fruits and vegetables consumption and risk of non-hodgkin's lymphoma: a meta-analysis of...

Fruits and vegetables consumption and risk of non-Hodgkin’slymphoma: A meta-analysis of observational studies

Guo-Chong Chen1, Da-Bing Lv2, Zhi Pang3 and Qing-Fang Liu1

1 Department of Epidemiology, School of Public Health, Soochow University, China2 Department of Health Statistics, School of Public Health, Soochow University, China3 Department of Gastroenterology, Suzhou Municipal Hospital (North Campus), China

Epidemiologic evidence suggests that intakes of fruits and/or vegetables may play a role in the etiology of non-Hodgkin’s

lymphoma (NHL), but the findings are inconsistent. We aimed to assess fruits and/or vegetables intakes in relation to risk of

NHL by a meta-analytic approach. We searched on PubMed database from January 1966 to September 2012 to indentify case-

control and cohort studies. We used a random-effects model to compute summary risk estimates. For vegetables, the

summary relative risks (RRs) of NHL for high versus low intake for case-control, cohort and all studies were 0.75 (95% CI,

0.60–0.94; N 5 8), 0.90 (95% CI, 0.81–1.00; N 5 5) and 0.81 (95%CI, 0.71–0.92; N 5 13) ; and the corresponding RRs for

intake of 1 serving per day were 0.88 (95% CI, 0.80–0.96; N 5 8), 0.96 (95% CI, 0.92–1.00; N 5 5) and 0.92 (95%CI, 0.87–

0.96; N 5 13). For fruits and vegetables combined, the summary RR for high versus low intake was 0.78 (95%CI, 0.66–0.92;

N 5 4), and for intake of 1 serving per day was 0.95 (95%CI, 0.91–1.00; N 5 4). Regarding histological subtypes, vegetables

intake was significantly inversely associated with diffuse large B-cell lymphoma and follicular lymphoma, but not small

lymphocytic lymphoma/chronic lymphocytic leukemia (high vs. low intake, RR 5 0.70, 0.70 and 1.01, respectively; N 5 7, 7

and 10, respectively). Fruits intake was generally not associated with total NHL, or any histological subtypes. Our findings

suggest that intakes of vegetables, and fruits and vegetables combined, but not fruits alone, significantly reduce risk of NHL.

IntroductionNon-hodgkin’s lymphoma (NHL) is a heterogeneous groupof malignancies arising from lymphocytes. In particular inthe developed countries, the incidence and mortality rates ofNHL increased steadily over the later half of the 20th cen-tury.1,2 The established risk factors such as immunodeficiencyand viral infection are only responsible for a small propor-tion of this disease, 3,4 and the remaining reasons for theincreasing cases of NHL are largely unclear.

Diet has been hypothesized to play a role in the develop-ment of NHL.5 Among these, fruits and vegetables are promis-

ing protective factors because they are major dietary sources ofantioxidants which shown to have anticarcinogenic properties.Over the last three decades, many observational studies whoseprimary or secondary aims were looking at the relationshipsbetween fruits and/or vegetables and risk of NHL have beencarried out, 6–23 but the results have been inconsistent andinconclusive. Several potential explanations for the disparatefindings have been proposed, including low statistical power,and the differences in study designs, populations studied, distri-bution of various histological subtypes of NHL, adjustment forpotential confounders and methods used in the assessments ofexposures and cases. Hence, to systematically and quantitativelyassess the association of fruits and vegetables consumption withNHL risk is of both scientific and public health significance.We chose to conduct a meta-analysis of observational studies toinvestigate the effects of fruits and/or vegetables on risk of NHLand its histological subtypes, and also to evaluate the impacts ofsome individual fruits and vegetables on total NHL risk.

Material and MethodsLiterature search

We performed a literature search from January 1966 through Sep-tember 2012 on PubMed database (www.ncbi.nlm.nih.gov/pubmed) using the search terms as follows: (i) fruit, vegetable andcitrus; (ii) lymphoma and cancer; and (iii) cohort, prospective, fol-low-up, case-cohort, case-control and retrospective, with no lan-guage restrictions imposed. We also comprehensively reviewedthe reference lists of the retrieved articles to identify additionalstudies.

Key words: fruits, vegetables, diet, non-Hodgkin’s lymphoma, meta-

analysisAbbreviations: BMI: body mass index; CI: confidence interval; CLL:

B-cell chronic lymphocytic leukemia; DLBCL: diffuse large B-cell

lymphoma; FFQ: food-frequency questionnaire; FL: follicular

lymphoma; NHL: non-Hodgkin’s lymphoma; OR: odds ratios; RR:

relative risk; SLL: small lymphocytic lymphoma

Grant sponsor: Priority Academic Program Development of Jiangsu

Higher Education Institutions (PAPD)

DOI: 10.1002/ijc.27992

History: Received 6 Aug 2012; Accepted 12 Nov 2012; Online 13

Dec 2012

Correspondence to: Qing-Fang Liu, Department of Epidemiology,

School of Public Health, Soochow University, 199 Renai Road,

Dushu Lake Higher Education Town, Suzhou 215123, China.

Tel.: 86-0512-65880079, Fax: 86-0512-65884830, E-mail: lsguorong@

126.com

Epidemiology

Int. J. Cancer: 133, 190–200 (2013) VC 2012 UICC

International Journal of Cancer

IJC

Study selection

Studies were included if they met the following criteria: (i)the study had a prospective cohort or case-control design; (ii)the exposure of interest was consumption of fruits or vegeta-bles, or fruits and vegetables combined; (iii) the outcome ofinterest was NHL incidence; and (iv) the relative risk (RR)estimates [or odds ratios (OR) in case-control studies] withcorresponding 95% confidence interval (CI) were provided,or could be calculated using the raw data presented in thestudies. When multiple published publications from the samestudy were available, we used the paper with the largestsample size in the primary analyses, and used the others inthe subgroup analyses if they provided useful data whichwere not available in the paper with the larger sample size.Cross sectional studies were excluded.

