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For: Balboa-Castillo T, León-Muñoz LM, Graciani A, Rodríguez-Artalejo F, Guallar-Castillón P. Longitudinal association of physical activity and sedentary behavior during leisure time with health-related quality of life in community-dwelling older adults. Health Qual Life Outcomes 2011;9:47. [PMID: 21708011 PMCID: PMC3142200 DOI: 10.1186/1477-7525-9-47] [Citation(s) in RCA: 200] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2011] [Accepted: 06/27/2011] [Indexed: 12/18/2022] Open

For:	Balboa-Castillo T, León-Muñoz LM, Graciani A, Rodríguez-Artalejo F, Guallar-Castillón P. Longitudinal association of physical activity and sedentary behavior during leisure time with health-related quality of life in community-dwelling older adults. Health Qual Life Outcomes 2011;9:47. [PMID: 21708011 PMCID: PMC3142200 DOI: 10.1186/1477-7525-9-47] [Citation(s) in RCA: 200] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2011] [Accepted: 06/27/2011] [Indexed: 12/18/2022] Open

Number

Cited by Other Article(s)

Marcos-Delgado A, Martín-Sánchez V, Martínez-González MÁ, Corella D, Salas-Salvadó J, Schröder H, Martínez A, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Santos-Lozano JM, Álvarez-Pérez J, Bueno-Cavanillas A, Cano-Ibáñez N, Amezcua-Prieto C, Hernández-Segura N, Tur JA, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Vázquez C, Daimiel L, Ros E, Toledo E, Garcidueñas-Fimbres TE, Viaplana J, Asensio EM, Zomeño MD, Garcia-Rios A, Oncina-Cánovas A, Barón-López FJ, Pérez-Farinos N, Sayon-Orea C, Galmés-Panadés AM, Casas R, Tojal-Sierra L, Gómez-Pérez AM, Buil-Corsiales P, García-Gavilán JF, Ortega-Azorín C, Castañer O, Peña-Orihuela PJ, González-Palacios S, Babio N, Fitó M, Nieto J. Objectively Measured Sleep Duration and Health-Related Quality of Life in Older Adults with Metabolic Syndrome: A One-Year Longitudinal Analysis of the PREDIMED-Plus Cohort. Nutrients 2024;16:2631. [PMID: 39203769 PMCID: PMC11357069 DOI: 10.3390/nu16162631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/03/2024] Open

Affiliation(s)

Alba Marcos-Delgado Faculty of Health Sciences, Department of Biomedical Sciences, Area of Preventive Medicine and Public Health, Universidad de León, 24007 León, Spain; (V.M.-S.); (N.H.-S.) The Research Group in Gene-Environment and Health Interactions, Institute of Biomedicine (IBIOMED), Universidad de León, 24007 León, Spain CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.)
Vicente Martín-Sánchez Faculty of Health Sciences, Department of Biomedical Sciences, Area of Preventive Medicine and Public Health, Universidad de León, 24007 León, Spain; (V.M.-S.); (N.H.-S.) The Research Group in Gene-Environment and Health Interactions, Institute of Biomedicine (IBIOMED), Universidad de León, 24007 León, Spain CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.)
Miguel Ángel Martínez-González Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Preventive Medicine and Public Health, Navarra Institute for Health Research (IdiSNA), University of Navarra, 31009 Pamplona, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02124, USA
Dolores Corella CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine, University of Valencia, 46008 Valencia, Spain
Jordi Salas-Salvadó Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unitat de Nutrició, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43206 Reus, Spain Institut d’Investigació Sanitària Pere Virgili (IISPV), 43204 Reus, Spain
Helmut Schröder Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.F.)
Alfredo Martínez Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, 31009 Pamplona, Spain Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, 28222 Madrid, Spain;
Ángel M. Alonso-Gómez Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01004 Vitoria-Gasteiz, Spain
Julia Wärnberg Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain; (A.O.-C.); (F.J.B.-L.); (N.P.-F.); (S.G.-P.)
Jesús Vioque CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), 03202 Alicante, Spain
Dora Romaguera Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Health Research Institute of the Balearic Islands (IdISBa), 07012 Palma de Mallorca, Spain
José López-Miranda Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 30110 Cordoba, Spain
Ramon Estruch Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, Institut de Recerca en Nutrició y Seguretat Alimentaria (INSA-UB), University of Barcelona, 08001 Barcelona, Spain
Francisco J. Tinahones Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Virgen de la Victoria Hospital, Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain
José M. Santos-Lozano Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Research Unit, Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, 41006 Sevilla, Spain
Jacqueline Álvarez-Pérez Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, 35010 Las Palmas de Gran Canaria, Spain
Aurora Bueno-Cavanillas CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine and Public Health, University of Granada, 18071 Granada, Spain Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), 18071 Granada, Spain
Naomi Cano-Ibáñez CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine and Public Health, University of Granada, 18071 Granada, Spain Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), 18071 Granada, Spain
Carmen Amezcua-Prieto CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine and Public Health, University of Granada, 18071 Granada, Spain
Natalia Hernández-Segura Faculty of Health Sciences, Department of Biomedical Sciences, Area of Preventive Medicine and Public Health, Universidad de León, 24007 León, Spain; (V.M.-S.); (N.H.-S.) The Research Group in Gene-Environment and Health Interactions, Institute of Biomedicine (IBIOMED), Universidad de León, 24007 León, Spain
Josep A. Tur CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, 07012 Palma de Mallorca, Spain
Xavier Pintó Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge-IDIBELL, Hospitalet de Llobregat, 08901 Barcelona, Spain
Miguel Delgado-Rodríguez Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, 28222 Madrid, Spain; Division of Preventive Medicine, Faculty of Medicine, University of Jaén, 23003 Jaén, Spain
Pilar Matía-Martín Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain;
Josep Vidal CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28222 Madrid, Spain; (J.V.); (J.V.) Department of Endocrinology, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08001 Barcelona, Spain
Clotilde Vázquez Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, 28049 Madrid, Spain
Lidia Daimiel Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, 28222 Madrid, Spain Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Spain
Emili Ros Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, 08001 Barcelona, Spain
Estefanía Toledo Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Preventive Medicine and Public Health, Navarra Institute for Health Research (IdiSNA), University of Navarra, 31009 Pamplona, Spain;
Tany E. Garcidueñas-Fimbres Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unitat de Nutrició, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43206 Reus, Spain Institut d’Investigació Sanitària Pere Virgili (IISPV), 43204 Reus, Spain
Judith Viaplana CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28222 Madrid, Spain; (J.V.); (J.V.) Department of Endocrinology, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08001 Barcelona, Spain
Eva M. Asensio CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine, University of Valencia, 46008 Valencia, Spain
María D. Zomeño Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.F.)
Antonio Garcia-Rios Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 30110 Cordoba, Spain
Alejandro Oncina-Cánovas EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain; (A.O.-C.); (F.J.B.-L.); (N.P.-F.); (S.G.-P.) Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), 03202 Alicante, Spain
Francisco Javier Barón-López EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain; (A.O.-C.); (F.J.B.-L.); (N.P.-F.); (S.G.-P.)
Napoleón Pérez-Farinos EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain; (A.O.-C.); (F.J.B.-L.); (N.P.-F.); (S.G.-P.)
Carmen Sayon-Orea Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Preventive Medicine and Public Health, Navarra Institute for Health Research (IdiSNA), University of Navarra, 31009 Pamplona, Spain;
Aina M. Galmés-Panadés Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Health Research Institute of the Balearic Islands (IdISBa), 07012 Palma de Mallorca, Spain Physical Activity and Sport Sciences Research Group (GICAFE), Institute for Educational Research and Innovation (IRIE), University of the Balearic Island, 07122 Palma, Spain
Rosa Casas Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, Institut de Recerca en Nutrició y Seguretat Alimentaria (INSA-UB), University of Barcelona, 08001 Barcelona, Spain
Lucas Tojal-Sierra Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01004 Vitoria-Gasteiz, Spain
Ana M. Gómez-Pérez Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Virgen de la Victoria Hospital, Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain
Pilar Buil-Corsiales Department of Preventive Medicine and Public Health, Navarra Institute for Health Research (IdiSNA), University of Navarra, 31009 Pamplona, Spain;
Jesús F. García-Gavilán Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unitat de Nutrició, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43206 Reus, Spain Institut d’Investigació Sanitària Pere Virgili (IISPV), 43204 Reus, Spain
Carolina Ortega-Azorín CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28222 Madrid, Spain; (D.C.); (J.V.); (A.B.-C.); (N.C.-I.); (C.A.-P.); (J.A.T.); (E.M.A.); (C.O.-A.) Department of Preventive Medicine, University of Valencia, 46008 Valencia, Spain
Olga Castañer Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.F.)
Patricia J. Peña-Orihuela Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 30110 Cordoba, Spain
Sandra González-Palacios EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, 29010 Málaga, Spain; (A.O.-C.); (F.J.B.-L.); (N.P.-F.); (S.G.-P.) Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), 03202 Alicante, Spain
Nancy Babio Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28222 Madrid, Spain; (M.Á.M.-G.); (J.S.-S.); (H.S.); (A.M.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (F.J.T.); (J.M.S.-L.); (J.Á.-P.); (X.P.); (C.V.); (L.D.); (E.R.); (E.T.); (T.E.G.-F.); (M.D.Z.); (A.G.-R.); (C.S.-O.); (A.M.G.-P.); (R.C.); (L.T.-S.); (A.M.G.-P.); (J.F.G.-G.); (P.J.P.-O.); (N.B.) Unitat de Nutrició, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43206 Reus, Spain Institut d’Investigació Sanitària Pere Virgili (IISPV), 43204 Reus, Spain
Montse Fitó Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.F.)
Javier Nieto College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97330, USA;

