Menopause: The Journal of The North American Menopause SocietyVol. 19, No. 1, pp. 000/000DOI: 10.1097/gme.0b013e318223e6b3* 2011 by The North American Menopause Society

Walking training in postmenopause: effects on both spontaneousphysical activity and training-induced body adaptations

Andrea Di Blasio, BSc, MSc, PhD,1 Patrizio Ripari, MD,1,2 Ines Bucci, MD, PhD,1

Francesco Di Donato, BSc,2 Pascal Izzicupo, BSc, MSc,3 Emanuele D’Angelo, BSc, MSc,1

Barbara Di Nenno, MD,4 Mariagrazia Taglieri, MD,2 and Giorgio Napolitano, MD3,4

AbstractObjective: Because physical exercise has been widely used for primary and secondary preventions of car-

diometabolic diseases arising with menopause, the aim of our study was to determine whether participation inaerobic physical exercise is linked to the modification of spontaneous physical activity and whether this compen-sation affects aerobic trainingYrelated body adaptations.

Methods: Both before and after a 13-week walking training program, 34 postmenopausal women (mean T SDage, 55.89 T 3.57 y) were analyzed for lipids, adipokines, glucose, and insulin plasma levels, as well as for bodymeasures, heart rate and blood pressure at rest, maximal aerobic capacity, total daily energy expenditure, meanintensity of daily physical activities, and time and energy spent on physical activities with an intensity of more thanthree metabolic equivalents.

Results: Aerobic training induced significant reductions in body mass, body mass index, heart rate, systolic bloodpressure, basal cardiac double product, plasma glucose, leptin, and resistin. Aerobic fitness, the reserve of the cardiacdouble product, and the quantitative insulin sensitivity index were significantly improved. Cluster analysis of thevariations in the total daily energy expenditure, the mean intensity of daily physical activities, and the time andenergy spent on physical activities with an intensity of more than three metabolic equivalents identified two sub-groups: one showed reduced spontaneous physical activity (GROUPj), whereas the other did not (GROUP+). Thesubgroups differed significantly only for plasma lipid variation. GROUP+ showed significantly reduced low-densitylipoprotein cholesterol and total cholesterol, whereas GROUPj did not show significantly modified plasma lipids.

Conclusions: In postmenopause, participation in a program of aerobic physical exercise can result in a reductionof spontaneous physical activity, which inhibits the positive effects of the aerobic exercise on plasma lipids andlipoproteins.

Key Words: Postmenopause Y Spontaneous physical activity Y Physical exercise.

Together with the aging process, menopause has neg-ative effects on cardiorespiratory and muscular fitness,joint flexibility, and skeletal, cardiometabolic, and

mental health that can be counteracted by physical exercise.1

However, there are reports in the literature that exercise canresult in some negative behavioral adaptations that hampersome of the bodily benefits of exercise training (eg, body fatreduction). Indeed, both an increase in daily calorie intake2<5

and a decrease in spontaneous physical activity6<9 have been

reported as a consequence of participation in physical exerciseprograms, which suggests the need to monitor for associatedbehavioral compensation. This evidence suggests the neces-sity to note that even if physical activity and physical exerciseare believed to be synonymous in common practice, they arenot. Indeed, there is a substantial difference between these twoterms, because although physical activity is defined as anybody movement that is produced by the skeletal muscles thatresults in energy expenditure above the resting metabolic rate,physical exercise is a subset of this physical activity, that is,planned, structured, and repetitive movements that have, as afinal or intermediate objective, the improvement or main-tenance of physical fitness.10

As consequence, even if it has been reported that the amount,rather than the intensity, of exercise or fitness enhancement isimportant for plasma lipid improvements,11,12 there are alsostudies showing the failure of aerobic exercise to modifyplasma lipids.13<17 However, these studies have generally notincluded investigations into the physical activity remodelingthat might arise from the spontaneous physical activity. Thiswould be relevant because daily activities include movements

Received March 15, 2011; revised and accepted May 10, 2011.

From the 1Department of Human Movement Science, Faculty of Sci-ence of Motor Education; 2University Centre of Sports Medicine andPostgraduate School of Sports Medicine; 3Department of Medicine andAging Science; and 4Postgraduate School of Endocrinology, BG.D’Annunzio[ University of Chieti-Pescara, Chieti, Italy.

Funding/support: The study was supported in part by funds from theItalian Ministry for Education, University, and Research.

Financial disclosure/conflicts of interest: None reported.

Address correspondence to: Andrea Di Blasio, BSc, MSc, PhD, Depart-ment of Human Movement Science, c/o University Centre of SportsMedicine, BG. D’Annunzio[ University of Chieti-Pescara, Viale Abruzzo322, 66100 Chieti, Italy. E-mail: andiblasio@gmail.com

Menopause, Vol. 19, No. 1, 2012 1

at light, moderate, and vigorous intensities that can positivelyaffect body adaptations whenever they are practiced for aminimum of 30 minutes, as accumulated in sessions lasting atleast 10 minutes.18 On the contrary, both maximal aerobiccapacity and anaerobic threshold modification seem not to beaffected by the remodeling of spontaneous physical activity.9

This suggests the hypothesis that if participation in aphysical exercise program is coupled with a reduction inspontaneous physical activity, some of the positive training-related effects might be lost. The aim of this study was thusto determine whether the participation of postmenopausalwomen in a program of aerobic physical exercise is linkedto a modification in their spontaneous physical activity andwhether this compensation affects body adaptations relatedto the aerobic training.

METHODS

ParticipantsOne hundred thirty-four postmenopausal women (mean T

SD age, 55.89 T 1.83 y) responded to a public advertisementplaced in the offices of several general physicians in the Pes-cara area (Italy). Telephone interviews and preliminary med-ical examinations excluded 93 ineligible women. Forty-onewomen (mean T SD age, 55.95 T 4.16 y) met the inclusioncriteria as follows: age less than 65 years; body mass indexgreater than 18.5 kg/m2 and less than 40 kg/m2; no estrogentherapy; and no history of diabetes mellitus or pulmonary,myocardial, or orthopedic diseases that would limit walking.The further requirement was as follows: no participation inany controlled diet program and regular exercise programduring the 2 years before the study. Thirty-four of the 41participants (mean T SD age, 55.89 T 3.57 y) were notreceiving pharmacological treatment. The women were con-sidered postmenopausal if their menses had naturally ceasedfor at least 12 months, accompanied by a plasma estradiollevel lower than 20 pg/mL (Fig. 1).

