1

Tobacco smoking and the risk of diverticular disease - a

systematic review and meta-analysis of prospective studies

D. Aune, PhD student1,2, A. Sen, PhD2, M.F. Leitzmann, MD, Professor3, S. Tonstad, MD,

Professor4, T. Norat, PhD1, L.J. Vatten, MD, Professor2

Affiliations

1 Department of Epidemiology and Biostatistics, Imperial College London, London, United

Kingdom

2 Department of Public Health and General Practice, Faculty of Medicine, Norwegian

University of Science and Technology, Trondheim, Norway

3Department of Epidemiology and Preventive Medicine, Regensburg University Medical

Center, Regensburg, Germany

4Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University

Hospital, Oslo, Norway

Correspondence to: Dagfinn Aune, Department of Epidemiology and Biostatistics,

School of Public Health, Imperial College London, St. Mary's Campus, Norfolk Place,

Paddington, London W2 1PG, UK.

Telephone: +44 (0) 20 7594 8478

Fax: +44(0) 20 7594 0768

E-mail: d.aune@imperial.ac.uk

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Abstract

Aim: This systematic review and meta-analysis aimed to clarify whether tobacco smoking is

associated with increased risk of diverticular disease.

Methods: PubMed and Embase databases were searched for studies of smoking and

diverticular disease up to February 19, 2016. Prospective studies that reported adjusted

relative risk (RR) estimates and 95% confidence intervals (CIs) of diverticular disease

associated with current, former or ever smoking and by number of cigarettes per day were

included. Summary RRs were estimated using a random effects model.

Results: We identified six prospective studies including 6076 incident diverticular disease

(diverticulosis and diverticulitis) cases and 370699 participants and 1118 cases of diverticular

disease complications (abscess or perforation) among 278373 participants that could be

included in the meta-analysis. The summary RRfor incident diverticular disease was 1.36

(95% CI: 1.15-1.61, I2=84%, n=4) for current smokers, 1.17 (95% CI: 1.05-1.31, I2=49%,

n=4) for former smokers and 1.33 (95% CI: 1.22-1.46, I2=55%, n=7) for ever smokers. The

summary relative risk was 1.11 (95% CI: 0.99-1.25,I2=82%, n=4) per 10 cigarettes per day.

Although there was some indication of nonlinearity there was a dose-dependent positive

association with increasing number of cigarettes smoked per day. There was some evidence

that smoking also increases the risk of diverticular disease complications, but the number of

studies was small.

Conclusion: The current meta-analysis provides evidence of an increased risk of diverticular

disease incidence and diverticular disease complications associated with tobacco smoking.

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Word count abstract: 230

Word count text: 1942

Key words: Tobacco, smoking, diverticular disease, cohort studies, meta-analysis

Originality statement: This meta-analysis found an increased risk of diverticular disease

incidence among current, former and ever smokers and evidence of increased risk with

increasing number of cigarettes smoked per day. An increased risk of diverticular disease

complications was also seen among current and ever smokers.

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Introduction

Diverticular disease is a common disease in high-income countries and has been called a

“disease of the Western civilization” as the prevalence of the disease varies more than 20- to

40-fold between high and low risk populations and is more common in societies with a

westernized lifestyle (1). Diverticular disease consists of two conditions: diverticulosis which

is a condition where diverticula or pouches of the colonic mucosa and submucosa develops

through weaknesses in the muscle layers of the colonic wall, and diverticulitis which is when

these pouches become inflamed. Although the exact prevalence of diverticular disease is

difficult to assess because most of the cases are asymptomatic (2), it has been estimated that

in the US 65% of adults will develop diverticular disease by 80 years of age (3;4).

Complications, such as diverticulitis and diverticular bleeding occur in 10-35% of persons

with diverticulosis (2;5;6), while perforation occurs in 5-10% of diverticulitis cases (7), and

is associated with a 4.5-fold increase in the relative risk of 1-year mortality (8).

Secular trend studies have found that the incidence or mortality of diverticular disease

changes rapidly in countries with economic development over relatively short time periods

(9;10). For example in just 12 years between 1974 and 1986 there was a 2 to 4-fold increase

in diverticular disease incidence in Japan (9). One autopsy study reported a prevalence of 1%

among Japanese in Japan, but a prevalence of 50% among Japanese in the US (11). Other

studies have also found large ethnic differences in the incidence of diverticular disease

among immigrants to Sweden, but these differences were attenuated with longer duration

after the settlement (12). These observations suggest that modifiable risk factors are of major

importance in the etiology of diverticular disease. Established or suspected risk factors

include low dietary fiber intake, high meat intake, obesity and low physical activity (13).