Data extraction

The following data were extracted from each included eligiblestudy using a standardized data-collection form: study design,the first author’s last name, publication year, the characteris-tics of participants or controls (population based, hospitalbased or community based), sex of participants, number ofcases and participants, the kind of exposure(total or individ-ual fruits and/or vegetables), assessment of cases and expo-sure, fruits and vegetable categories, the RR or OR of NHLand corresponding 95% CI for each category of fruits andvegetables consumption, and variables adjusted for in theanalysis. We extracted the maximally adjusted RR or ORwith corresponding 95% CI for the highest versus lowestcategory of fruits and vegetables consumption for use in theprimary analyses. Data extraction were conducted independ-ently by two authors (G.-C.C. and Q.-F.L.), with any dis-agreements resolved by consensus.

Statistical analysis

We used a DerSimonian and Laird random-effects model,24

which considers both within-and between-study variation tocalculate the summary risk estimate. Because outcomes wererelatively rare, the ORs in case-control studies were consid-ered approximations of RRs. For 116 study that presentedresults on NHL subtypes separately, but not overall NHL, wecombined the results using a fixed-effects model and thenincluded the pooled RR estimates in the meta-analysis. Forthe studies6,8,14,21 that reported results separately for menand women, but not combined, we also used a fixed-effectsmodel to pool the risk estimates. We included in the primary

analyses only the food items described as ‘‘all vegetable(s)’’,‘‘total vegetable(s),’’ ‘‘vegetable(s),’’ ‘‘all fruit(s),’’ ‘‘totalfruit(s),’’ or ‘‘fruit(s).’’ We also assessed some specific fruitsand vegetables including citrus fruits, cruciferous vegetablesand green leaf vegetables. We only included the food itemsdescribed in primary studies as ‘‘citrus,’’ ‘‘citrus fruit(s),’’‘‘cruciferous vegetable(s)’’ or ‘‘green leaf vegetable(s)’’ in theanalysis of these subcategories. We also attempted to evaluateother subcategories that were described as ‘‘green vegeta-ble(s),’’ ‘‘leaf vegetable(s),’’ ‘‘yellow/orange vegetable(s),’’ and‘‘yellow/orange and red vegetable(s),’’ but the number ofincluded studies assessing these vegetable(s) was too limited.

To investigate the impacts of various study characteristicson the summary risk estimates, we also conducted subgroupanalyses stratified by study designs, geographic areas, subjectcharacteristics (population-based, hospital-based and commu-nity-based), sex, the number of FFQ items used in exposureassessment, rang of intakes and adjustment for confounders.We also examined relationship between fruits and vegetablesand NHL by common histological subtypes [including diffuselarge B-cell lymphoma (DLBCL), follicular lymphoma (FL)and small lymphocytic lymphoma/chronic lymphocytic leuke-mia (SLL/CLL)].

Given that fruits and/or vegetables intakes in the highestand lowest categories differed substantially between studies,we also conducted a dose-response analysis by use of themethod proposed by Greenland and Longnecker 25 andOrsini et al.26 This method requires that the number of casesand controls (or person-years in cohort studies) and the riskestimates with their variance estimates for at least 3 quantita-tive exposure categories are known. For the studies10,13,15,20

that did not provide the number of cases and controls (orperson-years) in each exposure category, we estimated thesedata from total number of cases and controls (or person-years). For each study, the median or mean level of fruitsand vegetables consumption for each category was assignedto each corresponding RR estimate. When the median ormean intake per category was not provided, we assigned themidpoint of the upper and lower boundaries in each categoryas average intake. If the highest or lowest category was open-ended, we assumed the width of the interval to be the sameas in the closest category. For the studies that providedresults in grams per day, we used 80 g as a serving size toestimate the RR with 95% CI for a 1 serving per day increasein intakes.27 When results for intakes were reported as a con-tinuous variable (e.g., for 100 g/d increase in intake), werescaled the RR to a 1 serving per day increase in intakes.

What’s new?

Eating fruits and vegetables surely affects one’s risk of developing non-Hodgkin’s lymphoma, but findings reported over the

years have not produced a clear picture of how diet affects risk. This study aimed to clear up the confusion by collating the

findings from various reports. The authors looked at 14 different papers dealing with the association between non-Hodgkin’s

lymphoma and consumption of either fruits, vegetables, or both. They found that eating vegetables, or fruits and vegetables,

but not fruits alone, reduces risk of NHL.

Epidemiology

Chen et al. 191


For 121 study that used cup equivalents as a measure, weassumed a cup equivalent to be equal to a serving size in theprimary analysis, and used 1.5 servings as a cup equivalentsize in the sensitivity analysis, and we also test whether thesummary risk estimates were substantially altered if excludingthis study.

Heterogeneity test was performed by use of Q and I2

statistics.28 For the Q statistic, a p-value of less than .1 wasconsidered statistically significant heterogeneity. Potentialpublication bias was investigated by use of Begg’s funnel plotsand Egger’s regression asymmetry test.29 All statistical analy-ses were done using STATA software, version 11.0 (STATAcorp., College Station, TX). All p-values are two-sided andp < 0.05 was considered statistically significant, unless explic-itly stated.

