Background: Insulin resistance (IR) is a key metabolic abnormality underlying type 2 diabetes and cardiometabolic diseases. Although lifestyle and sociodemographic determinants are well described, the role of psychosocial constructs—such as purpose in life—remains insufficiently characterized. No prior study in large occupational samples has examined the associations between purpose in life and IR when evaluated through three complementary indices: the triglyceride–glucose index (TyG), the Single-Point Insulin Sensitivity Estimator for Insulin Resistance (SPISE-IR), and the metabolic score for insulin resistance (METS-IR). Objectives: To analyze the cross-sectional associations between purpose in life and IR indicators in a large working population and determine whether these associations persist after accounting for sociodemographic and lifestyle factors. Methods: A cross-sectional study was conducted among 93,077 Spanish workers aged 20–69 years undergoing routine occupational health examinations. IR was estimated using TyG, SPISE-IR, and METS-IR indices. Purpose in life was assessed using the 10-item Purpose in Life Test and categorized into three groups based on the empirical distribution of scores. Multinomial logistic regression models adjusted for age, sex, social class, smoking, Mediterranean diet adherence, physical activity, and BMI were used to examine associations. Results: Lower purpose in life was consistently associated with higher IR categories across all indices. Compared with individuals reporting high purpose, those with low purpose had higher odds of belonging to the high IR category (TyG ORa 1.59; 95% CI 1.45–1.74; SPISE-IR ORa 1.94; 95% CI 1.76–2.13; METS-IR ORa 2.21; 95% CI 1.98–2.47). Adding purpose in life to sociodemographic and lifestyle models modestly improved discrimination for identifying high IR categories. Conclusions: In this large occupational cohort, purpose in life was independently associated with insulin resistance as measured by three metabolic indices. These findings highlight the relevance of psychosocial factors in metabolic health. Longitudinal studies are needed to clarify temporal pathways and assess whether purpose-oriented approaches may contribute to improved metabolic profiles.

BACKGROUND:Cardiovascular risk prediction models are central to primary prevention strategies, yet substantial variability exists between contemporary and traditional equations used in clinical practice. In Spain, SCORE2 and REGICOR currently coexist as major cardiovascular risk assessment tools despite important methodological differences. However, evidence regarding their concordance in large occupational populations remains limited. OBJECTIVE:To evaluate the agreement between SCORE2 and REGICOR in cardiovascular risk stratification among Spanish workers and to quantify the extent of cardiovascular risk reclassification associated with SCORE2 implementation. METHODS:A multicenter cross-sectional study was conducted in 216,310 Spanish workers aged 40-64 years undergoing routine occupational health examinations between 2019 and 2024. Cardiovascular risk was estimated using SCORE2, REGICOR, ERICE, DORICA, Globorisk, and Framingham-based equations. High-risk categories were defined according to the thresholds recommended for each model. Agreement between categorical classifications was assessed using Cohen's kappa coefficient, whereas Pearson correlation coefficients were calculated for continuous risk estimates. RESULTS:SCORE2 classified 15,617 workers (7.22%) as high cardiovascular risk, whereas REGICOR identified only 4409 individuals (2.04%). Among workers classified as high risk by SCORE2, 14,387 (92.1%) were not identified as high risk by REGICOR. Agreement between SCORE2 and REGICOR was slight (kappa = 0.094), indicating minimal concordance in high-risk classification. By contrast, SCORE2 demonstrated higher agreement with Framingham hard coronary events (kappa = 0.567) and Globorisk (kappa = 0.534). Correlation analyses showed strong associations between SCORE2 and several continuous cardiovascular risk estimates, including the Framingham categorical score (r = 0.768), Framingham hard coronary events (r = 0.758), and Globorisk (r = 0.739), whereas the correlation between SCORE2 and REGICOR was substantially lower (r = 0.251). These findings indicate that strong statistical correlation does not necessarily translate into clinically meaningful agreement in cardiovascular risk categorization. CONCLUSIONS:Substantial discordance exists between SCORE2 and REGICOR in the identification of high cardiovascular risk among Spanish workers. SCORE2 consistently classified a considerably larger proportion of individuals as high risk, whereas REGICOR showed limited concordance with contemporary cardiovascular prediction models. Continued reliance on REGICOR instead of SCORE2 may lead to under-identification of workers who could currently be considered candidates for intensified primary cardiovascular prevention according to contemporary European prevention strategies. Nevertheless, the present study does not establish which model provides superior prediction of future cardiovascular events, and prospective outcome-based validation studies remain necessary.

