Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis

Abstract

Objectives: In this study, we systematically synthesized scientific evidence on pork consumption in relation to body weight and composition among adults. Methods: We performed a keyword search using Cochrane Library, PubMed, Web of Science, CINAHL, and Google Scholar. We conducted a meta-analysis to estimate the pooled effect size of pork consumption on body weight and composition. Results: Overall, 12 studies met the eligibility criteria for inclusion in the review. Among the experimental studies without daily total energy intake restrictions, pork intake was associated with a reduction in body weight by 0.86 kg (95% CI = 0.17-1.55) and body fat percentage by 0.77% (95% CI = 0.11%-1.43%); pork intake was not associated with change in lean mass. Among the experimental studies with energy restrictions, pork intake was associated with a reduction in body weight by 5.56 kg (95% CI = 0.55-10.59), lean mass by 1.50 kg (95% CI = 1.39-1.62), and fat mass by 6.60 kg (95% CI = 6.42-6.79). Among the observational studies, pork intake was not associated with overweight/obesity. Conclusions: Findings on pork consumption in relation to body weight/composition differed by study design. Future experimental studies using representative samples are warranted to examine the effect of fresh/lean pork consumption on body weight and composition in the general population and by subgroups.

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Am J Health Behav.™ 2020;44(4):513-525 513
Obesity is a leading public health concern
in the United States (US) and worldwide.1
Over the past few decades, the obesity
prevalence more than doubled among US adults.2,3
According to the World Health Organization, ap-
proximately 1.9 billion adults worldwide are over-
weight, and of these, 650 million are obese.4
Pork is an essential food in the US and many
other countries.5 e annual global pork consump-
tion is at approximately 118 metric kilotons, with
consumption in China occupying about 46%.5
Many of the European Union member states have
high levels of pork consumption, such as Austria
and Germany (51-52 kg per capita/year), Spain (49
kg per capita/year), Poland (46 kg per capita/year),
Italy (40 kg per capita/year), the Netherlands (36
kg per capita/year), and France (33 kg per capita/
year).5 In the US, pork ranks third in annual meat
consumption, behind beef and chicken.6 Between
2014 and 2016, US adults averaged 23 kg of pork
consumption a year, accounting for over one-fourth
of overall meat intake.6 Given that pork is generally
less expensive and more aordable than beef, pork
sometimes serves as an alternative to beef among
red meat consumers.7,8
Pork is rich in protein and other essential nu-
trients such as iron, zinc, and several B vitamins.9
Protein intake is thought to be eective for body
weight management, in that it promotes satiety
and energy expenditure, and modies body com-
Ruopeng An, Assistant Professor, Brown School of Social Work, Washington University, St. Louis, MO. Jianxiu Liu and Ruidong Liu, Department of
Physical Education, Tsinghua University, Beijing, China.
Correspondence Mrs Liu; liujianx17@mails.tsinghua.edu.cn
Pork Consumption in Relation to Body
Weight and Composition: A Systematic
Review and Meta-analysis
Ruopeng An, PhD
Jianxiu Liu, MS
Ruidong Liu, MS
Objectives: In this study, we systematically synthesized scientic evidence on pork consump-
tion in relation to body weight and composition among adults. Methods: We performed a key-
word search using Cochrane Library, PubMed, Web of Science, CINAHL, and Google Scholar.
We conducted a meta-analysis to estimate the pooled eect size of pork consumption on body
weight and composition. Results: Overall, 12 studies met the eligibility criteria for inclusion in
the review. Among the experimental studies without daily total energy intake restrictions, pork
intake was associated with a reduction in body weight by 0.86 kg (95% CI = 0.17-1.55) and body
fat percentage by 0.77% (95% CI = 0.11%-1.43%); pork intake was not associated with change in
lean mass. Among the experimental studies with energy restrictions, pork intake was associated
with a reduction in body weight by 5.56 kg (95% CI = 0.55-10.59), lean mass by 1.50 kg (95% CI =
1.39-1.62), and fat mass by 6.60 kg (95% CI = 6.42-6.79). Among the observational studies, pork
intake was not associated with overweight/obesity. Conclusions: Findings on pork consumption
in relation to body weight/composition diered by study design. Future experimental studies
using representative samples are warranted to examine the eect of fresh/lean pork consump-
tion on body weight and composition in the general population and by subgroups.