ResultsLiterature search

Briefly, a total of 2,897 citations were identified through theprimary search. After screening the titles and the abstracts,30 articles appeared to be relevant to this meta-analysis andwere selected for full-text review. Two30,31 were excluded forirrelevant exposure, 432–35 were excluded because there wasno information on NHL, one 36 was excluded because theywere on individual fruits and vegetables that were notincluded in the analyses of subcategories of fruits and vegeta-bles (e.g., apples, pears, tomatoes), 55,37–40 were excludedbecause they were duplicate reports of 311,14,18 other largerstudies. For the Iowa Women’ Health Study with 35,17,18

overlapping reports, we included the report with the largestsample size in the primary analyses,18 and excluded 15 fromthis meta-analysis, and included the remaining 117 whichpresented result for CLL in the NHL subtypes analyses,because the results by histological subtypes were not providedin the report used for the primary analyses. One19 publica-tion from two large independent cohort studies in which theoutcomes were SLL/CLL only, was also excluded from pri-mary analyses but included in the analyses by histologicalsubtypes. Two22,23 papers on the association of citrus fruitsand total NHL were included in the analyses of subcategoriesof fruits, but excluded from any other analyses.

Hence, 186–20 publications from 17 studies (six cohortstudies, 11 case-control studies) were included in this meta-analysis, 146–16,18,20 of which were included in the primaryanalyses. Table 1 shows the characteristics of the selectedcase-control and cohort studies. Of the 14 studies that wereincluded in the primary analyses, four were from Europe,eight from the United States, one Canada and one Uruguay,and they were published between 1994 and 2012, and con-tained a total of 8718 NHL cases and 1,152,650 participants.

Fruits and vegetables

High- versus low-analysis. Four6,15,18,20 studies presentedresults on the association of total fruits and vegetables intakewith risk of NHL. The summary RR for the highest versus

the lowest intake was 0.78 (95%CI, 0.66–0.92), with no heter-ogeneity (p ¼ 0.46, I2 ¼ 0.0%) (Fig. 1a).

Dose-response analysis. The summary RR of four studiesfor an increment of total fruits and vegetables intake of 1serving/d was 0.95 (95%CI, 0.91–1.00), and the inverseassociation was statistically significant (p ¼ 0.03), with lowheterogeneity (p ¼ 0.27, I2 ¼ 23.2%) (Fig. 1b).

Fruits

High versus low analysis. Thirteen 6–13,15,16,18,20,21 studies(five cohort and eight case-control) were included in theanalysis of high versus low fruits intake and NHL. The sum-mary RR was 0.97 (95%CI, 0.87–1.08), with moderate hetero-geneity (p ¼ 0.07, I2 ¼ 39.7%; Fig. 2a).

Dose-response analysis. One 11 study was not eligible fordose-response analysis. The dose-response analysis of theremaining 12 studies showed that the summary RR per 1serving/d was 0.98 (95%CI, 0.94–1.02), with moderate hetero-geneity (p ¼ 0.02, I2 ¼ 51.5%; Fig. 2b).

Vegetables

High versus low analysis. Thirteen6–10,12–16,18,20,21 studies(five cohort and eight case-control) were included in theanalysis of high versus low vegetables intake and NHL. Thesummary RR was 0.81 (95%CI, 0.71–0.92), with moderateheterogeneity (p ¼ 0.02, I2 ¼ 51.6%; Fig. 3a).

Dose-response analysis. All 13 studies were included in thedose-response analysis. The summary RR per 1 serving/d ofvegetables intake was 0.92 (95%CI, 0.87–96), with moderateheterogeneity (p ¼ 0.003, I2 ¼ 59.4%; Fig. 3b).

Subgroup and sensitivity analyses

In the subgroup analysis (Table 2), there was no significantassociation between high versus low fruits intake and NHL inmost strata, except in the subgroup that was stratified bywhether or not adjusting for alcohol intake. The summary highversus low RR was 1.10 (95%CI, 1.00–1.21) for 68,10–12,16,21 stud-ies that adjusted for alcohol intake (or beer intake in 18 study),and was 0.85 (95%CI, 0.73–0.98) for those that did not (p-inter-action ¼ 0.02). When excluding the hospital based case–controlstudies from this subgroup, the corresponding RR was 1.14(95%CI, 1.02–1.28; N ¼ 410,12,16,21) and 0.89 (95%CI, 0.77–1.04;N ¼ 56,7,15,18,20), respectively. The association between high ver-sus low vegetables intake and NHL was inverse in most strata,although not always statistically significant. The significantinverse association was observed in women, and men andwomen combined, but not in men (p-interaction; N ¼ 0.02).

Ten6,7,9,10,12,15–19 studies (five case–control studies, fivecohort studies) presented results by histological subtypes. Inthe high versus low analyses, fruits intake was not signifi-cantly associated with any histological subtypes of NHL,vegetables intake was statistically significantly inversely asso-ciated with DLBCL (RR ¼ 0.70; 95% CI, 0.54–0.91) and FL

Epidemiology

192 Fruits, vegetables and non-Hodgkin’s lymphoma


Table

1.

Ch

ara

cte

rist

ics

of

the

incl

ud

ed

case

–co

ntr

ol

an

dco

ho

rtst

ud

ies

on

fru

its

an

dve

ge

tab

les

inta

ke

sa

nd

no

n-H

od

gk

in’s

lym

ph

om

a

Study(Location)

Subjects

(number)

Sex

Cases

Exp

osu

reCompariso

ns

OR/R

R(95%CI)

Exp

osu

res

assessment

NHL

assessment

Adjustment

Case-controlstudies

Wa

rd1

4(U

nit

ed

Sta

tes)

Po

pu

lati

on

ba

sed

(14

32

)M

/F3

85

(NH

L)V

eg

eta

ble

s�

27vs

.<

16

serv

/wk

1.0

(0.6

–1

.6)

(M)

30

-ite

mFF

QN

ot

spe

cifi

ed

Ag

e.

