The magnitude of the negative energy balance induced by exercise may be reduced due to compensatory increases in energy intake.
To address the question: Does increased exercise or physical activity alter ad-libitum daily energy intake or macronutrient composition in healthy adults?
PubMed and Embase were searched (January 1990–January 2013) for studies that presented data on energy and/or macronutrient intake by level of exercise, physical activity or change in response to exercise. Ninety-nine articles (103 studies) were included.
Study Eligibility Criteria
Primary source articles published in English in peer-reviewed journals. Articles that presented data on energy and/or macronutrient intake by level of exercise or physical activity or changes in energy or macronutrient intake in response to acute exercise or exercise training in healthy (non-athlete) adults (mean age 18–64 years).
Study Appraisal and Synthesis Methods
Articles were grouped by study design: cross-sectional, acute/short term, non-randomized, and randomized trials. Considerable heterogeneity existed within study groups for several important study parameters, therefore a meta-analysis was considered inappropriate. Results were synthesized and presented by study design.
No effect of physical activity, exercise or exercise training on energy intake was shown in 59% of cross-sectional studies (n = 17), 69% of acute (n = 40), 50% of short-term (n = 10), 92% of non-randomized (n = 12) and 75% of randomized trials (n = 24). Ninety-four percent of acute, 57% of short-term, 100% of non-randomized and 74% of randomized trials found no effect of exercise on macronutrient intake. Forty-six percent of cross-sectional trials found lower fat intake with increased physical activity.
The literature is limited by the lack of adequately powered trials of sufficient duration, which have prescribed and measured exercise energy expenditure, or employed adequate assessment methods for energy and macronutrient intake.
Citation: Donnelly JE, Herrmann SD, Lambourne K, Szabo AN, Honas JJ, Washburn RA (2014) Does Increased Exercise or Physical Activity Alter Ad-Libitum Daily Energy Intake or Macronutrient Composition in Healthy Adults? A Systematic Review. PLoS ONE 9(1): e83498. https://doi.org/10.1371/journal.pone.0083498
Editor: Guillermo López Lluch, Universidad Pablo de Olavide, Centro Andaluz de Biología del Desarrollo-CSIC, Spain
Received: August 30, 2013; Accepted: November 4, 2013; Published: January 15, 2014
Copyright: © 2014 Donnelly et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This review was funded by the International Life Sciences Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: JD and RW are investigators of individual trials included in this review. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials. The authors declare that they have no other competing interests.
Data from the 2009–2010 National Health and Nutrition Examination Survey (NHANES) suggest that 68.8% of those age ≥20 years are overweight (Body Mass Index [BMI]≥25 kg/m2) while 35.7% are obese (BMI≥30 kg/m2)  with approximately 51% of US adults predicted to be obese by 2030 Finkelstein . Medical expenditures associated with the treatment of obesity and obesity related conditions are estimated at greater than $147 billion annually . Data from the NHANES (2003–2008) indicated that among adults (18–54 years) approximately 75% of women and 54% of men expressed a desire to lose weight while 61% of women and 39% of men were actively pursuing weight control .
Exercise is recommended for weight management by several governmental agencies and professional organizations including the Association for the Study of Obesity , the Institute of Medicine , the U.S. Federal guidelines on physical activity , Healthy People 2020  and the American College of Sports Medicine . Compared with weight loss induced by energy restriction, weight loss achieved by exercise is composed predominantly of fat mass, while fat-free mass is preserved – and resting metabolic rate (RMR) is generally unchanged , , or slightly increased , , factors that may be associated with improved long term weight loss maintenance. However, several reports have demonstrated that the accumulated energy balance induced by an exercise intervention alone produces less of a negative energy balance than theoretically predicted for the imposed level of exercise-induced energy expenditure –. The energy balance induced by exercise training may be reduced due to compensatory changes in energy intake, non-exercise physical activity, or both –; thereby reducing the magnitude of observed weight loss. Although several narrative reviews regarding the impact of exercise on energy intake and appetite hormones have been conducted –, we are aware of only one systematic review/meta-analysis on this topic. Schubert et al.  recently published a meta-analysis on the effect of acute exercise on subsequent energy intake that included only studies that assessed energy intake for ≤24 hours post-exercise in healthy (lean and/or obese), non-smoking individuals. To date, no systematic reviews on the effect of exercise and energy and macronutrient intake have been conducted that evaluated both the effects of acute exercise and exercise training and have included data from studies utilizing a variety of designs, e.g. cross-sectional, acute-crossover, non-randomized and randomized trials. Therefore, the aim of this systematic review was to identify and evaluate studies that have employed a variety of designs to assess the impact of both acute exercise and exercise training on energy and macronutrient intake. Results of this review will clarify our understanding of the association between exercise and energy intake and identify both exercise parameters including mode, frequency, intensity and duration and participant characteristics including age, gender, body weight, activity level that may impact this association. Such information will be useful for the design of weight management trials utilizing exercise, the potential identification of groups of participants for whom exercise may be most effective, and to identify areas for future investigation.
The objective of this systematic review was to address the question:
Does increased exercise or physical activity alter ad-libitum daily energy intake or macronutrient composition in healthy adults?
