Effects of Meal Frequency on Weight Loss and Body Composition

Lead Article

Effects of meal frequency on weight loss and bodycomposition a meta-analysis

Brad Jon Schoenfeld Alan Albert Aragon and James W Krieger

It has been hypothesized that eating small frequent meals enhances fat loss andhelps to achieve better weight maintenance Several observational studies lendsupport to this hypothesis with an inverse relationship noted between the fre-quency of eating and adiposity The purpose of this narrative review is to presentand discuss a meta-analysis with regression that evaluated experimental researchon meal frequency with respect to changes in fat mass and lean mass A total of15 studies were identified that investigated meal frequency in accordance withthe criteria outlined Feeding frequency was positively associated with reductionsin fat mass and body fat percentage as well as an increase in fat-free massHowever sensitivity analysis of the data showed that the positive findings werethe product of a single study casting doubt as to whether more frequent mealsconfer beneficial effects on body composition In conclusion although the initialresults of this meta-analysis suggest a potential benefit of increased feeding fre-quencies for enhancing body composition these findings need to be interpretedwith circumspection

INTRODUCTION

The prevailing body of research indicates that weightmanagement is predicated on energy balance1

Specifically when caloric intake exceeds caloric expen-diture excess energy is stored primarily as triglycerides

in adipose tissue in the absence of regimented resistanceexercise Conversely a shift in energy balance favoringexpenditure over intake results in a loss of body mass

The energy balance equation is consistent with the firstlaw of thermodynamics which essentially states that en-

ergy is neither created nor destroyed but rather changedfrom one form to another

Because the human body is considered an open sys-tem various nutritional factors can impact the storage

or expenditure of energy within the context of the firstlaw of thermodynamics2 One such mitigating factor

often cited by researchers and practitioners is meal

frequency Specifically it has been hypothesized that

eating small frequent meals enhances fat loss and helpsto achieve better weight maintenance3 A number of

observational studies lend support to this hypothesiswith an inverse relationship noted between the fre-

quency of eating and adiposity4ndash7 Proposed mecha-nisms that explain the phenomenon include better

appetite control8ndash10 improved glucose homeostasis11ndash13

and an increase in the thermic effect of food1415

There also is evidence that frequent macronutrientintake may be beneficial to anabolism Several studies

show that protein synthesis and accretion are height-ened when protein-containing meals are consumed

frequently throughout the day Moore et al16 foundthat ingestion of protein every 3 h optimized increases

in net protein balance following a bout of lower bodyresistive exercise In relative agreement with thesefindings Areta et al17 demonstrated that post-exercise

Affiliations BJ Schoenfeld is with the Department of Health Science Lehman College Bronx NY USA AA Aragon is with California StateUniversity Northridge CA USA JW Krieger is with Weightology LLC Issaquah WA USA

Correspondence BJ Schoenfeld Department of Health Science CUNY Lehman College 250 Bedford Park Blvd West Bronx NY 10462 USAE-mail bradworkout911com

Key words adiposity body composition eating meal frequency meta-analysis weight management

VC The Author(s) 2015 Published by Oxford University Press on behalf of the International Life Sciences Institute All rights reservedFor Permissions please e-mail journalspermissionsoupcom

doi 101093nurenuu017Nutrition ReviewsVR Vol 73(2)69ndash82 69

by guest on March 13 2016

httpnutritionreviewsoxfordjournalsorg

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protein synthesis was maximal with a protein intake

spaced out over regimented 3-h intervals Beneficial ef-fects of smaller more frequent feedings on lean mass

have been attributed to an irreversible oxidation ofamino acids from larger protein boluses17 In addition

to having important implications for functional capac-ity an increase in lean mass would conceivably aid inweight management due to enhancements in resting

metabolic rate18

Despite an apparent theoretical basis results from

randomized controlled trials have been disparate re-garding an advantageous effect of frequent meals on

measures of body composition while some studies havereported benefits others have not Small sample sizes

and a consequent lack of statistical power may be re-sponsible for contradictory findings By pooling results

from the body of literature and controlling for con-founding variables a meta-analysis may help to provide

clarity on the topic The purpose of this article there-fore was to carry out a meta-analysis with regression

and to present an associated narrative review that evalu-ates experimental research on meal frequency with re-

spect to changes in fat mass and lean mass

METHODOLOGY

Inclusion criteria

Studies were deemed eligible for inclusion if they met the

following criteria 1) randomized controlled trial pub-lished in an English-language refereed journal 2) com-

pared unequal feeding frequencies of 3 meals a daywith 3 meals a day 3) had a study duration of at least

2 weeks 4) reported a pre- and post-intervention mea-sure of body composition (body mass body fat lean

mass) and 5) was carried out in human participants gt18years of age Studies investigating participants who had

undergone bariatric surgery were excluded from analysis

Search strategy

To carry out this meta-analysis and narrative review

English-language literature searches of the PubMed andCochrane Library databases were conducted for all time

periods up to November 2013 Combinations of thefollowing key words were used as search terms meal fre-

quency feeding frequency eating frequency meal patternfeeding pattern eating pattern body composition weight

loss fat loss lean mass and fat mass Per the methodsoutlined by Greenhalgh and Peacock19 the reference lists

of articles retrieved in the search were then screened forany additional articles that had relevance to the topic

Abstracts from conferences reviews and unpublished dis-sertationstheses were excluded from analysis

