A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study

Evan Y. W. Yu, Anke Wesselius*, Christoph Sinhart, Alicja Wolk, Mariana Carla Stern, Xuejuan Jiang, Li Tang, James Marshall, Eliane Kellen, Piet van den Brandt, Chih-Ming Lu, Hermann Pohlabeln, Gunnar Steineck, Mohamed Farouk Allam, Margaret R. Karagas, Carlo La Vecchia, Stefano Porru, Angela Carta, Klaus Golka, Kenneth C. JohnsonSimone Benhamou, Zuo-Feng Zhang, Cristina Bosetti, Jack A. Taylor, Elisabete Weiderpass, Eric J. Grant, Emily White, Jerry Polesel, Maurice P. A. Zeegers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Article number0007114520001439
Pages (from-to)611-619
Number of pages9
JournalBritish Journal of Nutrition
Volume124
Issue number6
DOIs
Publication statusPublished - 28 Sep 2020

Keywords

  • Bladder cancer
  • Data mining
  • Food groups
  • Epidemiological studies
  • DIETARY PATTERNS
  • RISK-FACTORS
  • FLUID INTAKE
  • CONSUMPTION
  • VEGETABLES
  • FRUIT
  • POLYMORPHISMS
  • METAANALYSIS
  • SMOKING
  • SYSTEM

Cite this

Yu, E. Y. W., Wesselius, A., Sinhart, C., Wolk, A., Stern, M. C., Jiang, X., Tang, L., Marshall, J., Kellen, E., van den Brandt, P., Lu, C-M., Pohlabeln, H., Steineck, G., Allam, M. F., Karagas, M. R., La Vecchia, C., Porru, S., Carta, A., Golka, K., ... Zeegers, M. P. A. (2020). A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study. British Journal of Nutrition, 124(6), 611-619. [0007114520001439]. https://doi.org/10.1017/S0007114520001439