Although tobacco smoking has been associated with increased risk of other diseases

of the colon including adenomas(14), colon cancer(15), and Crohn's disease(16) the

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association between smoking and diverticular disease is not clear. Tobacco smoking has been

associated with increased risk of diverticular disease in some studies(17-20), however, not all

studies reported a significant association (21-23). Although some studies suggested a positive

dose-response relationship between number of cigarettes smoked per day and diverticular

disease risk(19;20), not all studies were consistent with this(18;21). Because only few risk

factors for diverticular disease are established, we conducted a systematic review and meta-

analysis of prospective studies on the association between smoking and diverticular disease

with the aims of clarifying whether there is an association, assessing the strength of any

potential association and evaluating whether there is a dose-response relationship between

smoking and diverticular disease.

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Methods

Search strategy and inclusion criteria

Pubmed and Embase databases were searched from inception (1966 and 1947, respectively)

up to February 19, 2016 for eligible studies. As part of a larger project on risk factors for

diverticular disease we useda wide range of terms for the search: ("body mass index" OR

BMI OR overweight OR obesity OR anthropometry OR fatness OR "body fatness" OR

"abdominal fatness" OR "abdominal obesity" OR "waist circumference" OR "waist-to-hip

ratio" OR "waist-to-height ratio" OR “hip circumference” OR adiposity OR weight OR

"weight gain" OR "weight change" OR “weight loss” OR “body size”OR “physical activity”

OR exercise OR sports OR walking OR biking OR running OR fitness OR “exercise test” OR

inactivity OR sedentary OR fiber OR fibre OR diet OR meat OR "red meat" OR "processed

meat" OR beef OR pork OR lamb OR smoking OR tobacco OR risk factor OR risk factors)

AND ("diverticular disease" OR diverticulitis OR "diverticular bleeding" OR diverticula)

AND (“case-control” OR retrospective OR cohort OR cohorts OR prospective OR

longitudinal OR “follow-up” OR “cross-sectional” OR trial). In addition, we searched the

reference lists of the identified publications for further studies.We followed the PRISMA

criteria for conducting and reporting of meta-analyses (24). Two reviewers screened the

references for inclusion (DA, AS).

Study selection

We included published prospective studies that investigated the association between smoking

and the risk of diverticular disease or diverticular disease complications (abscess and/or

perforation). Adjusted estimates of the relative risk (RR) with the 95% CIs had to be

available in the publication. For the dose-response analysis a quantitative measure of the

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smoking level had to be provided. We identified six relevant prospective studies that could be

included in the analysis(17-21;25). A list of the excluded studies and the reasons for

exclusion are provided in Supplementary Table 1.

Data extraction

The following data were extracted from each study: first author’s last name, publication year,

country where the study was conducted, study period, sample size, sex, number of cases, ICD

codes or outcome definition, smoking status, number of cigarettes per day, RR and 95% CI,

and variables adjusted for in the analysis. Data were extracted by one reviewer (DA) and

checked for accuracy by a second reviewer (AS). Any disagreements were resolved by

discussion.

Statistical methods

We calculated summary RRs by smoking status (i.e. current, former and ever smokers vs.

never smokers) and for an increment of 10 cigarettes per day using the random-effects model

by DerSimonian and Laird(26) which takes into account both within and between study

heterogeneity. The average of the natural logarithm of the RRs was estimated and the RR

estimate from each study was weighted using random effects weights.

To investigate whether the number of cigarettes smoked per day was associated with

diverticular disease, we used the method described by Greenland and Longnecker(27) for the

dose-response analysis and computed study-specific slopes (linear trends) and 95% CIs from

the natural log of the RRs and CIs across categories of cigarettes smoked per day. The

method requires that the distribution of cases and person-years or non-cases and the RRs with

the variance estimates for at least three quantitative exposure categories are known. For

studies that did not provide this information, we estimated the distribution of cases and

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participants based on a method previously described(28). Studies that did not quantify the

number of cigarettes smoked per day were excluded from the dose-response analysis. We

assessed a potential nonlinear dose-response relationship between smoking and diverticular

disease using fractional polynomial models. We determined the best fitting second order

fractional polynomial regression model, defined as the one with the lowest deviance. A

likelihood ratio test was used to assess the difference between the nonlinear and linear models

to test for nonlinearity(29).