Background Vascular age, estimated using the Framingham model, is an intuitive indicator of cardiovascular risk. Metabolic syndrome (MetS) includes several cardiometabolic abnormalities associated with increased morbidity and mortality. The relationship between vascular age and MetS has not been extensively assessed in large working populations. Objective To evaluate the predictive ability of vascular age for identifying MetS in a large cohort of Spanish workers. Methods We conducted a cross-sectional study among 336,450 employees aged 18–69 years who underwent standardized occupational health examinations from 2018 to 2022. Vascular age and avoidable lost life years (ALLY) were calculated using the Framingham equation. MetS was defined according to NCEP ATP III, IDF, and Joint Interim Statement (JIS) criteria. Associations were examined using logistic regression models adjusted for sociodemographic and lifestyle variables. Discriminatory performance was assessed through ROC curve analyses. Results MetS prevalence increased progressively across higher vascular age categories in both sexes. Vascular age demonstrated strong diagnostic performance, with areas under the curve>0.80 and reaching 0.86 in women according to NCEP ATP III and JIS definitions. Multivariable analyses confirmed independent associations between elevated vascular age and MetS. Conclusions Vascular age is a strong and consistent predictor of MetS and represents a practical tool for early cardiometabolic risk detection in occupational settings. Its integration into workplace health surveillance may enhance the identification of high-risk workers and support targeted preventive strategies.

Background: Obesity remains a major public health challenge, with central and visceral fat distribution conferring particularly high cardiometabolic risk. Lifestyle factors, including diet, physical activity, and sleep quality, have been implicated in adiposity, yet their combined and interactive effects in working populations remain insufficiently characterized. Methods: We conducted a cross-sectional study in 88,343 Spanish employees (53,122 men, 35,221 women) attending occupational health examinations between 2021 and 2024. Obesity was assessed using four complementary indices: body mass index (BMI), waist-to-height ratio (WHtR), Clínica Universidad de Navarra–Body Adiposity Estimator (CUN-BAE), and Metabolic Score for Visceral Fat (METS-VF). Lifestyle factors included sleep quality (Pittsburgh Sleep Quality Index), Mediterranean diet adherence (MEDAS), and physical activity (IPAQ). Multivariable logistic regression models were adjusted for sociodemographic and lifestyle variables, with interaction, stratified, joint exposure, and dose–response analyses. Results: Obesity prevalence varied widely by index, ranging from 18.9% (BMI) to 55.6% (CUN-BAE). Poor sleep quality was independently associated with higher odds of obesity across all indices, particularly central obesity (WHtR OR 1.58, 95% CI 1.48–1.69), with stronger associations observed in women. Physical inactivity and non-adherence to the Mediterranean diet were robust predictors, with inactivity showing the largest effect sizes (METS-VF OR 9.92, 95% CI 8.70–11.15). Interaction analyses indicated that both Mediterranean diet adherence and regular physical activity attenuated the adverse association between poor sleep and obesity outcomes. Restricted cubic spline models revealed a progressive dose–response relationship between increasing PSQI score and central obesity. Joint exposure analyses showed nearly five-fold higher odds of central obesity among workers with concurrent poor sleep, physical inactivity, and low Mediterranean diet adherence. A graded inverse association was observed between a composite healthy lifestyle score (0–3) and obesity, with a score of 3 associated with 72–75% lower odds of BMI-obesity and WHtR-high. Conclusions: In this large occupational cohort, poor sleep quality, physical inactivity, and low Mediterranean diet adherence emerged as independent and combined determinants of general, central, and visceral obesity. Integrated workplace strategies promoting sleep hygiene, physical activity, and dietary quality—particularly among women and lower socioeconomic groups—may represent an effective approach to reducing obesity risk in working populations.

BACKGROUND:Atherogenic dyslipidemia (AD) and associated lipid ratios are critical markers for cardiovascular risk, yet little is known about how these markers vary by occupational sector and sociodemographic or lifestyle factors in working populations. OBJECTIVE:To evaluate the prevalence and determinants of elevated atherogenic risk according to total cholesterol/HDL-c (TC/HDL-c), LDL-c/HDL-c, triglycerides/HDL-c (TG/HDL-c), and AD in workers from the commerce and industry sectors, stratified by sex, age, education, physical activity, diet, and smoking. METHODS:This cross-sectional study included 56,856 Spanish workers (39,448 men and 17,408 women) from commerce (n=27,448) and industry (n=29,408). Sociodemographic, clinical, and lifestyle data were collected, and atherogenic risk was assessed using TC/HDL-c, LDL-c/HDL-c, TG/HDL-c ratios, and AD presence. Mean values and prevalence were compared by group, and multinomial logistic regression was used to estimate the association between risk markers and covariates. RESULTS:Workers in the industry sector showed higher mean values and prevalence of all atherogenic risk scales compared to those in commerce, particularly among men and older age groups. Male sex, older age, lower education, physical inactivity, absence of Mediterranean diet, and smoking were consistently associated with higher odds of elevated lipid ratios and AD. Notably, the absence of physical activity was strongly associated with all outcomes, with ORs ranging from 3.08 to 11.66. The industrial sector was independently associated with increased risk: TC/HDL-c (OR=1.23), LDL-c/HDL-c (OR=1.15), TG/HDL-c (OR=1.16), and AD (OR=1.19). CONCLUSIONS:Atherogenic risk profiles are less favorable among industrial workers and are significantly influenced by modifiable lifestyle factors. These findings support the need for preventive strategies tailored to the occupational context, with emphasis on promoting physical activity, smoking cessation, and healthier dietary habits, in order to reduce cardiovascular risk in these populations.