ProceduresThe medical examinations and measurements were per-

formed at the Centre of Sports Medicine of the BG.D’Annunzio[ University of Chieti-Pescara. The laboratoryconditions were controlled for temperature (ie, 21-C-23-C)and humidity (ie, 50%).19 The participants presented afterovernight fasting, without having performed maximal muscleexertion the day before, and underwent medical history datacollection, blood sampling, anthropometry, physical exami-nation, maximal stress test, and dietary habits interview. Afterthe tests and before the beginning of the physical exerciseprogram, the daily physical activities of the participants wererecorded for three consecutive days, in a free-living context,using the SenseWear Pro2 armband (T0). The same tests wererepeated at the end of the exercise program (T1).

Blood samplingAfter a 12-hour overnight fast, venous blood samples were

collected to measure total serum cholesterol (TC), low-densitylipoprotein cholesterol (LDL-C), high-density lipoprotein cho-

lesterol (HDL-C), triglycerides (TGs), estradiol, leptin, resistin,visfatin, glucose, and insulin. Glucose, HDL-C, TC, and TGswere assessed using direct measurements by enzymatic methods,with LDL-C calculated according to Friedewald equation.20

Enzyme-linked immunosorbent assay was used to measureplasma estradiol (DRG Instruments GmbH,Marburg, Germany),leptin (DBC Inc., London, Canada), resistin (B-Bridge Interna-tional, Inc., Cupertino, CA), visfatin (Phoenix Pharmaceuticals,Inc., Burlingame, CA), and insulin (DRG Instruments GmbH).The quantitative insulin sensitivity index (QUICKI) was calcu-lated as follows: 1/(log fasting insulin [KU/mL] + log fastingglucose [mg/dL]).21

Anthropometry and body compositionA first-level anthropometrist of the International Society

for the Advancement of Kinanthropometry carried out thebodily measurements. Body weight and stretched stature weremeasured to the nearest 0.1 kg and 0.1 cm, respectively, withthe participants dressed in light clothing and without shoes,22

using a stadiometer with a balance-beam scale (Seca 220;Seca, Hamburg, Germany). Body mass index was calculatedaccording to the formula of body weight/stature2 (in kilogramsper meter squared). Anthropometric tape (Seca 200; Seca) wasused to measure waist (WC) and hip (HC) circumferences.WC was measured as the smallest circumference between therib cage and the iliac crest, at the end of normal expiration.HC was measured at the level of the widest circumferencebetween the waist and the thighs.22 The waist-to-hip ratio was

FIG. 1. Scheme of participant recruitment and enrollment.

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calculated by dividing WC by HC. The body composition wasassessed by an electrical bioimpedance technique, using a leg-to-leg 50-kHz frequency bioelectrical impedance scale (BC-420MA; Tanita, Tokyo, Japan). The test was performed aftervoiding, in an upright position, barefoot, and without con-ducting garments. The participants also abstained from alco-hol consumption from 48 hours before the test.23 The sameanthropometrist carried out all of the bodily measurements atboth T0 and T1.

Blood pressure and aerobic fitness assessmentBlood pressure was measured twice, using a mercury

sphygmomanometer (Erkameter 3000; Erka, Bad Tolz, Ger-many) after a 5-minute seated rest. The mean of these meas-urements was used as the baseline blood pressure. If there wasmore than 5-mm Hg difference between the first and secondmeasurements, an additional measurement was taken, with themean of these three readings used. There was a 1-minute restbetween each measurement.24 Mean arterial blood pressurewas calculated as [systolic blood pressure + (2 � diastolicblood pressure)]/3. A resting 12-lead electrocardiogram (ECG;P8000, Esaote, Genoa, Italy) was performed after 10 minutesof supine rest. The heart rate (HR) recorded during the ECGwas used as the basal HR. The fitness level and eligibility ofthe participants for aerobic training were assessed through agraded maximal exercise test on a cycle ergometer (SANABIKE 150 F; Ergosana GmbH, Bitz, Germany). The partic-ipants were tested under continuous ECG monitoring (AT-10plus; SCHILLER, Baar, Switzerland) and step-by-step bloodpressure measurements. The Astrand protocol was used to testthe fitness of the participants, which ended the test accordingto the American College of Cardiology/American HeartAssociation guidelines.19 The AT-10 plus provided informa-tion about the duration and maximal intensity of the test,expressed in metabolic equivalents (METs), and the maximalpower level, expressed in watts. Maximal oxygen uptake(VO2max) was estimated by multiplying the maximal MET by3.5. The basal cardiac double product (DPbasal) was calcu-lated by multiplying the basal systolic blood pressure by HR.The maximal double product was calculated by multiplyingthe systolic blood pressure and HR recorded at the peak of thestress test. The reserve of the DP (DPreserve) was calculated bysubtracting DPbasal from maximal double product.

Dietary habits assessmentDietary habits and calorie intake were estimated by a die-

titian from 3-day dietary records, which covered two week-days and one weekend day, using the WinFood 2.7 software(Medimatica, Colonnella, Italy). This provided qualitative (ie,macronutrient composition of daily meals) and quantitative(ie, kilocalories and grams) information of the meals of theparticipants. The food portions were recorded as they wereconsumed, by self-measurements using a scale or householdmeasures (ie, cup and tablespoon), and they were recorded onan open-ended form that included a section that clarified howto draw up the dietary record. At the end of the recordingperiod, the dietitian reviewed the records with each participant

to clarify the entries, to probe for forgotten foods, and tocollect further details of the preparation of the foods.

Daily physical activity measurementsDaily physical activity was measured under free-living

conditions for 3 consecutive days,25 including two weekdaysand one weekend day, using the SenseWear Pro2 armband(BodyMedia, Pittsburgh, PA). The armband is a commerci-ally available monitor that integrates the information gatheredby the two axis accelerometers and sensors (ie, skin and near-body temperature, heat flux, and galvanic skin response) withthe sex, age, stature, weight, smoking status, and handness ofthe user, providing proprietary algorithms to give qualitative(eg, intensity) and quantitative (eg, number of daily steps andenergy expenditure) information about the daily physicalactivity. From the default information given by the software,we focused our attention on the mean values of total dailyenergy expenditure (TEEm/die), intensity of daily physicalactivities (METm/die), and time and energy spent on physicalactivities with an intensity of more than 3 METs (tPAm/die,PAEEm/die).

26 As recommended by the manufacturer, theparticipants wore the armband on the right arm over the tri-ceps muscle at the midpoint between the acromion and ole-cranon processes. The descriptive characteristics of theparticipants were entered into the software program (Sense-Wear Professional 6.1; BodyMedia) before the monitoringwas initialized. The T1 measurements included one trainingday and two nonYtraining days, including one weekday andone weekend day; they were coupled to the dietary habitsrecordings and were carried out 2 weeks before the end of thewalking training program. The mean of each parameter ofdaily physical activity of the 3-day recording was used for thestatistical analysis, for both T0 and T1. The T1 data were alsoenriched by calculating the mean physical activity parametersof both the T1 training day and the T1 nonYtraining days. Therecordings did not include days when it was raining.

