Influences of Obesity on Job Demands and Worker Capacity

The effect of clinically elevated body mass index on physiological stress during manual lifting activities

Individuals with a body mass index (BMI) classified as obesity constitute 27.7% of U.S. workers. These individuals are more likely to experience work-related injuries. However, ergonomists still design work tasks based on the general population and normal body weight. This is particularly true for manual lifting tasks and the calculation of recommended weight limits (RWL) as per National Institute of Occupational Safety & Health (NIOSH) guidelines. This study investigates the effects of BMI on indicators of physiological stress. It was hypothesized that, for clinically elevated BMI individuals, repeated manual lifting at RWL would produce physiological stress above safety limits. A repetitive box lifting task was designed to measure metabolic parameters: volume of carbon dioxide (VCO2) and oxygen (VO2), respiratory exchange ratio (RER), heart rate (HR), and energy expenditure rate (EER). A two-way ANOVA compared metabolic variables with BMI classification and gender, and linear regressions investigated BMI correlations. Results showed that BMI classification represented a significant effect for four parameters: VCO2 (p < 0.001), VO2 (p < 0.001), HR (p = 0.012), and EER (p < 0.001). In contrast, gender only had a significant effect on VO2 (p = 0.014) and EER (p = 0.017). Furthermore, significant positive relationships were found between BMI and VCO2 (R2 = 59.65%, p < 0.001), VO2 (R2 = 45.01%, p < 0.001), HR (R2 = 21.86%, p = 0.009), and EER (R2 = 50.83%, p < 0.001). Importantly, 80% of obese subjects exceeded the EER safety limit of 4.7 kcal/min indicated by NIOSH. Indicators of physiological stress are increased in clinically elevated BMI groups and appear capable of putting these individuals at increased risk for workplace injury.

Factors Associated with the Willingness to Perform a Physical Employment Standard in Probation Officers

PURPOSE

This study examined worker characteristics and behaviors and the perceived importance of job-related tasks associated with the willingness to perform a proposed probation officer physical ability test (PROPAT).

METHODS

North Carolina probation officers (N = 1213, 46.2% female, 39.8 ± 10.1 yr, 30.7 ± 6.6 kg·m-2) completed a survey including demographics, health history, and job-related tasks. A multivariable logistic regression model estimated the odds of being willing to perform the PROPAT. Adjusted odds ratios (ORadjusted) with 95% confidence intervals (CI) were calculated, with those excluding 1.00 deemed statistically significant.

RESULTS

The majority (72%) of probation officers were willing to perform the PROPAT. Being male (compared with female) (ORadjusted = 1.50, 95% CI = 1.12-2.02) and having moderate (ORadjusted = 1.51, 95% CI = 1.10-2.08) and high physical activity status (ORadjusted = 2.89, 95% CI = 1.97-4.28) (compared with low) increased the odds of being willing to perform the PROPAT. Additionally, reporting a greater importance of tasks, including running to pursue a suspect (TASKRUN, 1-unit increase, ORadjusted = 1.25, 95% CI = 1.10-1.43) and dragging an unresisting person (TASKDRAG, 1-unit increase, ORadjusted = 1.16, 95% CI = 1.01-1.32), increased the odds of being willing to perform the PROPAT. Increasing age (1-yr increase, ORadjusted = 0.96, 95% CI = 0.94-0.98), class II (ORadjusted = 0.45, 95% CI = 0.28-0.71) and class III obesity (compared with normal weight, ORadjusted = 0.55, 95% CI = 0.32-0.93), and a previous musculoskeletal injury (ORadjusted = 0.57, 95% CI = 0.35-0.93) all decreased the odds of being willing to perform the PROPAT.

CONCLUSIONS

These results suggest being older, previously injured, obese (body mass index ≥ 35 kg·m-2), and less active is associated with being less willing to participate in the PROPAT, whereas males and reporting a higher importance of the TASKRUN and TASKDRAG activities is associated with being more willing to participate in the PROPAT. Departments can use these findings to identify feasible strategies (e.g., education and physical training) to improve the implementation of physical employment standards.

