Original article Determination of functional f itness age in women aged 50 and older

Edgr Johni Ltorre-Rojs ,Jon Antoni Prt-Subirn ,Xvier Peiru-Terés ,SebstiàMs-Alòs ,c,*,JoséVicente Beltrán-Grrido ,d,Antoni Plns-Anzno

a National Institute of Physical Education of Catalonia,University of Lleida,Lleida,Catalonia E-25192,Spain

b Physical Fitness,Sport and Recreation Department,Floridablanca Campus,University Santo Tomás Aquino,Kilómetro 7 vía Floridablanca,Bucaramanga,Colombia

c Department of Nursery and Physiotherapy,University of Lleida,Lleida,Catalonia E-25198,Spain

d EUSESTE,Health and Sport Science School,Rovira i Virgili University,Amposta,Catalonia E-43870,Spain

Abstract Background:The construction of useful and attainable indicators of f itness assessment deserves special attention in clinical practice.We aimed to construct an indicator of thefunctional f itnessage(FFA)of women aged 50 and older by an equation using f itnessoutcomesand itscorrelation with chronological age(CA)and to analyze the external validity of our results by comparing our sample to others.Methods:Participants(n=459,age:70.3±7.9 years,mean±SD)were evaluated using the Senior Fitness Test battery.We applied a multiple regression and a subsequent Holt's exponential smoothing to analyze the outcomes.Results:We obtained a statistically signif icant expression of F(6,452)=328.384;p＜0.0005 in which the coeff icients of the equation explain 81%of variability(R2corrected=0.813).The equation correlates f itness assessment in women aged 50 and over with regards to CA:FFA=40.146+0.350×CS(stand)-0.714×AC(rep)-0.110×ST(step)-0.177×CSR(cm)-0.101×BS(cm)+8.835×FUG(s)where CS means chair stand test,ACmeans arm curl test,STmeans 2-min step test,CSRmeans chair sit-and-reach test,BSmeansback scratch test,FUG means 8-foot up-and-go test.We compared this index with percentiles distribution from our sample and from other studies.Conclusion:Wesuggest the use of FFA as avalid indicator of f itnessin adult and senior women as well asa useful motivational tool to undertake exercise programs.2095-2546/?2019 Published by Elsevier B.V.on behalf of Shanghai University of Sport.Thisisan open accessarticleunder the CCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords:Disability;Elderly;Exercise;Fitness assessment;Health outcomes;Senior Fitness Test

1.Introduction

Time is a standardized pattern in which humans situate numerous events that are interpreted unambiguously and universally.Associating the aging process to time enables referencing,positioning,and assessingthestatethat any organismor object is in.Biological age is a concept that can be understood as a progressive decrease in viability and increased vulnerability in the body over time,which ultimately leads to death.1Several authors have set algorithms related to biological age;2-7others established procedures for obtaining relevant indicators of aging in long-lived species;8and others even advise the use of theseindicators(e.g.,fat-freemasspercentage,grip strength,expiratory volume,cognitive and neuropsychological data)compared to other traditional indicators.9,10

The estimated spirometric lung age(i.e.,the age of the average healthy individual who would perform similar to them on spirometry)provides feedback that has been shown to improve the likelihood of smokers quitting smoking.11-13In relation to f itness and aging,several authors described the so-called f itness age score to intuitively evaluate the individual's corresponding physical f itness age.14-18Kimura et al.14recently determined 5 relevant f itness tests in relation to the f itnessagescore(i.e.,10 m walking time,functional reach,one leg stand with eyesopen,vertical jump,and grip strength)with a 7-year longitudinal study by applying the methods described by Ingram et al.8

Delimiting the concept of f itness to the elderly,we deem it more appropriate to use the term functional capacity,understood astheability to eff iciently carry out basic activities of daily living that peopleshould do to takecareof themselves and live independently and autonomously.19

Under this perspective,Rikli and Jones20-24build on the construction and validation of the Senior Fitness Test(SFT)battery,a set of tests resulted to be relevant for the functional f itnessin the elderly and that hasbeen used in other studies.25-26The SFT battery assesses lower body strength(30 s chair stand test(CS)),upper body strength(arm curl test(AC)),aerobic endurance(6-min walk test or the 2-min step test(ST)when space limitations),lower limb f lexibility(chair sit-and-reach test(CSR)),and upper limb f lexibility(back scratch test(BS)).

