Critical success factors for ergonomics programs and their relationship to benefits of health and safety in Mexico's manufacturing industries.

This research determines the critical factors for implementing ergonomics programs related to health and safety benefits in the manufacturing industries of Ciudad Juarez, Mexico, from the middle/upper management perspective. The sample was non-probabilistically selected for convenience, comprising individuals in middle and senior management positions. An original questionnaire containing 105 items measuring five latent variables was developed, reviewed, and validated for data collection. The sample size totalled 206 participants. Structural equation models using partial least squares (PLS) were employed to analyse interrelationships between variables. This research demonstrated acceptable reliability and quality indices. Management commitment emerged as the most significant factor, exerting the highest direct, indirect, and total effects on the work environment and prevention activities, significantly enhancing health and safety benefits. Consequently, manufacturing companies in Juarez City must strive to improve management commitment in the working environment and prevention activities since both strategies can increase employee health and safety benefits.

This paper presents a method focusing on the critical success factors of ergonomics programs associated with health and safety benefits in Mexico's manufacturing industries. The study uses structural equation modelling from the middle/upper management perspective. The proposed approach has potential applications across various industries.

Effects of mental workload on manufacturing systems employees: A mediation causal model.

BACKGROUND: Although some research has been done in the Mexican manufacturing industry regarding mental workload, none has explored its association with physical fatigue, body weight gain, and human error simultaneously. OBJECTIVE: This research examines the association between mental workload and physical fatigue, body weight gain, and human error in employees from the Mexican manufacturing systems through a mediation analysis approach. METHODS: A survey named Mental Workload Questionnaire was developed by merging the NASA-TLX with a questionnaire containing the mental workload variables mentioned above. The Mental Workload Questionnaire was applied to 167 participants in 63 manufacturing companies. In addition, the mental workload was used as an independent variable, while physical fatigue and body weight gain were mediator variables, and human error was a dependent variable. Six hypotheses were used to measure the relationships among variables and tested using the ordinary least squares regression algorithm. RESULTS: Findings indicated that mental workload significantly correlates with physical fatigue and human error. Also, the mental workload had a significant total association with human error. The highest direct association with body weight gain was provided by physical fatigue, and body weight gain had an insignificant direct association with human error. Finally, all indirect associations were insignificant. CONCLUSION: Mental workload directly affects human error, which physical fatigue does not; however, it does affect body weight gain. Managers should reduce their employees' mental workload and physical fatigue to avoid further problems associated with their health.

Impact of job strain and being overweight on middle and senior managers from the manufacturing sector in the Mexican industry.

BACKGROUND: This research work establishes the relationship between job strain and being overweight among Mexican managers. Recently in Mexico, there has been a sharp increase in work-related diseases and mental health disorders. Furthermore, evidence shows that Mexicans rank top among employees who suffer from stress, yet research on the impact of job strain on the phenomena of obesity and being overweight among such vulnerable job positions in the industrial field is scarce. METHODS: The sample included 170 overweight middle and senior managers from six companies in the Mexican Manufacturing Industry. Cedillo's Spanish version of the Job Content Questionnaire by Karasek was used, and the Body Mass Index (BMI) was used to characterize an overweight condition. Structural Equations Modelling studied the relationships among variables. RESULTS: Even though, the model shows a power of explanation of 6%(R2 = 0.06), the variable showing the greatest direct effect on the overweight variable is social support, with 21%(p < 0.01, ß= -0.21). Regarding the total effects, only two of the four variables studied contributed directly to the overweight variation: the social support variable and the job demand variable. CONCLUSIONS: The results of the model hold a relatively low explanatory power; however, they do show a relationship between the studied variables. Also, the importance of the supervisor and co-workers' support should be considered when developing organizational strategies for the prevention of work stress and an overweight condition.

Relationship between Burnout and Body Mass Index in Senior and Middle Managers from the Mexican Manufacturing Industry.

This research relates Burnout Syndrome (BS) with the Body Mass Index (BMI) among middle and senior managers of the Mexican manufacturing industry. Even though BS incidence is high in the Mexican industrial population, few systematic studies have explored BS and its relationship with other health problems, such as obesity. The goal of this research is to determine the relationship between BS and the BMI in employees with normal weight, overweight, and obesity. We present three structural equation models to relate BS and the BMI. The BMI ranges were determined according to the parameters (normal weight, overweight, and obesity) proposed by the World Health Organization (WHO). The sample includes 361 employees that voluntarily answered a 31-item questionnaire. We measure the levels of BS using the Maslach Burnout Inventory-General Survey (MBI-GS) and analyze anthropometric and sociodemographic data from the participants. Then, we determine the relationships between the variables through structural equation models and estimate the direct, indirect, and total effects in the three models, which show acceptable reliability. As main findings, the normal weight model has a larger explanatory power than the overweight and obesity models. The same research hypotheses were tested and the effects of BS on the BMI differ across the three models. Such results are presented by taking into account that obesity and overweight require additional factors, such as genetic factors and personal eating habits, to be better explained.