A total of 327 studies were evaluated based on the

search criteria To reduce the potential for selectionbias each study was independently evaluated by 2 of

the investigators (BJS and AAA) and a mutual deci-sion was made as to whether or not it met the basic in-

clusion criteria Any interreviewer disagreements weresettled by consensus andor consultation with the thirdinvestigator (JWK) A total of 15 studies were identi-

fied that investigated meal frequency in accordancewith the criteria outlined and provided adequate data

for analysis (Figure 1) Table 1 summarizes the studiesincluded for analysis

Coding of studies

Studies were read and individually coded by 2 of the in-

vestigators (BJS and AAA) for the following variablesdescriptive information of participants by group includ-

ing gender body mass body mass index age and strati-fied participant age (classified as either young [18ndash49

years] or elderly [50thorn years]) whether or not total en-ergy intake was equated between groups whether the

study was a parallel-group or crossover design the num-ber of participants in each group duration of the studywhether exercise was included in the study and if so if it

was endurance resistance or both whether participantswere in an energy deficit energy balance or energy sur-

plus and type of body composition measurement (scaleweight bioelectrical impedance analysis (BIA) dual

x-ray absorptiometry (DXA) etc) Coding was cross-checked between coders and any discrepancies were re-

solved by mutual consensus To assess potential coderdrift 4 studies were randomly selected for recoding as

described by Cooper et al35 Per-case agreement was de-termined by dividing the number of variables coded the

same by the total number of variables Acceptance re-quired a mean agreement of 090

Statistical analyses

The variance within each intervention group was calcu-

lated as the squared standard error of the mean (SEM)of the difference between pre- and post-diet outcomesWhere the SEM of the difference was not reported it

was calculated using the P value or confidence interval(CI) where available Otherwise an upper bound on the

SEM was calculated using the following formula inwhich s1 and s2 represent the standard deviation for the

pre- and post-test means respectively36

SEM frac14 peths1

2=nTHORN thorn eths22=nTHORN

If this calculation could not be made due to missing

standard deviation data then missing within-group

70 Nutrition ReviewsVR Vol 73(2)69ndash82

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variance data were imputed using multiple imputa-

tion37 Fifty imputed data sets were created and ana-lyzed for each outcome and the results were combined

for statistical inferencesMeta-analyses were performed using hierarchical

linear mixed models modeling the variation between

studies as a random effect the variation between treat-ment groups as a random effect nested within studies

and group-level predictors as fixed effects38 Thewithin-group variances were assumed known

Observations were weighted by the inverse of thewithin-group variances Model parameters were esti-

mated by the method of restricted maximum likeli-hood39 an exception was made during the model

reduction process in which parameters were estimatedby the method of maximum likelihood as likelihood

ratio tests (LRTs) cannot be used to compare nested

models with restricted maximum likelihood estimatesDenominator degrees of freedom for statistical tests and

CIs were calculated according to Berkey et al40 Foreach outcome an intercept-only model was createdModels were constructed for the change in body mass

fat-free mass (FFM) percent body fat ( BF) and fatmass For each outcome a simple model was created

with only number of meals as a continuous predictorFull models were then created with the following pre-

dictors initial body mass (kilograms) weeks calorie in-take and number of meals Models were reduced by

removing predictors one at a time starting with themost insignificant predictor41 The final model repre-

sented the reduced model with the lowest Bayesian in-formation criterion42 which was not significantly

Figure 1 Flow diagram of literature search

Nutrition ReviewsVR Vol 73(2)69ndash82 71

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ealsthorn

a Fora

ndash49

nloaded from

different (Pgt 005) from the full model when compared

using a likelihood ratio test Number of meals was notremoved during the model reduction process After the

model reduction process identical reduced modelswere created with number of meals as either a categori-

cal (1ndash2 meals 3ndash4 meals and 5thornmeals) or binary(lower and higher equivalent to the lower or higher fre-quency within each study) predictor Adjustments for

post hoc multiple comparisons among meal categorieswere made using a Hochberg correction43 Because

meta-regression can result in inflated false-positive rateswhen heterogeneity is present andor when there are

few studies44 a permutation test described by Higginsand Thompson44 was used to verify the significance of

the predictors in the final reduced models 1000 per-mutations were generated

In order to identify the presence of highly influen-tial studies that might bias the analysis a sensitivity

analysis was carried out for each model by removing 1study at a time and then examining the meal frequency

predictor Studies were identified as influential ifremoval resulted in a change of the meal frequency pre-

dictor going from significant or a trend (P 010) tononsignificant (Pgt 010) or vice versa

All analyses were performed using S-Plus 82(Tibco Spotfire Boston MA USA) Effects were con-

sidered significant at P 005 and trends were declaredat 005lt P 010 Data are reported as x 6 SEM and

95 CIs

RESULTS

Body mass change

The analysis of changes in participantsrsquo body mass com-prised 30 treatment groups from 15 studies The change

in body mass among these studies was 441 6 076 kg(95 CI 596 to 286)

In the simple model with number of meals as a con-tinuous predictor meal frequency was not significantly

associated with change in body mass (change in bodymass with each unit increase in number of meals

003 6 006 kg 95 CI 015 to 009 Pfrac14 065) Thiswas also true in the full model and reduced models

