Choice of study design

A combination of study designs has been used previously to investigate cancer risks among meat workers, i.e. studies based on routinely collected mortality and incidence data, proportionate mortality and incidence studies, and case-control and cohort studies. While increased risks of all cancers, and in particular of cancers of the lung, larynx and

lymphohaematopoietic system have been suggested by these studies, the available evidence is inadequate to conclude either that the risk for any specific cancer is real or to implicate any specific exposure. Of the study designs applied the analyses of routinely collected data [Lynge, 1 982; Fox, 1 982; Griffith, 1 982; Lagorio et aI, 1 995; Morton & Marjanovich, 1 984] were useful in generating hypotheses, but were of limited value in assessing whether there was a true exposure-outcome relationship at an individual level. The measures of proportionate mortality and incidence [Fox, 1 982; Milham, 1 982; lohnson & Fischman, 1 982, lohnson et aI, 1 986a; lohnson et aI, 1 986b; lobnson et aI,

1 987] also need to be interpreted with caution due to the potential biases inherent in such analyses [Checkoway et aI, 1 989] .

For the study of cancer and other diseases of long induction, population-based case­ control studies are usually very efficient, particularly for investigating rare diseases [Breslow & Day, 1 980]. They allow a wide range of exposures that might be related to the disease to be evaluated simultaneously and are, therefore, particularly useful for screening hypotheses regarding occupational exposures that may warrant more intensive inquiry in subsequent industry based studies [Checkoway et aI, 1 989]. Case-control studies have the added benefit of providing the opportunity to obtain detailed information both on the exposure(s) of interest and on potential confounders, but they may be more susceptible to bias and in particular selection bias (e.g. selection of an appropriate control group) and information bias (e.g. accurate measures of past exposures). Furthermore, they are not suitable for investigating exposures that are rare in the source population unless the exposure is responsible for a large proportion of cases. Where the putative exposure is

rare in the general population and is responsible for only a small proportion of the cases of any specific cancer, and where it is possible to identify a specific group with that exposure, the historical cohort study is the most efficient study design for evaluating cancer risk. As multiple health outcomes can be examined, this study design will also provide the clearest picture of the overall health experience of that group [Checkoway et al, 1 989] .

A benefit of the historical cohort study design is that, provided that an appropriate cohort can be identified and that historical exposure information exists, recall bias is eliminated and selection bias is usually minimised. This is because exposure status is ascertained, and because exposed and unexposed individuals are enrolled into the study population, before the outcome of interest has developed. Confounding may still occur due to the so­ called "healthy worker effect", which manifests as lower overall morbidity and mortality in the working population being studied when comparisons are made between an

occupational cohort and the general popUlation. This occurs because only relatively healthy people are able to gain employment, and to remain in employment, whereas the general population includes a wider range of people including those too ill to work [Checkoway et ai, 1 989].

There is, in addition, the potential for information bias (other than recall bias) in historical cohort studies where classification of exposure or outcome is invalid [dos Santos Silva, 1 999]. However, this is likely to involve non-differential misclassification because exposure status is ascertained before the outcome of interest has developed, and

subjects therefore have the same chance of their exposure status being misclassified regardless of their outcome status. This is relatively common in historical cohort studies of occupational groups because, as records of actual measurements of individual

exposure rarely exist, individuals are often categorised as exposed or non-exposed on the basis of surrogate measures such as job title or work area. The use of surrogate measures of exposure such as these, which attribute the same exposure estimate to each individual within the same job title, will introduce (non-differential) misclassification as even workers performing the same job experience significant variability in average exposure levels [Boleij et ai, 1 995]. Where non-differential misclassification of the exposure status of study subjects exists, the risk estimates will be biased toward the null, thereby

underestimating the strength of association between that exposure and outcome

[Copeland et ai, 1 977]. Differential misclassification of exposure on the other hand, which occurs where the classification of exposure status is dependent on the outcome status of individual study subjects and which can bias the risk estimates in either

direction, is less likely in historical cohort studies of occupational cohorts where exposure data is collected on the study population before the outcome is known.

Another limitation of the historical cohort study design is the fact that there is potential for uncontrolled confounding where information on factors such as tobacco smoking is lacking. The potential confounding effect of smoking is often overestimated, however, as differences in smoking rates between groups of manual workers are usually small. Even for lung cancer the differences in smoking status are unlikely to account for a relative risk of greater than 1 .5 in studies involving a comparison with national mortality rates

[Axelson, 1 978], and the confounding effect of smoking is even weaker for internal dose­ response analyses [Siemiatycki et aI, 1 988].

The cohort studies conducted previously to examine cancer risks among meat workers in the USA [Johnson et aI, 1 986a, 1 986b, 1 995], the UK [Coggon et aI, 1 989; Coggon & Wield, 1 995] and in Switzerland [Guberan et aI, 1 993] have been limited primarily by their study size, or in the case of the one large Swedish cohort [Boffetta et aI, 2000] by the relatively crude exposure data based on occupation listed at census. Possibly because of these limitations, these cohort studies have produced results that contradict those of the case-control studies, showing only a small increase in lung cancer risk (albeit within the range that could be attributable to differences in smoking rates) and little evidence of any increase in cancers of the Iymphohaematopoietic system.

As no cohort study of New Zealand meat workers had been done previously, it was considered appropriate to conduct studies here primarily to establish whether the elevated risks for cancers of the lymphohaematopoietic system found in earlier case-control studies could be replicated with this study design, and also to examine the associations between specific exposures and any increased cancer risk. Although the processing of meat and meat products is a significant industry in this country's predominantly

agricultural economy, and is a significant employer with 20,000 people directly employed in meat processing and packing plants, the exposure of interest is still very rare with less than 1 % of the adult population working in this industry. While the earlier New Zealand case-control studies have shown consistently elevated risks for cancers of the

lymphohaematopoietic system [Pearce et aI, 1 985; Pearce et aI, 1 986; Pearce et aI, 1 987; Reif et aI, 1 989] and a clear dose-response [Bethwaite et aI, 200 1 ], these have been based on only small numbers of exposed cases and relied on participants' recall of job titles and exposure.

Historical cohort studies provide the opportunity, therefore, to evaluate the disease experience of a large cohort with known exposure. It also permits the classification of individual study subjects according to exposure based on a work history compiled from historical records, with less potential for information bias than exists with the case­ control study design.

There are also a number of reasons why New Zealand is a good place to do this type of study. Compared with many other countries, the meat processing industry in New

Zealand has a relatively stable workforce with annual turnover of only 1 0 to 1 5%, as well as a relatively stable population for which acceptable rates of follow-up can be achieved. A National Cancer Registry with compulsory registration, first established in 1 948, also provides reliable cancer incidence data for an aetiological study of this type [New

Zealand Health Information Service, 2002] and death registration data are also considered to be valid and virtually complete [Brown & Frankovitch, 1 998]. Two historical cohort studies were, therefore, conducted to examine mortality and cancer incidence, and to investigate associations between disease and a range of exposures, among workers employed in the New Zealand meat processing industry.