Abstract This paper will highlight current evidence about health and well-being that could encourage investment in health for older populations. The paper uses the example of hypertension throughout to illustrate how data collection efforts are translating research to policy. Hypertension, is a global scourge for poor and wealthy, younger and older adults, increasing the risk of stroke and cardiovascular disease. Although it is easily diagnosed and can be effectively treated the burden of hypertension continues to grow as awareness, prevention and treatment lags, particularly for the poor and old. The focus is brought back to how current research can inform policy for ageing populations in the final section, using Ireland's experience to demonstrate how to legislate the good life for older adults.
IntroductionThe cancer burden preventable through modifications to risk factors can be quantified by calculating their population attributable fractions (PAFs). PAF estimates require large, prospective data to inform risk estimates and contemporary population-based prevalence data to inform the current exposure distributions, including among population subgroups.
Objectives and ApproachWe provide estimates of the preventable future cancer burden in Australia using large linked datasets. We pooled data from seven Australian cohort studies (N=367,058) and linked them to national registries to identify cancers and deaths. We estimated the strength of the associations between behaviours and cancer risk using a proportional hazards model, adjusting for age, sex, study and other behaviours. Exposure prevalence was estimated from contemporary National Health Surveys. We harmonised risk factor data across the data sources, and calculated PAFs and their 95% confidence intervals using a novel method accounting for competing risk of death and risk factor interdependence.
ResultsDuring the first 10-years follow-up, there were 3,471 incident colorectal cancers, 640 premenopausal and 2,632 postmenopausal breast cancers, 2,025 lung cancers and 22,078 deaths. The leading preventable causes were current smoking (53.7% of lung cancers), body fatness or BMI ≥ 25kg/m2 (11.1% of colorectal cancers, 10.9% of postmenopausal breast cancers), and regular alcohol consumption (12.2% of premenopausal breast cancers). Three in five lung cancers, but only one in four colorectal cancers and one in five breast cancers, were attributable to modifiable factors, when we also considered physical inactivity, dietary and hormonal factors. The burden attributable to modifiable factors was markedly higher in certain population subgroups, including men (colorectal, lung), people with risk factor clustering (colorectal, breast, lung), and individuals with low educational attainment (breast, lung).
Conclusion/ImplicationsEstimating PAFs for modifiable risk factors across cancers using contemporary exposure prevalence data can inform timely public health action to improve health and health equity. Testing PAF effect modification may identify population subgroups with the most to gain from programs that support behaviour change and early detection.