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Wu M, Yang D, Tian Y. Enjoying the golden years: social participation and life satisfaction among Chinese older adults. Front Public Health 2024;12:1377869. [PMID: 39145156 PMCID: PMC11322126 DOI: 10.3389/fpubh.2024.1377869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 07/16/2024] [Indexed: 08/16/2024] Open

Wang LT. Effects of semi-immersive virtual reality exercise on the quality of life of community-dwelling older adults: Three-month follow-up of a randomized controlled trial. Digit Health 2024;10:20552076241237391. [PMID: 38449682 PMCID: PMC10916470 DOI: 10.1177/20552076241237391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 02/19/2024] [Indexed: 03/08/2024] Open

Meghani NAA, Hudson J, Stratton G, Mullins J. Older adults' perspectives on physical activity and sedentary behaviour within their home using socio-ecological model. PLoS One 2023;18:e0294715. [PMID: 37983222 PMCID: PMC10659182 DOI: 10.1371/journal.pone.0294715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 11/07/2023] [Indexed: 11/22/2023] Open

Liu W, Zheng R, Zhang Y, Zhang W. Differences in the influence of daily behavior on health among older adults in urban and rural areas: evidence from China. Front Public Health 2023;11:1259204. [PMID: 37869199 PMCID: PMC10587611 DOI: 10.3389/fpubh.2023.1259204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 09/19/2023] [Indexed: 10/24/2023] Open

Abstract

Background

As the population of older adult in China keeps growing, the degree of aging is becoming increasingly serious and the health of older adults is a growing concern. Comparing the personal characteristics and health levels of urban and rural older adults and determining the relationship between these factors are of great significance in maintaining their health. In addition, exploring how these relationships differ between urban and rural areas is important.

Method

This study conducted a literature review to examine the impact of various factors on the physical and mental health of older adults in urban and rural areas in China. Moreover, based on cross-sectional data from the 2017 Chinese General Social Survey (CGSS), urban-rural differences in the factors' degree of influence on the perceived health of older adults were studied using multiple logistic regression.

Results

Regular physical exercise had a powerful protective effect on urban older adults' physical and mental health, whereas regular participation in social activities had a positive impact on rural older adults' health. Low income, low educational level, low social trust, lack of a partner, and having more than one child negatively affected the physical health of rural older people. Low socioeconomic status had a negative impact on rural people's health both in mind and body. Overall, the rural adults' health status was found to be relatively low and deserves more attention.

Conclusion

This study demonstrated that older people's physical and mental health levels can be significantly affected by the frequency of daily activities and individual and family characteristics. Furthermore, urban-rural differences were observed. These findings could provide feasible suggestions for governments, communities, and older adults' family members to help alleviate health inequality.

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Zaborova V, Zolnikova O, Dzhakhaya N, Prokhorova S, Izotov A, Butkova T, Pustovoyt V, Yurku K, Shestakov D, Zaytseva T, Shafaei H. Associations between Physical Activity and Kyphosis and Lumbar Lordosis Abnormalities, Pain, and Quality of Life in Healthy Older Adults: A Cross-Sectional Study. Healthcare (Basel) 2023;11:2651. [PMID: 37830688 PMCID: PMC10572639 DOI: 10.3390/healthcare11192651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 09/01/2023] [Accepted: 09/14/2023] [Indexed: 10/14/2023] Open

Affiliation(s)

Victoria Zaborova Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (V.Z.); (O.Z.); (N.D.); (S.P.)
Oxana Zolnikova Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (V.Z.); (O.Z.); (N.D.); (S.P.)
Natiya Dzhakhaya Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (V.Z.); (O.Z.); (N.D.); (S.P.)
Svetlana Prokhorova Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia; (V.Z.); (O.Z.); (N.D.); (S.P.)
Alexander Izotov Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (A.I.); (T.B.)
Tatyana Butkova Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (A.I.); (T.B.)
Vasiliy Pustovoyt Laboratory of Big Data and Precision Restorative Medicine, State Research Center-Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 119435 Moscow, Russia; (V.P.); (K.Y.)
Ksenia Yurku Laboratory of Big Data and Precision Restorative Medicine, State Research Center-Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, 119435 Moscow, Russia; (V.P.); (K.Y.)
Dmitry Shestakov Moscow Clinical Scientific Center Named after A. S. Loginov, 111123 Moscow, Russia;
Tatyana Zaytseva Institute of Public Health, Sechenov First Moscow State Medical University, 119991 Moscow, Russia;
Hassan Shafaei Department of Physical Rehabilitation, Massage and Health-Improving Physical Culture Named after I. M. Sarkizov-Serazini RSUFKSMiT, 105122 Moscow, Russia

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Hudgins BL, Hevel DJ, Maher JP. Screen-based and non-screen-based sedentary behaviors are differentially associated with affective states in older adults. PSYCHOLOGY OF SPORT AND EXERCISE 2023;67:102433. [PMID: 37665886 DOI: 10.1016/j.psychsport.2023.102433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/27/2023] [Accepted: 03/28/2023] [Indexed: 09/06/2023]

Yerrakalva D, Hajna S, Suhrcke M, Wijndaele K, Westgate K, Khaw KT, Wareham N, Brage S, Griffin S. Associations between change in physical activity and sedentary time and health-related quality of life in older english adults: the EPIC-Norfolk cohort study. Health Qual Life Outcomes 2023;21:60. [PMID: 37349799 PMCID: PMC10288723 DOI: 10.1186/s12955-023-02137-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 05/23/2023] [Indexed: 06/24/2023] Open

Abstract

BACKGROUND

No previous studies have examined the associations between changes in objectively-measured physical behaviours with follow-up QoL in older adults. Based on cross-sectional evidence, it is biologically plausible that such associations exist. If so, this bolsters the case for the commissioning of activity interventions and for including QoL as an outcome in trials of such interventions.

METHODS

We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers at baseline (2006-2011) and follow-up (2012-2016) and health-related quality-of-life (QoL) using EQ-5D questionnaires at follow-up in 1433 participants (≥ 60 years) of the EPIC (European Prospective Investigation into Cancer)-Norfolk study. The EQ-5D summary score was used, with 0 as the worst to 1 as best perceived quality-of-life. We evaluated the prospective associations of baseline physical behaviours with follow-up QoL, and of changes in behaviours with follow-up QoL using multi-level regression.

RESULTS

On average, MVPA decreased by 4.0 min/day/year (SD 8.3) for men and 4.0 min/day/year for women (SD 12.0) between baseline and follow-up. Total sedentary time increased by an average 5.5 min/day/yr (SD 16.0) for men and 6.4 min/day/yr (SD 15.0) for women between baseline and follow-up. Mean (SD) follow-up time was 5.8 (1.8) years. We found that higher baseline MVPA and lower sedentary time was associated with higher subsequent QoL (e.g. 1 h/day greater baseline MVPA was associated with 0.02 higher EQ-5D score, 95% CI 0.06, 0.36). More pronounced declines in activity were associated with worse Hr-QoL (0.005 (95% CI 0.003, 0.008) lower EQ-5D per min/day/yr decrease in MVPA). Increases in sedentary behaviours were also associated with poorer QoL (0.002 lower EQ-5D, 95% CI -0.003, -0.0007 per hour/day/yr increase in total sedentary time).

CONCLUSIONS

Promotion of physical activity and limiting sedentary time among older adults may improve quality-of-life, and therefore this relationship ought to be included in future cost effectiveness analyses so that greater commissioning of activity interventions can be considered.