(003 6 006 kg 95 CI 015 to 010 Pfrac14 064) (Table2) In the reduced model with meal frequency as a

categorical predictor there were no significant differ-

ences in body mass change among the 1ndash2 meals 3ndash4meals and 5thorn meals groups (Figure 2) In the reduced

model with meal frequency as a binary predictor therewas no significant difference between lower and higher

frequencies for body mass change (differencefrac14020 6 021 95 CI 023 to 063 Pfrac14 035) (Figure 3)

Fat mass change

The analysis of changes in participantsrsquo fat mass com-

prised 18 treatment groups from 10 studies The changein fat mass among these studies was 355 6 112 kg

(95 CI 590 to 119)In the simple model with number of meals as a

continuous predictor meal frequency was significantlyassociated with change in fat mass (change in fat mass

with each unit increase in number of meals025 6 011 kg 95 CI 049 to 001 Pfrac14 004)This was also true in the full model and reduced models

(027 6 011 kg 95 CI 052 to 003 Pfrac14 003)(Table 3) However permutation test results failed to

support the significance of the meal frequency predictor(Pfrac14 041) In the reduced model with meal frequency

as a categorical predictor there was a trend for5thornmeals to result in greater fat loss than 1ndash2 meals

(differencefrac14 124 6 049 kg 95 CI 011 to 259Pfrac14 007) with no other differences among categories

(Figure 4) In the reduced model with meal frequencyas a binary predictor higher meal frequencies were as-

sociated with greater fat loss compared with lower fre-quencies (differencefrac14 089 6 039 95 CI 006 to 171

Pfrac14 004) (Figure 5)Sensitivity analyses revealed that the significant im-

pact of meal frequency on fat loss was highly affected bythe study performed by Iwao et al28 When this study

was removed from the analysis the impact of meal fre-quency on change in fat mass was no longer significant

(change in fat mass with each unit increase in numberof meals 016 6 019 kg 95 CI 061 to 030

Pfrac14 044) (Figure 5)

Fat-free mass change

The analysis of changes in participantsrsquo FFM included17 treatment groups from 9 studies The change in FFM

Table 2 Reduced model for change in body massEffect Coefficienta 95 Confidence interval P valueIntercept 824 6 129 1086 to 561 lt00001Weeks 010 6 005 021 to 001 007Energy intake (kcal) 00032 6 00006 0002 to 0004 lt00001Number of meals 003 6 006 015 to 009 060aNegative values of coefficients indicate larger decreases in body mass for each unit increase in the covariatePositive values indicate smaller decreases in body mass for each unit increase in the covariate

nloaded from

+51minus2 3minus4

Meals Per Day

Figure 2 Reduced model for differences in change in body mass with meal frequency Values in kilograms

Figure 3 Forest plot of meal frequency on body mass

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among these studies was 188 6 054 kg (95 CI

303 to 074)In the simple model with number of meals as a con-

tinuous predictor there was a trend for more meals to

be associated with better FFM retention (change inFFM with each unit increase in number of meals

022 6 011 kg 95 CI 002 to 046 Pfrac14 007) In thefull and reduced models the trend became significant

(025 6 010 kg 95 CI 003 to 047 Pfrac14 003) (Table 4)However permutation test results failed to support the

significance of the meal frequency predictor (Pfrac14 025)In the reduced model with meal frequency as a categori-

cal predictor there was a trend for 5thorn meals to result ingreater FFM retention compared with 1ndash2 meals (differ-

encefrac14 109 6 041 kg 95 CI 007 to 224 Pfrac14 006)with no other differences between categories (Figure 6)

In the reduced model with meal frequency as a binary

predictor there was no impact of meal frequency on

FFM retention (differencefrac14 062 6 052 95 CI 049to 174 Pfrac14 025) (Figure 7)

Sensitivity analyses revealed that the significant im-

pact of meal frequency on FFM retention was highly af-fected by the study performed by Iwao et al28 When this

study was removed from the analysis the impact of mealfrequency on FFM was no longer significant (change in

FFM with each unit increase in number of meals002 6 030 kg 95 CI 068 to 065 Pfrac14 096)

Percent body fat change

The analysis of changes in participantsrsquo BF included17 treatment groups from 9 studies The change in

BF among these studies was 181 6 063 (95 CI315 to 048)

Table 3 Reduced model for change in fat massEffect Coefficienta 95 Confidence interval P valueIntercept 319 6 306 336 to 973 031Initial body mass (kg) 008 6 003 015 to 001 003Weeks 033 6 013 060 to 006 002Energy intake (kcal) 00017 6 00009 00002 to 00036 008Number of meals 027 6 011 052 to 003 003 b

aNegative values of coefficients indicate larger decreases in fat mass for each unit increase in the covariate Positivevalues indicate smaller decreases in fat mass for each unit increase in the covariatebThis covariate was not significant using a permutation test (Pfrac14 041) Also sensitivity analyses revealed that the sig-nificance of this covariate was highly influenced by the study by Iwao et al28 When this study was removed from theanalysis the impact of meal frequency on change in fat mass was no longer significant (change in fat mass with eachunit increase in number of meals 016 6 019 kg 95 confidence interval 061 to 030 Pfrac14 044)

+53minus41minus2

Meals Per Day

Figure 4 Reduced model for differences in change in fat mass with meal frequency Values in kilograms

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In the simple model with number of meals as a

continuous predictor a higher number of meals was as-sociated with a greater decrease in BF (change in

