Adiposity and the risk of colorectal adenomatous polyps: a meta ...

Cancer Causes Control (2011) 22:1021–1035 DOI 10.1007/s10552-011-9777-9

ORIGINAL PAPER

Adiposity and the risk of colorectal adenomatous polyps: a meta-analysis Yeon Ji Lee • Seung-Kwon Myung • BeLong Cho • Byung-Joo Park • Jin Ho Park Woong Ju • Min-Sun Park • Ji-Ho Choi

•

Received: 6 December 2010 / Accepted: 7 May 2011 / Published online: 22 May 2011 Ó Springer Science+Business Media B.V. 2011

Abstract Objective The findings from epidemiological studies addressing the association between adiposity and the risk of colorectal adenomatous polyps are inconsistent. We performed a meta-analysis of epidemiological studies including cross-sectional, case–control, and cohort studies. Methods We searched PubMed and EMBASE in June, 2010. All searched articles were reviewed and selected independently by two evaluators according to pre-determined selection criteria. Results We included 25 studies (nine cross-sectional studies, eleven case–control studies, and five prospective cohort studies) that comprised a total of 300,671 participants and 20,903 cases in the final analysis. When all studies were pooled, the odds ratio (OR) or relative risk

(RR) of adiposity and abdominal adiposity for colorectal adenomatous polyp risk was 1.43 (95% confidence interval (CI) 1.23–1.67; n = 22) and 1.42 (95% CI 1.30–1.56; n = 12), respectively. Similarly, an increased risk of colorectal adenomatous polyps was observed in most of the subgroup meta-analyses. Conclusions Overall, we found that adiposity and abdominal adiposity significantly increased the risk of colorectal adenomatous polyps in a meta-analysis of epidemiological studies. Keywords Adiposity Abdominal adiposity Colorectal adenomatous polyps Meta-analysis

Introduction Y. J. Lee J.-H. Choi Department of Family Medicine, School of Medicine, Inha University, Incheon, Republic of Korea S.-K. Myung (&) Cancer Epidemiology Branch, Research Institute, Smoking Cessation Clinic, Family Medicine Clinic, and Center for Cancer Prevention and Detection, Hospital, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang, Gyeonggi-do 410-769, Republic of Korea e-mail: [email protected] B. Cho J. H. Park M.-S. Park Health Promotion Center, Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea B.-J. Park Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea W. Ju Department of Obstetrics and Gynecology, School of Medicine, Ewha Womans University, Seoul, Republic of Korea

Malignant transformation of the colorectal epithelium typically takes place as a multistep, multipath, and multifocal process that requires gradual and cumulative damage to serial genes within and across cellular generations [1]. This adenoma-carcinoma sequence, the progression from normal mucosa to small adenomatous polyps to larger adenomas and those with advanced histological features to an invasive cancer, is a principle of our understanding and management of colorectal adenomatous polyps [2]. During this malignant transformation, various modifiable lifestylerelated risk factors including adiposity are estimated to account for up to 90% of colorectal cancers (CRCs) and adenomatous polyps [3]. In addition, CRC is the third most common cancer worldwide [4], and it is the second leading cause of cancer mortality in the United States [5]. With regard to the growing prevalence of obesity worldwide, the contribution of obesity to the development of colorectal adenomatous polyps and invasive colon cancer could

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constitute a significant proportion of the global burden of CRC mortality and morbidity. As for the association between adiposity and colorectal adenomatous polyps, epidemiological studies [6–30] such as cross-sectional studies, case–control studies, and cohort studies have reported the association between adiposity and risk of colorectal adenomatous polyps. Even though most studies supported a positive association, some of these studies [6, 11, 14–19, 21, 22, 24–29] showed nonsignificant associations either in the main analysis of total population or in subgroup analyses. To date, however, there has been no meta-analysis that has quantitatively analyzed the effect of adiposity on the risk of incidence of colorectal adenomatous polyps. The purpose of the current study was to investigate the association between adiposity and the risk of colorectal adenomatous polyps using a meta-analysis of epidemiological studies such as cross-sectional, case–control, and cohort studies.

Methods Data sources and keywords PubMed (1964 to June 2010) and EMBASE (1975 to June 2010) were searched by using selected common key words regarding adiposity and colorectal adenomatous polyps in epidemiological studies such as cross-sectional studies, case–control studies, and cohort studies. Inserted keywords were as follows; ‘‘obesity or body-mass index (BMI) or overweight’’ for the exposure factors and ‘‘colonic polyp or adenomatous polyp or colorectal adenomatous polyp’’ for the outcome factors. These searches were performed by one of the authors (Dr. Lee YJ) and then confirmed by another author (Dr. Myung SK). The bibliographies of relevant articles were also scanned to identify additional studies. Selection criteria We included cross-sectional, case–control, and cohort studies reporting an association between adiposity and colorectal adenomatous polyp risk using adjusted odds ratios (ORs) or relative risks (RRs). The selected studies should have shown a quantitative definition of adiposity or abdominal adiposity group and included the subjects who had never been diagnosed with adenomatous polyps before the study started. Excluded studies were those with no available data for exposure or outcome measures, studies reporting only unadjusted ORs or RRs, and studies concerning hyperplastic polyps of colon and recurrence or