0.9

(0.5

–1

.7)

(F)

De

Ste

fan

i8

(Uru

gu

ay)

Ho

spit

al

ba

sed

(16

3)

M/F

16

0(N

HL)

Fru

its

>5

.1vs

.�

1.1

serv

/wk

(M)

1.7

9(0

.74

–4

.36

)(M

)FF

QN

ot

spe

cifi

ed

Me

n:

Ag

e,

resi

de

nce

,u

rba

n/r

ura

lst

atu

s,sm

ok

ing

,b

ee

rin

tak

ea

nd

ma

te/y

ea

rs.

>7

.0vs

.�

3.0

serv

/wk

(F)

0.7

8(0

.33

–1

.83

)(F

)

Ve

ge

tab

les

>3

.1vs

.�

1.0

serv

/wk

(M)

1.3

7(0

.58

–3

.23

)(M

)W

om

en

:A

ge

,re

sid

en

ce,

urb

an

/ru

ral

sta

tus,

yea

ro

fd

iag

no

sis

an

dp

ari

ty.

>3

.1vs

.�

1.0

serv

/wk

(F)

2.5

7(0

.98

–6

.71

)(F

)

LaV

ecc

hia

11

(Ita

ly)

Ho

spit

al

ba

sed

(10

05

8)

M/F

52

9(N

HL)

Fru

its

Hig

hvs

.Lo

w0

.95

(0.8

–1

.2)

14

–3

7it

em

FFQ

No

tsp

eci

fie

dA

ge

,a

rea

of

resi

de

nce

,ca

len

da

rp

eri

od

at

inte

rvie

w,

ed

uca

tio

n,

smo

kin

g,

alc

oh

ol

con

sum

pti

on

an

dse

x.

Pu

rdu

e1

2

(Ca

na

da

)P

op

ula

tio

nb

ase

d(5

03

9)

M/F

16

42

(NH

L)Fr

uit

s>

2.6

vs.0

–3

serv

/10

,00

0K

J1

.23

(1.0

0–

1.5

1)

69

-ite

mFF

QIC

D-9

,IC

D-O

-2A

ge

,se

x,in

com

ea

de

qu

acy

,in

tak

es

of

alc

oh

ol,

tota

le

ne

rgy,

fru

it,

veg

eta

ble

,p

ota

toe

s,Le

gu

me

sa

nd

nu

ts,

bre

ad

an

dce

rea

l,d

ess

ert

foo

d,

an

ima

lp

rote

in,

an

dfa

t.

Ve

ge

tab

les

>2

.8vs

.0

–1

.6se

rv/1

0,0

00

KJ

0.8

5(0

.68

–1

.07

)

Ch

an

g1

5

(Sw

ed

en

)P

op

ula

tio

nb

ase

d(4

67

)M

/F5

97

(NH

L)Fr

uit

s>

3.0

vs.

0–

1.2

serv

/d;

1.0

(0.6

–1

.7)

(M)

13

7-i

tem

FFQ

WH

O cla

ssifi

cati

on

Ag

e.

0.6

(0.3

–1

.1)

(F)

Ve

ge

tab

les

>4

.0vs

.0

–1

.9se

rv/d

;1

.0(0

.6–

1.6

)(M

)

0.5

(0.3

–0

.8)

(F)

Fru

its

an

dve

ge

tab

les

>7

.0vs

.0

–3

.5se

rv/d

;0

.9(0

.6–

1.5

)(M

)

0.4

(0.2

–0

.8)

(F)

Tala

min

i13

(Ita

ly)

Ho

spit

al

ba

sed

(48

4)

M/F

19

0(N

HL)

Fru

its

>3

4.5

vs.<

16

.5se

rv/w

k;

0.5

1(0

.30

–0

.85

)6

3-i

tem

FFQ

ICD

-OA

ge

,g

en

de

r,ce

nte

r,e

du

cati

on

,p

lace

of

bir

th,

HC

V(h

ep

ati

tis

Cvi

rus)

test

,a

nd

tota

le

ne

rgy

inta

ke

.

Table

1.

Ch

ara

cte

rist

ics

of

the

incl

ud

ed

case

–co

ntr

ol

an

dco

ho

rtst

ud

ies

on

fru

its

an

dve

ge

tab

les

inta

ke

sa

nd

no

n-H

od

gk

in’s

lym

ph

om

a(C

on

tin

ue

d)

Study(Location)

Subjects

(number)

Sex

Cases

Exp

osu

reCompariso

ns

OR/R

R(95%CI)

Exp

osu

res

assessment

NHL

assessment

Adjustment

Ve

ge

tab

les

>1

9.0

vs.<

10

.0se

rv/w

k0

.49

(0.2

8–

0.8

7)

Ke

lem

en

10

(Un

ite

dS

tate

s)P

op

ula

tio

nb

ase

d(3

91

)M

/F4

66

(NH

L)Fr

uit

s>

23vs

.�

8se

rv/w

k0

.88

(0.4

3–

1.8

1)

FFQ

No

tsp

eci

fie

dA

ge

,se

x,st

ud

yce

nte

r,ra

ce,

tota

le

ne

rgy

inta

ke

,sm

ok

ing

,fa

mil

yh

isto

ryo

fN

HL,

BM

I,e

xerc

ise

,e

du

cati

on

,a

lco

ho

l,a

nd

die

tary

fib

er.