Primary source articles published in English in peer-reviewed journals were eligible for inclusion in this systematic review if data were presented on energy and/or macronutrient intake by level of exercise or physical activity or changes in energy or macronutrient intake in response to acute exercise or exercise training. Specific eligibility criteria included: Types of studies: Cross-sectional, acute/short-term (exercise duration ranging from a single 30-min exercise bout to daily exercise over 14 days), and both non-randomized and randomized trials. Types of participants: Healthy adults (age 18–65 years). Types of exercise interventions: Aerobic and resistance exercise. Types of outcome measures: No restrictions were placed on the assessment methods for the primary outcome (energy/macronutrient intake). Other criteria: There were no restrictions on the length of interventions or the types of comparisons. We included cross-sectional comparisons between participants differing by level of exercise or physical activity and longitudinal pre/post within group changes vs. non-exercise control or vs. a different level of exercise. Articles were excluded if they provided no data on energy or macronutrient intake by level of exercise or physical activity, manipulated or controlled energy intake, or were conducted in non-recreational athletes or individuals with chronic disease(s).
Studies were identified by searching electronic data bases, related article reference lists, and consulting with experts in the field. The search was applied to PubMed (1990-present) and adapted for Embase (1990-present). The last search was conducted on January 4, 2013. The search was developed as a collaborative effort of the research team in consultation with a Kansas University reference librarian and conducted by a co-author (SDH). No attempts were made to contact study investigators or sponsors to acquire any information missing from the published article.
We used the following search terms in PubMed and Embase to identify potential articles with abstracts for review: exercise[ti (title), ab (abstract) ] or “physical activity”[ti,ab] or “energy expenditure”[ti,ab] OR “resistance training”[ti,ab] OR “strength training”[ti,ab]) AND (diets[ti,ab] OR diet[ti,ab] OR dieting[ti,ab] or “energy intake”[ti,ab] OR “energy restriction”[ti,ab] OR “nutrient composition”[ti,ab] OR “appetite”[ti,ab]). Additional search terms were applied to eliminate case reports and studies involving participants with chronic disease, and to retrieve studies published in English and conducted in adults (age 18–65 years). Word truncation and the use of wildcards allowed for variations in spelling and word endings.
Retrieved abstracts were independently assessed for eligibility for inclusion in the review by 2 investigators and coded as “yes”, “no” or “maybe.” All investigators who participated in eligibility assessments were trained regarding study inclusion/exclusion criteria and completed practice eligibility assessments on 50 test abstracts prior to actual coding. Eligibility assessments on the practice abstracts were reviewed by the primary author (JED) and any coding problems were discussed. Disagreements regarding eligibility for inclusion were resolved via development of consensus among all co-authors. Full text articles for abstracts coded as “yes” or “maybe” were retrieved and reviewed by 2 independent co-authors prior to inclusion in the review. An excel spread sheet was developed and used to track eligibility status.
Extracted data was entered into the University of Kansas secure, REDCap (Research Electronic Data Capture, Version 4.14.5) data base . A REDCap data extraction form was developed, pilot tested on a sample of 10 studies (at least 2 studies of each of the 4 study designs included in this review), and revised accordingly. Relevant data were extracted from each manuscript by one author and verified by a second author. Disagreements were resolved by group discussion. Data extracted from each article included basic study information (design, sample size, groups compared, exercise or physical activity groups/intervention(s), participant characteristics (age, gender, BMI, minority status), energy and macronutrient assessment method, and results.
Risk of Bias in Individual Studies
Risk of bias for randomized trials was independently evaluated by two authors using the Cochrane risk of bias tool . Risk of bias was assessed in the following domains: selection bias, performance bias, detection bias, attrition bias, reporting bias, and other bias. A third reviewer resolved any discrepancies in bias coding. Studies were not excluded on the basis of risk of bias.
Synthesis of Results
Articles were grouped by study design: cross-sectional, acute/short-term, non-randomized, and randomized trials. Considerable heterogeneity existed within study groups for several important study parameters. These parameters included: 1) participant characteristics (age, gender, BMI), 2) physical activity assessment methods (questionnaires, pedometers, accelerometers), 3) exercise prescriptions (mode, frequency, intensity, duration), 4) comparison groups (interventions: pre vs. post-exercise, exercise vs. non-exercise control, varying amounts), 5) intervention length, and 6) energy and macronutrient assessment methods (food frequency questionnaire, weighed and un-weighed food records, direct observation weigh and measure technique). A meta-analysis was therefore considered inappropriate. Results based on the extracted data were instead synthesized and presented grouped by study design.
The initial database search plus hand searching identified 4,668 unique records of which 4,490 were excluded based on review of title and abstract. Full-text articles for the remaining 178 citations were reviewed of which 79 articles did not satisfy our inclusion criteria and were excluded. Thus 99 articles representing 101 studies were included in the review (Figure 1).
The 17 cross-sectional studies identified comprised ∼17% of the total number of studies included in this review (Table 1).
Cross-Sectional Studies: Study Characteristics
Median (range) sample size for studies that included both men and women was 447 (14–921) for men and 428 (10–1483) for women. In studies that included only men or women the median sample size for men was 137 (one study) and women was 60 (21–38,876).
Seven studies compared 2 groups (active vs. sedentary) , –. Six studies compared 3 groups – while 3 studies compared physical activity over 4 or more groups –. One study reported the correlation between physical activity level and energy intake .
Physical activity assessment.
Seven studies (∼41%) employed a physical activity questionnaire , , , , , , , 5 studies (∼29%) used a single item self-report or self-report physical activity rating scale , , , , , and one study used a physical activity diary. Two studies used objective assessments of physical activity (accelerometers/pedometers) ,  while 2 studies recruited participants based on their self-reported participation in recreational aerobic sports , .
Energy/Macronutrient intake assessment.
Food frequency questionnaires were used in 6 studies –, , ,  while 4 studies used non-weighed 3-day food records , –. One , 4 ,  and 7-day  non-weighed food records, 3  and 7-day weigh and measure food records  and repeated 24-hour recalls were also employed in 2 studies , .