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growth of adenomatous polyps. As well, studies with the intervention for chemoprevention of CRC were excluded. Selection of relevant studies All studies retrieved from databases and bibliographies were independently evaluated by the aforementioned authors. When there were disagreements between evaluators concerning the selected studies, the two authors reached a consensus following discussion of the issue. Of all articles found in the two databases, duplicate articles and those that did not meet the selection criteria were excluded. After these processes, a total of 25 studies were selected (nine cross-sectional studies published between 1993 and 2009, eleven case–control studies published between 1991 and 2009, and five prospective cohort studies published between 1995 and 2008). The following data was extracted from the included studies: last name of the first author and year of publication, journal name, country and design, enrollment or follow-up periods, population characteristics and range of age, measurement of adiposity, OR or RR with 95% CI, and adjustment factors. Data abstraction was also done in duplicate as was study selection. Assessment of methodological quality The methodological quality of included case–control and cohort studies was assessed based on the Newcastle– Ottawa Scale (NOS) for quality of nonrandomized studies in meta-analyses [31]. Among several quality assessment tools for observational studies, the NOS is quite comprehensive for assessing the quality of non-randomized studies in metaanalyses. The NOS for nonrandomized studies, including case–control and cohort studies, consists of eight items with three subscales: the selection of the study groups (four items, one star each), the comparability of the groups (one item up to two stars), and the ascertainment of either the exposure or outcome of interest for case–control or cohort studies respectively (three items, one star each). A ‘‘star’’ system of the NOS (range 0–9 stars) was developed for the assessment: each study could be awarded a maximum of one star for each numbered item within the selection and exposure categories, while a maximum of two stars could be given for the comparability category. In this study, after independent assessment and discussion by the two authors(Dr. Lee YJ, and Dr. Ju W), the mean value for all the studies assessed was 6.6 stars, comprising 6.8 for the case–control studies and 6.2 for the cohort studies. Based on the mean value in the current study, a study awarded 7 or more stars was considered a high-quality study, as standard criteria had not been


established. The quality of cross-sectional studies was not assessed because there is no proper assessment tool for cross-sectional studies. Statistical analyses Adjusted data (adjusted OR or RR with a 95% CI) was used for the meta-analysis. The main analysis was to estimate the association between adiposity or abdominal adiposity and the incidence of colorectal adenomatous polyps. The definition of adiposity varied from study to study and from population to population. In the current study, most of the studies published before 2005 and all cohort studies used percentile values of BMI as the cut-off value of adiposity (we considered the highest percentile group as having adiposity), which were diverse between 27 and 35 kg/m2. On the other hand, studies published in the year 2005 or later generally used a fixed cut-off value of BMI for the definition of adiposity corresponding with the WHO BMI guidelines, which is 30 kg/m2 or more. However, there have been debates about the obese BMI cut-offs in Asian and Pacific populations because the proportion of Asians with a high risk of type 2 diabetes and cardiovascular disease is substantial at the BMI values lower than the WHO’s cut-off point for overweight (25 kg/m2) [32]. For this reason, the Korean Society for the Study of Obesity and the Japanese Society for the Study of Obesity accepted a BMI of 25 kg/m2 as a cut-off for Koreans and Japanese. According to this criteria, studies like Kim et al. [8], Chung et al. [23], and Omata et al. [25] used a BMI of 25 kg/m2 or greater as the definition of obesity, and our study also followed it. Adiposity was defined by body mass index (BMI) which is obtained by dividing a bodyweight in kilograms by the square of height in meters, and abdominal adiposity was defined by waist circumference (WC) or waist-to-hip ratio (WHR). Also, subgroup analyses were conducted by gender, study design, region of the world, size or histology of polyps, methodological quality of study, year of publication, method of abdominal adiposity classification, site of colon polyps, and collection method for anthropometric data. Regarding a dose–response relationship, to test for linear trend, a weighted linear regression was performed to model the natural logarithm (LN) of OR or RR for the risk of adenomatous colon polyp as severity of adiposity defined by BMI (low = 1, moderate = 2, and the highest = 3) using the inverse variance calculated from confidence intervals of each category; the standard error (SE) for the LN of the OR or RR was estimated as {LN(upper limit)LN(lower limit)}/2 9 1.96, and the inverse variance as 1/SE2. Highest adiposity was defined as BMI [ 35 for European or American populations and BMI [ 30 for

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Asian populations; moderate adiposity as BMI [ 30 for European or American populations and BMI [ 25 for Asian populations; lower adiposity as BMI [ 25 for European or American populations and BMI [ 23 for Asian populations, respectively, based on the WHO obesity guidelines and Asia–pacific standard as described above. In order to combine effect sizes across studies, it was decided whether a random or fixed effect model is appropriate for the selected studies by evaluating the heterogeneity of the studies using Higgins I2, which measures the percentage of total variation across studies. I2 is calculated as follows: I 2 ¼ 100% ðQ df Þ=Q; where Q is the Cochran’s heterogeneity statistic and df is degrees of freedom. Negative values of I2 are set at zero so that I2 exists between 0% (no observed heterogeneity) and 100% (maximal heterogeneity) [33]. An I2 value [ 50% represents substantial heterogeneity. A pooled OR or RR with 95% CI was estimated based on both fixed-effects and random-effects models. When substantial heterogeneity was not observed (i.e., if I2 B 50%), the pooled estimate calculated based on the fixed-effects model was reported. When substantial heterogeneity was observed (i.e., if I2 [ 50%), the pooled estimate calculated based on the random-effects model was reported. The Woolf method (inverse variance method) was used for a fixed-effects analysis [34], and the DerSimonian [35] and Laird method was used for a random-effects analysis. Begg’s funnel plot and Egger’s test were used to identify publication bias. If there is publication bias, the funnel plot is asymmetrical or the p-value is \0.05 by Egger’s test. The analyses used Stata SE version 10.0 software package (StataCorp, College Station, TX, USA).