Heterogeneity between studies was evaluated using Q and I2 statistics(30). All

statistical tests were two-sided and p<0.05 was considered statistically significant. I2-values

of 25%, 50% and 75% indicated low, moderate and high heterogeneity, respectively(31). We

conducted main analyses (all studies combined) and stratified by study characteristics such as

sample size, number of cases, geographic location, study quality score and adjustment for

confounding factors. Study quality was assessed using the Newcastle-Ottawa scale which

ranks the studies on a scale from 0 to 9 based on the selection of the study population,

comparability between cases and non-cases and the assessment of the outcome (32).

Publication bias was assessed using Egger’s test(33) and Begg-Mazumdar’s test(34)

and with funnel plots, and p<0.10 was considered to indicate possible publication bias as the

tests have low power when the number of studies is low.The statistical analyses were

conducted using the software package Stata, version 12.0 software (StataCorp, Texas, US).

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Results

Of a total of 1898 records identified by the searches, we identified six prospective studies(17-

21;25) involving a total of 6076 diverticular disease (diverticulosis and diverticulitis

combined) cases among 370699 participants that could be included in the analyses of

smoking and diverticular disease and three studies (18;20;25) with 1118 cases of diverticular

disease complications (perforation and/or abscess) as the outcome among 278373 participants

(Figure 1, Table 1). Five studies were from Europe and one was from the US (Table 1).

Smoking status and diverticular disease incidence

Four cohort studies (18-21) were included in the analysis of current smoking and diverticular

disease and included 5964 cases and 363205 participants. The summary RR was 1.36 (95%

CI: 1.15-1.61,I2=84%, pheterogeneity=0.0004)(Figure 2a). Four cohort studies (18-21) were

included in the analysis of former smoking and diverticular disease (5964 cases and 363205

participants) and the summary RR was 1.17 (95% CI: 1.05-1.31, I2=49%, pheterogeneity=0.12)

(Figure 2b). Five cohort studies (17-21) were included in the analysis of ever smoking and

diverticular disease (6076 cases and 370699 participants) and the summary RR was 1.33

(95% CI: 1.21-1.47, I2=63%, pheterogeneity=0.02) (Figure 3). There was no evidence of

publication bias with Egger’s test or with Begg’s test among current smokers, p=0.90 and

p=0.33, former smokers, p=0.93 and p=0.33, or ever smokers, p=0.82 and p=0.72,

respectively (Supplementary Figures 1-3).

Dose-response analyses

Four cohort studies (18-21) were included in the dose-response analysis of cigarettes per day

and diverticular disease risk. The summary relative risk was 1.11 (95% CI: 0.99-

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1.25,I2=82.4%, pheterogeneity=0.001) per 10 cigarettes per day (Figure 3a). There was evidence of

a nonlinear association (pnonlinearity<0.0001), with a slightly steeper increase in risk at low than

high smoking levels, but the association appeared to be linear from about 5 cigarettes smoked

per day and upwards (Figure 3b).

Smoking status and diverticular disease complications

Two studies of current smokers (18;20), two studies of former smokers (18;20), and three

studies of ever smokers (18;20;25), respectively, were included in the analysis of smoking

status and diverticular disease complications (perforation and/or abscess). The summary RR

was 2.54 (95% CI: 1.49-4.33, I2=65.9%, pheterogeneity=0.09) for current smokers, 1.26 (95% CI:

0.81-1.95, I2=0%, pheterogeneity=0.41) for former smokers, and 1.83 (95% CI: 1.25-2.67,

I2=79.2%, pheterogeneity=0.008) for ever smokers (Figure 2d).

Subgroup and sensitivity analyses and cumulative meta-analyses

In subgroup analyses there were positive associations in most strata, defined by sex,

geographic location, number of cases, study quality and adjustment for confounding factors

(Table 2). In meta-regression analyses there was little evidence that the results differed

between these subgroups (Table 2).

