30 

The North African Journal of Food and Nutrition Research: (2017) 01; (02): 30-43 
https://doi.org/10.5281/zenodo.1245604 


Review Article 


9 


OPEN ACCESS 


NAI 

r\p 

THE NORTH AFRICAN JOURNAL OF 
FOOD AND NUTRITION RESEARCH 


elSSN: 2588-1582 


Contents lists available at 
Journal homepage: httpsi//www.najfnr.ora 


Metabolic Syndrome and Risk of Colorectal Adenoma and 
Colorectal Cancer: A Meta-Analysis 

Salah Eddine ELHARAG \ Youssouf TRAORE ^ Meghit Boumediene KHALED' ^* 

'' Department of Biology, Faculty of Natural and Life Sciences, Djillali Liabes University, PO Box 89, Sidi-bel-Abbes (22000), Algeria 
^ Laboratory of Health & Environment, Djillali Liabes University, PO Box 89, Sidi-bel-Abbes (22000), Algeria 


ARTICLE INFO 


ABSTRACT 


Article history: 

Received 25 September 2017 
Accepted 26 October 2017 
Available online 28 October 2017 
Keywords: 

Metabolic syndrome 
Colorectal cancer 
Colorectal adenoma 
Incidence 
Meta-analysis 


Access this article online 

Quick Response Code: 

Website: 


www.naifnr.orq 



https://doi.org/10.5281/zenodo.1245604 


Article edited by: 

Dr. Lamia BENBRAHIM-TALLAA / Dr. Mickael RIALLAND 


BACKGROUND: Growing evidence suggests that metabolic syndrome (MetS) could be linked with 
the incidence of colorectal adenoma and cancer (CRA and CRC). AIMS: Conducting a meta¬ 
analysis to assess the association of MetS with both CRA and CRC. METHODS AND MATERIAL: 
Relevant studies were identified by systematically searching PubMed database for articles 
published in the last ten years. A random effect analysis model and Mantel-Haenszel statistical 
method were used to obtain pooled risk ratios (RRs) and their 95% confidence intervals (CIs) for 
dichotomous data. The analyses were assessed for heterogeneity and publication bias. RESULTS: 
35 studies were included in the meta-analysis involving approximately 1300000 participants. A 
significant high risk for CRA was observed among patients with MetS compared to those without 
(RR = 1.43; 95% Cl = 1.31, 1.57). The pooled RRs of CRC were 1.46 (95% Cl = 1.36, 1.56). The risk 
estimates varied according to the type of the study (cohorts and non-cohorts), gender (men and 
women), MetS definition (NCEP-ATPIII, IDF, harmonized and others), populations (Asia, Europe, 
and the USA), and cancer location (colon and rectum). CONCLUSIONS: MetS is associated with an 
increased risk of CRA and CRC. The risk was higher for advanced adenomas. Taking into 
consideration MetS patients in the secondary prevention programs and the management of this 
condition in the aim of the primary prevention is highly recommended. 


* Corresponding author ©Tel: -f213 551152261 ^ khaled@khaledmb.co.uk 


1. INTRODUCTION 


Colorectal cancer (CRC) is a true public health burden 
recording more than 1.3 million cases (9.7% of all cancers), 
and approximately 0.7 million deaths (8.5% of all cancers) 
worldwide [1]. 


Age, sex, ethnicity [2], family history of CRC [3], inherited 
genetic predispositions [ 4-6] , and inflammatory diseases 
[7, 8] play an essential role in CRC pathophysiology along 
with other risk factors including diet [9-11] , smoking [ 12] , 
physical inactivity [13], diabetes [14], and MetS [15]. 


This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work 
is properly cited. © 2017 The Authors. The North African Journal of Food and Nutrition Research. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 

























Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


31 


MetS has become a growing public health and a clinical 
challenge too. 20-25% of world's adult population has 
MetS according to the International Diabetes Federation 
(IDF) [16]. MetS is defined by a cluster of correlated 
physiological, biochemical, clinical, and metabolic factors 
reflecting a cohesive pathophysiology. Those factors 
include visceral obesity, dyslipidemia, hyperglycemia, and 
hypertension that increase the risk of developing type 2 
diabetes mellitus and cardiovascular diseases [ 17-191 . 

The association between MetS and CRC has been 
previously addressed in several studies, although the 
unavailability of evidence linking MetS with the 
precancerous lesions (adenomas, adenomatous polyps). 
Additionally, CRC is supposed to develop following the 
adenoma-carcinoma sequence [4], and those adenomas 
precede the cancer stage by several years which could 
allow for its prevention by targeting those precancerous 
lesions in the screening programs. Hence, understanding 
the correlation between CRA and MetS is crucial in clinical 
practice. 

Results from studies that addressed the association linking 
MetS and colorectal neoplasms (CRN) (CRA (colorectal 
adenoma) and CRC) were inconsistent [ 20, 211 . In the 
present meta-analysis, we aimed to tackle this issue, 
focusing especially on the effect of the full syndrome on 
CRC and CRA incidence. 

2. METHODS 


Search strategy 

The meta-analysis was carried out following the Preferred 
Reporting Items for Systematic Reviews and Meta- 
Analyses (PRISMA) guidelines [221 . 

The literature search was independently undertaken by 
two authors (S.E and Y.T). The author (MB.K) made the 
final decision in case of any discrepancy. 

Key terms according to the Medical subject headings 
(MeSh) were used to identify relevant studies on the 
relationship between colorectal neoplasm and MetS in 
PubMed database. Full English studies, published during 
the past 10 years until 2017/08/01, were systematically 
searched and the terms used were: "colorectal 
neoplasms", "colorectal cancer", and "metabolic 
syndrome". 

Study selection 

Study eligibility was independently assessed by two 
reviewers (S.E and Y.T), and resolutions, in case of 
disagreements, were achieved by the author (MB.K). 
Cohort, case-control, and cross-sectional studies with 
MetS as well as CRA and/or CRC incidence were eligible 
for the analysis. Studies were included if they met the 


following criteria: (a) CRA and/or CRC as the outcomes 
considered in the study, (b) MetS as the exposure, (c) the 
study must provide sufficient data to calculate the RRs and 
their 95% CIs, (d) the study must state the definition of 
MetS used. 

Furthermore, reviews, meta-analyses, articles not 
published in English, articles not published as full text 
(case reports, letters to editors, editorials, comments, news 
etc.), and in vitro or studies where the subjects were 
organisms other than humans were excluded. The 
selection of any article was primarily based on title and 
abstract in order to exclude irrelevant studies. 
Subsequently, the full texts were strictly analyzed to 
determine the relevancy of any retrieved study. 

Data extraction 

Data extracted from each included study were: the first 
author's name, the year of publication, the country where 
the study was undertaken, duration of the study, type of 
lesions, number of subjects, number of events, and the 
definition of MetS used. Two authors (S.E and Y.T) 
independently gathered the relevant data. 

Statistical analysis 
Summary measures 

A random effect meta-analysis model, which represents 
the assumption that there is a distribution of true effect 
sizes and aims to estimate the mean of this distribution 
[231 , was used in our main meta-analysis to assess the 
relative risks (RRs) and their 95% confidence intervals (CIs) 
for dichotomous data. Mantel-Haenszel method was used 
to estimate the amount of the between-study variation. 
The between-study variance was assessed using the Tau- 
squared (T^) statistic. Z-test of the null hypothesis was 
calculated and P < 0.05 was considered statistically 
significant. 

Synthesis of results 

Cochran's test or Q-test (X^) was used to indicate the 
extent of heterogeneity and P < 0.05 was considered 
statistically significant. The H statistic, which measures the 
degree of inconsistency across studies in a meta-analysis 
and which describes the percentage of total variation 
across studies that is due to heterogeneity rather than 
chance [24], was as well obtained. A value of 40% 
suggests low heterogeneity, 40-70% indicates moderate 
heterogeneity, and a value of > 70% may suggest high 
heterogeneity. Funnel plots were obtained and visually 
assessed for risk of publication bias. 

Subgroup analysis 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 






Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


32 


Subgroup analysis was undertaken to explore source of 
heterogeneity according to study design (cohort, case- 
control, and cross-sectional), gender (men and women), 
MetS definition (NCEP-ATPIII, IDF, the harmonized 
definition, and other definitions), geography (the USA, 
Asia, and Europe), cancer site (colon or rectal cancer). 