Physical exercise programThe participants walked at moderate intensity for 4 days/

week, for 13 weeks. The exercise intensity was assigned andmonitored according to the ratings of the perceived exertionmethod, 27 as a low-cost method that does not require the useof devices (eg, HR monitor), and because this method allowedan automatic increase in the walking training speed to main-tain the assigned intensity as the aerobic fitness increased.This latter characteristic is important because, to adequatelystimulate the body, the use of the HR method requires thecalculation of new target HR values when aerobic fitnessincreases and resting HR decreases as a consequence of theaerobic training.

The participants were familiarized with this method beforethe beginning of the training and during the first week oftraining. During the first month of training, each trainingsession lasted 40 minutes, at a walking speed for an effort of11 on the 15-category rating of perceived exertion scale(RPE).27 During the second month of training, each trainingsession lasted 50 minutes at the same intensity, whereas during

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the third month of training, the participants increased only thetraining intensity, from 11 to 13 RPE. All of the participantswalked together, even though the beginning and end of theexercise programs were split according to the date of their firstassessments: the participants were evaluated during the weekbegan their training the following Monday. Two of the fourweekly sessions were supervised. Compliance with the trainingsessions was checked through the training diaries of the womenand the exercise trainer. The walking training was the onlystudy intervention. We calculated the volume of each exercisesession, multiplying the time of the session by the RPE points.The sum of the volume of all of the completed exercise ses-sions provided the volume of the exercise program of each

participant. To eliminate the effects of seasonal changes on theamounts and patterns of physical activity,28 the study wasconducted during summer.

Statistical analysisStatistical analysis was performed on the 34 participants

who were not receiving any pharmacological treatments. Theseven women who were excluded from the analysis tookblood pressureY and plasma lipidYlowering drugs that couldcover the relationships of both physical activity and phy-sical exercise with blood pressure and plasma lipids. The datawere tested for normality before statistical analysis and arepresented as means T SD. Paired-sample t tests were performed

TABLE 1. Characteristics of the 34 participants assessed at T0 and T1

Characteristic T0 T1 P

Anthropometric parametersBody mass, kg 65.98 T 10.16 65.53 T 10.03 0.034BMI, kg/m2 26.87 T 4.17 26.68 T 4.31 0.027Waist circumference, cm 85.12 T 10.47 84.37 T 10.35 0.219Hip circumference, cm 103.08 T 7.99 101.25 T 8.11 0.001Waist-to-hip ratio 0.82 T 0.06 0.83 T 0.06 0.224Fat mass, % 34.73 T 6.04 34.87 T 6.10 0.536Fat mass, kg 23.48 T 7.32 23.39 T 7.30 0.629

Cardiovascular and aerobic fitness parametersHeart rate, beats/min 65.88 T 7.58 60.26 T 5.81 G0.001Systolic blood pressure, mm Hg 126.32 T 16.8 121.03 T 9.67 0.020Diastolic blood pressure, mm Hg 79.26 T 8.08 77.65 T 5.39 0.148Mean arterial blood pressure, mm Hg 94.95 T 10.5 89.26 T 17.06 0.084DPbasal, beats/min � mm Hg 9,794.70 T 1,670.58 7,259.41 T 978.27 G0.001DPmax, beats/min � mm Hg 24,712.94 T 4,674.19 24,660.59 T 3,437.17 0.925DPreserve, beats/min � mm Hg 14,918.24 T 4,357.71 17,401.18 T 3,554.72 G0.001VO2max, mL kgj1 minj1 27.01 T 5.03 29.45 T 4.97 G0.001

Physical activity parametersTEEm/die, kcal 2,311.41 T 300.96 2,347.42 T 349.61 0.434METm/die 1.49 T 0.25 1.51 T 0.27 0.492tPAm/die, min 119.40 T 84.09 115.40 T 94.59 0.793PAEEm/die, kcal 476.91 T 284.65 494.79 T 335.01 0.764

Dietary habitsTotal energy intake, kcal 1,776.47 T 406.34 1,856.30 T 367.28 0.106Protein, % 15.90 T 1.96 15.80 T 1.97 0.771Lipid, % 34.24 T 4.83 33.59 T 5.42 0.381Carbohydrate, % 49.83 T 4.93 50.55 T 6.11 0.334Saturated fat, %TEI 8.18 T 1.94 10.43 T 9.60 0.162Polyunsaturated fat, %TEI 2.96 T 1.21 3.23 T 1.42 0.094Monounsaturated fat, %TEI 15.53 T 4.03 15.04 T 3.68 0.394Thiamine, mg 0.69 T 0.18 0.77 T 0.20 0.021

Plasma lipidsTotal cholesterol, mg/dL 235.62 T 43.38 232.35 T 40.73 0.392Low-density lipoprotein, mg/dL 152.62 T 37.52 149.18 T 36.41 0.240High-density lipoprotein, mg/dL 60.50 T 16.06 60.74 T 13.19 0.879Triglycerides, mg/dL 110.06 T 67.50 110.00 T 44.72 0.992

AdipokinesLeptin, ng/mL 55.10 T 26.45 44.97 T 25.91 G0.001Resistin, ng/mL 3.12 T 1.79 2.40 T 1.20 G0.001Visfatin, ng/mL 5.09 T 7.44 7.14 T 7.58 0.954

MiscellaneousEstradiol, pg/mL 10.46 T 5.33 Y YInsulin, KU/mL 11.26 T 6.58 12.04 T 8.42 0.555Glycemia, mg/dL 80.32 T 7.86 75.97 T 8.46 G0.001QUICKI 0.34 T 0.03 0.35 T 0.03 G0.001

Data are presented as means T SD. Although the software used gave information about 70 bromatological components of the daily meals, we present here the datafor only the total energy intake, the macronutrient composition of daily meals, the composition of the lipid intake, and the modified micronutrients.BMI, body mass index; DPbasal, basal cardiac double product; DPmax, maximal cardiac double product; DPreserve, reserve of cardiac double product; TEEm/die,mean total daily energy expenditure; METm/die, intensity of daily physical activities; tPAm/die, time spent on physical activities with an intensity greater than 3METs; PAEEm/die, energy spent on physical activity with an intensity greater than 3 METs; TEI, total energy intake; QUICKI, quantitative insulin sensitivityindex; VO2max, maximal oxygen uptake; METs, metabolic equivalents; T0, before exercise program; T1, end of exercise program.

