Adherence to the World Cancer Research Fund/American Institute forCancer Research guidelines and risk of death in Europe: results fromthe European Prospective Investigation into Nutrition and Cancercohort study1–5

Anne-Claire Vergnaud, Dora Romaguera, Petra H Peeters, Carla H van Gils, Doris SM Chan, Isabelle Romieu,Heinz Freisling, Pietro Ferrari, Francoise Clavel-Chapelon, Guy Fagherazzi, Laureen Dartois, Kuanrong Li, Kaja Tikk,Manuela M Bergmann, Heiner Boeing, Anne Tjønneland, Anja Olsen, Kim Overvad, Christina C Dahm, Maria Luisa Redondo,Antonio Agudo, Marıa-Jose Sanchez, Pilar Amiano, Marıa-Dolores Chirlaque, Eva Ardanaz, Kay-Tee Khaw,Nick J Wareham, Francesca Crowe, Antonia Trichopoulou, Philippos Orfanos, Dimitrios Trichopoulos, Giovanna Masala,Sabina Sieri, Rosario Tumino, Paolo Vineis, Salvatore Panico, H Bas Bueno-de-Mesquita, Martine M Ros, Anne May,Elisabet Wirfalt, Emily Sonestedt, Ingegerd Johansson, Goran Hallmans, Eiliv Lund, Elisabete Weiderpass, Christine L Parr,Elio Riboli, and Teresa Norat

ABSTRACTBackground: In 2007, the World Cancer Research Fund (WCRF)and the American Institute for Cancer Research (AICR) issuedrecommendations on diet, physical activity, and weight manage-ment for cancer prevention on the basis of the most comprehensivecollection of available evidence.Objective: We investigated whether concordance with WCRF/AICR recommendations is related to risk of death.Design: The current study included 378,864 participants from 9 Euro-pean countries enrolled in the European Prospective Investigation intoCancer and Nutrition study. At recruitment (1992–1998), dietary, an-thropometric, and lifestyle information was collected. A WCRF/AICRscore, which incorporated 6 of the WCRF/AICR recommendations formen [regarding body fatness, physical activity, foods and drinks thatpromote weight gain, plant foods, animal foods, and alcoholic drinks(score range: 0–6)] and 7 WCRF/AICR recommendations for women[plus breastfeeding (score range: 0–7)], was constructed. Higher scoresindicated greater concordance with WCRF/AICR recommendations.Associations between the WCRF/AICR score and risks of total andcause-specific death were estimated by using Cox regression analysis.Results: After a median follow-up time of 12.8 y, 23,828 deathswere identified. Participants within the highest category of theWCRF/AICR score (5–6 points in men; 6–7 points in women)had a 34% lower hazard of death (95% CI: 0.59, 0.75) comparedwith participants within the lowest category of the WCRF/AICRscore (0–2 points in men; 0–3 points in women). Significant inverseassociations were observed in all countries. The WCRF/AICR scorewas also significantly associated with a lower hazard of dying fromcancer, circulatory disease, and respiratory disease.Conclusion: Results of this study suggest that following WCRF/AICRrecommendations could significantly increase longevity. Am JClin Nutr 2013;97:1107–20.

INTRODUCTION

In 2004, WHO estimated that diet and lifestyle-related risk factorssuch as high blood pressure, high blood glucose, physical inactivity,

overweight and obesity, high cholesterol, and low fruit and vegetableintake accounted for 18% and 25% of the world death burden in low-middle–income countries and high-income countries, respectively(1). Therefore, improving poor quality diet and lifestyle is one of themajor public health goals, and national and international health or-ganizations published guidelines accordingly.

Scores derived from dietary recommendations, such as theAlternative Healthy Eating Index, Diet Quality Index, andRecommended Food Score (RFS)6 have been previously

1From the Department of Epidemiology and Biostatistics, School of Pub-lic Health, Imperial College London, London, United Kingdom (A-CV, DR,DSMC, PV, ER, and TN); the Julius Center for Health Sciences and PrimaryCare, University Medical Center Utrecht, Utrecht, Netherlands (PHP, CHvG,and AM); the International Agency for Research on Cancer, Lyon, France(IR, HF, and PF); the Institut National de la Sante et de la RechercheMedicale, Centre for Research in Epidemiology and Population, Health,U1018, Institut Gustave Roussy, Villejuif, France (FC-C, GF, and LD); theParis South University, Unite Mixte de Recherche 1018, Villejuif, France(FC-C, GF, and LD); the Division of Clinical Epidemiology, German CancerResearch Center, Heidelberg, Germany (KL and KT); the Deutsches Institutfur Ernahrungsforschung Potsdam-Rehbrucke German Institute of HumanNutrition, Potsdam-Rehbrucke, Germany (MMB and HB); the Danish Can-cer Society, Institute of Cancer Epidemiology, Copenhagen, Denmark (ATjønneland and AO); the Department of Epidemiology, School of PublicHealth, Aarhus University, Aarhus, Denmark (KM and CCD); the Depart-ment of Cardiology, Centre for Cardiovascular Research, Aalborg Hospital,Aarhus University Hospital, Aalborg, Denmark (KM and CCD); the PublicHealth Directorate, Asturias, Spain (MLR); the Unit of Nutrition, Environ-ment and Cancer, Catalan Institute of Oncology, Bellvitge Biomedical Re-search Institute, Barcelona, Spain (AA); the Andalusian School of PublicHealth, Spain (M-JS); the Consorcio de Investigacion Biomedica de Epide-miologıa y Salud Publica (CIBERESP), Spain (M-JS, M-DC, and EA); thePublic Health Division of Gipuzkoa, BIODonostia Research Institute, De-partment of Health of the Regional Government of the Basque Country, SanSebastian, Spain (PA); the Department of Epidemiology, Murcia RegionalHealth Authority, Spain (M-DC); the Navarre Public Health Institute, Pam-plona, Spain (EA); the Clinical Gerontology Unit, University of Cambridge,Cambridge, United Kingdom (K-TK and NJM); the Cancer EpidemiologyUnit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford,United Kingdom (FC); the WHO Collaborating Center for Food and Nutrition

Am J Clin Nutr 2013;97:1107–20. Printed in USA. � 2013 American Society for Nutrition 1107

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49569.DCSupplemental.html http://ajcn.nutrition.org/content/suppl/2013/04/10/ajcn.112.0Supplemental Material can be found at:

associated with 20–45% lower mortality risk (2–6). However,results differed according to the cause of death. After 4 y offollow-up, a higher Diet Quality Index score, which was in-dicative of a poorer quality diet, was associated with higherrisk of circulatory disease mortality in American women butnot with risk of cancer mortality in either men or women (6).Similarly, subjects from the United Kingdom in the top com-pared with the bottom one-third of the Alternative HealthyEating Index score showed 40% lower mortality from cardio-vascular disease (CVD), but no association was observed withmortality from cancer (2). In Sweden, the association betweenRFS and CVD death was weaker than the association betweenRFS and cancer death in women (5) and was not significant inmen (3). Similar results were observed in American women inwhom a higher RFS was associated with a lower mortalityfrom cancer but not from coronary heart disease or stroke after9.5 y of follow-up (4).

The weaker predictive value for mortality from cancer ob-served in most of these studies could have been due to the fact thatthese indexes were based on recommendations for general healthand not for cancer prevention specifically. However, the only 2previous studies that specifically tested indexes on the basis ofcancer-prevention recommendations were performed in theUnited States and showed contradictory results as well (7, 8).Both studies included recommendations on dietary behaviors aswell as weight and physical activity. In the IowaWomen’s Healthstudy, a higher adherence to the American Institute for CancerResearch (AICR) guidelines was as expected associated withlower cancer mortality but not with CVD mortality (7). How-ever, in the Cancer Prevention study II Nutrition cohort, ad-herence to the American Cancer Society Cancer Preventionguidelines was inversely associated with both outcomes and theassociation was stronger for CVD mortality compared withcancer mortality (8). In addition, previous studies focused ondeath from cancer and circulatory disease. However, diet andlifestyle factors have previously been associated with variousother chronic diseases. It is therefore also relevant to know howadhering to those major public health recommendations couldaffect other leading causes of death.