Results Selection of studies Out of the 347 articles that were initially searched, a total of 25 studies [6–30] were included in the final analysis. The 25 studies comprised nine cross-sectional studies, eleven case–control studies, and five prospective cohort studies; they were published between 1991 and 2009 and involved a total of 300,671 participants with 20,903 cases. Figure 1 shows a flow diagram of the procedure used to identify the relevant studies. Searches of the two databases and the bibliographies of relevant articles yielded 347 articles. After the exclusion of duplicates (n = 66), the remaining 281 screened articles were reviewed. Of these, 229 were excluded because they did not meet the selection

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criteria. After the full texts of the remaining 52 articles were reviewed, 25 articles were included in the final analysis. The main reasons for the exclusion of 27 studies during the final review were insufficient data on adiposity state (n = 14), studies involving study subjects with a history of polyps (n = 4), studies about chemoprevention of colon polyps (n = 4), study involving hyperplastic polyps (n = 2), a study using unadjusted data (n = 2) and a study written in Chinese (n = 1). Characteristics of studies included in the final analysis Table 1 shows the main characteristics of all 25 studies included in the final analysis. Anthropometric factors were measured directly by trained workers in eleven studies [7–13, 18, 19, 23, 29], while self-reported body size information was used in other 14. One study [25] included adenomatous polyp cases that proved to contain adenocarcinoma tissue in their analysis of the risk of colorectal neoplasia, while the proportion of cases of adenocarcinoma was negligible (19 CRC out of 870 colorectal neoplasia cases). Two studies [11, 23] analyzed only advanced adenomas excluding small or non-multiple adenomatous polyps. The countries in which studies had been conducted were Germany (n = 1) [6], Japan (n = 4) [7, 9, 18, 25], South Korea (n = 4) [8, 12, 13, 23], Taiwan (n = 1) [10], the United States (n = 12) [11, 14, 15, 17, 21, 22, 24,

26–30], Denmark (n = 1) [16], Norway (n = 1) [19], and France (n = 1) [20]. Six studies [15, 17, 18, 21, 23, 25] had hospital-based case–control designs. Five [16, 19, 20, 22, 24] were population-based case–control studies, and all the cohort studies [26–30] were prospectively designed and conducted in the United States. The range of enrollment periods for participants was 1976–2005, and the information about enrollment periods of three case–control studies [19, 20, 25] were not available. The age range of enrolled populations was between 21 and 84 years. Concerning the examination method of colonoscopy and the site of polyps, five studies [7, 10, 14, 17, 27] analyzed distal or left side colorectal adenomas with sigmoidoscopy, and one study [28] analyzed either total colon or distal colorectal polyps without distinguishing colonoscopy or sigmoidoscopy. Adiposity and the risk of colorectal adenomatous polyps Figure 2 shows the association between adiposity and colorectal adenomatous polyp risk in a meta-analysis of 22 studies that showed adiposity status defined by BMI, which included seven cross-sectional studies, eleven case–controls studies, and four prospective cohort studies. In those 22 studies, adiposity was associated with an increased risk

Identified studies from the databases using the keywords and the bibliographies of relevant articles (n = 332): PubMed (n = 142), EMBASE (n =189), and Bibliographies (n = 16)

Excluded with duplicates (n = 66)

Articles after excluded duplicates (n = 281)

Excluded according to selection criteria during 1 st screening (n = 229)

Articles reviewed including the full text (n = 52)

Excluded articles (n = 27): Insufficient data on adiposity (n = 14) Studies involving study subjects with a history of polyps (n = 4) Studies about chemoprevention of polyps (n = 4) Studies involving hyperplastic polyp (n = 2) Unadjusted data used (n = 2) An article written in Chinese (n = 1) Studies included in the final analysis (n = 25): Cross-sectional studies (n = 9), Case-control studies (n = 11), and cohort studies (n = 5)

Fig. 1 Flow diagram of identification of relevant studies

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Journal

Nation; design

Japan

Taiwan

USA

Jpn J Cancer Res

J Prev Med Public Health

Asian Pac J Cancer Prev

J Gastr Hep

J Clin Gastoenterol

Shinchi et al. [7]

Kim et al. [8]

Morita et al. [9]

Wang et al. [10]

Anderson et al.

South Korea

2005

Obesity

[13] (40–70)

689 cases among 1,898 men

(51.8 ± 7.9)

Lee et al.

[12]

2004–2005

731 cases among 2,531 persons

South Korea

Cancer Epidem Biomar

Kim et al.

236 cases among 2,493 persons

341 cases among 4,938 persons (50.1 ± 12.6)

(44–59)


(40–70)

99 cases among 575 men

(49–55)


172 cases among 693 men (60.5 ± 11.5)

Population (range or mean ± SD of age, years)

([40)

1999–2005

2001–2002

1995–2002

2002

1991–1992

1987–1988

Enrollment or follow-up periods

[11]c

Japan

South Korea

Germany

Gastroenty

Bayerdorffer et al. [6]

Cross-sectional study (n = 9)

Study (reference no.)

(\22.4) vs. 5th quintile ([26.6)

1st quintile

n.a.

\90 vs. C90

F B 80 vs. [80

M B 90 vs. [90

n.a.

\25 vs. C40

n.a.

n.a.

n.a.

n.a

n.a.

\85 vs. C90 n.a

30th percentile (B0.86) vs. 90th percentile (C0.95)

30th percentile (\0.878) vs. 90th percentile (C0.958)

n.a.

n.a.

n.a.

n.a.

\27 vs. C27

n.a.

\23 vs. C25

30th percentile (\22.48) vs. 90th percentile (C26.95)

2nd & 3rd (21.97–25.09) vs. 4th & 5th ([25.09) quintile

1.81 (1.28–2.56)

n.a.

F: 4.26 (2.00–9.11)

M: 1.27 (0.49–3.27)

2.39 (1.48–4.74)

1.32 (1.05–1.66)

n.a.

1.81(1.02–3.19)

Large adenomab: 2.1(1.1–4.1)

1.9 (1.2–3.0);

Low-risk 1.03 (0.55–1.93)

High-riskaadenoma 0.95 (0.61–1.48)

0.98 (0.68–1.4)

BMI group

WHR

BMI (kg/m2) WC (cm)

OR or RR (95% CI)

Measurement Reference group vs. compared group

Table 1 Characteristics of the studies included in the final analysis (n = 25)

1.24 (1.00–1.55)

1.46 (1.22–1.75)

n.a.

n.a

1.66 (1.33–2.06)

n.a.

n.a.

n.a.

WC group

n.a.

n.a.

n.a.

n.a

n.a.

3.94 (1.77–8.77)

2.9 (1.4–5.9)

Large adenomab:

2.1 (1.1–4.1)

n.a.

WHR group

Age, education, income, smoking, drinking, exercise, and medication

Age, sex, smoking, drinking

Age, smoking, drinking, family history, diet factors, and NSAID use.

