Computational Methods in Official Statistics with an Example on Calculating and Predicting Diabetes Mellitus [DM] Prevalence in Different Age Groups within Australia in Future Years, in Light of the Aging Population
Authors: D. Hilton
Abstract:
An analysis of the Australian Diabetes Screening Study estimated undiagnosed diabetes mellitus [DM] prevalence in a high risk general practice based cohort. DM prevalence varied from 9.4% to 18.1% depending upon the diagnostic criteria utilised with age being a highly significant risk factor. Utilising the gold standard oral glucose tolerance test, the prevalence of DM was 22-23% in those aged >= 70 years and <15% in those aged 40-59 years. Opportunistic screening in Australian general practice potentially can identify many persons with undiagnosed type 2 DM. An Australian Bureau of Statistics document published three years ago, reported the highest rate of DM in men aged 65-74 years [19%] whereas the rate for women was highest in those over 75 years [13%]. If you consider that the Australian Bureau of Statistics report in 2007 found that 13% of the population was over 65 years of age and that this will increase to 23-25% by 2056 with a further projected increase to 25-28% by 2101, obviously this information has to be factored into the equation when age related diabetes prevalence predictions are calculated. This 10-15% proportional increase of elderly persons within the population demographics has dramatic implications for the estimated number of elderly persons with DM in these age groupings. Computational methodology showing the age related demographic changes reported in these official statistical documents will be done showing estimates for 2056 and 2101 for different age groups. This has relevance for future diabetes prevalence rates and shows that along with many countries worldwide Australia is facing an increasing pandemic. In contrast Japan is expected to have a decrease in the next twenty years in the number of persons with diabetes.
Keywords: Epidemiological methods, aging, prevalence.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1096415
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[1] T. A. Welborn, C. M. Reid, and G. Marriott, "Australian diabetes screening study; impaired glucose intolerance and non-insulin dependent diabetes mellitus,” Metabolism, vol. 46, Suppl 1, pp. 35-39, 1997.
[2] D. Hilton, P. K. O’Rourke, T. A. Welborn, and C. M. Reid, "Diabetes detection in Australian general practice – a comparison of diagnostic criteria,” Medical Journal of Australia, vol. 176, pp. 104-107, 2002.
[3] International Diabetes Federation. Diabetes Atlas, 6th ed., Brussels, Belgium: International Diabetes Federation; 2013.
[4] G. Danaei, M. M. Finucane, Y. Lu, G. M. Singh, M. J. Cowan, C. J. Paciorek, et al, "National, regional and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants,” Lancet, vol. 378, pp. 31-40, 2011.
[5] D. R. Whiting, L. Guariguata, C. Weil, J. Shaw. "IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030,” Diabetes Research and Clinical Practice, vol. 94, pp. 311-321, 2011.
[6] D. W. Dunstan, P. Z. Zimmet, T. A. Welborn, M. P. De Courten, A. J. Cameron, R. A. Sicree et al, "The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study,” Diabetes Care, vol. 25, pp. 829-834, 2002.
[7] D. Trewin, Australian Bureau of Statistics, "Population Projections. 1999 – 2101,” ABS catalogue number 3222.0. Canberra: Commonwealth of Australia, 2000.
[8] Australian Bureau of Statistics, "Population Projections. 2012 (base) – 2101,” ABS catalogue number 3222.0. Canberra: Commonwealth of Australia, 2000.
[9] A. J. Cameron, T. A. Welborn, P. Z. Zimmet, D. W. Dunstan, N. Owen, J. Salmon et al, "Overweight and obesity in Australia: the 1999-2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab),” Medical Journal of Australia, vol. 178, pp. 427-432, 2003.
[10] Microsoft Office. Microsoft EXCEL. Redmond; Washington, 2013.
[11] L. Guariguata, D. R. Whiting, I. Hambleton, J. Beagley, U. Linnenkamp and J. E. Shaw, "Global estimates of diabetes prevalence for 2013 and projections for 2035,” Diabetes Research and Clinical Practice, vol. 103, pp. 137-149, 2014.