Key words: pork; body weight; obesity; body composition; review; meta-analysis
Am J Health Behav.™ 2020;44(4):513-525
DOI: https://doi.org/10.5993/AJHB.44.4.12

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Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis
514
position in favor of lean mass.10 A systematic review
and meta-analysis of 20 randomized controlled tri-
als assessed the eects of protein intake on energy
restriction-induced changes in body mass, lean
mass, and fat mass in adults aged 50 years and old-
er.11 Study participants were found to retain more
lean mass and lose more fat mass when consuming
higher protein diets.11
Some observational studies found that red meat
consumption was associated with elevated risks for
obesity, type 2 diabetes, and cardiovascular dis-
ease.12,13 ese discrepancies between experimental
and observational studies may a result of at least 3
discrepancies. First, fresh/lean meat, which is high
in protein but low in saturated fat, is widely ad-
opted in clinical trials,11 whereas a signicant pro-
portion of daily meat consumption in the general
population consists of processed meat, which is
high in saturated fat, sodium, and other unhealthy
substance (eg, trans fat).14,15 Pork is a food of com-
plex nutrient composition, and the health implica-
tions of pork consumption are further complicated
by pork processing/cooking methods.16 On the
one hand, fresh/lean pork consumers are found to
have comparable daily fat and saturated fat intake
compared to non-consumers, suggesting that un-
processed fresh/lean pork can be part of a healthy
diet.7,8,17 On the other hand, processed meat con-
sumption was documented to link to higher dis-
ease incidences (eg, diabetes and certain cancer
types).18,19 Second, experimental studies may either
restrict or not restrict daily total energy intake,11
whereas observational studies mostly do not have
any restriction on daily energy intake (except when
study participants self-selected to be on a diet).20
From an energy balance perspective, being with
and without daily total energy consumption re-
striction may have rather dierent implications for
the change in body weight and composition.21,22
ird, in comparison to experimental studies, ob-
servational studies are more likely to be subject to
selection bias due to lacking randomization, so that
the estimated associations may not infer causality.23
In this study, we aimed at systematic identica-
tion and synthesis of the scientic evidence on pork
consumption in relation to body weight and com-
position. is study contributes to the literature
in 3 ways. First, this review serves as the rst at-
tempt to document and summarize study ndings
pertaining to the eect of pork intake on weight-
related outcomes. Whereas the vast majority of
nutritional epidemiologic studies focus on the rela-
tionship between individual nutrients (eg, protein,
iron, zinc, and multiple B vitamins) and weight-
related outcomes,24,25 there is a dearth of studies
that assess the overall impact of pork consumption.
Second, this review covers a wide range of study de-
signs from controlled experiments to observational
studies and contrasts their ndings.Importantly, in
light of the potentially heterogeneous health impli-
cations of pork consumption by type and process-
ing/cooking method, we summarize and synthesize
quantitatively (using meta-analysis) the studies by
research design. is is because experimental stud-
ies largely use unprocessed fresh/lean pork in their
interventions,11 whereas observational studies typi-
cally reect a wider variety of pork products, both
unprocessed (eg, tenderloin) and processed (eg, ba-
con).14,15 Arguably, categorization by study design
may not fully address the potentially dierential
impact of pork consumption on weight and body
composition as the total number of original stud-
ies remains limited and most observational studies
combine dierent pork products together. Nev-
ertheless, we believe that such categorization can
provide more informative and content-specic in-
sights on the relationship between pork consump-
tion and body composition. Finally, ndings from
this review may shed light on pork-related dietary
recommendations and inform future studies to ad-
vance research on pork consumption in relation to
weight and body composition.
Methods
Study Selection Criteria
We included in the review studies that met all
of the following criteria: (1) Study designs: experi-
mental and observational studies; (2) Study partici-
pants: adults aged 18 years and older; (3) Exposure:
pork consumption; (4) Outcomes: body weight
and composition; (5) Article type: peer-reviewed
publications; (6) Time window of search: from the
inception of an electronic bibliographic database to
August 15, 2019; and (7) Language: articles writ-
ten in English.
We excluded studies that met any of the follow-
ing criteria: (1) studies that incorporated no out-
come pertaining to pork consumption in relation

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An et al
Am J Health Behav.™ 2020;44(4):513-525 515 DOI: https://doi.org/10.5993/AJHB.44.4.12
to body weight and/or composition; (2) studies
that examined the inuence of overall red meat
consumption or certain dietary patterns (eg, Medi-
terranean diet) on body weight and/or composi-
tion without dierentiating the independent eect
of pork consumption; (3) studies that exclusively
focused on children and adolescents aged 17 years
and younger; (4) letters, editorials, study protocols,
conference proceedings, books, or review articles;
and (5) articles not written in English.
