response of bone mineral density, inflammatory cytokines, and biochemical bone markers to a 32-week...

Archives of Gerontology and Geriatrics xxx (2013) xxx–xxx

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AGG-2845; No. of Pages 8

Response of bone mineral density, inflammatory cytokines, andbiochemical bone markers to a 32-week combined loading exerciseprogramme in older men and women

Elisa A. Marques a,b,*, Jorge Mota a, Joao L. Viana b,c,d, Diana Tuna e, Pedro Figueiredo b,f,Joao T. Guimaraes e,g, Joana Carvalho a

a Research Centre in Physical Activity, Health and Leisure, Faculty of Sport Science, University of Porto, Rua Dr. Placido Costa 91, 4200-450 Porto, Portugalb Higher Education Institute of Maia (ISMAI), Maia, Portugalc School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, UKd Research Center in Sports, Health Sciences and Human Development (CIDESD), Portugale Department of Clinical Pathology, S. Joao Hospital, Alameda Prof. Hernani Monteiro, 4200-319 Porto, Portugalf Centre of Research, Education, Innovation and Intervention in Sport, Faculty of Sport Science, University of Porto, Rua Dr. Placido Costa 91, 4200-450 Porto,

Portugalg Department of Biochemistry, Faculty of Medicine, University of Porto, Alameda Prof. Hernani Monteiro, 4200-319 Porto, Portugal

Contents lists available at SciVerse ScienceDirect

Archives of Gerontology and Geriatrics

jo ur n al ho mep ag e: www .e lsev ier . c om / lo cate /ar c hg er

A R T I C L E I N F O

Article history:

Received 4 January 2013

Received in revised form 19 February 2013

Accepted 26 March 2013

Available online xxx

Keywords:

Bone mass

Elderly

Resistance exercise

Weight-bearing exercise

Inflammation

Biomarkers

A B S T R A C T

This study examines the effec

strength, bone mineral density

older adults. Forty-seven healt

in a exercise intervention (60

75–80% of maximum plus a

Outcome measures included

strength, serum levels of bone

collagen (CTX), osteoprotegeri

and serum levels of inflammat

6, tumor necrosis factor (TNF)-

composition, dietary intake (u

32 weeks, both men and wo

trochanter (0.7%), intertrochan

OPG and RANKL levels remain

TNF-a levels were unchanged

suggest that our combined im

lower-extremity muscle stre

reinforces the role of exercise

balance and BMD reduction.

Abbreviations: ANOVA, analysis of variance; B-ALP, bone alkaline phosphatase;

BMD, bone mineral density; OC, osteocalcin; CTX, C-terminal telopeptide of Type I

collagen; OPG, osteoprotegerin; RANKL, receptor activator of nuclear factor kappa B

ligand; hs-CRP, high sensitive C-reactive protein; IL-6, interleukin-6; TNF-a, tumor

necrosis factor-alpha; IFN-g, interferon-gamma; PA, physical activity; BMI, body

mass index; MVPA, moderate to vigorous physical activity; ES, effect size; RCT,

randomized controlled trial; 1RM, one-repetition maximum.

* Corresponding author at: Research Centre in Physical Activity, Health and

Leisure, Faculty of Sport Science, University of Porto Rua Dr. Placido Costa 91, 4200-

450 Porto, Portugal. Tel.: +351 220425291; fax: +351 225500689.

E-mail address: [email protected] (E.A. Marques).

Please cite this article in press as: Marques, E.A., et al., Response of bonmarkers to a 32-week combined loading exercise programme in odx.doi.org/10.1016/j.archger.2013.03.014

0167-4943/$ – see front matter � 2013 Published by Elsevier Ireland Ltd.

http://dx.doi.org/10.1016/j.archger.2013.03.014

ts of 32 weeks of exercise training on balance, lower-extremity muscle

(BMD) and serum levels of bone metabolism and inflammatory markers in

hy older adults (women = 24, men = 23; mean age 68.2 years) participated

min/session) that included resistance exercise training (2 days/week) at

multicomponent weight-bearing impact exercise training (1 day/week).

lumbar spine and proximal femoral BMD, dynamic balance, muscle

metabolism markers [osteocalcin (OC), C-terminal telopeptide of Type I

n (OPG) and receptor activator of nuclear factor kappa B ligand (RANKL)]

ory markers [high sensitive (hs)-C-reactive protein (CRP), interleukin (IL)-

a, and interferon (IFN)-g]. Potential confounding variables included body

sing 4-day diet records), and accelerometer-based physical activity. After

men increased dynamic balance (6.4%), muscle strength (11.0%) and

ter (0.7%), total hip (0.6%), and lumbar spine BMD (1.7%), while OC, CTX,

ed unchanged. In addition, hs-CRP and IFN-g levels were decreased, while

, and a decrease in IL-6 levels was only observed in men. These findings

pact protocol reduces inflammation and increases BMD, balance, and

ngth, despite having little effect on bone metabolism markers. This

to counteract the age-related inflammation, and the muscle strength,

� 2013 Published by Elsevier Ireland Ltd.

