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Applied Physiology, Nutrition, and Metabolism

Physiologie appliquée,nutrition et métabolisme

The Canadian Society for Exercise Physiology and the Canadian Nutrition Society have chosen Applied Physiology, Nutrition, and Metabolism as their principal medium for the publication of research papers

La Société canadienne de physiologie de l’exercice et la Société canadienne de nutrition ont choisi Physiologie appliqueé, nutrition et métabolisme comme leur principal organe de publication d’articles de recherche

Volume 38

2013

An NRC Research Press Journal

Une revue deNRC Research Press

ARTICLE

A moderate dose of caffeine ingestion does not change energyexpenditure but decreases sleep time in physically active males:a double-blind randomized controlled trialPedro B. Júdice, João P. Magalhães, Diana A. Santos, Catarina N. Matias, Ana Isabel Carita, Paulo A.S. Armada-Da-Silva, Luís B. Sardinha,and Analiza M. Silva

Abstract: Research on the effect of caffeine on energy expenditure (EE), physical activity (PA), and total sleep time (TST) duringfree-living conditions using objective measures is scarce. We aimed to determine the impact of a moderate dose of caffeine onTST, resting EE (REE), physical activity EE (PAEE), total EE (TEE), and daily time spent in sedentary, light, moderate, and vigorousintensity activities in a 4-day period and the acute effects on heart rate (HR) and EE in physically active males. Using adouble-blind crossover trial (ClinicalTrials.gov ID: NCT01477294) with two conditions (4 days each with 3-day washout) randomlyordered as caffeine (5mg/kg of bodymass/day) and placebo (maltodextrin) administered twice per day (2.5mg/kg), 30 nonsmokermales, low-caffeine users (<100 mg/day), aged 20–39, were followed. Body composition was assessed by dual-energy X-rayabsorptiometry. PA was assessed by accelerometry, while a combined HR and movement sensor estimated EE and HR on thesecond hour after the first administration dose. REE was assessed by indirect calorimetry, and PAEE was calculated as [TEE −(REE + 0.1TEE)]. TST and daily food records were obtained. Repeated measures ANOVA and ANCOVA were used. After a 4-day period,adjusting for fat-freemass, PAEE, andREE, TSTwas reduced (p=0.022) under caffeine intake,whilenodifferenceswere foundbetweenconditions for REE, PAEE, TEE, and PA patterns. Also, no acute effects on HR and EE were found between conditions. Though a largeindividual variability was observed, our findings revealed no acute or long-term effects of caffeine on EE and PA but decreased TSTduring free-living conditions in healthy males.

Key words: caffeine, energy expenditure, physical activity, total sleep time, accelerometry, free-living conditions, body composition.

Résumé : Il y a très peu d'études sur les effets de la caféine au moyen de mesures objectives de la dépense d'énergie (EE), del'activité physique (PA) et de la durée totale de sommeil (TST) enmilieu naturel. Cette étude se propose d'évaluer l'effet d'une dosemodérée de caféine sur la TST, la EE au repos (REE), la EE au cours de l'activité physique (PAEE), la EE totale (TEE) et sur le tempsjournalier consacré a des activités sédentaires et d'intensité légère, modérée et vigoureuse sur une période de 4 jours en plus deseffets immédiats sur le rythme cardiaque (HR) et sur la EE chez des hommes physiquement actifs. Au cours d'un essai croisé adouble insu (ClinicalTrials.gov ID : NCT01477294) et incluant deux conditions (d'une durée de 4 jours suivis de 3 jours de lavagea épuisement) présentées aléatoirement : café (5 mg/kg de poids corporel/jour) et placebo (maltodextrine); on administre cessubstances a raison de deux fois par jour (2,5 mg/kg) a 30 non-fumeurs âgés de 20 a 39 ans et consommant peu de caféine (<100mg/jour). On évalue la composition corporelle par absorptiométrie a rayons X en double énergie. On évalue la PA par accéléro-métrie et, au moyen d'un capteur de HR et de mouvement, on évalue la EE et le HR au cours de la deuxième heure suivantl'administration de la première dose de substance. On estime la REE par calorimétrie indirecte et on calcule la PAEE par laformule suivante : TEE − (REE + 0,1TEE). On obtient la TST et l'apport alimentaire dans le cahier fourni a cette fin. On compareles résultats par une ANOVA et une ANCOVA pour mesures répétées. Après une période de 4 jours, on observe une diminutionde la TST avec la consommation de caféine, et ce, en prenant en compte la masse maigre, la PAEE et la REE (p = 0,022), mais onn'observe pas de différences entre les conditions en ce qui concerne les REE, PAEE, TEE et les modalités de PA. De plus, d'unecondition a l'autre, on n'observe aucun effet immédiat sur le HR et la EE. Même si on note une importante variation interindi-viduelle, cette étude ne révèle aucun effet a court et a long terme de la caféine sur les EE et PA, mais révèle un effet sur ladiminution de TST chez des hommes en bonne santé et vivant en milieu naturel. [Traduit par la Rédaction]

Mots-clés : caféine, dépense énergétique, activité physique, temps total de sommeil, accélérométrie, conditions de vie en liberté,composition corporelle.