Search Strategy
We performed a keyword search in 5 electron-
ic bibliographic databases: Cochrane Library,
PubMed, Web of Science, Cumulative Index
of Nursing and Allied Health (CINAHL), and
Google Scholar. e search algorithm included all
possible combinations of keywords from the fol-
lowing 2 groups: (1) “pork” and (2) “body com-
position,” “obesity,” “obese,” “adiposity,” “adipose,”
“overweight,” “weight,” “body weight,” “body
mass,” “BMI,” “skinfold thickness,” “waist cir-
cumference,” “WC,” “hip circumference,” “HC,”
“waist/hip ratio,” “WHR,” “waist-hip ratio,” “waist
to hip,” “waist-to-hip,” “lean mass,” “abdominal,”
“lean body,” “fat,” “muscle mass,” or “anthropo-
metric.” e MeSH terms “body composition,”
“obesity,” “overweight,” “body weight,” “body mass
index,” “skinfold thickness,” “waist circumference,”
and “waist-hip ratio” were included in the PubMed
search. All keywords in PubMed were searched
with the “(All elds)” tag, which are processed us-
ing Automatic Term Mapping. e search func-
tion TS = Topic was used in Web of Science, which
launches a search for topic terms in the elds of
title, abstract, keywords, and Keywords Plus®. e
search algorithm in PubMed is provided in Appen-
dix A. Titles and abstracts of the articles identied
through the keyword search were screened against
the study selection criteria. Potentially relevant arti-
cles were retrieved for an evaluation of the full text.
Two co-authors independently conducted the title
and abstract screening and identied potentially
relevant articles for the full-text review. Inter-rater
agreement was assessed using Cohen’s kappa (κ =
0.87). Discrepancies were resolved through face-
to-face discussions between the 2 co-authors. Arti-
cles identied from the title and abstract screening
were reviewed in full texts. e 2 co-authors jointly
determined the nal pool of articles included in the
review.
Data Extraction and Synthesis
A standardized data extraction form was used to
collect methodological and outcome variables from
each selected study, including authors, publication
year, country, sample size, sample age distribu-
tion, sample sex distribution, sample weight status,
study design, body weight/composition outcome
and measure, number of repeated measures, sta-
tistical model, attrition rate, and main study re-
sults and ndings. One co-author developed and
pilot-tested the data extraction form based on 3
studies (one each from experimental, longitudi-
nal, and cross-sectional study designs), and subse-
quently 2 co-authors independently extracted data
from individual studies using the data extraction
form. Afterwards, the 2 co-authors compared their
data extraction results and resolved discrepancies
through discussion.
Meta-analysis
We performed a meta-analysis to estimate the
pooled eect size of pork consumption on body
weight and composition. e outcomes included
body weight, overweight status, obesity status, fat
mass, body fat percentage, and lean mass. A total of
8 studies were included in the meta-analysis. Four
articles were excluded from the meta-analysis due
to the following 2 reasons: less than 2 studies re-
ported the same outcome,26-28 and neither standard
error nor condence interval (CI) was reported.29
Separate meta-analysis was performed on the ex-
perimental studies with overall daily energy intake
restrictions, those without restrictions, and obser-
vational studies. Eorts were made to group studies
that used the same weight and body composition
measure and adopted similar intervention condi-
tion (ie, either with or without daily total energy
intake restriction), with the aim of reducing study
heterogeneity. Study heterogeneity was assessed us-
ing the I2 index. e level of heterogeneity repre-
sented by I2 was interpreted as modest (I2 ≤ 25%),
moderate (25% < I2 ≤ 50%), substantial (50% < I2
≤ 75%) or considerable (I2 > 75%). A xed-eect
model was estimated when modest or moderate
heterogeneity was present, and a random-eect
model was estimated when substantial or consider-

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Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis
516
able heterogeneity was present. We used Begg’s and
Egger’s tests to assess publication bias. All statistical
analyses were conducted using Stata 16.1 MP ver-
sion (StataCorp, College Station, TX). All analyses
used 2-sided tests, and p-values less than .05 were
considered statistically signicant.
