Multilevel determinants of breast cancer survival: association with geographic remoteness and area-level socioeconomic disadvantage
- First Online:
- Cite this article as:
- Dasgupta, P., Baade, P.D., Aitken, J.F. et al. Breast Cancer Res Treat (2012) 132: 701. doi:10.1007/s10549-011-1899-y
- 469 Views
A major priority for cancer control agencies is to reduce geographical inequalities in cancer outcomes. While the poorer breast cancer survival among socioeconomically disadvantaged women is well established, few studies have looked at the independent contribution that area- and individual-level factors make to breast cancer survival. Here, we examine relationships between geographic remoteness, area-level socioeconomic disadvantage and breast cancer survival after adjustment for patients’ socio-demographic characteristics and stage at diagnosis. Multilevel logistic regression and Markov chain Monte Carlo simulation were used to analyze 18,568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30–70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas in Queensland, Australia. Independent of individual-level factors, area-level disadvantage was associated with breast cancer survival (P = 0.032). Compared to women in the least disadvantaged quintile (quintile 5), women diagnosed while resident in one of the remaining four quintiles had significantly worse survival (OR 1.23, 1.27, 1.30, 1.37 for quintiles 4, 3, 2, and 1, respectively). Geographic remoteness was not related to lower survival after multivariable adjustment. There was no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual-level, Indigenous status, blue collar occupations and advanced disease were important predictors of poorer survival. A woman’s survival after a diagnosis of breast cancer depends on the socio-economic characteristics of the area where she lives, independently of her individual-level characteristics. It is crucial that the underlying reasons for these inequalities be identified to appropriately target policies, resources and effective intervention strategies.