The ALSWH is a longitudinal study of factors affecting the health and well-being of three national cohorts of women who were born in 1973-78, 1946-51, and 1921-26. The women were selected randomly from the national Medicare health insurance database (which includes all citizens and permanent residents of Australia), with intentional over-sampling of women living in rural and remote areas. In 1996, more than 40 000 women responded to the initial survey; they were reasonably representative of the general population of Australian women in each age group, although compared with data from the 1996 Australian Census there was over-representation of women who were born in Australia, employed and had a university education . More details about the study can be found at http://www.alswh.org.au. Ethical clearance for the study was obtained from the Universities of Newcastle and Queensland.
This paper focuses on the 12 432 women in the 1921-26 cohort who participated in the baseline survey in 1996. Although these women had a nominal age range of 70 to 74 years when the sample was selected, 5% of women were aged 75 years. Due to the small number of participants from the Northern Territory this jurisdiction is not included in the State/Territory comparisons.
Using personal identifying information provided by the participants, vital status was ascertained by probabilistic linkage to the National Death Index (NDI) for all participants from baseline (1996) to 31 October 2008 . The expected mortality of the study population was ascertained using annual life tables produced by the Australian Bureau of Statistics (ABS) for each State and Territory of Australia .
National Health Survey
The Australian National Health Survey (NHS) is conducted periodically by trained interviewers from the ABS. In addition to demographic information, the survey provides detailed information about the health status of Australians; their use of health services, facilities, and medications; and health-related aspects of their lifestyle. It consists of a representative sample of residents of private and non-private dwellings in all States and Territories, but excludes special dwellings such as hospitals, institutions, and nursing homes.
The 1995 NHS was conducted during the 12-month period of January 1995 to January 1996. It comprised about 23 800 households, representing approximately 57 600 persons . A total of 894 women aged 70 to 74 years (i.e., women born in 1921-25) participated in the 1995 NHS. Using unit record data supplied by the ABS, these women were compared against the ALSWH cohort participants at the first survey for selected characteristics .
Relative survival analysis
Relative survival - the ratio of survival observed in the study sample to the survival to that it should have experienced - can be calculated based on the life table of the population from which it was drawn . In this instance, the study sample was those ALSWH participants born in 1921-26 and the reference population was all Australian women of the same age and State or Territory of residence. It was assumed that the expected mortality experienced by the study sample during a particular period would be the same as mortality in the general population of the same sex, age, and State or Territory of residence from which they are drawn. The Ederer II method was used to calculate interval-specific relative survival .
Firstly the population (L) at the start of each interval in each birth cohort and the number of deaths (D) and those lost to follow-up (W) during the interval were determined. From this information, both the population at risk (L') and interval-specific survival (P) were estimated by assuming withdrawals and deaths were evenly distributed over the interval via the formulae:
The cumulative survival (CP) for a particular interval (i) was then obtained by the cumulative product of the interval-specific survival terms where the initial cumulative survival (CP(0)) was equal to one, and:
The expected interval-specific and expected cumulative survival (P* and CP*) were calculated similarly, using expected deaths (D*) obtained from appropriate life tables. Finally the interval-specific and cumulative relative survival ratios (R and CR) were calculated as the ratios of the observed and expected interval-specific and cumulative survivals:
The effect of oversampling women in rural and remote areas in the ALSWH was accounted for via the use of sampling weights, wherein individual weighted deaths both observed and expected were summed to derive the survival estimates.
Separate analyses were carried out for each State and Territory of residence, each category of the Accessibility/Remoteness Index of Australia (ARIA) classification , and initial age in years. ARIA categorises areas as 'highly accessible', 'accessible', 'moderately accessible', 'remote' and 'very remote' based on the road distance from the closest service centre. Relative survival was calculated using SAS macros created by Paul Dickman .
Comparison to NHS
Selected demographic, health behaviour, and health status characteristics of the ALSWH sample were compared to those of participants of the 1995 NHS of the same age in order to explore possible reasons for observed differences in survival. These comparisons were presented as percentages and analysed using the χ2 statistic.
Effects of factors associated with mortality
A proportional hazards model was used in order to assess the effects of initial differences in potential factors associated with mortality between the study sample and the population [12
]. The model was of the form:
where λi(a, s, zi(a)) is the death intensity at age a and State/Territory (s) for the ith individual with covariates zi(a) and λ*i(a, s) represent the population mortality at age a for an individual of the same sex and State/Territory as the ith individual in the study who is born in the same year as i. The State and Territory specific life tables  were used to obtain values for λ*i(a, s).
A multiplicative model was used because in the more widely used additive model it is assumed that, at all times and for all values of covariates, the mortality in the study sample is always either higher or lower than that of the general population. This assumption was not justifiable in this context. The effect of oversampling in rural areas was accounted for by including place of residence as it was defined in the original sample (urban, rural and remote) as a covariate in the model. Factors considered in this analysis were based on the results of a previous study of the survival of this cohort . These factors included were: age, marital status, country of birth, State or Territory of residence, Accessibility/Remoteness Index (ARIA), education, smoking status, physical activity, body mass index and self rated health. The proportional hazards model was conducted using the SAS PHREG procedure; a hazard ratio of less than one indicates better relative survival. All analyses were performed using SAS version 9.1 .