Kimuraet al.14test battery for elder populationsincludesthe vertical jump test,an osteoarticular and muscular demanding task that we consider less appropriate than the 30 s CStest for senior people because of risk of injury.27

A standardized method for assessing functional f itness age(FFA)in adult and senior women has not yet been established.Thisstudy aims(1)to obtain an indicator of the FFA of women aged 50and over by an equationusingthe SFToutcomesand its correlation with chronological age(CA)and(2)to analyze the external validity of our results by comparing our sample to others.

2.Materials and methods

2.1.Participants

The sample wasobtained from a total of 757 people attending 22 supervised exerciseprogramsoffered by the Lleida City Council(i.e.,1 h for 2-day weekly of calisthenics,Tai-Chi,and aquatic exercise)from September to May.Four hundred and f ifty-nine(61%)met thefollowing inclusion criteria:(1)female gender;(2)50 or older at the time of starting the study;(3)not suffering from any physical or mental illnessthatwould prevent them from performing any of the tests;(4)able to walk independently without the assistance of devices such as canes or walkers;and(5)accepting and signing theinformed consent to participate in the study.Participants were required to state that they had no medical contraindicationsfor physical activity programsand to hold medical insurance.Participants underwent a supervised exercise program for 6 months by the time of data collection,ranging from an estimated weekly metabolic consumption(measured in metabolic equivalent value(MET))of 336 MET-min(calisthenics)to 360 MET-min(Tai-Chi)to 660 MET-min(aquatic exercise).28,29No other information regarding other dimensions of physical activity behavior(e.g.,transportation,occupational)were available to determine if the samplewascompliant with theminimum recommendations on physical activity for health by the World Health Organization(600 MET-min a week).30The study was conducted according to the Declaration of Helsinki and the Medical Ethical Committee of the Hospital Arnau de Vilanova,Lleida,approved the protocol and the study.

2.2.Measurements

The SFT battery was used for data collection due to a scarcity of equipment and facilities and so we could compare our results with other studies.Fitness test administrators participated in a training seminar to be familiar with the SFT battery and be compliant with the protocols set by Rikli and Jones.24The battery included CS,AC,ST,CSR,BS,8-foot up-and-go test(FUG),and a measurement of body mass index(BMI)as weight per height squared.Data collection took place when the subjects participated in the 1-h exercise workout in March,6 months after the exercise programs started.Data collection continued for 5 weeksto includeall participantswho metinclusion criteria.Participants were advised to avoid any extended physical activity during the day before the test.

2.3.Statistical analysis

Weobtained percentilesin strataof 5 yearsof agefrom 50 to 87(except for the last group which was from 85 to 87).Then,we applied a multiple regression model using the include method to establish the FFA by means of the SFT battery outcomes and data,that is,CS,AC,ST,CSR,BS,FUG,and BMI.The following application conditions were checked:sample size,metric variables,normality,linearity,absence of multicollinearity,normality of residuals,independence of residuals,and homoscedasticity.31,32Weconducted Holt'sexponential smoothing equation to predict the FFA.The statistical software package SPSSVersion 17.0 for Windows(SPSSInc.,Chicago,IL,USA)was used for all statistical analyses.

3.Results

3.1.Fitness outcomes

Table 1 shows the correlation coeff icients between the participants'age,BMI,and results on SFT battery outcomes.Table 2 showsdescriptive statisticsby age group and theeffect size(ES)between 2 contiguous age groups.

3.2.Functional f itness age equation

The estimated regression model was statistically signif icant,F(6,452)=328.384,p＜0.0005.The goodness of f it for the model is R2corrected=0.813.Among the f itness outcomes,FUG had the greatest inf luence on FFA(β=0.689),while BS(β=-0.052)and CSR(β=-0.074)were the 2 f itness components with a lowest inf luence on FFA.BMIwas removed from the equation given its small contribution(＜1%)(Table 3).

