinitis or nerve entrapment, such as carpal tunnel syndrome (CTS) [2,7–9]. CTS is due to compression of the median nerve inside the carpal tunnel, while flexor tendinitis causes compression of the median nerve by increased pressure in the carpal tunnel due to edema.

Currently, there are several methods that allow us to detect MSDs. For example, CTS is detected by means of palpation tests, such as the Phalen’s and Tinel’s tests, and elec- tromyography. However, the use of thermal imaging may improve medical diagnosis [10].

Temperature gradient changes (decrease and increase) on the skin surface or in the mid- dle of the body are indicators of disease, allowing the evaluation of changes in metabolism and blood flow, especially in a superficial layer of the skin [10–15]. Several studies indicate that the symmetry of the extremities and torso will not have a temperature difference on the two sides along a dermatome or thermatome of more than 0.30 ◦C, and of no more than 0.90 ◦C on the forearms [16]. The diagnosis of neuromuscular pathology by infrared thermography (IT) is based on the existence of thermal symmetry and asymmetry between normal and abnormal sites [17,18]. IT works by measuring the temperature distribution of a surface, which offers several advantages, because it is non-invasive, non-contact, non- radioactive, and painless, and the results are easy to reproduce (thermal imaging); it also has a low operating cost [10,19–21]. A broad range of research has proven the effectiveness of IT in diagnosing CTS [20,21].

Nowadays, CTS is a pathology of great interest in medical research, since it represents one of the greatest occupational health problems of any upper limb disorder [22], and yet, the etiology is not appropriately described [22,23].

Epidemiological studies have been undertaken to identify risk factors for CTS, and the results are contradictory. However, the most consistent factors have been being female [22–29], thirty years or older [22,23,25,26,28–36], having repetitive motor activity, and having a num- ber of systemic diseases, such as diabetes mellitus [10], rheumatoid arthritis [37,38], and hypothyroidism [37,39].

Campillo & De la Vega [40] developed a predictive model for CTDs by using sensory thermography as the main tool. They sought to determine whether there is a relationship between temperature variability and CTD diagnosis and, at the same time, whether there is a gender difference regarding CTDs. However, the model does not explain the temperature variation over time well. In turn, Márquez Gómez [41] used traditional methods, such as RULA (Rapid Upper Limb Assessment) and OCRA (Occupational Repetitive Action), in combination with statistical techniques for the selection of significant predictor variables

Int. J. Environ. Res. Public Health 2021, 18, 3830 3 of 19

for the development of predictive models. Grieco [42] reported a logarithmic conversion of the relative exposure (OCRA) and injury indices, with which he constructed a simple linear regression model for risk prediction of WRMSDs. In the same context, Álvarez-Tello et al. [43] developed a predictive model using binary logistic regression and the items of the strain index questionnaire as predictor variables. The aim of this study is to develop quantitative predictive models that integrate risk factors for CTD, such as age, sex, BMI (body mass index), blood pressure (BP), respiratory rate (RR), and heart rate.

2. Materials and Methods 2.1. Recruitment and Selection of Participants

At first, the target company was approached to explain the purposes of the research and to request approval to apply the project by means of a document expressing the objectives, procedures, and analyses to be carried out, as well as estimated times. Once permission was obtained from the business authorities, the study was initiated based on the clinical procedures established by the company’s occupational health department.

Two production areas were assigned, the sanding and tolex areas, which had the highest records for wrist problems among the operators. In the sanding area, the activities of the operators consist of the sanding process of the body, neck, and edges of the wood product using orbital and edge sanders. On the other hand, in the tolex area, the cabinet subassembly and lining process is performed, which includes the activities of vinyl and fabric cutting, gluing, and stapling. Next, each of the areas was visited to learn about their production processes and to determine the experimental space. Afterwards, a questionnaire was given to each operator (a total of 39 persons), designed to select the participants of the study, obtaining their socio-demographic information and health conditions. This phase had an approximate duration of one month, due to the time restriction so as not to affect the daily production goals of the company.

