Relationships between Physical Activity Frequency and Self-Perceived Health, Self-Reported Depression, and Depressive Symptoms in Spanish Older Adults with Diabetes: A Cross-Sectional Study

Denche-Zamorano, Ángel; Pérez‐Gómez, Jorge; Barrios-Fernández, Sabina; Oliveira, Rafael; Adsuar, José Carmelo; Brito, João Paulo

doi:10.3390/ijerph20042857

Cited by 6 publications

(2 citation statements)

References 94 publications

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“…La obesidad puede afectar la autoestima y la imagen corporal, lo que puede llevar a la depresión. Esto es ahondado con la resistencia a la insulina y la inflamación crónica que aumentan los síntomas de la diabetes que causa aún más daño emocional (20).…”

Section: Factores De Riesgounclassified

Intervenciones de afrontamiento ante la depresión en pacientes con Diabetes Mellitus Tipo 2

Urrutia Chari,

Tufiño Aguilar

2024

MedicienciasUTA

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Introducción: La diabetes mellitus tipo 2 (DM2) y la depresión son enfermedades crónicas graves que a menudo coexisten. La depresión es casi el doble de frecuente en personas con DM2 que en la población general. Cuando ambas condiciones están presentes, se asocian con un peor control glucémico, menor autocuidado, reducción de la calidad de vida, mayor riesgo de complicaciones y una mayor mortalidad. A pesar de su importancia, un número significativo de pacientes con DM2 y depresión permanecen sin ser tratados o incluso diagnosticados. Existe una falta de estudios y guías de manejo sobre el tratamiento simultáneo de estas dos condiciones. Objetivos: Esta revisión bibliográfica tiene como objetivo analizar las diferentes intervenciones de afrontamiento contra la depresión en pacientes con DM2 con el propósito de tener un panorama completo de las opciones de tratamiento disponibles e identificar las estrategias más efectivas. Además, de identificar los factores que predisponen a los pacientes con DM2 a desarrollar depresión. Metodología: Se realizó una revisión bibliográfica de metaanálisis, ensayos clínicos aleatorizados y revisiones sistemáticas publicados entre 2018 y 2024, obtenidos de bases de datos como PubMed, Google Académico y Scopus. Se identificaron los factores de riesgo, las diferentes intervenciones de afrontamiento contra la depresión, sus definiciones, eficacia y modos de aplicación respaldados por evidencia científica. Se seleccionaron los artículos más relevantes y se clasificó la información más significativa. Principales resultados: Los principales factores de riesgo para desarrollar depresión en pacientes con DM2 incluyen aspectos biológicos (hiperglucemia, daño vascular, complicaciones), conductuales (tratamiento de por vida, obesidad, inactividad física, alteraciones del sueño), socioeconómicos (bajo nivel socioeconómico, gastos en medicación, inestabilidad social, bajo nivel educativo), ambientales y psicológicos. Las intervenciones más efectivas para afrontar la depresión en pacientes con DM2 son la terapia cognitivo-conductual (TCC), la TCC grupal, el ejercicio, tratamiento farmacológico (ISRS) y el tratamiento online. Para mejorar tanto la depresión como el control glucémico, se destacan la farmacoterapia y la combinación de TCC con ejercicio. La selección de la intervención más adecuada debe considerar la gravedad de los síntomas depresivos, las preferencias del paciente, los recursos disponibles, la efectividad y los posibles efectos sobre el control glucémico. Los modelos escalonados brindan una guía útil para esta selección

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Section: Factores De Riesgounclassified

Intervenciones de afrontamiento ante la depresión en pacientes con Diabetes Mellitus Tipo 2

Urrutia Chari,

Tufiño Aguilar

2024

MedicienciasUTA

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“…Several studies have demonstrated that physical inactivity promotes body adiposity [ 3 , 4 , 5 ]. It is well known that the accumulation of body fat, mainly in the abdomen, is strongly associated with the presence of cardiometabolic risks such as high blood pressure, insulin resistance, dyslipidemia, diabetes mellitus, and metabolic syndrome, among others [ 6 , 7 , 8 ], because visceral fat is an active metabolic tissue that modulates numerous adipocytokines associated with non-communicable chronic diseases [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Skinfold Thickness as a Cardiometabolic Risk Predictor in Sedentary and Active Adult Populations

González-Torres,

Anaya-Esparza,

Trigueros del Valle

et al. 2023

JPM

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Studies report that increased body fat can lead to health risks for individuals. However, some methods used for analyzing adiposity did not identify its distribution in the human body because they are typically measured using bioimpedance scales. This study aims to associate the presence of cardiometabolic risk factors in sedentary and active adult populations through anthropometric methods based on skinfold thickness measurements. A cross-sectional study was conducted on 946 adults aged between 18 and 79 years with prior informed consent. Clinical, anthropometric, and biochemical parameters, as well as some cardiometabolic risk factors, were evaluated. Almost half of the population (45.1%; n = 427) is sedentary. A significant association was found between the sum of the skinfolds (bicipital, tricipital, subscapular, and suprailiac) and the cardiometabolic risk factors evaluated, highlighting the cardiovascular risk associated with abdominal obesity, risk of insulin resistance, as well as the development of hyperglycemia, and hypertriglyceridemia. The bicipital fold was thicker (19.67 mm) in the population with a sedentary lifestyle than in the physically active population (18.30 mm). Furthermore, the skinfolds that predict higher metabolic risks were suprailiac and subscapular in sedentary and active populations. Thus, these skinfold measurements could be considered in assessing the adult population for early cardiometabolic risk detection, even in healthy and physically active people.

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Depression screening model for middle-aged and elderly diabetic patients in China

Deng,

Luo,

Wang

et al. 2024

Sci Rep

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Diabetes is a common global disease closely associated with an increased risk of depression. This study analyzed China Health and Retirement Longitudinal Study (CHARLS) data to examine depression in diabetic patients across China. using 29 variables including demographic, behavioral, health conditions, and mental health parameters. The dataset was randomly divided into a 70% training set and a 30% validation set. Predictive factors significantly associated with depression were identified using least absolute shrinkage and selection operator (LASSO) and logistic regression analysis. A nomogram model was constructed using these predictive factors. The model evaluation included the C-index, calibration curves, the Hosmer-Lemeshow test, and DCA. Depression prevalence was 39.1% among diabetic patients. Multifactorial logistic regression identified significant predictors including gender, permanent address, self-perceived health status, presence of lung disease, arthritis, memory disorders, life satisfaction, cognitive function score, ADL score, and social activity. The nomogram model showed high consistency and accuracy, with AUC values of 0.802 for the training set and 0.812 for the validation set. Both sets showed good model fit with Hosmer-Lemeshow P > 0.05. Calibration curves showed significant consistency between the nomogram model and actual observations. ROC and DCA indicated that the nomogram had a good predictive performance. The nomogram developed in this study effectively assesses depression risk in diabetic patients, helping clinicians identify high-risk individuals. This tool could potentially improve patient outcomes.

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Relationships between Physical Activity Frequency and Self-Perceived Health, Self-Reported Depression, and Depressive Symptoms in Spanish Older Adults with Diabetes: A Cross-Sectional Study

Cited by 6 publications

References 94 publications

Intervenciones de afrontamiento ante la depresión en pacientes con Diabetes Mellitus Tipo 2

Intervenciones de afrontamiento ante la depresión en pacientes con Diabetes Mellitus Tipo 2

Skinfold Thickness as a Cardiometabolic Risk Predictor in Sedentary and Active Adult Populations

Depression screening model for middle-aged and elderly diabetic patients in China

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