3. RESULTS 


Study selection 

The process of selecting studies is displayed in the 
flowchart on Figure 1. 263 studies were identified through 
a database search. 179 studies unrelated to the topic and 
studies unpublished as full text or in the English language 
were excluded. 84 eligible studies reported MetS and 
CRA/CRC were retrieved and scanned carefully. 49 studies 
providing inadequate exposures, outcomes, or data and 
studies unfitting inclusion criteria were excluded out of the 
eligible studies. Eventually, 35 studies fulfilled the 
inclusion criteria comprised the meta-analysis. 

Study characteristics 

Table 1 summarizes properties of the included studies. 
Our meta-analysis comprised nine cohort studies [ 20, 21, 
25-311 , 13 case-control studies [32-441 , and 13 cross- 
sectional studies [ 45-571 . 26 studies were undertaken in 


Asia [ 25, 26, 28-31, 33-35, 37, 38, 42, 44-571 while eight 
were carried out in European countries [ 20, 27, 32, 36, 39- 
41, 431 , and only one study was performed in the USA [ 211 . 
Regarding the outcomes considered, 22 studies provided 
data on CRA risk [ 21, 25, 26, 28-31, 34-36, 44, 46, 47, 49- 
^1, 18 concerning CRC [ 20, 26, 27, 29, 30, 32, 33, 36-43, 
45, 46, 481 , whereas 5 studies on both outcomes [ 26, 29, 
30, 36, 461 . Furthermore, 20 studies utilized the definition 
formulated by the NCEP/ATPIII as diagnosis criteria in 
clinical practice [20, 25-29, 34, 36, 40, 41, 44, 46, 47, 49, 
50, 52-55, 571 , six studies provided the exposure data in 
basis of the IDF definition of MetS [ 20, 32, 38, 41, 43, 561 , 
three used the harmonized definition [ 39, 41, 511 , and nine 
presented MetS data patients using other definitions [ 21, 
30, 31, 33, 35, 37, 42, 45, 481 . 

Association of MetS with CRA 

A random effect meta-analysis model of 22 studies 
comprising 30 datasets of CRA incidence in individuals 
with MetS versus without MetS supported the association 
between MetS and CRA (RR = 1.43; 95% Cl = 1.31, 1.57) 
(Figure 2; Table 2). No evidence of publication bias was 
observed (Figure 3). The risk estimation showed 
significant differences between cohort, case-control, and 
cross-sectional studies, this latter revealed a moderate 
heterogeneity (1^ = 32%). 



Figure 1: Flowchart of study selection 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 
































Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


33 


MetS No MetS Risk Ratio Risk Ratio 


Stucty or Subgroup 

Events 

Total 

Events 

Total 

Weight 

M-H, Random, 95% Cl 

M-H, Random, 95% Cl 

Chang 201 4 AA (M) ATPIII 

59 

1063 

159 

4567 

3.1% 

1.59 [1.19, 2.13] 



Chang 201 4 AA (VV) ATPIII 

17 

491 

105 

4763 

1.9% 

1.57 [0.95, 2.60] 



Chiu 2015 AA/ATPIII 

41 

1237 

58 

3246 

2.5% 

1.85 [1.25, 2.75] 



Chiu 2015 CRA/ATPiii 

298 

1237 

654 

3246 

4.4% 

1.20 [1.06,1.35] 


— — 

Hong 2010 AA/Other 

22 

349 

35 

1412 

1.8% 

2.54 [1.51,4.28] 


- ^ -► 

Hong 2010 CRA/Other 

87 

349 

252 

1412 

3.7% 

1.40 [1.13,1.73] 



Hong 2015 CRA/Other 

295 

836 

963 

3790 

4.4% 

1.39 [1.25,1.55] 



Hu 2011 CRA/ATPIII 

132 

634 

265 

2472 

3.9% 

1.94 [1.61,2.35] 



Huang 2013 CRA/ATPIII 

60 

252 

156 

1270 

3.3% 

1.94 [1.49, 2.53] 



Hwang 2010 CRA/ATPIII 

106 

418 

450 

2499 

3.9% 

1.41 [1.17,1.69] 



Kaneko 2010 AC (M) Other 

39 

62 

180 

371 

3.7% 

1.30 [1.04,1.61] 



Kaneko 2010 AC (W) Other 

4 

11 

86 

249 

1.0% 

1.05 [0.47, 2.34] 



Kang 2010 ORA/ATPIII 

298 

511 

824 

1733 

4.5% 

1.23 [1.12,1.34] 


— 

Kim 2007 CRA/ATPIII 

125 

325 

606 

2206 

4.1% 

1.40 [1.20,1.63] 



Kim 2012 AA/ATPIII 

37 

536 

149 

4317 

2.7% 

2.00 [1.41,2.83] 



Kim 2012 CRA/ATPiii 

325 

824 

1446 

5614 

4.5% 

1.53 [1.39,1.68] 


— 

Kim 2015 CRA/ATPiii 

64 

119 

338 

947 

3.9% 

1.51 [1.25,1.82] 



Koo 2017 AA/ATPiii 

19 

406 

33 

1800 

1.7% 

2.55 [1.47, 4.44] 


- ^ -► 

Koo 2017 CRA/ATPiii 

122 

406 

410 

1800 

4.0% 

1.32 [1.11,1.57] 



Lee 201 4 AA/ATPiii 

8 

1 06 

23 

485 

1.0% 

1.59 [0.73, 3.46] 



Lee 2014 CRA/ATPiii 

37 

135 

117 

579 

2.9% 

1.36 [0.99,1.87] 



Lin 2014 CRA (M) ATPiii 

230 

289 

664 

805 

4.6% 

0.96 [0.90,1.03] 



Lin 2014 CRA (VV) ATPiii 

199 

247 

407 

528 

4.6% 

1.05 [0.97,1.13] 



Liu 2010 CRA/Other 

249 

963 

470 

2818 

4.3% 

1.55 [1.35,1.77] 


— ■ — 

Oh 2008 CRA/IDF 

11 

25 

42 

175 

1.8% 

1.83 [1.10, 3.07] 



Pyo 2016 CRA/ATPIII 

143 

295 

475 

1052 

4.3% 

1.07 [0.94,1.23] 



Sato 2011 CRA/Harmonized 

86 

231 

175 

732 

3.7% 

1.56 [1.26,1.92] 



Trabulo 2015 CRA/ATPIII 

55 

129 

32 

129 

2.7% 

1.72 [1.20, 2.47] 



Tsilidis 2010 CRA/Other 

40 

106 

92 

286 

3.1% 

1.17 [0.87,1.58] 



Yang 2010 0RA/ATPIII 

81 

147 

136 

341 

3.9% 

1.38 [1.14,1.68] 



Total (95% Cl) 


12739 


55644 

100.0% 

1.43 [1.31,1.57] 


♦ 

Total events 

3289 


9802 






Heterogeneity: Tau== 0.04; ChP 

= 218.91, df= 29 (P < 0.00001); 1= 

= 87% 


-^^- 

0 5 0 7 

-- 

Test for overaii effect: Z= 7.94 (P 

< 0.00001) 





Decrease CRA risk 

Increase CRA risk 


Figure 2; 

: Forest plot of association between MetS and CRA risk 



AA Advanced Adenoma, ATPIII (NCEP-ATPIII) National Cholesterol Education Program-Adult Treatment Panel III, CRA Colorectal Adenoma, IDF 
International Diabetes Foundation, M Men, W Women. 