In 2007, the World Cancer Research Fund (WCRF)/AICRissued 8 general and 2 special recommendations on diet, physicalactivity, and weight management on the basis of the mostcomprehensive collection of available evidence. The aim of therecommendations was to prevent cancer by taking into accountpreviously published recommendations designed to promotenutritional adequacy and prevent cardiovascular and otherchronic diseases (9). To our knowledge, WCRF/AICR guidelineshave been previously evaluated for cancer prevention (10) but notfor mortality. In the current study, we evaluate whether followingthe 2007 WCRF/AICR recommendations was related to totalmortality and cause-specific mortality in men and women from10 European countries enrolled in the large European ProspectiveInvestigation into Nutrition and Cancer (EPIC) cohort study.

SUBJECTS AND METHODS

The EPIC is a multi-center, prospective cohort study in-vestigating the role of metabolic, dietary, lifestyle, and envi-ronmental factors in the development of cancer and other chronicdiseases. Briefly, between 1992 and 2000, 521,330 men andwomen aged 25–70 y were recruited in 23 centers from 10European countries (Denmark, France, Germany, Greece, Italy,Netherlands, Norway, Spain, Sweden, and the United Kingdom).

Actual study populations were samples of convenience withparticipant eligibility within each center that was based essen-tially on geographic or administrative boundaries. Individualswere selected from the general population in most centers exceptin the French cohort, which was based on state-school employees,and the Utrecht (Netherlands) and Florence (Italy) cohorts, whichwere based on women who underwent breast cancer screening.Furthermore, a large proportion of participants from the centersof Spain and Italy were recruited among blood donors, membersof several health insurance programs, employees of several en-terprises, or civil servants. Most of the Oxford cohort consisted ofhealth-conscious subjects from England, Wales, Scotland, andNorthern Ireland, many of whom were vegetarians. Approval forthis study was obtained from the ethical review boards of the

Policies, Department of Hygiene, Epidemiology and Medical Statistics, Uni-versity of Athens Medical School, Athens, Greece (ATrichopoulou and PO);the Hellenic Health Foundation, Athens, Greece (A Trichopoulou, PO, andDT); the Department of Epidemiology, Harvard School of Public Health,Boston, MA (DT); the Bureau of Epidemiologic Research, Academy ofAthens, Athens, Greece (DT); the Molecular and Nutritional EpidemiologyUnit, Cancer Research and Prevention Institute, Florence, Italy (GM); theEpidemiology and Prevention Unit, Department of Preventive and PredictiveMedicine, Foundation of the Carlo Besta Neurological Institute, NationalCancer Institute, Milan, Italy (SS); the Cancer Registry and HistopathologyUnit, “Civile MP Arezzo” Hospital, Azienda Sanitaria Provinciale Ragusa,Ragusa, Italy (RT); the Human Genetics Foundation, Turin, Italy (PV); theDepartment of Clinical and Experimental Medicine, Federico II University,Naples, Italy (SP); the National Institute for Public Health and the Environ-ment, Bilthoven, Netherlands (HBB-d-M and MMR); the Department ofGastroenterology and Hepatology, University Medical Centre, Utrecht,Netherlands (HBB-d-M); the Department of Clinical Sciences in Malmo,Lund University, Malmo, Sweden (E Wirfalt); the Departments of Odontol-ogy (IJ) and Public Health and Clinical Medicine, Nutritional Research(GH), Umea University, Umea, Sweden); the Institute of Community Med-icine, University of Tromsø, Breivika, Norway (EL and E Weiderpass); andthe Institute of Basic Medical Sciences, Department of Biostatistics, Univer-sity of Oslo, Oslo, Norway (CLP).

2Funders had no role in the study design, data collection and analysis,decision to publish, or preparation of the manuscript.

3Supported by the World Cancer Research Fund, International RegularGrant Programme (grant 2009/44). In addition, European Prospective Inves-tigation into Nutrition and Cancer investigators acknowledge funding fromthe following agencies: the Institut National de la Sante et de la RechercheMedicale, Institut Gustave Roussy, the French League against Cancer, theMutuelle Generale de l’Education Nationale, and the Institut Gustave Roussy(France); the Health Research Fund of the Spanish Ministry of Health; Re-gional Governments of Andalucıa, Asturias, Basque Country, Murcia (6236)and Navarra; and Instituto de Salud Carlos III RETIC (RD06/0020) (Spain);the Italian Association for Research on Cancer, Milan (Italy); and the Hel-lenic Health Foundation and the JF Costopoulos Foundation (Greece).

4Address reprint requests to T Norat, Department of Epidemiology andBiostatistics, School of Public Health, Imperial College London, StMary’s Campus, Norfolk Place, W2 1PG, London, United Kingdom.E-mail: t.norat@imperial.ac.uk.

5Address correspondence to A-Claire Vergnaud, Department of Epi-demiology and Biostatistics, School of Public Health, Imperial CollegeLondon, St Mary’s Campus, Norfolk Place, W2 1PG, London, UnitedKingdom. E-mail: a.vergnaud@imperial.ac.uk.

6Abbreviations used: AICR, American Institute for Cancer Research;CVD, cardiovascular disease; EPIC, European Prospective Investigationinto Nutrition and Cancer; RAP, rate advancement period; RFS, Recom-mended Food Score; WCRF, World Cancer Research Fund.Received August 20, 2012. Accepted for publication February 8, 2013.First published online April 3, 2013; doi: 10.3945/ajcn.112.049569

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International Agency for Research on Cancer and from all localinstitutions where subjects had been recruited for the EPIC study.Written informed consent was obtained from all participantsbefore joining the EPIC study. Details of the study design used inthe EPIC study have been described elsewhere (11, 12).

For the current study, we excluded participants with in-complete follow-up information (n = 2922), participants witha missing date of death (n = 538), participants who did notcomplete the lifestyle (n = 1286) or dietary (n = 5315) ques-tionnaires, and participants within the lowest and highest 1% ofthe cohort distribution of the ratio of reported total energy in-take:energy requirement (13) (n = 10,119). We also excludedpregnant women (n = 560) and participants with missing data forthe following variables: weight or height (n = 4522), physicalactivity [n = 67,797, including all participants from Umea(Sweden) and Norway where this information was not col-lected in sufficient detail], and women with no information onbreastfeeding or duration of breastfeeding [n = 22,176, includingall female participants from Bilthoven (Netherlands) where thisinformation was not collected]. Finally, to avoid confounding bypreexisting chronic diseases, we excluded 27,231 participantswho reported a history of cancer, heart disease, or stroke atbaseline. Thus, the final study included 378,864 participants.

Data collection and dietary questionnaires

At baseline, participants filled out extensive medical, dietary,and lifestyle questionnaires, including questions on alcohol use,smoking status, physical activity, education, menopausal status,breastfeeding, and previous illnesses. For the current study,education was coded as follows: none, primary school, technicalschool, secondary school, and university degree; smoking statusand smoking intensity were coded as follows: never; former, quitsmoking .20 y ago; former, quit smoking 11–20 y ago; former,quit smoking #10 y ago; smoker, 1–15 cigarettes/d; smoker,16–25 cigarettes/d; smoker, .25 cigarettes/d; and smoker, pipeor cigar; and menopausal status was coded as follows: pre-menopausal, perimenopausal, and postmenopausal. Body weightand height were measured in all centers except France and inthe health-conscious group of the Oxford center where anthro-pometric measures were self-reported (14). Usual food intakeswere measured by using country-specific validated dietaryquestionnaires (15), and individual nutrient intakes were derivedfrom the standardized EPIC nutrient database (16). To correctfor any systematic underestimation or overestimation of dietaryintake between study centers, a dietary calibration study wasconducted in a random sample of 36,308 men and women (7.4%of the sample) who completed a standardized computerized 24-hdietary recall (EPIC-Soft; IARC). Dietary exposures acrosscenters were scaled by using an additive calibration (15).Briefly, differences between sex- and center- specific means ofvalues from the food-frequency questionnaire, and means of24-h recall values were calculated and added to questionnairevalues.

WCRF/AICR score construction

A WCRF/AICR score, which incorporated 6 WCRF/AICRrecommendations for men (regarding body fatness, physicalactivity, foods and drinks that promote weight gain, plant foods,

animal foods, and alcoholic drinks) and 7 WCRF/AICR rec-ommendations for women (plus breastfeeding) was constructed.Detailed information on the operationalization of the score hasbeen previously published (10) and is shown in Table 1.

