Background: Obesity constitutes a public health problem worldwide and causes non-alcoholic fatty liver disease (MALFD), the leading cause of liver disease in developed countries, which progresses to liver cirrhosis and liver cancer. MAFLD is associated with obesity and can be evaluated by validated formulas to assess MAFLD risk using different parameters such as the body mass index (BMI) and waist circumference (WC). However, these parameters do not accurately measure body fat. As MAFLD is strongly associated with obesity, we hypothesize that measuring body and visceral fat by electrical bioimpedance is an efficient method to predict the risk of MAFLD. The objective of our work was to demonstrate that electrical bioimpedance is a more efficient method than the BMI or WC to predict an elevated risk of MAFLD. Methods: A cross-sectional, descriptive study involving 8590 Spanish workers in the Balearic Islands was carried out. The study’s sample of employees was drawn from those who underwent occupational medicine examinations between January 2019 and December 2020. Five MAFLD risk scales were determined for evaluating very high levels of body fat and visceral fat. The determination of body and visceral fat was performed using bioimpedanciometry. Student’s t-test was employed to ascertain the mean and standard deviation of quantitative data. The chi-square test was used to find prevalences for qualitative variables, while ROC curves were used to define the cut-off points for body and visceral fat. The calculations included the area under the curve (AUC), the cut-off points along with their Youden index, sensitivity, and specificity. Correlation and concordance between the various scales were determined using Pearson’s correlation index and Cohen’s kappa, respectively. Results: As both total body fat and visceral fat increase, the risk of MAFLD increases with a statistically significant result (p < 0.001), presenting a higher risk in men. The areas under the curve (AUC) of the five scales that assess overweight and obesity to determine the occurrence of high values of the different MAFLD risk scales were very high, most of them exceeding 0.9. These AUC values were higher for visceral and body fat than for the BMI or waist circumference. FLD-high presented the best results in men and women with the AUC at around 0.97, both for visceral fat and total body fat, with a high Youden index in all cases (women body fat = 0.830, visceral fat = 0.892; men body fat = 0.780, visceral fat = 0.881). Conclusions: In our study, all the overweight and obesity scales show a very good association with the scales assessing the risk of MAFLD. These values are higher for visceral and body fat than for waist circumference and the BMI. Both visceral fat and body fat are better associated than the BMI and waist circumference with MAFLD risk scales.

Background: Shift work has been associated with unhealthy lifestyle habits and a higher prevalence of obesity, which negatively impacts the health of shift workers. The objective of our study was to examine the influence of shift work on obesity, as well as on sociodemographic variables, anthropometric measurements, and lifestyle habits in individuals working this type of schedule. Methods: An observational, cross-sectional, descriptive study involving 53,053 workers from various labour sectors across several Spanish autonomous communities was conducted. It included 31,753 men (17,527 of them working shifts) and 21,300 women (11,281 of them working shifts). The relationship between shift work and obesity was examined, as well as its association with sex, age, social class, education level, smoking, alcohol consumption, sedentary behaviour, and unhealthy diet. Results: Obesity showed higher prevalence and mean values among shift workers across all four formulas used (BMI obesity, WtHR high, CUN BAE obesity, METS-VF high). All variables related to unhealthy lifestyle habits revealed a significantly greater prevalence among shift workers, with high statistical significance (p < 0.001). Age, sex, and social class affected the risk of obesity, with a greater prevalence observed in shift workers compared to non-shift workers (p < 0.001). Men had a higher risk than women, with an OR ranging from 1.17 (1.12–1.21) for BMI obesity to 7.45 (6.71–8.20) for METS-VF high. Conclusions: Shift workers exhibit a higher prevalence of obesity and unhealthy lifestyle habits, with men at greater risk. The variables that most significantly increase the risk of obesity include age, physical inactivity, low adherence to the Mediterranean diet, and alcohol consumption.

Introduction: Metabolic syndrome (MetS) and hypertriglyceridemic waist (HTW) are two multifactorial pathological conditions that have been increasing in prevalence worldwide. The objective of this study was to evaluate how various sociodemographic variables and healthy habits are associated with the presence or absence of MetS and HTW. Methodology: This study employed a mixed-methods approach, consisting of a retrospective longitudinal study and a cross-sectional descriptive study, analyzing 44,939 healthcare workers with MS and HTW across four professional categories to evaluate the relationship between age, sex, smoking, physical activity, and adherence to the Mediterranean diet using three diagnostic criteria. Descriptive analysis included categorical and quantitative variables, which were assessed through frequencies, Student’s t-test, chi-square, and binary logistic regression models. Logistic regression and Cohen’s kappa were used to evaluate associations and concordances. Age, sex, and lack of physical activity showed the strongest associations with MetS (OR: 2.65–2.84). The results highlight the importance of physical activity and other factors in metabolic prevention. Results: Age, sex, and physical activity were the variables most strongly associated with MetS and HTW across the three evaluated diagnostic criteria. The odds ratios revealed significant values: age (9.07–13.71 for MetS and 13.42 for HTW), sex (2.82–3.31 for MetS and 3.72 for HTW), and physical activity (2.65–2.84 for MetS and 2.40 for HTW). Conclusions: The risk of developing MetS and HTW among healthcare personnel is influenced by lifestyle habits, sex, and age, with the highest ORs observed in nursing assistants and orderlies. Future research that delves deeper into the causal relationship between lifestyle factors and the severity of MetS and HTW in healthcare personnel will improve understanding and facilitate the development of preventive activities to reduce their incidence.

