RESUMEN
Background and objective Even though obesity is a major global health concern, few studies in the literature have discussed obesity in the workplace. In light of this, we aimed to explore obesity in the workplace and its contributing factors. Methodology An online survey was distributed via official work emails. The survey assessed demographic variables and work environment-related factors, such as physical and mental well-being, lack of time, and social and personal habits. The total sample included 380 full-time employees, of which 16.67% were excluded for not meeting the inclusion criteria. Data were analyzed by using descriptive and inferential statistics. Results Of note, 79.87% of the participants reported an increase in weight after getting employed. The average weight gain was 10.4 kg for 8.2 years of experience. The physical and mental items and time-related items had the highest average scores of 3.24 and 3.44, respectively. The multivariable logistic regression showed a significant association between work experience (p = 0.0259) and time (p = 0.0363), as well as physical and mental domains (p = 0.0007). Conclusions Based on our findings, greater work experience, a lack of time, and negative mental and physical well-being are risk factors for weight gain among employees.
RESUMEN
Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m2). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R2 = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R2 = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.