Briefly, for each component we assigned 1 point when therecommendation was met, 0.5 points when it was half met, and0 points otherwise. When available, quantitative criteria providedin the recommendations were used as cutoffs, and intermediatecutoffs defined by the authors were used otherwise. For rec-ommendations including several subrecommendations (foodsand drinks that promote weight gain or plant foods), the finalscore was the average of each subrecommendation score. Thefollowing 3 recommendations were not implemented: 1) rec-ommendation 7 on preservation, processing, and preparation offoods because of insufficient data available, 2) recommendation8 on dietary supplements, which could not be operationalized interms of cancer prevention without additional assumptions aboutthe type or dose of supplementation, and 3) the special recom-mendation S2 related to cancer survivors, which was outside thescope of cancer prevention. Because WCRF/AICR recommen-dations were not ranked according to priority, all major rec-ommendations were summed to contribute equally to the totalWCRF/AICR score. Therefore, the total WCRF/AICR scoreranged from 0 to 6 for men and from 0 to 7 for women, withgreater adherence to WCRF/AICR recommendations indicatedby higher scores.

The score was further categorized into 5 categories accord-ing to predefined cutoffs (ie, 0–2, 2.25–2.75, 3–3.75, 4–4.75, and5–6 points in men; 0–3, 3.25–3.75, 4–4.75, 5–5.75, and 6–7points in women). With this categorization, the score differencebetween the upper limit of the first category and the lower limitof the fifth category was 3 points.

Case ascertainment

Vital status and the cause and date of death were ascertained bymeans of record linkages with cancer registries, boards of health,and death indexes (in the case of Denmark, Italy, Netherlands,Spain, Sweden, and the United Kingdom) or by active follow-up(in the case of Germany, Greece, and France). Active follow-upincluded inquiries by mail or telephone to participants, municipalregistries, regional health departments, physicians, and hospitals.The last year of record linkage varied between centers and rangedbetween 2006 and 2010. In the total EPIC cohort (n = 521,330),1.5% of participants were lost to follow-up (because of with-drawal, emigration, or unknown reason). Follow-up began at thedate of enrollment and ended at either the date of death or lastcomplete follow-up. Because of a time interval between therecording of the vital status and recording of the cause of deathin some centers, the last complete follow-up for cause-specificdeaths was potentially before the last complete follow-up for all-cause deaths. For the current study, the follow-up for cause-specific deaths was considered complete when $80% of causesof deaths that occurred in the past 6 mo were recorded. Onaverage, 96% of causes of deaths that occurred in the past 6 mowere known at the last complete follow-up date in the currentstudy.

The underlying cause of death was coded according to the firstlevel of the International Classification of Diseases, 10th Re-vision hierarchy. Causes of death were analyzed separately if

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TABLE1

WCRF/AICRrecommendations

forcancer

preventionandoperationalizationoftheWCRF/AICRscore

intheEPIC

study1

Personalrecommendations

Operationalization

Scoring

Percentage

WCRF/AICR

recommendations

1.Bodyfatness

1a.

Ensure

that

bodyweightthroughchildhoodand

adolescentgrowth

projectstowardthelower

endofthe

norm

alBMIrangeat

age21y

Insufficientdataavailable

NA

Beas

lean

aspossible

without

becomingunderweight

1b.Maintainbodyweightwithin

thenorm

alrangefrom

age

21y

BMI(inkg/m

2)of18.5–24.9

148.4

BMI:25–29.9

0.5

35.8

1c.Avoid

weight

gainandincreasesin

waistcircumference

throughoutadulthood

BMI,18.5

or.30

Insufficientdataavailable

0 NA

15.9

—

2.Physicalactivity

2a.

Bemoderatelyphysicallyactive,equivalentto

brisk

walking,$30min/d

Manual/heavymanual

job,or.2h/wkof

vigorousPA

,or.30min/d

ofcycling/sports2

139.2

Bephysicallyactive

aspartof

youreveryday

life

2b.

Asfitnessim

proves,aim

for$60min

ofmoderateor

$30min

ofvigorousPA

/d

15–30min/d

ofcycling/sports2

0.5

15.5

,15min/d

ofcycling/sports2

045.3

2c.

Lim

itsedentary

habitssuch

aswatchingtelevision

Insufficientdataavailable

NA

—

Insufficientdataavailable

NA

—

3.Foodsanddrinks

that

promote

weight

gain3

,4

Lim

itconsumptionofenergy-dense

foods;avoid

sugarydrinks

3a.

Consumeenergy-dense

foodssparingly

3b.

Avoid

sugarydrinks

3c.

Consumefastfoodssparingly,ifat

all

ED

#125kcal/100g/d

51

23.0

ED

.125–,

175kcal/100g/d

50.5

59.1

ED

.175kcal/100g/d

50

17.9

Sugarydrinksintakeof0g/d

61

21.2

Sugarydrinksintake#250g/d

60.5

61.5

Sugarydrinksintake.250g/d

60

17.3

Insufficientdataavailable

NA

4.Plantfoods3

,44a.

Eat

$5portions/servings($

400g)ofavarietyof

nonstarchyvegetablesandoffruiteveryday

4b.Eatrelatively

unprocessed

cereals(grains)and/orpulses

(legumes)witheverymeal

4c.

Lim

itrefined

starchyfoods

4d.Peoplewhoconsumestarchyrootsortubers

asstaples

shouldalso

ensure

asufficientintakeofnonstarchy

vegetables,fruit,andpulses

(legumes)

F&V

intake$400g/d

142.7

Eat

mostly

foodsofplantorigin

F&V

intakeof200to

,400g/d

0.5

38.4

F&V

intake,200g/d

Dietary

fiber

intake$25g/d

Dietary

fiber

intakeof12.5

to,25g/d

Dietary

fiber

intake,12.5

g/d

Insufficientdataavailable

Notapplicable

tothispopulation

0 1 0.5 0 NA

NA

18.9

27.3

60.5

12.2

— —

5.Anim

alfoods4

5a.

Peoplewhoeatredmeatto

consume,500g/wk,very

little,ifany,

tobeprocessed

Red

andprocessed

meat,500g/wkof

whichprocessed

meatintake,3g/d

115.0

Lim

itintakeofredmeatand

avoid

processed

meat

Red

andprocessed

meat,500g/wkof

whichprocessed

meatintakeof3to

,50g/d

0.5

35.9

Red

andprocessed

meat$500g/wkor

processed

meatintake$50g/d

049.1

6.Alcoholicdrinks

6a.

Ifalcoholicdrinks

areconsumed,limitconsumption

to

#2drinks/d

formen

and1drink/dforwomen

Ethanolintake#20g/d

(men)7

166.2

Lim

italcoholicdrinks

Ethanolintake#10g/d

(women)7

Ethanolintake.20and#30g/d

(men)7

0.5

16.1

Ethanolintake.10and#20g/d

(women)7

Ethanolintake.30g/d

(men)7

017.8

Ethanolintake.20g/d

(women)7

(Continued)

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TABLE

1(C

ontinued

)

Personal

recommendations

Operationalization

Scoring

Percentage

7.Preservation,processing,preparation

7a.

Avoid

salt-preserved,salted,orsaltyfoods;preserve

foodswithout

usingsalt

Insufficientdataavailable

NA

—

Lim

itconsumptionofsalt.Avoid

moldy

cereals(grains)

orpulses

(legumes)

7b.Lim

itconsumptionofprocessed

foodswithadded

saltto

ensure

anintake,6g(2.4

gNa)/d

Insufficientdataavailable

NA

—

7c.

Donoteatmoldycereals(grains)

orpulses

(legumes)

Insufficientdataavailable

NA

—

8.Dietary

supplem

ents

8a.

Dietary

supplementsarenotrecommended

forcancer

prevention

Notapplicable

tothispopulation

NA

—

Aim

tomeetnutritionalneedsthrough

dietalone

WCRF/AICR

specialrecommendations

S1.Breastfeeding

S1a.

Aim

tobreastfeedinfantsexclusively

upto

6moand

continue

withcomplementary

feedingthereafter

Cum

ulative

breastfeeding$6mo

135.2

Mothersto

breastfeed;children

tobebreastfed

Cum

ulative

breastfeeding.0to

,6mo

0.5

35.0

Nobreastfeeding

029.8

S2.Cancersurvivors

S2a.Allcancersurvivorsto

receivenutritionalcare

from

an

appropriately

trainedprofessional

Notapplicable

tothispopulation

NA

—

Follow

recommendationsfor

cancer

prevention

S2b.