Ve

ge

tab

les

>2

0vs

.�

8se

rv/w

k0

.58

(0.3

8–

0.9

5)

Ch

iu7

(Un

ite

dS

tate

s)P

op

ula

tio

nb

ase

d(4

70

)M

/F3

48

(NH

L)Fr

uit

s�

17

0vs

.�

47

g/w

k;

0.8

(0.5

–1

.3)

FFQ

WH

O cla

ssifi

cati

on

Ag

e,

sex,

ma

rita

lst

atu

s,B

MI,

an

dto

tal

en

erg

yin

tak

e.

Ve

ge

tab

les

�1

62vs

.�

66

g/w

k;

0.8

(0.5

–1

.3)

Ho

lta

n9

(Un

ite

dS

tate

s)H

osp

ita

lb

ase

d(1

00

7)

M/F

60

3(N

HL)

Fru

its

>1

02

vs<

36

.3se

rv/m

o;

0.8

9(0

.66

–1

.21

)1

28

-ite

mFF

QW

HO cla

ssifi

cati

on

Ag

e,

sex,

resi

de

nce

an

dto

tal

en

erg

y.

Ve

ge

tab

les

>1

09

.8vs

.<

42

.0se

rv/m

o;

0.5

2(0

.37

–0

.72

)

Mo

zah

eb

23

a

(Ira

n)

Ho

spit

al

ba

sed

(19

0)

17

0C

itru

sQ

4vs

.Q

10

.06

8(0

.03

7–

0.1

25

)6

0-i

tem

FFQ

WH

O cla

ssifi

cati

on

-

Cohort

studies

Zh

an

g2

0(U

nit

ed

Sta

tes)

Co

mm

un

ity

ba

sed

(88

41

0)

F1

99

(DLB

CL/

FL)

Fru

its

�3vs

.<1

serv

/d0

.79

(0.4

9–

1.2

7)

61

/11

6-i

tem

FFQ

ICD

Ag

e,

tota

le

ne

rgy,

len

gth

of

foll

ow

-up

,g

eo

gra

ph

icre

gio

n,

smo

kin

g,

he

igh

t,a

nd

be

ef,

po

rko

rla

mb

as

am

ain

dis

h.

Ve

ge

tab

les

�3vs

.<1

serv

/d0

.65

(0.3

7–

1.1

3)

Fru

its

an

dve

ge

tab

les

�6vs

.<3

serv

/d0

.69

(0.4

2–

1.1

5)

Ro

ss1

7b

(Un

ite

dS

tate

s)C

om

mu

nit

yb

ase

d(3

52

21

)F

58

(CLL

)Fr

uit

s>

20

.9vs

.<1

3.1

serv

/wk

0.7

2(0

.35

–1

.49

)1

26

-ite

mFF

QIC

D-O

Ag

e,

en

erg

yin

tak

e,

blo

od

tra

nsf

usi

on

sta

tus,

ed

uca

tio

n,

BM

I,a

nd

smo

kin

g.

Ve

ge

tab

les

>2

8.0

vs.<

18

.1se

rv/w

k0

.86

(0.4

2–

1.7

6)

Ro

hrm

an

n1

6

(10

Eu

rop

ea

nco

un

trie

s)

Po

pu

lati

on

ba

sed

(41

10

97

)M

/F8

10

(NH

L)Fr

uit

s>

31

9vs

.<1

05

g/d

1.5

9(0

.48

–5

.23

)(T

-NH

L)FF

QIC

D-O

-2,

ICD

-O-3

Sm

ok

ing

,a

lco

ho

lin

tak

e,

en

erg

yin

tak

e,

an

de

du

cati

on

.

1.0

4(0

.81

–1

.33

)(B

-NH

L)

Ve

ge

tab

les

>2

75vs

.<1

09

g/d

0.4

0(0

.11

–1

.51

)(T

-NH

L)

Table

1.

Ch

ara

cte

rist

ics

of

the

incl

ud

ed

case

–co

ntr

ol

an

dco

ho

rtst

ud

ies

on

fru

its

an

dve

ge

tab

les

inta

ke

sa

nd

no

n-H

od

gk

in’s

lym

ph

om

a(C

on

tin

ue

d)

Study(Location)

Subjects

(number)

Sex

Cases

Exp

osu

reCompariso

ns

OR/R

R(95%CI)

Exp

osu

res

assessment

NHL

assessment

Adjustment

1.0

1(0

.77

–1

.32

)(B

-NH

L)

Iso

22

a(J

ap

an

)P

op

ula

tio

nb

ase

d(1

02

62

3)

M/F

14

7(N

HL)

Cit

rus

fru

its

�5vs

.<

3se

rv/w

(M)

0.6

6(0

.34

–1

.28

)(M

)3

9-i

tem

FFQ

No

tsp

eci

fie

dA

ge

,a

rea

of

stu

dy.

�5vs

.<

3se

rv/w

(F)

0.7

6(0

.38

–1

.75

)(F

)

Ge

org

e2

1

(Un

ite

dS

tate

s)P

op

ula

tio

nb

ase

d(4

83

33

8)

M/F

19

81

(NH

L)Fr

uit

s1

.4vs

.0

.3cu

pe

qu

iva

len

ts/

10

00

kca

l(M

)

1.1

4(0

.94

–1

.39

)1

24

-ite

mFF

QIC

D-O

Ag

e,

smo

kin

g,

en

erg

yin

tak

e,

BM

I,a

lco

ho

l,p

hys

ica

la

ctiv

ity,

ed

uca

tio

n,

race

,m

ari

tal

sta

tus,

fam

ily

his

tory

of

NH

L,m

en

op

au

sal

ho

rmo

ne

the

rap

y,a

nd

fru

it(o

rve

ge

tab

le)

inta

ke

.

2.4

vs.