Age and sex

study center, and rank in the army

Age,

Age, smoking, drinking, and exercise

Smoking, drinking, Exercise, study center, and rank in the army

Age and serum cholesterol level

Adjustment

Cancer Causes Control (2011) 22:1021–1035 1025

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123

Cancer Causes Control

Leitzmann et al. [14]

Am J Gastroenterol

Nutr Cancer

Cancer Epidem Biomar

Almendingen et al. [19]

Boutron et al. [20]

Morimoto et al. [21]

Am J Epidemil

Bird et al. [17]

Keio J Med

Eur J Cancer

Olsen et al. [16]

Takemura et al. [18]

J Natl Cancer Inst

USA; HCC

France; PCC

Norway; PCC

1991–1994

n.a.

n.a.

1996

1991–1993

1986–1990

1986–1988

1999–2002


Japan; HCC

USA; HCC

Denmark; PCC

USA; HCC

USA

Nation; design

Neugut et al. [15]

Case–control study (n = 11)

Journal


Table 1 continued

(30–74)

437 cases and 708 controls

(30–79)


(50–76)


(50–55)

51 cases and 46 control men

(50–75)

483 cases and 483 hospital controls

172 cases and 362 controls (45–74)

303 cases and 509 controls (35–84)

(40–79)

292 cases among 1,420 women


n.a

1st quartile (\24.2) vs. 4th quartile (C29.7)

(M B 21.7, F B 20.1) vs. 5th quintile (M C 27.3, F C 25.7)

1st quintile

1st quartile (B23) vs. 4th quartile (C29.9)

\25 vs. C25

n.a.

n.a.

n.a.

n.a.

1st quartile (M B 24.41, F B 23.461) vs. 4th quartile (M C 29.2, F C 30.2)

1st tertile (16.4–23.7) vs. 3rd tertile (26.6–43.9)

1st quartile (M B 23.1, F B 26.5 kg/m1.5) vs. 4th quartile (M C 27.1, F C 33.5 kg/m1.5)

B24.9 vs. C30.0

n.a.

n.a.

n.a.

n.a

n.a.

n.a.

n.a.


n.a.

n.a.

n.a.

1.6 (0.9–2.6)

n.a

n.a.

n.a.

n.a.

F: 0.8 (0.5–1.3)

M: 1.6 (1.0–2.8)

1.7 (1.0–3.1)

Small adenoma:

2.1 (1.2–3.5)

Large adenomaa:

0.2(0.1–2.8)

1.04 (0.30–3.69)

Small adenoma:

2.5 (1.1–5.4)

Large adenomab:

1.7 (1.0–2.8)

0.87 (0.6–1.4)

F: 3.1 (1.3–7.6)

M: 1.6 (0.7–3.6)

Large adenomab:

F: 2.1 (1.1–4.0)

M: 1.4 (0.8–2.5)

1.25 (0.81–1.93)

WC group

BMI group

WHR

BMI (kg/m2) WC (cm)

OR or RR (95% CI)


n.a.

n.a.

n.a.

n.a.

F: 0.4 (0.2–1.1)

M: 1.7 (0.9–3.2)

n.a.

n.a.

n.a.

n.a.

n.a.

n.a.

n.a

WHR group

Age, BMI, HRT, smoking, and alcohol

Age and sex

Age, sex, smoking, region of residence, family history, and diet factors

BMI in their thirties and best time of 1,500-m run

date of sigmoidoscopy, study center, BMI history, NSAIDs use, exercise, and diet factors

Age, sex, race, smoking,

Age, Sex, and energy intake

Age

Age, study center, race, family history, history of examination, smoking, drinking, aspirin use, menopause, exercise, red meat, and vitamin D consuumption

Adjustment

1026 Cancer Causes Control (2011) 22:1021–1035

Japan; HCC

Intern Med

Omata et al. [25]d

Ann Intern Med

Cancer Causes Control

J Gen Intern Med

Giovannucci et al. [26]

Giovannucci et al. [27]

Kahn et al. [28]

Cohort study (n = 5)

USA; PCC

Contraception

Wolf et al. [24]

USA; PCS

USA; PCS

PCS

USA;

South Korea; HCC

Dig Liver Dis

USA; PCC

1982–1992

1976–1992

1986–1992

n.a.

1991–1994

2002–2004

1995–1997


Chung et al. [23]c

Nation; design

Am J Epidemiol

Journal

Hauret et al. [22]


Table 1 continued

12,615 cases among 72,868 men and 81,356 women (40–64)

330 cases among 13,057 female nurses (30–55)

(40–75)


194 cases and 586 controls (52.2 ± 14.5)

(30–74)

209 cases and 247 control women

(35–75)


(30–74)



1st quintile (\35 inches) vs. 5th quintile (C43 inches)

1st quintile vs. 5th quintile

n.a.

\21 vs. C29

22 * 26 vs. [28

n.a.

n.a.

n.a.

n.a.


n.a.

n.a.

1st quintile vs. 5th quintile

F: 1.08 (0.99–1.17)

M: 1.06 (1.00–1.13)

1.44 (0.86–2.38)

Small adenoma:

Large adenomab: 2.21 (1.18–4.16)

n.a.

Large adenomab:

Large adenomaa: 1.54 (0.86–2.76)

n.a.

1.65 (0.93–2.92)

1.55 (1.09–2.21)

0.77 (0.48–1.23)

1.55 (1.08–2.21)

1.07 (0.53–2.12)

Small adenoma:

Small adenoma:

n.a.

0.85 (0.48–1.51)

n.a.

1.46 (0.73–2.92)


n.a.

n.a.

n.a.

0.92 (0.49–1.72)

WHR group


1.29 (0.79–2.12)

1.49 (0.89–2.49)

10.8 (4.0–25.3)

0.70 (0.37–1.34)

1.50 (1.02–2.21)

n.a.

