In epidemiology and demography, age adjustment, also called age standardization, is a technique used to allow statistical populations to be compared when the age profiles of the populations are quite different.
Example
editFor example, in 2004/5, two Australian health surveys investigated rates of long-term circulatory system health problems (e.g. heart disease) in the general Australian population, and specifically in the Indigenous Australian population. In each age category over age 24, Indigenous Australians had markedly higher rates of circulatory disease than the general population: 5% vs 2% in age group 25–34, 12% vs 4% in age group 35–44, 22% vs 14% in age group 45–54, and 42% vs 33% in age group 55+.[1]
However, overall, these surveys estimated that 12% of all Indigenous Australians had long-term circulatory problems[1] compared to 18% of the overall Australian population.[2]
Standard populations
editIn order to adjust for age, a standard population must be selected. Some agencies which produce health statistics also publish standard populations for age adjustment. Standard populations have been developed for specific countries[3] and regions.[4] World standard populations have also been developed to compare data from different countries, including the Segi World Standard and the World Health Organization (WHO) standard.[5] These agencies must balance between setting weights which may be used over a long period of time, which maximizes comparability of published statistics, and revising weights to be close to the current age distribution. When comparing data from a specific country or region, using a standard population from that country or region means that the age-adjusted rates are similar to the true population rates.[6] On the other hand, standardizing data using a widely used standard such as the WHO standard population allows for easier comparison with published statistics.
See also
edit- Controlling for a variable – Binning data according to measured values of the variable
- Simpson's paradox – Error in statistical reasoning with groups
References
edit- ^ a b "National Aboriginal and Torres Strait Islander Health Survey" (PDF). Australian Bureau of Statistics. 2006. Retrieved 2009-01-12.
- ^ "National Health Survey: Summary of results" (PDF). Australian Bureau of Statistics. 2006. Retrieved 2009-01-12.
- ^ Shalala, D.E. (August 26, 1998). "Policy statement on changing the population standard used for age adjusting death rates in DHHS publications". Retrieved May 24, 2014.
- ^ Pace, M.; G. Lanzieri; M. Glickman; E. Grande; T .Zupanic; B. Wojtyniak; M. Gissler; E. Cayotte; et al. (2013). Revision of the European Standard Population (PDF) (Technical report). Methodologies and Working papers. Eurostat.
- ^ Ahmad, O.B.; C. Boschi-Pinto; A.D. Lopez; C.J.L. Murray; R. Lozano; M. Inoue (2001). AGE STANDARDIZATION OF RATES: A NEW WHO STANDARD (PDF) (Technical report). GPE Discussion Paper Series: No.31. World Health Organization (WHO).
- ^ Wyper GM, Grant I, Fletcher E, McCartney G, Fischbacher C, Stockton DL (2020). "How do world and European standard populations impact burden of disease studies? A case study of disability-adjusted life years (DALYs) in Scotland". Archives of Public Health. 78 (1): 1. doi:10.1186/s13690-019-0383-8. PMC 6941317. PMID 31908777.
Further reading
edit- Lee WC; Liaw YP (October 1999). "Optimal weighting systems for direct age-adjustment of vital rates". Stat Med. 18 (19): 2645–54. doi:10.1002/(SICI)1097-0258(19991015)18:19<2645::AID-SIM184>3.0.CO;2-Q. PMID 10495462.