Document 5b2mnVOa1d3JK8qxg5LdaB6G4

134. Rappaport, S. M., H. Kromhout, E. Symanski. Variation of Exposure Between Workers in Homogeneous Exposure Groups. Am. Ind. Hyg. Assoc. J 54(11): 654-662, 1993. 135. Rappaport, S.M., Review: Assessment of Long-Term Exposures to Toxic Substances in Air, Ann. Occup. Hyg. 35(1):61-121, 1991. 136. Hewett P. Sample Size Formulae for Estimating the True Arithmetic or Geometric Mean of Lognormal Exposure Distributions. Am. Ind. Hyg. Assoc. J. 56: 219-221, 1995. 137. Nicas, M., and Spear, RC. A Task-Based Statistical Model of a Worker's Exposure Distribution: Part I - Description of the Model. Am. Ind. Hyg. Assoc. J. 54(5):211-220, 1993. 138. Nicas, M., and Spear, RC. A Task-Based Statistical Model of a Worker's Exposure Distribution: Part II - Application ot Sampling Strategy. Am. Ind. Hyg. Assoc. J. 54(5): 221-227,1993. 139. Armstrong, T.W., Pearlman, E.D., Schnatter, A.R, Bowes, S.M., Murray, N. and Nicolich, M., Retrospective Benzene and Total Hydrocarbon Exposure Assessment for A Petroleum Marketing and Distribution Worker Epidemiology Study, Am. Ind. Hyg. Assoc. J. 57(4) 333-343, 1996 140. Dodgson, J., J. Cherrie, and S.Groat: Estimates of Past Exposure to Respirable ManMade Mineral Fibres in the European Insulation Wool Industry. Ann. Occup. Hyg. 31(4B):567-582, 1987. 141. Yu, RL., W-Y. Tan, RM. Mathew, D.A. Andjelkovich, and RJ. Levine: A Deterministic Mathematical Model for Quantitative Estimation of Historical Exposure. Am. Ind. Hyg. Assoc. J. 51(4):194-201, 1990. 142. Schneider, T., I. Olsen, O. Jorgensen, and B. Lauersen: Evaluation of Exposure Information. App. Occup. Environ. Hyg. 6(6):475-481, 1991. 143. Ramachandran,G., and Vincent, J.H. A Bayesian Approach to Retrospective Exposure Assessment. Appl. Occ. Envir. Hyg. 14(8):547-57, 1999. 8 ENROLLMENT OF SUBJECTS 8.1 Case Control Study A Inclusion Criteria In-patients of either gender 16-75 years of age presenting at any of the participating referral hospitals in Shanghai are candidates for enrollment in this study. The rationale for this age range is based on a relatively young workforce (18-60) and an expected maximum latency of 15 years 41 SH ELL-MCCLU RG-059759