Background: The Gulliver syndrome is a recently proposed conceptual framework intended to identify individuals with the simultaneous presence of multiple borderline cardiometabolic abnormalities that, when considered separately, may appear clinically unimportant. However, its epidemiological characteristics and sociodemographic distribution remain unknown. This study aimed to estimate, for the first time, the prevalence of Gulliver syndrome and to examine its association with sex, age, social class, and educational attainment in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted among 395,660 Spanish workers undergoing routine occupational health examinations between 2019 and 2020. Gulliver syndrome was defined as the simultaneous presence of borderline abdominal adiposity, prehypertensive blood pressure, impaired fasting glucose, and elevated non-high-density lipoprotein cholesterol according to previously proposed criteria. Crude prevalence estimates and multivariable logistic regression analyses were performed to identify independent sociodemographic determinants associated with the syndrome. Results: A total of 10,920 workers fulfilled the diagnostic criteria for Gulliver syndrome, corresponding to an overall prevalence of 2.76% (95% confidence interval [CI]: 2.71–2.81). The prevalence was markedly higher in men than in women (3.83% vs. 1.11%, p<0.001) and increased with age, reaching its highest values among individuals aged 50–59 years. In multivariable analyses, women showed significantly lower odds of presenting the syndrome than men (odds ratio [OR]: 0.28; 95% CI: 0.26–0.29). Strong age gradients were observed, with adjusted ORs ranging from 2.98 (95% CI: 2.70–3.29) among individuals aged 30–39 years to 7.41 (95% CI: 6.72–8.16) among those aged 50–59 years. Lower educational attainment was independently associated with a higher probability of presenting the syndrome, whereas workers belonging to more advantaged occupational classes exhibited lower odds. Sensitivity analyses yielded similar results. Age-stratified analyses demonstrated distinct sex-specific trajectories, with a pronounced increase in prevalence among women aged 60–69 years. Conclusions: Approximately one in every 36 Spanish workers fulfilled the diagnostic criteria for Gulliver syndrome. The syndrome exhibited marked sociodemographic gradients according to sex, age, educational attainment, and socioeconomic status. These findings provide the first epidemiological characterization of this novel phenotype and support the hypothesis that the accumulation of multiple borderline cardiometabolic abnormalities may represent an intermediate stage between optimal cardiometabolic health and overt disease. Prospective studies are warranted to determine its prognostic significance and potential value for cardiovascular risk stratification and early prevention.

Background: Burnout is a growing occupational health problem associated with psychological, organizational, and lifestyle de-Emerging evidence suggests that dietary patterns, particularly the Mediterranean diet (MD), may influence stress and mental health. Objective: To examine the association between Mediterranean diet adherence and burnout risk in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted among 92,470 employees (55,918 men and 36,552 women) undergoing occupational health examinations between January 2021 and December 2023. Mediterranean diet adherence was assessed using the 14-item MEDAS questionnaire, categorized as low, intermediate, or high. Burnout was measured with the Maslach Burnout Inventory (MBI) and classified as low, moderate, or high. Logistic regression models adjusted for age, sex, social class, physical activity, and smoking were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CI). Results: High MD adherence was significantly associated with lower odds of high burnout (OR 0.68, 95% CI: 0.62-0.75). Stratified analyses revealed stronger associations in women (OR 0.64, 95% CI: 0.58-0.72) and participants under 40 years (OR 0.53, 95% CI: 0.45-0.62). Results were consistent when MD was treated as a continuous variable and robust across sensitivity analyses, including exclusion of smokers and highly active individuals. Conclusions: Adherence to the Mediterranean diet is inversely associated with burnout risk in Spanish workers. These findings highlight the potential of integrating dietary strategies, alongside organizational and behavioral interventions, into workplace wellness programs to prevent burnout.

