Cancer survival in New Zealand: ethnic, social and geographical inequalities.
This study investigated the combined effects of ethnicity, deprivation and geographical access to health services on the likelihood of survival from a range of common cancers in New Zealand. Individual cancer registry records of 99,062 cases of melanoma, colorectal, lung, breast and prostate cancers diagnosed in the period 1994-2004 were supplemented with small area information on social deprivation and estimates of travel time to the nearest primary care and cancer centre. Logistic regression was used to identify the variables associated with advanced extent of the disease at diagnosis. Adverse influences on survival were investigated using Cox proportional hazards models. Controlling for age and gender, Māori and Pacific peoples' ethnicity was strongly associated with poorer survival, partly because ethnicity was also linked to the likelihood of advanced disease at diagnosis. Living in a deprived area was related to later stage presentation and poorer survival of people with melanoma, but there was no other evidence that living in a deprived area or in a remote location were associated with later stage presentation. Some disease-specific trends in survival were observed. Colorectal and lung cancers were more likely to be fatal for people living in deprived areas, survival from prostate cancer was poor for men living remote from primary care, and people with colorectal, breast and prostate cancers had adverse survival chances if they lived distant from a cancer centre.
School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom. r.haynes@uea.ac.uk
Robin
R
Haynes
Jamie
J
Pearce
Ross
R
Barnett
D000368:Aged; D005260:Female; D006297:Health Services Accessibility; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000208:ethnology* / Q000401:mortality*; D009520:New Zealand / Q000453:epidemiology; D016017:Odds Ratio; D011204:Poverty Areas; D016016:Proportional Hazards Models