Multisystem physiological perspective of human frailty and its modulation by physical activity.

"Frailty" is a term used to refer to a state characterized by enhanced vulnerability to, and impaired recovery from, stressors compared with a nonfrail state, which is increasingly viewed as a loss of resilience. With increasing life expectancy and the associated rise in years spent with physical frailty, there is a need to understand the clinical and physiological features of frailty and the factors driving it. We describe the clinical definitions of age-related frailty and their limitations in allowing us to understand the pathogenesis of this prevalent condition. Given that age-related frailty manifests in the form of functional declines such as poor balance, falls, and immobility, as an alternative we view frailty from a physiological viewpoint and describe what is known of the organ-based components of frailty, including adiposity, the brain, and neuromuscular, skeletal muscle, immune, and cardiovascular systems, as individual systems and as components in multisystem dysregulation. By doing so we aim to highlight current understanding of the physiological phenotype of frailty and reveal key knowledge gaps and potential mechanistic drivers of the trajectory to frailty. We also review the studies in humans that have intervened with exercise to reduce frailty. We conclude that more longitudinal and interventional clinical studies are required in older adults. Such observational studies should interrogate the progression from a nonfrail to a frail state, assessing individual elements of frailty to produce a deep physiological phenotype of the syndrome. The findings will identify mechanistic drivers of frailty and allow targeted interventions to diminish frailty progression.

An Empirical Investigation of Variance Design Parameters for Planning Cluster-Randomized Trials of Science Achievement.

BACKGROUND: Prior research has focused primarily on empirically estimating design parameters for cluster-randomized trials (CRTs) of mathematics and reading achievement. Little is known about how design parameters compare across other educational outcomes. OBJECTIVES: This article presents empirical estimates of design parameters that can be used to appropriately power CRTs in science education and compares them to estimates using mathematics and reading. RESEARCH DESIGN: Estimates of intraclass correlations (ICCs) are computed for unconditional two-level (students in schools) and three-level (students in schools in districts) hierarchical linear models of science achievement. Relevant student- and school-level pretest and demographic covariates are then considered, and estimates of variance explained are computed. Subjects: Five consecutive years of Texas student-level data for Grades 5, 8, 10, and 11. MEASURES: Science, mathematics, and reading achievement raw scores as measured by the Texas Assessment of Knowledge and Skills. Results: Findings show that ICCs in science range from .172 to .196 across grades and are generally higher than comparable statistics in mathematics, .163-.172, and reading, .099-.156. When available, a 1-year lagged student-level science pretest explains the most variability in the outcome. The 1-year lagged school-level science pretest is the best alternative in the absence of a 1-year lagged student-level science pretest. CONCLUSION: Science educational researchers should utilize design parameters derived from science achievement outcomes.