Background: The rapid digitalization of workplaces has transformed organizational processes and communication patterns, generating new psychosocial risks for employees. Among these emerging risks, technostress has become an important occupational health concern. However, evidence regarding the sociodemographic and lifestyle determinants of technostress in large working populations remains limited. Objective: To examine the association between sociodemographic characteristics, lifestyle factors, and high technostress in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted using data from 102,878 Spanish workers who underwent routine occupational health examinations between January 2021 and December 2024. Technostress was assessed using the Technostress Short Questionnaire (TCS-Short). Sociodemographic variables included sex, age, educational level, and social class. Lifestyle variables comprised physical activity, adherence to the Mediterranean diet, and smoking status. Associations with high technostress were evaluated using multivariable logistic regression models, and adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. Results: Moderate technostress was the most frequent category (46.6%), followed by low (23.3%), high (22.0%), and very high technostress (8.2%). Overall, 30.1% of workers were classified as having high or very high technostress. Female workers showed significantly lower odds of high technostress than men (OR = 0.15; 95% CI 0.14–0.16). A marked age-related gradient was observed, with workers aged 60–69 years presenting substantially higher odds than those aged 20–29 years (OR = 84.52; 95% CI 73.48–97.23). Secondary and university education were independently associated with lower odds of high technostress (OR = 0.60 and OR = 0.34, respectively). Social class III was associated with increased odds of technostress (OR = 1.53; 95% CI 1.26–1.87). Regular physical activity (OR = 0.14; 95% CI 0.13–0.15) and adherence to the Mediterranean diet (OR = 0.41;95% CI 0.38–0.44) emerged as strong protective factors. Smoking showed a modest inverse association (OR = 0.83; 95%CI 0.80–0.87). Conclusions: Technostress affects nearly one-third of Spanish workers and is strongly associated with sociodemographic and lifestyle characteristics. Older age, male sex, lower educational attainment, and lower social class were associated with a greater likelihood of elevated technostress, whereas physical activity and adherence to the Mediterranean diet showed significant protective effects. These findings highlight the importance of integrating digital risk management with occupational health promotion strategies in increasingly digitalized workplaces.

INTRODUCTION:insulin resistance is a key contributor to cardiometabolic diseases, yet it remains understudied among domestic workers. This study evaluates the usefulness of the TyG, METS-IR, and SPISE indices as non-invasive tools to estimate insulin resistance risk in this population. BACKGROUND:insulin resistance (IR) is a major precursor of type 2 diabetes and cardiovascular disease, yet its prevalence and associated factors remain underexplored in informal labor sectors. This study aimed to evaluate the prevalence of elevated IR scores using validated non-invasive indices (TyG, METS-IR, and SPISE) and their association with sociodemographic and lifestyle variables in a large cohort of Spanish female domestic workers. METHODS:a cross-sectional analysis was conducted using health examination data from 6,321 adult female domestic workers in Spain. IR was assessed using three surrogate indices: the triglyceride-glucose index (TyG), the metabolic score for insulin resistance (METS-IR), and the single-point insulin sensitivity estimator (SPISE). Participants were classified into quartiles based on each index. Associations with age, smoking status, physical activity (IPAQ-SF), and adherence to the Mediterranean diet were evaluated using logistic regression models adjusted for potential confounders. RESULTS:a high proportion of participants were in the highest-risk quartile for TyG (25.3 %), METS-IR (24.9 %), and the lowest-risk quartile for SPISE (26.8 %). Older age, smoking, low physical activity, and low Mediterranean diet adherence were significantly associated with unfavorable IR profiles across all three indices. Multivariate logistic regression showed that physical inactivity was strongly associated with high TyG (OR = 3.12), high METS-IR (OR = 3.28), and low SPISE (OR = 4.07) scores. The prevalence of high IR scores increased with age and was notably higher among smokers and individuals with poor dietary habits. CONCLUSIONS:this study reveals a concerning prevalence of elevated insulin resistance among female domestic workers in Spain and identifies modifiable lifestyle factors associated with metabolic risk. The use of simple, cost-effective indices such as TyG, METS-IR, and SPISE offers a valuable opportunity for early identification of cardiometabolic risk in underserved labour populations. Targeted interventions promoting physical activity, dietary improvement, and smoking cessation are urgently needed to reduce long-term health disparities in this occupational group.

Background: Insulin resistance (IR) is a key antecedent of type 2 diabetes and cardiometabolic disease. Whether IR differs systematically across professional groups remains underexplored. We assessed occupational gradients in IR using non-insulin-based indices among physicians, nurses, and non-healthcare workers. Methods: Cross-sectional study (Spain, 2021-2024) including 12,874 adults (physicians, nurses, and non-healthcare controls). Standardized anthropometry, blood pressure, and fasting biochemistry were obtained. IR was estimated using TyG, TyG-BMI, METS-IR, and SPISE-IR. "High IR risk" was defined by sex-specific 75th percentiles. Between-group differences were tested with ANOVA/X2 (Bonferroni post-hoc). Multivariable linear and logistic models examined associations between occupation and IR (adjusted for age, sex, BMI, smoking, alcohol, physical activity, Mediterranean diet adherence, shift work, and sleep duration). We evaluated discrimination (AUC with DeLong tests), calibration, decision-curve analysis (DCA), and E-values for robustness. Results: We observed a graded occupational pattern: physicians had the most favorable profiles, nurses were intermediate, and controls were least favorable across all indices. Prevalence of high TyG was similar to 13-14% in controls versus 1-3% in physicians/nurses. In adjusted models, odds of high TyG were higher in nurses vs. physicians (OR 2.15; 95% CI 1.80-2.51) and markedly higher in controls vs. physicians (OR 7.25; 95% CI 6.01-8.50); comparable gradients were observed for TyG-BMI, METS-IR, and SPISE-IR (e.g., controls vs. physicians OR range ). Age-BMI interactions showed steeper IR increases with advancing age at higher BMI. METS-IR and TyG-BMI yielded the strongest discrimination (AUC typically >0.75), with satisfactory calibration and net clinical benefit on DCA within 0.10-0.30 risk thresholds. E-values >7 for control vs. physician contrasts indicated robustness to unmeasured confounding. Conclusions: IR risk varies substantially by occupation, with a consistent gradient from physicians to nurses to non-healthcare workers, independent of sociodemographic and lifestyle factors. Simple non-insulin-based indices enable prag-risk stratification in occupational health. Findings support targeted preventive strategies (schedule design, sleep and-trition programs, and physical activity) and warrant longitudinal and interventional studies incorporating chronobiology-aware exposure metrics.