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Discussion

To our knowledge this is the first meta-analysis of observational studies of smoking

and the risk of diverticular disease. We found 36%, 17%, and 33% increases in the relative

risks of diverticular disease among current, former and ever smokers, respectively. In the

linear dose-response analysis there was a non-significant 11% increase in the relative risk per

10 cigarettes per day, however, the test for nonlinearity was significant and in the nonlinear

dose-response analysis there was a statistically significant association, with a slightly steeper

increase in the relative risk up to 5 cigarettes per day than at higher levels of consumption,

but with increasing risk with an increasing number of cigarettes smoked per day. In addition,

there was 154% and 83% increases in the relative risks of diverticular disease complications

among current and ever smokers, however, these results were based on only two and three

studies, respectively.

The present systematic review and meta-analysis has some limitations that need to be

discussed. The number of studies included was modest and some studies could not be

included in the dose-response analysis because they only reported on smoking status and not

on the number of cigarettes smoked per day. Further studies should aim to clarify the dose-

response relationship between number of cigarettes per day, duration of smoking, and time

since quitting smoking in relation to diverticular disease risk, and they should report

sufficient detail to be included in future updated dose-response meta-analyses. Many of the

included studies adjusted for important confounding factors and the results persisted in

subgroup analyses by whether the studies adjusted for body mass index, physical activity,

fiber, and red meat, although there were few studies in some of these subgroup analyses.

Publication bias is a possibility but we did not find evidence of such bias with the statistical

tests used or by inspection of the funnel plots, although the number of studies was modest.

Strengths of the present meta-analysis include the detailed dose-response, subgroup and

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sensitivity analyses, and the large sample size providing a robust estimate of the association

between smoking status and risk of diverticular disease.

Given that there was some evidence of a dose-response relationship in the analysis of

number of cigarettes per day and of smoking status and diverticular disease incidence and of

smoking status and diverticular disease complications, with stronger associations with

increasing number of cigarettes smoked per day and among current smokers compared to

former smokers, and with associations for ever smokers in between, it seems that the

observed associations may reflect an underlying biologic effect. However, little is known

about the biological mechanisms that could explain the adverse effect of smoking on risk of

diverticular disease. Smoking impairs immune function, alters gut transit time, reduces blood

flow and is associated with increased risk of other diseases of the colon (14-16;35-38).

Smoking has a prokinetic effect on the bowel and increases intestinal motility and

intraluminal pressure and may thereby enhance the bulging of the colonic mucosa (39;40).

Smoking has also been associated with abdominal fatness (41;42) which has been associated

with increased risk of both diverticulitis and diverticular bleeding (43), and there is some

evidence to suggest that increased fat deposition in the mesentery leads to activation of

macrophages and inflammation (44). In addition, smoking may increase inflammation

directly as it is an established risk factor for Crohn's disease (16), although it has also been

suggested that nicotine inhibits proinflammatory cytokines in the colonic mucosa (45), which

could reduce mucosal immunity, and could result in septic complications (39). Some

evidence suggest that smoking may alter the intestinal microbiota (46-48), which may be of

importance for the development of diverticular disease (49). In addition, our findings of a

stronger association between smoking and complications from diverticular disease (including

abscess or perforation) than with incident diverticular disease is consistent with follow-up

studies of diverticular disease patients requiring surgery or hospitalization, which reported

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that smoking was associated with a 2-3 fold increase in complications (39;40), suggesting

that smoking might enhance the disease process. Smokers have higher plasma concentrations

of serotonin, which may cause vasoconstriction in the endothelium (50), and it is possible that

a compromised blood supply to the colonic wall may contribute to an increased number of

strictures and perforations (40).

In conclusion, the results from this systematic review and meta-analysis confirm that

smoking increases the risk of developing diverticular disease. Because an increased risk was

observed among former smokers as well, further studies are needed to clarify the effects of

long-term smoking cessation on the risk of diverticular disease. However, the current results

add to the already huge burden of disease caused by tobacco smoking and provide further

support for efforts to reduce the prevalence of smoking.

Conflict of interest: The authors declare that there are no conflicts of interest.

Funding: This project was funded the Imperial College National Institute of Health Research

(NIHR) Biomedical Research Centre (BRC). The funders had no role in the study design,

data collection, data analysis and interpretation, writing of the report, or the decision to

submit the article for publication.