Ifable

todoso,andunless

otherwiseadvised,aim

to

follow

therecommendationsfordiet,healthyweight,and

PA

Notapplicable

tothispopulation

NA

—

1Percentages

show

thedistributionofthepopulationbyeach

componentcategorizationoftheWCRF/AICRscore.AICR,American

Institute

ofCancerResearch;ED,energydensity;EPIC,European

Prospective

Investigationinto

CancerandNutrition;F&V,fruitandvegetable;NA,notavailable;PA

,physicalactivity;WCRF,

WorldCancerResearchFund.

2Variablesselected

tooperationalizetherecommendationonPA

arethose

included

intheCam

bridgePA

index(exceptforvigorousPA

)that

has

beenvalidated

foritsuse

inepidem

iologic

studies.

3Score

forrecommendations

3and4was

theresultofaveragingthescoresofeach

subrecommendation.

4Alldietary

variablesusedfortheconstructionoftheWCRF/AICRscore

werecalibratedusingadditivecalibration(exceptforalcoholandED).

5EDwas

calculatedas

energy

(kcal)from

foods(solidfoodsandsemi-solidorliquid

foodssuch

assoups)divided

bytheweights(g)ofthesefoods.Drinks(includingwater,tea,coffee,juice,softdrinks,

alcoholicdrinks,andmilk)

werenotincluded

inthecalculation.

6Sugarydrinksincluded

both

softdrinks

andF&V

juices.

7A

drinkcorrespondsto

10gethanol.Fortheanalysis

that

usedlifetimealcoholconsumption,thealcoholaveragelifetimeintake(g/d)was

usedwiththesamecodingas

forbaselinealcoholintake.

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$1000 deaths were identified, which led to the following cate-gories: death from cancer (C00–D48; ie, including benignneoplasms), circulatory disease (I00–I99) and respiratory dis-ease (J00–J99). Remaining causes were combined into the cat-egory other. Results for this category are not discussed becausedeath from other causes was a very heterogeneous group and,therefore, difficult to interpret as a whole. See Table S1 under“Supplemental data” in the online issue for details of deathfrequencies in each category.

Statistical analyses

We first examined the distribution of the population’s maincharacteristics according to WCRF/AICR score categories andsex, which showed percentages within groups for categoricalvariables as well as group means6SDs for continuous variables.Associations between the WCRF/AICR score and risk of deathwere analyzed with the use of a Cox regression model, whichwas stratified according to study center, sex, and age at re-cruitment (in 5-y categories) to allow for a slight departure fromthe proportional hazards assumption. Age was used as the pri-mary time variable, with the entry time defined as the subject’sage at recruitment and exit time as he age at death or censoring(whichever came first). The WCRF/AICR score was assessed asa continuous variable (1-point increment) and as a categoricalvariable (by using the 5 predefined categories). Because ofa slightly different coding of the score in men and women,analyses were performed in men and women separately (P-interaction = 0.52). Crude models (model 0: stratified for sex,age, and center) as well as models adjusted for educational level,smoking status, and intensity of smoking (and menopausal statusin women) (model 1) were performed. We also investigated theeffect of additional adjustment for total energy intake (contin-uous) (model 2). Participants with missing data for confoundingvariables were classified as a separate category (n = 13,404 foreducational level and n = 8803 for smoking status). The effect ofa difference in the WCRF/AICR score was also calculated byusing the mortality rate advancement period (RAP) (17) by di-viding the regression coefficient of the WCRF/AICR score bythe regression coefficient of age (y). RAPs can be interpreted asthe average time period by which the death-rate level could, intheory, be postponed through a 1-unit increase in the WCRF/AICR score (in the absence of competing causes of death).

Sensitivity analyses were performed with the exclusion ofparticipants who died in the first 2 y of follow-up, participantswho reported hyperlipidemia, hypertension, or diabetes atbaseline, or participants with BMI (in kg/m2),18. When alcoholconsumption at baseline was used to determine adherence to thealcohol recommendation, alcohol abstainers included formerdrinkers who could have quit drinking because of illness.Therefore, we also evaluated whether the results were modifiedwhen lifetime alcohol consumption (18) was used to determineadherence to the alcohol recommendation. This sensitivityanalyses were performed in a subsample of 341,884 participantsfor whom lifetime alcohol consumption was available.

To evaluate the relative importance of each of the componentsof the WCRF/AICR score on risk of death, we estimated theindividual association for each mutually adjusted component ofthe WCRF/AICR score (in 3 categories of 0, 0.25–0.5, and 0.75–1) as well as by subtracting alternately one component at a time

from the original score (and including this component as a co-variate in the model). To be able to compare risk estimates tothat of the total WCRF/AICR score, these alternative scoreswere assessed as continuous variables per 1-SD increment.

Plausible effect modifications by baseline BMI category (,25,25 to ,30, and $30), age category (#50 and .50 y), educa-tional level, and smoking status (former smokers, currentsmokers, and never smokers) were explored by modeling in-teraction terms between these variables and the WCRF/AICRscore. Potential heterogeneity between countries in the associ-ation between the WCRF/AICR score and risk of death wasassessed by calculating country-specific estimates and usingrandom-effect meta-analyses (I2). Differences according to thecause of death were examined in competing risk models byusing data augmentation (19) with the same level of adjustmentas previously specified. HRs for the comparison of participantswho adhering to each recommendation (0.75–1 point) to thosewho did not (0 points) were presented.

All statistical analyses were performed with SAS 9.2 software(SAS Institute Inc) or Stata 10.0 software (StataCorp LP).

RESULTS

After a median follow-up time of 12.8 y (4,808,572 person-years of follow-up), 23,828 deaths were identified in the EPICcohort (11,430 in men and 12,398 in women). Of 19,849 deathsthat occurred before the follow-up date for cause-specific death(83.3% of deaths), 47.3% of deaths were from cancer, 26.3% ofdeaths were from circulatory disease, and 5.1% of deaths werefrom respiratory disease (see Table S1 under “Supplementaldata” in the online issue).

The distribution and characteristics of the study populationaccording to the 5 predefined categories of the WCRF/AICRscore and sex are shown in Table 2. Participants in the highestcategory of the score (5–6 points in men; 6–7 points in women)were more likely to be younger (especially in men) and havea higher educational level and less likely to be a current smokerand to report hyperlipidemia, hypertension, or diabetes atbaseline. Women within the highest categories of the score weremore likely to be premenopausal.

Participants in the highest category of the score had a 46%lower hazard of death (95% CI: 0.48, 0.61) than that of partic-ipants in the lowest category (0–2 points in men; 0–3 points inwomen) in the crude Cox model (stratified for sex, age at re-cruitment, and center; Table 3). The association was attenuatedafter adjustment for educational level, smoking status, and in-tensity of smoking and menopause status (model 1) but re-mained significant. The association was a bit stronger in womenthan men for score categories [HR (95% CI) in the highestcompared with lowest category of the score: 0.62 (0.52, 0.73)and 0.74 (0.62, 0.88), respectively)] but similar on a continuousscale. Each unit increase of WCRF/AICR score was associatedwith a 13% lower hazard of death (95% CI: 0.86, 0.88). Themortality RAP associated with a 1-unit increase of the WCRF/AICR score was 1.2 y. This result meant that the age-relatedincrease in the death rate could be postponed by 1.2 y for eachadditional WCRF/AICR recommendation that participants fol-low (for example, participants who adhered to 4 recommenda-tions reached the hazard of death of participants who adhered to3 recommendations 1.2 y later).