Background: Early identification of individuals at increased risk of type 2 diabetes mellitus (T2DM) is essential for effective prevention strategies. Although several validated diabetes risk scores are available, their routine application may be limited in large-scale or occupational settings. Simple anthropometric and metabolic indexes may represent practical alternatives for diabetes risk screening. Objective: To evaluate the association and discriminatory performance of four anthropometric and metabolic indexes-body mass index (BMI), waist-to-height ratio (WtHR), triglyceride-glucose (TyG) index, and waist-triglyceride index (WTI)-in relation to high-risk classifications defined by QDScore, FINRISK, CANRISK, and TRAQ-D. Methods: A cross-sectional study was conducted in 383,980 Spanish workers aged 18-69 years without diagnosed diabetes. Anthropometric measurements and fasting biochemical parameters were obtained using standardized protocols. Diabetes risk scores were calculated, and receiver operating characteristic (ROC) curve analyses were performed to assess the ability of each index to identify individuals classified as high risk. Analyses were stratified by sex. Results: Higher values of BMI, WtHR, TyG, and WTI were consistently associated with high-risk classifications across all diabetes risk scores (p < 0.001). BMI and WtHR showed excellent discriminatory performance, particularly in women, with area under the curve (AUC) values exceeding 0.90 for several scores. Metabolic indexes (TyG and WTI) demonstrated moderate but consistent discrimination in both sexes. Conclusions: Simple anthropometric and metabolic indices are closely associated with validated T2DM risk scores and allow for the effective identification of individuals at higher risk within occupational populations. Their simplicity and low cost support their use in population and occupational screening strategies.

Background: Obesity is a major public health concern and shows a clear social gradient, with higher prevalence among individuals with lower socioeconomic position. Educational level is a key indicator of socioeconomic status, but the extent to which lifestyle factors explain its association with obesity remains unclear. Objective: To examine the association between educational level and obesity in a working-age population and to evaluate how adjustment for lifestyle factors influences the magnitude of the association between educational level and obesity. Methods: A cross-sectional study was conducted among 3108 working-age adults undergoing occupational health assessments in Spain. Educational level was categorised into three groups (higher, intermediate, and primary or none). Obesity was defined as a body mass index ≥30 kg/m2. Lifestyle variables included smoking status, physical activity assessed using the International Physical Activity Questionnaire (IPAQ-SF), and adherence to the Mediterranean diet evaluated with the MEDAS-14 score. Sequential logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CI), with progressive adjustment for demographic, behavioural, and clinical factors. Results: The overall prevalence of obesity was 16.6%, with a clear gradient across educational levels (11.5% in higher education vs. 19.8% in primary or no education). In crude analyses, individuals with the lowest educational level had higher odds of obesity (OR 1.89; 95% CI 1.46–2.45). Adjustment for age and sex attenuated the association (OR 1.72; 95% CI 1.32–2.24), with further reduction after inclusion of lifestyle factors (OR 1.63; 95% CI 1.24–2.13). In the fully adjusted model, the association remained statistically significant (OR 1.61; 95% CI 1.18–2.21), indicating that adjustment for lifestyle factors attenuated the association between educational level and obesity, although the association remained statistically significant. Conclusions: Lower educational level is associated with a higher risk of obesity. Adjustment for lifestyle factors attenuated this association, although a statistically significant relationship remained. These findings support the role of education as a fundamental determinant of health and highlight the need for strategies addressing broader social and structural determinants of obesity.