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Psarrou A, Adamakidou T, Apostolara P, Koreli A, Drakopoulou M, Plakas S, Mastrogiannis D, Mantoudi A, Parissopoulos S, Zartaloudi A, Mantzorou M. Associations between Physical Activity and Health-Related Quality of Life among Community-Dwelling Older Adults: A Cross-Sectional Study in Urban Greece. Geriatrics (Basel) 2023;8:61. [PMID: 37367093 DOI: 10.3390/geriatrics8030061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/28/2023] Open

Affiliation(s)

Anna Psarrou MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Theodoula Adamakidou MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Paraskevi Apostolara MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Alexandra Koreli MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Marianna Drakopoulou MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Sotirios Plakas MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Dimos Mastrogiannis MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Alexandra Mantoudi MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Stelios Parissopoulos MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Afroditi Zartaloudi MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece
Marianna Mantzorou MSc Program in Community and Public Health Nursing, Nursing Department, School of Health and Care Sciences, University of West Attica, 12243 Athens, Greece

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Gavilán-Carrera B, Delgado-Fernández M, Álvarez-Gallardo IC, Acosta-Manzano P, Borges-Cosic M, Estévez-López F, Soriano-Maldonado A, Carbonell-Baeza A, Aparicio VA, Segura-Jiménez V. Longitudinal association of sedentary time and physical activity with pain and quality of life in fibromyalgia. Scand J Med Sci Sports 2023;33:292-306. [PMID: 36326665 DOI: 10.1111/sms.14258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 10/21/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022]

Abstract

OBJECTIVE

To analyze changes over time and the predictive value of baseline and changes of sedentary time (ST) and physical activity (PA) on pain, disease impact, and health-related quality of life (HRQoL) at 2- and 5-year follow-up in women with fibromyalgia.

METHODS

This is a longitudinal and exploratory study with three time points. A total of 427 women with fibromyalgia (51.4 ± 7.6 years) were followed after 2 (n = 172) and 5 years (n = 185). ST and PA (light and moderate-to-vigorous [MVPA]) were assessed using triaxial accelerometers. Pain, disease impact, and HRQoL were measured using: pressure pain threshold, the pain subscale of the revised fibromyalgia impact questionnaire (FIQR), the bodily pain subscale of the 36-item short-form health survey (SF-36), a visual analog scale (VAS), the FIQR, and the SF-36 physical and mental components.

RESULTS

Over 5 years, pressure pain threshold, ST, light PA, and MVPA variables were worsened, while FIQR and SF-36 variables were improved (Cohen's d < 0.1-0.3). Baseline ST or light PA were not associated with future outcomes, whereas greater MVPA at baseline was associated with better SF-36 bodily pain at 5-year follow-up (β = 0.13). Reducing ST and increasing light PA were associated with better bodily pain (β = -0.16 and 0.17, respectively) and SF-36 physical component (β = -0.20 and 0.17, respectively) at 5-year follow-up. Increasing MVPA was associated with less pain (pressure pain threshold, VAS, and FIQR-pain) and better SF-36 physical component at 2- and 5-year follow-up (β's from -0.20 to 0.21).

CONCLUSIONS

Objectively measured variables slightly worsened over years, while for self-reported outcomes there was a trend for improvement. Reductions in ST and increases in light PA and MVPA were associated with better HRQoL at 5-year follow-up, and increases in MVPA were additionally associated with better pain and HRQoL at 2-year follow-up.

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Affiliation(s)

Blanca Gavilán-Carrera Departamento de Medicina Interna, Hospital Universitario Virgen de las Nieves, Granada, Spain.,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain.,PA-HELP "Physical Activity for Health Promotion, CTS-1018" research group. Department of Physical Education and Sports, Faculty of Sports Science, University of Granada, Granada, Spain.,Sport and Health University Research Institute (IMUDS), University of Granada, Granada, Spain
Manuel Delgado-Fernández PA-HELP "Physical Activity for Health Promotion, CTS-1018" research group. Department of Physical Education and Sports, Faculty of Sports Science, University of Granada, Granada, Spain.,Sport and Health University Research Institute (IMUDS), University of Granada, Granada, Spain
Inmaculada C Álvarez-Gallardo GALENO research group, Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Cadiz, Spain.,Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Cadiz, Spain
Pedro Acosta-Manzano PA-HELP "Physical Activity for Health Promotion, CTS-1018" research group. Department of Physical Education and Sports, Faculty of Sports Science, University of Granada, Granada, Spain.,Sport and Health University Research Institute (IMUDS), University of Granada, Granada, Spain.,Institute of Human Movement Science, Sport and Health, University of Graz, Graz, Austria
Milkana Borges-Cosic GALENO research group, Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Cadiz, Spain.,Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Puerto Real, Spain
Fernando Estévez-López Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Massachusetts, Boston, USA
Alberto Soriano-Maldonado Department of Education, Faculty of Education Sciences, University of Almería, Almería, Spain.,Sport Research Group (Cts-1024), Cernep Research Center, University of Almería, Almería, Spain
Ana Carbonell-Baeza Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Cadiz, Spain.,MOVE-IT Research Group and Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Puerto Real, Spain
Virginia A Aparicio Sport and Health University Research Institute (IMUDS), University of Granada, Granada, Spain.,Department of Physiology, School of Pharmacy, University of Granada, Granada, Spain.,Institute of Nutrition and Food Technology (INYTA), Biomedical Research Centre (CIBM), University of Granada, Granada, Spain
Víctor Segura-Jiménez Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain.,GALENO research group, Department of Physical Education, Faculty of Education Sciences, University of Cádiz, Cadiz, Spain.,Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Cadiz, Spain.,UGC Neurotraumatología y Rehabilitación, Hospital Universitario Virgen de las Nieves, Granada, Spain

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Chang KC, Chen HS, Wu CS, Chang CK, Hwang JJ, Huang SH, Chen YM, Cheng BW, Weng MH, Hsu CC, Huang WL. Evaluation of the optimal cutoff number of types of social participation activities in older people. J Formos Med Assoc 2023:S0929-6646(23)00036-0. [PMID: 36788044 DOI: 10.1016/j.jfma.2023.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 12/23/2022] [Accepted: 01/30/2023] [Indexed: 02/16/2023] Open

Hakimi S, Kaur S, Ross-White A, Martin LJ, Rosenberg MW. A systematic review examining associations between physical activity, sedentary behaviour, and sleep duration with quality of life in older adults aged 65 years and above. Appl Physiol Nutr Metab 2023;48:97-162. [PMID: 36302262 DOI: 10.1139/apnm-2022-0298] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]

Mei N, Chang Y. EFFECT OF AEROBIC EXERCISE ON PHYSICAL FUNCTION INDICES IN THE ELDERLY. REV BRAS MED ESPORTE 2023. [DOI: 10.1590/1517-8692202329012022_0236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open

Scarabottolo CC, Tebar WR, Araújo Guerra PH, Martins CMDL, Ferrari G, Beretta VS, Christofaro DGD. Association between Different Domains of Sedentary Behavior and Health-Related Quality of Life in Adults: A Longitudinal Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022;19:16389. [PMID: 36554270 PMCID: PMC9778904 DOI: 10.3390/ijerph192416389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]

Television-viewing time and bodily pain in Australian adults with and without type 2 diabetes: 12-year prospective relationships. BMC Public Health 2022;22:2218. [PMID: 36447213 PMCID: PMC9706940 DOI: 10.1186/s12889-022-14566-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022] Open

Abstract

BACKGROUND

Bodily pain is a common presentation in several chronic diseases, yet the influence of sedentary behaviour, common in ageing adults, is unclear. Television-viewing (TV) time is a ubiquitous leisure-time sedentary behaviour, with a potential contribution to the development of bodily pain. We examined bodily pain trajectories and the longitudinal relationships of TV time with the bodily pain severity; and further, the potential moderation of the relationships by type 2 diabetes (T2D) status.

METHOD

Data were from 4099 participants (aged 35 to 65 years at baseline) in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), who took part in the follow-ups at 5 years, 12 years, or both. Bodily pain (from SF36 questionnaire: a 0 to 100 scale, where lower scores indicate more-severe pain), TV time, and T2D status [normal glucose metabolism (NGM), prediabetes, and T2D] were assessed at all three time points. Multilevel growth curve modelling used age (centred at 50 years) as the time metric, adjusting for potential confounders, including physical activity and waist circumference.

RESULTS

Mean TV time increased, and bodily pain worsened (i.e., mean bodily pain score decreased) across the three time points. Those with T2D had higher TV time and more-severe bodily pain than those without T2D at all time points. In a fully adjusted model, the mean bodily pain score for those aged 50 years at baseline was 76.9(SE: 2.2) and worsened (i.e., bodily pain score decreased) significantly by 0.3(SE: 0.03) units every additional year (p <0.001). Those with initially more-severe pain had a higher rate of increase in pain severity. At any given time point, a one-hour increase in daily TV time was significantly associated with an increase in pain severity [bodily pain score decreased by 0.69 (SE: 0.17) units each additional hour; p <0.001], accounting for the growth factor (age) and confounders' effects. The association was more-pronounced in those with T2D than in those without (prediabetes or NGM), with the effect of T2D on bodily pain severity becoming more apparent as TV time increases, significantly so when TV time increased above 2.5 hours per day.

CONCLUSION

Bodily pain severity increased with age in middle-aged and older Australian adults over a 12-year period, and increments in TV time predicted increased bodily pain severity at any given period, which was more pronounced in those with T2D. While increasing physical activity is a mainstay of the prevention and management of chronic health problems, these new findings highlight the potential of reducing sedentary behaviours in this context.

