contribution of Physical Fitness component to health Status in elderly Males and Females over 60 years – Short Report Corresponding

Corresponding Author: Paseo de Martirícos, S / N. Physiotherapy Area, Department of Psychiatry and Physiotherapy, University of Malaga, Malaga. 29009. E­mail: acuesta@uma.es. AbSTrAcT: The purpose of this study was to identify the physical fitness (PF) level of a cohort of elderly people that are subjected to physical activity (PA), and to establish a regression model for the evaluation of health status (HS) of elderly people based on their PF. This is a Cross-sectional study. Consists of 114 Participants over 60 years old, that were recruited from a physical activity program. Were measured variables about anthropometric characteristics, jumping tests with jumping platform, dynamic and static balance, risk of falls, lung capacity, HS and quality of life (QoL). We used Pearson’s linear correlation with 95% Zr. We looked for simple and multiple regression models. We used the bayesian information criterion approach and statistical inference to find and calculated a numerical estimate of the best regression model. We used the dependent variable physical function of SF-12. Physical fitness variables selected for the models were weight, height, Countermovement Jump test (flight time), Functional Reach test, lumbosacral flexion mobility, Extended Timed Get Up and Go (ETGUG) (10 meters time score and total time score). The HS and QoL measurement are important for the prevention of injury during physical exercise and should be conducted whenever is possible. The regression models proposed in this study can be used as an initial screening of HS or QoL at fitness facilities and fitness clubs that do not provide HS or QoL questionnaires. However, these models are not an alternative to health care for a detailed determination of HS and is not intended for use as a final evaluation.


INTRODUCTION
The World Health Organization defines Health as a state of complete physical and mental wellbeing and not merely the absence of disease or infirmity (ACSM 2000).Physical Fitness (PF) is a multifactorial concept that includes characteristics such as body size and shape, weight, body mass index, mor photype, susceptibility to disease and disorders, sensory acuity, functional difficulty, body functioning, recupera tive ability, the ability to perform certain the American Heart Association pre sented an update where the ACSM took into consideration the recommendations regarding physical activity in the older American adult population (Haskell et al. 2007).The actual number of facili ties with systems for the determination of Health Status (HS), including medical checkups, HS and Quality of Life (QoL) questionnaires, PF tests, is limited due to the lack of operating funds and staff able to handle the equipment used for such purposes (Scheinowitz et al 2008).The results indicated that HS and level of PF were closely correlated (Sato et al 2005, Sato et al 2006, Sato et al 2007, Sato et al 2009).
Therefore, the aim of this study was to examine in males, females and both together, the relationship between a set of selfreport clinical variables, related to the Short Form Health Survey (SF12) and the EuroQol5D (EQ5D), to directly measure physical variables related to strength, mobility, dynamic and static balance and spirometry.The second purpose of this study was to identify the PF level in a cohort of elderly people subjected to a PA program

MATERIAL AND METHODS
Participants.This study presents a crosssectional study with 114 par ticipants (63 female and 51 male).The mean age of participants was 70.17 years with a standard deviation of 7.3 years and they were recruited for a PA program following the lines of ACSM.

It was approved by the Research Ethics
Committee of the University of Málaga.After committee approval, we initiated subject recruitment with the corre sponding informed written consent.We performed an assessment of individual functional abilities.
Physical Fitness Test.The physical fitness variables selected for the models were weight, height, Countermovement Jump test (flight time), Functional Reach test, lumbosacral flexion mobi lity, Extended Timed Get Up and Go (ETGUG) (10 meters time score and total time score).The values of the physical fitness assessment are shown in Table 1.