1. Introduction

Aging is linked to a reduced amount of bone tissue, whichconsequently motivates bones to become weaker, commonlyleading to osteoporosis (Kostenuik & Shalhoub, 2001). This is acommon, serious, and disabling condition due to the inherentassociation with low-energy trauma or fragility fractures, and withalso severe economic consequences (Cummings & Melton, 2002).Increasing evidence has suggested a central role for falls as thestrongest single risk factor for a fracture (Peeters, van Schoor, &Lips, 2009). Accordingly, strategies targeting the prevention ofbone fractures in the elderly should focus on reducing the risk of

e mineral density, inflammatory cytokines, and biochemical bonelder men and women. Arch. Gerontol. Geriatr. (2013), http://


mailto:[email protected]



http://www.sciencedirect.com/science/journal/01674943


Table 1Baseline characteristics of the sample.

Variable Women

(n = 24)

Men

(n = 23)

p value

Age (years) 68.2 � 5.7 68.2 � 5.2 0.876

Education (years) 7.9 � 4.5 8.4 � 3.6 0.373

Number of routine

medications

1.9 � 1.8 2.2 � 1.6 0.459

History of cigarette

smoking (n/%)

1/4.2 2/8.3 0.525

Anthropometry and

body composition

Weight (kg) 64.2 � 10.2 83.0 � 11.7 <0.001

BMI (kg/m2) 28.6 � 4.1 29.2 � 3.4 0.134

Lean mass (kg) 38.4 � 4.8 54.9 � 5.9 <0.001

Fat mass (%) 37.8 � 5.8 27.6 � 27.2 <0.001

Diet

Energy intake (kcal/day) 1444.6 � 345.4 1618.3 � 496.5 0.169

Protein intake (g/day) 68.7 � 14.6 71.5 � 19.4 0.578

Calcium intake (mg/d) 643.7 � 337.9 658.3 � 253.3 0.868

Phosphorus intake (mg/day) 988.7 � 299.6 1049.1 � 319.2 0.507

Vitamin D intake (mg/day) 1.7 � 1.9 1.5 � 1.2 0.619

Coffee intake (mL/day) 62.4 � 57.0 98.2 � 48.5 0.025

Daily physical activity

MVPA (min/day) 80.4 � 30.6 91.9 � 31.5 0.294

Daily counts per minute 377.6 � 123.6 418.1 � 139.1 0.383

Daily step count 9255.7 � 3195.2 10,629.1 � 9668.4 0.614

Bone mineral density

Lumbar spine (g/cm2) 0.848 � 0.121 1.039 � 0.173 <0.001

Femoral neck (g/cm2) 0.687 � 0.108 0.817 � 0.099 0.001

Lumbar spine (T-score) �1.8 � 1.2 �0.4 � 1.6 0.011

Femoral neck (T-score) �1.5 � 1.0 �0.7 � 0.9 0.014

BMI, body mass index; MVPA, moderate to vigorous physical activity.

E.A. Marques et al. / Archives of Gerontology and Geriatrics xxx (2013) xxx–xxx2

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falls and maintaining or improving bone health. Mixed loadingexercise programs combining impact activity with high-magni-tude exercise as resistance training and odd-impact protocolsappear effective against aging-induced bone weakness (Marques,Mota, & Carvalho, 2012; Martyn-St James & Carroll, 2009). Despitethe importance of bone density in the elderly and their attenuatedbone response to physical forces (exercise) (Lanyon & Skerry,2001), most studies have focused on postmenopausal women.

In addition, experimental animal studies have recentlyimplicated inflammation in the pathogenesis of osteoporosis(Nanes, 2003). The effect is primarily driven on the differentiationand activity of the bone-resorbing cell, the osteoclast; and it isestablished that pro-inflammatory cytokines suppress osteopro-tegerin (OPG) expression while simultaneously enhancing recep-tor activator of nuclear factor kappa B ligand (RANKL) expression(Schett, 2011). Evidence exists to support a relationship betweenregular exercise and improvements in systemic low-gradeinflammation (Gleeson et al., 2011), even in old age (Ogawa,Sanada, Machida, Okutsu, & Suzuki, 2011), along with in vitro andin vivo experiments (Saunders et al., 2006) suggesting thatmechanical stimulation can inhibit osteoclast formation andactivity by increasing OPG/RANKL ratio. Nevertheless, to datethere are no reports documenting whether changes in bone-related inflammatory cytokines are associated with alterations inBMD in both older men and women after long-term exercisetraining.

Basic and clinical studies have established the relevance ofbiochemical markers of bone metabolism, showing an earlyresponse following treatment compared with BMD; and wasproved to be useful for monitoring therapeutic response andefficacy on individual patients (Garnero, 2008). A combination ofmarkers has been used to evaluate the rate of bone remodeling,including measuring predominantly osteoblastic or osteoclasticenzyme activities or assaying bone matrix components in bloodand/or urine (Garnero, 2008). Currently, there are very limited datathat have addressed the influence of long-term exercise (>12weeks) on those biomarkers on older adults (Bemben, Palmer,Bemben, & Knehans (2010); Vincent & Braith, 2002).

Therefore, the aim of the this study was to analyze several boneturnover and inflammatory biomarkers that may be associatedwith increased BMD after combined loading training in olderadults. In addition, the alterations in balance and lower-extremitymuscle strength as key factors associated with fall risk were alsoevaluated. We hypothesized that exercise would improve thebone-related inflammatory cytokines and bone turnover markers.Favorable alterations on BMD, muscle strength and balance werealso expected.