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to determine the significant changes from T0 to T1. The varia-tions in TEEm/die, METm/die, tPAm/die, and PAEEm/die were usedas clustering variables in a cluster analysis to investigate thepresence of different responses of spontaneous physical acti-vity to participation in the aerobic physical exercise. Twosubgroups were detected, according to their different sponta-neous physical activity remodeling: one group that reduced itsspontaneous physical activity (GROUPj) and a second groupthat did not (GROUP+). Two-way analysis of variance(ANOVA; group � time) with repeated measures for the factorBtime[ was used to determine the trends in both physicalactivity parameters and maximal aerobic capacity of the twosubgroups. One-way ANOVA with repeated measures for thefactor time was performed to identify any changes withingroups. Independent-sample t tests were performed to deter-mine whether the subgroups had different basal levels ofthe variables investigated. Two-way analysis of covariance(ANCOVA; group � time) with repeated measures for thefactor time was used to separately investigate the trends in thecardiovascular parameters, plasma lipids, adipokines, andinsulin, according to the two subgroups. The changes in WCwere used as the covariate in the cardiovascular parametersanalysis, and the changes in thiamine in the plasma lipidsanalysis, whereas the changes in the kg fat mass (FMkg) andQUICKI were used as the covariates in the adipokine analysis.The changes in WC and FMkg were used as covariates in the

QUICKI analysis. One-way ANCOVA with repeated mea-sures for the factor time was performed to identify changeswithin groups. The changes in each parameter were calculatedby subtracting the values recorded at T0 from those recorded atT1. Statistical analysis was performed using STATA 10 soft-ware (StataCorp LP, College Station, TX).

RESULTS

Basal conditionsThe participants were 5.36 T 2.71 years postmenopause,

and their full characteristics are shown in Table 1. Comparisonof their data according to the regional tables of the ProgettoCuore (an Italian epidemiological study that reported theprevalence of cardiovascular risk factors according to sex andphysiological [eg, menopause] and pathological conditions;http://www.cuore.iss.it/eng/) and relating to their plasma lip-ids, body composition, and daily physical activity indicatedthat our sample was representative of postmenopausal women.They were, on average, overweight, showing an anthropometricvariability that ranged from normal body composition to obe-sity.23 They had normal blood pressures on average, althoughsome women with first-grade hypertension were included.29

Their mean aerobic fitness was fair, although it ranged frompoor to good.23 The intensity of their daily physical activity waslow active on average and ranged from sedentary to highlyactive.30 On average, they had normal levels of plasma TGsand high levels of both TC and HDL-C.31 Their plasma glu-cose and insulin levels were normal, whereas they showedhigh levels of leptin,32 normal levels of resistin, and low levelsof visfatin.33,34 Their dietary habits were characterized bydiets high in protein and low in sugar, with their protein andcarbohydrate intake just outside the reference ranges. Theirpolyunsaturated and monounsaturated fat intakes were nor-mal, whereas their saturated fat intake exceeded the recom-mended levels.35

T0 versus T1

Paired-sample t tests showed that from T0 to T1, several ofthe investigated parameters changed significantly, whereas

TABLE 2. Cluster analysis results characterizing the subgroupsaccording to the changes in their physical activity

Physical activity changes GROUP+ (n = 19) GROUPj (n = 15)

$TEEm/die, kcal 218.01 T 173.83 j194.51 T 158.67$ METm/die 0.14 T 0.11 j0.13 T 0.08$tPAm/die, min 44.53 T 62.35 j65.46 T 78.07$PAEEm/die, kcal 223.80 T 269.11 j233.62 T 262.91

Data are presented as means T SD.TEEm/die, mean total daily energy expenditure; METm/die, mean intensity ofdaily physical activities; tPAm/die, time spent on physical activities with anintensity greater than 3 METs; PAEEm/die, energy spent on physical activi-ties with an intensity greater than 3 METs; METs, metabolic equivalents;GROUPj and GROUP+, a group that reduced its spontaneous physicalactivity and the one that did not, respectively.

TABLE 3. Two-way ANOVA analysis for comparisons of the subgroups for physical activity changes fromT0 to the T1 training day and the T1 nonYtraining days

Physical activity parameters T0 T1 training day T1 nonYtraining days T0 vs T1 training day T0 vs T1 nonYtraining days

TEEm/die, kcalGROUP+ 2,281.87 T 278.86 2,556.26 T 299.33 2,442.68 T 323.25 F = 28.738 F = 42.545GROUPj 2,348.83 T 332.92 2,254.43 T 349.50 2,080.3 T 320.01 P G 0.001 P G 0.001

METm/die

GROUP+ 1.45 T 0.25 1.64 T 0.30 1.56 T 0.30 F = 39.067 F = 46.850GROUPj 1.54 T 0.24 1.45 T 0.18 1.36 T 0.20 P G 0.001 P G 0.001

tPAm/die, minGROUP+ 103.68 T 76.39 166.73 T 113.48 130.89 T 115.52 F = 24.091 F = 15.844GROUPj 139.30 T 91.68 101.33 T 46.22 53.60 T 42.32 P G 0.001 P G 0.001

PAEEm/die, kcalGROUP+ 409.53 T 238.92 722.21 T 368.79 537.00 T 397.12 F = 27.169 F = 18.269GROUPj 562.27 T 321.91 441.00 T 202.89 237.76 T 196.47 P G 0.001 P G 0.001

df = 1,32; Data are presented as means T SD.TEEm/die, mean total daily energy expenditure; METm/die, mean intensity of daily physical activities; tPAm/die, time spent on physical activities with an intensitygreater than 3 METs; PAEEm/die, energy spent on physical activity with an intensity greater than 3 METs; METs, metabolic equivalents; GROUPj and GROUP+,a group that reduced its spontaneous physical activity and the one that did not, respectively; ANOVA, analysis of variance; T0, before exercise program; T1, end ofexercise program.

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there were no significant changes in TEEm/die, METm/die,tPAm/die, and PAEEm/die, despite the use of the walkingtraining program (Table 1). To better understand this lackof effect of the walking training program here, cluster anal-ysis was performed on the changes in TEEm/die, METm/die,tPAm/die, and PAEEm/die. This revealed two subgroups: onesubgroup that reduced its spontaneous physical activity(GROUPj) and a second subgroup that did not (GROUP+;Table 2). The attendance for the physical exercise programwas 85.90% T 10.75%.

GROUP+ versus GROUPjThese subgroups identified had significant opposite trends in

their TEEm/die, METm/die, tPAm/die, and PAEEm/die (Table 3).GROUPj showed significant reductions in all four of theseparameters from T0 to both the T1 training day and the T1nonYtraining days (Table 4). GROUP+ showed significantimprovements for TEEm/die, METm/die, tPAm/die, and PAEEm/die

from T0 to the T1 training day, although significant improve-ments were only seen for TEEm/die and METm/die in the com-parison of T0 with the T1 nonYtraining days (Table 4). Of note,independent-sample t tests performed on the basal levels ofthese subgroups showed that they did not differ. Table 5 sum-marizes the results of the two-way ANOVA. Here, the sub-groups showed the same trends in maximal aerobic capacity(F1,31 = 22.486; P G 0.001), HR (F1,31 = 18.166; P G 0.001),systolic blood pressure (F1,31 = 4.663; P = 0.039), DPbasal(F1,31 = 98.522; P G 0.001), and DPreserve (F1,31 = 27.157;P G 0.001): all of these parameters were significantly improved,independent of the subgroup membership (Table 5).