The multiple regression equation for predicting FFA is as follows:

The analysis of the relationship between CA and FFA indicated that both increasesimultaneously and aredirectly proportional.We also observed that only 4%of participants(n=20)were outside the 95%conf idence interval(Fig.1).

The age difference(year)was calculated as age_dif=FFA-CA.The mean score was 0.0173 years(±9.19,minimum=-23.14,and maximum=37.92)(Fig.2).

Table1Correlation coeff icients between the Senior Fitness Test battery outcomes and participants'age and BMI(n=459).

Table2Senior Fitness Test battery scores for age groups(n=459).

Table3Multiple regression coeff icients and constant.

3.3.Equation adequacy compared to percentile values

We obtained percentilesof each SFT outcomefor women in Lleida according to the CA(in 5-year strata).Each participant had a global score,that is,the mean value of the percentiles from the 6 fitness tests.Fig.3 represents this global score and its relationship with the age_dif.

There is a signif icant linear association (R2=0.66,p＜0.005)and an inverse proportionality between age_dif and the global score of percentiles.That is,a smaller mean value in the percentiles relates to a more positive difference between FFA and CA(less functional f itness than predicted by CA).Otherwise,participants who obtained better ratings in the global score showed lower FFA than CA(greater functional f itness that predicted by CA).

Fig.1.Relationship between FFA and CA resulting from the multiple regression equation for predicting the FFA.Discontinuous lines show the 95%conf idence interval.CA=chronological age;FFA=functional f itness age.

4.Discussion

4.1.Indicators of functional f itness—FFA equation and percentiles

Our cross-sectional analysisdetermined thef itnesscondition of 459 women.We then proceeded to calculate 2 indicators of functional f itness:FFA and theglobal scoreof average percentiles.Each indicator provides accessible and understandable information for practitioners in clinical practice.The age_dif showsthedisparity between someone'sexpected f itnesscondition according to the CA.Theindicatorsage_dif and theglobal score are not equal but they are strongly related(R2=0.66),as can be seen in Fig.3.

Fig.2.Functional f itness according to age_dif(FFA-CA)compared to CA only.Participantsplaced under thelinewith avalueof 0 on the y-axishavegood physical f itness because their age_dif value is negative;therefore,their FFA is lower than their CA.In other words,their functional f itness levels are like younger women's f itness.On the other hand,participants above the horizontal red line have less functional f itness than what would be expected chronologically,that is,higher FFA than CA.CA=chronological age;FFA=functional f itness age.

Thesubstantial differencebetween FFA and theglobal score of average percentiles is that the global score(mean score)assumes equal weight to each test,whereas each test outcomes weights differently for the FFA calculation,as indicated by the coeff icients obtained from the regression analysis model(Table 3).

The 50th percentile ref lects the expected score for the CA.As an example(Fig.4),a 70-year-old woman showing the following scores:CS=22,AC=17,ST=120,CSR=3,BS=10,FUG=4.88 would result in an FFA of 64.08 years,almost 6 years younger.

In our f indings,the FUG weights the greatest amongst all to calculate the FFA.This is in line with other previous research

where walking33or gait speed34showed the greatest relation with risk of premature mortality.

Fig.3.The relationship between age_dif (functional f itness age -chronological age)and the mean value of percentiles from each of the Senior Fitness Test battery outcomes.

4.2.Comparison of f itness outcomes with other populations

Our cross-sectional data showed decreasing performance in each test over time(Table 4).Fitness decline of our sample of 459 women was similar to that of other populations reported elsewhere,despite differences in sample size.

4.2.1.Leg strength

Our results of the CS showed a decrease of 29.74%of leg strength from the age of 50 to 80-87 years old.Other studies suggest a1.5%decreaseof strength when comparing theageof 45 and 60 years.1,35Samuel and Rowe36indicated that thereisa 20.0%decrease of strength performance when comparing the age range of 60 to 80 and above.Goodpaster et al.37indicated that theyearly declinefrom theageof 80 is2.6%.Nú?ez Roca et al.38showed a decrease of 30.0%in leg strength from the range of 55-64 years to 64 years and above.Generally,the decrease of leg strength of our sample was lower compared to other studies(Table 5).