2. Materials and methods

2.1. Subjects and experimental design

Subjects were recruited through advertisements in Porto areanewspapers for participation in this university-based study. A totalof 55 Caucasian older adults (29 women and 26 men) volunteeredto participate in the study. The eligible subject pool was restrictedto older adults with the following characteristics: aged 60–85years, community-dwelling status, not engaged in regular exercisetraining in the preceding year, lack of use of bone-acting drugs andnutritional supplements known to affect bone metabolism (such asvitamin D and calcium) within the previous year, and lack of andsignificant sensory/cognitive impairment or medical conditionsthat contraindicated exercise participation. On the initial screeningvisit, all participants received a complete explanation of thepurpose, risks, and procedures of the investigation and, aftersigning a written consent form, medical history and current


medications of the subjects were documented. Participants wereinstructed to continue their daily routines and to refrain fromchanging their physical activity levels during the course of theexperiment.

The baseline characteristics of the participants are given inTable 1. The study was carried out in full compliance with theHelsinki Declaration, and all methods and procedures wereapproved by the institutional review board.

2.2. Exercise protocol

The 32-week combined loading training involved odd-impactloading training performed once a week (Wednesdays) and high-magnitude joint reaction force loading through resistance trainingperformed twice a week on separate days (Mondays and Fridays).Each session lasted approximately 60 min, and three physicaleducation instructors specialized in PA for older adults, andsupervised by the researchers led all sessions at the University ofPorto – Faculty of Sport facilities.

The odd-impact training was designed to load bones withintermittent and multidirectional compressive forces, introducingatypical and novel stress on the bone, and to improve neuromus-cular function. Each training session included six differentcomponents:

I) A 10-min light stretching and warm-up exercise;II) 15 min of weight-bearing activities, consisting of stepping

exercise at a speed of 120–125 beats per minute using a 15-cm-high bench, bounding exercises, and heel-drops performed on ahard surface – a heel-drop consists of raising the body weightonto the toes and then letting it drop to the floor, keeping theknees locked and hips extended;




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III) Muscular endurance exercises performed concentrically andeccentrically for about 10 min, involving squats while wearingweight vests, hip flexors, extensors, and abductors; kneeflexors and extensors and upper body exercises performedusing elastic bands and dumbbells;

IV) 10 min of balance training with static and dynamic exercises(e.g. walking in a straight line, walking heel to toe, usingadditional resources such as ropes, sticks, balls, and balloons);

V) 10-min games where movements included directional ele-ments that the body is not normally accustomed to, and agilitytraining aimed at challenge hand-eye coordination, foot-eyecoordination, dynamic balance, standing and leaning balance;

VI) 5-min of stretching.

For weight-bearing and strength exercises, the repetitions wereincreased from 8 to 15 and the number of sets increased to 3.

Resistance exercise training sessions involved the following: astandardized warm-up period (8–10 min) on a bicycle ergometer(Bike-Max; Tectrix, Irvine, CA) and/or rowing ergometer (ConceptII, Morrisville, VR) at low intensity (50–60 rpm) and somestretching exercises; specific resistance training period (30–40 min) that included leg press and leg extension, seated leg curl,hip abduction, double chest press, lateral raise, overhead press, andabdominal machine; and a cool-down period (5–10 min) thatincluded walking and stretching exercises. Subjects exercised onvariable resistance machines (Nautilus Sports/Medical Industries,Independence, VA). To minimize fatigue, the exercises for theupper/lower body were performed in a non-consecutive way, withapproximately 2 min rest in-between. Training intensity wasgradually increased during the first four weeks. Participantsunderwent a 2-week familiarization period with the equipmentand the exercises. The intensity of the training stimulus wasinitially set at 60% of one-repetition maximum (1RM), asdetermined at week 2, with a work range of three sets of 12–15repetitions. Subjects then progressed from 75% to 80% of 1RM at awork range of six to eight repetitions (3 sets) and remained at thislevel until the end of the program. Training was continuouslymonitored by heart rate monitors (Polar Vantage XL, Polar ElectroInc., Port Washington, NY) and ratings of perceived exertion (Borg’s10-point psychometric scale) (Borg, Hassmen, & Lagerstrom,1987). 1RM tests were performed every two weeks for the firstmonth and then every four weeks until the end of the program.Between these tests, the load was increased for those subjects whowere able to easily complete 12 or more repetitions for both sets.

The three research assistants were responsible for warm-up,cool down, and stretching exercises; the monitoring of correctlifting form; the appropriate amount of exercise and rest intervals;the maintenance of daily exercise logs; and the progression of theexercises. During training sessions, subjects were also encouragedto exercise with a training partner to provide additional motiva-tion.

Exercise compliance was defined as the number of exercisesessions reported divided by the number of maximum exercisesessions possible.

2.3. Measurements

Participants were tested prior to the beginning of training (lastweek of September 2009) and after eight months of training (firstweek of June 2010).

2.3.1. Blood sampling and analysis

Fasting venous blood samples were drawn between 8 a.m. and10 a.m. always on Mondays to ensure at least 2 days withoutexercise training. Serum samples were clotted at room tempera-ture for 90 min after which they were centrifuged for 10 min at


1000 � g. Samples were aliquoted and stored at �80 8C untilanalysis.