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Nascimento MDM, Gouveia ÉR, Gouveia BR, Marques A, França C, Freitas DL, Campos P, Ihle A. Exploring Mediation Effects of Gait Speed, Body Balance, and Falls in the Relationship between Physical Activity and Health-Related Quality of Life in Vulnerable Older Adults. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022;19:14135. [PMID: 36361009 PMCID: PMC9655035 DOI: 10.3390/ijerph192114135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 10/19/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]

Affiliation(s)

Marcelo de Maio Nascimento Department of Physical Education, Federal University of Vale do São Francisco, Petrolina 56304-917, Brazil
Élvio Rúbio Gouveia Department of Physical Education and Sport, University of Madeira, 9020-105 Funchal, Portugal LARSYS, Interactive Technologies Institute, 9020-105 Funchal, Portugal Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, 1205 Geneva, Switzerland
Bruna R. Gouveia LARSYS, Interactive Technologies Institute, 9020-105 Funchal, Portugal Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, 1205 Geneva, Switzerland Regional Directorate of Health, Secretary of Health of the Autonomous Region of Madeira, 9004-515 Funchal, Portugal Saint Joseph of Cluny Higher School of Nursing, 9050-535 Funchal, Portugal
Adilson Marques CIPER, Faculty of Human Kinetics, University of Lisbon, 1495-751 Lisbon, Portugal ISAMB, Faculty of Medicine, University of Lisbon, 1649-020 Lisbon, Portugal
Cíntia França Department of Physical Education and Sport, University of Madeira, 9020-105 Funchal, Portugal LARSYS, Interactive Technologies Institute, 9020-105 Funchal, Portugal
Duarte L. Freitas Department of Physical Education and Sport, University of Madeira, 9020-105 Funchal, Portugal Centre of Research, Education, Innovation and Intervention in Sport (CIFI2D), Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
Pedro Campos LARSYS, Interactive Technologies Institute, 9020-105 Funchal, Portugal Department of Informatics Engineering and Interactive Media Design, University of Madeira, 9020-105 Funchal, Portugal
Andreas Ihle Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, 1205 Geneva, Switzerland Department of Psychology, University of Geneva, 1205 Geneva, Switzerland Swiss National Centre of Competence in Research LIVES—Overcoming Vulnerability: Life Course Perspectives, 1015 Lausanne, Switzerland

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Conde-Pipó J, Valenzuela-Barranco I, López-Moro A, Román-Alconchel B, Mariscal-Arcas M, Zurita-Ortega F. Influence of Alpine Skiing on Health-Related Quality of Life and Physical Self-Concept in Physically Active Adults over 55 Years of Age. Sports (Basel) 2022;10:sports10100153. [PMID: 36287766 PMCID: PMC9607613 DOI: 10.3390/sports10100153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/29/2022] [Accepted: 10/03/2022] [Indexed: 11/17/2022] Open

Muscle Strength and Balance as Mediators in the Association between Physical Activity and Health-Related Quality of Life in Community-Dwelling Older Adults. J Clin Med 2022;11:jcm11164857. [PMID: 36013095 PMCID: PMC9409764 DOI: 10.3390/jcm11164857] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 07/06/2022] [Accepted: 08/16/2022] [Indexed: 12/02/2022] Open

Moura EF, Cabral DAR, Rêgo MLM, Browne RAV, Macêdo GAD, Cabral LLP, Vivas A, Oliveira GTA, Lucena BEB, Elsangedy HM, Costa EC, Fontes EB. Associations of objectively measured movement behavior and cardiorespiratory fitness with mental health and quality of life in older adults with hypertension: an exploratory analysis during the COVID-19 pandemic. Aging Ment Health 2022;26:1678-1685. [PMID: 34219568 DOI: 10.1080/13607863.2021.1942436] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]

Regional Variation in National Healthcare Expenditure and Health System Performance in Central Cities and Suburbs in Japan. Healthcare (Basel) 2022;10:healthcare10060968. [PMID: 35742020 PMCID: PMC9223123 DOI: 10.3390/healthcare10060968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/14/2022] [Accepted: 05/18/2022] [Indexed: 11/19/2022] Open

Abstract

The increasing national healthcare expenditure (NHE) with the aging rate is a significant social problem in Japan, and efficient distribution and use of NHE is an urgent issue. It is assumed that comparisons in subregions would be important to explore the regional variation in NHE and health system performance in targeted municipalities of the metropolitan area of Tokyo (central cities) and the neighboring municipalities of Chiba Prefecture (suburbs). This study aimed to clarify the differences of the socioeconomic factors affecting NHE and the health system performances between subregions. A multiple regression analysis was performed to extract the factors affecting the total medical expenses of NHE (Total), comprising the medical expenses of inpatients (MEI), medical expenses of outpatients (MEO), and consultation rates of inpatients (CRI) and outpatients (CRO). Using the stepwise method, dependent variables were selected from three categories: health service, socioeconomic, and lifestyle. Then, health system performance analysis was performed, and the differences between regions were clarified using the Mann–Whitney U test. The test was applied to 18 indicators, classified into five dimensions referred to in the OECD indicators: health status, risk factors for health, access to care, quality of care, and health system capacity and resources. In the central cities, the number of persons per household was the primary factor affecting Total, MEI, MEO, and CRO, and the number of persons per household and the percentage of the entirely unemployed persons primarily affected CRI. In the suburbs, the ratio of the population aged 65–74 and the number of hospital beds were significantly positively related to Total, MEI, and CRI, but the number of workers employed in primary industries was negatively related to Total and MEI. The ratio of the population aged 65–74 was significantly positively related to MEO and CRO. Regarding health system performance, while risk factors for health was high in the central cities, the others, including access to care, quality of care, and health system capacity and resources, were superior in the suburbs, suggesting that the health system might be well developed to compensate for the risks. In the suburbs, while risk factors for health were lower than those in the central cities, access to care, quality of care, and health system capacity and resources were also lower, suggesting that the healthcare system might be poorer. These results indicate a need to prioritize mitigating healthcare disparities in the central cities and promoting the health of the elderly in the suburbs by expanding the suburbs’ healthcare systems and resources. This study clarified that the determinants of NHE and health system performance are drastically varied among subregional levels and suggested the importance of precise regional moderation of the healthcare system.

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Keramat SA, Ahammed B, Mohammed A, Seidu AA, Farjana F, Hashmi R, Ahmad K, Haque R, Ahmed S, Ali MA, Ahinkorah BO. Disability, physical activity, and health-related quality of life in Australian adults: An investigation using 19 waves of a longitudinal cohort. PLoS One 2022;17:e0268304. [PMID: 35552556 PMCID: PMC9098066 DOI: 10.1371/journal.pone.0268304] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 04/26/2022] [Indexed: 11/23/2022] Open

Abstract

Background

Any form of long-term physical or mental impairment might negatively influence health-related quality of life (HRQoL). HRQoL, as an independent concept, covers a wide range of characteristics that includes physical, mental, social, and spiritual functions. People with disabilities are continuously exposed to multiple barriers that deteriorate their HRQoL. It also creates impairment in performing physical activities. However, experts opine regular physical exercise as an intervention to help disabled people. This research aims to investigate the association between disability and physical activity with HRQoL among the adult population in Australia.

Design

A retrospective cohort study.

Methods

This study utilized the most recent 19 waves of data (2002–2020) from the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey. Component summary scores such as physical component summary (PCS) and mental component summary (MCS), and SF-6D utility scores were utilized to measure HRQoL. Random-effects GLS regression technique was fitted to estimate the association between disability and physical activity with HRQoL, after adjusting for a range of socio-demographic and health-related characteristics.

Results

Disability was negatively associated with the PCS (-5.95), MCS (-2.70) and SF-6D (-0.060) compared with non-disabled counterparts. However, respondents engaged in the recommended level of physical activity had substantial gain in PCS (b = 0.96), MCS (1.57), and SF-6D (0.021) scores. Besides, the results showed that performing the recommended level of physical activity in the presence of disability has lessen the negative effect of disability/ positive moderating effect of physical activity on PCS, MCS, and SF-6D scores by 1.84 points, 0.82 points, and 0.013 percentage points, respectively.

Conclusion

This study found an inverse association between disability and HRQoL among Australian adults. However, physical activity was associated with improved HRQoL. Therefore, public health interventions, such as the orientation of physical activities, have a higher potential to dwindle the burden regarding HRQoL.

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Salinas-Rodríguez A, Manrique-Espinoza B, Palazuelos-González R, Rivera-Almaraz A, Jáuregui A. Physical activity and sedentary behavior trajectories and their associations with quality of life, disability, and all-cause mortality. Eur Rev Aging Phys Act 2022;19:13. [PMID: 35488197 PMCID: PMC9052456 DOI: 10.1186/s11556-022-00291-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 04/14/2022] [Indexed: 11/10/2022] Open

Abstract

BACKGROUND

Physical activity (PA) and sedentary behavior (SB) are not stable conditions but change over time and among individuals, and both could have deleterious effects on health-related outcomes among older adults. This study aimed to identify the longitudinal trajectories of PA and SB and estimate their association with quality of life, disability, and all-cause mortality in a national sample of older Mexican adults.