BF with each unit increase in number of meals023 6 009 95 CI 043 to 003 Pfrac14 003)

However permutation tests failed to support the signifi-cance of the meal frequency predictor (Pfrac14 013)

Also the significant effect disappeared upon control forother covariates in the full and reduced models

(009 6 016 95 CI 043 to 025 Pfrac14 058)(Table 5) In the reduced model with meal frequency

as a categorical predictor there were no significantdifferences in BF between 1ndash2 meals 3ndash4 meals and

5thorn meals (Figure 8) In the reduced model with mealfrequency as a binary predictor there was no im-

pact of meal frequency on BF change

(differencefrac14 008 6 040 95 CI 078 to 094

pact of meal frequency in the simple model was highlyaffected by the study by Arciero et al20 When this study

was removed from the analysis the impact of meal fre-quency on BF was no longer significant (change in

BF with each unit increase in number of meals0005 6 027 kg 95 CI 060 to 059 Pfrac14 099)

DISCUSSION

This is the first meta-analysis to evaluate the effects

of differing meal frequencies on body composition Theprimary novel and important findings of the analysis

are that increased feeding frequency appeared to be

Figure 5 Forest plot of meal frequency on fat mass

Table 4 Reduced model for change in fat-free massEffect Coefficienta 95 Confidence interval P valueIntercept 735 6 181 1131 to 340 0002Initial body mass (kg) 006 6 002 001 to 011 003Number of meals 025 6 010 003 to 047 003 b

aNegative values of coefficients indicate larger decreases in fat-free mass for each unit increase in thecovariate Positive values indicate smaller decreases in fat-free mass for each unit increase in the covariatebThis covariate was not significant using a permutation test (Pfrac14 025) Also sensitivity analyses revealed that thesignificance of this covariate was highly influenced by the study by Iwao et al When this study was removedfrom the analysis the impact of meal frequency on fat-free mass was no longer significant (change in fat-freemass with each unit increase in number of meals 002 6 030 kg 95 CI 068 to 065 Pfrac14 096)

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positively associated with reductions in fat mass and

body fat percentage as well as an increase in FFMHowever sensitivity analysis of the data showed that

the positive findings were largely the product of a single

study casting doubt as to whether more frequent meals

confer beneficial effects on body composition These re-sults have important implications with respect to the

popular suggestion that eating small frequent meals is a

+53minus41minus2

Meals Per Day

Figure 6 Reduced model for differences in change in fat-free mass with meal frequency Values in kilograms

Figure 7 Forest plot of meal frequency on fat-free mass

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preferred method for optimizing weight managementin the general population3

Increasing meal frequency is often promoted as abeneficial strategy for reducing fat mass3 Justification

for this claim generally revolves around the belief thatfrequent feedings enhance postprandial thermogenesis

defined as the increase in heat production that occursfor up to 8 h after consumption of a meal45 LeBlanc

et al15 demonstrated that feeding dogs 4 small mealsdoubled the thermogenic response compared with eat-

ing the same number of total calories as a large singlemeal In a follow-up study the same group ofresearchers found similar results in humans which

the authors attributed to repeated stimulation of thesympathetic nervous system14 However the majority of

studies on the topic have failed to show a positive rela-tionship between meal frequency and energy expendi-

ture46ndash50 and 1 trial with adult women actually found agreater thermic effect from consuming a single food bo-

lus as compared with 6 small calorie-equated meals45

Interestingly Smeets et al10 found no differences in

diet-induced thermogenesis or energy expenditure inthe consumption of 2 versus 3 calorie-equated meals a

day but did note that 24-h fat oxidation was greater inthe 3-meal condition

On the surface the results of the present analysisseem to provide support for the contention that eating

more frequently results in greater body fat losses A sig-nificant positive effect was found between frequency of

feeding and reductions in fat mass with an additional027 kg loss of fat noted for each additional meal These

results held true even after controlling for total energyintake In multiple comparisons there was a trend for a

superiority of 5thorn meals compared with 1ndash2 meals (adifference of 124 kg and an adjusted P value of 007)

no other differences in fat loss were detected betweencategories The binary higher frequency variable alsoshowed significance with the higher frequency in each

study associated with a 09-kg greater reduction in fatmass To determine if a particular study heavily influ-

enced outcomes a sensitivity analysis was performedwhereby 1 study was removed at a time in order to ex-

amine the effect of meal frequency on fat mass Thisanalysis showed that removal of the study by Iwao

et al28 completely eliminated the significant impact ofmeal frequency with the P value changing from 004 to

044 The standard error in this study was much smallerthan that of the other studies thereby giving it a dispro-

portionate weighting in the analysis Similarly althoughthe basic model for the present analysis displayed a

Table 5 Reduced model for change in percent body fatEffect Coefficienta 95 Confidence interval P valueIntercept 545 6 168 181 to 908 0007Weeks 036 6 013 065 to 007 002Energy intake (kcal) 0002 6 00005 0003 to 0001 00003Number of meals 009 6 016 043 to 025 058aNegative values of coefficients indicate larger decreases in percent body fat for each unit increase in the covari-ate Positive values indicate smaller decreases in percent body fat for each unit increase in the covariate

+51minus2 3minus4

Meals Per Day

Figure 8 Reduced model for differences in change in percent body fat with meal frequency Values in percentages