Cross-Sectional Studies: Participant Characteristics
Cross-Sectional Studies: Results
Seven of 17 (41%) cross-sectional studies indicated significantly higher absolute (kcal/day) , –,  or relative (kcal/kg/day) energy intake ,  in active compared with less active groups. There were no apparent differences in either basic study design parameters including sample size, assessment methods for both energy intake and physical activity, the number and type of comparison groups, or participant characteristics such as age, gender or BMI between studies that did and did not report a significant association between physical activity and energy intake.
Thirteen of 17 studies presented data on the intake of one or more macronutrients (fat, carbohydrate, protein). All 13 studies included data on fat intake. Six studies (46%) reported either lower absolute (grams) ,  or relative fat intake (% total energy intake) , , , , ,  in groups with higher levels of physical activity while 7 studies (54%) that reported fat intake by activity level failed to find a significant association , , , , , , . Eleven studies provided data on both carbohydrate and protein intake. Two studies (18%) reported higher carbohydrate intake in active groups , , while 9 studies (82%) found no association between the level of physical activity and carbohydrate intake , , , , , , , , . Relative protein intake was higher (2 studies) , , lower (one study)  or not different (8 studies) , –, , , ,  between groups reporting higher vs. lower levels of physical activity.
The 40 acute studies comprised ∼40% of the total studies identified for this review (Table 2). All acute studies employed cross-over designs, which compared energy intake assessed over a time frame of 24 hours or less following an acute exercise bout.
Acute Studies: Study Characteristics
The median (range) exercise intensity was 70% (60–75%) of HRMax, and 70% (30–75%) of maximal oxygen uptake. Five studies did not provide information on exercise intensity. The median (range) exercise duration was 50 min (3–90 min). Four acute studies dosed exercise by level of energy expenditure –.
Energy intake assessment.
Single ad-libitum test meals with energy intake assessed by the weigh and measure technique were utilized in the majority (25/40, 63%) of acute studies. Multiple ad-libitum meals , –, a combination of ad-libitum meal plus energy intake over the rest of the day by recall , –, diet recalls alone , and the consumption of specific food items, e.g. sandwiches , pasta salad  or cookies and chips  were also utilized.
Acute Studies: Participant Characteristics
No studies described the racial or ethnic composition of the study sample or reported post-exercise energy intake by race or ethnicity.
Participant activity level.
Participants recruited for the majority of acute studies (24/40–60%) were physically active and/or aerobically fit , , –, , , , , , , , –. Eleven studies (∼28%) recruited sedentary or moderately active participants , , , , , , , , ,  while 5 studies (∼13% ) did not describe baseline participant physical activity , , , .
Acute Studies: Results
Nine of 40 acute studies (∼23%) , , , , , , , ,  reported a significant increase in absolute energy intake (∼80 to 470 kcal/day) following exercise compared with non-exercise control while 27 studies (∼68%) found no difference in absolute energy intake between exercise and control conditions , –, , , , , –, –. Four studies (10%) reported a significant decrease in absolute energy intake (∼125 to 240 kcal/day) following exercise compared with non-exercise control , , , . Fifteen studies (∼38%) reported a significant decrease in relative energy intake (energy intake - exercise energy expenditure) following exercise compared with control –, , –, , , , , , , –; 5 of those studies also reported significant increases in absolute energy intake , , , ,  suggesting only partial compensation in energy intake following acute exercise.
Sixteen of the 40 acute studies (40%) reported data on macronutrient intake –, , , , –, , . Fifteen studies showed no effect, while one study indicated significantly higher fat and protein intake following exercise compared with non-exercise control .
Effect of Study Parameters on Energy Intake
Three studies provided information relative to the effect of exercise mode on post-exercise energy intake. Balaguera-Cortes et al.  reported no effect of either aerobic (treadmill) or resistance exercise while King et al.  showed no effect of swimming on absolute post-exercise energy intake. These results are in contrast to those of Laan et al.  who showed an increase in absolute post-exercise energy intake following both aerobic (cycling) and resistance exercise; however, relative energy intake was lower following aerobic exercise compared to resistance exercise or control.
Six acute studies reported the effect of exercise intensity on post-exercise energy intake. Four studies found no effect of exercise intensity on absolute energy intake following exercise , , , ; however, Imbeault et al.  reported a lower relative energy intake following high intensity exercise (75% VO2 max) compared with low intensity exercise (35% VO2 max) or non-exercise control. One study  showed a significant increase in absolute energy intake for high (70% VO2 peak) but not low intensity exercise (40% VO2 peak); however relative energy intake was lower in both the high and low intensity exercise groups compared with non-exercise controls. One study reported a significant decrease in absolute energy intake following strenuous (40 min/90 W cycle ergometer) but not moderate exercise (40 min/30 W cycle ergometer) in non-obese but not in obese women .
Two studies evaluated the role of exercise duration on post-exercise energy intake with divergent results. King et al.  reported no effect of exercise duration on post-exercise energy intake; however, Erdman et al.  reported that absolute energy intake was not significantly greater than control following cycle ergometer exercise bouts of 30 and 60 min, but was significantly greater than control following 120 minutes of exercise.
Exercise time of day.
Two studies evaluated the effect of the time of day of aerobic exercise on post-exercise energy intake , . Both studies found no significant difference in absolute post-exercise energy intake between exercise performed in the morning (7 and 8:15 AM) compared to the same exercise performed in the evening (5 and 7:15 PM). However, O'Donoghue et al.  showed that relative energy intake at breakfast was lower after morning exercise compared with afternoon exercise or control while relative energy intake at dinner was lower post afternoon exercise compared with control.
Composition of test meals.
