The effect of modifiable risk factors on geographic mortality differentials: a modelling study

Stevenson, Christopher E., Mannan, Haider, Peeters, Anna, Walls, Helen, Magliano, Dianna J., Shaw, Johnathan E., and McNeil, John J. (2012) The effect of modifiable risk factors on geographic mortality differentials: a modelling study. BMC Public Health, 12. 79. pp. 1-14.

[img]
Preview
PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (382kB) | Preview
View at Publisher Website: http://dx.doi.org/10.1186/1471-2458-12-7...
 
8
1163


Abstract

Background: Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown.

Methods: We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy.

Results: Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%.

Conclusions: These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

Item ID: 35537
Item Type: Article (Research - C1)
ISSN: 1471-2458
Additional Information:

© 2011 Stevenson et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Funders: Commonwealth Department of Health and Aged Care, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, AstraZeneca, Aventis Pharmaceutical, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly (Australia) Pty Ltd, GlaxoSmithKline, Janssen-Cilag (Australia) Pty Ltd, Merck Lipha s.a., Merck Sharp & Dohme (Australia), Novartis Pharmaceutical (Australia) Pty Ltd, Novo Nordisk Pharmaceutical Pty Ltd, Pharmacia and Upjohn Pty Ltd, Pfizer Pty Ltd, Roche Diagnostics, Sanofi Synthelabo (Australia) Pty Ltd, Servier Laboratories (Australia) Pty Ltd, BioRad Laboratories Pty Ltd, HITECH Pathology Pty Ltd, Australian Kidney Foundation, Diabetes Australia, Diabetes Australia Northern Territory, Queensland Health, South Australian Department of Human Services, Tasmanian Department of Health and Human Services, Territory Health Services, Victorian Department of Human Services, Health Department of Western Australia, National Health and Medical Research Council (NHMRC)
Projects and Grants: NHMRC grant no. 465130
Date Deposited: 16 Oct 2014 23:57
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 50%
01 MATHEMATICAL SCIENCES > 0104 Statistics > 010402 Biostatistics @ 50%
SEO Codes: 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920499 Public Health (excl. Specific Population Health) not elsewhere classified @ 100%
Downloads: Total: 1163
Last 12 Months: 93
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page