Background: Metabolic syndrome (Met-S) is considered one of the most important health problems of the 21st century. It includes a group of metabolic disorders that increase the risk of cardiovascular diseases such as overweight and obesity, elevated lipid profile and blood pressure and insulin resistance (IR). Based on the information mentioned above in which there seems to be a relationship between IR and Met-S, the objective of this work was twofold: on the one hand, to assess the relationship between the values of different insulin resistance risk scales and Met-S determined with three different scales, and on the other, to determine whether any of the components of Met-S predispose more to the appearance of IR. Methods: A descriptive cross-sectional study of 418,343 workers. Waist circumference was measured and evaluated together with six formulas to assess the insulin resistance index. Categorical variables were evaluated by calculating the frequency and distribution of each one. For quantitative variables, mean and standard deviation were determined, and Student’s t-test was applied, while for qualitative variables, the chi-square test was performed. The usefulness of the different risk scales for insulin resistance for predicting metabolic syndrome was evaluated using ROC curves, the area under the curve (AUC), as well as their cut-off points for sensitivity, specificity, and the Youden index. Results: People with metabolic syndrome applying any criteria had higher values in the IR risk scales. The different IR scales made it possible to adequately classify people with metabolic syndrome. Of the three definitions of Met-S, the one that showed the greatest relationship with IR was IDF. Conclusions: Most risk scales for insulin resistance enable the presence of metabolic syndrome to be adequately classified, finding the best ones if the International Diabetes Federation (IDF) criteria are applied. Of the elements included in the Met-S, the one that seems to increase the risk of presenting IR the most is waist circumference; hence, the Met-S definition that is most related to IR is that of the IDF, which is the only one of the three in which a high value of waist circumference is necessary to be able to diagnose Met-S. Waist circumference can be considered the central essential component for detecting insulin resistance and, therefore, the early detection of metabolic syndrome.

The aim of the study was to determine the criterion validity of a computerized version of the General Anxiety Disorder-7 (GAD-7) questionnaire to detect general anxiety disorder in Spanish primary care centers. A total of 178 patients completed the GAD-7 and were administered the Composite International Diagnostic Interview (CIDI) for DSM-IV Axis I Disorders, which was used as a reference standard. Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios were calculated. A cut-off of 10 yielded a sensitivity of .87, a specificity of .78, a positive predictive value of .93, a negative predictive value of .64, a positive likelihood ratio of 3.96 a negative likelihood ratio of .17 and Younden's Index of .65. The GAD-7 performed very well with a cut-off value of 10, the most frequently used cut-off point. Thus, a computerized version of the GAD-7 is an excellent screening tool for detecting general anxiety disorder in Spanish primary care settings.

Background: Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness. Objective: This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention—combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only—on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity. Methods: We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire–Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire. Results: Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (−0.26, 95% CI −1.21 to 0.70 kg; P=.02), BMI (−0.06, 95% CI −0.41 to 0.28 points; P=.01), waist-height ratio (−0.25, 95% CI −0.94 to 0.44; P=.03), body adiposity index (−0.33, 95% CI −0.77 to 0.11; P=.03), waist circumference (−0.48, 95% CI −1.62 to 0.66 cm, P=.04) and hip circumference (−0.69, 95% CI –1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI −30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people. Conclusions: The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups. Trial Registration: ClinicalTrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614 International Registered Report Identifier (IRRID): RR2-10.1097/MD.0000000000009633

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect. Trial Registration: Clinicaltrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614. International Registered Report Identifier (IRRID): RR2-10.1097/MD.0000000000009633

Background: Atherogenic dyslipidaemia (AD) and lipid triad (LT) are characterised by high triglyceride levels together with low HDL and normal or high LDL cholesterol and are favoured by a persistent state of insulin resistance (IR), which increases the release of free fatty acids from abdominal adipose tissue. This alteration in the lipid profile favours the accelerated development of atherosclerosis, which is the most important cause of morbidity and mortality in all countries in the developed and developing world. One of the elements that plays a major role in the genesis of AD is IR. The aim of this study was to determine the relationship between variables that assess atherogenic risk (AD and LT) and scales that assess the risk of presenting insulin resistance. Methods: A descriptive cross-sectional study of 418,343 workers was conducted to evaluate atherogenic dyslipidaemia and lipid triad; a relationship with three insulin resistance risk scales (Triglycerides/HDL, TyG index, METS-IR) was established. The usefulness of IR risk scales for predicting AD and LT was calculated by applying ROC curves, obtaining the area under the curve (AUC) and cut-off points with their sensitivity, specificity, and Youden index. Multivariate analysis was performed by binary logistic regression. Results: The prevalence of high-risk values for insulin resistance with all of the scales is much higher in people with AD and LT compared to those without. The ROC curves present us with an AUC with the three insulin resistance risk scales for the two dyslipidaemias studied with figures ranging between 0.856 and 0.991, which implies that the results are good/very good. Conclusions: A relationship between atherogenic dyslipidaemia and the three insulin resistance risk scales assessed is revealed, with higher IR mean values and prevalence in people with atherogenic dyslipidaemia and lipid triad. The three scales make it possible to adequately classify the presence of AD and LT. The highest AUC is presented by the triglycerides/HDL scale, with a result close to 1. METS-IR is the most recommended formula to estimate insulin resistance.

Background: Insulin resistance (IR) is an alteration of the action of insulin in cells, which do not respond adequately to this action, leading to an increase in blood glucose levels. IR produces a very diverse clinical picture and increases the cardiometabolic risk of the population that suffers from it. Among the factors that influence IR are genetics, unhealthy lifestyle habits, overweight, and obesity. The objective of this work was to determine how different sociodemographic variables and healthy habits influence the values of different scales that assess the risk of presenting IR in a group of Spanish workers. Methods: An observational, cross-sectional, descriptive study was carried out in 386,924 workers from different Spanish regions. Different sociodemographic variables and lifestyle habits were studied (age, social class, educational level, smoking, Mediterranean diet, physical exercise) along with their association with four scales to evaluate the risk of insulin resistance (TyG index, TyG-BMI, METS-IR, TG/HDL-c). To analyse the quantitative variables, Student’s t test was used, while the Chi-squared test was used for the qualitative variables. A multinomial logistic regression analysis was performed, calculating the odds ratio with its 95% confidence intervals. The accepted level of statistical significance was set at p < 0.05. Results: In the multivariate analysis, all variables, except educational level, increased the risk of presenting high values on the IR risk scales, especially a sedentary lifestyle and low adherence to the Mediterranean diet. Conclusions: Our results demonstrate an association between the practice of regular physical exercise and a reduction in the risk of IR; a strong role of the Mediterranean diet as a protective factor for IR; an association between aging and increased IR, which has also been suggested in other studies; and, finally, a relationship between a low socioeconomic level and an increase in IR.