Obesity impacts on task performance and perceived discomfort during seated foot target reaches

This study examined obesity impacts on task performance and perceived discomfort during seated foot target reaches. Three independent variables, participant group, movement distance, and, movement direction, were considered. The task performance measures employed were reaction time, movement time and task performance time. Perceived discomfort was measured using a modified Borg CR-10 scale. Statistical analyses revealed that: obesity was associated with increases in movement time, reaction time and performance time; movement distance significantly affected the three task performance measures and discomfort rating; and, movement direction significantly affected movement time, performance time and discomfort rating. The obesity impacts observed are thought to reflect the decelerating effects of the extra fat mass in the obese body during foot reaches and possibly obesity-related physiological and cognitive changes. Design improvements of foot-operated systems, such as reducing distances to targets, increasing target sizes and avoiding forward foot reaches, may help counteract the observed obesity impacts. Practitioner Summary: This study empirically investigated the obesity impacts on task performance and perceived discomfort during seated foot target reaches. Obesity was found to be associated with increases in movement time, reaction time and performance time. The observed obesity impacts seem attributable to the anthropometric, motor and cognitive characteristics of the obese.Abbreviations: ANOVA: analysis of variance; BMI: body mass index; ROM: range of motion; Borg CR-10: Borg's category ratio 10 scale.

Obesity impairs performing and learning a timing perception task regardless of the body position

Obesity has been associated with poorer sensorimotor performance. However, it remains unclear whether these obesity-related impairments can be mitigated by practice. In the present study, we sought to investigate the effects of practice on performing and learning a temporal estimation task, in women with and without obesity. The experimental task consisted of synchronizing the arrival of two rectangles at a target point. Limited to the pressing of a switch, the task was intended to minimize possible muscular fatigue, self-generated perturbations to balance and the need to accelerate/decelerate body segments. Participants were allowed to choose the displacement velocity of the rectangle they controlled and were informed that they would not be offered any choice over it during a test to come. To control for the effect of different body positions on sensorimotor performance and learning, the 19 women with obesity (BMI = 40.0 + 7.33, age = 44.2 + 6.6) and 20 without obesity (BMI = 22.3 + 1.95, age = 43 + 6.9) were assigned into 4 groups, according to their BMI and body position assumed during practice (standing upright with feet together or sitting). As no significant differences concerning body position were found, the data were reanalysed disregarding this factor. Results revealed that while both groups reduced errors during the Acquisition, participants with obesity showed poorer performance (Acquisition) and sensorimotor learning (Transfer). Given the experimental task and adopted procedures, our results tend to support the hypothesis that hindered perception and/or integration of sensory information is associated with obesity.

Obesity moderates the benefit of retirement on health: A 21-year prospective study in the GAZEL cohort

OBJECTIVES

Self-rated health and depressive symptoms have been shown to improve upon retirement. Participants with obesity might benefit more of retirement because of the extra work-related burden they are carrying. The present study aimed to investigate whether the association between retirement and health changes may depend upon obesity in the large French GAZEL occupational cohort during 21 years of follow-up.

METHODS

17,655 men and women were included in the analyses. Self-rated health was measured on a scale from 1 to 8 with 8 being very bad. Depressive symptoms were measured at four time points by the CES-D score. Mixed models examined the association of self-rated health or depressive symptoms with time (i.e. from -10 years before to +10 years after retirement), retirement, body mass index (BMI), and their interactions.

RESULTS

Regardless of retirement, BMI was associated with poorer health. Positive BMI by time interactions showed a less favorable time course of both health indicators in the presence versus the absence of obesity (0.024 versus 0.014 and - 0.19 versus -0.07 points per year for self-rated health and depressive symptoms, respectively). However, negative BMI by retirement interactions showed that the improvement of health observed upon retirement was stronger in with the presence versus the absence of obesity (-0.4 versus -0.3 and - 2.42 versus -1.70 points for self-rated health and depressive symptoms, respectively).

CONCLUSION

Improvement upon retirement was observed in the presence of obesity and was even higher than in the presence of normal weight and overweight.

