Metabolic homeostasis emerges from the interplay between several feedback systems that regulate the physiological variables related to energy expenditure and energy availability, maintaining them within a certain range. Although it is well known how each individual physiological system functions, there is little research focused on how the integration and adjustment of multiple systems results in the generation of metabolic health. The aim here was to generate an integrative model of metabolism, seen as a physiological network, and study how it changes across the human lifespan. We used data from a transverse, community-based study of an ethnically and educationally diverse sample of 2572 adults. Each participant answered an extensive questionnaire and underwent anthropometric measurements (height, weight, waist), fasting blood tests (glucose, HbA1c, basal insulin, cholesterol HDL, LDL, triglycerides, uric acid, urea, creatinine), along with vital signs (axillar temperature, systolic and diastolic blood pressure). The sample was divided into 6 groups of increasing age, beginning with less than 25 years and increasing by decades up to more than 65 years. In order to model metabolic homeostasis as a network, we used these 15 physiological variables as nodes and modeled the links between them, either as a continuous association of those variables, or as a dichotomic association of their corresponding pathological states. Weight and overweight emerged as the most influential nodes in both types of networks, while high betweenness parameters, such as triglycerides, uric acid and insulin, were shown to act as gatekeepers between the affected physiological systems. As age increases, the loss of metabolic homeostasis is revealed by changes in the network's topology that reflect changes in the system-wide interactions that, in turn, expose underlying health stages. Hence, specific structural properties of the network, such as weighted transitivity, can provide topology-based indicators of health that assess the whole state of the system.

Se realizó una prueba del modelo Health Action Process Approach (HAPA) para predecir el ejercicio físico y sus efectos sobre los resultados corporales, cardiometabólicos y psicológicos en una muestra de adultos mexicanos con riesgo cardiometabólico que deseaban adelgazar. Se hicieron medidas al inicio del estudio, en la semana 6 y en la semana 12 después de la intervención de las variables HAPA (autoeficacia, expectativas de resultados, percepción de riesgo, intención, autoeficacia de mantenimiento, planificación de acciones); las variables de resultado como la salud corporal (el peso y la grasa), la salud cardiometabólica (colesterol LDL y triglicéridos), la salud psicológica percibida (calidad de vida y estrés psicológico); el IMC y la relación cintura/altura. Un total de 82 adultos cumplieron los criterios de inclusión: IMC ≥ 25 y/o relación peso/talla ≥ .5 cm, de estos, 50 finalizaron el programa. El modelo probado mediante ecuaciones estructurales no mostró un ajuste adecuado: CFI = .782, GFI = .858, SRMR = .111. Sin embargo, la variable expectativas tuvo un efecto significativo sobre las intenciones y la autoeficacia de la acción sobre la autoeficacia de mantenimiento, representando el 24% y el 17% de la varianza, respectivamente, sin encontrar otra relación. Además, los cambios en el ejercicio tuvieron un efecto positivo en la salud corporal explicando el 11% de la varianza. Se necesitan más estudios para comprender otros predictores cruciales de la actividad física en muestras fuera de los países occidentales, educados, industrializados, ricos y democráticos.