Evaluation of Health Status
Health Status Questionnaire with the short-form SF-12.The measurement of the HS was determined by questionnaire shortform SF12, adapted from the long version SF36.We studied the physical and mental component.The reliability of the SF12 has demonstrated a high internal consistency with an ICC close to 0.9 (Vigalut et al 2005) Quality of life related to health with the EuroQol-5D questionnaire.EuroQol 5D is a multidimensional measure of QoL related to health.The reliability and validity of the questionnaire EuroQol 5D has been demonstrated in studies of validity and reliability, with ICC of 0.90 (Janssen et al 2008) Data Analysis.The analysis was guided to the search of differents correlations between clinical variables of QoL and measured physical variables, related to weight, height, and lumbosacral flexion mobility, as well as the Countermovement Jump Test, the Functional Reach Test, and the Time Up and Go Test.

Predictors of HS and QoL in older adults
Although the link between functional variables and psychometric variables of physical fitness are often mentioned, few studies have systematically investigated this relationship.To our knowledge, pre vious studies have identified a detailed conceptual relationship between these components, but in most cases do not provide quantitative data.Regarding increased HS in the elderly, the PF level must be maintained and increased together with appropriate physical acti vities and an exercise program (ACSM 2000).There have only been a few studies on the quantitative relationship, although many conceptual relationship studies have been performed.However, in most cases, the correlation level was determined by simple correlation and only a qualitative description of the process.
Our results suggest that the independ ent variables (related to HS and QoL) could explain 54.7% (p < 0.05) in males, 46.6% (p < 0.05) in female, and 44% (p < 0.001) in both together of the variance in elderly people over 60 years of age.These results show that it is possible to correctly discriminate health status by the level of physical fitness, which is usually considered to be inde pendent of health.This also means that health status can be discriminated with a relatively high degree of accuracy by age and different physical fitness tests results.
As in our study, one recent study (Sato et al 2009) has demonstrated a relation ship between anatomy and/or function and healthrelated quality of life.In this study, we measured PF by 11 variables (height, weight, BMI, % fat, prehensile strength, flexibility, balance, agility, muscular strength, cardiovascular health and age) and PF was measured using 10 tests and 24 variables (height, weight, BMI, lumbosacral flexion mobility, jumping, static and dynamic balance and spirometry).This recent study (Sato et HS and physical fitness variables of lumbar sagittal mobility, vertical jump, dynamic and static balance and lung function.We looked for simple and multiple regresión models.We proposed diferents multiple regression models to evaluate HS in males, females and both together, we used the bayesian infor mation criterium approach and statis tical inference to find and calculated a numerical estimate of the best variables to use in these models.We used SPSS for Windows V 15.0.

RESULTS
The mean values and range of measure for each PF test item for the group are shown in Table 2.
From the Pearson's linear correla tion analyses, significant differences were found between the physical vari ables and the clinical variables: physical component of SF12 and Time Up Go Finally, the most seven relevant phy sically variables were localized using the Bayesian filtering approach: Weight, Size, Countermovement Jump test (flight time), Functional Reach test, lumbosac ral flexion mobility, Extended Timed Get Up and Go (ETGUG) (10 meters time score and total time score).A multiple regression analysis was performed using the physical component of the SF12 how to depedent variable and the seven relevant variables how to predictor vari ables.We have found a significant model for the physical component of SF12 for the males (p<0.05),females (p<0.05) and both together (p<0.01).The details of models are represented on table 3.

