Contribution of physical fitness component to health status in middle-aged and elderly males.
01 Sep 2006-Journal of Physiological Anthropology (Japan Society of Physiological Anthropology)-Vol. 25, Iss: 5, pp 311-319
TL;DR: There is a relatively high relationship between health status and physical fitness level for middle-aged and elderly females, and the result of this study is considered to be useful as objective data to prepare an exercise program considering the contribution of the physical fitness component of health status.
Abstract: This study determined the physical fitness component that contributes to improving and maintaining health status for each age group as well as quantifying the degree of the relationship between health status and physical fitness in middle-aged and elderly females. The participants were 2,371 females aged 30 to 69 years. Ten physical fitness tests and medical checkups were performed. The participants were divided into a healthy group and an unhealthy group according to health status. Multiple discriminant analysis was applied to the multivariate data. Correct discriminant probabilities of the multiple discriminant function to discriminate the healthy and unhealthy groups for females ranged from 63.0% to 77.5%. These results suggest that there is a relatively high relationship between health status and physical fitness level for middle-aged and elderly females. With each individual's discriminant score calculated by the obtained multiple discriminant function as the index of the degree of health, the Pearson's correlation coefficient of the discriminant score and the performance in each physical fitness test were calculated. The aging change from 30 to 69 years old was classified into four patterns according to the contribution. The result of this study is considered to be useful as objective data to prepare an exercise program considering the contribution of the physical fitness component of health status.
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TL;DR: One-leg standing time with eyes open, timed up-and-go test and grip strength proved to be easy, reliable and safe performance tests to evaluate and monitor an individual’s severity of LS as a complement to the GLFS-25.
79 citations
Cites background from "Contribution of physical fitness co..."
...sive set of physical performance tests that are associated with QOL or ADLs [20, 21]....
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...The timed up-and-go test was found to predict ADLs disability [20]....
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TL;DR: In this paper, the authors established reference values for these major physical performance tests with regards to diagnosing and assessing risk of locomotive syndrome (LS), and used them to evaluate locomotive safety.
63 citations
Cites background from "Contribution of physical fitness co..."
...Having our participants complete an extensive series of major physical performance tests that are known to be associated with QOL or ADLs [16, 17] is a strength of our study....
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TL;DR: Low back and knee pain proved to be significant contributors to individuals’ QOL, and TUG might be the most valuable function test for effectively evaluating an individual’s QOL.
44 citations
Cites background from "Contribution of physical fitness co..."
...Of the physical function tests, the TUG score was also strongly associated with QOL, and TUG was reported to be able to predict ADLs disability [27]....
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TL;DR: Unipedal stance time was the physical performance measure that was most strongly associated with LS, and may be useful for early detection of LS.
Abstract: BACKGROUND:: The Japanese Orthopaedic Association proposed a concept called locomotive syndrome (LS) to identify middle-aged and older adults at high risk of requiring health care services because of problems with locomotion. It is important to identify factors associated with the development of LS. Physical performance measures such as walking speed and standing balance are highly predictive of subsequent disability and mortality in older adults. However, there is little evidence about the relationship between physical performance measures and LS. PURPOSE:: To determine the physical performance measures associated with LS, the threshold values for discriminating individuals with and without LS, and the odds ratio of LS according to performance greater than or less than these thresholds in middle-aged and older Japanese women. METHODS:: Participants were 126 Japanese women (mean age = 61.8 years). Locomotive syndrome was defined as a score of 16 or more on the 25-question Geriatric Locomotive Function Scale. Physical performance was evaluated using grip strength, unipedal stance time with eyes open, seated toe-touch, and normal and fast 6-m walk time (6MWT). Variables were compared between LS and non-LS groups. RESULTS:: Fourteen participants (11.1%) were classed as having LS. Unipedal stance time, normal 6MWT, and fast 6MWT were significantly different between the 2 groups. The LS group had a shorter unipedal stance time and a longer normal and fast 6MWT than the non-LS group. For these 3 variables, the area under the receiver operating characteristic curve was greater than 0.7, and the threshold for discriminating the non-LS and LS groups was 15 s for unipedal stance time, 4.8 s for normal 6MWT and 3.6 s for fast 6MWT. These variables were entered into a multiple logistic regression analysis, which indicated that unipedal stance time less than 15 s was significantly related to LS (odds ratio = 8.46; P CONCLUSION:: Unipedal stance time was the physical performance measure that was most strongly associated with LS. This measure may be useful for early detection of LS. Language: en
24 citations
TL;DR: In both men and women, the predictive power of the young and middle-age groups was better than that of the elderly groups for predicting normal waist and viscerally obese subjects for both the individual and combined characteristics.
Abstract: Visceral obesity is associated with facial characteristics and chronic disease, but no studies on the best predictor of visceral obesity based on facial characteristics have been reported. The aims of the present study were to investigate the association of visceral obesity with facial characteristics, to determine the best predictor of normal waist and visceral obesity among these characteristics, and to compare the predictive power of individual and combined characteristics. Cross-sectional data were obtained from 11347 adult Korean men and women ranging from 18 to 80 years old. We examined 15 facial characteristics to identify the strongest predictor of normal and viscerally obese subjects and assessed the predictive power of the combined characteristics. FD_94_194 (the distance between both inferior ear lobes) was the best indicator of the normal and viscerally obese subjects in the following groups: Men-18-50 (p ≤ 0.0001, OR = 4.610, AUC = 0.821), Men-50-80 (p ≤ 0.0001, OR = 2.624, AUC = 0.735), and Women-18-50 (p ≤ 0.0001, OR = 2.979, AUC = 0.76). In contrast, FD_43_143 (mandibular width) was the strongest predictor in Women-50-80 (p ≤ 0.0001, OR = 2.099, AUC = 0.679). In a comparison of the combined characteristics, the area under the receiver operating characteristic curve (AUC) and the kappa values of the 4 groups ranged from 0.826 to 0.702 and from 0.483 to 0.279, respectively. The model for Men-18-50 showed the strongest predictive values and the model for Women-51-80 had the lowest predictive value for both the individual and combined characteristics. In both men and women, the predictive power of the young and middle-age groups was better than that of the elderly groups for predicting normal waist and viscerally obese subjects for both the individual and combined characteristics. The predictive power appeared to increase slightly with the combined characteristics.