Four studies evaluated the effect of the macronutrient composition of the test meal on post-exercise energy intake. Three studies found no significant differences in absolute post-exercise energy intake compared to rest between low or high fat test meals , , . King et al.  found no difference in absolute post-exercise energy intake when either high fat/low carbohydrate or low fat/high carbohydrate test meals were presented; however, relative energy intake was significantly lower in the low fat/high carbohydrate, but not the high fat/low carbohydrate condition compared with control.
Time between the end of exercise and the presentation of the test meal.
In the one acute study that investigated the effect of time between exercise and presentation of the test meal on energy intake, Verger et al.  showed that absolute energy intake increased as the time post-exercise that the test meals were presented increased (immediate to 120 min).
Effect of Participant Characteristics on Energy Intake
No studies evaluated the effect of age on post-exercise energy intake. Studies were generally conducted in young adults with a median age of 23 years.
Although 6 studies included both men and women – the data were presented separately in only one study. Verger et al.  showed significant increases in absolute EI following exercise (2 hours of non-stop submaximal aerobic athletic activities) in both men and women.
Three studies provided data on the effect of weight status on post-exercise energy intake , , . George et al.  found non-significant differences in absolute post-exercise energy intake between normal and overweight women. Kissileff et al.  reported significant decreases in post-exercise energy intake in non-obese, but not obese women, while Ueda et al.  found larger energy deficits (i.e. decreased energy intake) induced by exercise in obese compared with normal weight men.
Three studies evaluated the effect of combinations of weight, dieting status or level of eating restraint on post-exercise energy intake. Harris et al.  found no differences in post-exercise energy intake in a sample of men across 5 groups: 1) normal weight/low dietary restraint/non-dieting; 2) normal weight/high dietary restraint/non-dieting; 3) overweight/low dietary restraint/non-dieting; 4) overweight/high dietary restraint/non-dieting; and 5) overweight/high dietary restraint/dieting. In a sample of normal weight young women, Lluch et al.  found increased absolute post-exercise energy intake in women classified as unrestrained eaters and decreased energy intake in restrained eaters. Relative energy intake compared with rest was greater in restrained compared with unrestrained eaters. Visonia et al.  demonstrated a significant interaction between dieting/eating restraint status and study condition (exercise vs. control) on 12-hour energy intake in sample of women. The mean difference in 12-hour energy intake between the exercise and control day was significantly higher for the dieting-high restraint group compared with the non-dieting high restraint group.
Two studies evaluated the effect of activity level on post-exercise energy intake. Jokisch et al.  showed a significant decrease in post-exercise energy intake compared with control in inactive but not in active men. Larson-Meyer et al.  found non-significant differences between post-exercise energy intake and control in a normal weight sample of both habitual walkers (≥3 days/wk for ≥60 min/day) and habitual runners (≥32 km/wk); however, relative post-exercise energy intake was significantly lower in runners compared with controls, but not in walkers vs. controls.
The 10 short-term studies comprised ∼9% of the total studies identified for this review (Table 2). These studies employed cross-over designs that compared energy intake assessed over a time frame of 2–14 days during which participants engaged in exercise with energy intake during an equivalent period of no imposed exercise.
Short-Term Studies: Study Characteristics
One study prescribed exercise intensity at 70% of heart rate max (HRMax). Five studies prescribed intensity relative to VO2 max (median [range] 60% [44–75%]). Three studies did not report exercise intensity relative to VO2 or HRMax , , . Eight of 10 short-term studies (80%) dosed exercise by energy expenditure; 3 relative to body weight –, 3 relative to resting or baseline daily energy expenditure –, and 2 to an absolute exercise energy expenditure goal , . Two studies prescribed exercised by time that ranged from 60  to 100 min/day . Prescriptions ranged from 21.4  to 57.1 kJ/kg body weight , 1.4 to 1.8 times RMR , 12.5%  to 29% above baseline total energy expenditure  and net exercise energy expenditure from 2.8  to 2.98 MJ/day .
Short-Term Studies: Participant Characteristics
No studies describe the racial or ethnic composition of the study sample or reported an association between exercise level and energy intake by race or ethnicity.
Participant activity level.
Participants recruited for the majority of short-term studies (7/10 - 70%) were sedentary or moderately active –, , , . Two studies (20%) recruited active participants ,  while one study (10%) did not describe baseline participant physical activity .
Short-Term Studies: Results
Five of 10 short-term studies (50%) reported increased absolute energy intake (∼200–335 kcal/day) over periods of 2 to14 days when exercise was imposed compared with a non-exercise control period , , , , . Three studies that reported increased absolute energy intake showed relative energy intake at a level to maintain a negative energy balance during the exercise period , , ; however, Tremblay et al  showed that participants achieved a positive energy balance when presented with a high fat diet.
Seven of the 10 short-term studies (70%) reported macronutrient intake –, , , . Four of 7 studies (57%) showed no effect of exercise on macronutrient intake , , , . Farah et al.  reported increased intake of carbohydrate and protein while Stubbs et al.  observed increased intake of carbohydrate and fat with exercise compared to control. Whybrow et al.  noted increased intake of carbohydrate, fat and protein with exercise vs. control in men but not in women.
Effect of Study Parameters on Energy Intake
The one study that compared the effect of aerobic and resistance exercise reported no significant difference between exercise and control for short-term energy intake during either aerobic or resistance training .
Level of exercise energy expenditure.