0.4

cup

eq

uiv

ale

nts

/1

00

0k

cal

(F)

1.1

5(0

.87

–1

.53

)

Ve

ge

tab

les

1.3

vs.

0.8

cup

eq

uiv

ale

nts

/1

00

0k

cal

(M)

1.0

4(0

.86

–1

.27

)

1.4

vs.

0.9

cup

eq

uiv

ale

nts

/1

00

0k

cal

(F)

0.8

0(0

.61

–1

.05

)

Tho

mp

son

18

(Un

ite

dS

tate

s)P

op

ula

tio

nb

ase

d(3

51

59

)F

41

5(N

HL)

Fru

its

>9

6vs

.<4

5se

rv/m

o0

.78

(0.5

8–

1.0

4)

12

7-i

tem

FFQ

ICD

-O-2

,IC

D-O

-3A

ge

,to

tal

en

erg

yin

tak

e.

Ve

ge

tab

les

>1

12vs

.<5

3se

rv/m

o0

.84

(0.6

3–

1.1

2)

Fru

ita

nd

veg

eta

ble

s>

20

4vs

.<1

07

serv

/mo

0.6

9(0

.51

–0

.94

)

Tsa

i19

b(U

nit

ed

Sta

tes)

Po

pu

lati

on

ba

sed

(52

59

82

)M

/F1

12

9(C

LL/S

LL)

Fru

its

31

4.9

vs.

45

.1g

/10

00

Kca

l0

.93

(0.7

8–

1.1

2)

FFQ

No

tsp

eci

fie

dA

ge

,se

x,B

MI.

Ve

ge

tab

les

26

8.9

vs.

80

.5g

/10

00

Kca

l0

.93

(0.7

8–

1.1

1)

Ch

an

g1

5(U

nit

ed

Sta

tes)

Co

mm

un

ity

ba

sed

(11

02

15

)F

53

6(N

HL)

Fru

its

�2

.0vs

.�

0.6

serv

/d1

.05

(0.8

4–

1.3

2)

10

3-i

tem

FFQ

ICD

-O-3

Tota

le

ne

rgy

inta

ke

.

Ve

ge

tab

les

�2

.0vs

.�

0.6

serv

/d0

.82

(0.6

5–

1.0

3)

Fru

its

an

dve

ge

tab

les

�3

.5vs

.�

1.0

serv

/d0

.91

(0.7

1–

1.1

7)

BM

I,b

od

ym

ass

ind

ex;

FFQ

,fo

od

-fre

qu

en

cyq

ue

stio

nn

air

e;

ICD

,In

tern

ati

on

al

Cla

ssifi

cati

on

of

Dis

ea

ses;

ICD

-O,

Inte

rna

tio

na

lC

lass

ifica

tio

no

fD

ise

ase

sfo

rO

nco

log

y;W

HO

,W

orl

dH

ea

lth

Org

an

iza

tio

n;

NH

L,n

on

-Ho

dg

kin

’sly

mp

ho

ma

;D

LBL,

dif

fuse

larg

eB

-ce

llly

mp

ho

ma

;FL

,fo

llic

ula

rly

mp

ho

ma

;S

LL,

sma

llly

mp

ho

cyti

cly

mp

ho

ma

;C

LL,

B-c

ell

chro

nic

lym

ph

ocy

tic

leu

ke

mia

.se

rv,

serv

ing

s;d

,d

ay;

mo

,m

on

th;

wk

,w

ee

k.;

y,ye

ars

;O

R,

od

ds

rati

os;

RR

,re

lati

veri

sk.

aTh

est

ud

yin

clu

de

din

the

an

aly

ses

of

fru

itsu

bca

teg

ori

es(

citr

us)

,b

ut

exc

lud

ed

fro

ma

ny

oth

er

an

aly

ses.

bTh

est

ud

yin

clu

de

din

the

an

aly

ses

of

NH

Lh

isto

log

icsu

bty

pe

s,b

ut

exc

lud

ed

fro

ma

ny

oth

er

an

aly

ses.

(RR ¼ 0.70; 95% CI, 0.53–0.92), but not with SLL/CLL (RR¼ 1.01; 95% CI, 0.80–1.26). The test of interaction was bor-derline significant (p ¼ 0.06) (Table 3).

Nine 6,7,10,12,15,18,20,22,23 studies (five case-control studies,four cohort studies) provided results on some individual fruitsand vegetables. In the high versus low analysis, the summaryRR of total NHL of citrus fruits was 0.66 (95% CI, 0.45–0.97),with high heterogeneity(p < 0.000; I2 ¼ 91.5%; N ¼96,7,10,14,16,18,20,22,23). By study design, significant heterogeneitywas observed in case-control studies (RR ¼ 0.52, 95%CI, 0.23–1.18; p < 0.000; I2 ¼ 95.6%; N ¼ 56,7,10,14,23), but not in cohortstudies (RR ¼ 0.86, 95%CI, 0.73–1.01; p ¼ 0.82; I2 ¼ 0.0%; N¼ 416,18,20,22). The corresponding RRs for intakes of cruciferousvegetables and green leaf vegetables were 0.83 (95%CI, 0.74–0.93; p ¼ 0.43; I2 ¼ 0.0%; N ¼ 76,7,10,12,15,18,20) and 0.78(95%CI,0.62–0.99; p ¼ 0.11; I2 ¼ 46.4%; N ¼ 56,7,10,18,20).

For 1 study that reported result in cup equivalents, eitherusing 1.5 servings as a cup equivalent size, or excluding thisstudy from dose-response analysis did not substantially changethe summary dose-repose risk estimates (data not shown).

