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Resumen Fundamento: La obesidad predispone a sufrir diabetes tipo 2 con tanta frecuencia que su combinación se denomina diabesidad. El objetivo de este estudio fue determinar la prevalencia de diabesidad en la población trabajadora y analizar las variables con las que se asocia. Material y métodos: Estudio transversal realizado entre enero de 2019 y junio de 2020 en 418.343 trabajadores de 18 a 67 años, de diferentes profesiones y áreas geográficas españolas. Se determinó la prevalencia de diabesidad con seis fórmulas diferentes para obesidad: IMC (índice de masa corporal), CUN BAE (Clínica Universidad de Navarra-Body Adiposity Estimator), ECORE-BF (Equation Córdoba for Estimation of Body Fat), Fórmula Palafolls, IMG (índice de masa grasa) de Deuremberg y RFM (Relative Fat Mass). Se analizó la asociación entre diabesidad y edad, sexo, clase social y tabaco. Resultados: La prevalencia global de diabesidad osciló entre 2,6 % por el IMC y 5,8% por la fórmula Palafolls. La variable más relacionada con la diabesidad fue la edad mayor de 50 años (OR = 5,9; IC95%: 5,7-6,2 para IMC, y OR = 8,1; IC95%: 7,9-8,4 para IMG de Deuremberg). El sexo masculino y la clase social III se relacionaron con la diabesidad estimada con todas las escalas, ser fumador solo con la fórmula Palafolls. Conclusiones: La prevalencia de diabesidad varía en función de la fórmula empleada, con una prevalencia menor entre las mujeres y un aumento con la edad independientemente de la fórmula utilizada. Su prevalencia es mayor en las clases sociales más bajas.

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.