Dietary Inflammatory Index and Risk of Colorectal Cancer in Women - PowerPoint Presentation

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Dietary Inflammatory Index and Risk of Colorectal Cancer in Women

Fred

Tabung

,

PhD(c

), MSPH

Department

of Epidemiology and Biostatistics

Cancer Prevention and Control Program

Arnold

School of Public

Health, USC

4

th

Annual

USC

Center for Research in Nutrition and Health Disparities, Annual Symposium

March 21, 2014

Literature-derived population-based index to assess the inflammatory potential of diet

Developed from published associations of 45 dietary factors (macronutrients, micronutrients and foods) and six inflammatory biomarkers

Assesses the inflammatory potential of an individual’s diet on a continuum from maximally anti-inflammatory to maximally pro-inflammatoryValidated using data on hsCRP and 24-hour dietary recall interviews (24HR) and 7-day dietary recalls (7DDR)

T

he dietary inflammatory index (DII)

Shivappa N, Steck SE, Hurley TG, Hussey JR, Hebert JR. Designing and Developing a Literature-derived, Population-based Dietary Inflammatory Index. Public Health Nutr 2013; S1368980013002115 [pii]; 10.1017/S1368980013002115 [doi]:1-8.

Shivappa

N, Steck SE, Hurley TG, Hussey JR, Ma Y, Ockene IS, Tabung FK, Hebert JR. A Population-based Dietary Inflammatory Index Predicts Levels of C-Reactive Protein in the Seasonal Variation of Blood Cholesterol Study (SEASONS). Public Health Nutr 2013; S1368980013002565 [pii]; 10.1017/S1368980013002565 [doi]:1-9.DII References

Distribution of

Food

Groups in Quintiles (Q) of the DIIFood group (medium servings/day)Q1 (-7.055, <-3.136) (healthiest)

Q2 (-3.136, <-1.995)

Q3 (-1.995, <-0.300)

Q4 (-0.300, <1.953)

Q5 (1.953, 5.636) (least healthy)

Fruits

2.712.041.851.731.73Vegetables3.152.302.122.002.00Combo Fruit/Veg 5.864.343.973.733.73Fish0.070.070.070.070.07Red meat0.630.730.740.760.76Poultry0.440.400.380.380.38Soy0.080.020.020.020.02Nuts0.260.200.180.170.17Combo Nut/soy0.340.220.200.180.18Grains5.894.694.554.474.47Whole Grain1.731.241.171.121.12Milk0.970.880.800.710.71Dairy2.302.061.921.761.76

Actual intake data in the WHI CT-OS

About 65,000 American women are projected to be diagnosed with colorectal cancer (CRC) in 2014

3

rd most commonly diagnosed cancer in women after breast and lung cancersAdherence to dietary patterns such as DASH, HEI and Med diet, has been shown to be associated with reduced CRC riskEvidence of an influence of inflammation on CRC:Patients with ulcerative colitis and Crohn's disease have an increased risk of developing CRCR

educed

risk of colon cancer with use of aspirin or

other NSAIDs

C

olorectal cancer

T

o

utilize the DII to evaluate the association of the inflammatory potential of diet with risk of colorectal cancer in postmenopausal womenObjective

DII calculated from baseline FFQs (1993-1998)

Both OS and CT data used

Categorized into quintiles Participants followed until incident colorectal cancer or September 30, 2010Colorectal cancer cases ascertained through a centralized physician adjudication process (n=1,922)Methods

Excluded from analysis:

Women

who reported previous CRC at baseline or missing previous CRC status at baseline Women with implausible reported total energy intake values (≤600 kcal/d or ≥ 5000 kcal/d) or extreme body mass index (BMI) values (≤15kg/m2or ≥ 50kg/m2) Multiple covariate-adjusted Cox

proportional hazards (PH) regression models

used

to calculate hazard ratios (

HR) for:

colorectal cancer

colon cancerproximal colon cancerdistal colon cancer rectal cancerStatistical Analysis

L

owest

DII quintile (most anti-inflammatory diet) was the referent for all modelsPotential effect modification by waist-to-hip ratio, waist circumference, BMI, and NSAID use, investigated by stratifying on these covariates in the Cox PH models Tests of linear trend adjusted for covariates, computed by assigning the median value of each quintile to each participant in the quintile