Study Quality Assessment
Given the diverse study designs included in this
review (ie, experimental, longitudinal, and cross-
sectional studies), the study quality and risk/bias
assessment tools developed by the National Insti-
tutes of Health or Cochrane Collaboration could
fully address our needs.30,31 erefore, adapting
from a few previously developed quality assessment
tools that proved suitable to cover a wide range of
study designs,32,33 we constructed and applied a
study quality assessment tool that rates each study
based on the following 8 questions: (1) Was the re-
search question or objective clearly stated? (2) Was
the study population clearly specied? (3) Was the
Records identified through database
searching
(N = 1259)
Screening
Included
Eligibility
Identification
Additional records identified
through other sources
(N = 6)
Records after duplicates removed
(N = 1172)
Records screened
(N = 1172)
Records excluded
(N = 1147)
Full-text articles assessed
for eligibility
(N = 25)
Full-text articles excluded,
with reasons
(N = 13)
Studies included in
qualitative synthesis
(N = 12)
Studies included in
quantitative synthesis
(meta-analysis)
(N = 8)
Figure 1
Study Selection Flow Diagram

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Am J Health Behav.™ 2020;44(4):513-525 517 DOI: https://doi.org/10.5993/AJHB.44.4.12
study a randomized controlled trial? (4) Was a sam-
ple size justication (eg, power analysis) provided?
(5) Were pork consumption measures clearly de-
ned, valid, reliable, and implemented consistently
across all study participants? (6) Were body weight
and/or body composition assessed more than once
over time? (7) Were body weight and/or body com-
position objectively measured? (8) Were the out-
come assessors blinded to the exposure status of
participants? For each criterion, a score of 1 was
assigned if “yes” was the response, whereas a score
of 0 was assigned otherwise. A study-specic global
score ranging from 0 to 8 was calculated by sum-
ming up scores across all criteria. e study quality
assessment measured the strength of scientic evi-
dence but was not used to determine the inclusion
of studies. Two co-authors independently rated/
scored all included articles based on the quality
assessment tool, and compared their results. Dis-
crepancies were resolved through discussion, and
when a mutual agreement failed to emerge, the
nal decision was made in consultation with the
third co-author.
RESULTS
Study Selection
Figure 1 shows the study selection ow diagram.
We identied a total of 1265 articles through the
keyword and reference search. After removing du-
plicates, 1172 unique articles underwent title and
abstract screening, in which 1147 articles were ex-
cluded. Full texts of the remaining 25 articles were
reviewed against the study selection criteria. Of
these, 13 articles were excluded. ere were sev-
eral reasons for exclusion: 9 articles did not mea-
sure body weight or composition,34-42 2 articles
did not include pork consumption,43,44 one article
Table 1
Basic Characteristics of the Studies Included in the Review
Study
ID
First Author
(year) Country Sample
size Age Female
(%) Age group Study design Attrition
(%)
1Mikkelsen
(2000)46 Denmark 12 26 0 Young men Randomized cross-over trial 0
2Leidy
(2007)47 USA 46 50 100 Women RCT 15
3Brunt
(2018)48 Canada 557 21 60.3 Young adults Cross-sectional study /
4Campbell
(2010)49 USA 28 >20 100 Women RCT 15
5Verbeke
(2011)50
Belgium,
Denmark,
Germany, and
Poland
1931 20-70 51 Adults Cross-sectional study /
6Gilsing
(2012)27 Netherlands 3902 55-69 49 Older Adults Longitudinal study /
7Murphy
(2012)51 Australia 164 18-65 / Adults RCT 12
8Murphy
(2014)52 Australia 49 50 51 Adults Randomized cross-over trial 23
9Sayer
(2015)26 USA 19 61 68 Adults RCT 32
10 Zou
(2015)53 China 5577 53 64 Adults Cross-sectional study /
11 Charlton
(2016)54 Australia 48 ≥65 65 Older Adults RCT 35
12 Kim
(2018)55 USA 29145 ≥20 / Adults Cross-sectional study /

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Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis
518
was a review,45 and the remaining one exclusively
recruited children.28 We included the remaining
12 articles examining pork consumption in rela-
tion to body weight and composition in the re-
view,26,27,46-55 of which 8 were further included in
the meta-analysis.46-52
Basic Characteristics of the Included Studies
Table 1 summarizes the basic characteristics of
the 12 articles, including 5 randomized controlled
trials,26,47,49,51,54 2 randomized crossover trials,46,52 4
cross-sectional studies,48,50,53,55 and one longitudinal
study.27 Four studies were conducted in US,26,47,49,55
3 in Australia,51,52,54 one each in the Netherlands,27
Denmark,46 Canada,48 and China,53 and one in 4
countries including Belgium, Denmark, Germany
and Poland.50 Sample size varied substantially across
studies, with a median of 107 participants, and a
Table 2
Measures, Statistical Methods, Outcomes and Main Results of the Studies
Included in the Review
Study
ID
Sample
weight
status
Measure(s) of
body weight and
composition
Statistical
model
No. of
repeated
measures
Main results
1Overweight
and obesity
Objective measure:
DEXA
Paired
t-test 2
Body weight associated with pork fat-reduced diet
revealed no difference compared to the baseline,
and pork diet had no difference compared with soy
or carbohydrate diets on body weight (p > .05).