Serum N-MID Osteocalcin (OC) was measured using anelectrochemiluminescence immunoassay on a Cobas E moduleanalyzer (Roche Diagnostics, Penzberg, Germany). For serum C-terminal telopeptide of Type I collagen (CTX) the serumCrossLaps enzyme-linked immunosorbent assay kit (Immuno-diagnostic Systems Ltd, Boldon, UK) was used. Serum concen-trations of IL-6, TNF-a, and IFN-g (Human 3-plex Cytokinepanel), serum OPG (Human bone panel 1A), and serum RANKL(Human RANKL Single Plex) were measured using Milliplextmmap kits (Millipore, St. Charles, MO) in a Luminex1 200TManalyzer (Luminex Corporation, Austin, TX). Raw data (meanfluorescence intensity, MFI) were analyzed using ISTM 2.3software (Luminex Corporation, Austin, TX). All these measure-ments were performed according to the manufacturers’ proto-cols. Standards and samples were measured in duplicate andassay methods had coefficients of variation-values (intra- andinter-assay) <9%.

Capillary blood samples were collected on the same occasionfrom the earlobe using a 50 ml lithium heparin-coated capillarytube and immediately assayed using the Cholestech LDX1

Analyzer (Cholestch Corporation – Hayward, CA, USA) fordetermination of hs-CRP.

2.3.2. Bone mineral density measurements

BMD was measured using dual-energy X-ray absorptiometry(DXA; QDR 4500A, Hologic, Bedford, MA) at the lumbar spine(L1–L4) and proximal femur on the non-dominant side usingstandard protocols. To minimize interobserver variation, thesame blinded technician carried out all analyses. Bone phantomswere scanned daily, and coefficients of variation were verifiedbefore and during the experimental period to ensure assessmentreliability, as previously described (Marques et al., 2011a).

2.3.3. Balance and muscle strength measures

Dynamic balance was assessed using the 8-foot Up and Gotest (Rikli & Jones, 1999a). Before starting the test, participantsremained seated and rested for 5 min. The score corresponded tothe shortest time to rise from a seated position, walk 2.44 m (8feet), turn, and return to the seated position, measured to thenearest 1/10th’s. Two attempts were allowed, with 1-minrest in-between, and the best performance was used foranalysis.

Lower-extremity muscle strength was measured using the 30 sChair Stand test (Rikli & Jones, 1999a). Participants were asked tosit in a 43-cm-high chair with arms crossed at the wrists and heldagainst the chest. Participants completed as many ‘‘stand ups’’ aspossible during 30 s. The score was the total number of standsexecuted correctly during 30 s. Both tests include normativeperformance standards established according to participants’ ageand gender (Rikli & Jones, 1999b).

2.3.4. Potential confounding variables

Total body scans were taken using the same DXA instrument.Scans were analyzed for total lean mass (kg), and body fat mass (%).Body mass and height were recorded using a digital medical scale(Seca GmbH, model 708, Germany) and a height rod (Seca 220).Body mass index (BMI) was calculated using the standard formula:mass (kg)/height2 (m).

The Actigraph GT1M accelerometer (Manufacturing Technolo-gy, Fort Walton Beach, FL) was used as an objective measure ofdaily PA, as described previously (Marques et al., 2011b). For bothtest periods (pre- and post-training), four subjects had only twovalid days. Those 4 participants were contacted and agreed to wearthe accelerometer again for seven days (one week later than the





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rest of the group). The average daily moderate to vigorous PA(MVPA), number of steps, and daily activity counts per minutewere analyzed.

Nutritional status was assessed using 4-day diet recordsover three weekdays and one weekend day. To ensurestandardization of the dietary records, a dietician gaveindividual instruction to the subjects concerning how to fillout the diet records and assess food-serving sizes. Diet recordswere analyzed using Food Processor Plus1 (ESHA Research,Salem, OR), which uses the table of food components from theUS Department of Agriculture. Some traditional Portuguesedishes were added based on the table of Portuguese foodcomposition. Total caloric, protein, calcium, phosphorous,vitamin D, and caffeine intakes were compared between menand women.

A baseline self-administered questionnaire to assess the impactof present and past lifestyle choices and clinical status wascompleted by interview to avoid misinterpretation of items and/orskipping of questions. Questionnaire included information regard-ing education, marital status, fall and fracture history, medicalhistory, current medical conditions, medication use, as well ascurrent and past smoking.

2.4. Statistical analysis

All statistical analyses were performed using SPSS Statistics(version 18; SPSS, Inc., Chicago, IL) for Windows with asignificance level of 5%. Data were checked for normaldistribution using the Shapiro–Wilk test, and the means � stan-standard deviations were calculated. Primary outcomes werechanges from baseline in response to training in balance, musclestrength, BMD and serum bone metabolism markers and inflam-matory cytokines. Secondary outcomes included 32-week changesfrom baseline in dietary intake, daily MVPA, and body composition(BMI, fat mass percentage, and lean mass). The results wereanalyzed on an intention-to-treat basis, and missing data due tolack of follow-up (the method assumed data were missing atrandom) was replaced using the process of multiple imputations.This method has been adapted to the analysis of longitudinal data(Mazumdar, Liu, Houck, & Reynolds, 1999). Between-groupcomparisons of continuous variables were performed usingindependent t-tests. Pearson’s correlation coefficients were usedto analyze the association between BMD of the femoral neck, totalhip, and lumbar spine, body composition, bone biomarkers, andinflammatory markers. Correlation analysis (adjusted for gender)was also used to determine relationships among the variables withsignificant change over time.