Publication bias

Egger et al. regression asymmetry test suggested someevidence of publication bias with regard to fruits intake

(p ¼ 0.02), but little evidence of such bias with regard tointake of vegetables (p ¼ 0.24) or fruits and vegetables com-bined (p ¼ 0.28), in relation to total NHL risk.

DiscussionTo our knowledge, this is the first meta-analysis aiming atsolving the inconsistency of the existing literatures concern-ing the associations of fruits and vegetables with NHL risk.The large number of subjects and NHL cases includedenhanced the statistical power of the study. The sufficientdata provided in the primary studies enabled us to addressthe issue of etiologic heterogeneity by investigating theassociation by histological subtypes. The results of this meta-analysis show that greater intakes of vegetables, and fruitsand vegetables combined were significantly inversely associ-ated with risk of total NHL, and there were dose-responserelationships. Regarding NHL subtypes, a high intake of vege-tables was significantly inversely associated with DLBCL and

Figure 1. Intake of fruits and vegetables combined and risk of

NHL. a, high versus low analysis; b, dose-response analysis. [Color

figure can be viewed in the online issue, which is available at

wileyonlinelibrary.com.]

Figure 2. Intake of fruits and risk of NHL. a, high versus low

analysis; b, dose-response analysis. [Color figure can be viewed in

the online issue, which is available at wileyonlinelibrary.com.]

Epidemiology



FL but not with SLL/CLL, compared with low intake. Intakeof fruit only was generally not associated with total NHL, orany histological subtypes.

Several mechanisms of action whereby fruits and vegeta-bles may protect against NHL have been proposed, the mostcommonly mentioned of which is the favorable impacts ofsome nutrients involved in antioxidants on the developmentof NHL. Fruits and vegetables are major dietary sources ofantioxidants which may have anticarcinogenic effects. Epide-miologic evidence suggested that SNPs in genes related to theoxidative stress pathway may be associated with increasedrisk of NHL.41,42 Antioxidants appear to inhibit reactive oxy-gen species (ROS) which are responsible for oxidative DNAdamage and mutations,43,44 and regulate cell survival and ap-optosis pathways,45 and enhance immune responses.46,47 Fur-thermore, genetic polymorphisms in oxidative stress pathwaygenes have recently been found to modify the associationbetween vegetables and fruits intake and risk of NHL, espe-

cially for the histological subtypes DLBCL and FL.30 Veryrecently, a case–control study nested in a multiethnic cohortalso suggested that higher total serum carotenoids, a markerfor a diet rich in fruits and vegetables, was associated with a34% (OR ¼ 0.66; 95%CI, 0.46–0.96) decreased risk of NHLwhen comparing the highest with the lowest tertiles.48

In the current study, the inverse association of NHL withvegetables intake was consistently more pronounced thanthat with fruits intake. The differences may suggest that somenutrients that are more abundant in vegetables than in fruitsmay account for a majority of the observed beneficial effectsof vegetables intake against NHL. For instance, cruciferousvegetables are rich source of glucosinolates, which are con-verted in vivo to isothiocyanates. Isothiocyanates have beensuggested to protect against cancer by inducing carcinogen-detoxifying enzymes, and by affecting several processesrelated to chemical carcinogenesis, such as the induction ofcarcinogen-detoxifying enzymes and DNA binding of carci-nogens.49–51 Nonetheless, a possibility that the number ofNHL cases was still too limited to detect a weak associationbetween fruits and NHL cannot be excluded.

A null association of vegetables consumption with NHLemerged in a subset of men-only analysis. It is possible thatthe disparate findings between gender were due to the differ-ences in lifestyles and diet habits between men and women,because men compared with women tend to be more likely tohave unhealthy lifestyles and diet habits, such as smoking. It isalso possible that hormonal, genetic and metabolic factors mayaffect the biology of how vegetables intake affect NHL risk.

This meta-analysis has several limitations. First, becausethe quantitative analyses were based on observational studies,confounding factors that are inherent in the primary studiescould be of concern. Although all included studies have pro-vided adjusted risk estimates, some of them appeared to failto fully control for confounders. For instance, we observedsome evidence of adverse effect of fruits intake on NHL inthe studies that adjusted for alcohol intake, but beneficialeffect among those that did not; the favourable role of vege-tables was also more evident in studies not adjusting for alco-hol (Table 2). Given that alcohol drinking has been demon-strated to have protective effect against NHL,52 we cannotentirely rule out the possibility that intake of alcohol waspartly responsible for the observed findings. Therefore, addi-tional large prospective studies with better control for poten-tial dietary confounders are warranted. Second, more thanhalf of the included studies were of a case-control design.This may introduce some biases including recall and selectionbiases, because lifestyles and diet habits in retrospective case-control studies are determined after the diagnosis of cancer.Although the pooled results were not significantly modifiedby study designs, we have acknowledged that the inverseassociation of vegetables with NHL was weaker in cohortstudies than that in case–control studies. Third, the charac-teristics of individual studies were not always comparable.Because 27,16 studies reported results in weights, we needed

Figure 3. Intake of vegetables and risk of NHL. a, high versus low

analysis; b, dose-response analysis. [Color figure can be viewed in

the online issue, which is available at wileyonlinelibrary.com.]