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TABLE2

Characteristicsofthepopulationaccordingto

WCRF/AICRscore

categories

andsex1

WCRF/AICRscore

categories

inmen

WCRF/AICRscore

categories

inwomen

12

34

51

23

45

WCRF/AICRscore

range

(minim

um–m

axim

um)

0–2

2.25–2.75

3–3.75

4–4.75

5–6

0–3

3.25–3.75

4–4.75

5–5.75

6–7

Deaths/totalsubjects(n)

2365/19,241

3328/31,111

3942/45,813

1560/21,243

235/4035

3103/51,337

3385/67,072

4166/92,707

1543/40,471

201/5834

Follow

-up(y)2

12.2

12.3

12.4

12.5

12.7

13.2

13.1

13

12.9

12.9

Age(y)

53.6

68.1

53.4

68.9

52.7

69.8

51.2

611.0

47.9

612.4

51.7

69.2

51.7

69.6

51.7

610.0

516

10.4

50.9

610.2

Totalenergy(kcal)3

25926

641

25546

656

25276

660

24626

644

23106

569

18966

553

18356

540

18056

530

17976

511

18016

499

Educational

level(%

)

None

4.8

4.7

4.8

4.3

3.2

4.5

6.2

6.6

4.7

3.3

Primaryschool

completed

32.6

32.8

31.2

26.7

15.2

28.0

27.4

25.7

22.0

17.1

Technical/professional

school

25.7

25.1

24.7

23.2

20.9

20.7

19.8

20.2

21.7

22.5

Secondaryschool

11.1

11.0

11.8

13.2

15.8

23.5

23.3

22.8

23.0

22.7

University

degreeandhigher

25.8

26.4

27.6

32.7

44.9

23.3

23.3

24.7

28.7

34.4

Smokingstatus(%

)

Never

22.3

27.1

33.1

40.0

51.6

53.6

59.5

62.4

63.9

63.8

Form

er37.6

38.0

37.3

37.1

33.0

22.2

21.3

21.8

23.2

26.0

Smoker

40.2

34.8

29.7

22.9

15.5

24.3

19.3

15.8

12.9

10.2

Hyperlipidem

ia(%

)430.2

27.6

24.1

20.2

15.0

16.1

15.8

15.4

13.7

11.5

Hypertension(%

)531.8

26.9

22.5

16.7

11.0

25.2

21.8

19.8

16.0

12.7

Diabetes

(%)6

3.8

3.8

3.5

3.6

2.6

2.7

2.6

2.3

1.6

1.5

Premenopausalwomen

(%)

——

——

—31.9

32.8

33.9

36.4

39.7

1Means6

SDsandpercentages

arepresentedforcontinuousandcategoricalvariables,respectively

(exceptwhereotherwisespecified).AICR,American

Institute

ofCancerResearch;WCRF,

World

CancerResearchFund.

2Number

ofyears

betweenrecruitmentandcensoring.Allvalues

aremedians.

3Withtheuse

ofcalibrateddietary

data.

4Self-reportedhyperlipidem

iaand/ortreatm

entofhyperlipidem

ia.

5Self-reportedhypertensionand/ortreatm

entofhypertension.

6Self-reporteddiabetes

and/ortreatm

entofdiabetes.

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TABLE3

HRs(95%

CIs)ofdeath

accordingto

WCRF/AICRscore

andsex1

Total

Men

Women

No.ofcases/total

subjects

Model

0Model1

No.ofcases/total

subjects

Model

0Model1

No.ofcases/total

subjects

Model0

Model1

Inthetotalsample

WCRF/AICRscore

categories

15468/70,578

1(reference)

1(reference)

2365/19,241

1(reference)

1(reference)

3103/51,337

1(reference)

1(reference)

26713/98,183

0.82(0.79,0.85)

0.87(0.83,0.90)

3328/31,111

0.82(0.78,0.87)

0.88(0.83,0.93)

3385/67,072

0.81(0.77,0.85)

0.86(0.81,0.90)

38108/138,520

0.69(0.67,0.71)

0.77(0.74,0.79)

3942/45,813

0.67(0.64,0.71)

0.77(0.73,0.81)

4166/92,707

0.71(0.67,0.74)

0.77(0.73,0.81)

43103/61,714

0.60(0.58,0.63)

0.70(0.67,0.74)

1560/21,243

0.59(0.56,0.63)

0.73(0.68,0.78)

1543/40,471

0.61(0.57,0.65)

0.69(0.65,0.74)

5436/9869

0.55(0.50,0.61)

0.66(0.60,0.73)

235/4035

0.56(0.49,0.65)

0.71(0.62,0.82)

201/5834

0.54(0.46,0.62)

0.62(0.54,0.72)

P-trend

—,0.0001

,0.0001

—,0.0001

,0.0001

—,0.0001

,0.0001

HRper

1-unitincrease

of

WCRF/AICRscore

23,828/378,864

0.82(0.81,0.83)

0.87(0.86,0.88)

11,430/12,1443

0.81(0.80,0.83)

0.88(0.86,0.90)

12,398/25,7421

0.83(0.82,0.85)

0.87(0.85,0.89)

After

exclusionofsubjects

withhyperlipidem

ia,

hypertension,

ordiabetes2

HRper

1-unitincrease

of

WCRF/AICRscore

14,711/268,919

0.81(0.81,0.84)

0.88(0.87,0.90)

68,80/81,074

0.82(0.79,0.84)

0.89(0.86,0.91)

7831/18,7845

0.84(0.82,0.86)

0.88(0.86,0.90)

After

exclusionofparticipants

whodiedin

thefirst2y

offollow

-up

HRper

1-unitincrease

of

WCRF/AICRscore

22,431/377,467

0.77(0.76,0.78)

0.87(0.86,0.88)

10,621/120,634

0.81(0.79,0.83)

0.88(0.86,0.90)

11,810/256,833

0.83(0.82,0.85)

0.87(0.85,0.89)

1WCRF/AICRscore

ranges

were0–6in

men

and0–7in

women.Calibrateddatawereused.M

odel0was

aCox

modelstratified

bysex,ageatrecruitment(5-y

category),andcenter.Model1was

adjusted

asformodel

0andforeducational

level(none,

primaryschool

completed,technicalorprofessional

school,secondaryschool,university

degree,

andunknownormissing),sm

okingstatusandintensity

of

smoking(never;form

er,quitsm

oking.20yago;form

er,quitsm

oking11–20yago;form

er,quitsm

oking#10yago;sm

oker,1–15cigarettes/d;sm

oker,16–25

cigarettes/d;sm

oker,.25cigarettes/d;and

smoker,pipeorcigar;andunknow

normissing),andmenopause

status(premenopausal,perim

enopausal,andpostmenopausal).AICR,American

Institute

ofCancerResearch;WCRF,

WorldCancerResearch

Fund. 2Atbaseline,participantswereclassified

withhyperlipidem

iaifthey

reported

havinghyperlipidem

iaortakingalipid-low

eringdrug,withhypertensionifthey

reported

havinghypertensionortakingan

antihypertensive

drug,andwithdiabetesifthey

reported

havingdiabetes

ortakingan

antidiabetic

drug.

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The association between the WCRF/AICR score and hazard ofdeath was not substantially modified after additional adjustmentfor total energy intake (model 2; data not presented) with theexclusion of participants with BMI ,18 (data not presented),participants with hyperlipidemia, hypertension, or diabetes atbaseline, or participants who died in the first 2 y of follow-up.Despite the heterogeneity in country (P-heterogeneity, 0.0001;see Figure S1 under “Supplemental data” in the online issue),significant associations between a higher score and lower risk ofdeath were observed in all countries, which indicated that theheterogeneity was due to differences in the strength of the as-sociation rather than the direction.

Each individual WCRF/AICR component was inversely as-sociated with risk of death except the consumption of animalfoods for which risk of death was significantly decreased inparticipants in the middle category only (Table 4). Main dif-ferences according to sex concerned the physical activity com-ponent, which was more protective in women, and the alcoholicdrinks component ,which was more protective in men. The as-sociation between the WCRF/AICR score and risk of death re-mained relatively unchanged when individual components of theWCRF/AICR score were excluded alternatively from the overall

score. Compared with the HR per 1 SD for the global score(0.86; 95% CI: 0.85, 0.88), HRs moved slightly more toward thenull when the BMI, physical activity, or breastfeeding compo-nents were removed from the overall score [0.89 (95% CI: 0.87,0.90), 0.88 (95% CI: 0.87, 0.90), and 0.89 (95% CI: 0.87, 0.90),respectively]. None of the remaining components strengthenedthe inverse association when removed.

The association between risk of death and the WCRF/AICRscore was not significantly modified by smoking status (see TableS2 under “Supplemental data” in the online issue). However, theinverse association appeared to be slightly stronger in normalweight and obese than overweight participants [HR (95% CI) per1-unit increase of the WCRF/AICR score: 0.86 (0.85, 0.88) and0.86 (0.83, 0.89) compared with 0.91 (0.89, 0.93), respectively;P-interaction = 0.0002)], in participants aged 50–59 comparedwith,50 and.60 y [0.85 (0.83, 0.87) compared with 0.88 (0.85, 0.91)and 0.89 (0.87, 0.90), respectively; P-interaction = 0.02], and inparticipants who completed primary school [0.86 (0.84,0.88)] ortechnical/professional school [0.85 (0.83, 0.88)] compared withparticipants without education [0.89 (0.85, 0.94)], with a sec-ondary school degree ([0.88 (0.86,0.91)], and with a universitydegree or higher [0.90 (0.87, 0.92)] (P-interaction = 0.03).

