Effect of short- and long-term protein consumption on appetite and appetite-regulating gastrointestinal hormones, a systematic review and meta-analysis of randomized controlled trials

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Physiology & Behavior

journal homepage: www.elsevier.com/locate/physbeh

Eﬀect of short- and long-term protein consumption on appetite and appetite-

regulating gastrointestinal hormones, a systematic review and meta-analysis

of randomized controlled trials

Ali Kohanmoo, Shiva Faghih, Masoumeh Akhlaghi

⁎

Department of Community Nutrition, School of Nutrition and Food Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

ARTICLE INFO

Keywords:

Protein

Appetite

Hunger

Satiety

Ghrelin

Cholecystokinin

Glucagon-like peptide-1

ABSTRACT

Aim: High-protein diets are considered as useful diets for weight loss programs. We collected randomized

controlled trials that evaluated the eﬀect of protein on appetite and gastrointestinal hormones involved in ap-

petite regulation.

Methods: Trials were included if participants were healthy adults and isocaloric treatments were used in

control and treatment arms. Random-eﬀects model was used to calculate mean diﬀerence and 95% conﬁdence

intervals.

Results: In total, 49 publications for acute and 19 articles for long-term eﬀect of protein were included. In

acute interventions, protein decreased hunger (-7 mm visual analogue scale (VAS), P<0.001), desire to eat

(-5 mm, P = 0.045), and prospective food consumption (-5 mm, P = 0.001) and increased fullness (10 mm,

P<0.001) and satiety (4 mm, P<0.001). There was also a decrease in ghrelin (-20 pg/ml, P<0.001) and in-

crease in cholecystokinin (30 pg/ml, P<0.001) and glucagon-like peptide-1 (GLP-1) (21 ng/ml, P<0.001), but

no change in gastric inhibitory polypeptide and peptide YY was observed. Appetite markers were aﬀected by

protein doses < 35 g but ghrelin, cholecystokinin, and GLP-1 changed signiﬁcantly after doses ≥ 35 g. Long-

term ingestion of protein did not aﬀect these outcomes, except for GLP-1 which showed a signiﬁcant decrease.

Conclusion: Results of this meta-analysis showed that acute ingestion of protein suppresses appetite, decreases

ghrelin, and augments cholecystokinin and GLP-1. Results of long-term trials are inconclusive and further trials

are required before a clear and sound conclusion on these trials could be made.

1. Introduction

After decades of combat against obesity, obesity is still an important

health concern around the world [1]. Since a number of obesity cases

occur due to overeating, proper regulation of appetite may help in

weight management programs as demonstrated by a recent meta-ana-

lysis [2]. Appetite is the desire or motivation to eat food. Appetite is

determined by two contradictory feelings of satiety and hunger [3].

These feelings play important roles in controlling the amount of food

and energy consumption and thus managing body weight [4]. Hence,

appetite can be considered as a promising target for prevention and

treatment of obesity.

The gut-brain axis is a bidirectional communication route between

gastrointestinal tract and brain [5, 6]. One of the gut communications is

exerted by gut endocrine system which induces neural circuits in hy-

pothalamus and brainstem to regulate appetite and control feeding

behavior. These hormones are secreted following sensing the presence

(or absence) of macronutrients in the gastrointestinal tract. There are

two major types of gastrointestinal hormones: orexigenic such as

ghrelin and anorexigenic such as cholecystokinin (CCK) [5, 6].

For decades, high-protein diets have been used in weight loss pro-

grams [7, 8]. In fact, the role of protein in suppression of appetite has

been put forward as a potential explanation for the high prevalence of

obesity (especially among low-income populations) and also as a

strategy for its treatment [9]. In addition, there is a protein leverage

hypothesis which states that human body prioritizes protein over car-

bohydrate and fat [9]. According to this hypothesis, if a diet lacks

suﬃcient protein, then the consumption of food increases in an attempt

to obtain higher amount of protein from food, leading to overeating and

increased risk of obesity [10]. In contrast, high-protein foods meet body

protein needs and decline energy intake.

A number of clinical trials have investigated the eﬀect of protein

https://doi.org/10.1016/j.physbeh.2020.113123

Received 8 April 2020; Received in revised form 2 August 2020; Accepted 3 August 2020

⁎

Corresponding author.

E-mail address: [email protected] (M. Akhlaghi).