2Overweight
and obesity
Objective mea-
sure: An electronic
platform scale and
DEXA
Repeated-
measure
ANOVA
2
Both high protein (40% pork, HP) and normal pro-
tein groups (NP) lost BMI, fat mass and lean mass
(p < .001) throughout the 12-week intervention.
However, the HP group had greater preservation of
lean mass compared with NP (p < .05).
3
Under-
weight, nor-
mal weight,
overweight,
and obesity
Self-reported ANOVA 1
The proportion of people who reported to eat
pork was higher in obese and overweight college
students. However, pork intake was not associated
with overweight (OR = 1.31, 95% CI = 0.67, 2.57)
or obesity (OR = 2.14, 95% CI = 0.77, 5.27).
4Overweight Objective measure:
DEXA
Repeated-
measure
ANOVA
2
Postmenopausal women in both NP and HP (40%
pork) energy restriction diet groups showed de-
crease in BMI, fat mass, and lean mass (p < .001).
However, no difference was found between normal
protein and higher protein diet on BMI, fat mass
and lean mass.
5Normal
weight Self-reported
Linear
mixed-ef-
fect model
3
Pork non-consumers are negatively associated with
overweight (OR = 0.69, 95% CI = 0.49, 0.97) and
obesity (OR = 0.59, 95% CI = 0.29, 0.89). Over-
weight (OR = 1.41, 95% CI = 1.06, 1.88) and obese
(OR = 1.58, 95% CI = 1.16, 2.16) respondents are
more likely to be “high variety, high frequency”
pork consumers. However, “low variety, low
frequency” and “high variety, medium frequency”
pork intake was not associated with overweight or
obesity.
6
Under-
weight, nor-
mal weight,
overweight,
and obesity
Self-reported Logistic
regression 1
When retrospectively examining the association
between pork consumption reported at baseline and
weight change from 20 years old to 55-69 years
old, the change of BMI was signicant when com-
pared highest category intakes of pork to the lowest
intakes of pork in women, whereas man showed no
difference.
(continued on next page)

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An et al
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range from 12 to 29,145 participants. Recruited
adults’ age ranged in age from 18 to 70 years. Two
of the 12 studies exclusively recruited females,47,49
one exclusively recruited males,46 whereas females
and males were largely equally distributed in the
other studies.
Table 2 summarizes the measures, statistical
methods, and outcomes of the studies included in
the review. Nine studies adopted objective measures
of body weight and/or composition (eg, dual-ener-
gy X-ray absorptiometry (DEXA), stadiometer, or
oor scale),26,46,47,49-55 and the other 3 used self-re-
7Overweight
Objective measure:
A metric tape and
DEXA
Repeated-
measure
ANOVA
3
Compared with the control group, the pork group
signicantly reduced their weight, BMI, waist
circumference and body composition including
body fat (%), fat mass and abdominal fat (time
× treatment effect: p < .01 in all cases). These
reductions in adiposity measures were still evident
after 6 months of intervention. However, there was
no change in lean mass, which indicates that the
reduction in weight was due to loss of fat mass.
8Overweight
or obesity
Objective measure:
A stadiometer, a
oor scale, body fat
scale and DEXA
GLS 4
There was no difference in BMI, body fat per-
centage, fat mass, abdominal fat, lean mass, WC,
and HC when comparing pork group with beef or
chicken diet group (p > .05). WHR was lower in
pork group than beef and chicken group (p = .046).
These were not signicant when adjusting for
multiple comparisons.
9
Normal
weight with
elevated BP
Objective measure:
Body composition
tracking system
Repeated-
measure
ANOVA
3
Body weight was 2.3± 0.2 kg lower at post-inter-
vention than at pre-intervention (post: 83.3 ± 2.6
kg; pre: 85.5 ± 2.6 kg; p < .05), and the body fat
percentage tended to be lower at post-intervention
(pre: 41.1 ± 1.5%; post: 39.2 ± 1.6%; p = .06).
However, this effect was not moderated by diet
type (DASH-P vs DASH-CF).
10 Normal
weight
Objective measure:
A stadiometer and
a calibrated beam
scale
Mann-
Whitney
test
1
The intake of pork in obese and non-obese people
was not different (City: z = -0.142, p = .887; Town-
ship: z = 0.579, p = .563; and Rural area: z = 1.938,
p = .053).