TABLE 4

HRs (95% CIs) of death according to individual WCRF/AICR components and sex1

WCRF/AICR components

Total Men Women

HR (95% CI) P-trend HR (95% CI) P-trend HR (95% CI) P-trend

Body fatness

0 1 (reference) 1 (reference) 1 (reference)

0.5 0.77 (0.74, 0.79) 0.74 (0.70, 0.77) 0.81 (0.77, 0.85)

1 0.78 (0.75, 0.81) ,0.0001 0.79 (0.75, 0.83) ,0.0001 0.78 (0.74, 0.82) ,0.0001

Physical activity

0 1 (reference) 1 (reference) 1 (reference)

0.5 0.85 (0.81, 0.88) 0.88 (0.83, 0.94) 0.82 (0.78, 0.87)

1 0.85 (0.82, 0.87) ,0.0001 0.87 (0.84, 0.91) ,0.0001 0.82 (0.78, 0.85) ,0.0001

Foods and drinks that

promote weight gain

0 1 (reference) 1 (reference) 1 (reference)

0.25–0.5 0.89 (0.84, 0.95) 0.88 (0.82, 0.95) 0.91 (0.81, 1.02)

0.75–1 0.91 (0.85, 0.97) 0.14 0.95 (0.87, 1.03) 0.71 0.89 (0.79, 1.01) 0.07

Plant foods

0 1 (reference) 1 (reference) 1 (reference)

0.25–0.5 0.84 (0.81, 0.88) 0.82 (0.76, 0.88) 0.86 (0.82, 0.91)

0.75–1 0.79 (0.75, 0.83) ,0.0001 0.76 (0.70, 0.82) ,0.0001 0.81 (0.77, 0.87) ,0.0001

Animal foods

0 1 (reference) 1 (reference) 1 (reference)

0.5 0.95 (0.92, 0.98) 0.93 (0.88, 0.98) 0.96 (0.93, 1.00)

1 1.01 (0.96, 1.06) 0.60 0.98 (0.90, 1.06) 0.33 1.03 (0.97, 1.10) 0.79

Alcoholic drinks

0 1 (reference) 1 (reference) 1 (reference)

0.5 0.83 (0.79, 0.87) 0.80 (0.75, 0.86) 0.87 (0.82, 0.93)

1 0.92 (0.89, 0.95) 0.003 0.89 (0.85, 0.93) ,0.0001 0.97 (0.92, 1.03) 0.51

Breastfeeding

0 1 (reference) 1 (reference)

0.5 0.87 (0.83, 0.91) NA 0.87 (0.83, 0.91)

1 0.83 (0.80, 0.87) ,0.0001 0.83 (0.80, 0.87) ,0.0001

1With the use of calibrated data. Cox model was stratified by sex, age at recruitment (5-y category), and center and adjusted for educational level (none,

primary school, technical school, secondary school, and university degree, and unknown or missing), smoking status and intensity of smoking (never; former,

quit smoking.20 y ago; former, quit smoking 11–20 y ago; former, quit smoking #10 y ago; smoker, 1–15 cigarettes/d; smoker, 16–25 cigarettes/d; smoker,

.25 cigarettes/d; and smoker, pipe or cigar; and unknown or missing), and menopause status (premenopausal, perimenopausal, and postmenopausal), and all

WCRF/AICR components were mutually adjusted. AICR, American Institute of Cancer Research; WCRF, World Cancer Research Fund.

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Hazards of cause-specific death according to the WCRF/AICRscore are presented in Table 5. Hazards of death from all causeswere lower in participants with a higher WCRF/AICR score (allP , 0.0001). Dose-response associations were observed for allcauses of death apart from death from cancer for which hazardsof death decreased from the first to third categories of the scoreand stagnated afterward. The strongest inverse association wasobserved for death from respiratory disease per 1-unit increaseof the WCRF/AICR score [HR: 0.79; 95% CI: 0.74, 0.85) fol-lowed by death from circulatory disease (HR: 0.83; 95% CI:0.81, 0.86) and finally death from cancer (HR: 0.91; 95% CI:0.89, 0.93). Results were similar according to sex apart for thehazard of death from respiratory disease, which decreased morestrongly with the adherence to WCRF/AICR recommendationsin women than men. Results were similar when only neversmokers were analyzed, although the association in men was notsignificant anymore (see Table S3 under “Supplemental data” inthe online issue).

Hazards of cause-specific deaths for each WCRF/AICRcomponent are presented in Table 6. The body fatness compo-nent was inversely associated with the hazard of death from allcauses and the strongest predictor of death from circulatorydisease (HR for participants with 1 point compared with par-ticipants with ,0.5 points: 0.60; 95% CI: 0.55, 0.65). Thephysical activity component was inversely associated with thehazard of death from all causes as well, but the association wasstronger for death from respiratory disease (HR: 0.53; 95% CI:0.44, 0.64). The component of foods and drinks that promoteweight gain was only significantly associated with the hazard ofdeath from respiratory disease (HR: 0.65; 95% CI: 0.48, 0.89).The plant foods component was inversely associated with thehazard of death from all causes and the strongest predictor ofdeath from cancer (HR: 0.84; 95% CI: 0.87, 0.91) and deathfrom respiratory disease HR: 0.54; 95% CI: 0.44, 0.68; along

with the physical activity component). The animal foods com-ponent was not significantly associated with any cause of death.The alcoholic drinks component was only inversely associatedwith the hazard of death from cancer (HR: 0.88; 95% CI: 0.84,0.93). However, this association was mainly observed in men. Inaddition, the alcoholic drinks component was positively associ-ated with death from circulatory disease in women. The breast-feeding component was inversely associated with the hazard ofdeath from both cancer (HR: 0.90; 95% CI: 0.84, 0.97) and cir-culatory disease (HR: 0.83; 95% CI: 0.75, 0.92) but not withdeath from respiratory disease (HR: 0.85; 95% CI: 0.68, 1.06).

When we used life-time alcohol consumption instead of al-cohol consumption at baseline to determine adherence to thealcohol recommendation, the inverse association between thealcohol component and risk of death was strengthened for allcauses of death (see Table S4 under “Supplemental data” in theonline issue). In particular, the inverse association between thealcohol component and risk of death from circulatory and re-spiratory diseases became significant. Consequently, the inverseassociation between the global WCRF/AICR score and risk ofdeath was strengthened as well.

DISCUSSION

Main findings

In this large European cohort study, adherence to WCRF/AICR recommendations on diet, physical activity, and bodyfatness was inversely related to risk of death. After 12 y of follow-up, participants in the fifth category of theWCRF/AICR score (5–6 points in men; 6–7 points in women) had a 34% lower hazardof death compared with that of participants in the first categoryof the score (0–2 points in men; 0–3 points in women). A sig-nificant lower hazard was already observed from the second

TABLE 5

HRs (95% CIs) of cause-specific death according to the WCRF/AICR score and sex1

Causes of

death

No. of

cases

WCRF/AICR score

categories

P-trend

HR per 1-unit increase

of WCRF/AICR score1 2 3 4 5

Total

Cancer 9388 1 (reference) 0.92 (0.87, 0.98) 0.82 (0.77, 0.86) 0.80 (0.74, 0.86) 0.80 (0.69, 0.93) ,0.0001 0.91 (0.89, 0.93)

Circulatory disease 5229 1 (reference) 0.84 (0.77, 0.90) 0.73 (0.68, 0.79) 0.60 (0.54, 0.66) 0.56 (0.46, 0.69) ,0.0001 0.83 (0.81, 0.86)

Respiratory disease 1004 1 (reference) 0.82 (0.69, 0.97) 0.63 (0.53, 0.75) 0.56 (0.45, 0.70) 0.50 (0.31, 0.80) ,0.0001 0.79 (0.74, 0.85)

Other causes 4228 1 (reference) 0.84 (0.77, 0.91) 0.72 (0.66, 0.78) 0.62 (0.56, 0.70) 0.55 (0.43, 0.70) ,0.0001 0.83 (0.80, 0.86)