IntroductionCaffeine is a stimulant of the central nervous system and is the

world's most popular drug. In North America, the United King-dom, and Denmark, 82% to 95% of adults regularly consume caf-feine (Armstrong et al. 2005). Caffeine is widely used to promotewakefulness and counteract fatigue induced by restriction of

sleep, but also to counteract the effects of caffeine abstinence(Porkka-Heiskanen 2011). Both short-term (Carrier et al. 2007;Carrier et al. 2009; Drapeau et al. 2006; Paterson et al. 2009) andlong-term (Calamaro et al. 2009; Drescher et al. 2011; James 1998)studies found that caffeine was associated with shortened totalsleep time (TST), which is recognized to be linked to obesity

Received 19 April 2012. Accepted 10 July 2012.

P.B. Júdice, J.P. Magalhães, D.A. Santos, C.N. Matias, L.B. Sardinha, and A.M. Silva. Exercise and Health Laboratory, CIPER, Fac Motricidade Humana, Univ TecnLisboa, 1499-002, Cruz-Quebrada, Portugal.A.I. Carita. Mathematical Methods Laboratory, BIOLAD-CIPER, Fac Motricidade Humana, Univ Tecn Lisboa, 1499-002, Cruz-Quebrada, Portugal.P.A.S. Armada-Da-Silva. Biomechanics and Functional Morphology, CIPER, Fac Motricidade Humana, Univ Tecn Lisboa, 1499-002, Cruz-Quebrada, Portugal.

Corresponding author: Analiza Mónica Silva (e-mail: analiza@fmh.utl.pt).

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Appl. Physiol. Nutr. Metab. 38: 49–56 (2013) dx.doi.org/10.1139/apnm-2012-0145 Published at www.nrcresearchpress.com/apnm on 18 January 2013.

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(Gangwisch et al. 2005; Gottlieb et al. 2006; Landhuis et al. 2008),type 2 diabetes (Spiegel et al. 2004, 2009), and hypertension(Gottlieb et al. 2006). The majority of studies investigated theeffects of caffeine on TST in laboratorial settings by using objec-tive measures (Bracco et al. 1995; Dulloo et al. 1999; Hursel et al.2011). However, during free-living conditions, only self-reporteddata were used (Calamaro et al. 2009; Drescher et al. 2011; James1998). Therefore, the relationship between caffeine intake andTST during free-living conditions is still unclear and needs to beassessed using objective measures such as movement sensor de-vices that have been shown to accuratelymeasure total sleep time(Adamec et al. 2010; Butte et al. 2010; Kawada et al. 2012).

Caffeine has been considered as a thermogenic agent (Arcieroet al. 1995; Astrup et al. 1990; Berube-Parent et al. 2005) that couldhelp in preventing a positive energy balance and obesity (Dullooet al. 1989; Hursel and Westerterp-Plantenga 2010). Although theeffect of caffeine on energy expenditure has been the subject ofnumerous investigations (Bracco et al. 1995; Dulloo et al. 1999;Hursel et al. 2011), its effects on daily free-living conditions havenot hitherto been studied. In addition, some uncertainty remainsabout the effect of caffeine ingestion on energy expenditure duetomethodological limitations, specifically because there has beenno accounting for potential variables such as regular caffeine con-sumption, type of caffeine ingestion, physical activity (PA) status,and body composition (Maughan and Griffin 2003).

Studies that focused on the short-term effects of caffeine inges-tion observed a significant increase in energy expenditure(Hamada et al. 2008; Vukovich et al. 2005), even when a smalldosage of caffeine (150 mg) was considered (Vukovich et al. 2005).Dulloo et al. (1999) with a small dose (100 mg) confirmed theseresults, founding a possible role of fat-free mass (FFM) in mediat-ing the effects of caffeine on daily energy expenditure.

To date, no research study has investigated the effect of a mod-erate dose of caffeine ingestion on energy expenditure and PAdimensions during free-living conditions. Therefore, we aimed toanalyze the impact of a moderate dose of caffeine during a 4-dayperiod on TST, resting energy expenditure (REE), PA energy expen-diture (PAEE), total energy expenditure (TEE), and daily time spentin sedentary (ST), light (LPA), moderate (MPA), and vigorous (VPA)intensity activities in nonobese, physically active males in free-living conditions. In addition, we also investigated the acute ef-fects of caffeine on heart rate (HR) and EE at the second hour afteradministration in free-living conditions.