11 Normal
weight
Objective measure:
A stadiometer, a
oor scale and a
body fat scale
Linear
mixed
regression
3
No difference was found when comparing BMI and
body fat of pork diet intervention with baseline (p
> .05). The BMI of pork group did not differ from
chicken group (p = .08); and body fat of pork group
and chicken group also did not differ (p = .86).
12
Normal
weight, over-
weight, and
obesity
Objective method:
A stadiometer and
a calibrated beam
scale
Linear
regression 6
The mean intake of pork was not different across
various body weight status (overweight: 0.42 ±
0.04 kg; normal weight: 0.38 ± 0.02 kg, p > .05).
Note.
WC, waist circumference; WHR, waist to hip ratio; HC, hip circumference; BMI, body mass index; DEXA, Dual energy
x-ray absorptiometry; BP, blood pressure; GLS, generalized least squares; DASH-P, Dietary Approaches to Stop Hyper-
tension diet with pork; DASH-CF, DASH diet with chicken and sh; NP, normal protein; and HP, high protein. All values
are means ± SEs.
Table 2 (continued)
Measures, Statistical Methods, Outcomes and Main Results of the Studies
Included in the Review
Study
ID
Sample
weight
status
Measure(s) of
body weight and
composition
Statistical
model
No. of
repeated
measures
Main results

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Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis
520
Table 3
Results from Meta-analysis
Study design Outcome Outcome
measures Contrast Studies included
in meta-analysis I2 index Pooled effect size
(95% CI) Model
Publication bias test
p-value
Egger’s
test
p-value
Begg’s test
Interventions
without energy
restriction
Body weight Floor scale Pre-intervention vs
post-intervention
Murphy, 2012;
Murphy, 2014;
Charlton, 2016
0% β = -0.86 (-1.55, -0.17) FE 1.00 .20
Lean mass Body fat
scale,
DEXA
Pre-intervention vs
post-intervention
Murphy, 2014;
Charlton, 2016 98.4% β = 1.79 (-1.74, 5.32) RE 1.00 /
Body fat
percentage
Body fat
scale,
DEXA
Pre-intervention vs
post-intervention
Murphy, 2012;
Murphy, 2014;
Charlton, 2016
90.4% β = -0.77 (-1.43, -0.11) RE 1.00 .84
Interventions
with energy
restriction
Body weight DEXA Pre-intervention vs
post-intervention
Mikkelsen, 2000;
Leidy, 2007;
Campbell, 2010
98.7% β = -5.56 (-10.59, -0.55) RE .60 .56
Lean mass DEXA Pre-intervention vs
post-intervention
Leidy, 2007;
Campbell, 2010 0% β = -1.50 (-1.62, -1.39) FE .32 /
Fat mass DEXA Pre-intervention vs
post-intervention
Leidy, 2007;
Campbell, 2010 0% β = -6.6 (-6.79, -6.42) RE 1.00 /
Observational
studies
Overweight Self-report-
ed height
and weight
Eating vs
non-eating pork
Brunt, 2008;
Verbeke, 2011 64.0% OR = 0.89 (0.48, 1.64) RE 1.00 /
Obesity Self-report-
ed height
and weight
Eating vs
non-eating pork
Brunt, 2008;
Verbeke, 2011 80.6% OR = 1.06 (0.30, 3.71) RE 1.00 /
Note.
FE: xed-effect model; RE: random-effect model

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An et al
Am J Health Behav.™ 2020;44(4):513-525 521 DOI: https://doi.org/10.5993/AJHB.44.4.12
ported body weight and height.27,48,50 Participants’
weight status varied across studies: 5 recruited
people that had overweight or obesity;46,47,49,51,52
4 recruited people of normal weight;26,50,53,54 and
3 recruited people of dierent weight categories
(eg, underweight, normal weight, overweight and
obesity).27,48,55 e outcomes pertaining to body
weight and composition were measured more than
once in 9 of the 12 studies.26,46,47,49,50-52,54,55 A variety
of statistical analyses were applied across studies,
including paired t-test, Mann-Whitney test, ANO-
VA, repeated-measure ANOVA, linear mixed-ef-
fect model, and logistic regression. Attrition rates
across the studies ranged from 12% to 35%.
