Premenopausal endogenous oestrogen levels and breast cancer risk: a meta-analysis.

BACKGROUND: Many of the established risk factors for breast cancer implicate circulating hormone levels in the aetiology of the disease. Increased levels of postmenopausal endogenous oestradiol (E2) have been found to increase the risk of breast cancer, but no such association has been confirmed in premenopausal women. We carried out a meta-analysis to summarise the available evidence in women before the menopause. METHODS: We identified seven prospective studies of premenopausal endogenous E2 and breast cancer risk, including 693 breast cancer cases. From each study we extracted odds ratios of breast cancer between quantiles of endogenous E2, or for unit or s.d. increases in (log transformed) E2, or (where odds ratios were unavailable) summary statistics for the distributions of E2 in breast cancer cases and unaffected controls. Estimates for a doubling of endogenous E2 were obtained from these extracted estimates, and random-effect meta-analysis was used to obtain a pooled estimate across the studies. RESULTS: Overall, we found weak evidence of a positive association between circulating E2 levels and the risk of breast cancer, with a doubling of E2 associated with an odds ratio of 1.10 (95% CI: 0.96, 1.27). CONCLUSION: Our findings are consistent with the hypothesis of a positive association between premenopausal endogenous E2 and breast cancer risk

Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort

Correction to Banks E, Jorm L, Lujic S, Rogers K. Health, ageing and private health insurance: baseline results from the 45 and Up Study cohort. ANZ Health Policy 2009; 6: 16

Geographical classifications to guide rural health policy in Australia

The Australian Government's recent decision to replace the Rural Remote and Metropolitan Area (RRMA) classification with the Australian Standard Geographical Classification - Remoteness Areas (ASGC-RA) system highlights the ongoing significance of geographical classifications for rural health policy, particularly in relation to improving the rural health workforce supply. None of the existing classifications, including the government's preferred choice, were designed specifically to guide health resource allocation, and all exhibit strong weaknesses when applied as such. Continuing reliance on these classifications as policy tools will continue to result in inappropriate health program resource distribution. Purely 'geographical' classifications alone cannot capture all relevant aspects of rural health service provision within a single measure. Moreover, because many subjective decisions (such as the choice of algorithm and breakdown of groupings) influence a classification's impact and acceptance from its users, policy-makers need to specify explicitly the purpose and role of their different programs as the basis for developing and implementing appropriate decision tools such as 'rural-urban' classifications. Failure to do so will continue to limit the effectiveness that current rural health support and incentive programs can have in achieving their objective of improving the provision of health care services to rural populations though affirmative action programs