METHODS

Data comes from three waves of the WHO Study on global AGEing and adult health (SAGE) in Mexico (2009, 2014, 2017). In total, 3209 older adults ages 50 and above were included. PA and SB were determined by using the Global Physical Activity Questionnaire (GPAQ). Disability was measured using the WHO Disability Assessment Schedule (WHODAS 2.0), quality of life using the WHOQOL (WHO Quality of Life) instrument, and all-cause mortality using a verbal autopsy. We used growth mixture modeling (GMM) to investigate the longitudinal trajectories of PA and SB. Three-level linear mixed effect models were used to estimate the associations of PA and SB with quality of life and disability and the Cox model for the association with all-cause mortality.

RESULTS

Three longitudinal trajectories of PA and SB were found: low-PA-decreasers, moderate-PA-decreasers, and high-PA-decreasers for PA; and low-maintainers, steep-decreasers, and steep-increasers for SB. Decreased quality of life, increased disability, and all-cause mortality were all consistently associated with worse PA and SB trajectories.

CONCLUSIONS

Our results highlight the need for health policies and prevention strategies that promote PA and limit SB in middle-aged adults. Further studies should consider these activities/behaviors as exposures that vary throughout life and work to identify vulnerable groups of older adults for whom physical activation interventions and programs would be most impactful.

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Scarabottolo CC, Tebar WR, Gobbo LA, Ohara D, Ferreira AD, da Silva Canhin D, Christofaro DGD. Analysis of different domains of physical activity with health-related quality of life in adults: 2-year cohort. Health Qual Life Outcomes 2022;20:71. [PMID: 35488344 PMCID: PMC9052447 DOI: 10.1186/s12955-022-01981-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 04/22/2022] [Indexed: 12/12/2022] Open

Abstract

BACKGROUND

It is estimated that, worldwide, 9% of deaths occur as a result of insufficient physical activity (PA) practice. Practicing PA can prevent and/or reduce the deleterious effects of different types of diseases and can improve general health aspects related to health-related quality of life (HRQoL).

PURPOSE

To analyze the relationship of different PA domains with different HRQoL domains over a two-year period.

METHODS

This is an observational study with a two-year longitudinal design. The sample, composed of adults, was selected from a randomization of the streets of the different regions (north, south, east, west and center) covering individuals from all areas of the city. To assess the practice of PA, the Baecke questionnaire was used. The instrument Medical Outcomes Study SF-36-Item Short Form Health Survey was used to assess the HRQoL domains. Linear regression models were used to analyzed the association of different PA domains with changes in HRQoL. Multivariate statistical models were adjusted for gender, age, socioeconomic status, marital status, the respective PA score at baseline, smoking, body mass index, and morbidity.

RESULTS

331 adults were evaluated. There was a decrease in the practice of PA in the occupational domain and an increase in the leisure/locomotion domain. Regarding HRQoL, there was an increase in the scores of body pain and mental health, and a decrease in scores of general health, vitality, social aspects and emotional aspects. The PA practice in the occupational domain was inversely related to functional capacity (β = - 7.2 [CI 95% - 13.0; - 1.4]). The practice of PA through sports in leisure time was positively associated with vitality (β = 5.5 [CI 95% 0.2; 10.7]) and mental health (β = 15.2 [CI 95% 6.8; 23.7]). PA practice during leisure and locomotion was inversely associated with functional capacity (β = - 5.68 [CI 95% - 10.7; - 0.6]) and positively associated with vitality β = 4.8 [CI 95% 0.8; 8.7]) and mental health (β = 8.4 [CI 95% 2.0; 14.9]). The total PA practice was inversely associated with functional capacity (β = - 3.8 [CI 95% - 6.5; - 1.2]) and positively associated with pain in the body (β = 4.9 [CI 95% 0.3; 9.4]), vitality (β = 2.9 [CI 95% 0.7; 5.0]) and mental health (β = 5.7 [CI 95% 2.2; 9.2]).

CONCLUSIONS

It is suggested that practicing PA continuously within a period of two years can positively affect some physical aspects and some mental aspects related to HRQoL, but not all of them. A strategy for public policy actions is to explore these variables by domain and thus detect the real needs and improvements that can be made for the population.

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Ortolá R, García-Esquinas E, Buño-Soto A, Cabanas-Sánchez V, Martínez-Gómez D, Sotos-Prieto M, Struijk EA, Caballero FF, Lopez-Garcia E, Banegas JR, Rodríguez-Artalejo F. Associations of device-measured sleep, sedentariness and physical activity with growth differentiation factor 15 in older adults. J Cachexia Sarcopenia Muscle 2022;13:1003-1012. [PMID: 35132822 PMCID: PMC8977966 DOI: 10.1002/jcsm.12924] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 12/14/2021] [Accepted: 01/10/2022] [Indexed: 12/18/2022] Open

Abstract

BACKGROUND

Growth differentiation factor 15 (GDF-15) is a biomarker for chronic disease burden that might explain the health effects of sedentary behaviours (SBs) and physical activity (PA). We examined associations of device-measured sleep, SB and PA, and time reallocations among them, with GDF-15 in older adults.

METHODS

We used data from 2245 older adults participating in the Seniors-ENRICA-2 study. Wrist-worn accelerometers were employed to ascertain total time in sleep, SB, light PA (LPA) and moderate-to vigorous PA (MVPA). Associations between these activities and serum GDF-15 levels were analysed using linear regression, including isotemporal substitution models for time reallocations among activities, and adjusted for potential confounders. Analyses were conducted separately in two groups (less active and more active individuals) according to the median total PA time.

RESULTS

In the less active participants, 30 min/day more of MVPA were related to lower levels of GDF-15 when replacing sleep (fully adjusted mean percentage differences [95% confidence interval] in GDF-15 of -9.2% [-13.2, -5.0]), SB (-9.8% [-13.6, -5.8]) and LPA (-5.8% [-11.1, -0.3]), whereas 30 min/day more of LPA were related to lower GDF-15 when replacing both sleep (-3.6% [-6.1, -1.0]) and SB (-4.2% [-6.7, -1.7]). In the more active participants, 30 min/day more of MVPA were also associated with lower GDF-15 when replacing sleep (-2.9% [-5.3, -0.3]), SB (-2.4% [-4.6, -0.2]) and LPA (-3.5% [-6.6, -0.3]), but no associations were found for more time in LPA. Spending more time in SB was associated with higher GDF-15 levels only among those less active (1.9% [0.9, 2.9] per 30 min/day increment). Sleep time did not appear to be associated with GDF-15.

CONCLUSIONS

The MVPA was inversely associated with GDF-15, with stronger associations at lower PA volumes. Also, more LPA and less SB time were linked to lower GDF-15 in the less active individuals. This suggests that simply moving more and sitting less may reduce chronic disease burden in older adults.

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Affiliation(s)

Rosario Ortolá Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
Esther García-Esquinas Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
Antonio Buño-Soto Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,Department of Laboratory Medicine, La Paz University Hospital-IdiPaz, Madrid, Spain
Verónica Cabanas-Sánchez IMDEA Food Institute. CEI UAM + CSIC, Madrid, Spain
David Martínez-Gómez Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.,IMDEA Food Institute. CEI UAM + CSIC, Madrid, Spain
Mercedes Sotos-Prieto Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.,Department of Environmental Health and Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
Ellen A Struijk Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
Francisco Félix Caballero Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
Esther Lopez-Garcia Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.,IMDEA Food Institute. CEI UAM + CSIC, Madrid, Spain
José R Banegas Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
Fernando Rodríguez-Artalejo Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain.,Cardiovascular and Nutritional Epidemiology Group, IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain.,CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.,IMDEA Food Institute. CEI UAM + CSIC, Madrid, Spain

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Abdalla PP, Neto ESDQ, de Souza Lage ACS, Gomes S, de Freitas MDDB, Pedro-Costa S, Machado DRL, Oliveira J, Mota J, Bohn L. Sleep Quality and Quality of Life Among Older Adults During COVID-19 Pandemic: A Cross-sectional Study. Curr Aging Sci 2022;15:186-196. [PMID: 35249520 DOI: 10.2174/1874609815666220304195647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/13/2021] [Accepted: 01/12/2022] [Indexed: 11/22/2022]

Affiliation(s)

Pedro Pugliesi Abdalla Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
Elzier Sampaio de Queiroz Neto Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
Ana Carolina Silveira de Souza Lage Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
Sérgio Gomes Prefeitura Municipal de Fortaleza, Coordenadoria do Idoso, Rua São José, 01, 60.060-170, Fortaleza, Ceará, Brazil
Maria das Dores Bezerra de Freitas Prefeitura Municipal de Fortaleza, Coordenadoria do Idoso, Rua São José, 01, 60.060-170, Fortaleza, Ceará, Brazil
Simão Pedro-Costa Faculty of Phycology, Education and Sport, University Lusófona of Porto, Rua Augusto Rosa, 24, 4000-098, Porto, Portugal
Dalmo Roberto Lopes Machado Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
José Oliveira Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
Jorge Mota Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal
Lucimere Bohn Research Center in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto (FADEUP), Portugal Laboratory for Integrative and Translational Research in Population Health (ITR), Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal

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Ren P, Zhang X, Du L, Pan Y, Chen S, He Q. Reallocating Time Spent in Physical Activity, Sedentary Behavior and Its Association with Fear of Falling: Isotemporal Substitution Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022;19:ijerph19052938. [PMID: 35270631 PMCID: PMC8910553 DOI: 10.3390/ijerph19052938] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 02/21/2022] [Accepted: 02/28/2022] [Indexed: 12/16/2022]

Chen S, Malete L, Ling J. An examination of physical activity guidelines and health-related quality of life among U.S. older adults. Prev Med 2022;156:106986. [PMID: 35150753 DOI: 10.1016/j.ypmed.2022.106986] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/30/2021] [Accepted: 02/06/2022] [Indexed: 01/02/2023]

Abstract

Physical activity can help improve the poor health-related quality of life in older adult population. Although the Physical Activity Guidelines for Americans recommend both aerobic and muscle strengthening activities for adults, previous studies predominantly focused on aerobic activity with limited research on muscle strengthening activities. The purpose of this cross-sectional study was to examine the relationships between meeting physical activity guidelines (i.e., aerobic activity, muscle strengthening activity) and health-related quality of life in the older adult population. Data of 87,495 older adults aged ≥65 years from the U.S. 2019 Behavioral Risk Factor Surveillance System were analyzed. Phone interviews and validated questionnaires were used to assess aerobic activity, muscle strengthening activity, and health-related quality of life. Binomial logistic regression was used to examine the relationships between meeting physical activity guidelines and health-related quality of life while adjusting for key covariates (i.e., age, sex, race, education, marital status, employment status, income, body mass index, smoking, drinking, and comorbidities). Participants meeting both or aerobic activity guideline only had significantly lower odds of reporting all components of health-related quality of life (i.e., general health, mental health, physical health, activity limitation) than those who met neither guideline (OR = 0.37-0.58) and those who met muscle strengthening activity guideline only (OR = 0.34 - 0.74). Given the stronger positive association between aerobic activity and health-related quality of life than that between muscle strengthening activity and health-related quality of life, future research should focus on promoting aerobic activity to increase health-related quality of life among older people.

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Zhang J, Bloom I, Dennison EM, Ward KA, Robinson SM, Barker M, Cooper C, Lawrence W. Understanding influences on physical activity participation by older adults: A qualitative study of community-dwelling older adults from the Hertfordshire Cohort Study, UK. PLoS One 2022;17:e0263050. [PMID: 35077522 PMCID: PMC8789143 DOI: 10.1371/journal.pone.0263050] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 01/12/2022] [Indexed: 01/24/2023] Open

Abstract

BACKGROUND

The health benefits of physical activity (PA) participation in later life are widely recognised. Understanding factors that can influence the participation of community-dwelling older adults in PA is crucial in an ageing society. This will be paramount in aiding the design of future interventions to effectively promote PA in this population. The main aim of this qualitative study was to explore influences on PA among community-dwelling older people, and the secondary aim was to explore gender differences.

METHODS

Qualitative data were collected in 2014 by conducting focus group discussions using a semi-structured discussion guide with older people resident in Hertfordshire, UK. Discussions were audio-recorded, transcribed verbatim and transcripts analysed thematically.

RESULTS

Ninety-two participants were recruited to the study (47% women; 74-83 years) and a total of 11 focus groups were conducted. Findings indicated six themes that appeared to affect older adults' participation in PA: past life experiences; significant life events; getting older; PA environment; psychological/personal factors; and social capital. Overall, the findings emphasised the role of modifiable factors, namely psychological factors (such as self-efficacy, motivation, outcome expectancy) and social factors (such as social support and social engagement). These factors exerted their own influence on physical activity participation, but also appeared to mediate the effect of other largely non-modifiable background and ageing-related factors on participants' engagement with PA in later life.

CONCLUSION

In view of these findings, intervention designers could usefully work with behavioural scientists for insight as to how to enhance psychological and social factors in older adults. Our data suggest that interventions that aim to build self-efficacy, motivation and social networks have the potential to indirectly promote PA participation in older adults. This would be best achieved by developing physical activity interventions through working with participants in an empowering and engaging way.

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Affiliation(s)

Jean Zhang MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
Ilse Bloom MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom * E-mail:
Elaine M. Dennison MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom Victoria University of Wellington, Wellington, New Zealand
Kate A. Ward MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom
Sian M. Robinson MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom AGE Research Group, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
Mary Barker MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
Cyrus Cooper MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Musculoskeletal Biomedical Research Unit, University of Oxford, Oxford, United Kingdom
Wendy Lawrence MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom

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Associations of objectively measured physical activity and sedentary time with pregnancy-specific health-related quality of life. Midwifery 2022;104:103202. [PMID: 34801955 PMCID: PMC8671341 DOI: 10.1016/j.midw.2021.103202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 10/25/2021] [Accepted: 11/06/2021] [Indexed: 01/03/2023]

O’Brien WJ, Badenhorst CE, Draper N, Basu A, Elliot CA, Hamlin MJ, Batten J, Lambrick D, Faulkner J. Physical Activity, Mental Health and Wellbeing during the First COVID-19 Containment in New Zealand: A Cross-Sectional Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021;18:12036. [PMID: 34831789 PMCID: PMC8620825 DOI: 10.3390/ijerph182212036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/09/2021] [Accepted: 11/11/2021] [Indexed: 11/17/2022]

Almeida LV, Fukuchi CA, Sakanaka TE, Cliquet A. A low-cost easily implementable physiotherapy intervention clinically improves gait implying better adaptation to lower limb prosthesis: a randomized clinical trial. Sci Rep 2021;11:21228. [PMID: 34707169 PMCID: PMC8551177 DOI: 10.1038/s41598-021-00686-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 10/15/2021] [Indexed: 11/13/2022] Open

Abstract

Lower limb amputation highly impacts the lives of individuals. The inability to walk due to difficulties in adapting to wearing prosthesis can potentially result in physical degeneration and comorbidity in this population. In this randomized clinical trial study, we investigated if a low-cost and easily implementable physiotherapy intervention was effective in improving gait performance and adaptation to lower limb prosthesis in individuals with an amputation. A total of 26 individuals participated in the study, 16 with lower limb amputation and 10 without amputation. Participants with amputation were further divided in intervention and control groups. The intervention group underwent a rehabilitation protocol aimed at strengthening muscles and improving prosthesis adaptation. Muscle strengthening targeted the hip segment, prioritizing the abdominal muscles, hip flexors, extensors, adductors and abductors, followed by cicatricial mobilization and weight-bearing on the stump for desensitization. Assessment and measures were performed across the kinetic and kinematic parameters of gait. In the comparison between pre-and post-intervention, a significant increase in gait speed (0.68—2.98, 95% CI, 1.83, effect size ES) and cadence (0.56—2.69, 95% CI, 1.63, ES) was found between groups and time points. Step (0.73—3.11, 95% CI, 1.92, ES) and stride length (0.62—2.84, 95% CI, 1.73) increased between pre- and post-intervention, while in the control group both variables remained smaller. The intervention group decreased stance phase as a percentage of gait cycle between pre- and post-intervention (− 1.33—0.62, 95% CI, − 36, ES), while it increased in the control group. Improvement in a combination of important gait parameters indicates that the intervention protocol promoted the adaptation to prosthesis and the functional independence of individuals with lower limb amputation. It is recommended that the participants continue receiving follow-up assessments and rehabilitation interventions.