Cardiovascular and Psychophysical Response to Repetitive Lifting Tasks in Women

Background

Understanding the cardiovascular and psychophysical demands of repetitive lifting tasks is important in job design strategies. This study determined the cardiovascular (oxygen consumption (VO₂) and heart rate (HR) and psychophysical response to repetitive lifting tasks in women.

Methods

Ten female (age 27 ± 5 yrs) participants transferred 11.4, 15.9, and 20.5 kg weights back and forth from a rung 40.6 cm high to a rung 156.2 cm high. Rungs were 195.6 cm apart horizontally. Three, 10 minute bouts (1 = 11.4 kg; 2 = 15.9 kg; 3 = 20.5 kg) were performed at 6 lifts per minute. Cardiovascular and psychophysical (rating of perceived exertion, RPE) parameters were monitored throughout the bouts. VO₂max and HRmax were determined via a maximal treadmill test.

Results

VO₂, HR, and RPE were significantly different between each work bout (p < 0.01), with each outcome variable increasing as load increased. VO₂max and HRmax equaled 46.5 ± 7.5 mL·kg⁻¹·min⁻¹ and 191 ± 11 bpm, respectively. Work at 11.4 kg was performed at 38% VO₂max and 63% HRmax; at 15.9 kg at 41% VO₂max and 72% HRmax; and at 20.5 kg at 49% VO₂max and 81% HRmax. RPE at 11.4, 15.9, and 20.5 kgs were: 8.4 ± 1.6, 11.4 ± 1.9, and 15.0 ± 2.2.

Conclusion

During these repetitive lifting tasks, metabolic cost and perceived exertion increased with weight lifted; average work intensity ranged from 63 to 81% of HRmax and 38 to 49% of VO₂max. Results have important implications in relation to job pacing and design, and worksite health promotion strategies aimed at reducing work place injury.

Plus size and obese workers: anthropometry estimates to promote inclusive design

A significant proportion of the adult population globally is overweight, obese or classed as 'plus size'. This has led to variability in size and shape across the working population and exclusion in the workplace. A new dataset of the anthropometry of plus size people has been created. Length dimensions were similar to other data, but breadth, circumference, and depth measurements were substantially larger. The hip breadth and abdominal depth were important for predicting largeness in this population. These data help explain the high exclusion rates from design and the number of fit, reach, posture and clearance issues reported by participants with a high BMI: generally, the higher the BMI the greater prevalence of problems. It is hoped that a better understanding of the anthropometric characteristics of the plus size worker will inform the design of safe, productive work environments to promote inclusion for a wider range of people. Practitioner Summary: A new anthropometry dataset of plus size people has been created. The higher the BMI the greater the problems with design in the workplace for fit, reach, posture and clearance. To ensure inclusion and reduce stigma it is important to understand more about the size and shape of this population.

Morbidity associated with overweight and obesity in health personnel: a 10-year retrospective of hospital-based cohort study in Taiwan

PURPOSE

To investigate morbidity associated with overweight and obesity in health personnel and compare the differences among work roles.

MATERIALS AND METHODS

This retrospective cohort study examined measurements obtained during employee medical checkups between 2007 and 2016 in a Taiwan medical center. BMI was used to define overweight (≥24 and <27 kg/m²) and obesity (≥27 kg/m²). Morbidity refers to prevalence, period incidence proportion, and incidence rate. Multivariable Cox model was used to estimate the HRs and 95% CI of the incidence proportion across work roles.