Men

Cancer 4301 1 (reference) 0.93 (0.85, 1.01) 0.81 (0.75, 0.88) 0.81 (0.72, 0.90) 0.86 (0.69, 1.07) ,0.0001 0.92 (0.89, 0.95)

Circulatory disease 2948 1 (reference) 0.84 (0.75, 0.93) 0.73 (0.66, 0.81) 0.62 (0.54, 0.71) 0.64 (0.50, 0.82) ,0.0001 0.84 (0.80, 0.88)

Respiratory disease 493 1 (reference) 0.91 (0.70, 1.19) 0.67 (0.51, 0.87) 0.66 (0.48, 0.90) 0.85 (0.48, 1.50) 0.006 0.84 (0.76, 0.94)

Other causes 1984 1 (reference) 0.85 (0.75, 0.96) 0.68 (0.60, 0.77) 0.65 (0.55, 0.76) 0.56 (0.40, 0.79) ,0.0001 0.82 (0.78, 0.87)

Women

Cancer 5087 1 (reference) 0.91 (0.84, 0.99) 0.82 (0.76, 0.89) 0.80 (0.72, 0.87) 0.76 (0.62, 0.93) ,0.0001 0.91 (0.88, 0.94)

Circulatory disease 2281 1 (reference) 0.84 (0.75, 0.94) 0.73 (0.65, 0.82) 0.58 (0.50, 0.69) 0.44 (0.32, 0.65) ,0.0001 0.83 (0.79, 0.86)

Respiratory disease 511 1 (reference) 0.75 (0.59, 0.95) 0.63 (0.50, 0.79) 0.50 (0.36, 0.68) 0.17 (0.06, 0.52) ,0.0001 0.76 (0.69, 0.83)

Other causes 2244 1 (reference) 0.82 (0.73, 0.92) 0.75 (0.67, 0.84) 0.60 (0.52, 0.70) 0.54 (0.38, 0.76) ,0.0001 0.83 (0.80, 0.87)

1WCRF/AICR scores ranges were 0–6 in men and 0–7 in women. Calibrated data were used. Cox model was stratified by sex, age at recruitment (5-y

category), and center and adjusted for educational level (none, primary school, technical school, secondary school, and university degree, and unknown or

missing), smoking status and intensity of smoking (never; former, quit smoking .20 y ago; former, quit smoking 11–20 y ago; former, quit smoking #10 y

ago; smoker, 1–15 cigarettes/d; smoker, 16–25 cigarettes/d; smoker, .25 cigarettes/d; and smoker, pipe or cigar; and unknown or missing), and menopause

status (premenopausal, perimenopausal, and postmenopausal). AICR, American Institute of Cancer Research; WCRF, World Cancer Research Fund.

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TABLE6

HRs(95%

CIs)ofcause-specificdeathsper

1-unitincrease

ofeach

WCRF/AICRscore

componentaccordingto

sex1

Death

from

cancer

Death

from

circulatory

disease

Death

from

respiratory

disease

Death

from

other

causes

Total

Bodyfatness

0.93(0.88,0.99)

0.02

0.60(0.55,0.65)

,0.0001

0.77(0.65,0.91)

0.003

0.72(0.66,0.79)

,0.0001

Physicalactivity

0.90(0.86,0.94)

,0.0001

0.79(0.74,0.84)

,0.0001

0.59(0.51,0.69)

,0.0001

0.76(0.71,0.82)

,0.0001

Foodsanddrinks

that

promote

weightgain

1.03(0.92,1.15)

0.66

0.91(0.79,1.04)

0.17

0.65(0.48,0.89)

0.006

0.76(0.65,0.88)

0.0002

Plantfoods

0.84(0.78,0.91)

,0.0001

0.74(0.67,0.82)

,0.0001

0.54(0.44,0.68)

,0.0001

0.79(0.70,0.89)

,0.0001

Anim

alfoods

0.93(0.86,1.01)

0.09

0.97(0.88,1.08)

0.62

1.15(0.92,1.44)

0.21

1.19(1.06,1.34)

0.003

Alcoholicdrinks

0.88(0.84,0.93)

,0.0001

1.07(0.99,1.16)

0.09

1.09(0.91,1.31)

0.34

0.82(0.75,0.88)

,0.0001

Breastfeeding2

0.90(0.84,0.97)

0.004

0.83(0.75,0.92)

0.0004

0.85(0.68,1.06)

0.14

0.72(0.65,0.80)

,0.0001

Men Bodyfatness

0.98(0.90,1.08)

0.69

0.57(0.51,0.63)

,0.0001

0.93(0.72,1.19)

0.55

0.78(0.69,0.89)

0.0002

Physicalactivity

0.93(0.87,0.99)

0.03

0.84(0.77,0.91)

,0.0001

0.66(0.54,0.82)

0.0001

0.79(0.72,0.88)

,0.0001

Foodsanddrinks

that

promote

weightgain

1.09(0.94,1.26)

0.24

0.92(0.78,1.09)

0.32

0.68(0.46,1.01)

0.06

0.79(0.66,0.95)

0.01

Plantfoods

0.81(0.71,0.93)

0.002

0.70(0.60,0.81)

,0.0001

0.57(0.40,0.81)

0.002

0.67(0.56,0.82)

,0.0001

Anim

alfoods

0.87(0.75,1.00)

0.04

0.97(0.84,1.13)

0.73

1.18(0.84,1.64)

0.34

1.10(0.91,1.34)

0.31

Alcoholicdrinks

0.86(0.80,0.92)

,0.0001

1.04(0.95,1.14)

0.41

1.03(0.81,1.30)

0.84

0.76(0.69,0.84)

,0.0001

Women

Bodyfatness

0.90(0.83,0.97)

0.008

0.64(0.57,0.72)

,0.0001

0.67(0.53,0.84)

0.0006

0.68(0.61,0.77)

,0.0001

Physicalactivity

0.86(0.81,0.92)

,0.0001

0.72(0.65,0.80)

,0.0001

0.52(0.41,0.65)

,0.0001

0.72(0.65,0.80)

,0.0001

Foodsanddrinks

that

promote

weightgain

0.93(0.77,1.12)

0.45

0.92(0.69,1.22)

0.54

0.68(0.41,1.12)

0.13

0.89(0.65,1.21)

0.45

Plantfoods

0.86(0.77,0.95)

0.003

0.78(0.68,0.90)

0.0006

0.54(0.41,0.73)

,0.0001

0.87(0.75,1.01)

0.07

Anim

alfoods

0.97(0.88,1.08)

0.59

0.97(0.84,1.12)

0.69

1.17(0.86,1.58)

0.32

1.25(1.08,1.45)

0.004

Alcoholicdrinks

0.93(0.86,1.01)

0.10

1.18(1.01,1.37)

0.04

1.19(0.89,1.58)

0.24

0.92(0.82,1.04)

0.20

Breastfeeding

0.90(0.84,0.96)

0.003

0.83(0.75,0.92)

0.0006

0.86(0.69,1.07)

0.18

0.72(0.65,0.80)

,0.0001

1WCRF/AICRscore

ranges

were0–6in

men

and0–7in

women.Calibrateddatawereused.C

oxmodelwas

stratified

bysex,ageatrecruitment(5-y

category),andcenter

andadjusted

foreducationallevel

(none,primaryschool,technicalschool,secondaryschool,and

university

degree,andunknownormissing),sm

okingstatusandintensity

ofsm

oking(never;form

er,quitsm

oking>20yago;form

er,quitsm

oking

11–20

yago;form

er,quitsm

oking#10yago;sm

oker,1–15cigarettes/d;sm

oker,16–25

cigarettes/d;sm

oker,>25cigarettes/d;andsm

oker,pipeorcigar;andunknow

normissing),andmenopause

status

(premenopausal,perim

enopausal,andpostmenopausal),andallWCRF/AICRcomponentsweremutually

adjusted.HRscompared

participantswhoadhered

torecommendation(1

point)withthosewhodid

not

(,0.5

points).AICR,American

Institute

ofCancerResearch;WCRF,

WorldCancerResearchFund.

2In

women

only.

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category of the score. All specific causes of death studied wereinversely associated with the score, but the strongest associationwas observed for risk of death from respiratory disease followedby death from circulatory disease and, finally, by death fromcancer. Recommendations on adiposity and plant foods were themost strongly associated with the hazard of death. However,associations of each WCRF/AICR score component differedaccording to the cause of death and sex.