SE(log[RR]) 


0.1 


0.2 


0.3 


0.4 


0.5 


Oo 

O 


o 

o 


3 ° 


o 


o 


o 


o 


o 

o 

o 

o 


O o o 
o 


o 


o 


0.5 


0.7 


1.5 


Figure 3: Funnel plot of the association between MetS and CRA 


RR 


The summary of RRs for Asians was significant, but not for 
the other populations, similarly to studies reporting results 
for both sexes. The pooled analysis for risk estimates of 
studies using the NCEP/ATPIII definition of MetS were 
similar to studies using other definitions (RR = 1.43; 95% 


Cl = 1.28, 1.59) and (RR = 1.45; 95% Cl = 1.36, 1.55) 
respectively. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 
































Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


34 


Table 1 : Characteristics of included studies 


Cohorts 

Authors, year of 
publication [Ref] 

Country 

Years 

Type of lesion 

N2 events / N2 total 

N2 of 

MetS 

patients 

MetS 

definition 

Lu et at, 2015 [20] 

Norway 

1995-2010 

Colorectal cancer 

2044 /143 477 

43775" 

40234*= 

IDF 

NCEP-ATPIII 

Chiu etal, 2015 [25] 

Taiwan 

12/2003- 

07/2011 

Colorectal adenomas 

952/4 483 

1237 

NCEP-ATPIII 

Lin etal, 2014 [26] 

China 

10/2007- 

12/2011 

Colorectal adenomas 
and cancer 

1500 CRA +446 
CRC/2 315 

705 

NCEP-ATPIII 

Van Kruijsdijk et al, 
2013 [27] 

Netherlands 

09/1996- 

03/2011 

Colorectal cancer 

71 / 5937 

3179 

NCEP-ATPIII 

Huang etal, 2013 
[28] 

Taiwan 

01/2003- 

12/2010 

Colorectal adenomas 

216/1522 

252 

NCEP-ATPIII 

Kim et at 2012 [29] 

South Korea 

04/2007- 

04/2009 

Colorectal adenomas 
Colon and rectal cancer 

1771 CRA + 1292 

CC + 146 RC / 

6438 

5614 

NCEP-ATPIII 

Kaneko etal, 2010 
[30] 

Japan 

2007 and 2008 

Colorectal adenomas 
and cancer 

309 CRA + 34AC/ 
727 

80 

other 

Liu etat 2010 [31] 

China 

01/2006- 

05/2008 

Colorectal adenomas 

719/4122 

963 

Other 

Tsilidis etal, 2010 
[21] 

The USA 

1989-2000 

Colorectal adenomas 

132/392 

106 

other 

Case-control 

Authors, year of 
publication [Ref] 

Country 

Years 

Type of lesion 

Cases/controls 

N2 of 

MetS 

patients 

MetS 

definition 

Harlid et al, 2017 
[32] 

Sweden 

1985-2014 

Colorectal cancer 

69/69 

24 

IDF 

Pyo etat 2016 [33] 

South Korea 

01/2002- 

12/2012 

Rectal neuroendocrine 

tumors 

102/52583 

7137 

Other 

Pyo etat 2016 [34] 

South Korea 

10/2009- 

12/2011 

Colorectal adenomas 

618/729 

295 

NCEP-ATPIII 

Hong etat, 2015 

South Korea 

01/2011- 

21/2011 

Colorectal adenomas 

1258/3368 

863 

other 

Trabulo etal, 2015 
[36] 

Portugal 

03/2013- 

03/2014 

Colorectal adenomas 
and cancer 

87 CRA/171 

23 AC/235 

129 

NCEP-ATPIII 

Jeon etat 2014 [3Z] 

South Korea 

06/2004- 

01/2009 

Colon and rectal cancer 

264 CC / 400 

186 RC/400 

193 

Other 

Ulaganathan et al, 

2012 [38] 

Malaysia 

12/2009- 

01/2011 

Colorectal cancer 

140/140 

196 

IDF 

Danese etal, 2012 
[39] 

Italy 

01/2011- 

08/2011 

Colorectal cancer 

40/40 

36 

Harmonized 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 

























Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


35 


Kontou eta/, 2012 
[40] 

Greece 

12/2009- 

12/2010 

Colorectal cancer 

250/250 

127 

NCEP-ATPIII 

Aleksandrova eta/, 
2011 [41] 

Europe"^ 

1999-2003 

Colon and rectal cancer 

689 CC / 689 

404 RC / 404 

424d 

461'* 

350' 

IDF 

Harmonized 

NCEP-ATPIII 

Shen eta/, 2010 
[42] 

China 

01/2002- 

03/2007 

Colorectal cancer 

507 / 507 

248 

other 

Pelluchi eta/, 2010 
[43] 

Italy and 
Switzerland 

1992-2001 

Colon and rectal cancer 

1378 CC + 878 RC 
/4 661 

159 

IDF 

Kang eta/, 2009 
[44] 

South Korea 

01/2006- 

12/2007 

Colorectal adenomas 

1 122/1 122 

511 

NCEP-ATPIII 

Cross-sectional 

Authors, year of 
publication [Ref] 

Country 

Years 

Type of lesion 

N2 events / N2 total 

N2 of 

MetS 

patients 

MetS 

definition 

Pan etal, 2017 [«] 

China 

01/2011- 

11/2015 

Colorectal cancer 

27/1793 

262 

Other 

Koo eta/, 2017 [46] 

South Korea 

01/2010- 

12/2010 

Colorectal adenomas 
and cancer 

588 CRA + 4 CRC / 
2206 

142 

NCEP-ATPIII 

Kim efa/(2015 [4Z] 

South Korea 

01/2011- 

12/2011 

Colorectal adenomas 

402/1066 

119 

NCEP-ATPIII 

Jung etal. 2014 [481 

South Korea 

2010-2011 

Rectal neuroendocrine 

tumors 

101 / 57819 

9297 

Other 

Chang eta/, 2014 
[49] 

Taiwan 

01/2006- 

12/2009 

Colorectal adenomas 

340/10884 

1554 

NCEP-ATPIII 

Lee eta/, 2014 m] 

South Korea 

07/2005- 

12/2012 

Colorectal adenomas 

154/714 

135 

NCEP-ATPIII 

Sato etal, 2011 [51] 

Japan 

06/2008- 

01/2010 

Colorectal adenomas 

261 / 963 

231 

Harmonized 

Hu eta! 2011 [52] 

Taiwan 

10/2004- 

04/2006 

Colorectal adenomas 

397/3106 

634 

NCEP-ATPIII 

Yang eta! 2010 
[53] 

South Korea 

10/2003- 

06/2008 

Colorectal adenomas 

217/488 

147 

NCEP-ATPIII 

Hong eta/, 2010 
[M] 

South Korea 

09/2005- 

03/2009 

Colorectal adenomas 

339/1761 

349 

NCEP-ATPIII 

Hwang et a! 2010 
[55] 

South Korea 

2007 

Colorectal adenomas 

556/2917 

418 

NCEP-ATPIII 

Oh eta/, 2008 [%] 

South Korea 

10/2005- 

12/2005 

Colorectal adenomas 

53 /200 

25 

IDF 

Kim eta/, 2007 [^] 

South Korea 

03/2004- 

12/2005 

Colorectal adenomas 

731 /2531 

325 

NCEP-ATPIII 


AC adenocarcinomas^ AHA/NHLBI America Heart Association and National Heart Lung Blood Institute, CC colon cancer, CRA colorectal adenoma, CRC 
colorectal cancer, IDF International Diabetes Foundation, MetS metabolic syndrome, NCEP-ATPIII National Cholesterol Education Program-Adult 
Treatment Panel III, RC rectal cancer. 

°, ^ According to IDF definition, 
f According to the NCEP-ATPIII definition. 

Participants are from Denmark, France, Germany, Greece, Italy, Spain, the Netherlands, and the United Kingdom. 

® According to the harmonized definition. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 


























Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


36 


Table 2 : Results of subgroup analysis 


Subgroups 

No of 

studies 
(No of 
datasets) 

[References] 

Meta- 

analysis 

model 

RR (95% Cl) 

Z-test 

p(%) 

Heterogeneity 

Colorectal adenomas 

All studies 

22 (30) 

[21. 25. 26. 28-31. 34-36. 

44. 46. 47. 49-571 

RE 

1.43 [1.31,1.57] 

7.94 

fP < 0.00001) 

87 

0.04 

218.91, df = 29 
(P < 0.00001) 

Type of study 

Cohort 

7(11) 

[21. 25. 26. 28-311 

RE 

1.36 [1.15,1.61] 

3.62 

(P = 0.0003) 

93 

0.06 

143.81, df = 10 
(P < 0.00001) 

Case-control 

4(4) 

[34-36. 441 

RE 

1.27 [1.11,1.46] 

3.47 

(P = 0.0005) 

75 

0.01 

11.89, df = 3 
(P = 0.008) 

Cross-sectional 

11 (15) 

[46. 47. 49-571 

RE 

1.52 [1.40,1.64] 

10.38 

(P < 0.00001) 

32 

0.01 

20.49, df = 14 
(P = 0.12) 

Study location 

Asia 

20 (28) 

[25. 26. 28-31. 34. 35. 44. 