The delta percentage was calculated with the standard formula:% change = [(post training score � baseline score)/baselinescore] � 100, and the effect size for within-subjects (pre-testmean – post-test mean/pre-test standard deviation), was alsocalculated. An ES of 0.2 or less is considered small, an ES around 0.5is moderate, and an ES of 0.8 or greater is large (Thomas, Nelson, &Silverman, 2005).

A two-way (group and time) factorial ANOVA, with repeatedmeasures on one factor (time), was performed for main effects andtime by group (males vs. females) interactions for each dependentvariable. Main effects were considered when interactions were notsignificant. When significant interactions were found, Bonferronipost hoc tests were used to determine significant differencesamongst mean values.

A power analysis based on a formulation of 75% power, an effectsize of 0.5 for overall muscle strength, balance and BMD fromprevious studies, and a significance level of 5% deemed that asample of 23 per group was sufficient to address the researchquestions.


3. Results

3.1. Subjects

Eight subjects did not meet selection criteria due to use ofmedication known to affect bone metabolism (n = 3), use ofhormone replacement therapy (n = 2), and current involvement inwater-based activities (n = 3). Forty of the original 47 subjects(women = 24, men = 23) who underwent the initial assessmentcompleted the study (women = 20, men = 20). Dropout rates weresimilar amongst men and women. Three participants dropped outbecause of surgery, two participants dropped out due to medicalissues unrelated to the intervention, and two other subjectsbecause of personal reasons. One hundred percent compliance tothe exercise sessions was set at 96 training sessions. Excludingdropouts, mean compliance to exercise sessions was 82.6% (60.0–100%). There were no exercise- or assessment-related (pre- andpost-training) adverse events. In comparison to individuals whocompleted the trial, those who failed to provide follow-up data hadlower daily MVPA level and lower performance in balance test. Nosignificant differences in the remaining baseline measurementswere found, including age, body weight, and inflammatory orbone-related variables. Our analysis included all subjects as resultswere analyzed on an intention-to-treat basis, and missing data dueto lack of follow-up (the method assumed data were missing atrandom) were replaced using the process of multiple imputation.Yet, using the per-protocol analysis (n = 40), the results for alloutcomes were similar, in direction and statistical significance, tointention-to-treat analysis.

Demographics and descriptive parameters of all groups arelisted in Table 1. Of all the participants, 45% were overweight,almost half of them had hypertension, women never smoked, andonly a small proportion of participants (6%) had a history ofcigarette smoking (2 men and one women). On average,participants obtained 78 min of MVPA per day. Compared withmen, women had significantly higher fat mass percentage(p < 0.001), lower weight and lean mass (p < 0.001), lower caffeineintake (p = 0.025), and significantly less BMD and T-score values.

3.2. Bone mineral density, balance, and muscle strength responses

There were no significant interactions between group and timeon all measurements of BMD, balance and muscle strength(Table 2). A significant main effect of time for all balance, musclestrength, and bone variables was observed, excepting for femoralneck BMD. Accordingly, both men and women improved lower-extremity strength, the time to perform the balance test, andimproved BMD at several bone sites, including lumbar spine, totalhip, trochanter, and intertrochanteric region. However, themagnitude of the effect observed on muscle strength and balancewas moderate in women, and low in men. In addition, effect sizesfor BMD sites were low (<0.2). A significant main effect of groupwas also observed for all variables, excepting for muscle strength;thus, as expected, women had lower BMD at both time-points, andsignificant lower performance on the up and go test at baseline andafter training.

3.3. Bone markers and inflammatory cytokines responses to training

The 32-week exercise training did not significantly change inboth bone turnover markers (OC and CTX) and in OPG, RANKL andtheir ratios (Table 3). OPG was significantly greater (p < 0.05) inthe female group compared to the male group at baseline and post-training.

Inflammatory markers were not significantly different betweengroups at baseline. There was a significant treatment effect




Table 2Pre- and post-training values, and effect sizes (ES) for proximal femur and lumbar spine BMD, dynamic balance and lower-extremity muscle strength.

Variable Women ES Men ES p (Group) p (Time) p (Interaction)

Pre-training Post-training Pre-training Post-training

Femoral neck (g/cm2)a 0.715 � 0.119 0.705 � 0.104 0.08 0.822 � 0.113 0.821 � 0.115 0.01 0.002 0.241 0.406

Troch (g/cm2)a 0.640 � 0.081 0.648 � 0.080 0.10 0.773 � 0.112 0.774 � 0.114 0.01 <0.001 0.032 0.070

Inter (g/cm2)a 1.031 � 0.142 1.041 � 0.139 0.07 1.169 � 0.165 1.172 � 0.163 0.02 0.005 0.038 0.276

Total hip (g/cm2)a 0.864 � 0.108 0.872 � 0.111 0.08 1.004 � 0.140 1.006 � 0.138 0.01 0.001 0.021 0.129

Lumbar spine (g/cm2)a 0.877 � 0.122 0.896 � 0.129 0.15 1.051 � 0.161 1.065 � 0.172 0.08 <0.001 <0.001 0.427

8 ft Up and go (s)a 5.33 � 1.04 4.74 � 0.54 0.56 4.55 � 0.74 4.35 � 0.51 0.28 0.004 <0.001 0.059

30 s Chair stand (rep) 18.54 � 4.48 19.59 � 3.51 0.43 18.65 � 4.27 19.59 � 3.11 0.22 0.709 0.004 0.304

a Significant difference between groups at baseline and post-training, p < 0.05. 8 ft, 8-foot; BMD, bone mineral density; Troch, trochanter; Inter, intertrochanteric region;

Rep, number of repetitions.