Four studies evaluated the effect of increased levels of exercise energy expenditure on short-term energy intake –. Levels of energy compared were 12.5% vs. 25% above baseline energy expenditure , 21.4 vs. 42.8 kJ/kg/day ,  and 28.6 vs.57.1 kJ/kg/day . Three studies observed no effect , , . The study by Whybrow et al.  reported increased short-term energy intake associated with higher levels of exercise energy expenditure (57.1 vs. 28.6 kJ/kg/day) in men but not in women.
No studies evaluated the effect of exercise intensity on short-term energy intake.
Composition of test meals.
The one study that compared the effect of the composition of test meals (mixed, high fat, low fat) on short-term energy intake noted increased energy intake when high fat, but not low or mixed fat meals were presented .
Effect of Participant Characteristics on Energy Intake
No short-term studies evaluated the effect of age on post-exercise energy intake. Studies were generally conducted in young adults with a median age of 28.3 years.
Results from the two studies that evaluated gender differences in short-term energy intake with exercise reported that absolute energy intake increased in men but not in women , . Results from 2 separate studies that used identical exercise and energy intake protocols in samples of men  and women  found increased energy intake with exercise in women, but not in men.
The 12 non-randomized trials comprised ∼12% of the total studies identified for this review (Table 3). Most trials (11/12) evaluated changes in energy intake in a single group (no control) assigned to complete a longitudinal exercise training program , , – while one study observed differences in energy intake between women who participated in an 8 week exercise program at a commercial exercise facility with a group of non-exercise volunteer controls .
Non-Randomized Trials: Study Characteristics
Sample size/completion rate.
The median (range) sample size across the 12 non-randomized trials was 31 (10–107). The median (range) rate of trial completion in the 5 trials that provided data on this parameter was 83% (68–87%) of participants who started the intervention –, .
Six of 12 non-randomized trials involved laboratory based aerobic exercise conducted on cycle ergometers/rowers/steppers/treadmills , , , –, 5 trials employed indoor or outdoor walking , , , , while one trial required participants to complete a combination of gym activities (jogging/coordination/resistance) .
Exercise prescription (intensity).
Three trials prescribed intensity as a percentage of maximal VO2 –, 5 by percentage of HRMax , , , , , one by heart-rate-reserve  and one by ratings of perceived exertion . The median (range) of intensity prescriptions were: 40% (40–80%) max VO2; 73% (70–75%) HRMax, 59–67% heart-rate-reserve; and perceived exertion 11–13 on a 15 point scale. Prescribed exercise intensity was not reported in 2 trials , .
Exercise prescription (duration).
Six trials prescribed exercise duration by time , –, , 4 by level of exercise energy expenditure , , , , one by walking distance  and one by pedometer steps/day . The median (range) duration for the 6 trials prescribing exercise by time was 40 (30–60) min/day. All 4 studies prescribing exercise by energy expenditure assigned 500 kcal/exercise session. Prescribed walking distance was 3–6 km/day, and pedometer steps were to increase steps by 2,000 per day above baseline over 2 weeks.
Compliance with the exercise protocol.
Seven studies presented data relative to participant compliance with the exercise protocol , , –, , . Five trials reported the percentage of exercise sessions attended (range 82–100%) , , , , , 1 reported the level of exercise energy expenditure (prescribed 10.5 MJ/wk; achieved 9.9 MJ/wk)  and one trial reported pedometer steps/day (prescribed 2,000; achieved 2,677 steps/day) .
Energy and macronutrient assessment.
Five trials used non-weighed food records , , , , , 2 used weighed food records , , 3 used test meals , , , 1 used 12 hour recall  and one used a combination of food records and 24-hour recalls . Six studies assessed energy intake at baseline and end , , , , , , 3 studies completed energy intake assessments at 4 time points , , , one study at 3 time points  while 2 studies collected daily estimates of energy intake over the course of the intervention , .
Non-Randomized Trials: Participant Characteristics
The median (range) BMI was 29.3 (21.5–32.5) kg/m2. Five of 12 studies (42%) had a mean sample BMI in the overweight category (i.e. ≥25 kg/m2) , , , , , while the mean sample BMI was classified as obese (i.e. ≥30 kg/m2) in 5 trials , , , ,  and normal weight (i.e. BMI<25 kg/m2) in 2 trials , .
No non-randomized trials described the racial or ethnic composition of the study sample or reported an association between exercise level and energy intake by race or ethnicity.
Participant activity level.
Eleven of 12 non-randomized trials described inclusion criteria for level of baseline physical activity or aerobic fitness. With the exception of the trial of Koulouri et al.  who recruited regularly active participants, non-randomized trials were conducted in participants categorized as sedentary , , , , , , , or with low aerobic fitness , .
Non-Randomized Trials: Results
Eleven of 12 (92%) of non-randomized trials reported no change in energy intake in response to exercise training , –. One non-randomized trial reported a significant increase in energy intake (∼84 kcal/day) as a result of participating in an exercise training program .
Effect of Study Parameters on Energy Intake
No studies evaluated the effect of exercise mode on changes in energy intake in response to exercise training.
Level of exercise energy expenditure/duration.
No studies evaluated the effect of exercise energy expenditure/duration on energy intake in response to exercise training.
No studies evaluated the effect of exercise intensity on energy intake in response to exercise training.
Effect of Participant Characteristics on Energy Intake
No studies evaluated the effect of age on changes in energy intake in response to exercise training.
Three non-randomized trials provided data on gender differences , , . Two trials reported no differences for change in energy intake between men and women in response to exercise training , , while one trial found no effect in men or lean women, and a significant decrease in energy intake with exercise training in obese women .