46. 47. 49-571 

RE 

1.44 [1.31,1.58] 

7.71 

(P < 0.00001) 

87 

0.04 

215.89, df = 27 
(P < 0.00001) 

Other 

2(2) 

[21, 36] 

RE 

1.40 [0.96, 2.03] 

1.76 

(P = 0.08) 

61 

0.04 

2.58, df = 1 
(P = 0.11) 

MetS definition 

NCEP-ATPIII 

15 (21) 

[25. 26. 28. 29. 34. 36. 44. 

46. 47. 49, 50. 52. 53. 55, 

RE 

1.43 [1.28,1.59] 

6.38 

(P < 0.00001) 

89 

0.05 

187.17, df = 20 
(P < 0.00001) 

Other 

7(9) 

[21, 30, 31, 35, 51, 54, 561 

EE 

1.45 [1.36,1.55] 

10.91 

(P < 0.00001) 

27 

NA 

11.00, df = 8 
(P = 0.20) 

Gender 

Men 

3(3) 

[26, 30, 491 

RE 

1.24 [0.87,1.75] 

1.19 

(P = 0.23) 

90 

0.08 

21.05, df = 2 
(P < 0.0001) 

Women 

3(3) 

[26, 30, 491 

RE 

1.13 [0.88,1.45] 

0.95 

(P = 0.34) 

30 

0.02 

2.86, df = 2 
(P = 0.24) 

Advanced 

adenomas 

6(7) 

[25, 29, 46, 49, 50, 541 

EE 

1.85 [1.58, 2.17] 

7.55 

(P < 0.00001) 

0 

NA 

4.48, df = 6 
(P = 0.61) 

Colorectal cancer 

All studies 

18 (45) 

[20, 26, 27, 29, 30, 32, 34, 

36-43, 45, 46, 481 

RE 

1.46 [1.36,1.56] 

10.89 

(P < 0.00001) 

74 

0.03 

166.67, df = 44 
(P < 0.00001) 

Type of study 

Cohort 

5(15) 

[20, 26, 27, 29, 301 

RE 

1.63 [1.46,1.82] 

8.49 

(P < 0.00001) 

76 

0.03 

57.26, df = 14 
(P < 0.00001) 

Case-control 

10 (27) 

[32, 33, 36-431 

RE 

1.35 [1.26,1.45] 

8.41 

(P < 0.00001) 

62 

0.02 

61.SI, df = 26 
(P < 0.0001) 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 













































Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


37 


Cross-sectional 

3(3) 

[45. 46. 481 

FE 

1.77 [1.20, 2.62] 

2.85 

fP = 0.004) 

0 

NA 

0.78, df = 2 
(P = 0.68) 

Study location 

Asia 

10 (16) 

[26. 29. 30. 33. 37. 38. 42. 

45. 46. 481 

RE 

1.60 [1.42,1.79] 

7.93 

(P < 0.00001) 

60 

0.02 

37.20, df = 15 
(P = 0.001) 

Europe 

8(29) 

[20. 27. 32. 36. 39-41. 431 

RE 

1.40 [1.29,1.52] 

7.88 

(P < 0.00001) 

78 

0.04 

127.03, df = 28 
(P < 0.00001) 

MetS definition 

NCEP-ATPIII 

8(16) 

[20. 26. 27. 29. 36. 40. 41. 

46] 

RE 

1.41 [1.28,1.56] 

6.86 

(P < 0.00001) 

71 

0.02 

52.59, df = 15 
(P < 0.00001) 

IDF 

5(15) 

[20. 32. 38. 41. 431 

RE 

1.48 [1.29,1.69] 

5.69 

(P < 0.00001) 

79 

0.05 

66.43, df = 14 
(P < 0.00001) 

Harmonized 

2(5) 

[39. 411 

RE 

1.22 [1.07,1.38] 

3.05 

(P = 0.002) 

52 

0.01 

8.27, df = 4 
(P = 0.08) 

Other 

6(9) 

[30. 33. 37. 42. 45. 481 

FE 

1.74 [1.58,1.91] 

11.58 

(P < 0.00001) 

14 

NA 

9.30, df = 8 
(P = 0.32) 

Gender 

Men 

6(15) 

[20. 26. 30. 38. 41. 431 

RE 

1.41 [1.25,1.60] 

5.52 

(P < 0.00001) 

82 

0.04 

78.45, df = 14 
(P < 0.00001) 

Women 

6(15) 

[20. 26. 30. 38. 41. 431 

RE 

1.47 [1.32,1.63] 

7.11 

(P < 0.00001) 

70 

0.03 

47.43, df = 14 
(P < 0.0001) 

Cancer site 

Colon 

6(15) 

[20. 29, 37, 41-431 

RE 

1.53 [1.41,1.67] 

9.80 

(P < 0.00001) 

77 

0.02 

59.86, df = 14 
(P < 0.00001) 

Rectum 

8(17) 

[20, 29, 33, 37, 41-43, 481 

RE 

1.45 [1.29,1.63] 

6.19 

(P < 0.00001) 

72 

0.04 

56.50, df = 16 
(P < 0.00001) 

Colorectal adenomas versus colorectal cancer 

CRA 

5(9) 

[26, 29, 30, 36, 461 

RE 

1.38 [1.13,1.68] 

3.19 

(P = 0.001) 

93 

0.07 

118.45, df = 8 
(P < 0.00001) 

CRC 

5(8) 

[26, 29, 30, 36, 461 

RE 

1.48 [1.20,1.82] 

3.69 

(P = 0.0002) 

65 

0.04 

20.23, df = 7 
(P = 0.005) 


df degree of freedom^ FE fixed effect^ MetS metabolic syndrome^ NA not applicable^ NCEP-ATPIII National Cholesterol Education Program-Adult 
Treatment Panel III, RE random effect, RR risk ratio 


Association of MetS with advanced adenomas 

A fixed-effect meta-analysis model, since there was no 
evidence of heterogeneity, consisting of six studies and 
seven datasets reporting the incidence of advanced 
adenomas among individuals with MetS as compared with 
individuals without MetS gave evidence of a strong 
association (Table 2). A RR of 1.85 (95% Cl = 1.58, 2.17) was 
observed, with no heterogeneity (P = 0.61, 12 = 0%). 


Association of MetS with CRC 

Eighteen studies including 45 datasets were available for 
the meta-analysis (Figure 4; Table 2). MetS patients 
showed an RR of 1.46 (95% Cl = 1.36,1.56) to develop CRC 
compared with individuals without MetS. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 



































Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


38 


study or Subgroup 


MetS 

Events Total 


No MetS 

Events Total Weight 


Risk Ratio 

MH, Random, 95% Cl 


Risk Ratio 

M-H, Random, 95% Cl 


Aleksandrova 2011 CC (M) ATPIII 
Aleksandrova 2011 CC (M) Harmonized 
Aleksandrova 2011 CC (M) IDF 
Aleksandrova 2011 CC (VV) ATPIII 
Aleksandrova 2011 CC (W) Harmonized 
Aleksandrova 2011 CC (VV) IDF 
Aleksandrova 2011 RC (M) ATPIII 
Aleksandrova 2011 RC (M) Harmonized 
Aleksandrova 2011 RC (M) IDF 
Aleksandrova 2011 RC (W) ATPIII 
Aleksandrova 2011 RC (VV) Harmonized 
Aleksandrova 2011 RC (VV) IDF 
Danese 2012 CRC /Harmonized 
Harlid2017CRC/IDF 
Jeon 2014 CC/Other 
Jeon 2014 RC/Other 
Jung 2014 RC/Other 
Kaneko 2010 AC (M) Other 
Kaneko 2010 AC (VV) Other 
Kim 2012 CC /ATPIII 
Kim 2012 RC /ATPIII 
Kontou 2012 CRC /ATPIII 
Koo 2017 CRC /ATPIII 
Lin 2014 CRC (M) ATPIII 
Lin 2014 CRC (VV) ATPIII 
Lu 2015 CC (M) ATPIII 
Lu2015CC(M)IDF 
Lu 2015 CC (VV) ATPIII 
Lu 2015 CC (VV) IDF 
Lu 2015 RC (M) ATPIII 
Lu2015RC(M)IDF 
Lu 2015 RC (VV) ATPIII 
Lu 2015 RC (VV) IDF 
Pan 2017 CRC/Other 
Pelucchi2010CC (M) IDF 
Pelucchi2010CC(W)IDF 
Pelucchi2010RC (M) IDF 
Pelucchi2010RC(W)IDF 
Pyo 2016 RC/ Other 
Shen 201OCC/Other 
Shen 201ORC/Other 
Trabulo 2015 AC/ATPIII 
Ulaganathan 2013 CRC (M) IDF 
Ulaganathan 2013 CRC (W) IDF 
Van Kruijsdijk 2013 CRC /ATPIII 