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significant positive effect for greater meal frequencieson body fat percentage when covariates were not con-trolled subanalysis showed that this effect was fully ex-

plained by variances in total daily energy intake afteraccounting for this variable no differences were seen in

body fat percentages regardless of the number of mealsconsumed In combination the totality of findings indi-

cate that the significant impact of meal frequency onmeasures of fat loss is a false positive rather than a true

effect and can be attributed to undue weighting of a sin-gle study (ie Iwao et al28)

A potential confounding issue with the presentanalysis was an inability to assess the size and composi-

tion of each eating episode These variables couldpotentially account for differences in postprandial food

intake and could thus mediate a change in body massover time To account for any such discrepancies a sub-

analysis was run whereby the studies that did not con-trol for caloric intake were separated from those that

were energy equated All but 2 of the studies meetingthe inclusion criteria did in fact equate calories con-

sumed2632 Removal of these studies via regressionanalysis had no impact on any of the outcomes indicat-

ing that under calorie-controlled conditions meal fre-quency does not alter measures of body composition

The consumption of frequent meals also has beenpostulated to enhance the retention of FFM and possi-bly even increase muscle protein accretion The ana-

bolic impact of feeding has been estimated to lastapproximately 5ndash6 h based on the postprandial rate of

amino acid metabolism51 Some studies in rodents5253

and in humans5455 suggest that the rise in muscle pro-

tein synthesis (MPS) following consumption of aminoacids or a protein-rich meal is more transient with lev-

els returning to baseline after approximately 3 h Thisphenomenon is thought to occur despite sustained ele-

vations in amino acid availability leading to the ldquomus-cle-full hypothesisrdquo whereby MPS becomes refractory

and circulating amino acids are oxidized rather thanused for tissue-building purposes when a bolus of more

than approximately 20 g of amino acids is consumed byyoung individuals Anabolic sensitivity is diminished

with age so that the saturable limit in the elderly rises toapproximately 40 g per serving The muscle-full hypoth-

esis therefore suggests that multiple daily feedings of20ndash40 g depending on age are needed to maximize

anabolism The findings from nitrogen-balance studieshave been inconsistent on the topic with some showing

a positive correlation between meal frequency andnitrogen retention56 and others showing no such

Figure 9 Forest plot of meal frequency on percent body fat

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relationship27 It should be noted that the nitrogen-

balance technique measures whole-body protein fluxand thus does not necessarily reflect skeletal muscle

protein metabolism57 With respect to direct effects onskeletal muscle Areta et al17 found that 4 doses of 20 g

whey protein consumed every 3 h produced superioracute increases in MPS compared with a bolus provi-sion (2 doses of 40 g every 6 h) or a pulse feeding (8

doses of 10 g every 15 h) which is consistent with themuscle-full hypothesis58 The initial analysis performed

for this review with number of meals as a continuouspredictor did in fact show a trend for positive effects

of increased feeding frequencies on FFM and this be-came significant in the full and reduced models

However as with the effects on fat mass sensitivityanalysis revealed that the results were unduly influenced

by the results of Iwao et al28 and removal of this studynegated any benefit related to the number of meals con-

sumed per day with a change in P value from 003 to096 This suggests that findings can be attributed to a

false positive and that varying the frequency of feedingdoes not lead to a greater accumulation of FFM The

reasons for these divergent findings remain elusiveHowever it should be noted that acute measures of

MPS do not necessarily correlate with long-term in-creases in muscle hypertrophy59

It is tempting to assume that a within-day distribu-tion of dietary protein that is even has more favorable

effects on body composition than a distribution that isskewed However this area of study is largely unre-

solved as findings are conflicting Mamerow et al60

recently found that consuming 3 mixed meals with ap-

proximately 30 g protein each stimulated approximately25 more 24-h MPS than skewing the protein toward

the evening meal (approximately 10 15 and 65 g atbreakfast lunch and dinner respectively) However

this acute finding is challenged by longitudinal researchthat measured effects on body composition A 14-day

trial by Arnal et al61 found no difference in FFM or ni-trogen retention between young women who consumeda ldquopulse-feedingrdquo pattern with 79 of the dayrsquos protein

needs (approximately 54 g) in 1 meal versus proteinspread evenly across 4 meals

Interestingly a previous study by Arnal et al62 inelderly participants found that protein pulse-feeding re-

sulted in more positive nitrogen balance compared withan evenly spread feeding pattern The discrepant re-

sponses between the young and elderly participantscould potentially be due to age-associated anabolic re-

sistance where elicitation of robust MPS levels requiresa larger protein dose per meal in older participants63 It

is possible that the pulse-feeding condition provideda protein dose containing sufficient essential amino

acids (leucine in particular) to maximize the anabolic

response to one of the meals In contrast it is possible

that none of the meals in the spread condition reachedthe leucine threshold necessary for triggering MPS