Twenty-three questionnaires were applied in the sanding area and 16 in the tolex area. At the end of the recruitment process, 19 participants were selected from the sanding area (four persons were not selected due to disabilities and diabetes). Sixteen questionnaires were applied in the tolex area, and 14 participants were chosen (one person did not want to participate and another one had epilepsy). One woman and eighteen men participated in the sanding area (average age = 33 ± 9.7 years). Six women and eight men participated in the tolex area (average age = 35 ± 7.45 years). The experimental sample included a total of 33 people.

Then, the vital signs and somatometry of the chosen participants were recorded, including weight, height, body mass index (BMI), blood pressure (BP), heart rate, and respiratory rate (R.R). The sanding area showed an average BMI = 27 kg/m2, BP 78% normal, 13% high, and 9% low; 96% of the participants were right-handed, had an average heart rate of 77.43 beats per minute (BPM), and an RR of 17.63 breaths per minute. In the tolex area, an average BMI of 28.4 kg/m2, BP 75% normal, 12.5% high, and 12.5% low was recorded. All of the participants in this area were right-handed, and had an average heart rate of 94.18 BPM and an RR of 18.5 breaths per minute.

The selected subjects did not take drugs for the peripheral nervous system (vasodilator, antihypertensive) so as not to interrupt the sympathetic vasoconstrictive response and, therefore, affect their body temperature. Furthermore, they were asked to meet certain criteria in order to take the thermograms listed below. Data collection and thermograms at the company began in February 2019 and ended in June 2019.

A diagram with the measurement methodology appears in Figure 1.

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Figure 1. Measurement methodology flowchart.

2.2. Statement of Ethics This study was conducted in accordance with the written consent granted by the

company, which was provided verbally to all participants. The protocol was reviewed and approved by the ethics and bioethics committee of the postgraduate department of the Faculty of Engineering, Architecture, and Design of the Autonomous University of Baja California, according to the NOM-035-STPS-2018 Standard.

2.3. Preliminary Restrictions Prior to taking the thermograms and in order to eliminate uncertainties in tempera-

ture measurements, the following restrictions were imposed on participants, based on the protocols of Glamorgan [44], Standard Procedures for Infrared Imaging in Medicine [45],

Thermography for the prediction of

injuries and study of influence factors

Selection of participants

Somatometry and vital signs

Preparation of the area and

surroundings

Preparation of measuring devices

Thermograph collection

Temperature measurements

Thermogram analysis

Development of predictive models

Evaluation, Interpretation and comparison

of results, and recommendations

Figure 1. Measurement methodology flowchart.

2.2. Statement of Ethics

This study was conducted in accordance with the written consent granted by the company, which was provided verbally to all participants. The protocol was reviewed and approved by the ethics and bioethics committee of the postgraduate department of the Faculty of Engineering, Architecture, and Design of the Autonomous University of Baja California, according to the NOM-035-STPS-2018 Standard.

2.3. Preliminary Restrictions

Prior to taking the thermograms and in order to eliminate uncertainties in temperature measurements, the following restrictions were imposed on participants, based on the protocols of Glamorgan [44], Standard Procedures for Infrared Imaging in Medicine [45], and Design and Application of a Protocol for Acquiring and Processing Infrared Images from the Hands [46].

Int. J. Environ. Res. Public Health 2021, 18, 3830 5 of 19

• Not to smoke in the hours prior to taking the images (12 hours). • Not to drink alcoholic beverages in the hours prior to the exam (12 hours). • Not to drink coffee or tea for several hours before the study (12 hours). • Preferably, not to eat fatty foods before the analysis.