S

ensitivity analyses- exclusion of CRC cases that occurred within 3 years from baseline

A

nalyses

by stage of

CRC at diagnosis (localized, regional and distant)Statistical Analysis

Total energy intake

Age

BMIRace/ethnicityEducational levelPhysical activityFamily history of colorectal cancerDiabetesHypertensionArthritisHistory of colonoscopyH

istory

of occult blood

tests

NSAID use

C

ategory & duration of estrogen useCategory & duration of combined estrogen & progesterone useDM arm, HRT arm, and CaD armCovariates

Risk of colorectal cancer across quintiles of

the

DIIResults Q1 (-7.055, <-3.136) (healthiest)

Q3 (-1.995, <-0.300)

Q5 (1.953, 5.636) (least healthy)

Referent

HR (95%CI)HR (95%CI)PtrendColorectal cancer1.000.98 (0.84, 1.14)1.22 (1.05, 1.43)0.02Colorectal cancer cases, 1922365 (19.0%)360 (18.7%)435 (22.6%) Colon cancer 1.000.98 (0.83, 1.15)1.23 (1.03, 1.47)0.02Colon cancer cases, 1560299 (19.2%)289 (18.5%)346 (22.2%) Proximal colon 1.000.98 (0.79, 1.20)1.35 (1.09, 1.67)0.01Proximal colon cancer cases, 1034193 (18.7%)181 (17.5%)229 (22.2%) 

HRs were strengthened when CRC cases that developed within 3 years from baseline were excluded,

e.g. HR

Q5vsQ1 for colon cancer: 1.36 (1.11, 1.66), Ptrend=0.003HRs for CRC differed by category of NSAID use:Pinteraction=0.26Non-NSAID users: 1.31 (1.05, 1.65)Q5vsQ1, Ptrend=0.03NSAID users: 1.11 (0.89, 1.38)

Q5vsQ1

,

P

trend

=0.61

No significant association with:Distal colon cancerRectal cancerCRC stage at diagnosisResults

Study limited to postmenopausal women

FFQ measurement error

Diet assessment at only one time pointStudy Limitations

Consumption of pro-inflammatory diets  increases the risk of colorectal

cancer in older women,

especially colon cancer located in the proximal colonConsumption of pro-inflammatory diets  increases the risk of colorectal cancer in older women not regularly taking NSAIDsConclusions

Longitudinal Changes in Diet-related Inflammation and Risk of Cancer in

Women

An assessment of the inflammatory potential of diet over time in the Women’s Health InitiativeChanges in the DII over time and risk of colorectal cancer in women

Future Direction

Chair:

Susan

E. Steck USC Dept. of EPID/BIOS and Cancer Prevention and Control ProgramMembers:Yunsheng Ma UMass Medical SchoolAngela D. Liese USC Dept. of EPID/BIOS and Center for Nutrition & Health DisparitiesJiajia Zhang USC Dept. of Epidemiology & BiostatisticsJames R. Hebert

USC

Dept. of EPID/BIOS and Cancer

Prevention

and Control Program

Acknowledgements

Dissertation Committee

Lifang

Hou

Northwestern Univ. Feinberg School of MedicineBette Caan Kaiser Permanente Division of ResearchKaren K. Johnson Univ. of Tennessee Health Science Center

Yasmin

Mossavar-Rahmani

Albert

Einstein College of

MedicineJean Wactawski-Wende SUNY Dept. of Social and Preventive MedicineJudith K. Ockene UMass Medical SchoolNitin Shivappa USC Dept. of EPID/BIOS and Cancer Prevention and Control ProgramAcknowledgement of Co-Authors

Mr. Tabung

was supported by an NIH F31

National Research Service Predoctoral Award, a USC SPARC grant and a fellowship from the USC Center for Colon Cancer ResearchDrs. Steck and Zhang were supported by the Prevent Cancer Foundation - Living in Pink grantDr. Hébert was supported by an Established Investigator Award in Cancer Prevention and Control from the Cancer Training Branch of the National Cancer Institute (K05 CA136975).Funding for DII development was provided by the CPCP The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C.Acknowledgements - Funding

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