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Lassandro G, Trisciuzzi R, Palladino V, Carriero F, Giannico OV, Tafuri S, Valente R, Gianfelici A, Accettura D, Giordano P. Psychophysical health and perception of well-being between master badminton athletes and the adult Italian population. ACTA BIO-MEDICA : ATENEI PARMENSIS 2021;92:e2021253. [PMID: 34487105 PMCID: PMC8477076 DOI: 10.23750/abm.v92i4.9857] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 08/31/2020] [Indexed: 01/06/2023]

Law RJ, Langley J, Hall B, Burton C, Hiscock J, Williams L, Morrison V, Lemmey AB, Lovell-Smith C, Gallanders J, Cooney J, Williams NH. Promoting physical activity and physical function in people with long-term conditions in primary care: the Function First realist synthesis with co-design. HEALTH SERVICES AND DELIVERY RESEARCH 2021. [DOI: 10.3310/hsdr09160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open

Abstract Background As people age and accumulate long-term conditions, their physical activity and physical function declines, resulting in disability and loss of independence. Primary care is well placed to empower individuals and communities to reduce this decline; however, the best approach is uncertain. Objectives To develop a programme theory to explain the mechanisms through which interventions improve physical activity and physical function in people with long-term conditions in different primary care contexts, and to co-design a prototype intervention. Data sources Systematic literature searches of relevant databases with forwards and backwards citation tracking, grey literature searches and further purposive searches were conducted. Qualitative data were collected through workshops and interviews. Design Realist evidence synthesis and co-design for primary care service innovation. Setting Primary care in Wales and England. Participants Stakeholders included people with long-term conditions, primary care professionals, people working in relevant community roles and researchers. Methods The realist evidence synthesis combined evidence from varied sources of literature with the views, experiences and ideas of stakeholders. The resulting context, mechanism and outcome statements informed three co-design workshops and a knowledge mobilisation workshop for primary care service innovation. Results Five context, mechanism and outcome statements were developed. (1) Improving physical activity and function is not prioritised in primary care (context). If the practice team culture is aligned to the elements of physical literacy (mechanism), then physical activity promotion will become routine and embedded in usual care (outcome). (2) Physical activity promotion is inconsistent and unco-ordinated (context). If specific resources are allocated to physical activity promotion (in combination with a supportive practice culture) (mechanism), then this will improve opportunities to change behaviour (outcome). (3) People with long-term conditions have varying levels of physical function and physical activity, varying attitudes to physical activity and differing access to local resources that enable physical activity (context). If physical activity promotion is adapted to individual needs, preferences and local resources (mechanism), then this will facilitate a sustained improvement in physical activity (outcome). (4) Many primary care practice staff lack the knowledge and confidence to promote physical activity (context). If staff develop an improved sense of capability through education and training (mechanism), then they will increase their engagement with physical activity promotion (outcome). (5) If a programme is credible with patients and professionals (context), then trust and confidence in the programme will develop (mechanism) and more patients and professionals will engage with the programme (outcome). A prototype multicomponent intervention was developed. This consisted of resources to nurture a culture of physical literacy, materials to develop the role of a credible professional who can promote physical activity using a directory of local opportunities and resources to assist with individual behaviour change. Limitations Realist synthesis and co-design is about what works in which contexts, so these resources and practice implications will need to be modified for different primary care contexts. Conclusions We developed a programme theory to explain how physical activity could be promoted in primary care in people with long-term conditions, which informed a prototype intervention. Future work A future research programme could further develop the prototype multicomponent intervention and assess its acceptability in practice alongside existing schemes before it is tested in a feasibility study to inform a future randomised controlled trial. Study registration This study is registered as PROSPERO CRD42018103027. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 16. See the NIHR Journals Library website for further project information. Collapse

Endoh Y, Tamashiro Y, Toyosato T, Omine F, Takeda M, Kobayashi M, Endoh H. Child-rearing Assistance Enhances Physical Activity and Health-related Quality of Life among Japanese Grandmothers. JOURNAL OF INTERGENERATIONAL RELATIONSHIPS 2021. [DOI: 10.1080/15350770.2021.1965064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]

Brandão GS, Brandão GS, Sampaio AAC, Damas Andrade L, Fonseca AL, Campos FKR, Silva AS, Silva MM, Oliveira-Silva I, Vieira RP, Donner CF, Silva RA, Camelier AA, Oliveira LVF. Home physical exercise improves functional mobility and quality of life in the elderly: A CONSORT-prospective, randomised controlled clinical trial. Int J Clin Pract 2021;75:e14347. [PMID: 33977587 DOI: 10.1111/ijcp.14347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 05/01/2021] [Accepted: 05/05/2021] [Indexed: 01/06/2023] Open

DURAN M, KEKLİK SS, ÇOBANOĞLU G. The Comparison of Physical Activity, Fatigue and Quality of Life in Different Age Groups. CLINICAL AND EXPERIMENTAL HEALTH SCIENCES 2021. [DOI: 10.33808/clinexphealthsci.858588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]

Vacchiano M, Valente R. Did the screens win? An autoregressive model linking leisure, relatedness and mental health. COMPUTERS IN HUMAN BEHAVIOR 2021. [DOI: 10.1016/j.chb.2021.106755] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]

Owari Y. Relationship between Psychological Distress and Prolonged Sedentary Bouts in the Elderly: Four Period Analysis. Healthcare (Basel) 2021;9:healthcare9060676. [PMID: 34200000 PMCID: PMC8230261 DOI: 10.3390/healthcare9060676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 05/25/2021] [Accepted: 06/01/2021] [Indexed: 12/04/2022] Open

Biddle SJH, Henson J, Davies MJ, Khunti K, Sutton S, Yates T, Edwardson CL. Device-assessed total and prolonged sitting time: associations with anxiety, depression, and health-related quality of life in adults. J Affect Disord 2021;287:107-114. [PMID: 33774318 DOI: 10.1016/j.jad.2021.03.037] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/11/2021] [Accepted: 03/15/2021] [Indexed: 12/30/2022]

Blair CK, Harding E, Wiggins C, Kang H, Schwartz M, Tarnower A, Du R, Kinney AY. A Home-Based Mobile Health Intervention to Replace Sedentary Time With Light Physical Activity in Older Cancer Survivors: Randomized Controlled Pilot Trial. JMIR Cancer 2021;7:e18819. [PMID: 33847588 PMCID: PMC8087341 DOI: 10.2196/18819] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 11/14/2020] [Accepted: 03/08/2021] [Indexed: 12/20/2022] Open

Abstract

Background

Older cancer survivors are at risk of the development or worsening of both age- and treatment-related morbidity. Sedentary behavior increases the risk of or exacerbates these chronic conditions. Light-intensity physical activity (LPA) is more common in older adults and is associated with better health and well-being. Thus, replacing sedentary time with LPA may provide a more successful strategy to reduce sedentary time and increase physical activity.

Objective

This study primarily aims to evaluate the feasibility, acceptability, and preliminary efficacy of a home-based mobile health (mHealth) intervention to interrupt and replace sedentary time with LPA (standing and stepping). The secondary objective of this study is to examine changes in objective measures of physical activity, physical performance, and self-reported quality of life.

Methods

Overall, 54 cancer survivors (aged 60-84 years) were randomized in a 1:1:1 allocation to the tech support intervention group, tech support plus health coaching intervention group, or waitlist control group. Intervention participants received a Jawbone UP2 activity monitor for use with their smartphone app for 13 weeks. Tech support and health coaching were provided via 5 telephone calls during the 13-week intervention. Sedentary behavior and physical activity were objectively measured using an activPAL monitor for 7 days before and after the intervention.

Results

Participants included survivors of breast cancer (21/54, 39%), prostate cancer (16/54, 30%), and a variety of other cancer types; a mean of 4.4 years (SD 1.6) had passed since their cancer diagnosis. Participants, on average, were 70 years old (SD 4.8), 55% (30/54) female, 24% (13/54) Hispanic, and 81% (44/54) overweight or obese. Malfunction of the Jawbone trackers occurred in one-third of the intervention group, resulting in enrollment stopping at 54 rather than the initial goal of 60 participants. Despite these technical issues, the retention in the intervention was high (47/54, 87%). Adherence was high for wearing the tracker (29/29, 100%) and checking the app daily (28/29, 96%) but low for specific aspects related to the sedentary features of the tracker and app (21%-25%). The acceptability of the intervention was moderately high (81%). There were no significant between-group differences in total sedentary time, number of breaks, or number of prolonged sedentary bouts. There were no significant between-group differences in physical activity. The only significant within-group change occurred within the health coaching group, which increased by 1675 daily steps (95% CI 444-2906; P=.009). This increase was caused by moderate-intensity stepping rather than light-intensity stepping (+15.2 minutes per day; 95% CI 4.1-26.2; P=.008).

Conclusions

A home-based mHealth program to disrupt and replace sedentary time with stepping was feasible among and acceptable to older cancer survivors. Future studies are needed to evaluate the optimal approach for replacing sedentary behavior with standing and/or physical activity in this population.

Trial Registration

ClinicalTrials.gov NCT03632694; https://clinicaltrials.gov/ct2/show/NCT03632694

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Yadav R, Yadav RK, Pandey RM, Upadhyay AD. Predictors of Health-Related Quality of Life in Indians with Metabolic Syndrome Undergoing Randomized Controlled Trial of Yoga-Based Lifestyle Intervention vs Dietary Intervention. Behav Med 2021;47:151-160. [PMID: 31743071 DOI: 10.1080/08964289.2019.1683711] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]

Lau JH, Lee ES, Zhang Y, Vaingankar JA, Abdin E, Chong SA, Subramaniam M. Association Between Self-Reported Sedentary Behavior and Health-Related Quality of Life Among Multimorbidity Patients in Singapore. Am J Health Promot 2021;35:929-938. [PMID: 33739160 DOI: 10.1177/08901171211001274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]

Yamashita R, Sato S, Akase R, Doi T, Tsuzuku S, Yokoi T, Otsuki S, Harada E. Effects of social network incentives and financial incentives on physical activity and social capital among older women: a randomized controlled trial. BMC Public Health 2021;21:188. [PMID: 33478465 PMCID: PMC7819206 DOI: 10.1186/s12889-021-10175-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 01/05/2021] [Indexed: 12/04/2022] Open

Abstract

Background

Financial incentives have been used to increase physical activity. However, the benefit of financial incentives is lost when an intervention ends. Thus, for this study, we combined social network incentives that leverage the power of peer pressure with financial incentives. Few reports have examined the impact of physical activity on social capital. Therefore, the main goal of this study was to ascertain whether a combination of two incentives could lead to more significant changes in physical activity and social capital during and after an intervention.