Material and methods

ParticipantsA total of 30 healthy young adult males aged between 20 and

39 years volunteered to participate in this study. Inclusion criteriawere body mass index (BMI) between 18.5 and 29.9 kg/m2, non-smokers, and not taking any medications or dietary supplementsthatmay affect energy expenditure. In addition, participants werelow-caffeine users (<100 mg/day) (Currie et al. 1995). The dailyconsumption of caffeine was estimated based on self-report ofdaily intakes of coffee, tea, caffeinated sodas, and other dietarysources. All participants were informed about the possible risks ofthe investigation before giving their written informed consent toparticipate. All procedures were approved by the Ethics Commit-tee of the Faculty of Human Kinetics, Technical University of Lis-bon, and were conducted in accordance with the declaration ofHelsinki for human studies (World Medical Association 2008).

Experimental designParticipants were followed in a double-blind crossover experi-

mental design with two conditions in a random sequence: caf-feine (5 mg/kg body mass/day) and maltodextrin as placebo, boththrough capsules. Each condition lasted for 4 days, and partici-pants were instructed to keep the same eating patterns and levelof PA. There was a washout period of 3 days between each condi-

tion. Moreover, to reduce the variability of individual PA patternsduring the week, both conditions were performed on the sameweekdays while the washout period always included the weekenddays. Evaluations were performed at three time points: (i) base-line, first visit for collecting the initial measurements; (ii) condi-tion 1, second visit, 4 days after baseline, for collecting the finalmeasurements of the first randomly assigned condition (placeboor caffeine); and (iii) condition 2, third visit, 7 days after the end ofthe first condition, including the 3-day washout period, for col-lecting the final measurements of the second randomly assignedcondition (placebo or caffeine).

For testing the acute effects of caffeine on HR and EE, we ana-lyzed the first day of each condition, 2 h after the first adminis-tration of caffeine or placebo. This option was based on findingsthat the effects of caffeine are increased after the first 30 min andbefore 150 min (Dulloo et al. 1989; Hamada et al. 2008). To assurethat these effects were a result of caffeine ingestion, we reducedthe variability on PA during this period by defining the followingcriteria. Two hours after the dose administration, participantsneeded to (i) be engaged in sedentary behaviors (<100 counts/min)measured by accelerometry and (ii) display a complete time regis-tration during the 2 h after dose administration, with no heartrate (HR) data lost, interpolated, or recovered from the combinedHR and movement sensor registration. It is important to under-line that these criteria were considered to compare HR and EEunder caffeine or placebo conditions to reduce the potential effectof habitual PA on HR and EE. However, we did try to reduce thevariability of PA patterns by performing both conditions on thesame weekdays. As a result, only 14 participants were eligible forthis analysis. The characteristics of this subsample were generallysimilar to the initial sample. The mean age was 24.4 ± 4.8 years,ranging from 20 to 38 years. Mean height was 1.77 ± 0.07 m, rang-ing from 1.64 to 1.87 m, and body mass ranged between 62.0 and90.2 kg, with a mean of 72.8 ± 9.0 kg. Mean BMI was 23.7 ± 2.3 kg/m2,ranging from 20.5 to 26.7 kg/m2. Relative FM ranged between 11%and 23%, with a mean value of 16.6% ± 3.8%, corresponding toapproximately 12.2 ± 3.9 kg of FM. Mean FFM was 59.7 ± 6.6 kg,ranging from 51.9 to 70.3 kg.

Participants were required to fast for at least 12 h prior to eachvisit, refrain from vigorous exercise for at least 15 h, refrain fromother caffeine sources and alcohol consumption for 24 h, andconsume a normalmeal on the night before the visit. All measure-ments were carried out in the same morning. In brief, the proce-dures are described as follows.

Caffeine and placebo intakeAfter the participants were weighed, the dose was individually

prepared to assure that 5 mg of caffeine per kilogram of bodymass per day was administered. The dose of caffeine was dividedinto two equal parts (2.5 mg/kg) to be orally consumed throughcapsules in themorning and after lunch. An equivalent number ofplacebo capsules, of the same colour as the caffeine capsules,containingmaltodextrinwere provided for the placebo condition.

Body composition measures

AnthropometryParticipants wearing a bathing suit and without shoes were

weighed to the nearest 0.01 kg on an electronic scale connected toa plethysmograph computer (BOD POD, COSMED, Rome, Italy).Height was measured to the nearest 0.1 cm with a stadiometer(Seca, Hamburg, Germany) according to the standardized proce-dures described elsewhere (Lohman et al. 1988). BMI was calcu-lated as body mass (kg)/height2 (m).