Total (95% Cl) 

Total events 

Heterogeneity: Tau== 0.03; ChP= 166.67, 
Test for overall effect: Z= 10.89 (P < 0.00001) 


108 

182 

204 

442 

3.1% 

1.29(1.10,1.50] 



— 

150 

257 

162 

367 

3.1% 

1.32(1.13,1.54] 



— ^ — 

140 

234 

172 

390 

3.1% 

1.36(1.16,1.58] 



— 

121 

191 

256 

563 

3.2% 

1.39(1.21,1.60] 



— ■ — 

156 

254 

221 

500 

3.2% 

1.39(1.21,1.60] 



— • — 

140 

234 

237 

520 

3.2% 

1.31 (1.14,1.51] 



— ■ — 

75 

135 

144 

303 

2.8% 

1.17 (0.97,1.42] 




97 

181 

122 

257 

2.9% 

1.13(0.94,1.36] 




87 

164 

132 

274 

2.8% 

1.10(0.91,1.33] 




46 

80 

139 

290 

2.6% 

1.20(0.96,1.50] 




58 

107 

127 

263 

2.7% 

1.12(0.91,1.39] 




57 

104 

128 

266 

2.7% 

1.14 (0.92,1.41] 




1 6 

36 

24 

44 

1.4% 

0.81 (0.52,1.28] 




9 

24 

60 

114 

1.1% 

0.71 (0.41,1.23] 




98 

193 

166 

471 

2.9% 

1.44(1.20,1.73] 




73 

168 

113 

418 

2.5% 

1.61 (1.27,2.03] 




24 

9297 

77 

48522 

1.4% 

1.63(1.03,2.57] 




5 

28 

1 4 

205 

0.5% 

2.61 (1.02, 6.71] 




2 

9 

13 

176 

0.2% 

3.01 (0.80,11.37] 




231 

730 

1061 

5229 

3.3% 

1.56(1.38,1.76] 



— ■ — 

23 

522 

123 

4291 

1.5% 

1.54(0.99,2.38] 




75 

127 

175 

373 

2.9% 

1.26(1.05,1.51] 




1 

91 

406 

3 

1800 

0.1% 

1.48(0.15,14.17] ^ 




150 

185 

326 

3.0% 

1.07 (0.91,1.25] 




78 

126 

92 

213 

2.7% 

1.43(1.17,1.76] 




317 

40234 

432 

103243 

3.1% 

1.88(1.63,2.18] 



— ■ — 

347 

43775 

395 

99702 

3.1% 

2.00(1.73,2.31] 



— ■ — 

278 

40234 

449 

103243 

3.1% 

1.59(1.37,1.84] 



— 

327 

43775 

390 

99702 

3.1% 

1.91 (1.65,2.21] 



— ■ — 

125 

40234 

218 

103243 

2.6% 

1.47(1.18,1.83] 




140 

43775 

202 

99702 

2.7% 

1.58(1.27,1.96] 




90 

40234 

122 

103243 

2.3% 

1.89 (1.44,2.48] 




102 

43775 

111 

99702 

2.3% 

2.09(1.60,2.74] 




8 

262 

19 

1532 

0.6% 

2.46(1.09,5.57] 




26 

73 

725 

2982 

2.0% 

1.46(1.07,2.01] 




15 

56 

552 

2729 

1.4% 

1.32(0.85,2.05] 




21 

68 

487 

2744 

1.8% 

1.74(1.21,2.51] 




9 

50 

314 

2491 

0.9% 

1.43(0.78,2.60] 




24 

7137 

78 

45548 

1.4% 

1.96(1.24,3.10] 




112 

185 

207 

641 

3.0% 

1.87(1.60,2.20] 




67 

140 

135 

569 

2.6% 

2.02(1.61,2.53] 




17 

129 

6 

129 

0.5% 

2.83(1.15,6.96] 




37 

85 

43 

154 

1.8% 

1.56(1.10,2.21] 




46 

111 

21 

85 

1.5% 

1.68(1.09,2.58] 




39 

3179 

32 

2758 

1.3% 

1.06(0.66,1.68] 





361450 


940759 

100.0% 

1.46 [1.36,1.56] 



♦ 

4108 

<0.00001); 

9088 







= 44 (P 

r= 



0*5 

0*7 1 

1*5 2 

) 






Decrease CRC risk 

Increase CRC risk 


Figure 5 : Forest plot of association between MetS and CRC risk 


AC Adenocarcinoma, ATPIII (NCEP-ATPIII) National Cholesterol Education Program-Adult Treatment Panel III, CC Colon Cancer, Cl confidence interval, CRC 
Colorectal Cancer, IDF International Diabetes Foundation, M Men, RC Rectal Cancer, W Women. 


SE(log[RR]) 



O 




1.5 


0.1 


0.2 


0.5 


Figure 4 : Funnel plot of the association between MetS and CRC 


RR 

H- 

10 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 











































Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


39 


Differences between cohort, case-control, and cross- 
sectional studies were noticed. No significant 
heterogeneity was observed for cross-sectional studies (P 
= 0.68) and no evidence of publication bias was noticed 
(Figure 5). Positive and significant risk estimates were 
obtained for both Asian and European populations and 
for studies provided data for both sexes separately. 
Comparing studies using different definitions of MetS, 
studies using the harmonized definition and the other 
definitions had the lowest and the highest risk with no 
significant heterogeneity (RR = 1.22; 95% Cl = 1.07,1.38; P 
value for heterogeneity = 0.08) and (RR = 1.74; 95% Cl = 
1.58, 1.91; P value for heterogeneity = 0.32) respectively. 
Our results showed that the risk of developing rectal 
cancer is slightly lower than that of colon cancer with an 
RR of 1.45 (95% Cl = 1.29, 1.63) and 1.53 (95% Cl = 1.41, 
1.67) correspondingly. 

Colorectal adenomas versus colorectal cancer 

We weighted the association of MetS with CRA and CRC 
using the same datasets. Five studies reported data for 
both CRA and CRC. The comparison showed that the risk 
of developing CRC is 10% higher than the risk of 
developing CRA (RR = 1.48; 95% Cl = 1.20,1.82) and (RR = 
1.38; 95% Cl = 1.13,1.68) respectively. 

4. DISCUSSION 


Our meta-analysis of 35 studies provided evidence that 
metabolic syndrome increases the risk of colorectal 
neoplasm, especially for advanced adenoma and 
colorectal cancer. To sum up, the results showed 46% and 
43% increased CRC and CRA risk among subjects with 
MetS compared to those without MetS. 

Including different types of studies (cohort, case-control, 
and cross-sectional), MetS definition (NCEP/ATPIII, IDF, 
the harmonized, and other), gender (men and women), 
populations (Asia, Europe, and the USA), and the type and 
location of the lesion slightly influenced the risk estimates. 
Several factors and signaling pathways are reported to be 
implicated. The insulin receptor and the IGF-1 receptor are 
over-stimulated which reduces apoptosis and promotes 
cancer cells proliferation. Insulin favors type II T helper cell 
production by modulating the polarization of effector T 
cells which indirectly favors cancer cells progression and 
metastasis [^]. In a case-control study including 615 CRC 
patients and 650 control healthy individuals, high levels of 
IGF-1 were possibly linked with the initiation of CRC [ 591 . 
Moreover, the adipose tissue is the largest endocrine 
organ of the human body producing free fatty acids, 
different cytokines (interleukin 6, monocyte 


chemoattractant proteini, tumor necrosis factor-a) and 
hormones (leptin, aromatase, adiponectin, plasminogen 
activator inhibitor 1), which may be involved in cancer 
genesis and progression [ 60, 611 . 