Statistical analysis of the plasma lipids showed that thesubgroups differed in their LDL-C (group � time: F1,31 =

5.177; P = 0.030) and TC (group � time: F1,31 = 10.575; P =0.003) trends independent of the changes in thiamine (Fig. 2):GROUP+ showed reduced LDL-C (F1,17 = 4.193; P = 0.05)and TC (F1,17 = 5.897; P = 0.027), whereas GROUPj did not

TABLE 4. One-way ANOVA analysis data for thephysical activity changes from T0 to the T1training day and the T1 nonYtraining days

Physical activity F df P

GROUPj T0 vs T1 training dayTEEm/die, kcal 31.875 1, 15 G0.001METm/die 10.565 1, 15 0.006tPAm/die, min 6.851 1, 15 0.02PAEEm/die, kcal 4.703 1, 15 0.048

GROUPj T0 vs T1 nonYtraining daysTEEm/die, kcal 32.991 1, 15 G0.001METm/die 35.557 1, 15 G0.001tPAm/die, min 11.847 1, 15 0.004PAEEm/die, kcal 15.823 1, 15 0.001

GROUP+ T0 vs T1 training dayTEEm/die, kcal 38.729 1, 18 G0.001METm/die 32.667 1, 18 G0.001tPAm/die, min 19.580 1, 18 G0.001PAEEm/die, kcal 27.803 1, 18 G0.001

GROUPj T0 vs T1 nonYtraining daysTEEm/die, kcal 12.577 1, 18 0.002METm/die 14.512 1, 18 0.001

TEEm/die, mean total daily energy expenditure; METm/die, mean intensity ofdaily physical activities; tPAm/die, time spent on physical activities with anintensity greater than 3 METs; PAEEm/die, energy spent on physical activitywith an intensity greater than 3 METs; METs, metabolic equivalents;GROUPj and GROUP+, a group that reduced its spontaneous physicalactivity and the one that did not, respectively; ANOVA, analysis of variance;T0, before exercise program; T1, end of exercise program.

TABLE 5. Response to aerobic training according to subgroupmembership for maximal aerobic capacity (VO2max), HR,systolic blood pressure, basal cardiac double product

(DPbasal), and double product reserve(DPreserve). RM-ANOVA results

GROUP+ (n = 19) GROUPj (n = 15)

VO2max, mL kgj1 minj1

T0 25.97 T 4.89 28.32 T 5.05T1 28.44 T 5.29 30.74 T 4.37

HR, beats/minT0 65.74 T 6.59 66.07 T 8.91T1 61.37 T 6.21 58.87 T 5.12

Systolic blood pressure, mmHgT0 127.63 T 19.24 124.67 T 13.55T1 122.63 T 10.45 119.00 T 8.49

DPbasal, beats/min � mm HgT0 9,840.52 T 1,799.69 9,736.66 T 1,551.67T1 7,451.57 T 1,029.87 7,016.00 T 882.36

DPreserve, beats/min � mm HgT0 14,864.47 T 5,312.59 14,986.33 T 2,909.44T1 17,341.32 T 4,511.27 17,477.00 T 1,899.37

Data are presented as means T SD.HR, heart rate; RM-ANOVA, repeated-measures analysis of variance; GROUPjand GROUP+, a group that reduced its spontaneous physical activity andthe one that did not, respectively; T0, before exercise program; T1, end ofexercise program.

FIG. 2. Responses for TC and LDL-C to aerobic training accord-ing to subgroup membership: white column, GROUPj; gray column,GROUP+. TC, total cholesterol; T0, before exercise program; LDL-C, low-density lipoprotein cholesterol; T1, end of exercise program; GROUPj, agroup that reduced its spontaneous physical activity; GROUP+, a groupthat maintained its spontaneous physical activity.

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show significantly modified plasma lipids. In contrast, in two-way ANCOVA with the changes in FMkg and QUICKI usedas covariates, both leptin (F1,30 = 13.072; P = 0.001) andresistin (F1,30 = 8.104; P = 0.008) were significantly improvedindependent of the subgroup membership and changes in thecovariates (ie, FMkg and QUICKI; Table 6). Also, QUICKIshowed significant improvements independent of the sub-group membership and changes in the covariates (ie, Fmkg andWC; F1,30 = 16.583; P G 0.001; Table 6). No other signifi-cant modifications were seen, and the subgroups did notdiffer in their volumes of the exercise program accomplished,expressed as minutes � RPE (GROUP+ 24,159.87 T 5,769.88vs GROUPj 24,136.17 T 6,343.78; P = 0.991).

DISCUSSION

Physical activityThe first finding in this study was the confirmation that the

addition of an aerobic physical exercise program can indeednegatively affect the spontaneous physical activity of post-menopausal women. Given the results of the cluster analysisacross the two subgroups (ie, GROUPj, GROUP+) and theobservation that these two subgroups achieved the same vol-ume of physical exercise, it seems that these two subgroupsdiffered only in this remodeling of their spontaneous physicalactivity. This hypothesis is supported by the two-wayANOVA comparing the T0 physical activity parameters (ie,TEEm/die, METm/die, tPAm/die, PAEEm/die) with those of the T1training day and the T1 nonYtraining days separately: at theend of the treatment, the GROUPj participants had reducedtheir spontaneous physical activity during both the T1 trainingday and the T1 nonYtraining days, whereas GROUP+ partic-ipants showed increased spontaneous physical activity duringthe T1 nonYtraining days (Tables 3-6). Even if we do not knowthe reason for this different behavior, which was also observedby Manthou et al,9 this is a very important phenomenon toconsider because such compensatory reduction in their spon-taneous physical activity will hamper some of the positive

physiological modifications that are induced by the physicalexercise.