Contribution: DA had full access to all of the data and takes responsibility for the integrity of

the data and the accuracy of the data analysis. DA and AS are guarantors for the study. Study

concept and design: DA, ML, ST, LJV. Acquisition, analysis or interpretation of data: DA,

AS, ML, ST, LJV. Checking of data extractions: AS. Drafting of manuscript: DA. Critical

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revision of the manuscript for important intellectual content: DA, AS, ML, ST, LJV.

Statistical analysis: DA. Obtained funding: DA, ML, ST, LJV. Study supervision: LJV.

Funding: This project was funded by the Imperial College National Institute of Health

Research (NIHR) Biomedical Research Centre (BRC). The funders had no role in the study

design, data collection, data analysis and interpretation, writing of the report, or the decision

to submit the article for publication.

Role of the Sponsors: The funding sources had no role in the design and conduct of the study,

collection, management, analysis, and interpretation of the data; preparation, review, or

approval of the manuscript; and decision to submit the manuscript for publication.

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Table 1. Prospective studies of smoking and diverticular disease

First author, publication year, country

Study name Study period

Number of participants, number of cases

ICD - code or outcome definition

Smoking exposure Quantity Relative risk (95% confidence interval)

Adjustment for confounders

Aldoori WH et al, 1995, USA

Health Professionals Follow-up Study

1988-1992, 4 years follow-up

47678 men, age 40-75 years: 382 symptomatic diverticular disease cases

Not available, self-reported symptomatic diverticular disease (confirmed by supplementary questionnaires)

Smoking status

Smoking, pack-years

NonsmokersPastCurrent, 1-14 cig/dCurrent, 15-24Current, ≥25Nonsmokers1-9 pack-years10-1920-2930-39≥40

1.000.96 (0.77-1.19)0.94 (0.50-1.80)1.28 (0.78-2.11)1.25 (0.75-2.09)1.000.73 (0.51-1.05)1.00 (0.71-1.40)1.30 (0.94-1.82)0.72 (0.44-1.16)1.21 (0.90-1.64)

Age, physical activity, dietary fiber, total fat

Rosemar A et al, 2008, Sweden

The Multifactorial Prevention Trial

1970-1973 - 1998, max 28 years follow-up

7494 men, age 47-55 years: 112 diverticular disease hospitalizations

ICD-8 and 9: 562.11, 562.18, 562.19, 562BICD-10: 57.4, 57.5, 57.8, 57.9

Smoking status NoYes

1.01.4 (1.0-2.0)

Age

Humes DJ et al, 2011, United Kingdom

UK General Practice Research Database

1990-2005, ~15 years follow-up

Nested case-control study: 899 cases of diverticular perforation8980 controlsAge 45-≥85 years

Not available, diverticular perforation (excluding acute diverticulitis, diverticular abscess, diverticular bleeding)

Smoking status NeverEver

1.001.54 (1.31-1.80)

Age, sex

Hjern F et al, 2011, Sweden

Swedish Mammography Cohort

1997-2009, 12 years follow-up

35809 women, mean age 61.8 years: 561 symptomatic diverticular

Diverticular disease cases: ICD-10: K57.2, K57.3, K57.9

Smoking status, diverticular disease

NeverFormer, allFormer, 1-9 cig/dFormer, ≥10 cig/dCurrent, all

1.001.26 (1.02-1.56)1.13 (0.85-1.50)1.33 (1.01-1.76)1.23 (0.99-1.52)

Age, dietary fiber, diabetes, hypertension, acetylsalicylic acid, NSAID

19

disease cases

90 diverticular disease cases with abscess/ perforation

Diverticular disease perforation/ abscess: K57.2

Smoking status, diverticular disease with abscess/ perforation

Current, 1-9 cig/dCurrent, ≥10 Ever, allEver, 1-9 cig/dEver, ≥10NeverFormer, allFormer, 1-9 cig/dFormer, ≥10 cig/dCurrent, allCurrent, 1-9 cig/dCurrent, ≥10 Ever, allEver, 1-9 cig/dEver, ≥10