TNF-a, IL-6, and IL-1p can promote pro-inflammatory 
gene expression and induce CRC cell lines to express a 
variety of cytokines and chemokines that recruit and 
activate APCs and granulocytes through numerous 
signaling pathways such as MARK-, JAK/STAT, and NF-k 
B- mediated signaling. Similarly, inflammation-induced 
DNA damage has been linked to altered expression of 
genes involved in CRC such as p53, ARC, KRAS, and BCL- 
2 [621. For instance, the expression of leptin in tissues of 
80 CRC patients was assessed in a research study and the 
results revealed that leptin affects CRC stem cells growth 
and survival and induces the activation of JAK and ERK 
signaling pathways that regulate the invasion and 
adhesion of these cells [ 631 . 

MetS is as well strongly associated with other types of 
cancer [^1. A study was undertaken in the USA has 
concluded that subjects with prostate cancer have a high 
prevalence of MetS [64]- In accordance, a Japanese 
retrospective cohort study endeavored to elucidate the 
relationship between MetS and the incidence of cancer 
found that MetS increased the risk of breast cancer and 
prostate cancer [ 651 . 

Although, epidemiological studies provide a strong 
evidence of an association between MetS and colorectal 
neoplasm, our understanding of the biological 
mechanism underlying this association is incomplete. This 
may be due to the complex pathophysiology and the 
numerous common factors such as those shared between 
both diseases [ 661 . 

Concerning incidence risk of CRC and MetS, our results 
agree with several studies. Although the incidence was 
low compared to our findings, Jinjuvadia et al. reported 
an increased risk of developing CRA, and CRC among 
MetS patients (RR = 1.37; 95% Cl = 1.26, 1.49) and (RR = 
1.30; 95% Cl = 1.18,1.43) respectively [6Z1. 

Esposito et al. observed, in a meta-analysis of 17 studies, 
that MetS was linked with a higher incidence of CRC for 
women compared to men (RR = 1.41; 95% Cl = 1.18, 1.70) 
for women and (RR = 1.33; 95% Cl = 1.18, 1.50) for men 
[681 which is consistent with our results (RR = 1.47; 95% 
Cl=1.32, 1.63) for women and (RR = 1.41; 95% Cl = 1.25, 
1.60) for men, though the difference in the magnitude of 
the risk estimate. 

To the best of our knowledge, our meta-analysis could be 
the first investigating the association between MetS and 
CRA incidence. 

There were some potential limitations in the current study 
such as the loss of some studies due to inclusion criteria. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 





Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


40 


where non-English articles were excluded. Nevertheless, 
we found only one Chinese case-control study (included 
135 CRC cases and 120 controls) that met the inclusion 
criteria [^]. There were 46 and 27 MetS patients in the 
case and control groups respectively. Some analyses 
showed evidence of heterogeneity. However, subgroup 
analysis demonstrated sources of heterogeneity. 
Furthermore, heterogeneity could be attributable to using 
different definitions of MetS and including cohorts and 
non-cohorts in the analyses. 

5. CONCLUSION 


In conclusion, our meta-analysis showed that MetS is 
associated not only with colorectal cancer but with earlier 
precancerous conditions such as colorectal adenomas 
and advanced adenomas too. Those conditions are the 
primary targets for screening programs aiming for an 
early detection and prevention of this malignancy. 
Patients with MetS should be included in such programs. 
Besides, subjects with MetS should consider lifestyle 
modifications like weight loss, physical activity, and diet 

[17, _ 70], along with management of its individual 

components. The implication of some pharmacological 
treatments with CRC development should be taking into 
consideration [ 71, 721 . 

6. REFERENCES 


1. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer 
incidence and mortality worldwide: Sources, 
methods and major patterns in GLOBOCAN 2012: 
Globocan 2012. IntJ Cancer. 2015;136(5):E359-E386. 
doi:10.1002/ijc.29210. 

2. Moore JS, Aulet TH. Colorectal Cancer Screening. 
Adv Colorectal Neoplasia. 2017;97(3):487-502. 
doi:10.1016/j.suc.2017.01.001. 

3. Johnson CM, Wei C, Ensor JE, et al. Meta-analyses 
of colorectal cancer risk factors. Cancer Causes 
Control. 2013;24(6):1207-1222. doi:10.1007/s10552- 
013-0201-5. 

4. Kuipers EJ, Grady WM, Lieberman D, et al. 
COLORECTAL CANCER. Nat Rev Dis Primer. 
2015,1:15065. doi10.1038/nrdp.2015.65. 

5. Aran V, Victorino AP, Thuler LC, Ferreira CG. 

Colorectal Cancer: Epidemiology, Disease 

Mechanisms and Interventions to Reduce Onset 
and Mortality. Clin Colorectal Cancer. 
201615(3)195-203. doi10.1016/j.clcc.2016.02.008. 

6. Carrer A, Giacca M, Giacca M. Molecular Parameters 
for Prognostic and Predictive Assessment in 


Colorectal Cancer. In: de Manzini N, ed. Rectal 
Cancer. Milano: Springer Milan; 2013:41-62. 
doi:10.1007/978-88-470-2670-4_4. 

7. Jess T, Rungoe C, Peyrin-Biroulet L. Risk of 
Colorectal Cancer in Patients With Ulcerative Colitis: 
A Meta-analysis of Population-Based Cohort 
Studies. Clin Gastroenterol Hepatol. 2012;10(6):639- 
645. doi101016/j.cgh.2012.01.010. 

8. Colussi D, Brandi G, Bazzoli F, Ricciardiello L. 
Molecular Pathways Involved in Colorectal Cancer: 
Implications for Disease Behavior and Prevention. 
Int J Mol Sci. 201314(8)16365-16385. 
doi10.3390/ijms140816365. 

9. Zhu B, Sun Y, Qi L, Zhong R, Miao X. Dietary legume 
consumption reduces risk of colorectal cancer: 
evidence from a meta-analysis of cohort studies. Sci 
Rep. 2015;5:8797. doi101038/srep08797. 

10. Godos J, Bella F, Torrisi A, Sciacca S, Galvano F, 
Grosso G. Dietary patterns and risk of colorectal 
adenoma: a systematic review and meta-analysis of 
observational studies. J Hum Nutr Diet. 
2016;29(6):757-767. doi101111/jhn12395. 

11. Vieira AR, Abar L, Chan D, et al. Foods and 
beverages and colorectal cancer risk: a systematic 
review and meta-analysis of cohort studies, an 
update of the evidence of the WCRF-AICR 
Continuous Update Project. Ann Oncol Off J Fur Soc 
Med Oncol. April 2017. doi:10.1093/annonc/mdx171. 

12. Tsoi KKF, Pau CYY, Wu WKK, Chan FKL, Griffiths S, 
Sung JJY. Cigarette Smoking and the Risk of 
Colorectal Cancer: A Meta-analysis of Prospective 
Cohort Studies. Clin Gastroenterol Hepatol. 
2009;7(6):682-688.e5. doi:101016/j.cgh.2009.02.016. 

13. Zhou X-Y, Yan L, Wang L-L, Wang J. Association 

between physical activity and colorectal cancer risk 
and prognosis: A meta-analysis. Cancer Treat Res 
Commun. 2016;9:62-69. 

doi101016/j.ctarc.2016.07.002. 

14. Kort S de, Masclee AAM, Sanduleanu S, et al. Higher 
risk of colorectal cancer in patients with newly 
diagnosed diabetes mellitus before the age of 
colorectal cancer screening initiation. Sci Rep. 
2017,7:46527. doi:10.1038/srep46527. 

15. Ishino K, Mutoh M, Totsuka Y, Nakagama H. 
Metabolic syndrome: a novel high-risk state for 
colorectal cancer. Cancer Lett. 2013;334(1):56-61. 
doi101016/j.canlet.201210.012. 

16. The International Diabetes Federation (IDF). IDF 
Consensus Worldwide Definition of the Metabolic 
Syndrome. https://idf.org/e-library/consensus- 
statements/60-idfconsensus-worldwide- 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 







Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


41 


definitionof-the-metabolic-syndrome. Published 
2006. Accessed July 17, 2017. 