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(decrease) for IL-6, IFN-g, and hs-CRP (Table 3). A significant groupx time interaction was observed only for IL-6, thus a differentresponse between males and females was evident over time,supported by the significant decrease observed in the male group(effect size = 0.52 vs. effect size = 0.09). There was no significantinteraction or main effects of group and time in TNF-a.

3.4. Change correlations

Adjusting to gender, there were no significant correlationsbetween change values of inflammatory markers (IL-6, IFN-g, andhs-CRP) and change in total hip, trochanter, intertrochanter andlumbar spine BMD.

3.5. Confounding variables

Total energy intake was similar amongst men and women atbaseline and during the period of intervention. Energy intake was 1530 � 430 kcal/day at baseline and 1 452 � 463 at 32-week. Dietaryprotein, phosphorus, caffeine, calcium, and vitamin D intakemeasured with a 4-day dietary record, remained unchanged after32 weeks of intervention.

In total, pre- and post-training data from all participants wereincluded in the analysis (47 files with seven valid days, 7 files with6 valid days, and 11 files with 5 valid days). No significant changesin MVPA level were observed. There was no significant interactive(p = 0.210) or main effect of group (p = 0.102) and time (p = 0.326)on MVPA changes.

No significant interaction occurred for body composition inresponse to exercise intervention (Table 2). There was a main effectof group on lean mass (p < 0.001) and fat mass percentage(p < 0.001). Thus, women had significant lower lean mass andgreater fat mass percentage on both time-points. However, the

Table 3Serum bone-related and pro-inflammatory markers responses to 32 weeks of exercise

Variable Women ES Men

Pre-training Post-training Pre-training

OC (ng/mL) 14.82 � 3.64 15.43 � 4.12 �0.17 14.08 � 2.87

CTX (ng/mL) 0.38 � 0.14 0.38 � 0.15 0.01 0.37 � 0.12

OC/CTX 42.91 � 15.35 43.83 � 12.55 �0.06 39.45 � 7.92

OPG (pg/mL)a 514.61 � 117.57 503.45 � 118.85 0.09 432.80 � 126.

RANKL (pg/mL) 29.64 � 13.82 26.53 � 14.64 0.23 27.20 � 9.72

OPG/RANKL 30.38 � 39.60 31.49 � 36.85 �0.03 17.64 � 6.83

IL-6 (pg/mL) 1.18 � 0.81 1.11 � 0.91 0.09 1.62 � 1.25

TNF-a (pg/mL) 7.30 � 2.46 7.28 � 2.16 0.01 7.39 � 2.05

IFN-g (pg/mL) 0.75 � 0.51 0.48 � 0.36 0.54 0.63 � 0.43

hs-CRP (mg/L) 3.06 � 2.27 2.54 � 1.81 0.23 2.53 � 1.95

a Significant difference between groups at baseline and post-training, p < 0.05.b Significantly different from baseline, p < 0.05. ES, effect size; OC, osteocalcina; CTX, C

kappa B ligand; OPG, osteoprotegerin; IL, interleukine; TNF, tumor necrosis factor; IFN


effect sizes for all body composition variables were low (<0.2) andchanges in body composition were non-significant. Finally, nosignificant interactions were observed between the covariates fatmass and MVPA with all the main outcomes.

4. Discussion

Regular exercise training is consistently linked with a variedrange of health-related benefits, including improvements in low-grade inflammation, BMD and bone metabolism. In fact, increasedinflammation seems to be associated with a reduction in BMD, askey cytokines are associated with critical factors for boneremodeling (Schett, 2011). However, few comprehensive effortshave been made to characterize the relationship between changesin BMD, bone metabolism, and inflammatory response after long-term exercise training in older adults. We found that the 32-weekresistance exercise combined with weight-bearing exercisetraining increased BMD and favorably modulated inflammatorymarkers in older adults. No changes were observed in OPG, RANKL,and OC and CTX (bone formation and resorption markers,respectively) after exercise. Finally, balance and lower bodystrength, as markers of fall risk factors, significantly improvedafter exercise training.

Evidence regarding exercise effects on bone mass andmetabolism has been mostly based on women and single-stimuliexercise interventions, thus fewer studies have focus on elderly(age > 60y), particularly men (Marques et al., 2012). Humanstudies examining the effects of long-term exercise interventionsin older men have shown positive results on both femoral neck andlumbar spine BMD (Bemben & Bemben, 2010; Kukuljan et al.,2011). All previous studies were based on evidence from 6 to 18months resistance exercise training, which is consistent with ourintervention. Our data also revealed that the relative improve-

training.

