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Letters

The article by Booth1 in the December1998 issue of Parasitology Today makes animportant contribution to the field, becauseparasitologists can see how specific epi-demiological methodology can be adaptedinto a familiar context, in this instance, toenhance data analysis and interpretation.To avoid any possible confusion in suchadaptations, it becomes essential to ensurethat correct epidemiological terminology isused. In this regard, it might be helpful topoint out some inconsistencies with epi-demiological terminology. The definitionspresented in Box 2 of Ref. 1, for example,are not strictly the definitions presented in

Last’s Dictionary2 and have been adaptedconsiderably for the very specific applica-tion presented. The term ’randomizedcross-sectional data’ is incorrect; cross-sec-tional data might be obtained from a ran-dom sample of a population, but they arenot randomized. ‘Risk’ and its estimation ismost appropriately obtained from cohortstudies and not from cross-sectional studies.The denominator of PRw should be ∑ ci ei / Niand not ∑ ai ei / Ni.

These examples highlight the challengefacing us all when we incorporate a new, orunfamiliar, specialized vocabulary into ourwork (see Ref. 3). Authors, editors and

reviewers share the responsibility of provid-ing the readership with a vocabulary that iscorrect and current.

References1 Booth, M. (1998) Parasitol. Today 14,

497–5002 Last, J.M. (1988) A Dictionary of Epidemiology

(2nd edn), Oxford University Press3 Rothman, K.J. and Greenland, S. (1998) Mod-

ern Epidemiology (2nd edn), Lippincott-RavenPublishers

Theresa W. GyorkosLawrence JosephDepartment of Epidemiology and BiostatisticsMcGill University, Montreal, Quebec, CanadaH3A 1A2

Helene CarabinWellcome Trust Centre for the Epidemiology ofInfectious DiseaseOxford University, Oxford, UK OX1 3PS

Reply

Theresa Gyorkos and colleagues makeseveral valid points in their letter, and Ithank them for correcting the typographicalerror in the equation of PRw. In addition,they criticize the use of the term ‘risk’, andcorrectly point out that the terminologywas heavily adapted for the situation. Indoing so, they highlight a general problemassociated with terminology of cross-sectional data.

The issue is whether concepts and termsof risk analysis should only be used with

incidence data (which record the numberof cases over a given period of time), or ifthey can also be used when discussingprevalence data (which record the numberof cases at a particular point in time). Thereis often no distinction in the literature,which is not surprising since analyticalmethods for prevalence data are essentiallya special application of methods developedfor cohort studies1. Even Last’s Dictionaryoffers no special terminology for prevalencedata – for example, the term ‘attributablefraction’ is defined only for incidence data2.Thus, the problem lies in having to usemethods in a situation where there is no

suitable terminology, rather thanintroducing unfamiliar terminology into aparticular field of research.

References1 Rothman, K.J. and Greenland, S. (1998)

Modern Epidemiology (2nd edn), Lippincott–Raven Publishers

2 Last, J.M. (1995) A Dictionary of Epidemiology(3rd edn), Oxford University Press

Mark BoothDepartment of Public Health and EpidemiologySwiss Tropical InstituteSocinstrasse 57CH4051 Basel, Switzerland

Further Analysis of Attributable Risk in

Helminth Epidemiology