Background: BMI is widely used for obesity classification, yet it does not adequately reflect adiposity distribution and related metabolic risk. Normal-weight obesity (NWO), defined as excess adiposity despite normal BMI, has emerged as a clinically relevant phenotype associated with increased cardiometabolic risk. However, its prevalence and implications in young populations remain insufficiently characterized. Objective: To evaluate the prevalence of normal-weight obesity and its association with cardiometabolic risk markers in a cohort of young adults undergoing occupational health assessments. Methods: A cross-sectional study was conducted in 12,874 adults aged 22–30 years undergoing routine occupational health assessments. NWO was defined using a strict criterion (normal BMI with a waist-to-height ratio ≥ 0.5) and an expanded definition including additional adiposity markers derived from body fat percentage and visceral fat estimates. Anthropometric, adiposity-related, biochemical, and lifestyle data were collected using standardized protocols. Multivariable logistic regression models adjusted for age and sex were used to assess associations between NWO and cardiometabolic risk markers. Results: Among individuals with normal BMI (n = 9290), the prevalence of NWO was 1.79% (n = 166) using the strict definition and 2.30% (n = 214) with the expanded definition. Compared with metabolically healthy normal-weight individuals, those with NWO exhibited higher triglycerides, fasting glucose, and atherogenic lipid indices, along with lower HDL cholesterol (all p < 0.05). In multivariable analyses, NWO was independently associated with elevated triglycerides (OR 4.99; 95% CI 2.90–8.58), an unfavorable triglyceride-to-HDL ratio (OR 7.44; 95% CI 5.19–10.65), and impaired fasting glucose (OR 3.87; 95% CI 2.19–6.82). Associations were consistent across sensitivity and sex-stratified analyses. Conclusions: Normal-weight obesity is present in a measurable proportion of young adults and is associated with an unfavorable cardiometabolic profile despite normal BMI. The triglyceride-to-HDL ratio was consistently associated with normal-weight obesity and showed marked differences across adiposity-defined phenotypes. These findings highlight the limitations of BMI-based classification alone and suggest that additional anthropometric and metabolic markers may help identify individuals with less favorable cardiometabolic characteristics.

Background: The identification of individuals at risk for metabolic syndrome (MetS) is essential for preventing cardiometabolic complications. Traditional anthropometric indices such as body mass index (BMI) and waist circumference (WC) are widely used, but the potential utility of bioimpedance-derived total and visceral fat is gaining interest. Objective: To compare the predictive value of body fat, visceral fat, BMI, and WC in diagnosing MetS according to NCEP ATP III, IDF, and JIS criteria in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted in 8,590 Spanish adults (4,104 men and 4,486 women). Anthropometric measurements and bioimpedance analysis were performed. MetS was classified using NCEP ATP III, IDF, and JIS definitions. ROC curve analyses were applied to determine diagnostic accuracy. Results: WC exhibited the highest predictive performance for MetS in both sexes across all criteria (AUCs up to 0.947 in men and 0.937 in women). Visceral fat also showed high discriminative ability (AUCs up to 0.927), surpassing BMI and body fat in several models. Optimal cut-off points varied by sex and criterion. Agreement among MetS definitions was high (Cohen's Kappa > 0.85). Conclusion: Visceral fat measured by bioimpedance provides significant discriminatory power in identifying MetS but does not outperform WC. WC remains the most practical and effective tool in occupational health screening.

Background:Obesity remains a major global health concern, and psychosocial stressors such as burnout may contribute to its development. While lifestyle and sociodemographic factors are recognized determinants, their interaction with burnout has been less studied, especially using advanced adiposity indices. In this study, we assessed the associations between burnout, sociodemographic variables, lifestyle habits, and obesity in a large cohort of Spanish employees. Methods:We performed a cross-sectional analysis of Spanish workers undergoing occupational health examinations. Burnout was classified into low, moderate, and high levels. Obesity was assessed using body mass index (BMI), waist-to-height ratio (WtHR), the Clínica Universidad de Navarra Body Adiposity Estimator (CUN-BAE), and the Metabolic Score for Visceral Fat (METS-VF). Logistic regression models adjusted for sociodemographic and behavioral variables were applied, including interaction analyses. Results:Burnout showed a strong and graded association with obesity across all indices. Compared with low burnout, high burnout was associated with up to a 40% higher odds of obesity by BMI, and even stronger associations when using CUN-BAE and METS-VF. Women, older employees, and those from lower social classes were disproportionately affected. Adherence to a Mediterranean diet and engagement in regular physical activity were associated with lower obesity risk among participants with higher burnout levels. Conclusions:Burnout is a significant and independent correlate of obesity in working populations, particularly when measured with indices capturing visceral fat. Vulnerable groups, women, older workers, and lower social classes, -require targeted interventions. Workplace health programs should integrate stress management with lifestyle promotion as dual strategies to combat obesity. Longitudinal research is needed to confirm causality and assess intervention effectiveness.