The 24 randomized trials constituted ∼24% of the total number of studies identified for this review (Table 4). The majority of trials (16/24; ∼67%) evaluated the effect of exercise training on energy and macronutrient intake between participants randomized to exercise compared with non-exercise controls –. The effect of specific exercise training parameters on energy intake including mode (resistance/resistance plus aerobic/swim) –, , , intensity –, volume , ,  and timing (intermittent vs. continuous)  were also reported. The majority of randomized trials employed an efficacy design; however, reports from Jakicic et al.  and Foster-Schubert et al.  employed an intent-to-treat design, and Rosenkilde et al.  reported both efficacy and intent-to-treat results.
Randomized Trials: Study Characteristics
Sample size/completion rate.
The median (range) sample size across the 24 randomized trials was 43.5 (12–411). The median (range) proportion of randomized participants who completed the intervention and provided data for energy intake for the 23 trials that provided data on this parameter was 74% (21–100%).
Eight of 24 randomized trials involved laboratory based aerobic exercise where participants used a variety of modalities including cycle ergometers, rowers, recumbent cycles, steppers and treadmills , , , , , , , 8 evaluated indoor/outdoor walk/jog , , , , , , , , 5 trials employed primarily laboratory based treadmill walking/jogging , , , , , 4 trials involved resistance training only , , , , 2 trials used a combination of resistance and aerobic training ,  and one trial each involved swimming  and laboratory cycle ergometer exercise .
All exercise sessions were supervised in 15/24 (63%) of randomized trials , –, , , –, , –, , partially supervised in 6 trials (25%) , , , , ,  and unsupervised in 3 trials (∼13%) , , .
Exercise prescription (frequency).
The median (range) exercise frequency was 4 (2–7) days/wk in trials/groups randomized to aerobic exercise and 3 (2–4) days/wk for participants randomized to resistance training.
Exercise prescription (intensity).
Seven randomized trials prescribed intensity as a percentage of maximal VO2 , , , , , , , 8 trials used a percentage of HRMax , , , , , –, 6 used a percentage of heart-rate-reserve , , , , ,  and in 2 trials intensity was “self-paced” , . The median (range) of intensity prescriptions were: 65% (50–85%) maximal VO2; 70% (50–90%) HRMax, and 65% (50–75%) heart-rate-reserve.
Exercise prescription (duration).
Sixteen randomized trials prescribed exercise duration by time –, –, , , , –, 3 by level of exercise energy expenditure , , , and one each by energy expenditure/kg body weight , caloric equivalent of walking 12 miles/wk  and walking distance . The median (range) duration for the 16 trials prescribing exercise by time was 42 (30–60) min/day. Exercise prescriptions by level of energy expenditure were 300 kcal/day , 600 kcal/day  and both 300 and 600 kcal/day . Church et al.  randomized participants to energy expenditure groups of 4, 8 and 12 kcal/kg/wk, while Bales et al.  assigned participants to a combination of aerobic exercise modes (treadmill, elliptical, cycle ergometer) at a caloric equivalent of 12 miles/wk and Brandon et al.  prescribed walking 3 miles/session.
Compliance with the exercise protocol.
Eighteen studies presented data relative to participant compliance with the exercise training protocol , –, , , , –, –. Fifteen trials reported the percentage of exercise sessions attended [(median(range) 95% (74–100%)] , –, , , , –, , –, while 3 trials compared the prescribed with actual minutes of actual exercise completed. Bryner et al.  prescribed 40–45 min/day, 4 days/wk and observed 45 min/day, 4.1 days/wk. Cox et al.  prescribed 90 and achieved 124 min/wk while Nordby et al.  prescribed 600 kcal/session and achieved 576 kcal/session.
Energy and macronutrient assessment.
Twelve trials used non-weighed food records over 2 to 7 days , , , , , , , , , , , , 2 used weighed 3-day food records , , 5 used food frequency questionnaires , , , , , 3 used a combination of food records and 24 hour recalls , , , and one study each employed repeated 24 hour recalls , one study used weigh and measure ad libitum eating over 2 weeks , and one study used test meals offered over 8 days . Nine studies assessed energy intake only at baseline and end , , –, , , , 7 studies completed energy intake assessments at 3 time points –, , , , and 4 studies at 4 time points , , ,  and 4 at more than 4 time points , , , .
Randomized Trials: Participant Characteristics
Eleven trials (∼46%) included only women , , –, , , –, , 9 men only , , , –, , ,  and four studies (∼17%) included both men and women , , , ; however, only 2 of these studies provided separate result data by gender , .
The median (range) BMI for participants over the 24 randomized trials was 28.3 (25.0–32.4) kg/m2. Thirteen of the 24 randomized trials (∼54%) evaluated overweight participants (i.e. BMI>25 to ≤30 kg/m2) , , –, , , –, , , , while the mean sample BMI was classified as obese (i.e. ≥30 kg/m2) in 8 trials , , , , , , ,  and normal weight (i.e. BMI≤25 kg/m2) in 3 trials , , .
The median (range) percentage of non-white participants was 19% (0–60%) for the 9 randomized that provided information relative to the racial or ethnic composition of the study sample , –, , , , .
Participant activity level.
With the exception of the trial by Broeder et al. , who studied active but untrained participants; all randomized trials were conducted in participants who were sedentary or minimally active at baseline.
Randomized Trials: Results
Eighteen of 24 randomized trials (75%) found no significant change in energy intake in response to exercise training –, –, –, –. Five randomized trials reported significant decreases (∼200–500 kcal/day) in energy intake in response to exercise training , , , , . One randomized trial reported a significant increase in energy intake (Brandon 06). However, energy intake increased only in African American, but not white women, where energy intake decreased .