1st quartile (M \ 0.95, F \ 0.78) vs. 4th quartile (M C 1.02, F C 0.88)

1st quintile (\0.90) vs. 5th quintile (C0.99)


n.a.

\22 vs. [25

\25.0 vs. C30.0

B22.9 vs. C25.0


WC group

BMI group

WHR

BMI (kg/m2) WC (cm)

OR or RR (95% CI)


Age, race, smoking, drinking, exercise, education, and gallbladder status

diet factors

family history, history of endoscopy, aspirin use, and

Age, smoking, drinking,

diet factors

Aspirin use, and

family history, history of endoscopy,

drinking, exercise,

Age, smoking,

Age, sex, smoking, and drinking

Smoking, and family history

Age,

Age, sex, fasting glucose, triglyceride, and total cholesterol

Age, sex, smoking, exercise, family history of colorectal cancer, NSAIDs use, energy intake and diet factors

Adjustment


123

123

Obesity

Wise et al. [30]

USA; PCS

USA; PCS

1995–2003

1992–2004


(21–69)

1,189 cases among 59,000 AfricanAmerican women

(C49)

136 cases among 600 persons


1st tertile (M B 91.0, F B 80.8) vs. 3rd tertile (M C 99.0, F C 91.6)

1st quintile (\28 inches) vs. 5th quintile (C37 inches)

\25 vs. [30 n.a.

\25 vs. C35 1st quintile (\0.71) vs. 5th quintile (C0.87)

1.39 (1.16–1.67)

Non-advanced adenoma: 2.14 (1.04–4.42)

Advanced adenoma: 1.90 (0.57–6.37)

2.16 (1.13–4.14)

WC group

BMI group

WHR

BMI (kg/m2) WC (cm)

OR or RR (95% CI)


1.42 (1.15–1.74)

Nonadvanced adenoma: 1.29 (0.69–2.39)

Advanced adenoma: 2.31 (0.65–8.21)

1.49 (0.84–2.64)

WHR group

1.31 (1.08–1.59)

n.a.

Age, smoking, exercise, family history, education, NSAIDs use, menopausal status, HRT, and diet factors

study center, total estimated energy expenditure, and previous polyp history

Age, sex, race, smoking,

Adjustment

d

c

b

a

19 cases of colon cancer in histology were included in this case–control study as cases of colorectal adenomatous polyps

This article analyzed only advanced adenomas which mean adenomatous polyps larger than 10 mm or greater in size with villous component or high-grade dysplasia in histology

Adenomatous polyps larger than 10 mm in size

Villous or tubulovillous adenoma, adenomas with severe dysplasia, adenomas with a diameter of C2 cm, and multiple adenomas (C6 cm)

BMI body mass index; WC waist circumference; WHR Waist-to-hip ratio; OR odds ratio; RR relative risk; HCC hospital-based case–control study; PCC population-based case–control study; PCC prospective cohort study; n.a. not available; M male subject; F female subject

Cancer Epidemiol Biomarkers Prev

Sedjo et al. [29]

Nation; design

Journal


Table 1 continued

1028 Cancer Causes Control (2011) 22:1021–1035


1029 OR or RR (95% CI)

Study

Weight (%)

Cross-sectional study (n = 7) Bayerdorffer, 1993 Shinchi, 1994 Kim, 2005 Wang, 2005 Anderson, 2007 Lee, 2008 Leitzmann, 2009

0.98 (0.68, 1.40) 1.90 (1.20, 3.00) 1.81 (1.02, 3.19) 1.32 (1.05, 1.66) 2.39 (1.48, 4.74) 1.81 (1.28, 2.56) 1.25 (0.81, 1.93)

5.66 4.76 3.86 6.96 3.78 5.81 4.97

Subtotal (I-squared = 49.7%)

1.50 (1.21, 1.85)

35.80

Neugut, 1991 Olsen, 1994 Bird, 1998 Takemura, 2000 Almendingen, 2001 Boutron-Ruault, 2001 Morimoto, 2002 Hauret, 2004 Chung, 2006 Wolf, 2007 Omata, 2009

1.67 (1.09, 2.56) 0.87 (0.60, 1.40) 1.70 (1.00, 2.80) 1.04 (0.30, 3.69) 0.20 (0.10, 2.80) 1.90 (1.29, 2.80) 1.12 (0.57, 2.22) 0.70 (0.37, 1.34) 10.80 (4.60, 25.30) 1.49 (0.89, 2.49) 1.29 (0.79, 2.12)

5.04 5.07 4.28 1.27 0.77 5.41 3.15 3.37 2.33 4.28 4.45


1.41 (0.99, 2.02)

39.43 5.42 8.10 3.88 7.38


1.50 (1.02, 2.21) 1.07 (1.02, 1.17) 1.54 (0.87, 2.71) 1.39 (1.16, 1.67) 1.28 (1.04, 1.59)

Overall (I-squared = 73.4%)

1.43 (1.23, 1.67)

Case-control study (n = 11)

Cohort study (n = 4) Giovannucci, 1996 Kahn, 1998 Sedjo, 2007 Wise, 2008

.2

.5

1

2

24.78 100.00

5

Fig. 2 Association between adiposity defined by body-mass index and risk of colorectal adenomatous polyp in meta-analyses of epidemiological studies by type of study design (n = 22). *Random-effects model. OR odds ratio; RR relative risk; CI confidence interval OR or RR (95% CI)

Study

Weight (%)

Cross-sectional study (n =5) Shinchi, 1994 Kim, 2005 Morita, 2005 Kim, 2007 Lee, 2008 Subtotal (I-squared = 57.2%)

1.50 (0.90, 2.50) 3.94 (1.77, 8.77) 1.66 (1.33, 2.06) 1.46 (1.22, 1.75) 1.24 (1.00, 1.55) 1.48 (1.32, 1.65)

3.17 1.29 17.28 25.42 17.22 64.39

Case-control study (n = 3) Wolf, 2007 Morimoto, 2002 Hauret, 2004 Subtotal (I-squared = 0.0%)