Fat mass (FM) and fat-free mass (FFM)Dual energy X-ray absorptiometry (Hologic Explorer-W, fan-

beam densitometer, software QDR for Windows version 12.4,Waltham, Massachusetts, USA) was used to estimate FM and FFM.

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The equipment measures the attenuation of X-rays pulsed be-tween 70 and 140 kV synchronously with the line frequency foreach pixel of the scanned image. Following the protocol for DXAdescribed by the manufacturer, a step phantom with six fields ofacrylic and aluminium of varying thickness and known absorp-tive properties was scanned to serve as an external standard forthe analysis of different tissue components. The same technicianpositioned the participants, performed the scans, and executedthe analysis according to the operator's manual using the stan-dard analysis protocol. Based on test–retest using 10 participants,the coefficients of variation (CV) in our laboratory for FM and FFMare 1.7% and 0.8%, respectively.

Resting energy expenditureResting energy expenditure (REE) was assessed in the morning

(0700–1100). All measurements were performed in the same roomat an environmental temperature and humidity of approximately22 °C and 40%–50%, respectively.

The MedGraphics CPX Ultima (Medical Graphics Corp., St. Paul,Minnesota, with Breeze suite software) indirect calorimeter wasused to measure breath-by-breath oxygen consumption (VO2) andcarbon dioxide production (VCO2) using a facialmask. One trainedtechnician conducted all measurements. The oxygen and carbondioxide analysers were calibrated in the morning before testingusing known gas concentration. The flow and volume were mea-sured using a pneumotachograph calibrated with a 3 L syringe(Hans Rudolph, Inc.). The device's autocalibration was performedbetween participants. Before testing, participants were instructedabout all of the procedure and asked to relax, breathe normally,not to sleep, and not to talk during the evaluation. Total restduration was 60 min, participants lay supine for 30 min coveredwith a blanket, and the calorimeter device was then attached tothe mask and breath-by-breath VO2 and VCO2 were measured foranother 30-min period. Outputs of VO2, VCO2, respiratory ex-change ratio (RQ), and ventilation were collected and averagedover 1-min intervals for data analysis. The first and the last 5 minof data collection were discarded, and themean of a 5-min steady-state interval between 5min and 25min with RQ between 0.7 and1.0 was used to determine REE. Steady state was defined as a 5-minperiod with ≤10% CV for VO2 and VCO2 (Compher et al. 2006). Themean VO2 and VCO2 of 5-min steady states were used in the Weirequation (Weir 1949), and the period with the lowest REE wasconsidered.

Based on test–retest using seven participants, the CV in ourlaboratory for REE is 4.0%.

Physical activity assessmentAll participants were asked to use an accelerometer (ActiGraph,

GT1Mmodel, Fort Walton Beach, Florida, USA), worn on the righthip near the iliac crest, during 11 consecutive days, including twoweekend days (Trost et al. 2005). The delivery and reception of theaccelerometers to the participants, as well the explanation of itsuse, were made personally (Ward et al. 2005). The devices wereactivated on the first day at 07:00, and data were recorded in 10-sepochs. The device activation and data download were performedusing the software Actilife Lifestyle (ver. 3.2). Processing was per-formed using the software MAHUffe (ver. 1.9.0.3; available atwww.mrc-epid.cam.ac.uk) from the original downloaded files(*.dat). For the analyses, a valid day was defined as having 600 ormore minutes (10 h) of monitor wear, corresponding to theminimum daily use of the accelerometer (Ward et al. 2005).Apart from accelerometer nonwear time (i.e., when it was re-moved for sleeping or water activities), periods of at least 60 con-secutivemin of zero activity intensity counts were also consideredas nonwear time.

The amount of activity assessed by accelerometry was ex-pressed as (i) the number of minutes per day spent in differentintensities and in 10-min bouts of moderate or greater intensity

PA, (ii) the mean time (minutes per day) of total PA (light, moder-ate, and vigorous), and (iii) the mean intensity of PA (counts perminute per day). The cutoff values used to define the intensity ofPA and therefore to quantify the mean time in each intensity(sedentary, light, moderate, or vigorous) were as follows: seden-tary, <100 counts/min; light, 100–2019 counts/min; moderate,2020–5998 counts/min (corresponding to 3–5.9 METs); and vigor-ous, ≥5999 counts/min (corresponding to ≥6METs) (Troiano 2005).TEEwas estimated using the derived regression equation of Freed-son (Freedson et al. 1998). Accelerometer datawere collected using10-s epochs and were converted to counts per 60 s to use thisregressionmodel. An inactivity threshold of 1 METwas used whencounts per minute were less than 50.