Physiology & Behavior 226 (2020) 113123

Available online 05 August 2020

consumption on appetite sensations as well as appetite-regulating

hormones. Here, we evaluated the eﬀect of protein ingestion on appe-

tite markers and a number of gastrointestinal hormones involved in

appetite regulation. In addition, we performed an extensive subgroup

analysis based on sex and BMI of participants as well of dose, protein

source, and placebo type. We further questioned if the eﬀect of protein

on the assessed outcomes diﬀers between short and longer term protein

intake.

2. Methods

2.1. Search

PubMed, Scopus, and Embase were searched to ﬁnd articles related

to the eﬀect of protein on appetite markers and gastrointestinal hor-

mones involved in appetite regulation. The search was performed from

the earliest available date until September 2019. No limitation on

language was made. Search terms included appetite, satiety, satiation,

fullness, hunger, ghrelin, cholecystokinin (CCK), glucagon-like peptide-

1 (GLP-1), gastric inhibitory polypeptide (GIP), incretins, and peptide

YY (PYY). These hormones are the mostly recognized gastrointestinal

hormones involved in appetite regulation [ 11, 12]. Screening the li-

brary, reading the articles, and extraction of the data was performed by

two independent investigators.

2.2. Eligibility criteria

Randomized controlled trials were included if the following criteria

were met: 1) healthy subjects; 2) adult ages; and 3) isocaloric treat-

ments in control and treatment arms. Both acute (i.e. short-term) and

long-term (3 days to 9 months) trials were included. Acute trials were

those in which the eﬀect of protein was determined within few hours

(< 5.5 h) after protein consumption whereas in long-term trials the

intervention period was between 3 days to 9 months. Trials were ex-

cluded in the case of any of the following situations: 1) participants

involved in diseases or medical conditions such as diabetes, glucose

intolerance, kidney failure, cancer, protein-energy malnutrition, sar-

copenia, anorexia, bulimia, and carbohydrate craving; 2) ad libitum (or

uncontrolled) consumption of protein supplements or protein meals; 3)

high-protein ketogenic diets; 4) treatments combined with exercise; 5)

protein treatments mixed with ﬁber; 6) examining proteins with unu-

sual amino acid content, for instance, proteins enriched with speciﬁc

amino acids such as leucine; 7) non-isocaloric control or control with

the same amount of protein as treatment arm; 8) insuﬃcient informa-

tion for the time of measurements in long-term interventions; 9) re-

porting mean change in appetite markers throughout a day or over a

number of days instead of reporting them at speciﬁc time points after a

test meal; 10) expressing data as area under the curve instead of linear

curve or instead of actual values at speciﬁc post-treatment time points;

11) insuﬃcient information for the macronutrient composition of the

diets or test meals or mean and standard deviation (SD) of the data; 12)

repeated publications.

2.3. Outcomes

Investigated outcomes included hunger, fullness, satiety, desire to

eat, and prospective food consumption as markers of appetite, and

ghrelin, CCK, GLP-1, GIP, and PYY as gastrointestinal hormones in-

volved in appetite regulation.

2.4. Data extraction

Mean and SD (or SE) of the data were collected in Excel sheets. Most

articles reported the outcomes at diﬀerent time points after ingestion of

a test meal in the form of linear graphs. The 3 h post-treatment was

recognized and used as the most common post-intervention time point

measured but in studies with shorter post-treatment duration, the

nearest time point to the 3 h was used. The values of linear graphs were

quantiﬁed by Plot Digitizer software version 2.6.6 (Free Software

Foundation Inc., USA).

2.5. Statistical analysis

Mean and SD of the diﬀerence between pre- and post-intervention

data was used to calculate pooled eﬀects. The random-eﬀects inverse-

variance model was used to obtain weighted mean di

ﬀerence

and 95%

conﬁdence interval (CI). Between-study heterogeneity was evaluated

using Cochrane χ

test and I

. Publication bias was determined by

Egger's test [13]. Subgroup analysis was performed based on partici-

pants’ body mass index (BMI) (lean (< 25 kg/m

), overweight and

obese (≥ 25 kg/m

), or both), protein dose (< 35 g/day vs. ≥ 35 g/

day), protein source (whey, casein (or dairy, milk, yogurt), meats/egg

(veal, turkey, egg), vegetable (soy, wheat, gluten, pea), or mixed), and

control type (carbohydrate, fat, or both). The cutoﬀ point for protein

dose was chosen according to the median of doses used in the trials.

STATA software version 12.0 (StataCorp, USA) was used for data ana-

lysis. The trim-and-ﬁll analysis was used to adjust any signiﬁcant

publication bias detected. P < 0.05 was considered statistically sig-

niﬁcant.