17. Kaur J. A Comprehensive Review on Metabolic 
Syndrome. Cardiol Res Pract. 2014;2014:e943162. 
doi:10.1155/2014/943162. 

18. Sorrentino MJ. The Metabolic Syndrome. In: 

Sorrentino MJ, ed. Hyperlipidemia in Primary Care: 
A Practical Guide to Risk Reduction. Totowa, NJ: 
Humana Press; 2011:13-39. doi:10.1007/978-1- 

60327-502-6_2. 

19. LeRoith D, Vinik Al, eds. Controversies in Treating 
Diabetes. Totowa, NJ: Humana Press; 2008. 
doi:10.1007/978-1-59745-572-5. 

20. Lu Y, Ness-Jensen E, Hveem K, Martling A. 
Metabolic Predispositions and Increased Risk of 
Colorectal Adenocarcinoma by Anatomical 
Location: A Large Population-Based Cohort Study in 
Norway. Am J Epidemiol. 2015;182(10):883-893. 
doi:10.1093/aje/kwv141. 

21. Tsilidis KK, Brancati FL, Poliak MN, et al. Metabolic 
syndrome components and colorectal adenoma in 
the CLUE II cohort. Cancer Causes Control CCC. 
2010;21(1):1-10. doi:10.1007/s10552-009-9428-6. 

22. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred 
Reporting Items for Systematic Reviews and Meta- 
Analyses: The PRISMA Statement. J Clin Epidemiol. 
2009;62(10):1006-1012. 
doi:10.1016/j.jclinepi.2009.06.005. 

23. Borenstein M, Hedges LV, Higgins JPT, Rothstein 
HR. A basic introduction to fixed-effect and 
random-effects models for meta-analysis. Res Synth 
Methods. 2010;1(2):97-111. doi:10.1002/jYsm.12. 

24. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. 
Measuring inconsistency in meta-analyses. BMJ. 
2003;327(7414):557. doi:10.1136/bmj.327.7414.557. 

25. Chiu H-M, Lee Y-C, Tu C-H, et al. Effects of 
Metabolic Syndrome and Findings From Baseline 
Colonoscopies on Occurrence of Colorectal 
Neoplasms. Clin Gastroenterol Hepatol. 
2015;13(6):1134-1142.e8. 
doi:10.1016/j.cgh.2014.10.022. 

26. Lin X-F, Shi K-Q, You J, et al. Increased risk of 
colorectal malignant neoplasm in patients with 
nonalcoholic fatty liver disease: a large study. Mol 
Biol Rep. 2014;41(5):2989-2997. doi:10.1007/s11033- 
014-3157-y. 

27. Kruijsdijk RCM van, Graaf Y van der, Peeters PHM, 
Visseren FLJ, Group on behalf of the SM of Art 
disease (SMART) study. Cancer Risk in Patients with 
Manifest Vascular Disease: Effects of Smoking, 
Obesity, and Metabolic Syndrome. Cancer 


Epidemiol Prev Biomark. 2013;22(7):1267-1277. 
doi:10.1158/1055-9965.EPI-13-0090. 

28. Huang K-W, Leu H-B, Wang Y-J, et al. Patients with 

nonalcoholic fatty liver disease have higher risk of 
colorectal adenoma after negative baseline 

colonoscopy. Colorectal Dis Off J Assoc 
Coloproctology G B Irel. 2013;15(7):830-835. 
doi:10.1111/codi.12172. 

29. Kim BC, Shin A, Hong CW, et al. Association of 

colorectal adenoma with components of metabolic 
syndrome. Cancer Causes Control CCC. 

2012;23(5):727-735. doi:10.1007/s10552-012-9942-9. 

30. Kaneko R, Sato Y, An Y, et al. Clinico-epidemiologic 
study of the metabolic syndrome and lifestyle 
factors associated with the risk of colon adenoma 
and adenocarcinoma. Asian Pac J Cancer Prev 
APJCP. 2010;11(4):975-983. 

31. Liu C-S, Hsu H-S, Li C-l, et al. Central obesity and 
atherogenic dyslipidemia in metabolic syndrome 
are associated with increased risk for colorectal 
adenoma in a Chinese population. BMC 
Gastroenterol. 2010,10:51. doi10.1186/1471-230X-10- 
51. 

32. Harlid S, Myte R, Van Guelpen B. The Metabolic 
Syndrome, Inflammation, and Colorectal Cancer 
Risk: An Evaluation of Large Panels of Plasma 
Protein Markers Using Repeated, Prediagnostic 
Samples. Mediators Inflamm. 2017;2017:4803156. 
doilO.1155/2017/4803156. 

33. Pyo JH, Hong SN, Min B-H, et al. Evaluation of the 
risk factors associated with rectal neuroendocrine 
tumors: a big data analytic study from a health 
screening center. J Gastroenterol. 2016;51(12):1112- 
1121. doi10.1007/s00535-016-1198-9. 

34. Pyo JH, Hong SN, Min B-H, et al. Is height a risk 
factor for colorectal adenoma? Korean J Intern Med. 
2016;31(4):653-659. doi10.3904/kjim.2014.313. 

35. Hong SN, Lee TY, Yun S-C. The Risk of Colorectal 
Neoplasia in Patients with Gallbladder Diseases. J 
Korean Med Sci. 2015;30(9)1288-1294. 
doi10.3346/jkms.2015.30.9.1288. 

36. Trabulo D. Metabolic syndrome and colorectal 

neoplasms: An ominous association. World J 
Gastroenterol. 2015;21(17):5320. 

doi10.3748/wjg.v21.i17.5320. 

37. Jeon YJ, Kim JW, Park HM, et al. Interplay between 
3'-UTR polymorphisms in the vascular endothelial 
growth factor (VEGF) gene and metabolic syndrome 
in determining the risk of colorectal cancer in 
Koreans. BMC Cancer. 201414:881. doi101186/1471- 
2407-14-881. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 



Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


42 


38. Ulaganathan V, Kandiah M, Zalilah MS, et al. 
Colorectal cancer and its association with the 
metabolic syndrome: a Malaysian multi-centric 
case-control study. Asian Pac J Cancer Prev APJCP. 
2012;13(8):3873-3877. 

39. Danese E, Montagnana M, Minicozzi AM, et al. The 
role of resistin in colorectal cancer. Clin Chim Acta 
Int J Clin Chem. 2012;413(7-8):760-764. 
doi:10.1016/j.cca.2012.01.019. 

40. Kontou N, Psaltopoulou T, Soupos N, et al. 
Metabolic syndrome and colorectal cancer: the 
protective role of Mediterranean diet—a case- 
control study. Angiology. 2012;63(5):390-396. 
doi:10.1l77/0003319711421164. 

41. Aleksandrova K, Boeing H, Jenab M, et al. Metabolic 

Syndrome and Risks of Colon and Rectal Cancer: 
The European Prospective Investigation into Cancer 
and Nutrition Study. Cancer Prev Res (Phila Pa). 
2011;4(11):1873. doi:10.1158/1940-6207.CAPR-11- 

0218. 

42. Shen Z, Wang S, Ye Y, et al. Clinical study on the 
correlation between metabolic syndrome and 
colorectal carcinoma. ANZ J Surg. 2010;80(5):331- 
336. doi:10.1111/j.1445-2197.2009.05084.x. 

43. Pelucchi C, Negri E, Talamini R, et al. Metabolic 
syndrome is associated with colorectal cancer in 
men. Eur J Cancer. 2010;46(10):1866-1872. 
doi:10.1016/j.ejca.2010.03.010. 

44. Kang HW, Kim D, Kim HJ, et al. Visceral Obesity and 
Insulin Resistance as Risk Factors for Colorectal 
Adenoma: A Cross-Sectional, Case-Control Study. 
Am J Gastroenterol. 2009;105(1):178-187. 
doi:10.1038/ajg.2009.541. 

45. Pan S, Hong W, Wu W, et al. The relationship of 
nonalcoholic fatty liver disease and metabolic 
syndrome for colonoscopy colorectal neoplasm. 
Zarko. B, ed. Medicine (Baltimore). 
2017;96(2):e5809. 

doi:10.1097/MD.0000000000005809. 

46. Koo JE, Kim K-J, Park HW, et al. Prevalence and risk 
factors of advanced colorectal neoplasms in 
asymptomatic Korean people between 40 and 
49 years of age. J Gastroenterol Hepatol. 
2017;32(1):98-105. doi:10.1111/jgh.13454. 