Recent work by Adechian et al64 further challengesthe presumed benefits of evenly distributing protein in-

take throughout the day No significant between-groupdifferences in body composition change were seen in a6-week comparison of whey versus casein consumed in

a ldquopulserdquo meal pattern (88048) versus a ldquospreadrdquopattern (25252525) Collectively these findings

strengthen the hypothesis that the within-day meal fre-quency and distribution pattern should be determined

by individual preference Further research is necessaryto elucidate discrepancies between acute and longitudi-

nal studies and determine if certain feeding strategiesare in fact better than others with respect to muscle

anabolismThis meta-analysis had several limitations First

the vast majority of studies analyzed were conducted ina sedentary population so the findings may not apply

to athletes or those involved in structured physical ac-tivity programs Indeed the one RCT that investigated

the effects of meal frequency in an athletic populationshowed a favorable effect on body composition from

more frequent feedings28 Moreover a published ab-stract by Benardot et al65 showed a significant increase

in FFM and a decrease in fat mass following provisionof a 250-calorie snack versus placebo over a 2-week pe-

riod in college athletes This has led to speculation thatincreased meal frequency may be beneficial for enhanc-

ing body composition in those who participate in vigor-ous physical exercise57 Unfortunately the paucity of

research on the topic precludes the formation ofevidence-based conclusions Further investigation is

needed to better determine whether altering meal fre-quency has a positive effect on body composition in

well-trained individualsSecond it is not clear if the results of this analysis

apply to diets that include higher daily protein intakesVirtually all of the studies on this topic to date used lowto moderate amounts of protein The one exception a

study by Arciero et al20 did show significant improve-ments in body composition when an energy-equated

high-protein diet (approximately 34 of total calories)was consumed in 6 versus 3 daily meals The re-

searchers speculated that these results were related to anenhanced thermogenic response with the greater meal

frequency Future research should seek to determinewhether spreading out feedings over the course of a day

confers beneficial effects in those consuming high-protein diets

Third the present findings are specific to changesin body composition Although improvements in body

composition are often related to better health-related

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outcomes this analysis did not directly investigate the

influence of meal frequency on factors related to cardio-metabolic risk There is some evidence that increasing

the frequency of feeding can have positive effects onglucose homeostasis insulin sensitivity and lipid

levels12136667 although not all studies support thishypothesis6768 The scope and generalizability of theseeffects cannot be determined from the present analysis

and thus warrant further investigationFinally the present study did not determine

whether meal frequency might play a role in suppress-ing appetite Acute studies on the topic have been con-

flicting While several trials reported that appetite wasreduced when meals were spaced out over the course of

a day8ndash1031 others failed to detect such differencesregardless of feeding frequency2569 Moreover some

studies found that eating 3 as opposed to 6 daily mealsactually promotes greater feelings of satiety4970 Pooled

analysis of the data did show a positive effect of mealfrequency on body fat that was negated after accounting

for energy intake which suggests that more frequentfeedings may have contributed to better appetite con-

trol These findings require further study in controlledad libitum trials

CONCLUSION

Although the initial results of the present meta-analysissuggest a potential benefit of increased feeding frequen-

cies for enhancing body composition these findingsneed to be interpreted with circumspection The posi-

tive relationship between the number of meals con-sumed and improvements in body composition were

largely attributed to the results of a single study callinginto question the veracity of results Moreover the

small difference in magnitude of effect between fre-quencies suggests that any potential benefits if they ex-

ist at all have limited practical significance Given thatadherence is of primary concern with respect to nutri-

tional prescription the number of daily meals con-sumed should come down to personal choice if onersquos

goal is to improve body compositionThere is emerging evidence that an irregular eating

pattern can have negative metabolic effects at least inthe absence of formal exercise7172 This gives credence

to the hypothesis that it may be beneficial to stay consis-tent with a given meal frequency throughout the week

Acknowledgments

Author contributions BJS devised the search strategyJWK carried out the statistical analysis BJS and

AAA carried out the search of literature All authors

were involved in the coding and writing of themanuscript

Funding No external funding was received for this

Declaration of interest The authors have no relevant

interests to declare

REFERENCES

1 Hall KD Heymsfield SB Kemnitz JW et al Energy balance and its components im-plications for body weight regulation Am J Clin Nutr 201295989ndash994

2 Thomas DM Ciesla A Levine JA et al A mathematical model of weight changewith adaptation Math Biosci Eng 20096873ndash887

3 Louis-Sylvestre J Lluch A Neant F et al Highlighting the positive impact of in-creasing feeding frequency on metabolism and weight management ForumNutr 200356126ndash128

4 Fabry P Hejl Z Fodor J et al The frequency of meals Its relation to overweighthypercholesterolaemia and decreased glucose-tolerance Lancet 19642614ndash615

5 Metzner HL Lamphiear DE Wheeler NC et al The relationship between frequencyof eating and adiposity in adult men and women in the Tecumseh CommunityHealth Study Am J Clin Nutr 197730712ndash715

6 Ma Y Bertone ER Stanek EJ 3 rd et al Association between eating patterns andobesity in a free-living US adult population Am J Epidemiol 200315885ndash92

7 Ruidavets JB Bongard V Bataille V et al Eating frequency and body fatness inmiddle-aged men Int J Obes Relat Metab Disord 2002261476ndash1483

8 Speechly DP Buffenstein R Greater appetite control associated with an increasedfrequency of eating in lean males Appetite 199933285ndash297

9 Speechly DP Rogers GG Buffenstein R Acute appetite reduction associated withan increased frequency of eating in obese males Int J Obes Relat Metab Disord1999231151ndash1159

10 Smeets AJ Westerterp-Plantenga MS Acute effects on metabolism and appetiteprofile of one meal difference in the lower range of meal frequency Br J Nutr2008991316ndash1321

11 Jenkins DJ Ocana A Jenkins AL et al Metabolic advantages of spreading the nu-trient load effects of increased meal frequency in non-insulin-dependent diabe-tes Am J Clin Nutr 199255461ndash467