3. Results

Following the search of the databases, 8862 articles were found, of

which 3805 were duplicates and excluded, the rest were screened, and

at last 325 full texts were assessed according to the eligibility criteria

described in the Methods (Supplemental Figure 1). Of these, 257 arti-

cles were excluded due to reasons described in Fig. 1 and 68 passed the

eligibility stage and entered in the meta-analysis: 49 publications in-

vestigated acute eﬀect of protein and 19 articles conducted long-term

interventions. A total of 2740 and 1159 subjects participated in the

acute and long-term interventions, respectively. Except 2 trials which

had a parallel design, acute interventions had either a crossover or a

within-subject design, meaning that all their participants experienced

both treatment and control conditions. Long-term interventions were

conducted in both parallel and crossover design. Characteristics of the

short- and long-term trials are outlined in Supplemental Tables 1 and 2,

respectively.

Among acute interventions, 13 trials had multiple arms based on

various protein sources [14, 21, 28, 32, 36, 40 , 41], protein doses [16,

18, 19], or divergent participants [22, 23, 38]. These studies were cited

more than once. Likewise, among long-term interventions 6 trials were

cited more than once due to using diﬀerent proteins [45, 48, 50, 51]

and diﬀerent doses [44, 47].

In acute interventions, trials reported the outcomes at diﬀerent

times following protein load but 3 h was the mostly used time point. In

longer trials, the length of the intervention varied between 3 days and 9

months. Parameters of interest were measured either in fasting state,

pre- and post- protein ingestion, or at a speci ﬁc time point during the

day of measurement.

Whey protein was the mostly examined protein but there were also

reports on protein from other sources such as casein, milk, yogurt, soy,

beef, turkey, and egg. According to the inclusion criteria, it was ne-

cessary for the control group to be isocaloric with the treatment.

Although some control meals contained protein but extra protein in the

treatment group needed to be substituted with fat or carbohydrate in

control in order to have isocaloric intakes in both groups. The actual

dose of protein was calculated from subtraction of protein in the

treatment and control groups (Supplemental Tables 1 and 2). The actual

protein dose varied from 8.5 g to about 130 g per day.

Among 49 acute interventions, 28, 23, 18, 15, and 11 trials assessed

hunger, fullness, desire to eat, prospective food consumption, and sa-

tiety, and 25, 15, 25, 12, and 11 trials examined ghrelin, CCK, GLP-1,

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

GIP, and PYY respectively. Also, among 19 long interventions, 13, 13, 6,

4, and 8 studies assessed hunger, fullness, desire to eat, prospective

food consumption, and satiety, and 6, 1, 6, 1, and 6 trials determined

ghrelin, CCK, GLP-1, GIP, and PYY, respectively.

4. Acute interventions

Hunger, fullness, desire to eat, prospective food consumption, and

satiety were the commonly assessed markers of appetite. The method of

assessment was visual analogue scale (VAS) which is a tool that rates

the perception of a sensation or feeling on a 100-mm horizontal line.

This line is anchored at the ends by words that deﬁne bounds of the

sensation.

Estimated pooled eﬀects showed signiﬁcant decrease in hunger

(−7; 95% CI: −11, −3 mm; P < 0.001; n = 28) (Fig. 1), desire to eat

(−5; 95% CI: −11, −0.1 mm; P = 0.045; n = 18) (Table 1), and

prospective food consumption (−5; 95% CI: −8, −2 mm; P = 0.001;

n = 15) (Table 1) and signiﬁcant increase in fullness (10; 95% CI: 5,

14 mm; P < 0.001; n = 23) (Fig. 2) and satiety (4; 95% CI: 2, 6 mm; P

< 0.001; n = 11) (Table 1) following consumption of protein. Also,

there was a signiﬁcant decrease in ghrelin (−20; 95% CI: −29, −12

pg/ml; P < 0.001; n = 25) (Fig. 3), signiﬁcant increase in CCK (30;

95% CI: 17, 43 pg/ml; P < 0.001; n = 15) (Fig. 4) and GLP-1 (21; 95%

CI: 13, 29 ng/ml; P < 0.001; n

= 25) (Fig.

5), and no change in GIP

(−2; 95% CI: −32, 28 ng/ml; P = 0.891; n = 12) (Table 1) and PYY

(3; 95% CI: −24, 30 ng/ml; P = 0.817; n = 11). There was a high

heterogeneity in the ﬁndings in all of the outcomes except for satiety

= 0), ranging from 69.7% to 98.4% (P < 0.001) (Table 1).

