This systematic review and meta-analysis aim to provide the best evidence on the association between metabolic syndrome (MetS) and uric acid (UA) by determining the size of the effect of this biomarker on MetS. The review protocol is registered with PROSPERO (CRD42021231124). The search covered the PubMed and Scopus databases. Methodological quality was assessed with the STROBE tool, overall risk of bias with RevMan (Cochrane Collaboration) and quality of evidence with Grade Pro. Initially, 1582 articles were identified. Then, after excluding duplicates and reviewing titles and abstracts, 1529 articles were excluded from applying the eligibility criteria. We included 43 papers (56 groups) comparing UA concentrations between subjects 91,845 with MetS and 259,931 controls. Subjects with MetS had a higher mean UA of 0.57 mg/dl (95% CI 0.54–0.61) (p < 0.00001). Given the heterogeneity of the included studies, the researchers decided to perform subgroups analysis. Men with MetS have a higher UA concentration mg/dl 0.53 (95% CI 0.45–0.62, p < 0.00001) and women with MetS 0.57 (95% CI 0.48–0.66, p < 0.00001) compared to subjects without MetS. Assessment of UA concentration could provide a new avenue for early diagnosis of MetS, as a new biomarker and the possibility of new therapeutic targets.

Approximately one-third of overweight individuals, and half of those with obesity, do not have cardiometabolic disorders. For this reason, a phenotype called metabolically healthy obese (MHO) has emerged to describe this population group. The early detection of this situation could save costs associated with the development of comorbidities or pharmacological interventions. Therefore, the aim is to know the prevalence of MHO in the working population and propose variables for its detection. Cross-sectional descriptive study of 635 workers of the Cordoba City Council was carried out based on the results of the 2016 health surveillance. The outcome variables were the MHO, established based on the criteria of the IDF, NCEP—ATP III, and Aguilar—Salinas. In addition, the degree of agreement between the different MHO criteria was studied using Cohen's kappa (k), and the predictive capacity of the anthropometric variables was assessed with Receiver Operator Curves. The prevalence of MHO ranged from 6.6 to 9%. The highest agreement was reached between the IDF and NCEP-ATP III definitions (k = 0.811; 95% CI 0.724–0.898; p &lt; 0.001). The waist-to-height ratio (WHtR) showed the highest discriminant capacity for MHO, with its best cut-off point at 0.55 for all criteria used. Sensitivity ranged from 84 to 93%. The prevalence of MHO in the working population differed according to the criteria used for diagnosis. The anthropometric variable with the highest discriminant capacity for MHO was WHtR, presenting the same cut-off point in the three criteria analyzed. Therefore, WHtR is the variable that best detects the presence of MHO.

Background: Overweight and obesity are public health problems that affects the workplace. This paper aims to analyse the effectiveness of workplace health promotion interventions in reducing Body Mass Index (BMI); Methods: Following PRISMA guidelines, a systematic review was conducted using PubMed, MEDLINE, and SCOPUS databases. The inverse variance statistical method was used for the meta-analysis with a random effects analysis model and standardised means. The results have been represented by Forest Plots and Funnel Plots graphs; Results: The multicomponent approach had the best results for reducing BMI (−0.14 [−0.24, −0.03], 95% CI; p = 0.009) compared to performing physical activity only (−0.09 [−0.39, 0.21], 95% CI; p = 0.56). However, both methods resulted in positive changes in reducing BMI in the general analysis (−0.12 [−0.22, −0.02], 95% CI; p = 0.01). The GRADE evaluation showed low certainty due to the high heterogeneity between interventions (I2 = 59% for overall analysis). Conclusions: The multicomponent approach could be an effective intervention to reduce obesity in the working population. However, workplace health promotion programs must be standardised to conduct quality analyses and highlight their importance to workers’ well-being.

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