Epidemiology

Chen et al. 197


Table 2. Summary estimates of the relative risk (RR) for the associations of non-Hodgkin’s lymphoma with fruits and vegetablesintakes, high versus low analysis

Fruits Vegetables

N RR (95%CI) p-het I2 N RR (95%CI) p-het I2

All studies 13 0.97 (0.87–1.08) 0.07 39.7% 13 0.81 (0.71–0.92) 0.02 51.6%

Designs

Cohort 5 1.01 (0.88–1.16) 0.18 36.2% 5 0.90 (0.81–1.00) 0.57 0.0%

Case-control 8 0.92 (0.77–1.10) 0.07 46.3% 8 0.75 (0.60–0.94) 0.01 61.1%

p-interaction 0.58 0.28

Geographic areas

Europe 4 0.88 (0.70–1.10) 0.08 54.8% 3 0.66 (0.50–0.87) 0.48 0.0%

North America 8 1.00 (0.88–1.14) 0.13 37.4% 9 0.80 (0.70–0.91) 0.09 41.9%


Subject characteristics

Population based 7 1.01 (0.88–1.17) 0.12 41.0% 8 0.87 (0.78–0.96) 0.59 0.0%

Hospital based 4 0.87 (0.68–1.11) 0.14 45.9% 3 0.75 (0.36–1.55) 0.002 83.8%

Community based 2 0.99 (0.78–1.24) 0.29 10.7% 2 0.79 (0.64–0.98) 0.45 0.0%


Sex

Men 4 1.05 (0.77–1.42) 0.20 36.0% 5 1.01 (0.86–1.18) 0.44 0.0%

Women 7 0.90 (0.74–1.08) 0.18 32.0% 8 0.80 (0.67–0.95) 0.19 30.2%

Men and women 7 0.95 (0.80–1.12) 0.06 51.2% 6 0.67 (0.53–0.84) 0.14 40.2%


No. of FFQ items

<100 3 0.91 (0.64–1.30) 0.01 80.9% 3 0.79 (0.59–1.07) 0.14 49.0%

>100 6 0.96 (0.83–1.10) 0.16 36.9% 6 0.77 (0.64–0.92) 0.04 58.0%


Range of intakes

<2 servings/d 5 1.01 (0.83–1.22) 0.11 47.2.% 6 0.84 (0.66–1.08) 0.06 55.7%

>2 servings/d 7 0.92 (0.77–1.10) 0.07 48.9% 7 0.79 (0.67–0.93) 0.03 55.6%


Adjustment

Age

Yes 11 0.93 (0.81–1.07) 0.04 48.6% 11 0.78 (0.66–0.92) 0.01 57.4%

No 2 1.05 (0.89–1.24) 0.96 0.0% 2 0.88 (0.74–1.05) 0.35 0.0%


BMI, Height

Yes 4 1.00 (0.81–1.23) 0.28 21.7% 4 0.80 (0.63–1.02) 0.18 38.4%

No 9 0.97 (0.87–1.08) 0.05 47.9% 9 0.81 (0.68–0.96) 0.01 58.3%


Smoking

Yes 6 1.04 (0.94–1.16) 0.60 0.0% 5 0.90 (0.71–1.16) 0.05 57.0%

No 7 0.89 (0.74–1.08) 0.02 60.4% 8 0.76 (0.66–0.88) 0.15 34.5%


Alcohola

Yes 6 1.10 (1.00–1.21) 0.42 0.0% 5 0.90 (0.79–1.03) 0.30 17.7%

No 8 0.85 (0.74–0.98) 0.36 8.6% 9 0.76 (0.63–0.91) 0.26 20.2%

Epidemiology



to convert the intakes to frequency. This may have intro-duced some measurement error. Finally, we have also noticedthat there was significant publication bias in the results forfruits intake, suggesting that the overall risk estimates ofNHL with respect to fruits intake was probably an overesti-mation, because small studies with null results tend not to bepublished.

In summary, our study indicates that intakes of vegetablesand fruits and vegetables combined statistically significantlydecrease the risk of NHL, in particular DLBCL and FL. Con-sumption of fruits only was generally not associated with risk oftotal NHL, or any common histological subtypes. Further pro-spective studies of fruits and vegetables intakes and NHL riskwith adjustment for potential confounding factors are needed.

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Table 2. Summary estimates of the relative risk (RR) for the associations of non-Hodgkin’s lymphoma with fruits and vegetablesintakes, high versus low analysis (Continued)

Fruits Vegetables

N RR (95%CI) p-het I2 N RR (95%CI) p-het I2


Energy intake

Yes 10 0.96 (0.84–1.10) 0.03 50.7% 10 0.78 (0.68–0.90) 0.04 49.6%

No 3 0.94 (0.79–1.12) 0.63 0.0% 3 1.00 (0.64–1.57) 0.04 68.9%


Education

Yes 5 0.96 (0.80–1.17) 0.05 57.2% 4 0.80 (0.61–1.04) 0.04 63.2%

No 8 0.96 (0.83–1.10) 0.17 32.1% 9 0.80 (0.68–0.94) 0.06 46.4%


Geographic region

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No 7 1.03 (0.91–1.16) 0.13 39.0% 8 0.83 (0.73–0.94) 0.09 45.2%


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Table 3. Summary estimates of the relative risk (RR) for the associations of NHL subtypes with fruits and vegetables intakes,high versus low analysis

Fruits Vegetables

N RR (95%CI) p-het I2 N RR (95%CI) P-het I2

DLBCL 8 0.94 (0.79–1.13) 0.40 4.2% 7 0.70 (0.54–0.91) 0.08 47.7%

FL 8 0.96 (0.72–1.28) 0.04 53.5% 7 0.70 (0.53–0.92) 0.12 40.5%

SLL/CLL 10 0.97 (0.84–1.11) 0.66 0.0% 10 1.01 (0.80–1.26) 0.13 37.6%


NHL, Non-hodgkin’s lymphoma; DLBCL, diffuse large B-cell lymphoma; FL, follicular lymphoma; SLL, small lymphocytic lymphoma; CLL, B-cellchronic lymphocytic leukemia.

Epidemiology

Chen et al. 199


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