Geographic remoteness, area-level socioeconomic disadvantage and breast cancer: a multilevel study — ASN Events
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  3. Geographic remoteness, area-level socioeconomic disadvantage and breast cancer: a multilevel study

Geographic remoteness, area-level socioeconomic disadvantage and breast cancer: a multilevel study (#761)

Peter D Baade 1 2 3 , Paramita Dasgupta 1 , Gavin Turrell 2 , Joanne F Aitken 1 2 3
  1. Cancer Council Queensland, Fortitude Valley, QLD, Australia
  2. Queensland University of Technology, Brisbane, QLD, Australia
  3. Griffith University, Gold Coast, Queensland, Australia

Aims: Although significant geographical variations in both breast cancer stage and survival have been reported, few studies have analysed the independent contribution of area- and individual-level factors to these variations. Here we describe the relationship that geographic remoteness and area disadvantage have on stage at diagnosis and survival after diagnosis with invasive breast cancer while controlling for individual-level characteristics.

Methods: Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze 18,568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30 to 70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas. Maximum follow-up was to 31 December, 2007.

Results: Independently of individual-level factors, women living in the most disadvantaged areas had an increased risk of being diagnosed with advanced disease (OR 1.21, 95% CI 1.07-1.37, p=0.002) and poorer survival (OR 1.23, 1.27, 1.30, 1.37 for Quintiles 4, 3, 2 and 1 respectively, p=0.032) compared to women from least disadvantaged area (Quintile 5). After full adjustment, women from outer regional (OR 1.13, 95% CI 1.02-1.24) or most disadvantaged areas (OR 1.16, 95% CI 1.02-1.32) had significantly higher (p<0.001) risks of advanced disease. However geographic remoteness was not associated with lower survival (p=0.366) after multivariate adjustment. There was also no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual level, being Indigenous and having blue collar occupations were important predictors of advanced disease and poorer survival.


Conclusions: Both a woman’s risk of being diagnosed with advanced disease and her survival after invasive breast cancer depend on where she lives, independently of her individual characteristics. The underlying reasons for these inequalities must be identified and barriers to early diagnosis of breast cancer addressed to reduce existing inequalities in breast cancer survival