Prevalence and characteristics of prediabetes in workers in industry

To examine the prevalence of work stress and prediabetes in computer technology company employees; to analyse the relationships among stress, work stress, and prediabetes; and to explore the potential mediating effects sleep on the relationship between work stress and prediabetes.

A descriptive, cross-sectional design was used. A convenience sample included employees from a large computer technology company in central Texas.

Data collection during March-October 2015 included: retrospective electronic medical record review and online surveys. Electronic medical record review data included: height, weight, waist circumference, blood pressure, high-density lipids, triglycerides, and fasting glucose. Online surveys collected demographic, global stress, diet, exercise, coping, sleep and work stress data from participants. Spearman rho calculations analyzed associations between demographic, socio-cultural factors, health behaviours, work stress, and prediabetes variables. Logistic regression analyses identified probability variables. A structural equation model examined mediating variables.

Prediabetes prevalence was lower and prevalence of work stress was higher in the participant sample than in the USA population. Findings suggested that low job imbalance increases the probability for prediabetes. Job imbalance was inversely related to prediabetes. Three variables increased the probability prediabetes: alcohol, job imbalance, and sleep. Sleep potentially modified the relationship between job imbalance and prediabetes. Participants were college-educated males working in white-collar, technical jobs. Participants had high rates of work stress. Job imbalance was inversely related to prediabetes, which challenges previous empirical data. Future research should continue to explore the relationship between work stress and prediabetes in this population.

This study explored the relationship between work stress and prediabetes in a white-collar worker population in technical industry. Findings suggested that workers in industry have a unique type of stress. Nurses who learn to recognize the non-traditional risk factors for prediabetes can improve screening for prediabetes by including work stress and poor sleep questions.