5. Long-term interventions

In long-term interventions, protein did not have a signiﬁcant eﬀect

on hunger (P = 0.077; n = 13), fullness (P = 0.165; n = 13), desire to

eat (P = 0.676; n = 6), prospective food consumption (P = 0.210;

n = 4), satiety (P = 0.213; n = 8), ghrelin (P = 0.535; n = 6), and PYY

(P = 0.256; n = 6), but GLP-1 decreased signiﬁcantly (−7; 95% CI:

−1.2, −0.02 ng/ml; P = 0.008; n =6)(Table 1). CCK and GIP were

assessed in only one trial. Except for ghrelin (I

= 12.5%; P = 0.335),

the results for other parameters had high heterogeneity ranging from

70.6% to 95.5% (P < 0.05).

6. Subgroup analysis for acute interventions

Subgroup analysis based on participants’ BMI and sex, source and

dose of protein, and placebo type is shown in Table 2 (for briefness only

data of hunger, fullness, ghrelin, CCK, GLP-1, and GIP have been

shown). In the dose subgroups, appetite markers were aﬀected by

protein doses < 35 g but ghrelin, CCK, and GLP-1 changed signiﬁcantly

by doses ≥ 35 g; although less substantial but still signiﬁcant alteration

was also observed in ghrelin in doses of < 35 g protein (Table 2). In the

placebo subgroups, protein decreased hunger and ghrelin and increased

fullness, CCK, GLP-1, and PYY compared to carbohydrate (data not

shown for PYY). In some outcomes (fullness, CCK, GIP, and PYY), the

number of trials with fat placebo was insuﬃcient to allow making an

accurate conclusion. Similarly, subgroup analysis based on protein

source was not useful because of limited number of trials in protein

sources other than whey. Whey was the most frequently examined

protein for appetite investigations. In the whey subgroup, a signiﬁcant

Fig. 1. Forest plot of clinical trials examining the eﬀect of protein intake on the sensation of hunger in acute interventions. Data are presented as mean diﬀerence

between treatment and control groups with 95% CIs.

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

reduction was observed in hunger and ghrelin and a signiﬁcant increase

was observed in fullness and GLP-1 following protein consumption, but

no eﬀect was observed on CCK, GIP, and PYY. Results of subgroup

analysis based on sex showed that protein intake reduced hunger and

increased fullness in both males and females but ghrelin was decreased

and CCK was increased only in males. The number of trials with females

was merely 2 for CCK and GLP-1 and no signiﬁcant eﬀect was observed

for females in these outcomes. Likewise, subgroup analysis based on

BMI was not successful because there were not enough trials in over-

weight/obese subgroup (Table 2).

7. Publication bias

Publication bias was detected for hunger (Egger's test P = 0.02),

ghrelin (Egger's test P = 0.01), and CCK (Egger's test P = 0.04) in

short-term trials but there was no bias in long-term interventions. Trim-

Table. 1

Pooled eﬀect of protein on markers and hormones involved in appetite regulation in trials with short- and long-term interventions

Outcomes Studies (n) Mean diﬀerence (95% CI)* P value Heterogeneity P for heterogeneity

Acute eﬀects

Desire to eat (mm) 18 −5(−11, −0.1) 0.045 97.7% < 0.001

Prospective food consumption (mm) 15 −5(−8, −2) 0.001 67.4% < 0.001

Satiety (mm) 11 4 ([2], [6]) < 0.001 0% 0.54

GIP (ng/ml) 12 −2(−32, 28) 0.891 95.2% < 0.001

PYY (ng/ml) 11 3 (−24, 30) 0.817 95.6% < 0.001

Long-term eﬀects

Hunger (mm) 13 5 (−0.5, 10) 0.077 85.8% < 0.001

Fullness (mm) 13 3 (−1, 8) 0.165 87.9% < 0.001

Desire to eat (mm) 6 −2(−9, 6) 0.676 78.1% < 0.001

Prospective food consumption (mm) 4 −11 (−28, 6) 0.210 95.5% < 0.001

Satiety (mm) 8 3 (−2, 8) 0.213 79.5% < 0.001

Ghrelin (pg/ml) 6 0.4 (−1, 2) 0.535 12.5% 0.335

CCK (pg/ml) 1 −0.03 (−0.2, 0.1) 0.540 ––

GLP-1 (ng/ml) 6 −0.7 (−1.2, −0.02) 0.008 77.4% <0.001

GIP (ng/ml) 1 13 (−23, 48) 0.494 ––

PYY (ng/ml) 6 −3(−8, 2) 0.256 70.6% 0.004

1 Mean diﬀerence and its standard deviation (SD) of control and intervention groups were used to calculate pooled eﬀects (expressed as mean diﬀerence and 95%

conﬁdence interval). Statistical heterogeneity was assessed by I

test using random inverse-variance heterogeneity. CI: conﬁdence interval.