23 citations
References
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TL;DR: This book deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material.
Abstract: Chapter 3 deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material. Chapter 4 is a detailed study of the concept of utility including the psychological aspects, risk, attributes, rules for utilities, multidimensional utility, and normal form of analysis. Chapter 5 treats games and optimization, linear optimization, and mixed strategies. Entropy is the topic of Chapter 6 with sections devoted to entropy, disorder, information, Shannon’s theorem, demon’s roulette, Maxwell– Boltzmann distribution, Schrodinger’s nutshell, maximum entropy probability distributions, blackbodies, and Bose–Einstein distribution. Chapter 7 is standard statistical fare including transformations of random variables, characteristic functions, generating functions, and the classic limit theorems such as the central limit theorem and the laws of large numbers. Chapter 8 is about exchangeability and inference with sections on Bayesian techniques and classical inference. Partial exchangeability is also treated. Chapter 9 considers such things as order statistics, extreme value, intensity, hazard functions, and Poisson processes. Chapter 10 covers basic elements of risk and reliability, while Chapter 11 is devoted to curve fitting, regression, and Monte Carlo simulation. There is an ample number of exercises at the ends of the chapters with answers or comments on many of them in an appendix in the back of the book. Other appendices are on the common discrete and continuous distributions and mathematical aspects of integration.
19,893 citations
Journal Article•
TL;DR: These definitions are offered as an interpretational framework for comparing studies that relate physical activity, exercise, and physical fitness to health.
Abstract: "Physical activity," "exercise," and "physical fitness" are terms that describe different concepts. However, they are often confused with one another, and the terms are sometimes used interchangeably. This paper proposes definitions to distinguish them. Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure. The energy expenditure can be measured in kilocalories. Physical activity in daily life can be categorized into occupational, sports, conditioning, household, or other activities. Exercise is a subset of physical activity that is planned, structured, and repetitive and has as a final or an intermediate objective the improvement or maintenance of physical fitness. Physical fitness is a set of attributes that are either health- or skill-related. The degree to which people have these attributes can be measured with specific tests. These definitions are offered as an interpretational framework for comparing studies that relate physical activity, exercise, and physical fitness to health.
7,608 citations
"Contribution of physical fitness co..." refers background in this paper
...Conceptually, health status can be closely related to physical fitness, as expressed by the term “health-related physical fitness” (American College of Sports Medicine, 1988; Caspersen et al., 1985)....
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...Conceptually, health status can be closely related to physical fitness, as expressed by the term “health-related physical fitness” (American College of Sports Medicine, 1988; Caspersen et al., 1985)....
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Book•
30 Aug 2004
TL;DR: This report is the first report of the Surgeon General on physical activity and health, and strong evidence is shown to indicate that regular physical activity will provide clear and substantial health gains.
Abstract: : This report is the first report of the Surgeon General on physical activity and health. For more than a century, the Surgeon General of the Public Health Service has focused the nation's attention on important public health issues. Reports from Surgeons General on the adverse health consequences of smoking triggered nationwide efforts to prevent tobacco use. Reports on nutrition, violence, and HIV/AlDS - to name but a few - have heightened America's awareness of important public health issues and have spawned major public health initiatives. This new report, which is a comprehensive review of the available scientific evidence about the relationship between physical activity and health status, follows in this notable tradition. Scientists and doctors have known for years that substantial benefits can be gained from regular physical activity. The expanding and strengthening evidence on the relationship between physical activity and health necessitates the focus this report brings to this important public health challenge. Although the science of physical activity is a complex and still-developing field, we have today strong evidence to indicate that regular physical activity will provide clear and substantial health gains. In this sense, the report is more than a summary of the science - it is a national call to action.
5,107 citations
Book•
01 Jan 1971
TL;DR: In this paper, the authors propose a multivariate analysis of variance for multidimensional scaling and correspondence analysis using a Structural Equation Modeling (SEM) approach.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance IV Interdependence Techniques 7 Cluster Analysis 8 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 9 Structural Equation Modeling: Overview 10 Appendix - SEM 10a CFA: Confirmatory Factor Analysis 11 Appendix - CFA 11a SEM: Testing A Structural Model 12 Appendix - SEM 12a Conjoint Analysis APPENDIX A Basic Stats
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TL;DR: The results do, however, question whether the current classification of individuals as "overweight" is optimal in the sense, since there is little evidence of increased risk of mortality in this group, and the results do not document once again, excess mortality associated with obesity.
571 citations
"Contribution of physical fitness co..." refers background in this paper
...In a study on the relationship between BMI and a disease, it was reported (McGee, 2005) that BMI exceeding the standard is not healthy, and it is considered that weight and BMI are effective as characteristic of the degree of health regardless of age....
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