Browsing by Subject "Cohort"

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    From improved sleep regularity to reduced sleep complaints and mental health conditions: a population-based interventional study using a smartphone-based virtual agent
    (Oxford University Press, 2023-09) Coelho, Julien; Pecune, Florian; Levavasseur, Yannick; Sevin, Etienne de; D'incau, Emmanuel; Patricia Sagaspe, Patricia; Sánchez Ortuño, María Montserrat; Micoulaud Franchi, Jean Arthur; Philip, Pierre; Enfermería
    Study Objectives To explore the effect of sleep regularity on sleep complaints and mental health conditions (i.e. insomnia, fatigue, anxiety, and depressive symptoms) in a population-based interventional study using a smartphone-based virtual agent. Methods A populational cohort based on the Kanopée application, which provided interactions with a virtual companion to collect data on sleep and make personalized recommendations to improve sleep over 17 days. A pre-intervention sleep diary and interview were used for cross-sectional analysis (n = 2142), and a post-intervention sleep diary and interview were used for longitudinal analysis (n = 732). The intra-individual mean (IIM) and standard deviation (ISD) of total sleep time (TST) were calculated to measure sleep quantity and sleep regularity. Results The mean age at baseline was 49 years, 65% were female, 72% reported insomnia, 58% fatigue, 36% anxiety, and 17% depressive symptoms. Before the intervention, irregular and short sleep was associated with a higher likelihood of insomnia (Relative risk [RR] = 1.26 [1.21–1.30] for irregular TST and RR = 1.19 [1.15–1.23] for short TST), fatigue, anxiety, and depressive symptoms. After the intervention, the IIM of the TST increased while the ISD of the TST and sleep complaints and mental health conditions decreased. More regular TST was associated with reduced insomnia and depressive symptoms (RR = 1.33 [1.10–1.52] and RR = 1.55 [1.13–1.98], respectively). Conclusions Our results reveal a longitudinal association between sleep regularity and sleep complaints and mental health conditions. Policymakers, health professionals, and the general population should be aware that, beyond its positive effect on sleep health, regular sleep could promote mental health.
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    Identification of predictors of sarcopenia in older adults using machine learning: English Longitudinal Study of Ageing
    (MDPI, 2024-11-12) Pavón Pulido, Nieves; Domínguez, Ligia; Blasco García, Jesús Damián; Veronese, Nicola; Lucas Ochoa, Ana María; Fernández Villalba, Emiliano; González Cuello, Ana María; Barbagallo, Mario; Herrero Ezquerro, María Trinidad; GOING FWD Investigators; Medicina Interna; Facultades de la UMU::Facultad de Medicina
    Background: After its introduction in the ICD-10-CM in 2016, sarcopenia is a condition widely considered to be a medical disease with important consequences for the elderly. Considering its high prevalence in older adults and its detrimental effects on health, it is essential to identify its risk factors to inform targeted interventions. Methods: Taking data from wave 2 of the ELSA, using ML-based methods, this study investigates which factors are significantly associated with sarcopenia. The Minimum Redundancy Maximum Relevance algorithm has been used to allow for an optimal set of features that could predict the dependent variable. Such a feature is the input of a ML-based prediction model, trained and validated to predict the risk of developing or not developing a disease. Results: The presented methods are suitable to identify the risk of acquired sarcopenia. Age and other relevant features related with dementia and musculoskeletal conditions agree with previous knowledge about sarcopenia. The present classifier has an excellent performance since the “true positive rate” is 0.81 and the low “false positive rate” is 0.26. Conclusions: There is a high prevalence of sarcopenia in elderly people, with age and the presence of dementia and musculoskeletal conditions being strong predictors. The new proposed approach paves the path to test the prediction of the incidence of sarcopenia in older adults.202
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    La diversificación de las generaciones femeninas en España, siglos XX y XXI
    (Universidad de Murcia, Servicio de Publicaciones, 2025) Montfort Chipell, Anna; Domingo i Valls, Andreu; Bayona i Carrasco, Jordi; Sin departamento asociado
    Esta investigación tiene como objetivos principales examinar el crecimiento y la diversificación por procedencia de las generaciones femeninas en España durante los siglos XX y XXI a nivel provincial, establecer pautas territoriales comparativas entre generaciones de mujeres según su origen, y explorar la diversificación intra e intergernacional entre migrantes y autóctonas. Se han utilizado datos de los Censos de Población y Viviendas (1930-2021), centrando el análisis en cohortes nacidas entre 1926 y 2005 agrupadas por décadas, las cuales fueron afectadas por las migraciones internas del siglo XX y los dos booms migratorios del siglo XXI. Los resultados muestran que la migración interna del siglo XX y la internacional del siglo XXI han alterado el número y perfil de las generaciones femeninas en España. Sin embargo, la diversificación a nivel provincial en cuanto a volumen e impacto migratorio sugiere que estos complejos patrones regionales superan la dicotomía tradicional entre emigrantes e inmigrantes. Además, las diferencias en nivel educativo, estado civil y ocupación entre mujeres nativas e inmigrantes ofrecen una perspectiva sobre cómo estas migraciones contribuyen a la diversificación intrageneracional en la reproducción social de las generaciones.