RESUMEN
BACKGROUND: Frailty is a highly prevalent condition in old age leading to vulnerability and greater risk of adverse health outcomes and disability. Detecting and tackling frailty at an early stage can prevent disability. The purpose of this study is to evaluate the effectiveness of a multifactorial intervention program to modify frailty parameters, muscle strength, and physical and cognitive performance in people aged 65 years or more. It also assesses changes from baseline in falls, hospitalizations, nutritional risk, disability, institutionalization, and home-care. METHODS/DESIGN: The current study is a randomised single-blind, parallel-group clinical trial, with a one and a half year follow-up, conducted in eight Primary Health Care Centres located in the city of Barcelona. Inclusion criteria are to be aged 65 years or older with positive frailty screening, timed get-up-and-go test between 10 to 30 seconds, and Cognition Mini-Exam (MEC-35) of Lobo greater than or equal to 18. A total of 352 patients have been equally divided into two groups: intervention and control. Sample size calculated to detect a 0.5 unit difference in the Short Physical Performance Battery (Common SD: 1.42, 20% lost to follow-up). In the intervention group three different actions on frailty dimensions: rehabilitative therapy plus intake of hyperproteic nutritional shakes, memory workshop, and medication review are applied to sets of 16 patients. Participants in both intervention and control groups receive recommendations on nutrition, healthy lifestyles, and home risks.Evaluations are blinded and conducted at 0, 3, and 18 months. Intention to treat analyses will be performed. Multivariate analysis will be carried out to assess time changes of dependent variables. DISCUSSION: It is expected that this study will provide evidence of the effectiveness of a multidisciplinary intervention on delaying the progression from frailty to disability in the elderly. It will help improve the individual's quality of life and also reduce the rates of falls, hospital admissions, and institutionalizations, thus making the health care system more efficient. This preventive intervention can be adapted to diverse settings and be routinely included in Primary Care Centres as a Preventive Health Programme. TRIAL REGISTRATION: ClinicalTrials.gov PRS: NCT01969526. Date of registration: 10/21/2013.
Asunto(s)
Accidentes por Caídas/prevención & control , Cognición/fisiología , Personas con Discapacidad/rehabilitación , Terapia por Ejercicio/métodos , Anciano Frágil , Fuerza Muscular/fisiología , Atención Primaria de Salud/métodos , Anciano , Femenino , Estudios de Seguimiento , Humanos , Masculino , Pronóstico , Calidad de Vida , Estudios Retrospectivos , Método Simple Ciego , Factores de TiempoRESUMEN
Introducción y objetivos: Algunas medidas antropométricas muestran mayor capacidad que otras para discriminar la presencia de factores de riesgo cardiovascular. Este trabajo estima la magnitud de la asociación de diversos indicadores antropométricos de obesidad con hipertensión, dislipemia y prediabetes (glucemia basal o glucohemoglobina alteradas). Métodos: Análisis transversal de la información recogida en 2.022 sujetos del estudio PREDAPS (etapa basal). Se definió obesidad general como índice de masa corporal ≥ 30 kg/m2 y obesidad abdominal con 2 criterios: a) perímetro de cintura (PC) ≥ 102 cm en varones/PC ≥ 88 cm en mujeres, y b) índice cintura/estatura (ICE) ≥ 0,55. La magnitud de la asociación se estimó mediante regresión logística. Resultados: La hipertensión arterial mostró la asociación más alta con la obesidad general en mujeres (OR = 3,01; IC95%, 2,24-4,04) y con la obesidad abdominal según el criterio del ICE en varones (OR = 3,65; IC95%, 2,66-5,01). La hipertrigliceridemia y los valores bajos de colesterol unido a lipoproteínas de alta densidad mostraron la asociación más alta con obesidad abdominal según el criterio del ICE en mujeres (OR = 2,49; IC95%, 1,68-3,67 y OR = 2,70; IC95%, 1,89-3,86) y la obesidad general en varones (OR = 2,06; IC95%, 1,56-2,73 y OR = 1,68; IC95%, 1,21-2,33). La prediabetes mostró la asociación más alta con obesidad abdominal según el criterio del ICE en mujeres (OR = 2,48; IC95%, 1,85-3,33) y con obesidad abdominal según el criterio del PC en varones (OR = 2,33; IC95%, 1,75-3,08). Conclusiones: Los indicadores de obesidad abdominal mostraron la mayor asociación con la presencia de prediabetes. La relación de los indicadores antropométricos con hipertensión y con dislipemia mostró resultados heterogéneos (AU)
Introduction and objectives: Some anthropometric measurements show a greater capacity than others to identify the presence of cardiovascular risk factors. This study estimated the magnitude of the association of different anthropometric indicators of obesity with hypertension, dyslipidemia, and prediabetes (altered fasting plasma glucose and/or glycosylated hemoglobin). Methods: Cross-sectional analysis of information collected from 2022 participants in the PREDAPS study (baseline phase). General obesity was defined as body mass index ≥ 30 kg/m2 and abdominal obesity was defined with 2 criteria: a) waist circumference (WC) ≥ 102 cm in men/WC ≥ 88 cm in women, and b) waist-height ratio (WHtR) ≥ 0.55. The magnitude of the association was estimated by logistic regression. Results: Hypertension showed the strongest association with general obesity in women (OR, 3.01; 95%CI, 2.24-4.04) and with abdominal obesity based on the WHtR criterion in men (OR, 3.65; 95%CI, 2.66-5.01). Hypertriglyceridemia and low levels of high-density lipoprotein cholesterol showed the strongest association with abdominal obesity based on the WHtR criterion in women (OR, 2.49; 95%CI, 1.68-3.67 and OR, 2.70; 95%CI, 1.89-3.86) and with general obesity in men (OR, 2.06; 95%CI, 1.56-2.73 and OR, 1.68; 95%CI, 1.21-2.33). Prediabetes showed the strongest association with abdominal obesity based on the WHtR criterion in women (OR, 2.48; 95%CI, 1.85-3.33) and with abdominal obesity based on the WC criterion in men (OR, 2.33; 95%CI, 1.75-3.08). Conclusions: Abdominal obesity indicators showed the strongest association with the presence of prediabetes. The association of anthropometric indicators with hypertension and dyslipidemia showed heterogeneous results (AU)