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Breast Cancer Research and Treatment

, Volume 159, Issue 1, pp 139–149 | Cite as

Patterns of change over time and history of the inflammatory potential of diet and risk of breast cancer among postmenopausal women

  • Fred K. Tabung
  • Susan E. Steck
  • Angela D. Liese
  • Jiajia Zhang
  • Yunsheng Ma
  • Karen C. Johnson
  • Dorothy S. Lane
  • Lihong Qi
  • Linda Snetselaar
  • Mara Z. Vitolins
  • Judith K. Ockene
  • James R. Hebert
Epidemiology

Abstract

We utilized the dietary inflammatory index (DII) to investigate associations between patterns of change in, and history of the inflammatory potential of diet and risk of breast cancer in the Women’s Health Initiative (WHI). We included 70,998 postmenopausal women aged 50–79 years recruited from 1993 to 1998 into the WHI Observational Study and Dietary Modification trial control group and followed through August 29, 2014. We utilized data from food frequency questionnaires administered at baseline and Year 3, to calculate average DII scores, patterns of change in DII, and used these measures in multivariable-adjusted Cox regression models to estimate hazards ratios (HR) and 95 % confidence intervals (CI) for incident invasive breast cancer and its subtypes. After 1,093,947 person-years of follow-up, 3471 cases of invasive breast cancer were identified. There was no substantial association between average DII scores or patterns of change in DII and risk of overall invasive breast cancer (HR, 1.03; 95 % CI, 0.90, 1.17; P-trend = 0.79; comparing extreme average DII quintiles). However, there was a significant nonlinear association between average DII scores and the ER−, PR−, HER2+, subtype (HR, 2.37; 95 % CI, 1.08, 5.20; P-trend = 0.18; comparing extreme quintiles). For patterns of change in DII, the age-adjusted association with ER−, PR−, HER2+ subtype comparing women in the proinflammatory stable to those in the anti-inflammatory stable categories (HR, 1.82; 95 % CI, 1.06, 3.13) persisted in the multivariable-adjusted model but was less precise (HR, 1.85; 95 % CI, 0.96, 3.55; P = 0.06). Dietary inflammatory potential may differentially influence the development of specific breast cancer phenotypes.

Keywords

Breast cancer Dietary patterns Inflammation Diet Epidemiology 

Notes

Acknowledgements

Dr. Tabung and Dr. Hebert were supported by National Cancer Institute Grants Numbers F31 CA177255 and K05 CA136975, respectively. The WHI program was 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.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Disclosure

Dr. James R. Hébert owns controlling interest in Connecting Health Innovations LLC (CHI), a company planning to license the right to his invention of the dietary inflammatory index (DII) from the University of South Carolina in order to develop computer and smart phone applications for patient counseling and dietary intervention in clinical settings.

Supplementary material

10549_2016_3925_MOESM1_ESM.doc (27 kb)
Supplementary material 1 (DOC 27kb)
10549_2016_3925_MOESM2_ESM.xlsx (114 kb)
Supplementary material 2 (XLSX 114kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Fred K. Tabung
    • 1
    • 2
    • 3
  • Susan E. Steck
    • 2
    • 3
    • 4
  • Angela D. Liese
    • 3
    • 4
  • Jiajia Zhang
    • 3
  • Yunsheng Ma
    • 5
  • Karen C. Johnson
    • 6
  • Dorothy S. Lane
    • 7
  • Lihong Qi
    • 8
  • Linda Snetselaar
    • 9
  • Mara Z. Vitolins
    • 10
  • Judith K. Ockene
    • 5
  • James R. Hebert
    • 2
    • 3
  1. 1.Departments of Nutrition and EpidemiologyHarvard T. H. Chan School of Public HealthBostonUSA
  2. 2.Cancer Prevention and Control ProgramUniversity of South CarolinaColumbiaUSA
  3. 3.Department of Epidemiology and BiostatisticsArnold School of Public Health, University of South CarolinaColumbiaUSA
  4. 4.Center for Research in Nutrition and Health DisparitiesUniversity of South CarolinaColumbiaUSA
  5. 5.Division of Preventive and Behavioral MedicineUniversity of Massachusetts Medical SchoolWorcesterUSA
  6. 6.Department of Preventive MedicineUniversity of Tennessee Health Science CenterMemphisUSA
  7. 7.Department of Family, Population and Preventive MedicineStony Brook University School of MedicineNew YorkUSA
  8. 8.Division of Biostatistics, Department of Public Health SciencesUniversity of CaliforniaDavisUSA
  9. 9.Department of EpidemiologyThe University of IowaIowa CityUSA
  10. 10.Department of Epidemiology and PreventionWake Forest School of MedicineWinston-SalemUSA

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