2.4. Experimental Protocol 2.4.1. Environmental Conditions for the Study

To avoid vasomotion phenomena, the controlled temperature of the rooms assigned by each area was kept between 23–24 ◦C (+/−1 ◦C). Regarding humidity, its values oscillated between 50–60%, depending on the weather conditions of the region. On days when the humidity of the environment was high, a dehumidifier was required to reduce it to adequate levels. Within the space allocated for the recordings, air drafts on the subjects’ hands and lamps or domes above them were avoided during the taking of the thermal images. The participants were asked to uncover their forearm (if necessary), not to wear bracelets, rings, or wristbands, and to remove earrings, glasses, and caps.

2.4.2. Thermographic Infrared Camera Implementation

The IT camera used in this study was a FLIR ThermaCAMTM E25 model, fabricated by FLIR Systems at Boston, MA, USA, with a resolution of 160 × 120 pixels, an accuracy of ±2 ◦C/±3.6 ◦C for ±2% of reading, and a spectral range of 7.5–13 µm. The camera was mounted on a tripod for better handling, with an emissivity of 0.98, as this is the average emissivity of human skin, and thus avoids errors in temperature measurement. Each time the infrared camera was used, the emissivity was set to this value. The chosen region (Figure 2) was taken for all participants. Before each shot, the camera was kept turned on for 15 minutes to maintain thermal equilibrium with its surroundings. The camera was placed perpendicular to the subject’s hand at a minimum distance of 0.601 m [46]. For this study, a distance of two meters was considered. It is worth mentioning that a black surface was placed as a background for the image, contributing to the improvement of the reading of the thermograms and reducing the surrounding noise.

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and Design and Application of a Protocol for Acquiring and Processing Infrared Images from the Hands [46]. • Not to smoke in the hours prior to taking the images (12 hours). • Not to drink alcoholic beverages in the hours prior to the exam (12 hours). • Not to drink coffee or tea for several hours before the study (12 hours). • Preferably, not to eat fatty foods before the analysis.

2.4. Experimental Protocol 2.4.1. Environmental Conditions for the Study

To avoid vasomotion phenomena, the controlled temperature of the rooms assigned by each area was kept between 23–24 °C (+/−1 °C). Regarding humidity, its values oscil- lated between 50–60%, depending on the weather conditions of the region. On days when the humidity of the environment was high, a dehumidifier was required to reduce it to adequate levels. Within the space allocated for the recordings, air drafts on the subjects’ hands and lamps or domes above them were avoided during the taking of the thermal images. The participants were asked to uncover their forearm (if necessary), not to wear bracelets, rings, or wristbands, and to remove earrings, glasses, and caps.

2.4.2. Thermographic Infrared Camera Implementation The IT camera used in this study was a FLIR ThermaCAMTM E25 model, fabricated

by FLIR Systems at Boston, MA, USA, with a resolution of 160 × 120 pixels, an accuracy of ±2 °C/±3.6 °C for ±2% of reading, and a spectral range of 7.5–13 μm. The camera was mounted on a tripod for better handling, with an emissivity of 0.98, as this is the average emissivity of human skin, and thus avoids errors in temperature measurement. Each time the infrared camera was used, the emissivity was set to this value. The chosen region (Fig- ure 2) was taken for all participants. Before each shot, the camera was kept turned on for 15 minutes to maintain thermal equilibrium with its surroundings. The camera was placed perpendicular to the subject’s hand at a minimum distance of 0.601 m [46]. For this study, a distance of two meters was considered. It is worth mentioning that a black surface was placed as a background for the image, contributing to the improvement of the reading of the thermograms and reducing the surrounding noise.

Figure 2. ROI (region of interest) taken for temperature analysis on the palms and back of the hand of the study subjects.

2.4.3. Handling of the Participants Prior to the start of the test, each participant was checked for compliance with the

requirements, that is, no caffeine, alcohol, vasodilator drugs, or smoking, to continue with

Figure 2. ROI (region of interest) taken for temperature analysis on the palms and back of the hand of the study subjects.