47. Kim HJ, Kim JE, Jung JH, et al. Uric Acid Is a Risk 
Indicator for Metabolic Syndrome-related 
Colorectal Adenoma: Results in a Korean Population 
Receiving Screening Colonoscopy. Korean J 
Gastroenterol Taehan Sohwagi Hakhoe Chi. 
2015;66(4):202-208. doi:10.4166/kjg.2015.66.4.202. 

48. Jung YS, Yun KE, Chang Y, et al. Risk factors 
associated with rectal neuroendocrine tumors: a 


cross-sectional study. Cancer Epidemiol Biomark 
Prev PubI Am Assoc Cancer Res Cosponsored Am 
Soc Prev Oncol. 2014;23(7):1406-1413. 
doi:10.1158/1055-9965.EPI-14-0132. 

49. Chang L-C, Wu M-S, Tu C-H, Lee Y-C, Shun C-T, 
Chiu H-M. Metabolic syndrome and smoking may 
justify earlier colorectal cancer screening in men. 
Gastrointest Endosc. 2014;79(6):961-969. 
doi:10.1016/j.gie.2013.11.035. 

50. Lee CG, Hahn SJ, Song MK, et al. Vegetarianism as 

a Protective Factor for Colorectal Adenoma and 
Advanced Adenoma in Asians. Dig Dis Sci. 
2014;59(5):1025-1035. doi:10.1007/s10620-013- 

2974-5. 

51. Sato T, Takeda H, Sasaki Y, Kawata S. Increased 
homeostasis model assessment-insulin resistance is 
a risk factor for colorectal adenoma in Japanese 
males. Tohoku J Exp Med. 2011;223(4):297-303. 

52. Hu N-C, Chen J-D, Lin Y-M, Chang J-Y, Chen Y-H. 

Stepwise Relationship Between Components of 
Metabolic Syndrome and Risk of Colorectal 
Adenoma in a Taiwanese Population Receiving 
Screening Colonoscopy. J Formos Med Assoc. 
2011;110(2):100-108. doi:10.1016/S0929- 

6646(11)60016-8. 

53. Yang SY, Kim YS, Chung SJ, et al. Association 
between colorectal adenoma and coronary 
atherosclerosis detected by CT coronary 
angiography in Korean men; a cross-sectional 
study. J Gastroenterol Hepatol. 2010;25(11):1795- 
1799. doi:10.1111/j.1440-1746.2010.06330.x. 

54. Hong SN, Kim JH, Choe WH, et al. Prevalence and 
risk of colorectal neoplasms in asymptomatic, 
average-risk screenees 40 to 49 years of age. 
Gastrointest Endosc. 2010;72(3):480-489. 
doi:10.1016/j.gie.2010.06.022. 

55. Hwang ST, Cho YK, Park JH, et al. Relationship of 

non-alcoholic fatty liver disease to colorectal 
adenomatous polyps. J Gastroenterol Hepatol. 
2010;25(3):562-567. doi:10.1111/j.1440- 

1746.2009.06117.x. 

56. Oh T-H, Byeon J-S, Myung S-J, et al. Visceral obesity 
as a risk factor for colorectal neoplasm. J 
Gastroenterol Hepatol. 2008;23(3):411-417. 
doi:10.1111/j.1440-1746.2007.05125.x. 

57. Kim JH, Lim YJ, Kim Y-H, et al. Is Metabolic 
Syndrome a Risk Factor for Colorectal Adenoma? 
Cancer Epidemiol Prev Biomark. 2007;16(8):1543- 
1546. 

58. Mendonga FM, de Sousa FR, Barbosa AL, et al. 
Metabolic syndrome and risk of cancer: Which link? 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02 



Elharag et al.: Metabolic Syndrome and Colorectal Cancer 


43 


Metabolism. 2015;64(2):182-189. 

doi:10.1016/j.metabol.2014.10.008. 

59. Jiang B, Zhang X, Du L-L, et al. Possible roles of 

insulin, IGF-1 and IGFBPs in initiation and 
progression of colorectal cancer. World J 
Gastroenterol. 2014;20(6):1608-1613. 

doi:10.3748/wjg.v20.i6.1608. 

60. Beck-Nielsen H, ed. The Metabolic Syndrome. 
Vienna: Springer Vienna; 2013. doi:10.1007/978-3- 
7091-1331-8. 

61. Pietrzyk L, Torres A, Maciejewski R, Torres K. Obesity 
and Obese-related Chronic Low-grade 
Inflammation in Promotion of Colorectal Cancer 
Development. Asian Pac J Cancer Prev APJCP. 
2015;16(10):4161-4168. 

62. Doerner SK, Heaney JD. Inflammation, Obesity, and 
Colon Cancer. In: Dannenberg AJ, Berger NA, eds. 
Obesity, Inflammation and Cancer. New York, NY: 
Springer New York; 2013:147-180. doi:10.1007/978- 
1-4614-6819-6_7. 

63. Yoon K-W, Park S-Y, Kim J-Y, et al. Leptin-induced 
adhesion and invasion in colorectal cancer cell lines. 
Oncol Rep. 2014;31(6):2493-2498. 

64. Yaturu S, Fort C. Prostate cancer is associated with 
the metabolic syndrome. J Mens Health. 
2009;6(2):125-129. doi:10.1016/j.jomh.2009.01.005. 

65. Osaki Y, Taniguchi S, Tahara A, Okamoto M, 
Kishimoto T. Metabolic syndrome and incidence of 
liver and breast cancers in Japan. Cancer Epidemiol. 
2012;36(2):141-147. doi:10.1016/j.canep.2011.03.007. 

66. Suchanek S, Grega T, Ngo O, et al. How significant 

is the association between metabolic syndrome and 
prevalence of colorectal neoplasia? World J 
Gastroenterol. 2016;22(36):8103-8111. 

doi:10.3748/wjg.v22.i36.8103. 


67. Jinjuvadia R, Lohia P, Jinjuvadia C, Montoya S, 

Liangpunsakul S. The Association between 
Metabolic Syndrome and Colorectal Neoplasm: 
Systemic review and Meta-analysis. J Clin 
Gastroenterol. 2013;47(1):33-44. 

doi:10.1097/MCG.0b013e3182688c15. 

68. Esposito K, Chiodini P, Capuano A, et al. Colorectal 
cancer association with metabolic syndrome and its 
components: a systematic review with meta¬ 
analysis. Endocrine. 2013;44(3):634-647. 
doi:10.1007/s12020-013-9939-5. 

69. Wu Q, Wu Q, Zhang A. [Metabolic disturbance and 
insulin resistance in patients with colorectal cancer]. 
Zhonghua Wei Chang Wai Ke Za Zhi Chin J 
Gastrointest Surg. 2011;14(4):261-263. 

70. Inoue K, Maeda N, Funahashi T. Metabolic 
Syndrome. In: Lammert E, Zeeb M, eds. Metabolism 
of Human Diseases: Organ Physiology and 
Pathophysiology. Vienna: Springer Vienna; 
2014:199-203. doi:10.1007/978-3-7091-0715-7_30. 

71. Kithcart AP, Curigliano G, Beckman JA. Treatment of 
Hypertension in Patients Receiving Cancer Therapy. 
In: Kimmick GG, Lenihan DJ, Sawyer DB, Mayer EL, 
Hershman DL, eds. Cardio-Oncology: The Clinical 
Overlap of Cancer and Heart Disease. Cham: 
Springer International Publishing; 2017:105-123. 
doi:10.1007/978-3-319-43096-6_5. 

72. Nie Z, Zhu H, Gu M. Reduced colorectal cancer 

incidence in type 2 diabetic patients treated with 
metformin: a meta-analysis. Pharm Biol. 

2016;54(11):2636-2642. 
doi:10.1080/13880209.2016.1176057. 


Cite this article as: Elharag SE, Traore Y, and Khaled MB. Metabolic Syndrome and Risk of Colorectal Adenoma and Cancer: A Meta-Analysis. 
Nor. Afr. J. Food Nutr Res. July - December (2017); 01 (02): 30-43. 


Nor. Afr. J. Food Nutr. Res. I July-December 2017 I Volume 01 I Issue 02