Plasma lipidsThe results observed suggest a role for spontaneous phys-

ical activity remodeling in the plasma lipid changes. In-deed, even if both subgroups performed the same volumes inthe physical exercise program and did not significantly mod-ify their body compositions, only GROUP+ had both TCand LDL-C improvements, which were also independent ofchanges in thiamine, which has been shown to modulate thelipid profile (Fig. 2).36,37 This micronutrient was used as acovariate because thiamine is the only micronutrient that issignificantly modified among those considered as influencingfactors of plasma lipids. The studies of Kraus et al11 andSlentz et al38 evaluated the importance of the volume and theintensity of physical exercise on dyslipidemia and showedthat the volume is more important than the intensity, at boththe end of a regular aerobic exercise program and 15 daysafter its end. Thus, our data are in agreement with thesestudies, and they can be explained through the analysis of thespontaneous daily physical activity. Indeed, housework andthe typical activities of daily living, such as walking at a briskpace, cycling on the flat, and dancing, are categorized asphysical activities of moderate intensities (ie, 3.0-6.0 METs),39

and these contribute to the daily volume of the physicalactivities that are useful for the control of plasma lipids.11,12,38

As a consequence, if such an aerobic physical exercise pro-gram is accompanied by a reduction in spontaneous dailyphysical activities of moderate intensities, the TC and LDL-Cwill not be positively modified. In this scenario, even if theaerobic physical exercise program provides metabolic andmuscular modifications that lead to increased lipid uptakeand oxidation in the skeletal muscle, the reduction in sponta-neous physical activity will impair the possibility of sig-nificantly increasing the daily energy expenditure and thusprevent the full benefit from being achieved from the meta-bolic consequences of these muscular adaptations and shiftsin fuel composition.40

Adipokines and insulin sensitivityIn contrast, the addition of an aerobic physical exercise

program seems to be sufficient to provide improvements toleptin and resistin levels in postmenopausal women, inde-pendent of spontaneous physical activity remodeling. Indeed,both of the subgroups showed the same trend for these adi-pokines, also taking into account the effects of the changes inboth FMkg and QUICKI (ie, insulin sensitivity), which havebeen shown to modulate both leptin and resistin.41<44 Thedifferent trends seen for the plasma lipids and adipokinesfocus the attention on the importance of the characteristics ofthe physical activity on some metabolic parameters: althoughthe volume of daily physical activities seems to be importantfor plasma lipids, participation in a physical exercise programhas a central role for adipokine improvements that is inde-pendent of spontaneous physical activity remodeling. Ourhypothesis suggests that in our subgroups, the reduction in

TABLE 6. Response to aerobic training according to subgroupmembership for leptin, resistin, and QUICKI. RM-ANCOVA results

GROUP+ (n = 19) GROUPj (n = 15)

Leptin, ng/mLT0 56.62 T 26.71 58.25 T 26.7T1 42.48 T 26.44 48.12 T 25.79

Resistin, ng/mLT0 3.56 T 2.08 2.55 T 1.17T1 2.59 T 1.27 2.17 T 1.09

QUICKIT0 0.354 T 0.03 0.344 T 0.04T1 0.357 T 0.031 0.346 T 0.041

Data are presented as means T SD. Variation of both kilograms of fat mass andQUICKI was used as a covariate for leptin and resistin analysis. Variation ofboth kilograms of fat mass and waist circumference was used as a covariatefor QUICKI analysis.QUICKI, quantitative insulin sensitivity check index; RM-ANCOVA, repeated-measures analysis of covariance; GROUPj and GROUP+, a group that reducedits spontaneous physical activity and the one that did not, respectively; T0, beforeexercise program; T1, end of exercise program.

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spontaneous physical activity did not negatively affect theplasma leptin and resistin levels because the nonexercisetimes of postmenopausal women were usually between sev-eral brief bouts (ie, G10 min) of moderate-intensity physicalactivities. Indeed, Esteghamati et al45 found that leptin con-centrations are directly associated with sedentary behaviorand inversely associated with the duration of the total dailyphysical activity, and with physical activities performed atmoderate and vigorous intensities, adjustment for age, sex,smoking, and body adiposity. Esteghamati et al45 estimatedthe quality and quantity of daily physical activities, inves-tigating physical activities that lasted continuously for atleast 10 minutes. Even if there is no specific study relating tothe relationships between resistin levels and the character-istics of physical activities in postmenopausal women, thestudy of Rubin et al46 on adolescents seems to partiallysupport our hypothesis. They found that the resistin levelscorrelated with vigorous physical activity independent ofbody fat, and they suggested that this was caused by reduc-tion in resistin production by peripheral blood mononuclearcells,47 for which the production of proinflammatory cyto-kines is down-regulated by exercise training.48 Anotherimportant finding relating to the adipokines is the reductionin both leptin and resistin that was independent of thechanges in FMkg and QUICKI, which is in agreement withstudies that support the relevance of physical exercise despitethe lack of macroscopic body modifications (eg, fat massreduction) and the underlying positive effects on adipo-kines production through both insulin-dependent42,49,50 andinsulin-independent pathways.41,51 The same result was seenfor insulin sensitivity, because there was a decrease in theQUICKI in both of our subgroups, independent of the ef-fects of the changes in FMkg and WC. Physical exerciseenhances insulin sensitivity in the exercised muscle and mus-cle contractionYinduced glucose uptake, through effects onreceptors, enzymes, blood vessels, blood flow, and the endo-thelium.12 The role of physical exercise in insulin sensi-tivity was also highlighted by Koo et al,52 who showed thatinsulin sensitivity is not related to the total daily energyexpenditure but to the energy expenditure derived frommoderate-to-vigorous-intensity exercise.

Cardiovascular and aerobic fitness parametersPositive effects of the physical exercise were seen for the

cardiovascular and aerobic fitness parameters, independent ofspontaneous physical activity remodeling. Indeed, both sub-groups showed reductions in HR, systolic blood pressure, andDPbasal and increases in DPreserve and maximal aerobic capacity.These data seem to be due to two contemporaneous conditions:a minimal VO2reserve intensity of 45% for normally fit, or 30%for less fit, persons,53 and a minimum of 30 minutes of aerobicactivity at moderate intensity that is accumulated in bouts ofnot less than 10 minutes.54 As a consequence, the reduction inspontaneous physical activity did not negatively affect thecardiovascular and aerobic fitness parameters of the GROUPjparticipants, probably because the qualitative and quantitative

characteristics of the nonexercise time of these postmenopausalwomen did not reach the minimal requirements to providecardiovascular adaptations and aerobic fitness improvements.

Study considerations and future directionsThe main limitation to this study is the presence of only two

observation points (ie, T0 and T1). Indeed, during the period of13 weeks, the participants might have had nonlinear trends intheir dietary and physical activity habits that can result in anabsence of changes in certain parameters (ie, FMkg) or can,otherwise, explain the changes observed. It is also importantto note that even if the weighed food records are coupled withthe dietitian interviews here, inaccuracies in data collection55

and underreporting56,57 would have affected the dietary habitsanalysis. Bearing these limitations in mind, further studies areneeded to allow us to better understand the results observed,with increased sample sizes and including intermediate eval-uations, to be sure of the real trends in each of the variablesconsidered. Also, even if we conducted the study during asingle season (ie, summer), to eliminate the known effects ofseasonal changes on the amounts and patterns of physicalactivity,28 the nonrandomized nature of the intervention doesnot fully eliminate the possibility that the modificationsobserved are exclusively linked to the participation in theaerobic physical exercise program. These limitations shouldbe overcome with future studies.