Methods

The participants were 39 older women over 65 years of age in Kumamoto, Japan. The participants were randomly divided into a financial incentive group (FI group) and a social network incentive plus financial incentive group (SNI + FI group). Both groups underwent a three-month intervention. Measurements of physical activity and social capital were performed before and after the intervention. Additionally, the effects of the incentives on physical activity and social capital maintenance were measured 6 months postintervention. The financial incentive group received a payment ranging from US$4.40 to US$6.20 per month, depending on the number of steps taken during the intervention. For the other group, we provided a social network incentive in addition to the financial incentive. The SNI + FI group walked in groups of three people to use the power of peer pressure.

Results

A two-way ANOVA revealed that in terms of physical activity, there was a statistically significant interaction between group and time (p = 0.017). The FI group showed no statistically significant improvement in physical activity during the observation period. In terms of the value of social capital, there was no significant interaction between group and time.

Conclusion

Our results suggest that social network incentives, in combination with financial incentives, are more effective for promoting physical activity than financial incentives alone among older women and that these effects can continue after an intervention. In the meantime, further studies should be conducted on the effect of physical activity on social capital.

Trial registration

UMIN000038080, registered on 09/22/2019 (Retrospectively registered).

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Compernolle S, De Bourdeaudhuij I, Cardon G, Van Dyck D. Sex-specific typologies of older adults' sedentary behaviors and their associations with health-related and socio-demographic factors: a latent profile analysis. BMC Geriatr 2021;21:66. [PMID: 33468055 PMCID: PMC7816402 DOI: 10.1186/s12877-021-02011-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 01/05/2021] [Indexed: 11/10/2022] Open

Abstract

BACKGROUND

Some types of sedentary behaviors tend to cluster in individuals or groups of older adults. Insight into how these different types of sedentary behavior cluster is needed, as recent research suggests that not all types of sedentary behavior may have the same negative effects on physical and mental health. Therefore, the aim of this study was to identify sex-specific typologies of older adults' sedentary behavior, and to examine their associations with health-related and socio-demographic factors.

METHODS

Cross-sectional data were collected as part of the BEPAS Seniors, and the Busschaert study among 696 Flemish older adults (60+). Typologies of self-reported sedentary behavior were identified using latent profile analysis, and associations with health-related and sociodemographic factors were examined using analyses of variances.

RESULTS

Five distinct typologies were identified from seven sedentary behaviors (television time, computer time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in men, and three typologies were identified from six sedentary behaviors (television time, transport-related sitting time, sitting for reading, sitting for hobbies, sitting for socializing and sitting for meals) in women. Typologies that are characterized by high television time seem to be related to more negative health outcomes, like a higher BMI, less grip strength, and a lower physical and mental health-related quality-of-life. Typologies that are represented by high computer time and motorized transport seem to be related to more positive health outcomes, such as a lower body mass index, more grip strength and a higher physical and mental health-related quality-of-life.

CONCLUSIONS

Although causal direction between identified typologies and health outcomes remains uncertain, our results suggests that future interventions should better focus on specific types of sedentary behavior (e.g. television time), or patterns of sedentary behavior, rather than on total sedentary behavior.

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Ortolá R, García-Esquinas E, Cabanas-Sánchez V, Migueles JH, Martínez-Gómez D, Rodríguez-Artalejo F. Association of Physical Activity, Sedentary Behavior, and Sleep With Unhealthy Aging: Consistent Results for Device-Measured and Self-reported Behaviors Using Isotemporal Substitution Models. J Gerontol A Biol Sci Med Sci 2021;76:85-94. [PMID: 32701141 DOI: 10.1093/gerona/glaa177] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Indexed: 01/15/2023] Open

Rollo S, Prapavessis H. A combined health action process approach and mHealth intervention to reduce workplace sitting time in office-working adults: a secondary analysis examining health-related quality of life and work performance outcomes. Psychol Health 2020;36:1200-1216. [PMID: 33108910 DOI: 10.1080/08870446.2020.1838522] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]

Felez-Nobrega M, Olaya B, Haro JM, Stubbs B, Smith L, Koyanagi A. Associations between sedentary behavior and happiness: An analysis of influential factors among middle-aged and older adults from six low- and middle-income countries. Maturitas 2020;143:157-164. [PMID: 33308622 DOI: 10.1016/j.maturitas.2020.10.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 09/21/2020] [Accepted: 10/18/2020] [Indexed: 10/23/2022]

Chase JAD, Otmanowski J, Rowland S, Cooper PS. A systematic review and meta-analysis of interventions to reduce sedentary behavior among older adults. Transl Behav Med 2020;10:1078-1085. [DOI: 10.1093/tbm/ibz189] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open

Abstract Abstract Sedentary behavior (SB) is associated with numerous negative health outcomes, independent of physical activity behavior. Older adults are the most sedentary population in the United States. Understanding the effects and characteristics of existing interventions to reduce SB can inform practice, future research, and public health initiatives to improve older adults’ health. We conducted a systematic review and meta-analysis to examine existing SB intervention research among older adults and quantitatively synthesize intervention effects. Comprehensive searches were conducted to identify studies testing interventions to reduce SB time among adults at least 60 years old. Data on study design, intervention content and delivery, and participant characteristics were extracted from eligible studies. Standardized mean difference effect sizes (Cohen’s d) were synthesized using a random-effects model for two-group pretest–posttest design studies. Twenty-two reports describing 17 distinct studies were included in the narrative synthesis, with eight studies included in the meta-analysis (k = 8; n = 1,024). Most interventions were theory-driven and employed multiple strategies, including education, self-monitoring, and goal setting. Although SB interventions significantly reduced total sedentary time, the overall effect was small (d = −0.25, 95% confidence interval [−0.50, 0.00], p = .05). Studies were significantly heterogeneous (Q = 22.34, p < .01); however, the small number of comparisons prevented moderator analyses. Practitioners should employ diverse SB-specific strategies to encourage older adults to reduce time spent sedentary. To develop public health programs targeting SB in older adults, future research should include measures of time spent in specific SB and duration/number of breaks in sedentary time and investigate SB intervention effects on health outcomes. Collapse

Pedestrian Walkways for Health in Shiraz, Iran, the Contribution of Attitudes, and Perceived Environmental Attributes. SUSTAINABILITY 2020. [DOI: 10.3390/su12187263] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]

Associations of Activity and Sleep With Quality of Life: A Compositional Data Analysis. Am J Prev Med 2020;59:412-419. [PMID: 32713616 DOI: 10.1016/j.amepre.2020.03.029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 11/20/2022]

Abstract

INTRODUCTION

Associations between time spent on physical activity, sedentary behavior, and sleep and quality of life are usually studied without considering that their combined time is fixed. This study investigates the reallocation of time spent on physical activity, sedentary behavior, and sleep during the 24-hour day and their associations with quality of life.

METHODS

Data from the 2011-2016 Rotterdam Study were used to perform this cross-sectional analysis among 1,934 participants aged 51-94 years. Time spent in activity levels (sedentary, light-intensity physical activity, moderate-to-vigorous physical activity, and sleep) were objectively measured with a wrist-worn accelerometer combined with a sleep diary. Quality of life was measured using the EuroQoL 5D-3L questionnaire. The compositional isotemporal substitution method was used in 2018 to examine the association between the distribution of time spent in different activity behaviors and quality of life.

RESULTS

Reallocation of 30 minutes from sedentary behavior, light-intensity physical activity, or sleep to moderate-to-vigorous physical activity was associated with a higher quality of life, whereas reallocation from moderate-to-vigorous physical activity to sedentary behavior, light-intensity physical activity, or sleep was associated with lower quality of life. To illustrate this, a reallocation of 30 minutes from sedentary behavior to moderate-to-vigorous physical activity was associated with a 3% (95% CI=2, 4) higher quality of life score. By contrast, a reallocation of 30 minutes from moderate-to-vigorous physical activity to sedentary behavior was associated with a 4% (95% CI=2, 6) lower quality of life score.

CONCLUSIONS

Moderate-to-vigorous physical activity is important with regard to the quality of life of middle-aged and elderly individuals. The benefits of preventing less time spent in moderate-to-vigorous physical activity were greater than the benefits of more time spent in moderate-to-vigorous physical activity. These results could shift the attention to interventions focused on preventing reductions in moderate-to-vigorous physical activity levels. Further longitudinal studies are needed to confirm these findings and explore causality.

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