RESULTS

Ten thousand six hundred fifty-one health personnel with 24,295 BMI measurements were recruited. Mean age was 33.4±10.7 years and 72.4% was female. In total, 1,992 (8.2%) health personnel were underweight, 13,568 (55.8%) had a normal BMI, 5,097 (21%) were overweight, and 3,638 (15%) were obese. Five thousand nine hundred one health personnel with 31,172 different interval-year arrangement combinations were obtained. The incidence proportion of overweight and obesity was 1,947 (6.2%) and 1,494 (4.8%), respectively. The incidence rate was 37/1,000 and 15/1,000 person-years, respectively. Compared with that in supporting staff, the HR of overweight in doctors, nurses, and allied health professionals was 0.93 (95% CI =0.73-1.18, P=0.553), 0.92 (95% CI =0.73-1.16, P=0.491), and 0.85 (95% CI =0.67-1.09, P=0.202), respectively. Similarly, the HR of obesity was 0.86 (95% CI =0.66-1.14, P=0.301), 0.89 (95% CI =0.67-1.18, P=0.430), and 0.84 (95% CI =0.63-1.13, P=0.248), respectively.

CONCLUSION

In health personnel, the prevalence of overweight and obesity was 21% and 15%, respectively. The incidence proportion was 6.2% and 4.8%, respectively. Morbidity across the four health work roles examined was not significantly different.

Experimental validation of a subject-specific maximum endurance time model

This study aimed at experimentally validating a subject-specific maximum endurance time (MET) model. Thirty health participants (15 males and 15 females; Age: mean = 21.5 years, SD = 1.6 years) volunteered to conduct an isometric elbow flexion task until exhaustion. The endurance times of each participant were measured under relative exertion levels ranging from 30% MVC (Maximum Voluntary Contraction) to 70% MVC at 10% intervals. Assessment of the model showed that the intensity-endurance time relationship for each studied individual could be well fitted by the subject-specific MET model (R² > 0.89). The fatigue rates identified from the model fitting were normally distributed (Mean = 0.96 min^-1, SD = 0.29 min^-1). In addition, the fatigue rates of the male group were significantly higher than the female group. The subject-specific MET model can be used to predict the MET for individual workers, and further support physical task design, based on the fatigability data of a targeted worker population. Practitioner Summary: Ergonomists have extensively used MET models in physical fatigue assessment and physical task design. A subject-specific MET model could be used to predict the MET at individual levels, and also to support work design for a target worker population, based on the fatigability data distribution obtained from sampled workers.

A data-driven approach to modeling physical fatigue in the workplace using wearable sensors

Wearable sensors are currently being used to manage fatigue in professional athletics, transportation and mining industries. In manufacturing, physical fatigue is a challenging ergonomic/safety "issue" since it lowers productivity and increases the incidence of accidents. Therefore, physical fatigue must be managed. There are two main goals for this study. First, we examine the use of wearable sensors to detect physical fatigue occurrence in simulated manufacturing tasks. The second goal is to estimate the physical fatigue level over time. In order to achieve these goals, sensory data were recorded for eight healthy participants. Penalized logistic and multiple linear regression models were used for physical fatigue detection and level estimation, respectively. Important features from the five sensors locations were selected using Least Absolute Shrinkage and Selection Operator (LASSO), a popular variable selection methodology. The results show that the LASSO model performed well for both physical fatigue detection and modeling. The modeling approach is not participant and/or workload regime specific and thus can be adopted for other applications.

Toward Unobtrusive Patient Handling Activity Recognition for Injury Reduction Among At-Risk Caregivers

Nurses regularly perform patient handling activities. These activities with awkward postures expose healthcare providers to a high risk of overexertion injury. The recognition of patient handling activities is the first step to reduce injury risk for caregivers. The current practice on workplace activity recognition is based on human observational approach, which is neither accurate nor projectable to a large population. In this paper, we aim at addressing these challenges. Our solution comprises a smart wearable device and a novel spatio-temporal warping (STW) pattern recognition framework. The wearable device, named Smart Insole 2.0, is equipped with a rich set of sensors and can provide an unobtrusive way to automatically capture the information of patient handling activities. The STW pattern recognition framework fully exploits the spatial and temporal characteristics of plantar pressure by calculating a novel warped spatio-temporal distance, to quantify the similarity for the purpose of activity recognition. To validate the effectiveness of our framework, we perform a pilot study with eight subjects, including eight common activities in a nursing room. The experimental results show the overall classification accuracy achieves 91.7%. Meanwhile, the qualitative profile and load level can also be classified with accuracies of 98.3% and 92.5%, respectively.