In contrast, the multisensory tool that was chosen tomeasure the daily physical activities here (ie, the SenseWearPro3 armband) allowed several characteristics of the dailymovements of the participants to be taken into account in theanalysis of physical activity remodeling and allowed us torecognize two subgroups based on the qualitative and quan-titative remodeling of their daily movement. This device willhave reduced the errors and limitations that are intrinsicallylinked with self-reporting diaries, pedometers, monoaxialaccelerometers, HR recordings, and the double-labeled watermethod.58

CONCLUSIONS

In conclusion, participation in a program of aerobic phy-sical exercise can negatively affect the spontaneous physicalactivities of postmenopausal women. This effect needs to beprevented to avoid the failure of some of the physiological goalsof physical exercise programs. Indeed, plasma lipids did notimprove when the spontaneous physical activity was reduced inboth quality and quantity. In contrast, improvements were seenfor leptin, resistin, insulin sensitivity, HR, systolic blood pres-sure, DPbasal, DPreserve, and maximal aerobic capacity inde-pendent of spontaneous physical activity remodeling and ofsome specific influencing factors, which suggests the impor-tance of the characteristics of the body movement for thestimulation of several body adaptations. Therefore, to obtainthe benefits of physical exercise in the primary and secondarypreventions of chronic cardiometabolic diseases, compliancein the physical exercise program, dietary habits, and sponta-neous physical activity remodeling should be monitored,

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with contemporary psychological counseling as a fair ally, toavoid a reduction in the daily movements.

Acknowledgments: We thank Dr. Christopher Berrie for linguisticrevision of the manuscript.

REFERENCES

1. Asikainen TM, Kukkonen-Harjula K, Miilunpalo S. Exercise for healthfor early post-menopausal women. Sports Med 2004;34:753-778.

2. Westerterp KR, Meijer GA, Janssen EM, Saris WH, Ten Hoor F. Long-term effect of physical activity on energy balance and body composition.Br J Nutr 1992;68:21-30.

3. King NA, Snell L, Smith RD, Blundell JE. Effects of short-term exerciseon appetite responses in unrestrained females. Eur J Clin Nutr 1996;50:663-667.

4. Stubbs RJ, Sepp A, Hughes DA, et al. The effect of graded levels ofexercise on energy intake and balance in free-living women. Int J ObesRelat Metab Disord 2002;26:866-869.

5. Turner JE, Markovitch D, Betts JA, Thompson D. Nonprescribed phys-ical activity energy expenditure is maintained with structured exerciseand implicates a compensatory increase in energy intake. Am J Clin Nutr2010;92:1009-1016.

6. Goran MI, Poehlman ET. Endurance training does not enhance totalenergy expenditure in healthy elderly persons. Am J Physiol 1992;263:E950-E957.

7. Kempen KP, Saris WH, Westerterp KR. Energy balance during an 8-wkenergy-restricted diet with and without exercise in obese women. Am JClin Nutr 1995;62:722-729.

8. Donnelly JE, Smith BK. Is exercise effective for weight loss with ad-libitum diet? Energy balance, compensation, and gender differences.Exerc Sport Sci Rev 2005;33:169-174.

9. Manthou E, Gill JMR, Wright A, Malkova D. Behavioral compensatoryadjustment to exercise training in overweight women. Med Sci SportsExerc 2010;42:1121-1128.

10. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exerciseand physical fitness: definitions and distinctions for health-relatedresearch. Public Health Rep 1985;100:126-131.

11. Kraus WE, Houmard JA, Duscha BD, et al. Effects of the amount andintensity of exercise on plasma lipoproteins. N Engl J Med 2002;347:1482-1492.

12. Pedersen BK, Saltin B. Evidence for prescribing exercise as therapy inchronic disease. Scand J Med Sci Sports 2006;16:3-63.

13. Hinkleman LL, Nieman DC. The effects of a walking program on bodycomposition and serum lipids and lipoproteins in overweight women. JSports Med Phys Fitness 1993;33:49-58.

14. Nieman DC, Warren BJ, O_Donnell KA, Dotson RG, Butterworth DE,Henson DA. Physical activity and serum lipids and lipoproteins in elderlywomen. J Am Geriatr Soc 1993;41:1339-1344.

15. Stensel DJ, Hardman AE, Brooke-Wavell KSF, et al. Brisk walking andserum lipoprotein variables in formerly sedentary men aged 42-59 years.Clin Sci 1993;85:701-708.

16. Santiago MC, Leon AS, Serfass RC. Failure of 40 weeks of brisk walkingto alter blood lipids in normolipemic women. Can J Appl Physiol1995;20:417-428.

17. Nieman DC, Brock DW, Butterworth D, Utter AC, Nieman CC. Reduc-ing diet and/or exercise training decreases the lipid and lipoprotein riskfactors of moderately obese women. J Am Coll Nutr 2002;21:344-350.

18. ACSM/AHA. Physical activity and public health. Circulation 2007;116:1081-1093.

19. ACSM. ACSM Guidelines for Exercise Testing and Prescription, 7th ed.Baltimore, MD: Lippincott Williams & Wilkins, 2005.

20. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concen-tration of low-density lipoprotein cholesterol in plasma, without use ofthe preparative ultracentrifuge. Clin Chem 1972;18:499-502.

21. Katz A, Nambi SS, Mather K, et al. Quantitative insulin sensitivity checkindex: a simple, accurate method for assessing insulin sensitivity inhumans. J Clin Endocrinol Metab 2000;85:2402-2410.

22. Marfell-Jones M, Olds T, Stewart A, Carter L. International Standardsfor Anthropometric Assessment. Potchefstroom, SA: ISAK, 2006.

23. Heyward VH. Advanced Fitness Assessment and Exercise Prescription.Champaign, IL: Human Kinetics, 2006.

24. Pickering TG, Hall JE, Appel LJ, et al. Recommendations for bloodpressure measurement in human and experimental animals: part 1. Bloodpressure measurement in humans. A statement for professionals from thesubcommittee of professional and public education of the AmericanHeart Association Council on High Blood Pressure Research. Hyper-tension 2005;45:142-161.

25. Pes GM, Tolu F, Battistini NC, Delitala G, Maioli M. Analisi cronobio-logica dell’attivita fisica in soggetti con ridotta tolleranza ai carboidrati(RTC). G It Diabetol Metab 2009;29:60-65.

26. Welk GJ, McClain JJ, Eisenmann JC, Wickel EE. Field validation of theMTI Actigraph and BodyMedia armband monitor using the IDEEAmonitor. Obesity 2007;15:918-928.

27. Borg G. Borg’s Perceived Exertion and Pain Scales. Champaign, IL:Human Kinetics, 1998.

28. Buchowski MS, Choi L, Majchrzak KM, Acra S, Mathews CE, ChenKY. Seasonal changes in amount and patterns of physical activity inwomen. J Phys Act Health 2009;6:252-261.