Short-term physical activity assessmentThe free-living EE and HR on the second hour after caffeine and

placebo ingestion were assessed using a combined HR and move-ment sensorusingdifferent energymodels, available in the commer-cial software (Actiheart, CamNtech Ltd, UK). Initially, participantsunderwent an 8-min step test (Brage et al. 2007) to provide individ-ual HR calibration. Subsequently, free-living HR and accelerationwere measured in 1-min epochs, which allowed the use of thecombined sensor during thewhole study period. However, for thisparticular assessment, only the second hour after the ingestion ofcaffeine and placebo was analyzed. The monitors should only beremoved for showering, bathing, or activities such as swimming.Data downloading, processing, and analysis were performed us-ing the Actiheart commercial software using the advance energyexpenditure mode. HR Flex using the individual HR calibrationmodel was used to estimate EE from PA as specified by the Acti-heart software (Brage et al. 2007).

The magnitudes of both HR and EE on the second hour afteradministration (caffeine and placebo), previously described at theexperimental design, were compared with a reference hour ob-tained as the lowest HR and EE values assessed during the REEmeasurement.

Along with the use of this combined motion sensor and HRequipment, participants were provided with a worksheet to re-cord the type and duration of the physical activities performed.

Sleep time assessmentAlongwith the use of both accelerometer and combinedmotion

sensor, participants were provided with a worksheet to record thetype and duration of physical activities performed and also thetime that they went to sleep and woke up. The data from thisself-reported information were checked with the combined mo-tion sensor registration and the accelerometry data. The meanTST for the two conditions was determined, and the mean differ-ences between conditions were considered as a potential con-founder and also as dependent variable.

Dietary-record analysisFood intake was assessed throughout the study (approximately

11 days) using 24-h diet records. Participants were instructed re-garding portion sizes, supplements, food preparation aspects, andothers aspects pertaining to an accurate recording of their energyintake. When the participants came to the laboratory for the sec-ond visit (4 days after baseline), the nutritionist was able to trackthe food records status to assure that participants were complet-ing them accurately. At the last visit, records were turned in andreviewed for water ingestion, macronutrient composition, andtotal energy intake by the same nutritionist. Diet records wereanalyzed using a software package (Food Processor SQL).

Statistical analysisStatistical analysis was performed using PASW Statistics for

Windows ver. 18.0, 2010 (SPSS Inc., an IBM Company, Chicago,

Júdice et al. 51

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Illinois, USA). Descriptive analysis included means ± SD for allmeasured variables. For reliability analysis, the coefficient of vari-ation was used and calculated as suggested by Bland (1995).

To compare the effects of caffeine onmean values of the depen-dent variables (TST, HR, TEE, PAEE, REE, ST, LPA, MPA, and VPA),a repeatedmeasures analysis of variance (ANOVA)was used. Treat-ment by order interaction was evaluated as suggested by Hills andArmitage (1979).

The Mauchly's sphericity test was performed to examine theform of the common covariance matrix, i.e., if p > 0.05, the spher-ical matrix has equal variances and covariances equal to zero.Further analyses were only conducted if the common covariancematrix of the transformed within-participant variables was spheri-cal, otherwise, the F tests and associated p values for the univariateapproach to testing within-subject hypotheses would be invalid.

Analysis of co-variance (ANCOVA) for crossover trials was per-formed as recommended by Senn et al. (1993).

Paired sample t test was performed to analyze food intake be-tween the two conditions.

The CV was calculated as suggested by Bland (1995).Statistical significance was set at p < 0.05.

ResultsSample characteristics at baseline are presented in Table 1.Table 2 displays the nutrition patterns in both the placebo and

caffeine treatment periods.Dietary intake did not differ between caffeine and placebo

conditions, specifically energy intake (p = 0.312), carbohydrates(p = 0.453), protein (p = 0.534), and fat (p = 0.361) intake.

Long-term effectsThe long-term effects of caffeine on total sleep time, EE, and PA

dimensions are presented in Table 3 for the main outcomes as-sessed during the two 4-day condition periods (TST, TEE, REE,PAEE), and the average number of minutes spent sedentary (ST)and in light (LPA), moderate (MPA), and vigorous (VPA) intensityactivities for both conditions (caffeine and placebo).

The results from ANOVA for repeated measures showed dif-ferences for TST between caffeine and placebo conditions(43 ± 97 min; F = 5.721, p = 0.022). Therefore, further analysisincluded the potential mediated effect of the TST differencesbetween conditions. In contrast, the results from ANOVA forrepeatedmeasures showednodifferences (p≥0.05) between caffeineand placebo intake, with mean differences of −11.7 ± 234.9 kJ/dayfor TEE, 47.9 ± 127.5 kJ/day for REE, −58.4 ± 227.9 kJ/day for PAEE,9 ± 104min for ST, 3 ± 36min for LPA, −1.9 ± 32.2min for MPA, and−0.5 ± 7.2 min for VPA.