ES p (Group) p (Time) p (Interaction)

Post-training

13.75 � 2.80 0.12 0.195 0.717 0.225

0.36 � 0.12 0.12 0.722 0.571 0.667

40.67 � 10.88 �0.15 0.309 0.450 0.915

10 423.81 � 107.64 0.07 0.018 0.294 0.909

26.53 � 9.89 0.07 0.722 0.090 0.269

19.66 � 12.32 �0.30 0.122 0.557 0.865

0.97 � 0.84b 0.52 0.538 0.042 0.013

7.99 � 2.52 �0.30 0.538 0.164 0.149

0.44 � 0.21 0.45 0.393 0.002 0.393

1.63 � 1.01 0.46 0.133 0.006 0.428

-terminal telopeptide of Type I collagen; RANKL, receptor activator of nuclear factor

, interferon; hs-CRP, high sensitive-C reactive protein.





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ments in BMD with training were similar for both men and women,supporting the findings of Bemben and Bemben (2010). Weexamined the effect of a combined training protocol, whichincluded 1-day/week odd-impact exercise (such as aerobic or stepclasses, bounding exercises, agility exercises and games, andimpact activities) with 2 days/week of resistance exercises, withsite-specific exercises that applied mechanical loads to theskeleton. The positive results mediated by this type of exerciseintervention are in agreement with results from a recent meta-analysis (Marques et al., 2012). However, as results were based ona disproportionate emphasis toward women, evidence to supportthe efficacy of exercise training on bone health in older men iswarranted.

Data from exercise training and bone turnover markers arehowever inconsistent with some studies showing positive effectsof exercise in attenuating bone turnover in aging adults (Karabulutet al., 2011). Others showed no effects on both bone formation andresorption markers (Yarasheski, Campbell, & Kohrt, 1997). RANKL,a member of TNF superfamily, is the key osteoclastogenic cytokine,because osteoclast formation requires its presence or its priming ofprecursor cells. OPG is a decoy receptor for RANKL and can blockRANKL/RANK interactions, thus protecting bones from excessivebone resorption (Kostenuik & Shalhoub, 2001). Therefore, an up-regulation of OPG and a down-regulation of RANKL would inhibitosteoclast formation, and therefore prevent bone loss. Ourprevious work also demonstrated no changes in serum OPG andRANKL levels and their ratio after 8 months of exercise training(Marques et al., 2011b). Similarly, Esen et al. (2009) reported nosignificant changes in OPG levels after a 10-week walking programin middle-aged men, and a study using human cell lines showedthat mechanical stimulation had not affected RANKL (Saunderset al., 2006). Our findings did not support the hypotheses thatmechanical load may induce down-regulation of RANKL (Esenet al., 2009; Lau et al., 2010). Findings of the present studyregarding changes in both bone turnover markers did not reachstatistical significant level, in agreement with data reported byRyan, Treuth, Hunter, and Elahi (1998) and Bemben et al. (2010).However, the ratio of OC to CTX increased 5% and the ratio of OPGto RANKL increased 15%, which may suggest a positive bonemetabolism change. Previous exercise-based studies on bonemetabolism were mostly short-term, lasting commonly 16 weeks,as bone marker responses to training are more rapid than BMDresponses (Harris et al., 1993). Karabulut et al. (2011) found asignificant increase in bone specific alkaline phosphatase (B-ALP)and B-ALP to CTX ratio after 6 weeks of resistance exercise in oldermen. Therefore, other results may have been observed if moreserial measurements would have been taken over the trainingperiod, rather than only at baseline and after 32 weeks.

Although regular exercise training results in lower circulatinglevels of pro-inflammatory cytokines such as IL-6 and TNF(Gleeson et al., 2011), the association between inflammationand bone metabolism after long-term exercise is less clear. Themechanisms by which pro-inflammatory cytokine mediate bonedamage have been postulated (Schett, 2011). Briefly, TNF exerts itseffect on osteoclastogenesis by acting directly on osteoclastprecursors, as well as indirectly, by upregulating the productionof macrophage colony-stimulating factor and RANKL on mesen-chymal cells (Lam et al., 2000). IL-6 can upregulate RANKL and thusindirectly support osteoclast formation via the interaction withmesenchymal cells (Udagawa et al., 1995). IFN-g is also animportant, yet controversial, osteoclastogenic-regulating factor(Takayanagi, Sato, Takaoka, & Taniguchi, 2005). In vitro, IFN-g has amarked suppressor effect on osteoclastogenesis by inhibitingRANK signaling (Takayanagi et al., 2002, 2000). However, the roleof IFN-g in vivo is more complex because it was shown to eitherdecrease osteoclastic bone resorption, leading to an improvement


of bone mass (Duque et al., 2011; Xu et al., 2009) or to increaseosteoclastic bone resorption, leading to a decrease in bone mass(Gao et al., 2007). Therefore, a decrease in both IL-6 and TNF-aprobably has some protective effect on bone loss by inhibitingosteoclast formation, while increased IFN-g levels could supportskeletal integrity.