Background: Work engagement, defined as a positive, fulfilling psychological state characterized by vigor, dedication, and absorption, has been proposed as a potential protective factor for cardiometabolic health. However, its relationship with obesity-particularly visceral adiposity- remains poorly understood. This study aimed to examine the association between work engagement and different adiposity indicators and to explore the mediating role of lifestyle behaviors in a large sample of Spanish workers. Methods: A cross-sectional analysis was conducted among employees attending occupational health evaluations between 2021 and 2022. After applying inclusion and exclusion criteria, 111,612 participants (60.1% men) were included. Work engagement was assessed using the Utrecht Work Engagement Scale (UWES-9) and categorized into very high, high, moderate, and low levels. Obesity and adiposity were evaluated through BMI, waist-to-height ratio (WtHR), CUN-BAE, and METS-VF. Logistic regression models estimated odds ratios (OR) and 95% confidence intervals (CI) for obesity outcomes across engagement levels, with progressive adjustment for sociodemographic and lifestyle covariates. Mediation analyses evaluated the indirect effects of physical activity, Mediterranean diet adherence, and smoking. Results: Lower engagement levels were independently associated with higher odds of adiposity across all indices, particularly visceral fat (METS-VF). Participants with low engagement had an adjusted OR = 2.59 (95% CI 2.34-2.85) for high METS-VF compared with those with very high engagement (p-trend < 0.001). Approximately 40% of this association was mediated by lifestyle factors, mainly physical activity. The results remained robust across sensitivity analyses, including nonlinear modeling, imputation, and cluster adjustment. Conclusions: Lower work engagement is strongly associated with increased visceral adiposity among Spanish workers, partly through behavioral mechanisms. Enhancing engagement may represent an effective psychosocial strategy to improve both psychological well-being and metabolic health in occupational settings.

Background: Technostress has emerged as a growing occupational health concern in increasingly digitalized workplaces. Although its psychological consequences have been extensively investigated, little is known about its potential association with metabolic health and insulin resistance. This study aimed to evaluate the relationship between technostress and insulin resistance risk using four validated surrogate markers in a large cohort of Spanish workers. Methods: A cross-sectional study was conducted among 104,175 Spanish workers who underwent routine occupational health assessments. Technostress was assessed using a 15-item questionnaire covering five technostress dimensions and was analyzed using four operational categories (low, moderate, high, and very high). Insulin resistance risk was assessed using the triglyceride–glucose (TyG) index, TyG-body mass index (TyG-BMI), the metabolic score for insulin resistance (METS-IR), and the single-point insulin sensitivity estimator (SPISE). Sociodemographic characteristics, lifestyle habits, anthropometric measurements, and biochemical parameters were also recorded. Modified Poisson regression with robust variance estimation was used to estimate crude and adjusted prevalence ratios (PRs) for increased insulin resistance risk according to technostress level. Firth penalized logistic regression was additionally performed as a sensitivity analysis to address sparse-data bias and separation. Results: Higher technostress levels were associated with progressively less favorable anthropometric and metabolic profiles. The prevalence of increased insulin resistance risk rose significantly across technostress categories for all markers evaluated (p < 0.001). For TyG, prevalence increased from 3.8% in the low technostress group to 54.3% in the very high technostress group. Corresponding increases were observed for TyG-BMI (0.2% to 78.2%), METS-IR (0.0% to 45.2%), and elevated SPISE-IR values (0.0% to 57.5%). After adjustment for age, sex, educational level, physical activity, adherence to the Mediterranean diet, and smoking status, higher technostress remained associated with a higher prevalence of increased insulin resistance risk. A clear graded cross-sectional pattern was observed, with the strongest associations found among workers reporting very high technostress. Conclusions: Higher technostress was associated with a higher prevalence of increased insulin resistance risk according to TyG, the primary outcome, with a clear graded cross-sectional pattern across technostress categories. Associations were also observed for the secondary BMI-containing indices (TyG-BMI, METS-IR, and SPISE-IR), which should be interpreted as complementary rather than independent evidence. Given the cross-sectional design and the pronounced clustering of technostress with adiposity and lifestyle characteristics, residual confounding cannot be excluded and causal inference is not possible.

Background: Behavioral procrastination has traditionally been considered a psychological construct related to self-regulatory failure and maladaptive coping behaviors. However, growing evidence suggests that procrastination may also influence physical health through unhealthy lifestyle patterns, chronic stress exposure, and impaired behavioral regulation. Nevertheless, the relationship between procrastination and objectively assessed cardiometabolic disease remains insufficiently explored. Objective: To evaluate the association between behavioral procrastination and metabolic syndrome in a large occupational cohort of Spanish workers.Methods: A cross-sectional study was conducted in 92,184 active workers undergoing routine occupational health assessments between 2021 and 2024. Behavioral procrastination was evaluated using the PPS-9 questionnaire and categorized into very low, moderate, high, and very high/chronic procrastination levels. Metabolic syndrome was defined according to harmonized international criteria. Anthropometric, clinical, biochemical, and lifestyle-related variables were analyzed. Logistic regression models were constructed to assess the independent association between procrastination and metabolic syndrome after adjustment for demographic, behavioral, and adiposity-related variables.Results: Higher behavioral procrastination levels were consistently associated with a markedly less favorable cardiometabolic profile, including higher body mass index, waist circumference, blood pressure, fasting glucose, triglycerides, TyG index, and estimated heart age (all p < 0.001). The prevalence of metabolic syndrome increased progressively across procrastination categories, ranging from 0.1% in participants with very low procrastination to 34.6% in those with very high/chronic procrastination according to IDF criteria. In fully adjusted models including age, sex, smoking status, physical activity, dietary habits, educational level, and BMI, behavioral procrastination remained independently associated with metabolic syndrome. Compared with participants with very low procrastination, adjusted odds ratios were 5.87 (95% CI 3.99–8.63) for moderate procrastination, 12.35 (95% CI 8.34–18.29) for high procrastination, and 22.97 (95% CI 15.29–34.52) for very high/chronic procrastination (all p < 0.001). A significant dose-response relationship was observed across the full spectrum of procrastination scores.Conclusions: Behavioral procrastination was strongly and independently associated with metabolic syndrome and adverse cardiometabolic profiles in this large occupational cohort. The observed dose-response relationship and the persistence of the association after extensive adjustment suggest that procrastination may represent a relevant behavioral marker of cardiometabolic vulnerability. Future longitudinal studies are needed to clarify potential causal mechanisms and evaluate whether behavioral interventions targeting procrastination may contribute to cardiometabolic prevention strategies.