Introduction and Objectives: Obesity constitutes a significant public health concern and is frequently linked to metabolic dysfunctions, particularly insulin resistance (IR). Nevertheless, a subset of obese individuals, referred to as metabolically healthy obese (MHO), do not exhibit overt metabolic abnormalities. The present study aims to assess the risk of developing IR among MHO workers and to explore the determinants contributing to this risk. Methods: This cross-sectional investigation utilized data from a cohort of 68,884 obese workers across multiple occupational sectors in Spain. The classification of participants as MHO was based on the number of metabolic syndrome components, in accordance with the criteria established by the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII). Anthropometric, clinical, and biochemical parameters—including body mass index (BMI), waist circumference, lipid profile, glycemic levels, and blood pressure—were systematically assessed. The likelihood of developing IR was estimated through various validated risk assessment models. Results: The analysis indicates that, despite having a relatively favorable metabolic profile, individuals classified as MHO also show signs of metabolic deterioration, such as an increased risk of insulin resistance. Key risk factors such as physical inactivity, low adherence to the Mediterranean diet, and socioeconomic disparities were identified as significant contributors to the transition from the MHO phenotype to a metabolically unhealthy state. Logistic regression analyses corroborated that insufficient physical activity and suboptimal dietary habits were strongly associated with an elevated risk of IR. Conclusions: The findings underscore the dynamic and potentially transient nature of the MHO phenotype, emphasizing the necessity of proactive monitoring and early preventive strategies. Encouraging physical activity, promoting adherence to a nutritionally balanced diet, and implementing workplace health initiatives emerge as critical measures to attenuate the risk of IR and metabolic deterioration in MHO individuals. Future longitudinal studies are warranted to enhance risk stratification and to formulate tailored preventive interventions.

Introduction: Metabolic age (MA) is the difference between an individual’s actual age and the age of their body based on physiological and biological factors. It is an indicator that reflects a person’s physical and biological state, regardless of chronological age. Insulin resistance (IR) is a health disorder in which tissues exhibit a reduced response to the circulating glucose uptake stimulated by insulin. Objective: The aim of this study is to evaluate the association between MA, determined through bioelectrical impedance analysis, and the risk of IR, assessed using validated scales, in a cohort of Spanish workers. Methodology: A descriptive cross-sectional study was conducted on 8590 Spanish workers to assess the association between MA and a set of sociodemographic variables, health habits, and IR risk scales such as the Triglyceride–Glucose Index (TyG Index), Metabolic Score for Insulin Resistance (METS-IR), and Single Point Insulin Sensitivity Estimator (SPISE). Results: All analyzed variables were associated with MA values, with the strongest associations observed for IR risk scale values (OR 4.88 [95% CI 4.12–5.65] for METS-IR, 4.42 [95% CI 3.70–5.15] for SPISE, and 3.42 [95% CI 2.97–3.87] for the TyG Index) and physical activity. Conclusions: Metabolic age is influenced by sociodemographic variables such as age, sex, and social class; health habits such as smoking, physical activity, and adherence to the Mediterranean diet; and by IR risk scale values.

Introduction: Insulin resistance (IR) is a highly prevalent pathophysiological entity implicated in the development of a wide variety of metabolic, cardiovascular, and endocrine disorders. The aim of this study is to assess the association between sociodemographic variables and healthy habits with IR risk scales. Methodology: This dual study, incorporating both longitudinal-retrospective and cross-sectional designs, analyzed healthcare workers across four professional categories (physicians, nurses, healthcare technicians, and auxiliary personnel). It examined the association of age, sex, professional category, smoking status, physical activity, and adherence to the Mediterranean diet with elevated scores on insulin resistance risk scales. Results: All the variables analyzed were associated with the presence of elevated values of the IR scales, with age, sex, and physical activity showing the strongest association (reflected in the odds ratio values). Conclusions: The profile of an individual with a higher risk of presenting elevated values of the IR risk scales would be an elderly male auxiliary health worker who is a smoker and is physically inactive, with a low adherence to the Mediterranean diet.