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the impression that the techniques and methodsdescribed are suIcient for an analysis. As anexample, the authors spend some time discussingnormality of the data, whereas the much morecritical assumption in ANOVA, that the variancesin subgroups are the same, is barely mentioned.In chapter 11, the EM algorithm is described asjust another, among many described, imputationmethod where estimates predicted from a regres-sion analysis is imputed for the missing data. Thisis only true for a very restricted class of exponentialfamily models. The Mantel–Haenszel techniqueto address diBerential item functioning, describedin chapter 6, has remained almost unnoticed inmedical statistics but is in my opinion the singlemost important tool in scale validation. In thebook it is not described in such a way that a new-comer would grasp its importance. Furthermore, itis described as if it were only relevant in connec-

tion with item response theory where, in fact, it is anon-model-based general technique with applica-tions for all types of data, for example, continuous,ordinal and non-ordinal categorical data.In conclusion, the authors have succeeded in

writing a book that covers a variety of impor-tant subjects and that gives excellent motivationand informal explanations. Despite my reserva-tions about the technical parts, I would certainlyrecommend this book as a Crst book on assessingquality of life measures.

JTRGEN HOLM PETERSENDepartment of BiostatisticsUniversity of Copenhagen

Blegdamsvej 3DK-2200 Copenhagen N

Denmark

6. HUMAN VARIABILITY IN RESPONSE TO CHEMICALEXPOSURES. David Neumann and Carole Kimmel,ILSI Life Sciences Institute, CRC Press, 1998. No.of pages: 304. Price: $99.95. ISBN 0-8493-2805-5

This edited volume addresses an important andtimely issue, namely how variability in human sus-ceptibility to disease should be reJected in envi-ronmental risk assessment. While it has long beenrecognized that humans diBer substantially with re-spect to their response to chemical and biologicalexposures, this variability is not explicitly reJectedin the setting of regulatory standards. Rather, it isgenerally hoped that even the most sensitive in-dividuals will be automatically protected throughthe naturally conservative assumptions built intothe risk assessment process, for example, applica-tion of safety and uncertainty factors in the settingof regulatory standards. To address these issues,the International Life Sciences Institute (ILSI), inpartnership with several U.S. government agenciesand organizations, formed a task force of expertsfrom industry, government and academia to reviewthe state of knowledge in the area and to makerecommendations and suggestions about future re-search needs. This volume represents the reportsfrom those experts.

The editors, Neumann and Kimmel, are goodwriters. Although neither are trained statisticians,their preface to the book and several chapters writ-ten by them show an impressive intuition for prob-abilistic thinking. The opening chapters, in par-ticular, argue convincingly for the role of human

variability in genetic make-up, social and phys-ical behavioural, as well as behavioural factorsin explaining observed variability in the dose re-sponse setting. Recent advances in medical re-search have opened the way to measuring a hugearray of biomarkers that can be helpful in quan-tifying this variability. For example, certain ge-netic polymorphisms are now known to play asigniCcant role in determining whether or not asmoker will develop lung cancer. Scientists canalso measure DNA adducts (basically, these arefragments of DNA bound to chemicals to whicha person has been exposed), which can indicate asusceptibility to developing certain types of can-cer. While work related to the measurement ofbiomarkers has forged ahead in recent years, therehas been relatively little progress in determininghow this information might be used formally forthe purpose of environmental risk assessment. Byreviewing the present state of knowledge regard-ing the factors that inJuence variability in humansusceptibility to disease, it was hoped that thisbook might serve to stimulate research along theselines.In chapter 1, Grassman, Kimmel and Neumann

review traditional risk assessment practices anddiscuss in general terms the likely impact of pop-ulation response heterogeneity. A more detailedargument is given by Hattis in chapter 2, where theemphasis is on a review of available strategies forquantifying human variability and incorporatingthese ideas into dose–response modelling. Whilesome of these strategies involve familiar ideas

Copyright ? 2001 John Wiley & Sons, Ltd. Statist. Med. 2001; 20:2209–2217

BOOK REVIEWS 2217

(for example, the idea of tolerance distributions asa way of generating dose–response models for bi-nary outcome data), there are some interesting newconcepts presented as well. One idea with particu-lar potential is that of using intermediate variablesto better characterize dose–response relationships.Such ideas have been developed in the context ofclinical trials (for example, use of CD4 counts instudies of AIDS), but not in the environmentalCeld. The next Cve chapters focus on what mightbe considered as case studies focused on speciCcdisease groupings. Eckerman, Glowa and Angerconsider human variability in response to neuro-toxicants such as alcohol and lead, while Scialliand Lione focus on reproductive and developmen-tal toxicity. Both these areas have in common thecomplication of considering factors such as timingof exposure, an issue that is particularly criticalfor the developing organism. In an interestingchapter on respiratory health, Bromberg considersthe challenging question of how to take accountof factors such as the intensity of exposure, aswell as biological factors such as breathing ratesand lung capacity in characterizing the risk asso-ciated with exposure to ozone. Two chapters aredevoted to cancer. Frame, Ambrosone, Kadlubarand Lang address the topic of how genetic fac-tors can interact with environmental exposures tomake certain individuals particularly susceptibleto developing cancer. This excellent chapter pro-vides a very accessible overview of many complexideas and terms that arise often in the geneticepidemiology literature. The chapter also givessome clear explanations of some of the populartheories regarding the role of enzymes associatedwith various genes (for example, the cytochromeP-450 drug-metabolizing enzymes, or CYPs) inmediating environmentally caused cancers. Thechapter by Caporaso and Rothman also dealswith genetic susceptibility and cancer, though the

emphasis here is primarily on heritable risk andassociated study designs. The concluding chapterpulls together many of the ideas touched on inother chapters and attempts to address a series oftargeted questions related to impact of human vari-ability on risk assessment. Predictably, the themeemerging from this Cnal chapter is that if character-izing human variability is hard, Cguring out how touse this information for risk assessment purposesis even harder. The chapter does a good job, how-ever, of summarizing where the knowledge gapsare, and outlining an agenda for future research inthis important area.Because it addresses a highly specialized topic,

this book is not for everyone. However, it providesa wealth of information useful for academics, re-searchers and practitioners in the Celd of risk as-sessment. For the statistician interested in method-ology related to risk assessment, the volume canprovide invaluable insight into the way toxicol-ogists and risk assessors think about populationversus individual risk and susceptibility. Becausethe contributors are not primarily trained in statis-tics, technical formulations and details are weak inplaces. Furthermore, the book suBers from some ofthe problems characteristic of edited volumes, forexample, some redundancy from chapter to chap-ter and variations in writing quality and style. De-spite these weaknesses, the astute reader will Cndthat this provocative book can generate many in-teresting new ideas and provides perfect fodder forcreative thinking on new statistical methodologyfor environmental risk assessment.

LOUISE RYANDepartment of Biostatistics

Harvard School of Public HealthRoom 409, Building 2

655 Huntington AvenueBoston; MA 02115, U.S.A.

Copyright ? 2001 John Wiley & Sons, Ltd. Statist. Med. 2001; 20:2209–2217