0.85 (0.48, 1.51) 0.85 (0.21, 3.50) 0.92 (0.49, 1.72) 0.88 (0.59, 1.32)

2.52 0.42 2.10 5.03

Cohort study (n = 4) Giovannucci, 1995 Giovannucci, 1996 Sedjo, 2007 Wise, 2008 Subtotal (I-squared = 0.0%)

1.60 (0.70, 3.65) 1.55 (1.09, 2.21) 1.11 (0.68, 1.81) 1.42 (1.15, 1.74)

1.21 6.62 3.45 19.29

1.41 (1.20, 1.67)

30.58

Overall (I-squared = 33.4%)

1.42 (1.30, 1.56)

100.00

.2

.5

1

2

5

Fig. 3 Association between abdominal adiposity and risk of colorectal adenomatous polyp in meta-analyses of epidemiological studies by type of study design (n = 12). *Fixed-effects model. OR odds ratio; RR relative risk; CI confidence interval

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1030


(A) 2

Egger’s test

log[rr]

P for bias = 0.019

0

-2 0

.5

1

s.e. of: log[rr]

Publication bias

Egger’s test

(B) 2

adiposity defined by WC or WHR, in which WC was not available in two cross-sectional studies [7, 8] and two case– control studies [21, 24]. Abdominal adiposity was associated with an increased risk of colorectal adenomatous polyps (OR or RR 1.42, 95% CI 1.30–1.56, I2 = 33.4%) in a fixed-effects meta-analysis of five cross-sectional studies, three case–control studies, and four prospective cohort studies, and the RR of four prospective cohort studies was 1.41 (95% CI 1.20–1.67, I2 = 0.0%).

log[rr]

P for bias = 0. 710

1

0

-1 0

.2

.4

.6

.8

s.e. of: log[rr] Fig. 4 Begg’s funnel plot and Egger’s test for identifying publication bias in a combined meta-analysis of cross-sectional studies, case– control studies, and cohort studies on the relationship between adiposity and colorectal adenomatous polyp (n = 22) (a) and between abdominal adiposity and risk of colorectal adenomatous polyp (n = 12) (b)

of colorectal adenomatous polyp (OR 1.43, 95% CI 1.23–1.67, I2 = 73.4%) in a random-effects meta-analysis: cross-sectional studies (OR 1.50, 95% CI 1.21–1.85, I2 = 49.7%), case–control studies (OR 1.41, 95% CI 0.99–2.02, I2 = 75.6%), and cohort studies (RR 1.28, 95% CI 1.04–1.59, I2 = 71.4%). Two outliers were apparent in Fig. 2. Of those, one study [23] (i.e., Chung et al. 2006) adjusted for inappropriate causal intermediates such as fasting glucose, triglyceride, and total cholesterol. When excluding it (i.e., Chung et al. 2006) [23], the overall effect size (OR or RR) of 21 studies (Fig. 2) was 1.36 (95% CI 1.19–1.55, I2 = 62.4%), and the OR of ten case–control studies was 1.25 (95% CI 0.97–1.62, I2 = 51.2%) (data were not presented due to space limitation). After excluding Chung et al’s study, even though the statistical significance had not changed, the heterogeneity was decreased, and the effect size was also decreased. With the exclusion of two outliers (i.e., Almendingen et al. 2001; Chung et al. 2006) [19, 23], the OR of nine case–control studies was 1.35 (95% CI 1.14–1.60) with heterogeneity (I2 = 40.6%), and the overall effect size (OR or RR) of all 20 studies consisting of seven cross-sectional, nine case–control and four cohort studies was 1.38 (95% CI 1.21–1.56) with heterogeneity (I2 = 61.1%). Figure 3 shows the association between abdominal adiposity and the risk of colorectal adenomatous polyps in a meta-analysis of 12 studies that showed abdominal

123

Publication bias was found in the selected studies. Figure 4a displays an unsymmetrical funnel plot and Egger’s test with p for bias = 0.019. It might mean that the articles reporting the positive association between adiposity defined by BMI and colorectal adenomatous polyps tended to be published more often. No publication bias was evident in the studies that showed the association between abdominal adiposity and colorectal adenomatous polyps (Begg’s funnel plot was symmetrical; Egger’s test, p for bias = 0.710; Fig. 4b). Methodological quality of studies Table 2 summarizes the methodological quality scores of eleven case–control studies and five cohort studies included in the final analysis. The mean value for all the studies assessed was 6.6 stars, comprising 6.8 for the case–control studies and 6.2 for the cohort studies. Subgroup meta-analyses Table 3 shows the associations between adiposity and the risk of colorectal adenomatous polyps in subgroup metaanalyses by various factors. There were similar significant positive associations between adiposity and colorectal adenomatous polyp in subgroup meta-analyses as in the overall meta-analysis, especially as for large or advanced polyps, its effect size was as high as 2.16 (95% CI 1.49–3.14) for adiposity defined by BMI. However, adiposity was marginally associated with an increased risk of adenomatous polyps in the low-quality studies. As for abdominal adiposity, its findings were similar to those of adiposity, as shown in Table 4. However, studies that analyzed subgroup with female population, small and non-advanced polyps, and low methodological quality showed nonsignificant associations. Dose–response relationships As shown in Table 5, a significant positive dose–response relationship was observed between adiposity defined by

q

q

Wise et al. [30]

– –

q

q

–

–

– q

qq

qq

qq

qq qq

q

q

q

q

q q

q

q

q

q

q

–

q

–

q q

Assessment of outcome

Outcome

q

–

q

q

q q

q

q

q

q

q

q

q

–

– q

q

q

q

q

q –

q

q

q

–

–

q

–

–

q q

4

6

8

8

8 7

7

6

8

8

5

Total (0–9)

7

7

4

5 8

Total (0–9)

Nonresponse rate*

Adequacy of follow up of cohorts

Same method of ascertainment for subjects

Follow-up long enough form outcomes to occur

Ascertainment of exposure (blinding)

Exposure

* If there was no significant difference in the response rate between both groups by using a chi-square test (p [ 0.05), one point was awarded

q q

q

q

Kahn et al. [28]

