Determinants of metabolic syndrome in obese workers: gender differences in perceived job-related stress and in psychological characteristics identified using artificial neural networks

Objective: The metabolic syndrome (MS) is a multifactorial disorder associated with a higher risk of developing cardiovascular diseases and type 2 diabetes. However, its pathophysiology and risk factors are still poorly understood. In this study, we investigated the associations among gender, psychosocial variables, job-related stress and the presence of MS in a cohort of obese Caucasian workers. Methods: A total of 210 outpatients (142 women, 68 men) from an occupational medicine service was enrolled in the study. Age, BMI, waist circumference, fasting glucose, blood pressure, triglycerides and HDL cholesterol were collected to define MS. In addition, we evaluated eating behaviors, depressive symptoms, and work-related stress. Data analyses were performed with an artificial neural network algorithm called Auto Semantic Connectivity Map (AutoCM), using all available variables. Results: MS was diagnosed in 54.4 and 33.1% of the men and women, respectively. AutoCM evidenced gender-specific clusters associated with the presence or absence of MS. Men with a moderate occupational physical activity, obesity, older age and higher levels of decision-making freedom at work were more likely to have a diagnosis of MS than women. Women with lower levels of decision-making freedom, and higher levels of psychological demands and social support at work had a lower incidence of MS but showed higher levels of binge eating and depressive symptomatology. Conclusion: We found a complex gender-related association between MS, psychosocial risk factors and occupational determinants. The use of these information in surveillance workplace programs might prevent the onset of MS and decrease the chance of negative long-term outcomes. Level of evidence: Level V, observational study