Publications Search - Abstract View
||Hair dye use and risk of bladder cancer in the New England bladder cancer study.
||Koutros S, Silverman DT, Baris D, Zahm SH, Morton LM, Colt JS, Hein DW, Moore LE, Johnson A, Schwenn M, Cherala S, Schned A, Doll MA, Rothman N, Karagas MR
||Int J Cancer
||2011 Dec 15
||OD, OEEB, REB
||Aromatic amine components in hair dyes and polymorphisms in genes that encode enzymes responsible for hair dye metabolism may be related to bladder cancer risk. We evaluated the association between hair dye use and bladder cancer risk and effect modification by N-acetyltransferase-1 (NAT1), NAT2, glutathione S-transferase Mu-1 (GSTM1) and glutathione S-transferase theta-1 (GSTT1) genotypes in a population-based case-control study of 1193 incident cases and 1418 controls from Maine, Vermont and New Hampshire enrolled between 2001 and 2004. Individuals were interviewed in person using a computer-assisted personal interview to assess hair dye use and information on potential confounders and effect modifiers. No overall association between age at first use, year of first use, type of product, color, duration or number of applications of hair dyes and bladder cancer among women or men was apparent, but increased risks were observed in certain subgroups. Women who used permanent dyes and had a college degree, a marker of socioeconomic status, had an increased risk of bladder cancer [odds ratio (OR) = 3.3, 95% confidence interval (CI): 1.2-8.9]. Among these women, we found an increased risk of bladder cancer among exclusive users of permanent hair dyes who had NAT2 slow acetylation phenotype (OR = 7.3, 95% CI: 1.6-32.6) compared to never users of dye with NAT2 rapid/intermediate acetylation phenotype. Although we found no relation between hair dye use and bladder cancer risk in women overall, we detected evidence of associations and gene-environment interaction with permanent hair dye use; however, this was limited to educated women. These results need confirmation with larger numbers, requiring pooling data from multiple studies.