DISCUSSION
The main finding from this study was that a set of selfreported clinical vari ables, related to HS and QoL, could be explained through different directly al 2009) estimated HS using different models with different variables, with the PF level varying from 66.5% to 76.4%.The authors found that increased age increased the probability of becoming ill and also increased the individual dif ferences in PF levels (Sato et al 2009).The presents study estimated the HS in elderly people over 60 years with a model where the PF level intervening in 44% in the HS for both male and female (p < 0.01), 54.7% in the HS for male sample (p<0.05) and 46.6% in the HS for female sample (p<0.05).
According our results, we have con firmed the strong influence of different musculoskeletal components to HS and QoL.Similar to the findings of our study on musculoskeletal fitness, one previous study (Kell et al 2001) revealed that if the musculoskeletal components are not maintained, musculoskeletal fitness is then compromised which can signifi cantly impact physical health and well being.Many other studies have identified this relationship between musculoske letal components and their impact on HS and QoL.Research based on exercise prescription for the elderly (Mazzeo et al 2001) has concluded that cardiovascu lar and resistance training programs are beneficial to HS and QoL.This finding was similar to those of another study (Kell et al 2001) as well as the results presented in this study, where we con firmed that many health benefits are associated with musculoskeletal fitness.Another study investigating endurance exercise training (Huang et al 2005) quantified the relationship between dif ferent physical variables of the muscu loskeletal system and QoL and HS.
Regarding the effectiveness, volume and intensity, and the quantification of the doseresponse effect of a multi modal program of physical exercise in the elderly, there are several studies of interest, but some limits have been iden tified.Research on the effectiveness of physical activity interventions (Van Der Bij et al 2002) have provided evidence on the best interventions with high suc cess rates in initiating and maintaining PA.Another study (Baker et al 2007)

Double inclinometry (degree)
The dual inclinometer IQ DUAL ® JtechMedical was used as follows, the primary inclinometer is placed on the space between T12-L1 vertebral segments and the secondary inclinometer on S1 segment, then the patient have to make a maximum trunk flexion with hands together, arms extended and holding the knees in extension Pearson correlation of 0.96 to 0.99 (Waddell et al 1992)

Jump
Countermovement Jump test: Flight time (seconds) Vertical mark (cm) The GLOBUS ERGOJUMP ® platform-jumping was used as follows, the subject on the platform, jump from the standing position with hands placed under the height of the iliac spines anterosuperiores there is a rapid exten sion and flexion of the knee joint with minimal stop between the concentric and eccentric phases Interclass correlation index of 0.88 for the Countermovement Jump Test (Slinde et al 2008)

Static and dynamic balance
Functional Reach test (cm) Extended Timed Get Up and Go (ETGUG) (seconds) The difference, in centimetres, between arm's length and maximal forward reach, using a fixed base of support The person is asked to stand up from a standard chair and walk a distance of approximately 10 meters, turn around and walk back to the chair and sit down again Functional Reach test and the Time Up and Go Extended test have been correlated in a specific study, identifying a ICC of> 0.9 (Russel et al 2008).
lung Function

FEV1s (milliliters)
FEV6s (milliliters) FEV1s/FEV6s (milliliters) The amount of air that you can forcibly blow out in one second The volume that is ejected in the first six seconds of a forced exhalation Ratio FEV1s / FEV6s In healthy adults, this should be approximately 75-80% (Tiffenau et al 1956)  The clinical implication of this study is that, having identified the clinical predictor variables that improve the per ception of health status and quality of life, and given that some of these factors are modifiable, there is some potential for interventions to selectively increase the perception of health status and quality of life in healthy older adults.Providing interventions for older adults with high body weight, lower strength in the lower limbs, poor mobility in terms of lumbosacral flexion and poor balance may also increase the perception of health status and quality of life.

CONCLUSSION
The PF level of the participants was calculated using ten test and twenty four difirent physical variables.The effective ness of the variables was examined using the bayesian filtering approach and sta tistical inference.We found a significant relationship between differents clinical and physical variables in the simple and multivaiant correlation examinations.
The HS and QoL measurement are important for the prevention of injury during physical exercise and should be conducted whenever is possible.The regression models proposed in this study can be used as an initial screening of HS or QoL at fitness facilities and fitness clubs that do not provide HS or QoL questionnaires.However, these models are not an alternative to health care for a detailed determination of HS and is not intended for use as a final evaluation.
Extended total time score (index cor relation = 0.328 p<0.01),Euroqol total score and Time Up and Go Exended total time score (index correlation = 0.309 p<0.01),Euroqol visual analogue scale and Time Up and Go Exended total time score (index correlation = 0.340 p<0.01),Euroqol visual analogue scale and vertical mark in Countermovement Jump Test (index correlation = 0.299 p<0.01).