Determinants of inequalities in cervical cancer stage at diagnosis and survival in New Zealand
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The aim of this study is to assess whether ethnic inequalities in cervical cancer mortality are due to differences in survival independent of stage and age at diagnosis, and to assess the contribution of screening to stage at diagnosis.
Demographic data and cervical screening history were collected for 402 women with histologically proven primary invasive cervical cancer, diagnosed in New Zealand between 1 January 2000 and 30 September 2002. Date of death was available for women who died up to 30 September 2004.
A Cox proportional hazard model showed that, after adjusting for age, the Māori mortality rate was 1.80 times (95% CI 1.07–3.04) that of non-Māori. This reduced to 1.25 (95% CI 0.74–2.11) when stage at diagnosis was also adjusted for. Among determinants of late stage at diagnosis, older age and being Māori significantly increased the risk, while screening was protective.
These results indicate that later stage at diagnosis is the main determinant of Māori women’s higher mortality from cervical cancer. Improving cervical screening among Māori women would reduce stage at diagnosis and therefore ethnic inequalities in mortality.
KeywordsHealth status disparities Cervical cancer Survival
This study uses data from the New Zealand Cervical Cancer Audit, which was funded by the New Zealand Ministry of Health (MoH) and carried out as a partnership between the MoH and UniServices Ltd, University of Auckland. The authors thank Drs Charlotte Paul, Brian Cox and Mary-Jane Sneyd for helpful comments on earlier drafts of this article; Ruth Herbert and Dr. William Rainger who managed the project; Sandra Coney, Dr. Peter Bethwaite, Dr. Gabriele Medley, and Harold Neal who provided expert advice to the project; Rachel Brown, Claire Macdonald, Orewa Barrett-Ohia, Charlotte Bergman, and Rhondda Kerins who performed the interviews; and Catherine Dick, Stephanie Smith, Kirstine Sutton, and Sarah Sparks who abstracted the medical records data.
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