Eighteen of the 23 randomized trials (∼78%) that provided data on macronutrient intake found no change as a result of exercise training , , , –, , –, . Results from the 5 randomized trials that reported significant changes in macronutrient intake as a result of exercise training were mixed , , , , . For example, Brandon et al.  reported a significant increase in absolute carbohydrate intake in white, but not African American women, while Kirkwood et al.  reported a significant increase in the intake of fat as a percentage of total energy intake, with no change in the percentage of energy intake from carbohydrate or protein. Studies reported significant decreases in the absolute intake of carbohydrate , , , fat , ,  and protein ,  as well as decreases in the intake of fat as a percentage of total energy intake .
Effect of Study Parameters on Energy Intake
Two randomized trials compared change in energy intake in response to aerobic and resistance training. Broeder et al.  reported no change in energy intake in either the aerobic or resistance training groups while Bales et al.  reported a significant decrease in energy intake induced by aerobic, but not resistance training. A combination of aerobic plus resistance training was compared with aerobic training alone in 2 trials. Bales et al.  reported no between group differences for the change in energy intake with significant decreases in energy intake in both groups. Shaw et al.  reported significant decreases in energy intake in the aerobic plus resistance training group but not the aerobic training group. No significant changes in energy intake were reported in the 2 trials that evaluated energy intake in response to resistance training compared with non-exercise controls ,  or between participants who completed swim vs. walking training programs .
Level of exercise energy expenditure/duration.
No between group differences for change in energy intake in response to aerobic exercise training at difference levels of exercise energy expenditure were reported in the 4 trials that evaluated this parameter , , , .
Four randomized trials compared changes in energy intake in response to aerobic exercise training at low or high intensity –, . No significant between group differences for change in energy intake were reported in any of the 4 trials.
Intermittent vs. continuous exercise.
The one randomized trial that compared changes in energy intake in response to continuous (one-30 minute sessions/day) vs. intermittent exercise (2–15 minute sessions/day) reported no between or within group differences .
Composition of test meals.
Rosenkilde et al.  found no differences in energy intake with exercise training when low or high carbohydrate test meals were offered.
Effect of Participant Characteristics on Energy Intake
No randomized trials evaluated the effect of age on changes in energy intake in response to exercise training.
Two randomized trials provided data on gender differences for changes in energy intake in response to exercise training , . Donnelly et al.  reported no between group (exercise vs. control) for change in energy intake in response to 16 months of supervised exercise in either men or women. Similarly, Washburn et al.  found no between group differences (exercise vs. control) for change in energy intake in response to 6 months of supervised resistance training in either men or women.
Other participant characteristics.
No randomized trials were identified that specifically evaluated the effect of weight status, level of physical activity or level of dietary restraint on the energy intake response to exercise training.
Risk of bias.
The risk of bias for all randomized trials is presented in Table 5. The description of the procedures for random sequence generation were unclear in the majority of trials (16/24 - ∼67%). Six trials adequately described randomization procedures and were considered low risk of bias , , , , , , while 2 trials were considered high risk for randomization bias based on failure to provide any description of the randomization process  or randomization based on level of occupational and lifestyle physical activity . With the exception of the trial reported by Cox et al. , which adequately described procedures for allocation concealment (low bias) all other randomized trials (96%) provided no description of procedures for allocation concealment. Blinding participants and personnel is not feasible in an exercise trial. Blinding of personnel performing outcome assessments is feasible in exercise trials; however, this was described in only 2 trials , . Twenty one trials provided no information relative to blinding of outcome assessments, while one trial directly stated that outcome assessments were not blinded . Based on an effectiveness study paradigm the risk of attrition bias is high in the majority of the 24 randomized trials included in this review. Fifty-four percent of trials reported completion rates of less than 80%; however, 22 of 24 of these studies were conducted as efficacy trials where data from participants who were non-adherence to the exercise intervention or outcome assessment protocols were not included in the analysis.
Summary of Evidence
In this paper we systematically reviewed 99 studies that employed a variety of study designs including cross-sectional, acute/short-term, non-randomized and randomized trials to address the question: Does increased exercise or physical activity alter ad-libitum daily energy intake or macronutrient composition in healthy adults? Our results can be summarized as follows.
It is commonly believed that individuals increase energy intake in response to increased physical activity or exercise training. However overall, we found no consistent, compelling evidence that any level of increased physical activity or exercise has any impact on energy intake. Forty-one percent of cross-sectional studies reported higher energy intake among active compared with inactive individuals. However, cross-sectional data precludes determination of cause and effect. Likewise, it is not possible to determine if the higher energy intake observed among inactive individuals meets or exceeds their level of daily energy expenditure or how between group differences in body weight may impact the results of cross-sectional studies. In agreement with the results of the recent meta-analysis by Schubert et al.  on acute exercise and subsequent energy intake, our results from both acute and short-term trials suggest that any observed increase in post-exercise energy intake only partially compensates for the energy expended during exercise. Thus, in the short-term, exercise results in a negative energy balance. Results from both non-randomized and randomized trials are in agreement with the results from acute and short-term trials. Only 2 of 36 (∼6%) non-randomized and randomized trials, ranging in duration from 3 to 72 weeks, report an increase in absolute energy intake in response to exercise training, thus implying that exercise does not result in a compensatory increase in energy intake. A limited number of studies across all study designs have evaluated the effect of exercise parameters and participant characteristics on energy intake. Our results suggest no effect of either exercise parameters including mode (aerobic, resistance), intensity, duration/energy expenditure or participant characteristics including age, gender, weight or physical activity level on energy intake. These results are in contrast to those of Schubert et al.  from their meta-analysis on the acute effect of exercise on absolute post-exercise energy intake where they noted individuals with low to moderate levels of physical activity were more likely to reduce energy intake in response to exercise compared to their more active counterparts.