Table 2 summarizes the main ndings regarding
the eect of pork consumption on body weight
and/or composition. e studies can be classied
into 2 categories by study design: experimental
studies (N = 7)26,46,47,49,51,52,54 and observational
studies (N = 5).27,48,50,53,55 Experimental studies in-
clude controlled trials with restrictions46,47,49 or
without restrictions on daily total caloric intake
(N = 4).51,52,54 Six of the 7 experimental studies
reported that pork consumption decreased body
weight and/or improved body composition among
participants,26,46,47,49,51,54 whereas the remaining one
reported a null eect.52 ree of the 5 observational
studies reported no association between pork con-
sumption and body composition,48,53,55 whereas the
remaining 2 found that the association between
pork consumption and body weight/composition
diered by consumption frequency and sex.27,50
Pork products consumed by study participants in-
cluded fresh pork, lean pork, cooked pork (eg, loin,
ham, or bacon), and other processed pork products.
Meta-analysis
Table 3 summarizes results from the meta-analy-
sis. Among the experimental studies without daily
total energy intake restrictions, pork intake was as-
sociated with a reduction in body weight by 0.86 kg
(95% CI = 0.17, 1.55) and body fat percentage by
0.77% (95% CI = 0.11%, 1.43%), whereas pork
intake was not associated with change in lean mass
(p > .05). Among the experimental studies with en-
ergy restrictions, pork intake was associated with a
reduction in body weight by 5.56 kg (95% CI =
0.55, 10.59), lean mass by 1.50 kg (1.39, 1.62),
and fat mass by 6.60 kg (6.42, 6.79). Among the
observational studies, pork intake was not associ-
ated with overweight or obesity status (p > .05).
No publication bias was identied by Egger’s test
or Begg’s test (p > .05).
Study Quality Assessment
Appendix B reports criterion-specic and glob-
al ratings from the study quality assessment. e
included studies on average scored 5.4 out of 8,
with a range from 3 to 7. All 12 studies includ-
ed in the review clearly stated the research ques-
tion and/or study objective, specied and dened
the study population, and pork consumption was
properly dened, valid, reliable, and implemented
consistently across study participants. Seven of the
12 studies adopted a randomized experimental de-
sign.26,46,47,49,51,52,54 Nine of the 12 studies assessed
body weight and/or composition more than once
over time.26,46,47,49–55 In contrast, none of the stud-
ies had outcome assessors blinded to the exposure
status of participants.
DISCUSSION
Our ndings on null or inverse associations be-
tween pork intake and body weight, body fat per-
centage, and fat mass appear to contradict results
of some previous observational studies. Using data
from the National Health and Nutrition Examina-
tion Survey, Wang and Beydoun45 found overall
meat consumption to be positively associated with
risk for obesity and central obesity. A systematic re-
view and meta-analysis of prospective cohort stud-
ies reported red meat consumption to be positively
associated with weight gain and risk for abdominal
obesity.56 However, observational studies are prone
to confounding bias (eg, other unhealthy habits
correlated with meat consumption that cause obe-
sity) and reverse causality (eg, people that have obe-
sity are more likely to consume red meat).23 is
review conducted a meta-analysis on randomized
controlled and crossover trials that assessed the
causal impact of pork consumption on body weight
and/or composition. Both trials with and without
daily overall energy restrictions conrmed an in-
verse relationship between pork intake and body
weight.26,46,47,49,51,52,54 Not surprisingly, trials with
energy restrictions found a much larger reduction
in body weight (5.56 kg) in comparison to those
without energy restrictions (0.86 kg). Moreover,

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Pork Consumption in Relation to Body Weight and Composition: A Systematic Review and Meta-analysis
522
pork intake also was associated with a reduction in
lean and fat mass as well as body fat percentage.
It is thought that pork consumption may improve
body composition and lean mass through increas-
ing satiety, enhancing thermogenesis, and facilitat-
ing glycemic control.57-61 e amino acids present
in pork protein enhance protein synthesis and
turnover rates, which may increase thermogenesis
and energy expenditure leading to less fat deposi-
tion.46 e rapid empty of gastric emptying and the
postprandial increase in plasma amino acid con-
centrations after ingestion of specic proteins may
increase satiety due to a greater stimulatory eect
on gastrointestinal hormones (eg, cholecystokinin
and glucagonlike peptide-1).46,62 Another possible
reason is that pork consumed in those trials is
healthier (eg, lean/fresh pork vs processed/high-fat
pork) than that generally consumed in the popu-
lation. A high-fat diet has been linked to weight
gain and adiposity, whereas protein-rich diet with
balanced energy intake is suggested to help weight
management.63
Some observational studies included in the review
reported that the relationship between pork con-
sumption and body weight/composition varied by
consumption frequency and sex.27,50 High but not
medium frequency pork consumers were found to
be associated with elevated risk of overweight; 27,50
and only women, but not men were associated with
higher BMI when comparing high to low daily
pork consumption quantity.27,50 ese ndings sug-
gest that daily total quantity of meat consumption,
rather than the specic type of meat consumed,
may serve as the driving factor for weight gain.45
Moreover, sex dierences in energy metabolism,64
which is poorly known to date, might moderate the
eect of pork intake on weight outcomes.