2.4.3. Handling of the Participants

Prior to the start of the test, each participant was checked for compliance with the requirements, that is, no caffeine, alcohol, vasodilator drugs, or smoking, to continue with the tests. For this purpose, they were given a reminder the day before the tests were to take

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place. The female menstrual cycle was considered. Nevertheless, none of the participants had their menstrual period during the intakes.

Afterwards, a black board formed of foil wood with plastic laminate was placed on the chair, on which the shots were taken of the palms and backs of the hands. This board had tape markers, which worked as guides to provide precise and reproducible positioning of the hands. Each participant was instructed not to touch the board directly to prevent hand heat from being retained on the board and causing noise on the thermograms. The participant was asked to position him/herself behind the chair and bend down a little until his/her fingers were positioned over the marks. Then, a sequence of infrared images was taken, spaced every 5 min at times 5, 10, 15, and 20 (based on Vardasca, R., E. Francis, J. Ring, P. Plassmann, C.D. Jones, and J. Gabriel [47], and García, A. [48]) for each participant (Figure 3). After each thermal image of the palms and back of the hands was taken, the participant waited seated in another chair, while five minutes remained to continue with the next shot, until the four moments were completed. Thermal imaging sessions were held Monday through Friday from 3:30 to 4:30 pm (hours established by the company), with three participants per day.

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the tests. For this purpose, they were given a reminder the day before the tests were to take place. The female menstrual cycle was considered. Nevertheless, none of the partici- pants had their menstrual period during the intakes.

Afterwards, a black board formed of foil wood with plastic laminate was placed on the chair, on which the shots were taken of the palms and backs of the hands. This board had tape markers, which worked as guides to provide precise and reproducible position- ing of the hands. Each participant was instructed not to touch the board directly to prevent hand heat from being retained on the board and causing noise on the thermograms. The participant was asked to position him/herself behind the chair and bend down a little until his/her fingers were positioned over the marks. Then, a sequence of infrared images was taken, spaced every 5 min at times 5, 10, 15, and 20 (based on Vardasca, R., E. Francis, J. Ring, P. Plassmann, C.D. Jones, and J. Gabriel [47], and García, A. [48]) for each participant (Figure 3). After each thermal image of the palms and back of the hands was taken, the participant waited seated in another chair, while five minutes remained to continue with the next shot, until the four moments were completed. Thermal imaging sessions were held Monday through Friday from 3:30 to 4:30 pm (hours established by the company), with three participants per day.

Figure 3. Experimental setup diagram.

The thermal images were then downloaded and analyzed through the ThermaCAM Researcher Pro 2.10 software, from FLIR Systems company, located at Boston, MA, USA, with which a total of 264 images were reviewed. When analyzing each IT image, the color palette was configured in the rain option. The emissivity (0.98) was already adjusted dur- ing the shots. The IR image was delimited according to the ROI in order to measure the temperature in that area. Then, the Results option was activated to display the tempera- ture values of maximum, minimum, max-min, average, and standard deviation (Figure 4).

Next, the data were exported to Excel to organize and group according to the times in which the temperatures were recorded (5′, 10′, 15′, and 20′). Afterwards, the tempera- ture differences were calculated for the minimum and maximum values of the tempera- ture captured by the thermographic camera. Thereafter, the thermal asymmetries that could represent a possible injury were identified and classified in their levels of alarm and severity, as established by Marins et al. [49], and as shown in Table 1.

Figure 3. Experimental setup diagram.

The thermal images were then downloaded and analyzed through the ThermaCAM Researcher Pro 2.10 software, from FLIR Systems company, located at Boston, MA, USA, with which a total of 264 images were reviewed. When analyzing each IT image, the color palette was configured in the rain option. The emissivity (0.98) was already adjusted during the shots. The IR image was delimited according to the ROI in order to measure the temperature in that area. Then, the Results option was activated to display the temperature values of maximum, minimum, max-min, average, and standard deviation (Figure 4).

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Figure 4. ThermaCAM Researcher Pro 2.10 software display.

Table 1. Scale of the level of attention given according to differences of temperatures between t