Data on macronutrient intake was reported in 67 of the 99 studies (68%) included in this review. Irrespective of study design we found no consistent evidence for an effect of exercise on macronutrient intake. Forty-four of 54 acute/short-term, non-randomized and randomized trials (81%) reported no effect of exercise on macronutrient intake, while results of the 10 trials reporting an association were mixed. Thus, it appears individuals do not spontaneously alter the composition of their diets in response to physical activity or exercise.
Limitations in the Available Literature
There are several important limitations in the literature available for this systemic review. The most critical limitation in the available literature is the lack of studies that have been specifically designed and adequately powered to detect significant between or within group differences in energy intake in response to exercise training. With the exception of 2 acute studies ,  no studies included in this review were statistically powered to detect between or within group differences in energy or macronutrient intake. Only 5 of 12 non-randomized trials (∼42%) , , – and 3 of 24 randomized trials (∼13%) were conducted specifically to evaluate the effect of exercise training on energy and macronutrient intake , , . The sample size in each of these 3 trials was <20 participants/group. Inadequate statistical power may explain the disconnect between the results of our review, which found no effect of exercise training on energy intake and other trials that have evaluated the effect of exercise on body weight. For example, studies have reported high individual variability in weight loss in response to the same level of exercise energy expenditure  and no significant increase in weight loss in response to increased level of exercise energy expenditure , . Both of these observations suggest compensatory increases in energy intake in response to exercise training; however, changes in resting metabolic rate and non-exercise physical activity may also play a role.
Because most exercise training studies did not prescribe exercise by level of energy expenditure, assess exercise energy expenditure, or employ adequate methods for the assessment of energy intake, it is not possible to determine the level of exercise induced energy imbalance actually achieved. Only 7 of the 36 non-randomized and randomized trials included in this review (∼19%) prescribed exercise by level of energy expenditure , , , , , ,  while only 3 of those trials included assessments of the actual level of exercise energy expenditure by indirect calorimetry , , . Furthermore, the heterogeneity of exercise/physical activity prescriptions prohibits the identification of a specific level that may elicit compensatory changes in energy intake. Only 5 of 36 non-randomized and randomized trials employed more precise estimates of dietary intake such as weigh and measure test meals , , ,  or observed weigh and measure ad-libitum eating . Two of the 3 trials that measured exercise energy expenditure used only 1 day assessments of energy intake using test meals at baseline and end study , , while one trial employed 4 day food records at baseline, mid and end study . Thus, reported estimates of energy balance should be cautiously interpreted. The available literature is also limited by a preponderance of data from acute/short-term studies as compared to non-randomized and randomized longitudinal trials. For example, approximately 50% of studies reviewed evaluated the acute or short-term (2–14 days) effect of exercise on energy and macronutrient intake. While acute/short-term studies have employed precise methods for the assessment of energy intake (weigh and measure test meals), the short time frame over which energy intake was assessed may be insufficient to demonstrate significant adaptations in energy intake that may be induced by changes in parameters such as aerobic fitness, body weight or hormonal status etc. associated with longer term exercise training. For example, in overweight men and women Kirk et al.  have shown that changes in aerobic fitness and weight takes 4 months and does not level off until 9 months in an exercise program with a typical progressive exercise protocol
Approximately 60% of acute studies reviewed recruited participants who were relatively young (median age = 23 years), normal weight, and physically active or aerobically fit. Thus, results from acute trials do not generalize to the older, sedentary overweight population in need of weight management. The available literature is also limited by an insufficient number of studies that have evaluated the impact of exercise parameters (e.g. mode, frequency, intensity, duration, time of day, time course) or participant characteristics (e.g. age, gender, ethnicity, weight, activity level) on energy and/or macronutrient intake.
Limitations of this Review
Our conclusions should be cautiously interpreted as they are based on both data from sub-optimal study designs (e.g. cross-sectional, acute/short-term, non-randomized trials) and from randomized trials with a high risk of one or more forms of bias. In addition, we did not contact authors to obtain missing data or for clarification of any information presented in the published reports; therefore missing information may reflect reporting bias as opposed to any limitations in the conduct of the study.
The present systematic review found limited evidence to suggest that acute exercise or exercise training has a significant effect on energy or macronutrient intake. However, as previously discussed the available literature on this topic suffers numerous methodological shortcomings. Therefore, we recommend additional randomized trials to specifically evaluate the impact of exercise training on energy and macronutrient intake that: 1) are powered specifically to detect clinically significant differences in energy and/or macronutrient intake; 2) utilize state-of-the-art techniques for the assessment of energy intake such as direct observation weigh and measure or picture-plate-waste and provide multiple measures across the duration of the study; 3) include assessments of exercise energy expenditure across the duration of the study; 4) evaluate and compare levels of exercise for weight management currently recommended by governmental agencies or professional organizations such as the International Association for the Study of Obesity, the Institute of Medicine, and the American College of Sports Medicine (i.e. 60–90 min/day, moderate intensity) to determine differential effects on energy and macronutrient intake; 5) include overweight and obese, sedentary middle-age or older adults; and 6) evaluate both the effect of exercise parameters (e.g. mode, frequency, intensity duration, time course) and participant characteristics (e.g. age, gender, body weight, activity level, ethnicity) on the association between exercise and energy and macronutrient intake.
PubMed complete search strategy.
Conceived and designed the experiments: JD RW SH KL JH AS. Performed the experiments: JD RW SH KL JH AS. Analyzed the data: JD RW SH KL JH AS. Contributed reagents/materials/analysis tools: JD RW SH KL JH AS. Wrote the paper: JD RW SH KL JH AS.
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