Carol Ewing Garber

Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory, Musculoskeletal, and Neuromotor Fitness in Apparently Healthy Adults: Guidance for Prescribing Exercise

SUMMARYThe purpose of this Position Stand is to provide guidance to professionals who counsel and prescribe individualized exercise to apparently healthy adults of all ages. These recommendations also may apply to adults with certain chronic diseases or disabilities, when appropriately evaluated and

ACSM Position Stand: The Recommended Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory and Muscular Fitness, and Flexibility in Healthy Adults

SUMMARYACSM Position Stand on The Recommended Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory and Muscular Fitness, and Flexibility in Adults. Med. Sci. Sports Exerc., Vol. 30, No. 6, pp. 975-991, 1998. The combination of frequency, intensity, and duration of chr

Effects of fatigue on physical activity and function in patients with Parkinson's disease.

Objective: To characterize the relationships between symptoms of fatigue, physical activity, physical function, and functional capacity in patients with idiopathic PD. Methods: Thirty-seven patients with PD underwent evaluation of physical activity, physical function, functional capacity, and fatigue. Physical activity and fatigue were measured by standard questionnaires (Godin Leisure Activity Questionnaire, Yale Physical Activity Questionnaire, and Fatigue Severity Scale); physical function was measured by the Up and Go Test and the Six-Minute Walk; and functional capacity was measured by a maximal oxygen uptake exercise test (VO2max). Results: Increased levels of fatigue were associated with decreased levels of leisure physical activity, lower frequency of vigorous physical activity, less time spent moving about performing daily tasks each day, lower diastolic blood pressure and VO2max, longer Up and Go performance time, and carbidopa–levodopa (CL) use. A multiple regression analysis was performed to determine factors predicting fatigue (Fatigue Severity Scale). The Up and Go Test, Leisure Activity Score, CL use, VO2max, and diastolic blood pressure were the best predictor variables of fatigue. The Up and Go Test and CL use contributed independently to the model, whereas the other variables appeared to moderate the relationships between these variables. Conclusions: PD patients with more severe fatigue are more sedentary and have poorer functional capacity and physical function compared with patients with less fatigue.

Updating ACSM's Recommendations for Exercise Preparticipation Health Screening.

The purpose of the American College of Sports Medicines (ACSM) exercise preparticipation health screening process is to identify individuals who may be at elevated risk for exercise-related sudden cardiac death and/or acute myocardial infarction. Recent studies have suggested that using the current ACSM exercise preparticipation health screening guidelines can result in excessive physician referrals, possibly creating a barrier to exercise participation. In addition, there is considerable evidence that exercise is safe for most people and has many associated health and fitness benefits; exercise-related cardiovascular events are often preceded by warning signs/symptoms; and the cardiovascular risks associated with exercise lessen as individuals become more physically active/fit. Consequently, a scientific roundtable was convened by the ACSM in June 2014 to evaluate the current exercise preparticipation health screening recommendations. The roundtable proposed a new evidence-informed model for exercise preparticipation health screening on the basis of three factors: 1) the individuals current level of physical activity, 2) presence of signs or symptoms and/or known cardiovascular, metabolic, or renal disease, and 3) desired exercise intensity, as these variables have been identified as risk modulators of exercise-related cardiovascular events. Identifying cardiovascular disease risk factors remains an important objective of overall disease prevention and management, but risk factor profiling is no longer included in the exercise preparticipation health screening process. The new ACSM exercise preparticipation health screening recommendations reduce possible unnecessary barriers to adopting and maintaining a regular exercise program, a lifestyle of habitual physical activity, or both, and thereby emphasize the important public health message that regular physical activity is important for all individuals.

Construct Validity of the Stages of Change of Exercise Adoption for Different Intensities of Physical Activity in Four Samples of Differing Age Groups.

Purpose. To examine whether the stages of change of exercise adoption appropriately address strenuous, moderate, and mild intensities of physical activity. Design and Setting. Secondary analysis of four data sets investigating transtheoretical model (TTM) constructs for exercise adoption. Subjects. Four samples of differing age groups (adolescents, n = 400; college students, n = 240; adults, n = 346; seniors, n = 504). Measures. Stage of change algorithm for exercise adoption and self-reported physical activity. Results. Multivariate analysis of variance (MANOVA) results showed that stages of change were distinguished by strenuous and moderate but not mild exercise in the adolescent, college student, and adult sample. In the senior sample, stage differences were found in the frequency of exercising (equivalent for moderate to strenuous exercise) and the frequency of walking (equivalent for mild exercise). Bivariate correlation coefficients as well as sensitivity, specificity, and related quality indices decreased respectively from strenuous to moderate to mild exercise and from exercising to walking. Conclusions. Results provide additional support for the construct validity of the stages of change for strenuous and moderate intensities of physical activity. Development of a new stage assessment instrument for mild intensities of physical activity is recommended. Limitations include use of a different validation measure of exercise behavior in the senior sample.

The Relationship Between Obesity, Physical Activity, and Physical Function in Older Adults

Objective: This study investigated the relationship between overweight and obesity, age, and gender with physical activity and physical function in community-dwelling older men and women. Method: Multivariate analysis of covariance was used to analyze differences between normal weight, overweight, and obese adults (n = 821) above the age of 60 years. Results: Obesity but not overweight was associated with lower levels of physical activity and physical function. Within BMI groups, individuals who were physically active were less likely to have abnormal physical function scores compared to those who were sedentary. Compared to men, obese women had lower physical function scores, placing them at higher risk for future disability. Aging was associated with lower levels of physical activity and physical function. Discussion: The study illustrates the importance of avoiding obesity and participating in regular physical activity to prevent or slow down the loss of functioning in older age.

