Epidemiology Measuring Disease Burden
Questions:
Answers:
1. Standardization is useful while measuring disease burden in one population or comparing between populations. Standardizing the rate is helpful when comparing rates between populations as it helps removes the potential confounders such as age factors that differ between population. Thus, standardization is a measure of disease frequency that promotes comparison of epidemiology in different population along with various confounding variables (Keiding & Clayton, 2014).
2. Standardization rate is applied in epidemiological research to overcome the effect of confounding variables such as control for age. Comparing mortality and morbidity rates in two or different countries is essential for the evaluation of health status of a community. Crude rates of population measure give misleading data as there is a chance of different frequency distributions in a diverse population. In this situation, standardization rates are useful as it makes population characteristics standard (Lopez & Mathers, 2013).
3. A crude rate is calculated based on population under study as a whole while the standardized rate in calculated on particular characteristics as a standard. In epidemiology, knowing the incidence of disease or mortality rate between two or more population is essential.
Comparison of crude mortality rate is often misleading because of demographic characteristics such as age or sex in that influences the overall morbidity rate. For example, two Australian health surveys investigated the rates of the long-term cardiovascular problem in the Australian population. In this case, age characteristics differ for indigenous and n0n-indegenous Australians. In this situation age, standardization is a useful technique to allow populations to be compared when age profiles of the population differ. Age is an important determinant of mortality, and crude rates may be affected by population distribution due to age characteristics. Thus, standardization helps in confounding age variable and comparing age-specific rates (Moran et al., 2014).
References
Keiding, N., & Clayton, D. (2014). Standardization and control for confounding in observational studies: a historical perspective. Statistical Sc
Lopez, A. D., & Mathers, C. D. (2013). Measuring the global burden of disease and epidemiological transitions: 2002–2030. Annals of tropical medicine and parasitology.
Moran, A. E., Tzong, K. Y., Forouzanfar, M. H., Roth, G. A., Mensah, G. A., Ezzati, M., ... & Naghavi, M. (2014). Variations in ischemic heart disease burden by age, country, and income: the Global Burden of Diseases, Injuries, and Risk Factors 2010 study. Global heart, 9(1), 91-99.
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