Fig. 2. Forest plot of clinical trials examining the eﬀect of protein intake on the sensation of fullness in acute interventions. Data are presented as mean diﬀerence

between treatment and control groups with 95% CIs.

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

Fig. 3. Forest plot of clinical trials examining the eﬀect of protein on ghrelin concentration in acute interventions. Data are presented as mean diﬀerence between

treatment and control groups with 95% CIs.

Fig. 4. Forest plot of clinical trials examining the eﬀect of protein on CCK in acute interventions. Data are presented as mean diﬀerence between treatment and

control groups with 95% CIs.

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

and-ﬁll analysis did not change the results, suggesting that the pub-

lication bias did not remarkably aﬀect the results.

8. Discussion

Results of this meta-analysis showed that acute ingestion of protein

suppressed appetite as evidenced by decreased sensation of hunger,

desire to eat, and prospective food consumption, and increased fullness

and satiety. Protein intake also decreased ghrelin and increased CCK

and GLP-1 concentrations without aﬀecting GIP and PYY. Long-term

ingestion of protein did not signiﬁcantly a ﬀect these outcomes, except

for GLP-1 which showed a signiﬁcant decrease.

9. Acute interventions

Overall, appetite is estimated by questioning ﬁve feelings of hunger,

fullness, satiety, desire to eat, and prospective food consumption. Short-

term interventions, where appetite was evaluated during hours after

protein consumption, demonstrated suppression of appetite in all ﬁve

types of feeling, providing a strong evidence for appetite-suppressing

eﬀect of protein shortly after consumption. A number of mechanisms

have been suggested for this appetite suppression. Gut hormones in-

cluding ghrelin, CCK, GLP-1, GIP, and PYY may play a role in this

suppression [12]. Except ghrelin which is an orexigenic peptide that

promotes hunger, the other mentioned gastrointestinal hormones are

suggested to induce satiety. Cell culture studies have shown that pro-

ducts of protein digestion may induce signaling pathways involved in

synthesis or secretion of the aforementioned gastrointestinal hormones

[52]. For instance, CCK arouses vagus nerve to convey signals to the

brain, activating noradrenergic satiety neurons in the solitary nucleus

while decreasing mRNA expression of the vagal receptor of orexin-1 in

nodose ganglion, inducing satiety while inhibiting the antagonist orexin

signaling [53, 54]. Of incretin hormones, GLP-1 may render satiating

eﬀect by delaying gastric emptying and stimulating insulin synthesis

and secretion [53] but GIP has not shown to delay gastric emptying

[55]. The satiating eﬀect of protein may also be mediated by me-

chanisms independent of the gut hormones. For instance, it has been

suggested that high blood concentration of amino acids, particularly

those that are not utilized for protein synthesis, may provoke satiety

signals [54] .

Results of this meta-analysis did not show the eﬀect of protein on

GIP and PYY. Previous studies using isocaloric meals have shown that

meals containing carbohydrate and fat induced substantial rises in in-

cretin hormones but protein had no eﬀect [56]. In this regard, Elliott

and colleagues studied circulating levels of GLP-1 and GIP following

consumption of isocaloric meals containing carbohydrate, fat, or pro-

tein [56]. They found that both GLP-1 and GIP were secreted following

consumption of carbohydrates and fat; although secretion occurred at

slower rate after fat than after carbohydrates. Protein also stimulated

GLP-1 section but GIP was not aﬀected by protein meals [56].

10. Subgroup analysis of acute interventions

10.1. Dose subgroups

Trials on the dose-dependent eﬀects of protein on appetite sensa-

tions and gastrointestinal hormones are quite conﬂicting. A number of

trials have supported a positive dose-response relationship between

dietary protein and appetite sensations and/or hormones [

27, 18]

while

others have denied such relationship [19, 16]. Results of this meta-

Fig. 5. Forest plot of clinical trials examining the eﬀect of protein on GLP-1 in acute interventions. Data are presented as mean diﬀerence between treatment and

control groups with 95% CIs.

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

Table. 2

Subgroup analysis based on participants’ BMI and sex, protein source and dose, and placebo for the eﬀect of protein on hunger, fullness, and concentrations of

appetite-regulating hormones in short-term interventions.