– –

q q

q q

Sedjo et al. [29]

Giovannucci et al. [26] Giovannucci et al. [27]

Outcome of interest not present at start of study

Control for important factor or additional factor

Ascertainment of exposure

qq –

Selection of the non exposed cohort

–

–

qq

qq

qq qq

qq

q

qq

qq

Representativeness of the exposed cohort

–

–

q

q

q q

q

q

q

q

Comparability

–

q

Omata et al. [25]

q

–

– –

–

–

q

q

Selection

q

q

Wolf et al. [24]

Cohort studies (n = 5)

q –

q q

q q

Boutron et al. [20] Morimoto et al. [21]

q

–

q

Almendingen et al. [19]

q

–

q

Takemura et al. [18]

Chung et al. [23]

–

q

Hauret et al. [22]

q

q

Bird et al. [17]

–

Olsen et al. [16]

q

–

q

Neugut et al. [15]

q

Control for important factor or additional factor

Definition of controls

Representativeness of cases

Adequate definition of cases

Selection of controls

Comparability

Selection

Case–control studies (n = 11)

Table 2 Methodological quality of studies included in the final analysis, based on the Newcastle–Ottawa Scale for assessing the quality of case–control studies and cohort studies (n = 16)


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1032


Table 3 Associations between adiposity defined by BMI and the risk of colorectal adenomatous polyp in subgroup meta-analyses by various factors No. of studies (reference no)

Summary OR or RR (95% CI)

Heterogeneity, I2 (%)

Model used

Male

8 (6–8, 11, 13, 15, 21, 28)

1.39 (1.10–1.76)

66.6

Random-effects

Female Region

7 (11,14, 15, 21, 27, 28, 30)

1.37 (1.08–1.73)

76.3

Random-effects

Category Sex

Western country

15 (6, 11, 14–17, 19–22, 24, 26–30)

1.30 (1.11–1.52)

64.0

Random-effects

Asian country

7 (7–10, 12, 13, 18, 23)

1.88 (1.30–2.71)

75.4

Random-effects

Size or Histology of polyps Large or advanced polypsa

10 (6, 7, 11, 14, 15, 17, 20, 23, 27, 29)

2.16 (1.49–3.14)

67.8

Small and non-advanced polyps

4 (14, 20, 27, 29)

1.51 (1.15–1.99)

0.0

Random-effects Fixed-effects

Methodological quality of study High quality

10 (16, 17, 19–23, 27, 29, 30)

1.44 (1.04–1.98)

77.6

Random-effects

Low quality

6 (15, 18, 24–26, 28)

1.09 (1.02–1.16)

49.8

Fixed-effects

Early (1991–2004)

12 (6, 7, 15–22, 27, 28)

1.24 (1.02–1.52)

63.4

Random-effects

Recent (2005–2009)

10 (8, 10, 11, 13, 14, 23–25, 29, 30)

1.68 (1.34–2.09)

67.3

Random-effects

5 (7, 10, 14, 17, 27)

Year of publication

Site of polyp in colon Distal colorectum

1.46 (1.23–1.72)

0.0

Total colorectum 17 (6, 8, 11, 13–16, 18–25, 29, 30) Collection method for anthropometric data

1.45 (1.17–1.78)

68.4

Fixed-effects Random-effects

Direct measurement

9 (7, 8, 10, 11, 13, 18, 19, 23, 29)

1.84 (1.29–2.62)

74.5

Random-effects

Self-reporting

12 (14–17, 20–22, 24, 25, 27, 28, 30)

1.29 (1.11–1.51)

59.3

Random-effects

OR odds ratio; CI confidence interval a

Definitions of large or advanced polyps, which are described in Table 1, varied across the studies

BMI and the risk of colorectal adenomatous polyps in subgroup meta-analyses (p for trend = 0.027).

Discussion The current meta-analysis of epidemiological studies revealed that adiposity and abdominal adiposity were associated with an increased risk of colorectal adenomatous polyps. Also, similar findings were observed in most of the subgroup meta-analyses by gender, region, size of histology of polyps, methodological quality of study (high quality), year of publication, site of polyp, and collection method for anthropometric data, except for abdominal obesity in subgroup meta-analyses of studies involving small/non-advance polyps and low quality. We found a positive dose–response relationship between BMI and the risk of colorectal adenomatous polyps. An advanced adenoma has a greater chance to progress to an invasive lesion than a non-advanced adenoma, even though more than 90% of adenomatous polyps do not progress to advanced or invasive lesions. A recent meta-

123

analysis that quantified the risk of developing advanced adenoma or cancer in patients with previously resected colorectal adenomas mentioned that the number and size of prior adenomas and the presence of villous features were associated with metachronous advanced neoplasia including CRC [36]. A strong positive association of adiposity with large adenomas supports the hyperinsulinemia hypothesis, which posits that insulin and insulin-like growth factor-I (IGF-I) are mediating molecules stimulating non-advanced adenomas to progress to advanced adenomas. The association between adiposity and the risk of incidence and growth of colorectal adenomatous polyp and its possible mechanisms have been suggested through diverse clinical and animal experiments. Some epidemiological studies [27, 37, 38] have demonstrated an association between WC (WHR) or intra-abdominal fat (visceral adipose tissue) and large adenomatous polyps or subsequent development of CRC. Moreover, it has been suggested that insulin and IGF-I, which are abundantly secreted in obese subjects, contribute to the growth and progression of colorectal adenomatous polyps, and their effects are stronger in advanced adenomas


1033

Table 4 Associations between abdominal adiposity and the risk of colorectal adenomatous polyp in subgroup meta-analyses by various factors Category

No. of studies (reference no)

Summary OR or RR (95% CI)

Heterogeneity, I2 (%)

Model used

Sex Male

6 (7–9, 13, 21, 26)

1.67 (1.29–2.17)

52.1

Random-effects

Female

4 (21, 24, 27, 30)

1.09 (0.72–1.64)

