Background: The aim of this study was to analyze the association between frailty and sedentary behavior and to examine the discriminative ability of sedentary behavior in screening frailty in older adults.
Methods: This was a cross-sectional study based on data from an epidemiologic population-based household survey involving 316 community-dwelling older adults (≥60 years) of both sexes (173 women and 143 men). The frailty was measured from an adapted version of the criteria proposed by Fried et al. in 2001, which is based on the presence of three or more of the following components: shrinking, weakness, poor endurance/exhaustion, slowness and low activity. Sedentary behavior was determined by the International Physical Activity Questionnaire (long version).
Results: The prevalence of frailty was 23.8%, and the average time in sedentary behavior was 6.1±3.2 h/day. Sedentary behavior was independently and positively associated with frailty (PR=1.10; 95% CI: 1.02-1.19; P=0.013). The ROC curve showed that the sedentary behavior could discriminate frail older adults (AUC=0.66; 95% CI: 0.61-0.72), and the best cutoff point was 7 h/day (sensitivity =54% and specificity =75%).
Conclusions: Frailty is strongly associated with sedentary behavior. Sedentary behavior can be a potential marker in screening of frailty in community-dwelling older adults. Our findings suggest that reducing the time with sedentary behavior and increasing the time with physical activity may prevent frailty syndrome.
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http://dx.doi.org/10.23736/S0022-4707.16.06289-7 | DOI Listing |
Sci Rep
January 2025
Department of Community Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Prolonged sitting can negatively impact postprandial glucose levels and cognitive function. While short bouts of stair climbing are thought to mitigate these risks, the findings remain inconclusive. The present study aimed to explore the effects of stair climbing bouts on postprandial glucose and cognitive functions during prolonged sitting.
View Article and Find Full Text PDFAm J Hum Biol
January 2025
Research Centre for Anthropology and Health, University of Coimbra, Coimbra, Portugal.
Objectives: This study aimed to (i) compare children's lifestyle by urbanization level and (ii) examine the association between children's body mass index (BMI) and the risk of having unhealthy sleep (American Academy of Pediatrics).
Methods: Eight thousand one hundred fifty-nine children (4124 females) aged 6-9 years were observed and classified as urban or nonurban. Height and weight were measured, and the BMI was calculated.
Med Sci Sports Exerc
January 2025
Energy Metabolism Section, National Institute of Diabetes, Digestive and Kidney Diseases, Diabetes, Endocrinology, and Obesity Branch, National Institutes of Health (NIH), Bethesda, MD.
Introduction: ActiGraph accelerometers are used extensively to objectively assess physical activity, sedentary behavior, and sleep. Here, we present an objective validation of five generations of ActiGraph sensors to characterize potential differences in output arising from changes to hardware or firmware.
Methods: An orbital shaker generated accelerations from 0 to 3700 milli-g in a randomized order to test the wGT3X-BT, GT9X, CentrePoint Insight Watch (CPIW) 1.
Int J Behav Nutr Phys Act
January 2025
Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, 110 Xiangya Road, Changsha, 410078, Hunan, China.
Background: Low physical activity (LPA) is a leading risk factor for type 2 diabetes mellitus (T2DM). We examine the temporal and spatial trends in the burden of T2DM attributable to LPA at the global, regional, and country scales.
Methods: Data were obtained from the Global Burden of Disease Study 2021.
Nutr J
January 2025
Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Background: The role of carbohydrates in diabetes risk is of particular interest due to conflicting results. This study aims to examine the prospective association between types of dietary carbohydrates (fiber, starch, total sugar, glucose, fructose, lactose, maltose, and added sugar) and the risk of diabetes. Further, this study examines the cross-sectional associations between these nutrients and cardiometabolic risk factors.
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