Subgroup

categorization

Studies (n) Mean diﬀerence (95%

CI)

P value I

P forI

Studies (n) Mean diﬀerence (95%

CI)

P value I

P for I

Hunger (mm) Fullness (mm)

BMI BMI

< 25 kg/m

22 −7(−11, −3) 0.001 96.4% < 0.001 < 25 kg/m

16 9 ([4], [15]) 0.001 97.4% < 0.001

≥ 25 kg/m

4 −7(−14, 1) 0.08 57.9% 0.07 ≥ 25 kg/m

410([4], [16]) 0.002 41.4% 0.16

Both 2 −7(−15, 1) 0.08 – 0.57 Both 2 14 ([2], [24] ) 0.02 55.6% 0.13

Sex Sex

Male 8 −8(−9, −7) < 0.001 0 0.82 Male 8 7 ([2], [11]) 0.003 53.9% 0.03

Female 5 −7(−14, −1) 0.03 64.8% 0.02 Female 3 9 (0.1, 17) 0.047 73.9% 0.02

Male/female 15 −7(−12, −3) 0.001 93.4% < 0.001 Male/female 11 12 ([7], [17] ) < 0.001 94.3% < 0.001

Protein source Protein source

Whey 18 −8(−12, −3) 0.001 95.9% < 0.001 Whey 15 9 ([3], [14]) 0.002 97.5% < 0.001

Casein/dairy 3 −10 (−21, 2) 0.10 84.3% 0.002 Casein/dairy 3 15 ([5], [24] ) 0.003 69.8% 0.04

Meat/egg 2 −8(−15, −2) 0.008 0 0.39 Meat/egg 2 13 ([7], [19] ) < 0.001 9.5% 0.29

Vegetable 3 −4(−9, 1) 0.12 0 0.70 Vegetable 2 8 ([2], [14]) 0.006 0 0.42

Mixed 2 −3(−5, −1) 0.01 0 0.53 Mixed –– –––

Protein dose Protein dose

<35g 16 −

9(−15, −3)

0.002 96.9% < 0.001 < 35 g 12 13 ([9], [17]) < 0.001 65.5% 0.001

≥ 35 g 12 −5(−11, 2) 0.16 94.0% < 0.001 ≥ 35 g 10 6 (−2, 15) 0.11 98.3% < 0.001

Placebo type Placebo type

CHO 23 −7(−11, −3) 0.001 95.3% < 0.001 CHO 21 9 ([5], [14]) < 0.001 96.5% < 0.001

Fat 4 −12 (−19, −4) 0.003 55.0% 0.08 Fat 1 22 ([10], [30]) < 0.001 ––

CHO/fat 1 −3(−5, −1) 0.01 –– CHO/fat –– –––

Ghrelin (pg/ml) CCK (pg/ml)

BMI BMI

< 25 kg/m

13 −20 (−33, −7) 0.002 85.7% < 0.001 < 25 kg/m

715([1], [26]) 0.04 93.5% < 0.001

≥ 25 kg/m

6 −4(−8, −0.4) 0.03 0 0.55 ≥ 25 kg/m

425(−36, 86) 0.42 92.1% < 0.001

Both 6 −57 (−81, −33) < 0.001 27.9% 0.22 Both 4 54 ([30], [47]) < 0.001 83.3% < 0.001

Sex Sex

Male 14 −42 (−62, −21) < 0.001 84.1% < 0.001 Male 11 21 ([2], [33]) 0.04 95.2% < 0.001

Female 3 6 (−51, 64) 0.84 60.5% < 0.001 Female 2 34 (−42, 110) 0.38 83.7% 0.01

Male/female 8 −2(−4, − 0.3) 0.02 0 0.69 Male/female 2 98 ([18], 178) 0.02 86.5% 0.006

Protein source Protein source

Whey 8 −29 (−48, −10) 0.003 90.5% < 0.001 Whey 7 7 (−7, 22) 0.30 93.9% < 0.001

Casein/dairy 1 −24 (−50, 2) 0.07 –– Casein/dairy 2 98 ([18], 178) 0.02 86.5% 0.006

Meat/egg 4 −39 (−60, −18) < 0.001 0 0.43 Meat/egg 2 44 ([7], [53]) 0.02 85.7% 0.008

Vegetable 3 −76 (−11, −46) < 0.001 0 0.46 Vegetable 2 63 ([39], [49]) < 0.001 0 1

Mixed 9 −7(−12, −1) 0.02 15.6% 0.30 Mixed 2 19 (−11, 48) 0.22 67.2% 0.08

Protein dose Protein dose

<35g 9 −7(−13, −2) 0.01 57.7% 0.01 < 35 g 5 21 (

−16,

58) 0.27 87.7% < 0.001

≥ 35 g 16 −29 (−50, −9) 0.006 83.5% < 0.001 ≥ 35 g 10 32 ([17], [37]) < 0.001 95.7% < 0.001