Causes of death

In agreement with most previous studies that investigated theadherence to diet and lifestyle recommendations (2, 3, 6, 8), weshowed a weaker association between the WCRF/AICR scoreand death from cancer compared with death from circulatorydisease, which seemed to be explained, to a large extent, bya weaker association with the BMI component for death fromcancer compared with circulatory disease. Obesity has beenpreviously associated with increased risk of several cancers andhas been widely acknowledge as a major determinant of CVD andendocrine and metabolic disturbances (20). In a previous EPICstudy, RRs of death associated with a high BMI were alsostrongest for circulatory causes of death, followed by other causesand neoplasms (21). The alcohol (by using lifetime consump-tion), plant food, and breastfeeding components were inverselyassociated with hazards of death from both cancer (21%, 17%,and 9% reduced risk, respectively) and circulatory disease (10%,29%, and 8% reduced risk, respectively). A previous EPIC studyreported that 10% and 3% of the incidence of total cancer wasattributable to former and current alcohol consumption, re-spectively (22). The association with death from circulatorydisease is more controversial, but a recent meta-analysis reportedreduced risk of death frommultiple cardiovascular outcomes withlight-to-moderate alcohol consumption (23). Several studiespreviously showed reduced risk of death from cancer and CVDwith increased consumption of fiber (24), fruit, and vegetables(24, 25). To our knowledge, no previous study investigated theassociation between breastfeeding and mortality in the mother.However, a previous review suggested that a failure to breastfeedcould be associated with an increased incidence of pre-menopausal breast cancer, ovarian cancer, type 2 diabetes,myocardial infarction, and the metabolic syndrome (26). Theterminal differentiation of breast tissue because of lactogenesis(with potential long-term effects on malignant transformation),development of the Mucin 1 antigen during mastitis, and mo-bilization of adipose stores with lactation were suggested aspotential mechanisms (26).

In the current study, respiratory disease was the cause of deaththat was most strongly associated with adherence to WCRF/AICR recommendations (21% lower hazard of death per 1-unitincrease). Similar results were observed in never smokers, al-though the association in men was not significant anymore,plausibly because of the low number of death from respiratorydisease in men who never smoked (n = 71). The stronger as-sociation with risk of death from respiratory diseases seems tobe explained to a large extend by a stronger inverse associationfor the plant foods and physical activity components. To ourknowledge, no previous study investigated the association be-tween scores derived from diet and lifestyle recommendationsand death from respiratory disease. However, individual factors

have been previously analyzed. First, significant inverse asso-ciations between fiber intake and risk of death from respiratorydisease (24) and between daily total vegetable intake and risk ofchronic obstructive pulmonary disease (27) have previouslybeen reported. Fiber could positively affect the makeup of theintestinal microbiota, which is involved in the regulation ofimmune and inflammatory responses (28). Second, severalstudies showed an inverse association between physical activityand mortality (29–32). Some (29, 30) but not all (31, 32) studiesreported a stronger protective effect on death from respiratorydisease than from other causes of death. Only one (24) of thestudies performed analyses in nonsmokers only. However, withonly 90 deaths from respiratory diseases, Park et al (24) couldnot confirm the inverse association between fiber intake and riskfrom respiratory disease observed in the total sample (24).Similar to these previous studies, we did not have baseline in-formation on history of respiratory illnesses, which could haveexplained the stronger inverse association observed for deathfrom disease of the respiratory system. This result was espe-cially likely for the physical activity component because dis-eases from the respiratory system often cause reductions inphysical activity. Deaths from respiratory disease represented7% of the total death burden worldwide in 2004 (33). The po-tential protective effect of the adherence to WCRF/AICR rec-ommendations on death from respiratory diseases is of majorpublic health importance and deserves additional investigationsin studies with a history of respiratory illnesses at baselineavailable and a large sample size that would permit stratificationby smoking status.

Strengths and limitations of the study

One of the main advantages of the current study was its verylarge sample size, which provided enough power to investigatecause-specific deaths including death from respiratory diseaseand to explore various interaction factors, including smokingstatus. The WCRF/AICR score operationalizes each recom-mendation as described in the WCRF/AICR report, is easilyreplicable, is associated with a healthy lifestyle overall, and hasbeen previously associated with reduced risk of cancer asexpected (10). All components of the score were significantlyassociated with the hazard of death after mutual adjustment foreach other, except the animal foods component for whicha significant lower hazard of death was observed in the middlecategory only. The HR associated with the animal foods rec-ommendation was similar for death from cancer compared withthose previously reported for cancer morbidity (HR: 0.94 and0.93, respectively) (10). The nonsignificant result in our studywas most likely to the result of the lower number of cancer deathsthan incident cancers. The WCRF/AICR score is also the firstscore derived from public health recommendations that includesbreastfeeding as a protective factor for the mother, and weshowed that adherence to this recommendation was associatedwith reduced risk of death from cancer and circulatory disease.

Several limitations of the current study should be considered.First, we could not include all WCRF/AICR recommendations inour score, either because we had not enough data available (ie, forthe preservation, processing, and preparation recommendationand the dietary supplements recommendation) or because rec-ommendations were not applicable to the objectives of this study

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(recommendation for cancer survivors). For example, the rec-ommendation of limiting the consumption of salt could not beincluded in the score, and salt intake has been associated withincreased blood pressure and CVD risk (34) as well as stomachcancer risk (35). Therefore, the reduction in risk of death as-sociated with adherence to WCRF/AICR recommendations waslikely to be underestimated. In addition, each component wasgiven an equal weight because the WCRF/AICR report did notrank recommendations in term of priority. Therefore, the effect offactors strongly related to the hazard of death could have beendiluted by the inclusion in the score of factors less stronglyassociated with the hazard of death, which could have led to anunderestimation of the joint effect of WRCF/AICR recommen-dations. However, we also investigated associations between eachcomponent of the score and each cause of death to providea more-comprehensive picture of associations between the scoreand risk of death. We used validated questionnaires (15) to assessthe exposure, and dietary data were calibrated according tocountry. However, lifestyle was assessed at baseline only andmayhave changed overtime. Therefore, residual measurement errorand misclassification may have biased estimates toward the null.Indeed, when lifetime alcohol consumption was used instead ofalcohol consumption at baseline, results for that component werestrengthened. Our analyses were adjusted for both smoking statusand the intensity of smoking. Nevertheless, residual confoundinglinked to smoking habits or other unmeasured confounders couldnot be ruled out. This may have occurred for death from re-spiratory disease in particular and resulted in the overestimationof the inverse association between the WCRF/AICR score andrisk of death from respiratory diseases. Finally, our analysis wasperformed in a large European population, and estimates may notbe directly applicable to other populations with different life-styles and risks of disease.

In conclusion, this large European study showed a strongassociation between adherence to lifestyle and dietary WCRF/AICR recommendations at baseline and reduced hazard of death.Adherence to WCRF/AICR recommendations was not only in-versely associated with death from cancer and circulatory diseasebut also with death from respiratory disease. At least 4 of 7WCRF/AICR components were strongly associated with eachcause of death, and all recommendations were inversely asso-ciated with at least one cause of death. These results are ofprimary importance to increase the awareness and the complianceof the population to those major recommendations as well asunderstand how to reduce the mortality burden worldwide.Additional research in other large populations is needed toconfirm our findings, especially regarding death from respiratorydisease and breastfeeding in the mother.

We thank all EPIC participants and staff for their contribution to the study.

The authors’ responsibilities were as follows—TN: was the principal in-

vestigator of the project and had primary responsibility for final content; ER:

is the overall coordinator of the EPIC study, which was conceptualized,

designed, and implemented in collaboration with the main investigators in

collaborating countries; IR, HBB-d-M, NJW, K-TK, FC-C, RT, ATjonneland,

HB, A Trichopoulou, DT, PV, SP, M-JS, GH, KO, EL, and PHP: contrib-

uted to the study design, subject recruitment, and data collection and

acquisition and are responsible for the ongoing follow-up and manage-

ment of the EPIC cohort; TN, PHP, CHvG, and ER: conceived the current

study; A-CV: was responsible for the study design, analysis of data, inter-

pretation of results, and drafting of the manuscript; TN, DR, PHP, CHvG,

DSMC, PF, and ER: helped with the interpretation of results, and drafting of

the manuscript; and all authors: contributed to data interpretation and critical

reading of the manuscript and saw and approved the final version of the

manuscript. None of the authors had a conflict of interest.

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