1.27 (0.95-1.70)1.08 (0.82-1.42)1.24 (1.04-1.48)1.19 (0.96-1.49)1.19 (0.96-1.48)1.001.07 (0.60-1.92)0.91 (0.40-2.04)1.45 (0.71-2.96)1.89 (1.15-3.10)2.30 (1.26-4.20)1.46 (0.76-2.81)1.48 (0.95-2.29)1.54 (0.91-2.62)1.45 (0.84-2.50)

use, steroid medication, alcohol, BMI, physical activity, education

Crowe FL et al, 2012, United Kingdom

EPIC-Oxford Study

1993-1999 - 2009, 11.6 years follow-up

47033 men and women, age ≥20 years: 812 diverticular disease cases

ICD-9: 562 and ICD-10: K57

Smoking status NeverFormerCurrent, <15 cig/dCurrent, ≥15 cig/d

1.001.31 (1.13-1.53)1.34 (0.98-1.82)1.86 (1.36-2.54)

Age, sex, method of recruitment, region of residence

Humes DJ et al, 2016, Sweden

Swedish Construction Workers Cohort

1971-1993 - 2013, 30/29 years follow-up

232685 men and 14592 women, age 20-79 years: 3891/318 symptomatic diverticular disease cases

129 diverticular disease cases with abscess or perforation

Diverticular disease cases: ICD-9: 562 and ICD-10: K57, 562

Perforated/ abscess: ICD-10: K57.0, K57.2, K57.4, K57.6, K57.8

Tobacco smoking, men

Tobacco smoking, women

Tobacco smoking, complicated diverticular disease

NonsmokersEx-smokersCurrent smokers, <15 cig/dCurrent smokers, ≥15 cig/dNonsmokersEx-smokersCurrent smokers, <15 cig/dCurrent smokers, ≥15 cig/d

NonsmokersEx-smokersCurrent smokers, <15 cig/dCurrent smokers, ≥15 cig/d

1.001.14 (1.04-1.27)1.39 (1.27-1.52)1.56 (1.42-1.72)1.001.33 (0.92-1.92)1.64 (1.25-2.14)1.12 (0.81-1.55)

1.001.55 (0.80-2.99)2.80 (1.64-4.77)3.80 (2.21-6.51)

Age, BMI, lag time, SES

20

Table 2. Subgroup analyses of smoking status and diverticular disease

Current Smoking Former smoking Ever smoking

n RR (95% CI) I2 (%) Ph1 Ph

2 n RR (95% CI) I2 (%) Ph1 Ph

2 n RR (95% CI) I2 (%) Ph1 Ph

2

All studies 4 1.36 (1.15-1.61) 83.7 <0.0001 4 1.17 (1.05-1.31) 49.2 0.12 5 1.29 (1.17-1.44) 61.9 0.03

Follow-up

<10 years 1 1.14 (1.04-1.27) 0.05 1 0.96 (0.77-1.19) 0.21 1 1.03 (0.86-1.23) 0.06

≥10 years 3 1.47 (1.38-1.56) 0 0.69 3 1.21 (1.11-1.31) 11.4 0.32 4 1.36 (1.30-1.43) 0 0.59

Sex

Men 2 1.30 (1.01-1.67) 94.1 <0.0001 0.39/

0.783

2 1.08 (0.92-1.26) 49.4 0.16 0.14/

0.323

3 1.27 (1.02-1.59) 78.8 0.009 0.58/

0.843 Women 2 1.38 (1.15-1.66) 0 0.81 2 1.28 (1.06-1.54) 0 0.80 2 1.31 (1.16-1.49) 0 0.37

Men and women 1 1.58 (1.27-1.96) 1 1.31 (1.13-1.53) 1 1.39 (1.23-1.58)

Geographic location

Europe 3 1.47 (1.38-1.56) 0 0.69 0.05 3 1.21 (1.11-1.31) 11.4 0.32 0.21 4 1.36 (1.30-1.43) 0 0.59 0.06

America 1 1.14 (1.04-1.27) 1 0.96 (0.77-1.19) 1 1.03 (0.86-1.23)

Asia 0 0 0

Number of cases

<250 0 0.05 0 0.21 1 1.60 (1.10-2.30) 0.90

250-<500 1 1.14 (1.04-1.27) 1 0.96 (0.77-1.19) 1 1.03 (0.86-1.23)

21

≥500 3 1.47 (1.38-1.56) 0 0.69 3 1.21 (1.11-1.31) 11.4 0.32 3 1.35 (1.29-1.42) 0 0.56