We further analyzed if FFM, registration time, and TST dif-ferences between conditions could influence the effect of caf-feine on ST, LPA, MPA, and VPA by introducing these variables ascovariates. However, as illustrated in Fig. 1, no differences werefound in sedentary time and PA dimensions after adjusting forthese covariates.

Neither the randomly assigned order of treatment nor the treat-ment by groups interaction influenced the mean values of ST(F = 0.459, p = 0.504), LPA (F = 3.118, p = 0.088), MPA (F = 4.000,p = 0.055), VPA (F = 1.037, p = 0.317), TST (F = 0.259, p = 0.614), TEE(F = 1.103, p = 0.303), PAEE (F = 0.657, p = 0.424), and REE (F = 0.085,p = 0.772).

As illustrated in Fig. 2, after adjusting for FFM, PAEE, and REE,the effect of caffeine on TST remained significant (p < 0.05). TEEand PAEE results did not alter (p > 0.05) when adjusted for FFM,registration time, and sleep time differences between conditions.To analyze the effect of caffeine on REE values, comparisons be-tween conditions were adjusted for FFM, sleep time, and baselineREE values.

Acute effectsTo analyze the acute effects of caffeine on EE and HR, we mea-

sured these variables in the second hour after caffeine and pla-cebo administration on the first day of administration. The resultsfrom the second hour showed a mean EE of 643 ± 282 kJ for theplacebo condition and 689 ± 297 kJ for the caffeine condition.Mean HR were 76 ± 13 and 77 ± 10 bpm for placebo and caffeine,respectively.

The results from ANOVA for repeatedmeasures showed no differ-encesbetweencaffeineandplacebo intake forbothEE (46.1 ± 121.4kJ)and HR (1.4 ± 5.0 bpm) in the second hour after administration (dif-ferences calculated as caffeine minus placebo). The randomly as-signed order of treatment did not influence themean values of thesevariables as the treatment-by-group interaction showed no differ-ences (HR, F = 0.281, p = 0.606; EE, F = 0.036, p = 0.852).

Differences were found between each condition and the lowestvalues obtained from the REEmeasurement, used as the referencehour, for both EE and HR (p < 0.001). Considering HR, the differ-ences between each treatment condition and the reference valueswere 23 ± 3 bpmand 22 ± 4 bpm, representing a raise above restingHR values of 43% and 41% for caffeine and placebo conditions,respectively. For EE, the differences from REEwere 441 ± 77 kJ and395 ± 76 kJ, respectively, for caffeine and placebo, which repre-sents a raise of 79% and 60% above REE values, respectively(p < 0.001).

Table 1. Participant characteristics and body composition (N = 30).

Mean ± SD Range

Age (years) 24.5±4.8 20–39Height (m) 1.77±0.07 1.64–1.93Body mass (kg) 72.7±8.8 51.8–90.2BMI (kg/m2) 23.6±2.5 19.6–29.9FM (kg) 11.9±4.3 5.1–23.3FM (%) 16.3±4.4 10.0–26.4FFM (kg) 59.9±6.2 46.2–70.3

Note: SD, standard deviation; N, number of participants; BMI, body massindex; FM, fat mass; FFM, fat-free mass.

Table 2. Dietary intake (N = 30) during the treatment conditions.

Placebo(mean ± SD)

Caffeine(mean ± SD)

Energy intake (kJ/day) 10961±2587 10471±1624Carbohydrates (g) 308±81 297±51Fat (g) 89±25 83±23Protein (g) 119±34 115±21

Note: SD, standard deviation; N, number of participants.

Table 3. Total sleep time, resting, total, and physical activity energyexpenditure, and dose of habitual physical activity by accelerometry(N = 30).

Placebo(mean ± SD)

Caffeine(mean ± SD)

TST (hh:mm) 08:27±01:16 07:43±01:32�

TEE (kJ/day) 11882±2010 11870±2114Total PA (cpm/day) 359±160 358±136REE (kJ/day) 6021±934 6071±988PAEE (kJ/day) 5857±1591 5799±1838Sedentary (min/day) 702±84 712±93Light (min/day) 151±38 154±40Moderate (min/day) 48±25 46±22Vigorous (min/day) 6±7 5±5

Note: SD, standard deviation;N, number of participants; TST, total sleep time,expressed in hours and minutes (hh:mm); TEE, total energy expenditure; PA,physical activity; PAEE, physical activity energy expenditure; REE, resting en-ergy expenditure; cpm, counts per minute.