12 Jenkins DJ Wolever TM Vuksan V et al Nibbling versus gorging metabolic ad-vantages of increased meal frequency N Engl J Med 1989321929ndash934

13 Bertelsen J Christiansen C Thomsen C et al Effect of meal frequency on bloodglucose insulin and free fatty acids in NIDDM subjects Diabetes Care 1993164ndash7

14 LeBlanc J Mercier I Nadeau A Components of postprandial thermogenesis in re-lation to meal frequency in humans Can J Physiol Pharmacol 199371879ndash883

15 LeBlanc J Diamond P Effect of meal size and frequency on postprandial thermo-genesis in dogs Am J Physiol 1986250(2 Pt 1)E144ndashE147

16 Moore DR Areta J Coffey VG et al Daytime pattern of post-exercise protein in-take affects whole-body protein turnover in resistance-trained males Nutr Metab20129doi 1011861743-7075-9-91

17 Areta JL Burke LM Ross ML et al Timing and distribution of protein ingestionduring prolonged recovery from resistance exercise alters myofibrillar protein syn-thesis J Physiol 2013591(Pt 9)2319ndash2331

18 Cunningham JJ A reanalysis of the factors influencing basal metabolic rate in nor-mal adults Am J Clin Nutr 1980332372ndash2374

19 Greenhalgh T Peacock R Effectiveness and efficiency of search methods in sys-tematic reviews of complex evidence audit of primary sources BMJ 20053311064ndash1065

20 Arciero PJ Ormsbee MJ Gentile CL et al Increased protein intake and meal fre-quency reduces abdominal fat during energy balance and energy deficit Obesity2013211357ndash1366

21 Antoine JM Rohr R Gagey MJ et al Feeding frequency and nitrogen balance inweight-reducing obese women Hum Nutr Clin Nutr 19843831ndash38

22 Bachman JL Raynor HA Effects of manipulating eating frequency during a behav-ioral weight loss intervention a pilot randomized controlled trial Obesity 201220985ndash992

23 Berteus-Forslund H Klingstrom S Hagberg H et al Should snacks be recom-mended in obesity treatment A 1-year randomized clinical trial Eur J Clin Nutr2008621308ndash1317

24 Bortz WM Wroldsen A Issekutz B Jr et al Weight loss and frequency of feedingN Engl J Med 1966274376ndash379

25 Cameron JD Cyr MJ Doucet E Increased meal frequency does not promotegreater weight loss in subjects who were prescribed an 8-week equi-energetic en-ergy-restricted diet Br J Nutr 20101031098ndash1101

nloaded from

26 Chapelot D Marmonier C Aubert R et al Consequence of omitting or adding ameal in man on body composition food intake and metabolism Obesity 200614215ndash227

27 Finkelstein B Fryer BA Meal frequency and weight reduction of young womenAm J Clin Nutr 197124465ndash468

28 Iwao S Mori K Sato Y Effects of meal frequency on body composition duringweight control in boxers Scand J Med Sci Sports 19966265ndash272

29 Poston WS Haddock CK Pinkston MM et al Weight loss with meal replacementand meal replacement plus snacks a randomized trial Int J Obes 2005291107ndash1114

30 Schlundt DG Hill JO Sbrocco T et al The role of breakfast in the treatment ofobesity a randomized clinical trial Am J Clin Nutr 199255645ndash651

31 Stote KS Baer DJ Spears K et al A controlled trial of reduced meal frequencywithout caloric restriction in healthy normal-weight middle-aged adults Am JClin Nutr 200785981ndash988

32 Vander Wal JS Waller SM Klurfeld DM et al Effect of a post-dinner snack and par-tial meal replacement program on weight loss Int J Food Sci Nutr 20065797ndash106

33 Verboeket-van de Venne WP Westerterp KR Frequency of feeding weight reduc-tion and energy metabolism Int J Obes Relat Metab Disord 19931731ndash36

34 Young CM Scanlan SS Topping CM et al Frequency of feeding weight reductionand body composition J Am Diet Assoc 197159466ndash472

35 Cooper H Hedges L Valentine J The Handbook of Research Synthesis and Meta-analysis 2nd ed New York Russell Sage Foundation 2009

36 Lane DM Sampling distribution of difference between means httponlinestatbookcom2sampling_distributionssamplingdist_diff_meanshtmlAccessed December 7 2014

37 Schafer JL Analysis of Incomplete Multivariate Data London Chapman and Hall1997

38 Hox JJ de Leeuw ED Multilevel models for meta-analysis In SP Reise N Duaneds Multilevel Modeling Methodological Advances Issues and ApplicationsMahwah NJ Lawrence Erlbaum Associates 200390ndash111

39 Thompson SG Sharp SJ Explaining heterogeneity in meta-analysis a comparisonof methods Stat Med 1999182693ndash2708

40 Berkey CS Hoaglin DC Mosteller F et al A random-effects regression model formeta-analysis Stat Med 199514395ndash411

41 Burnham KP Anderson DR Model Selection and Inference A PracticalInformation-theoretic Approach New York Springer-Verlag 2002

42 Schwarz G Estimating the dimension of a model Ann Stat 19786461ndash46443 Hochberg Y A sharper Bonferroni procedure for multiple tests of significance