29. Chobanian AV, Bakris GL, Black HR, et al. JNC7Vcomplete report:seventh report of the Joint National Committee on prevention, detection,evaluation, and treatment of high blood pressure. Hypertension 2003;42:1206-1252.

30. Brooks GA, Butte NF, Rand WM, Flatt JP, Caballero B. Chronicle of theInstitute of Medicine physical activity recommendation: how a physicalactivity recommendation came to be among dietary recommendations.Am J Clin Nutr 2004;79:921S-930S.

31. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cho-lesterol in Adults. Executive summary of the Third Report of the NationalCholesterol Education Program (NCEP). JAMA 2001;285:2486-2497.

32. Marques-Vidal P, Bochud M, Paccaud F, Mooser V, Waeber G,Vollenweider P. Distribution of plasma levels of adiponectin and leptinin an adult Caucasian population. Clin Endocrinol 2010;72:38-46.

33. Silha JV, Krsek M, Skrha JV, Sucharda P, Nyomba BL, Murphy LJ.Plasma resistin, adiponectin and leptin levels in lean and obese subjects:correlations with insulin resistance. Eur J Endocrinol 2003;149:331-335.

34. Berndt J, Kloting N, Kralisch S, et al. Plasma visfatin concentrationsand fat depot-specific mRNA expression in humans. Diabetes 2005;54:2911-2916.

35. Caballero B, Allen L, Prentice A. Encyclopedia of Human Nutrition,2nd ed. Oxford, UK: Elsevier, 2005.

36. Thornalley PJ. The potential role of thiamine (vitamin B1) in diabeticcomplications. Curr Diabetes Rev 2005;1:287-298.

37. Naveed AK, Quamar T, Ahmad I, Raheem A, Malik MM. Effect of thi-amine on lipid profile in diabetic rats. J Coll Physicians Surg Pak2009;19:165-168.

38. Slentz CA, Houmard JA, Johnson JL, et al. Inactivity, exercise trainingand detraining, and plasma lipoproteins. STRRIDE: a randomized, con-trolled study of exercise intensity and amount. J Appl Physiol 2007;103:432-442.

39. Ainsworth BW, Haskell MC, White MC. Compendium of physicalactivities: an update of activity codes and MET intensities. Med SciSports Exerc 2000;32:S498-S504.

40. Turcotte LP, Fisher JS. Skeletal muscle insulin resistance: roles of fattyacid metabolism and exercise. Phys Ther 2008;88:1279-1296.

41. Steppan CM, Bailey ST, Bhat S, et al. The hormone resistin links obesityto diabetes. Nature 2001;409:307-312.

42. Corpeleijn E, Feskens EJ, Jansen EH, Mensink M, Saris WH, Blaak EE.Lifestyle intervention and adipokine levels in subjects at high risk fortype 2 diabetes: the Study on Lifestyle Intervention and Impaired GlucoseTolerance, Maastricht (SLIM). Diabetes Care 2007;30:3125-3127.

43. Huuskonen A, Lappalainen J, Tanskanen M, Oksala N, Kyrolainen H,Atalay M. Genetic variations of leptin and leptin receptor are associatedwith body composition changes in response to physical training. CellBiochem Funct 2010;28:306-312.

44. Miyazaki S, Izawa T, Ogasawara J, et al. Effect of exercise training onadipocyte-sizeYdependent expression of leptin and adiponectin. Life Sci2010;86:691-698.

45. Esteghamati A, Khalilzadeh O, Ashraf H, et al. Physical activity is cor-related with serum leptin independent of obesity: results of the nationalsurveillance of risk factors of non-communicable diseases in Iran.Metabolism 2010;59:1730-1735.

46. Rubin DA, McMurray RG, Harrell JS, Thorpe DE, Hackney AC. Vigo-rous physical activity and cytokines in adolescents. Eur J Appl Physiol2008;103:495-500.

Menopause, Vol. 19, No. 1, 2012 9

PHYSICAL ACTIVITY, PHYSICAL EXERCISE, AND POSTMENOPAUSE

47. Patel L, Buckels AC, Kinghorn IJ, et al. Resistin is expressed in humanmacrophages and directly regulated by PPAR F activators. BiochemBiophys Res Commun 2003;300:472-476.

48. Smith JK, Dykes R, Douglas JE, Krishnaswamy G, Berk S. Long-termexercise and atherogenic activity of blood mononuclear cells in persons atrisk of developing ischemic heart disease. JAMA 1999;281:1722-1727.

49. Pasman WJ, Westerterp-Plantenga MS, Saris WH. The effect of exercisetraining on leptin levels in obese males. Am J Physiol 1998;274:E280-E286.

50. Montez JM, Soukas A, Asilmaz E, Fayzikhodjaeva G, Fantuzzi G,Friedman JM. Acute leptin deficiency, leptin resistance, and the physio-logic response to leptin withdrawal. Proc Natl Acad Sci U S A 2005;102:2537-2542.

51. Kadoglou NP, Perrea D, Iliadis F, Angelopoulou N, Liapis C, AlevizosM. Exercise reduces resistin and inflammatory cytokines in patients withtype 2 diabetes. Diabetes Care 2007;30:719-721.

52. Koo BK, Han KA, Ahn HJ, Jung JY, Kim HC, Min KW. The effects oftotal energy expenditure from all levels of physical activity vs. physicalactivity energy expenditure from moderate-to-vigorous activity on vis-ceral fat and insulin sensitivity in obese type 2 diabetic women. DiabetMed 2010;27:1088-1092.

53. Swain DP, Franklin BA. VO2 reserve and the minimal intensity for improvingcardiorespiratory fitness. Med Sci Sports Exerc 2002;34:152-157.

54. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health:updated recommendation for adults from the American College of SportsMedicine and the American Heart Association. Med Sci Sports Exerc2007;39:1423-1434.

55. Hill RJ, Davies PS. The validity of self-reported energy intake as deter-mined using the doubly labelled water technique. Br J Nutr 2001;85:415-430.

56. Goris AH, Westerterp-Plantenga MS, Westerterp KR. Underestimatingand under-recording of habitual food intake in obese men: selectiveunder-reporting of fat intake. Am J Clin Nutr 2000;71:130-134.

57. Hise ME, Sullivan DK, Jacobsen DJ, Johnson SL, Donnelly JE. Vali-dation of energy intake measurements determined from observer-recorded food records and recall methods compared with the doublylabeled water method in overweight and obese individuals. Am J ClinNutr 2002;75:263-267.

58. Rowlands AV. Field methods of assessing physical activity and energybalance. In: Eston R, Reilly T, eds. Kinanthropometry and ExercisePhysiology Laboratory Manual, 3rd ed. Oxon, UK: Routledge, 2009.

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