BACKGROUND:Sleep disturbances, particularly insomnia, are increasingly recognized as behavioral determinants of type 2 diabetes (T2DM). However, their contribution to validated diabetes risk scores beyond traditional sociodemographic and lifestyle factors remains insufficiently explored. OBJECTIVE:To examine the association between insomnia severity, sociodemographic variables, lifestyle habits, and estimated T2DM risk using three validated non-invasive risk assessment scales. METHODS:A cross-sectional study was conducted among 84,898 Spanish workers aged 18-69 years undergoing occupational health evaluations (2021-2024). Sociodemographic and behavioral data were collected through standardized questionnaires, including adherence to the Mediterranean diet (MEDAS-14), physical activity (IPAQ-SF), and smoking status. Insomnia was assessed using the Insomnia Severity Index (ISI). Diabetes risk was estimated using three validated non-invasive risk-assessment tools: the Finnish Diabetes Risk Score, the QDScore/QDiabetes, and the Trinidad Risk Assessment Questionnaire for Type 2 Diabetes Mellitus. As these instruments were developed and validated in different populations, comparisons of absolute risk categories across scales should be interpreted with caution. Multivariable logistic regression models adjusted for age, sex, social class, smoking, diet, and physical activity were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS:Severe insomnia was associated with approximately 2.1-2.6-fold higher odds of high estimated diabetes risk across all three scales in the pooled analyses, with significant trends across categories of insomnia severity (all P for trend <0.001). This association persisted across sex and activity strata. Adding ISI modestly improved model discrimination (ΔAUC ≈ +0.015; P≤0.003) and reclassification (continuous net reclassification improvement [NRI], 6.5%-8.1%). CONCLUSIONS:Insomnia severity was independently associated with higher estimated risk of T2DM beyond measured sociodemographic and lifestyle determinants. Incorporating sleep health-via brief tools such as the ISI-into diabetes risk assessment could enhance early prevention strategies in clinical and occupational settings.

Background: Body mass index (BMI) remains the standard tool for obesity screening; however, it does not account for body fat distribution or visceral adiposity, potentially leading to clinically relevant misclassification—particularly in young adults. Evidence on this issue in healthcare professionals is limited. Objective: To evaluate the extent of obesity misclassification when using BMI compared with alternative anthropometric and body composition indices, and to examine sex-specific associations between lifestyle factors and different adiposity phenotypes in young healthcare professionals. Methods: A large cross-sectional study was conducted in 12,874 medical residents, nursing residents, and age-matched controls (22–30 years). Obesity was defined using BMI (≥30 kg/m2), waist-to-height ratio (WtHR ≥ 0.5), Clínica Universidad de Navarra–Body Adiposity Estimator (CUN-BAE), body fat percentage, and bioimpedance-derived visceral fat. Multivariable logistic regression models adjusted for age, sex, professional group, smoking, physical activity, and Mediterranean diet adherence were fitted separately for each adiposity definition. Sex interaction terms were formally tested. Agreement between indices was assessed using Cohen’s kappa. Results: Obesity prevalence varied substantially according to the index applied and was consistently higher when central or visceral adiposity measures were used. Agreement between BMI and alternative indices was only fair to moderate, with the lowest concordance observed for visceral fat (κ = 0.29; 95% CI 0.26–0.32). Male sex was strongly associated with visceral fat-defined obesity (aOR 4.76; 95% CI 3.82–5.92), while effect sizes were attenuated for BMI-defined obesity (aOR 1.41; 95% CI 1.32–1.51). Significant sex interactions were detected for visceral adiposity, particularly for physical activity (p = 0.001) and smoking (p = 0.002), indicating differential lifestyle associations according to fat distribution phenotype. Conclusions: BMI substantially underestimates clinically relevant central and visceral adiposity in young healthcare professionals. Sex-specific differences were observed in the association between lifestyle behaviors and visceral fat. These findings highlight the limitations of relying exclusively on BMI for obesity screening. Incorporating waist-based or body composition-derived measures may improve early risk identification and support targeted preventive strategies.