Biometrika 198875800ndash80244 Higgins JPT Thompson SG Controlling the risk of spurious findings from meta-

regression Stat Med 2004231663ndash168245 Tai MM Castillo P Pi-Sunyer FX Meal size and frequency effect on the thermic

effect of food Am J Clin Nutr 199154783ndash78746 Verboeket-van de Venne WP Westerterp KR Influence of the feeding frequency

on nutrient utilization in man consequences for energy metabolism Eur J ClinNutr 199145161ndash169

47 Taylor MA Garrow JS Compared with nibbling neither gorging nor a morningfast affect short-term energy balance in obese patients in a chamber calorimeterInt J Obes Relat Metab Disord 200125519ndash528

48 Kinabo JL Durnin JV Effect of meal frequency on the thermic effect of food inwomen Eur J Clin Nutr 199044389ndash395

49 Ohkawara K Cornier MA Kohrt WM et al Effects of increased meal frequency onfat oxidation and perceived hunger Obesity 201321336ndash343

50 Hill JO Anderson JC Lin D et al Effects of meal frequency on energy utilization inrats Am J Physiol 1988255(4 Pt 2)R616ndashR621

51 Layman DK Protein quantity and quality at levels above the RDA improves adultweight loss J Am Coll Nutr 200423(6 Suppl)631 Sndash636 S

52 Wilson GJ Layman DK Moulton CJ et al Leucine or carbohydrate supplementa-tion reduces AMPK and eEF2 phosphorylation and extends postprandial muscleprotein synthesis in rats Am J Physiol Endocrinol Metab 2011301E1236ndashE1242

53 Norton LE Layman DK Bunpo P et al The leucine content of a complete meal di-rects peak activation but not duration of skeletal muscle protein synthesis andmammalian target of rapamycin signaling in rats J Nutr 20091391103ndash1109

54 Atherton PJ Etheridge T Watt PW et al Muscle full effect after oral protein time-dependent concordance and discordance between human muscle protein syn-thesis and mTORC1 signaling Am J Clin Nutr 2010921080ndash1088

55 Bohe J Low JF Wolfe RR et al Latency and duration of stimulation of humanmuscle protein synthesis during continuous infusion of amino acids J Physiol2001532(Pt 2)575ndash579

56 Garrow JS Durrant M Blaza S et al The effect of meal frequency and protein con-centration on the composition of the weight lost by obese subjects Br J Nutr1981455ndash15

57 La Bounty PM Campbell BI Wilson J et al International society of sports nutritionposition stand meal frequency J Int Soc Sports Nutr 201184

58 Phillips BE Hill DS Atherton PJ Regulation of muscle protein synthesis in humansCurr Opin Clin Nutr Metab Care 20121558ndash63

59 Mitchell CJ Churchward-Venne TA Parise G et al Acute post-exercise myofibrillarprotein synthesis is not correlated with resistance training-induced muscle hyper-trophy in young men PLoS One 20149e89431

60 Mamerow MM Mettler JA English KL et al Dietary protein distribution positivelyinfluences 24-h muscle protein synthesis in healthy adults J Nutr 2014144876ndash880

61 Arnal MA Mosoni L Boirie Y et al Protein feeding pattern does not affect proteinretention in young women J Nutr 20001301700ndash1704

62 Arnal MA Mosoni L Boirie Y et al Protein pulse feeding improves protein reten-tion in elderly women Am J Clin Nutr 1999691202ndash1208

63 Breen L Phillips SM Skeletal muscle protein metabolism in the elderly interven-tions to counteract the rsquoanabolic resistancersquo of ageing Nutr Metab 20118doi1011861743-7075-8-68

64 Adechian S Balage M Remond D et al Protein feeding pattern casein feedingor milk-soluble protein feeding did not change the evolution of body compositionduring a short-term weight loss program Am J Physiol Endocrinol Metab 2012303E973ndashE982

65 Benardot D Martin DE Thompson WR et al Between-meal energy intake effectson body composition performance and total caloric consumption in athletesMed Sci Sports Exerc 200537(Suppl)S339

66 Arnold LM Ball MJ Duncan AW et al Effect of isoenergetic intake of three or ninemeals on plasma lipoproteins and glucose metabolism Am J Clin Nutr 199357446ndash451

67 Munsters MJ Saris WH Effects of meal frequency on metabolic profiles and sub-strate partitioning in lean healthy males PLoS One 20127e38632

68 Holmstrup ME Owens CM Fairchild TJ et al Effect of meal frequency on glucoseand insulin excursions over the course of a day Eur e-J Clin Nutr Metab 20105277ndash280

69 Leidy HJ Tang M Armstrong CL et al The effects of consuming frequent higherprotein meals on appetite and satiety during weight loss in overweightobesemen Obesity 201119818ndash824

70 Leidy HJ Armstrong CL Tang M et al The influence of higher protein intake andgreater eating frequency on appetite control in overweight and obese menObesity 2010181725ndash1732

71 Farshchi HR Taylor MA Macdonald IA Beneficial metabolic effects of regularmeal frequency on dietary thermogenesis insulin sensitivity and fasting lipid pro-files in healthy obese women Am J Clin Nutr 20058116ndash24

72 Farshchi HR Taylor MA Macdonald IA Decreased thermic effect of food after anirregular compared with a regular meal pattern in healthy lean women Int J ObesRelat Metab Disord 200428653ndash660

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