72.9

Random-effects

Region Western country

7 (21, 22, 24, 26, 27, 29, 30)

1.34 (1.15–1.56)

0.0

Asian country

5 (7–9, 12, 13)

1.53 (1.25–1.87)

52.7


Size or histology of polyps Large or advanced polypsa

4 (7, 26, 27, 29)

2.12 (1.46–3.07)

0.0

Fixed-effects

Small and non-advanced polyps

2 (26, 29)

1.19 (0.75–1.89)

0.0

Fixed-effects

5 (21, 22, 27, 29, 30) 2 (24, 26)

1.38 (1.18–1.62) 1.04 (0.65–1.67)

0.0 34.3

Fixed-effects Fixed-effects

Early (1991–2004)

5 (7, 21, 22, 26, 27)

1.45 (1.13–1.84)

0.0

Fixed-effects

Recent (2005–2009)

7 (8, 9, 12, 13, 24, 29, 30)

1.41 (1.19–1.67)

56.6

Waist circumference

8 (9, 12,13, 22, 26, 27, 29, 30)

1.42 (1.29–1.56)

0.0

Fixed-effects

Waist-to-hip ratio

8 (7, 8, 21, 22, 24, 26, 27, 30)

1.38 (1.19–1.60)

34.2


Methodological quality of study High quality Low quality Year of publication Random-effects

Abdominal adiposity definition

Collection method for anthropometric data Direct measurement

6 (7–9, 12, 13, 29)

1.62 (1.32–1.99)

56.9

Self-reporting

6 (21, 22, 24, 26, 27, 30)

1.33 (1.12–1.59)

6.2

Fixed-effects

OR odds ratio; CI confidence interval; n.a. not applicable a

Definitions of large or advanced polyps, which are described in Table 1, varied across the studies

Table 5 Dose–response relationships between adiposity and the risk of colorectal adenomatous polyps Category of adiposity

No. of studies

Pooled RR or OR (95% CI)

Heterogeneity I2 (%)

Model used

P for trendb

Low

20

1.19 (1.05–1.35)

64.5

Random-effects

0.027

Moderate

19

1.40 (1.20–1.64)

71.1

Random-effects

Highesta

2

1.69 (1.02–2.82)

67.0

Random-effects

a

Highest adiposity was defined as BMI [ 35 for European or American populations and BMI [ 30 for Asian populations; moderate adiposity as BMI [ 30 for European or American populations and BMI [ 25 for Asian populations; lower adiposity as BMI [ 25 for European or American populations and BMI [ 23 for Asian populations, respectively, based on the WHO obesity guidelines and Asia–pacific standard as described in the discussion section b

A weighted linear regression was performed to model the natural logarithm of RR or OR for the risk of adenomatous colon polyps as a function of qualitatively described adiposity (lower = 1, moderate = 2, and highest = 3) using the inverse variance calculated from confidence intervals of each category; standard error = {LN(upper limit)-LN(lower limit)}/2 9 1.96; inverse variance = 1/(standard error 9 standard error)

than in less advanced ones. Hyperinsulinemia results in a decrease in IGF-binding protein (IGFBP) and elevates the level of circulating IGF-I. The subsequent activation of IGF-I receptors on colonocytes inhibits apoptosis and enhances epithelial cell proliferation, and this process is associated with the development, progression, and metastatic potential of CRC. In addition, the relationship between adiponectin and CRC incidence has been demonstrated in some case–control studies [39–41], as well as in animal experiments [42].

Also, patients with CRC had lower plasma adiponectin levels compared with controls in the case–control studies, indicating the association of adiponectin level with adenomatous polyp incidence, as well as the negative correlation of adiponectin with insulin level and homeostasis model assessment insulin resistance index (HOMA-IR). Regarding obesity and CRC, three recent meta-analyses [35–37] have estimated the strength of the association between obesity and CRC in men and women. In one study [43], a positive dose–response relationship between obesity

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and the risk of CRC was reported. For every 2 kg/m2 increase in body mass index (BMI), the risk of developing CRC increased by 7%, and every 2-cm increase in waist circumference (WC) was associated with a 4% increased risk of CRC. In this study, the risk was greater for colon cancer rather than rectal cancer, and was 30% higher in obese men compared with obese women. In another metaanalysis [44] assessing the risk of BMI, WC, and waist-tohip ratio (WHR) to CRC, for each 5-unit increase in BMI, the risk of colon cancer increased in men by 30% (95% CI 1.25–1.35) and in women by 12% (95% CI 1.07–1.18). BMI was associated with an increased risk of rectal cancer in men but not in women. The risk of colon cancer increased with every 10-cm increase in WC in men by 33% (95% CI 1.19–1.49) and by 16% (95% CI 1.09–1.23) in women, and with increasing WHR per 0.1 unit in men by 1.43 (95% CI 1.19–1.71) and in women by 1.20 (95% CI 1.08–1.33). The other meta-analysis [45] reported a stronger association in men than in women between obesity and CRC risk. Our study had several limitations. First, it could not provide a higher level of evidence because we included only observational studies such as cross-sectional, case– control, and cohort studies. In further research, randomized controlled trials are required to examine the effect of weight reduction in obese populations in the risk of colorectal polyps. Second, the regional distribution of the selected studies was not even. Thus, our findings could not be generalized. Third, we could not consider metabolic syndrome as a confounding factor because most of the included studies did not include it as a confounding factor. Last, the exclusion of non-English language articles might bias the findings. However, there was the only one nonEnglish paper written in Chinese that met the main eligibility criteria. Therefore, it could not have altered our main finding.

Conclusions Overall, we found that adiposity and abdominal obesity were significantly associated with an increased risk of colorectal adenomatous polyps in a meta-analysis of epidemiological studies, including cross-sectional studies, case–control studies, and cohort studies. BMI had a positive dose–response relationship with colorectal adenomatous polyps. Our findings should be confirmed in randomized controlled trials that give us a higher level of evidence. Acknowledgment Research Grant.

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This work was supported by INHA University

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