Placebo type Placebo type

CHO 17 −32 (−45, −18) < 0.001 84.3% < 0.001 CHO 14 37 ([23], [61]) < 0.001 94.4% < 0.001

Fat 7 −4(−14, 6) 0.42 43.0% 0.10 Fat 1 −93 (−130, −56) < 0.001 ––

CHO/fat 1 9 (−129, 146) 0.90 –– CHO/fat –– –––

GLP-1 (ng/ml) GIP (ng/ml)

BMI BMI

< 25 kg/m

12 11 ([2], [20]) 0.02 88.8% < 0.001 < 25 kg/m

89(−29, 47) 0.64 94.8% < 0.001

≥ 25 kg/m

444(−1, 90) 0.06 93.0% < 0.001 ≥ 25 kg/m

3 −15 (−60, 29) 0.50 90.2% < 0.001

Both 9 28 ([13], [35]) < 0.001 92.8% < 0.001 Both 1 −33 (−50, −17) < 0.001 ––

Sex Sex

Male 12 10 (−1, 20) 0.06 88.1% < 0.001 Male 7 −4(−44, 36) 0.84 97.0% < 0.001

Female 2 31 (−16, 79) 0.20 90.1% 0.001 Female 1 −25 (−145, 94) 0.68 ––

Male/female 11 30 ([19], [34]) < 0.001 86.2% < 0.001 Male/female 4 4 (−40, 48) 0.86 84.7% < 0.001

Protein source Protein source

Whey 11 10 (0.2, 19) 0.045 89.0% < 0.001 Whey 5 4 (−57, 65) 0.90 97.6% < 0.001

Casein/dairy 2 51 ([33], [43]) < 0.001 0 0.70 Casein/dairy 1 −36 (−55, −17) < 0.001 ––

Meat/egg 5 36 (−11, 83) 0.13 83.8% 0.01 Meat/egg 3 −8(−52, 37) 0.74 32.9 0.80

Vegetable 2 15 ([2], [25]) 0.02 71.7% 0.007 Vegetable 1 37 ([3], [46]) 0.03 ––

Mixed 5 37 ([13], [42]) 0.003 90.7% < 0.001 Mixed 2 −4(−86, 78) 0.93 94.4% < 0.001

Protein dose Protein dose

<35g 9 9(−4, 22) 0.17 75.0% < 0.001 < 35 g 5 12 (−14, 38) 0.37 86.6% < 0.001

≥ 35 g 16 26 ([16], [31]) < 0.001 91.6% < 0.001 ≥ 35 g 7 −18 (

−74,

38) 0.52 97.0% < 0.001

Placebo type Placebo type

CHO 20 25 ([16], [29]) < 0.001 93.3% < 0.001 CHO 10 6 (−27, 38) 0.73 95.4% < 0.001

Fat 5 −14 (−58, 29) 0.52 76.7% 0.002 Fat 2 −34 (−51, −18) < 0.001 0 0.44

CHO/fat –– –––CHO/fat –– –––

indicates between-study heterogeneity. CHO, carbohydrate.

A. Kohanmoo, et al.

Physiology & Behavior 226 (2020) 113123

analysis showed that appetite may be induced more eﬀectively by lower

doses of protein while appetite hormones including ghrelin, CCK, and

GLP-1 might be stimulated by higher doses. In agreement with our

results, King et al. reported that ingestion of a small dose of whey

protein immediately before meal increased satiety but could not induce

GLP-1, GIP, and PYY responses [57]. Also, Veldhorst and colleagues

reported that breakfasts with 25% energy from protein aﬀected ghrelin

and GLP-1 more eﬀectively than breakfasts with 10% energy from

protein [42].

10.2. Placebo subgroups

Protein decreased hunger and ghrelin and increased fullness, CCK,

GLP-1, and PYY compared to carbohydrate. We could not compare the

satiating eﬀect of protein with fat because there were only a few trials

with fat placebo. However, previous studies have found that protein has

a more pronounced eﬀect on suppressing appetite than fat [27]. In fact,

fat has been found the least satiating macronutrient which suppresses

hunger to a less extent than carbohydrate and particularly compared to

protein [27, 58 ].

10.3. Other subgroups

The eﬀect of various proteins on appetite markers have been com-

pared in a number trials. However, the results have been conﬂicting.