Fig.4.FFA report example.AC=arm curl test;BS=back scratch test;CA=chronological age;CS=chair stand test;CSR=chair sit-and-reach test;FFA=functional f itness age;FUG=8-foot up-and-go test;rep=repetition;ST=2-min step test.

Table4Percentage of performance decline of the Senior Fitness Test battery outcomes(n=459).

4.2.2.Arm strength

Arm strength measured with the arm curl test(AC)was the f itness condition that decreased the least,with a net loss of 26.30%.Asother researchersconcluded,thereisafurther decline in lower body strength than in upper body strength.21,38,39

In our study,the participants aged more than 64 years averaged 18%less repetitions than those younger than 64,while Nú?ez Roca et al.38found a loss of 21.58%in arm strength.

Strength declineisfaster aspeoplebecomeolder.Thebreakpoint of Lleida participants where strength reduction begins to accelerate is around 70 years.

4.2.3.Aerobic endurance

Participants results on the aerobic endurance f itness test,the ST showed a similar percentage of decline than other studies,although absolute scores showed that Lleida women scored 10 steps more per year than the Hong Kong(China)and U.S.samples.21,40

4.2.4.Lower limbs f lexibility

Comparing our CSR results with other studies from Hong Kong(China),40Brazil,41and the USA,21,41Hong Kong samples consistently show better resultsin absolute terms.However,the declinein lower limb f lexibility beginsearlier in Lleidawomen(70-79 yearscompared to 80 years)compared to the Brazilian and U.S.samples,whose decline is more gradual.

4.2.5.Upper limbs f lexibility

Comparing the results of upper limbs f lexibility using the BS,the Hong Kong(China)sample shows better results than the Lleidaand the U.S.population.21,40Theagegroup of 80 and abovein Lleidahasadecreasein upper limbsf lexibility greater than the sample from Hong Kong(China).The U.S.sample,however,shows the worst results and a more pronounced decline with time.

Table5Comparison of the decrease in leg strength(%).

4.2.6.Agility

Our participants'scores of agility measured with the FUG showed a similar percentage of decrease as other studies.21,40,41

5.Conclusion

We consider the SFT battery an appropriate set of tests to assess FFA)in elderly women dueto low technical diff iculty and safety of the tests(i.e.,low physical demand).Using the SFT battery we created an equation to determine the FFA and,when compared to the CA,may provide relevant information for practitioners to set exercise programs.The f itness outcomes of our sample were similar to other populations.The outcomes of a physical f itnesstest may indicatewhat capacity islow compared to normative values.However,we suggest that the indicator of FFA and thedifferencebetween FFA and CA(age_dif)iseasy to understand for ageneral population.It may bealso a motivation shiftto startan exerciseprogramor toadaptacurrentoneto more specif ic f itnesscapacities,liketheestimated spirometric lung age(i.e.,the age of the average healthy individual who would perform similar to them on spirometry)has been shown to improve the likelihood of smokers quitting smoking.Individual scores for each outcome may provide relevant information to individualize exercise programs aimed at improving lower health-related f itness capacities.Longitudinal studies including exercise programs to improve health-related f itness may use the FFA indicator(and age_dif)and focuson participation adherence or health-related outcomes(e.g.,number of injuries,risk of falls,cardiovascular risk factors,cognitive performance).

Our study evaluated active women participating in exercise programs.They may suffer frommedical conditionsbutnoneof the conditions limited their participation in exercise programs.Futureresearch should focuson other populations,such asmen or other age groups.The determination of FFA for patients of different medical conditionsmay even correlatewith morbidity and self-perception of quality of life.

Acknowledgments

The authors give special thanks to the Institut Municipal d'Activitats Esportives(IMAE),the Lleida City Council,the Universidad Santo Tomás Aquino of Colombia,and the National Institute of Physical Education of Catalonia(INEFC)for their support,and Tina Buchmann(Translations and Language Services).

Authors'contributions

EJLRperformed the SFTmeasurements;JAPSand APA conceived of the study,participated in its design and coordination;XPTand SMAdraftedthemanuscript;APAand JVBGperformed the data analysisand helped to draft the manuscript.All authors have read and approved the f inal version of the manuscript,and agreewith theorder of presentation of theauthors.

Competinginterests

The authors declare that they have no competing interests.