Cunningham et al. BMC Cancer 2010, 10:674 http://www.biomedcentral.com/1471-2407/10/674 amongst Māori women may also be an important factor in this change. Finally, it is important to note that breast cancer mor- tality differences between Māori and non-Māori remain more significant [26] and are more likely to be amenable to intervention than incidence differences, and so should remain a central concern of researchers and policy makers. Socioeconomic trends The pattern of higher breast cancer rates amongst women of higher socioeconomic status seen here is con- sistent with that found internationally [60-62], and is likely to be primarily due to differences in reproductive behaviour. Socioeconomic differences in reproductive behaviour, including differences in parity, age at first birth, childlessness, and the duration of breast feeding, are seen in almost all settings internationally [12]. In New Zealand there are significant fertility differentials by level of education, with women with the highest level of education having the fewest children, and this differ- ence is greatest in women born more recently indicating an increasing socioeconomic differentiation in reproduc- tive behaviour [63]. It is possible that over time this will result in widening of differentials in breast cancer rates between socioeconomic groups in New Zealand. Screen- ing uptake and HT use have also been socioeconomi- cally patterned, with higher uptake amongst better off women [64], and this will contribute to the difference in incidence seen. HT use in New Zealand declined mark- edly following the publication of the results of the Women’s Health Initiative trial in 2002 [65], and this is likely to have reduced the difference in the last time period by socioeconomic status. Strengths and Limitations This study is a series of five short-duration cohort stu- dies of the entire New Zealand population, followed up for breast cancer over a 24 year period. By using data from the entire New Zealand (census night) population as well as data from New Zealand’s population based cancer registry, it was possible to overcome numerator/ denominator bias and misclassification of ethnicity and socioeconomic group. Self identified ethnic affiliation from census forms was used to define the numerator and denominator populations, and therefore produce more reliable estimates of differences between ethnic groups. Individual measures of socioeconomic position were also able to be used rather than relying on area- based measures. Considering trends over 24 years also provides a good basis for understanding evolving differ- ences between population groups. However the study is not without limitations. Statisti- cal imprecision becomes a problem when stratifying by Page 8 of 10 ethnicity or socioeconomic position. This is particular problem for the Asian and Pacific groups where num- bers are small. It was not possible to link all cancer records back to the census, and so weighting for linkage bias was undertaken; we are confident that this will have eliminated most bias due to misclassification of out- come. The Cancer Registry Act, which came into effect in 1995, required mandatory registration of all cancers, and there may have been a small artefactual increase in breast cancer registrations following its introduction, but this is not thought to have a had a major effect on breast cancer rates and probably impacted ethnic groups and income groups in a similar manner. Household income is presented as an indicator of individual socioeconomic status. While education mea- sures socioeconomic status closer to the time of repro- ductive choices which are important for breast cancer risk, more proximal exposures such as post menopausal obesity, screening, and HT use are also important for breast cancer risk and so both measures are relevant. Education also lacks discriminatory power in older women in the earlier cohorts, as the majority of these women fall into the category of no qualifications. As similar results were found for both education and household income a decision was made to only present the results for household income in this paper. Finally, the lack of good information about risk factor distribution in the population, particularly in the rele- vant time period, makes it difficult to fully interpret the differences found between ethnic and socioeconomic groups; rather, these breast cancer rates over time might provide clues about unmeasured risk factors back in time. Conclusions Patterns of breast cancer incidence in Pacific women and between socioeconomic groups are probably explic- able in terms of the known risk factors for breast cancer. However no straightforward explanation for the relatively high incidence amongst Māori is apparent. Biological explanations put forward for unexpectedly high rates amongst Hawaiian women may provide a clue, but little is known about biological differences in breast tumours or risk factors between Māori and non- Māori and much more work needs to be done in this area. Even if underlying biological or genetic differences explain some of the difference in rates, the faster increase in rates amongst Māori women may in fact be the result of changes in risk factor distribution. Further research should focus on the role of known and new risk factors and the biological characteristics of breast tumours as determinants of the pattern of breast cancer incidence amongst Māori women. It may be that the currently inexplicable differences between Māori