�Significant difference from placebo, p < 0.05.

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Although less than 100 counts/min during the 2 h after the doseadministration was used as an inclusion criterion, we further an-alyzed if the different range (0–99 counts/min) observed couldinfluence the effects of caffeine on HR and EE. Therefore, weincluded this variable as a covariate. As illustrated in Fig. 3 andafter adjusting for total PA (counts/min), nonsignificant differ-ences between caffeine and placebo remained for HR and EE. Also,the magnitude of the differences between treatment conditionsand reference values from rest remained significant for both HRand EE variables (p < 0.001).

DiscussionThe aim of the present study was to analyze the effects of caf-

feine on total sleep time, energy expenditure, and PA dimensions,over a 4-day period under free-living conditions using accelerom-eters in a randomized controlled trial with a crossover design.Additionally, a new generation of motion sensors that combines aHR monitor with an accelerometer was used to assess the acuteeffects of caffeine ingestion on HR and EE after the second hour ofadministration in those participants considered sedentary basedon accelerometry data collection (<100 counts/min).

This was the first study that combined objective measures oftotal sleep time over a 4-day period under free-living conditions.Our findings showed that caffeine significantly decreased totalsleep time, which is in accordancewith previous data (Bracco et al.1995; Calamaro et al. 2009; Drescher et al. 2011; Dulloo et al. 1999;

Hursel et al. 2011; James 1998). So far, the effects of caffeine on TSThave been investigated in laboratorial settings using objectivemeasures (Bracco et al. 1995; Dulloo et al. 1999; Hursel et al. 2011),whereas self-reported data was used to assess TST under free-living conditions (Calamaro et al. 2009; Drescher et al. 2011; James1998). Moreover, under free-living conditions, a moderate dose ofcaffeine ingestion decreased TST. We further investigated if fat-freemass, resting, and PA energy expenditure could have played amediating role on these effects. After adjusting for these potentialcovariates, the significant reduction in total sleep time remained.

Our findings suggest no acute effects of caffeine on EE and HRafter the second hour under free-living conditions. These findingsdo not extend those reported by other research (Dulloo et al. 1989;Perkins et al. 1994). However, the less controlled environmentcompared with other research studies may explain the observeddiscrepancies. The administered dose (187 mg) may not explainthis lack of effect, as similar dosages produced thermogenic re-sponses in other reported studies (Astrup et al. 1990; Bracco et al.1995; Collins et al. 1994; Dulloo et al. 1989). Perhaps the method-ology used to assess PA may not be accurate enough to detect theexpected increase in thermogenesis after the second hour of caf-feine administration, particularly under free-living conditions. Al-though the differences were not significant, the magnitude of theincrease in EE (46.1 ± 66.5 kJ) was higher than in previous studies(35 kJ) (Astrup et al. 1990; Berube-Parent et al. 2005). Anotherinteresting observation in our research was the absence of an

Fig. 1. Mean and standard error values for daily time spent in sedentary (ST), light (LPA), moderate (MPA), and vigorous (VPA) intensityactivities for both conditions and both groups. Group 1 represents the 15 participants who started with placebo; group 2 represents the 15participants who started with caffeine. All values were adjusted for FFM, registration time, and sleep time.

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Fig. 2. Mean and standard error values for total sleep time (TST) and total energy expenditure (TEE), resting energy expenditure (REE), andphysical activity energy expenditure (PAEE) for both conditions and both groups. Group 1 represents the 15 participants who started withplacebo; group 2 represents the 15 participants who started with caffeine. The TST values were adjusted for FFM, PAEE, and REE, withsignificant differences between conditions regardless of the assigned order of treatment. TEE and PAEE were adjusted for FFM, registrationtime, and sleep time. REE was adjusted for FFM, sleep time, and baseline values.

Fig. 3. Mean and standard error values for heart rate (HR) and energy expenditure (EE) on the reference hour (time at rest) and the secondhour after capsule intake under placebo or caffeine. The values are valid for 14 participants and are adjusted for counts per minute registeredin the second hour.

54 Appl. Physiol. Nutr. Metab. Vol. 38, 2013

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effect of caffeine intake on energy expenditure and time spent inphysical activities of different intensities over a 4-day period. Sofar, we are only aware of two studies that investigated the effectsof caffeine on TEE in a metabolic chamber during 1 day (Berube-Parent et al. 2005; Dulloo et al. 1999). The former study found anincrease of 750 kJ in TEE considering a 600 mg/day caffeine dos-age, whereas the later, using a lower caffeine dose (150 mg/day),did not present significant differences between caffeine and pla-cebo (Dulloo et al. 1999). Although our mean caffeine dose admin-istration was considerable higher than that reported by Dullooet al. (1999), we also found nonsignificant effects of caffeine onenergy expenditure over a 4-day period. According to this study,the most likely explanation for these findings are probably re-lated to the mean dosage used (�375 mg/day), which is far belowthe threshold for stimulating thermogenesis, i.e., 600–1000 mgcaffeine/day (Dulloo et al. 1989). In addition, a possible toleranceto caffeine effects (Robertson et al. 1981) during the 4-day periodmay help explain these results.

