Merab Acham1, Anke Wesselius2, Frits H M van Osch1,3, Evan Yi-Wen Yu1, Piet A van den Brandt4, Emily White5, Hans-Olov Adami6,7, Elisabete Weiderpass6,8,9,10, Maree Brinkman11, Graham G Giles7,11,12, Roger L Milne7,11,13, Maurice P Zeegers1,14. 1. Department of Complex Genetics and Epidemiology, NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Universiteitssingel 40, 6200 MD Maastricht, The Netherlands, Maastricht University, Maastricht, The Netherlands. 2. Department of Complex Genetics and Epidemiology, NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Universiteitssingel 40, 6200 MD Maastricht, The Netherlands, Maastricht University, Maastricht, The Netherlands. anke.wesselius@maastrichtuniversity.nl. 3. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK. 4. Department of Epidemiology, Schools for Oncology and Developmental Biology and Public Health and Primary Care, Maastricht University Medical Centre, Maastricht, The Netherlands. 5. Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 6. Department of Medical Epidemiology and Biostatistics, Medical Epidemiology, Karolinska Institutet, Stockholm, Sweden. 7. Clinical Effectiveness Research Group, Institute of Health and Society, University of Oslo, Oslo, Norway. 8. Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway. 9. Genetic Epidemiology Group, Folkhälsan Research Center and Faculty of Medicine, Helsinki University, Helsinki, Finland. 10. Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway. 11. Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia. 12. Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia. 13. School of Public Health and Preventive Medicine, Monash University Faculty of Medicine, Nursing & Health Sciences, Melbourne, VIC, Australia. 14. CAPHRI School for Public Health and Primary Care, University of Maastricht, Maastricht, The Netherlands.
Abstract
BACKGROUND: Inconsistent associations between milk and other dairy product consumption and bladder cancer (BC) have been reported. We aimed to investigate possible associations with BC risk for total and individual dairy products by bringing together the world's data on this topic. METHODS: Thirteen cohort studies, included in the BLadder cancer Epidemiology and Nutritional Determinants (BLEND) study, provided data for 3590 BC cases and 593,637 non-cases. Associations between milk and other dairy product consumption and BC risk were investigated using Cox proportional hazard regression analyses stratified by study center and adjusted for potential confounders. RESULTS: Overall, total 'other' dairy product consumption was not associated with BC risk (HR comparing highest with lowest tertile: 0.97 (95% CI: 0.87-1.07; ptrend = 0.52) and likewise no association was observed for either liquid milk, processed milk, cream, cheese or icecream. However, an inverse association was observed between yoghurt consumption and BC risk when comparing those in the moderate (25-85 g/day) and high categories (>85 g/day) with non-consumers, with multivariate HR of 0.85 (95% CI: 0.75-0.96) and 0.88 (95% CI: 0.78-0.98), respectively. CONCLUSIONS: We found no evidence of association between either total or individual dairy products and BC risk, but suggestive evidence that consumption of yoghurt may be associated with a decreased risk.
BACKGROUND: Inconsistent associations between milk and other dairy product consumption and bladder cancer (BC) have been reported. We aimed to investigate possible associations with BC risk for total and individual dairy products by bringing together the world's data on this topic. METHODS: Thirteen cohort studies, included in the BLadder cancer Epidemiology and Nutritional Determinants (BLEND) study, provided data for 3590 BC cases and 593,637 non-cases. Associations between milk and other dairy product consumption and BC risk were investigated using Cox proportional hazard regression analyses stratified by study center and adjusted for potential confounders. RESULTS: Overall, total 'other' dairy product consumption was not associated with BC risk (HR comparing highest with lowest tertile: 0.97 (95% CI: 0.87-1.07; ptrend = 0.52) and likewise no association was observed for either liquid milk, processed milk, cream, cheese or icecream. However, an inverse association was observed between yoghurt consumption and BC risk when comparing those in the moderate (25-85 g/day) and high categories (>85 g/day) with non-consumers, with multivariate HR of 0.85 (95% CI: 0.75-0.96) and 0.88 (95% CI: 0.78-0.98), respectively. CONCLUSIONS: We found no evidence of association between either total or individual dairy products and BC risk, but suggestive evidence that consumption of yoghurt may be associated with a decreased risk.
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