Previous cross-sectional studies have linked high CRP levelswith lower BMD (de Pablo, Cooper, & Buckley, 2012), higher levelsof bone turnover markers (Kim et al., 2007), and greater risk offracture (Pasco et al., 2006). Others have also associated elevatedlevels of pro-inflammatory cytokines with increased risk of boneloss (Pfeilschifter, Koditz, Pfohl, & Schatz, 2002; Schett, 2011). Thecirculating levels of IFN-g and hs-CRP decreased in both men andwomen, and IL-6 significantly decreased only in men in response tothe training program (cf. Table 3). Of note, the observed decrease ininflammation was independent of weight loss, as no significantreductions on body weight or fat mass percentage occurred afterthe 32-week exercise intervention. The effect of exercise on theinflammatory profile was not due to the reduction of fat mass butto the exercise-induced muscle work per se. Indeed, most evidenceconcerning the exercise effect on inflammation had consistentlyfocused on obese and/or type 2 diabetic subjects (Jorge et al., 2011;Silverman, Nicklas, & Ryan, 2009). In addition, as no significantchanges were observed in lean mass, the exercise intervention waseffective in maintaing and therefore counteract the common age-related decline in muscle mass. In accordance with our results,some previous studies involving elderly subjects found thatexercise lead to a significant decrease in IL-6 (Nicklas et al.,2008; Prestes et al., 2009) and CRP (Martins, Neves, Coelho-Silva,Verissimo, & Teixeira, 2010; Ogawa et al., 2011), and no significantchanges on TNF-a (Ogawa et al., 2011; Prestes et al., 2009). Inaddition, exercise-associated changes in IFN-g have been poorlystudied, and results from prospective training studies arecontroversial, as the IFN-g production have been reduced (Golzari,Shabkhiz, Soudi, Kordi, & Hashemi, 2010) or did not change (Touvraet al., 2011) following a 8-week exercise training program in youngpatients. Yet, in our study, exercise induced a reduction in IFN-g,which may inhibit is protective role on osteoclast differentiationand bone loss, but no associations were found between change inIFN-g and bone biomarkers or BMD in response to our exerciseprogram.

Finally, previous studies reported that exercise training isassociated with balance and muscle strength improvements inhealthy older adults (Marques et al., 2011a, 2011b); reinforcing thenotion that exercise training has the potential to reduce fall risk inelderly people. In the present study, both older men and womensignificantly increased lower-extremity muscle strength anddynamic balance, which is in line with the prevailing evidencethat exercise protocols that include a specific strengthening andbalance component are the most effective exercise interventionsfor fall prevention compared with other modes of training(Sherrington et al., 2008).

The study does not have a control group so the within groupdifferences reported over 32 weeks may be due to seasonal change,test familiarization and/or lifestyle change. However, relevantlifestyle-related variables (such as clinical and nutritional status,body composition, and daily MVPA) were measured as potentialconfounding variables. As no significant changes were detected,those variables probably did not account for the observedoutcomes results. Due to the nature of the employed testingmethodology, no familiarization is possible for physical activity,BMD and serum measurements. It is possible that the failure todetect changes in bone turnover marker and the modestimprovement of BMD at several sites might be due to the agingprocess, and including a control group would possibly clarify thisissue. Using imaging techniques to assess bone changes, exercise





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interventions with longer duration (more than 1 year) are clearlyadvised, however biomarkers can effectively detect changes withina smaller time period (after 3–6 months). Although a longerexercise interventions would be convenient, it would increasedropout rates, due to participants’ difficulties in managing bothsummer or vacation period and continuing attending to trainingsessions. While we did not conduct a randomized controlled trial(RCT), the improvements in femoral neck (0.6%) and lumbar spineBMD (1.7%) demonstrated in this study are consistent with RCTs(Bemben & Bemben, 2010; Marques et al., 2011a, 2011b). It shouldbe noted that controlled trials may overestimate treatment effectscompared to RCTs (Wolff, van Croonenborg, Kemper, Kostense, &Twisk, 1999), which is not perceptible in the present study.Although DXA is the method most commonly used to measureareal BMD (g/cm2) because of its speed, precision, low radiationexposure and availability of reference data (Watts, 2004), it cannotyield direct measures of bone strength.

This study adds to the current literature by focusing on therelationship between a structured exercise program and bonechanges, including BMD measurements and bone metabolismmarkers, and inflammatory cytokines in this particular population.Another unique aspect of our study was the inclusion of both menand women, which allowed gender comparisons of the responsesto training. Moreover, this study has considered the possibleinfluence of critical confounding variables such as body composi-tion, daily MVPA levels objectively measured by accelerometers aswell as dietary intake.

In conclusion, our results support the beneficial role of long-term exercise training on lumbar spine and proximal femur BMDand inflammatory markers in elderly subjects. The exercise-induced anti-inflammatory effect seems to be dissociated from anyeffect on weight loss or lean mass. Moreover, we found noindication of an exercise-induced effect on biochemical markers ofbone turnover. We have also demonstrated that exercise trainingelicits significant gains in muscle strength and balance. Therelationship between exercise and changes in BMD as well as bonemetabolism markers, and inflammatory response needs to befurther explored given the public health importance of bonefragility and susceptibility to falls with aging.

Conflict of interest statement

None.

Acknowledgments

The authors thank Gustavo Silva for his kind support inbiochemical assays and Andreia Pizarro for carrying out BMDmeasurements by DXA. This research was funded by individualgrants SFRH/BD/36319/2007 and SFRH/BSAB/1025/2010 fromPortuguese Foundation of Science and Technology.

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