Although there are a large number of studies aimed at assessingthe acute effects of caffeine on REE in a laboratorial context, thiswas the first study that considered a 4-day period. A previousinvestigation found significant effects of caffeine on increasingREE (Arciero et al. 1995; Koot and Deurenberg 1995), even whenparticipants were moderate caffeine consumers (Astrup et al.1990; Collins et al. 1994). Despite the fact that no study aimed atassessing REE in a longer time period, an increase in caffeineintake over a 4-day period was expected. However, the resultsfrom the present investigation showed no significant increase indaily REE (47.9 kJ). It has been speculated that the contradictoryresults might be explained by the great variability of the individ-ual response to caffeine due to body composition and dietaryintake characteristics (Hamada et al. 2008). However, our findingsdid not confirm that fat-free mass mediated the effect of caffeineon REE, and no changes in dietary intake were observed betweencaffeine and placebo conditions. In fact, even after adjusting forbaseline REE, FFM, and total sleep time, the absence of a caffeineeffect on REE remained. Furthermore, we did not observe changesin PA energy expenditure and time spent in different activities. Itis well known that caffeine works as an ergogenic substance forthe central nervous system (Hursel et al. 2011), so an increase indaily PAwould be expected, specifically in the daily light-intensityactivities (Greenberg et al. 2005). Unexpectedly, no significant dif-ferences between caffeine and placebo were observed for PA en-ergy expenditure and time spent in sedentary, light, moderate,and vigorous intensities, even after adjusting for FFM, sleep time,and registration time.

It is important to mention a few limitations of the presentresearch study. Under free-living conditions, it is more difficult tocontrol variables that may mediate the effects of caffeine on en-ergy expenditure and PA, specifically those related to the acuteeffects. In fact, even including participants who showed a meanregistration of <100 counts/min at 2 h after the administration, wewere not able to assure that participants were really sedentary.Also, the larger variability observed in TEE and PA in both condi-tions assessed by accelerometry highlighted how daily PA pat-terns may vary under free-living conditions, making theidentification of a caffeine effect on energy expenditure and timespent in different intensities more difficult. Thus, it is plausiblethat the nonsignificant results on EE and PA dimensions betweentreatment conditions were due to this large individual variability,rather than the sample size (Perkins et al. 1994). It is important tounderscore that with the current sample size, our power to detecta 43 ± 97 min difference in the mean total sleep time is �0.7.Another limitation is that fidgeting and other very light move-ments might not have been detected by the accelerometers,which may have underestimated the time spent in light PA inten-sity, TEE, and PAEE. It is also important tomention thatwe did notassess hormonal changes that, in fact, could vary under caffeine

intake, which would likely affect energy expenditure, specificallyduring rest. Studies indicated that caffeine increases catechol-amine production (Dulloo et al. 1999; Dulloo et al. 1992; Hamadaet al. 2008). However, we did not find a significant effect of caf-feine on REE values assessed at baseline and at the end of eachcondition, which may suggest an unlikely effect of hormonalchanges on TEE and PA patterns. Finally, our findings are onlygeneralized to nonobese physically active males who are low-caffeine users and under amoderate dose of caffeine ingestion fora 4-day period. Further research should be conducted with ahigher caffeine dose and in a population that varies in age, bodymass index, and gender.

Considering the main findings of our study, the beneficial roleof caffeine ingestion as a strategy to increase thermogenesis andimprove weight management may be questionable. Indeed, theobserved reduction in sleep duration under caffeine intake andthe several studies that linked the decline in TST with obesity(Gangwisch et al. 2005; Gottlieb et al. 2006; Landhuis et al. 2008)suggest an unfavorable role of caffeine intake in weight manage-ment. These unexpected findings require further investigation toclarify the effects of amoderate dose of caffeine on sleep duration,particularly in participants who will be engaged in weight lossinterventions.

In conclusion, our findings revealed that a moderate dose ofcaffeine ingestion did not induce an acute or long-term effect onEE and PA but did induce a significant decrease in total sleep timeduring free-living conditions in healthy young males not accus-tomed to intake caffeine on a daily basis.

AcknowledgmentsWe express our gratitude to the participants for their time and

effort. This work was supported by the Hydration and HealthPortuguese Institute.

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