Some trials have found comparable subjective appetite ratings for

proteins from diﬀerent sources, for instance, from animal and plant

sources [28, 59], or from casein, soy and whey sources [41, 36]. But

there is also evidence for diﬀerent satiating eﬀect from various proteins.

For instance, Acheson et al. observed a higher satiating eﬀect from

casein and soy compared to whey [14]. Also, in a trial by Teunissen

et al. pea and milk proteins increased GLP-1 more than egg white

protein [40]. However, due to the paucity of data in some protein types,

subgroup analysis based on protein source did not give us much in-

formation for comparison of diﬀerent proteins. Whey was the mostly

examined protein which aﬀected appetite markers as well as ghrelin

and GLP-1. More trials need to be conducted on other protein sources,

including casein, meat, egg, and plant proteins.

Most of the trials were conducted on males; so subgroup analysis

produced unequal number of trials in sex subgroups. In spite of small

number of trials in females, protein demonstrated signiﬁcant eﬀect on

appetite markers in both males and females but the eﬀect of protein on

the gastrointestinal outcomes in women remained inconclusive.

Moreover, unequal number of trials did not allow us to estimate the

extent of the eﬀects on males and females [60]. In this regard, Gieze-

naar et al. reported that consumption of whey protein suppressed

hunger and increased CCK and GLP-1 concentrations in men more than

that in women [60],

suggesting that the satiating eﬀect of protein may

be stronger in men than in females.

Similar to protein source subgroups, subgroup analysis for BMI did

not produce useful results because most of the trials had been per-

formed on normal weight participants. Nevertheless, the few trials that

have compared the eﬀect of protein on appetite feelings found no dif-

ference in appetite suppression following protein intake between

normal weight and obese individuals [61, 59].

10.4. Long-term interventions

GLP-1 was the only outcome with signiﬁcant change over long-term

interventions. The lack of protein eﬀect on other outcomes including

appetite markers may be explained by diversity in the study design and

time of measurements in these trials compared to acute interventions.

For instance, in acute trials the parameters were measured pre- and

post- meal ingestion while in long-term interventions the time of

measurements diﬀered between trials, with some measuring the out-

comes pre- and post- protein ingestion and others measuring them at a

speciﬁc time point (for instance in fasting state or pre-lunch). Moreover,

the form of administered protein in long-term trials varied from diet to

snack or meals whereas in acute interventions protein was always ad-

ministered in the form of snacks, beverages, or meals. When protein is

administered in the form of diet, the satiating eﬀect of protein may not

be appropriately appeared. In this regard, Stubbs et al. reported that

breakfasts with high protein content led to detectable change in hunger

during hours between breakfast and lunch but the eﬀect was not of

suﬃcient magnitude to inﬂuence lunch-time intake [62] . In addition, in

long-term trials higher doses of protein were given with an average of

33.6 g/day compared to 9.3 g/day in acute interventions. Comparably,

higher doses have weaker eﬀect on appetite feelings but stronger eﬀect

on gastrointestinal hormones [57, 42]. The number of long-term trials

in each outcome was almost half of that of acute interventions and this

reason may also contribute to the lack of protein eﬀect in long-term

trials. These diﬀerences may explain the diﬀerence in the results of

short- and long-term trials.

10.5. Limitations

This was the ﬁrst meta-analysis investigating the eﬀect of protein on

gastrointestinal hormones involved in appetite regulation. However,

during meta-analysis we encountered several limitations. The number

of reports on some of the gastrointestinal hormones especially in long-

term investigations were limited. Likewise, there was insuﬃcient

number of trials in subgroups of protein source (e.g., meat, egg, and

vegetable protein), fat placebo, and subjects with BMI ≥ 25 kg/m

. Not

all studies speciﬁed the form of hormones that they examined or had

reported data on active form of hormones. The variability in the form of

hormones that were measured as well as the variability in the method of

measurement could also have inﬂuenced the results. The form of car-

bohydrates in studies that gave carbohydrates as placebo is also im-

portant. Moreover, the rate of absorption macronutrients can also aﬀect

secretion of gastrointestinal hormones like GLP-1 [56]. Long-term trials

encountered more diversities, for instance, in the time of measurements

and the form of protein administration (diet vs. supplement/meal).

10.6. Concluding remarks

According to the results of this meta-analysis acute ingestion of

protein suppresses appetite, decreases ghrelin, and augments CCK and

GLP-1. Due to numerous limitations, results of long-term trials are in-

conclusive and further well-designed and targeted trials are required

before a clear and sound conclusion could be made.

Supplementary materials

Supplementary material associated with this article can be found, in

the online version, at doi:10.1016/j.physbeh.2020.113123 .

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