Determinación de diferentes escalas de riesgo cardiovascular en el profesorado español: variables asociadas

Artículos originales[EN] Introduction: Cardiovascular disease is currently one of the most prevalent non-communicable diseases, affecting nearly 57% of the world’s population, accounting for 32% of deaths worldwide. The aim of the study is to determine the cardiovascular risk of teaching staff. Methods: Retrospective, cross-sectional study carried out on 4,738 teachers from different Spanish geographical areas with a mean age of 41 years. Different variables related to cardiovascular risk are determined, such as overweight and obesity scales, nonalcoholic fatty liver scales, atherogenic indices, metabolic syndrome and cardiovascular risk scales, among others. Results: Among the results we highlight a prevalence of hypercholesterolemia of 41%, hyperteriglyceridemia 12.1%, hypertension 15.5%, obesity using BMI 13%, high risk of fatty liver 11.3% and moderate or high SCORE values 11.4%. Conclusion: The teaching staff is not free from developing CVD that we can relate to the lack of physical activity and an unhealthy diet that increases the prevalence of obesity and overweight. [ES] Introducción: Las enfermedades cardiovasculares son actualmente una de las enfermedades no transmisibles más prevalentes, ya que afectan a casi el 57% de la población mundial siendo responsables del 32% de las muertes en el mundo. El objetivo del estudio es conocer el riesgo cardiovascular del personal docente. Métodos: Estudio retrospectivo y transversal realizado en 4.738 profesores de diferentes zonas geográficas españo las con una edad media de 41 años. Se determinan diferentes variables relacionadas con el riesgo cardiovascular, como escalas de sobrepeso y obesidad, escalas de hígado graso no alcohólico, índices aterogénicos, síndrome me tabólico y escalas de riesgo cardiovascular, entre otras. Resultados: Entre los resultados destacamos una prevalencia de hipercolesterolemia del 41%, hiperterigliceri demia del 12,1%, hipertensión del 15,5%, obesidad mediante IMC del 13%, alto riesgo de hígado graso del 11,3% y valores de SCORE moderados o altos del 11,4%. Conclusión: El profesorado no está exento de desarrollar ECV que podemos relacionar con la falta de actividad física y una dieta poco saludable que aumenta la prevalencia de obesidad y sobrepeso.N

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

[EN]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.This study was funded by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III and cofunded by the European Union (ERDF/ESF, “Investing in your future”; RD16/0007/0003, RD16/0007/0005, RD16/0007/0008, and RD16/0007/0009; and PI16/00101, PI16/00952, PI16/00765, PI16/00659, PI16/00421, PI16/00170, and FI17/00040; REDIAPP). Gerencia Regional de Salud de Castilla y Leon (GRS 1277/B/16 and GRS 1580/B/17) also collaborated with the funding of this study. They played no role in the study design, data analysis, reporting results, or the decision to submit the manuscript for publication

Effectiveness of an mHealth Intervention Combining a Smartphone App and Smart Band on Body Composition in an Overweight and Obese Population: Randomized Controlled Trial (EVIDENT 3 Study)

[EN]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.[EN]This study was funded by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III, and co-funded by the European Union (ERDF/ESF, “Investing in your future”) (RD12/0005/0001, RD16/0007/0003, RD16/0007/0005, RD16/0007/0008, RD16/0007/0009 and PI16/00101, PI16/00952, PI16/00765, PI16/00659, PI16/00421, PI16/00170, FI17/00040). Gerencia Regional de Salud de Castilla y Leon (GRS 1277/B/16) also collaborated in the funding of this study. They played no role in the study design, data analysis, reporting results, or decision to submit the manuscript for publication

Determination of Different Cardiovascular Risk Scales in Spanish Teaching Staff: Associated Variables

[eng] Introduction: Cardiovascular disease is currently one of the most prevalent non-communicable diseases, affecting nearly 57% of the world's population, accounting for 32% of deaths worldwide. The aim of the study is to determine the cardiovascular risk of teaching staff. Methods: Retrospective, cross-sectional study carried out on 4,738 teachers from different Spanish geographical areas with a mean age of 41 years. Different variables related to cardiovascular risk are determined, such as overweight and obesity scales, nonalcoholic fatty liver scales, atherogenic indices, metabolic syndrome and cardiovascular risk scales, among others. Results: Among the results we highlight a prevalence of hypercholesterolemia of 41%, hyperteriglyceridemia 12.1%, hypertension 15.5%, obesity using BMI 13%, high risk of fatty liver 11.3% and moderate or high SCORE values 11.4%. Conclusion: The teaching staff is not free from developing CVD that we can relate to the lack of physical activity and an unhealthy diet that increases the prevalence of obesity and overweight