e limitations pertaining to this review and the
selected studies warrant future research. A small
and heterogeneous set of studies were included
in the review. Studies were conducted in dier-
ent countries with diverse study designs (ie, con-
trolled trials vs observational studies) and samples
of dierent age groups, which conned the gen-
eralizability of review ndings. Pork was provided
in dierent forms such as fresh lean pork, cooked
pork (ie, loin, ham, or bacon), and other processed
pork products, which may exert dierential impact
on body weight and composition outcomes.7,8,17-19
We categorized studies by study design (ie, experi-
mental studies with and without daily total energy
restriction, and observational studies) to reduce
study heterogeneity; however, given the small num-
ber of studies and the variety of pork products, it
proved infeasible to examine product-specic eect
on weight and body composition. In the future, re-
searchers should adopt experimental study designs,
recruit nationally or regionally representative sam-
ples, and examine the eect of fresh and lean pork
consumption on body weight and composition in
population subgroups (eg, by age group and sex).
In conclusion, pork is an essential food source
in the US and many other countries. In this study,
we systematically reviewed scientic literature as-
sociating pork consumption with body weight and
composition. Twelve studies met the eligibility cri-
teria and were included in the review. Meta-analysis
found that among the experimental studies with-
out energy restrictions, pork intake was associated
with a reduction in body weight by 0.86 kg and
body fat percentage by 0.77%; among the experi-
mental studies with energy restrictions, pork intake
was associated with a reduction in body weight by
5.56 kg, lean mass by 1.50 kg, and fat mass by 6.60
kg; and among the observational studies, pork in-
take was not associated with overweight or obesity
status. is review has limitations pertaining to
the small and heterogeneous body of literature in-
cluded. Future experimental studies based on rep-
resentative samples are warranted to examine the
eect of fresh and lean pork consumption on body
weight and composition among the general popu-
lation and by subgroups.
Human Subjects Approval Statement
is study is a systematic review article that was
exempt from human subjects review by the Wash-
ington University in St. Louis Institutional Review
Board.
Conict of Interest Disclosure Statement
e authors declare no conict of interest.
Acknowledgements
is study was funded by the National Pork
Board. e funder had no role in the design, execu-
tion, interpretation, or writing of the study.

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An et al
Am J Health Behav.™ 2020;44(4):513-525 523 DOI: https://doi.org/10.5993/AJHB.44.4.12
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An et al
Am J Health Behav.™ 2020;44(4):513-525 525 DOI: https://doi.org/10.5993/AJHB.44.4.12
Appendix A
Search Algorithm in PubMed
“pork” AND (“body composition” [MeSH] or “body composition” or “obesity”[MeSH] or “obesity” or “obese” or “adi-
posity” or “adipose” or “overweight”[MeSH] or “overweight” or “weight” or “body weight”[MeSH] or “body weight” or
“body mass” or “body mass index”[MeSH] or “BMI” or “skinfold thickness”[MeSH] or “skinfold thickness” or “waist
circumference”[MeSH] or “waist circumference” or “WC” or “hip circumference” or “HC” or “waist/hip ratio” or “WHR” or
“waist-hip ratio” or “waist to hip” or “waist-to-hip”[MeSH] or “waist-to-hip” or “lean mass” or “abdominal” or “lean body” or
“fat” or “muscle mass” or “anthropometric”) AND (“humans”[MeSH])AND (English[lang])
Appendix B
Study Quality Assessment
Criterion
Study ID
1234567891011 12
1. Was the research question or objective clearly stated? 1111111111 1 1
2. Was the study population clearly specied? 1111111111 1 1
3. Was the study a randomized controlled trial? 1101001110 1 0
4. Was a sample size justication (eg, power analysis)
provided? 0000001110 1 0
5. Were pork consumption measures clearly dened, valid,
reliable, and implemented consistently across all study
participants?
1111111111 1 1
6. Were body weight and/or body composition assessed more
than once over time? 1101101110 1 1
7. Were body weight and/or body composition objectively
measured? 1101001111 1 1
8. Were the outcome assessors blinded to the exposure status
of participants? 0000000000 0 0
Total score 6636437774 7 6