Study quality

0-3 stars 0 0.43 0 0.36 0 0.32

4-6 stars 1 1.58 (1.27-1.96) 1 1.31 (1.13-1.53) 2 1.41 (1.25-1.59) 0 0.48

7-9 stars 3 1.30 (1.06-1.60) 87.9 <0.0001 3 1.13 (1.00-1.27) 38.9 0.19 3 1.22 (1.03-1.44) 77.8 0.01

Adjustment for confounding factors3

Age Yes 4 1.36 (1.15-1.61) 83.7 <0.0001 NC 4 1.17 (1.05-1.31) 49.2 0.12 NC 5 1.29 (1.17-1.44) 61.9 0.03 NC

No 0 0 0

Education Yes 1 1.33 (0.92-1.92) 0.93 1 1.26 (1.02-1.56) 0.67 1 1.24 (1.04-1.48) 0.80

No 3 1.36 (1.12-1.66) 89.1 <0.0001 3 1.15 (1.00-1.33) 63.0 0.07 4 1.30 (1.15-1.48) 69.4 0.02

Alcohol Yes 1 1.33 (0.92-1.92) 0.93 1 1.26 (1.02-1.56) 0.67 1 1.24 (1.04-1.48) 0.80

No 3 1.36 (1.12-1.66) 89.1 <0.0001 3 1.15 (1.00-1.33) 63.0 0.07 4 1.30 (1.15-1.48) 69.4 0.02

Diabetes Yes 1 1.33 (0.92-1.92) 0.93 1 1.26 (1.02-1.56) 0.67 1 1.24 (1.04-1.48) 0.80

No 3 1.36 (1.12-1.66) 89.1 <0.0001 3 1.15 (1.00-1.33) 63.0 0.07 4 1.30 (1.15-1.48) 69.4 0.02

Aspirin use Yes 1 1.33 (0.92-1.92) 0.93 1 1.26 (1.02-1.56) 0.67 1 1.24 (1.04-1.48) 0.80

No 3 1.36 (1.12-1.66) 89.1 <0.0001 3 1.15 (1.00-1.33) 63.0 0.07 4 1.30 (1.15-1.48) 69.4 0.02

NSAID use Yes 1 1.33 (0.92-1.92) 0.93 1 1.26 (1.02-1.56) 0.67 1 1.24 (1.04-1.48) 0.80

No 3 1.36 (1.12-1.66) 89.1 <0.0001 3 1.15 (1.00-1.33) 63.0 0.07 4 1.30 (1.15-1.48) 69.4 0.02

22

Acetampinophen Yes 0 NC 0 NC 0 NC

No 4 1.36 (1.15-1.61) 83.7 <0.0001 4 1.17 (1.05-1.31) 49.2 0.12 5 1.29 (1.17-1.44) 61.9 0.03

BMI Yes 2 1.46 (1.37-1.55) 0 0.63 0.70 2 1.17 (1.07-1.27) 0 0.44 0.81 2 1.35 (1.28-1.42) 0 0.33 0.87

No 2 1.32 (0.96-1.82) 86.1 0.007 2 1.13 (0.84-1.54) 81.1 0.02 3 1.28 (1.01-1.64) 77.1 0.01

Physical activity Yes 2 1.15 (1.05-1.27) 0 0.43 0.05 2 1.10 (0.84-1.44) 67.4 0.08 0.56 2 1.13 (0.94-1.36) 52.3 0.15 0.07

No 2 1.47 (1.38-1.56) 0 0.49 2 1.21 (1.07-1.37) 50.9 0.15 3 1.37 (1.30-1.44) 0 0.67

Meat Yes 0 NC 0 NC 0 NC

No 4 1.36 (1.15-1.61) 83.7 <0.0001 4 1.17 (1.05-1.31) 49.2 0.12 5 1.29 (1.17-1.44) 61.9 0.03

Fiber Yes 2 1.15 (1.05-1.27) 0 0.43 0.05 2 1.10 (0.84-1.44) 67.4 0.08 0.56 2 1.13 (0.94-1.36) 52.3 0.15 0.07

No 2 1.47 (1.38-1.56) 0 0.49 2 1.21 (1.07-1.37) 50.9 0.15 3 1.37 (1.30-1.44) 0 0.67

ndenotes the number of studies,

1P for heterogeneity within each subgroup,

2 P for heterogeneity between subgroups with meta-regression analysis