Physical activity, physical fitness, and coronary heart disease risk factors.

The relationships between physical activity, physical fitness, and coronary heart disease risk factors measured in a large community sample were evaluated. Self-reported physical activity using a single question, maximal oxygen consumption estimates derived from the Pawtucket Heart Health Step Test, blood pressure, nonfasting lipids, and body mass index were cross-sectionally evaluated in 381 men and 556 women. The correlation of estimated maximal oxygen consumption and self-reported physical activity was modest but statistically significant (r = 0.13 in men and r = 0.19 in women). Blood pressure, body mass index, and HDL cholesterol were correlated with physical fitness (r = 0.24-0.65) and correlated to self-reported physical activity (r = 0.09-0.14). Evaluation of coronary heart disease risk factors using both physical activity and physical fitness revealed a complex relationship that generally showed a stronger relationship with measures of physical fitness than with physical activity. This study suggests that simultaneous measurement of physical activity and physical fitness may be useful in epidemiologic studies of habitual physical activity and chronic disease.

Physical and mental health-related correlates of physical function in community dwelling older adults: a cross sectional study

BackgroundPhysical function is the ability to perform both basic and instrumental activities of daily living, and the ability of older adults to reside in the community depends to a large extent on their level of physical function. Multiple physical and health-related variables may differentially affect physical function, but they have not been well characterized. The purpose of this investigation was to identify and examine physical and mental health-related correlates of physical function in a sample of community-dwelling older adults.MethodsNine hundred and four community dwelling older men (n = 263) and women (n = 641) with a mean (95% Confidence Interval) age of 76.6 (76.1, 77.1) years underwent tests of physical function (Timed Up and Go; TUG), Body Mass Index (BMI) was calculated from measured height and weight, and data were collected on self-reported health quality of life (SF-36), falls during the past 6 months, number of medications per day, depression (Geriatric Depression Scale; GDS), social support, and sociodemographic variables.ResultsSubjects completed the TUG in 8.7 (8.2, 9.2) seconds and expended 6,976 (6,669, 7,284) Kcal.wk-1 in physical activity. The older persons had a mean BMI of 27. 6 (27.2, 28.0), 62% took 3 or more medications per day, and14.4% had fallen one or more times over the last 6 months. Mean scores on the Mental Component Summary (MCS) was 50.6 (50.2, 51,0) and the Physical Component Summary (PCS) was 41.3 (40.8, 41.8).Multiple sequential regression analysis showed that, after adjustment for TUG floor surface correlates of physical function included age, sex, education, physical activity (weekly energy expenditure), general health, bodily pain, number of medications taken per day, depression and Body Mass Index. Further, there is a dose response relationship such that greater degree of physical function impairment is associated with poorer scores on physical health-related variables.ConclusionsPhysical function in community-dwelling older adults is associated with several physical and mental health-related factors. Further study examining the nature of the relationships between these variables is needed.

Relationship between physical activity and general mental health

PURPOSE We investigated the relationship between physical activity and mental health and determined the optimal amount of physical activity associated with better mental health. METHOD Self-reported data from a national random sample of 7674 adult respondents collected during the 2008 U.S. Health Information National Trends 2007 Survey (HINTS) were analyzed in 2012. Mental health was plotted against the number of hours of physical activity per week using a fractional 2-degree polynomial function. Demographic and physical health factors related to poorer mental health were examined. The optimal range of physical activity associated with poorer mental health was examined by age, gender, and physical health. RESULTS A curvilinear association was observed between physical activity and general mental health. The optimal threshold volume for mental health benefits was of 2.5 to 7.5h of weekly physical activity. The associations varied by gender, age, and physical health status. Individuals who engaged in the optimal amount of physical activity were more likely to have reported better mental health (odds ratio=1.39, p=0.006). CONCLUSIONS This study established a hyperbolic dose-response relationship between physical activity and general mental health, with an optimal range of 2.5 to 7.5h of physical activity per week.

Correlates of the Stages of Change for Physical Activity in a Population Survey

OBJECTIVES We sought to identify variables associated with being in a particular stage of change for physical activity-a measure of behavioral intention to engage in regular physical activity. Understanding behavioral intentions can be useful in explaining why individuals are physically inactive or active. METHODS Data from the Rhode Island 2000 Behavioral Risk Factor Surveillance System were used to evaluate predictors of stage of change for physical activity. There were 3454 observations in the data set, representing a weighted population of 742636 people. Estimates were obtained from polytomous multiple logistic models. RESULTS Being a woman, Hispanic, non-Hispanic Black, and older than 55 years of age were associated with being in precontemplation and contemplation stages of change rather than maintenance. Self-perceived health status and rarely feeling healthy or full of energy were strongly predictive of stage of change. Having a health limitation was a dichotomous predictor, predicting being in action and precontemplation stages. CONCLUSIONS Several sociodemographic and health variables were associated with varying patterns of stages of change for physical activity. The complexity of individual intentions for physical activity provides evidence for the potential existence of mediating, effect-modifying, and confounding variables that differ depending on individual characteristics.