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The “secret” impact of population statistics on the metrics of diabetes

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Abstract

The accuracy of disease metrics is dependent on the quality of population-based data.
Many diseases, including diabetes, are age and sex dependant. Accurate age- and sexspecific population survey data, population estimates and projections are required to assess the scale and trends in the burden of these diseases.
No assessment of the quality of population data being used in the UAE diabetes metrics has been published. We provide insight into the availability and quality of
published population data, which is currently being used to inform diabetes research
and health services planning in the UAE.
We show the absence of credible population-based data impedes the accurate assessment of disease prevalence, incidence and trends. This means that many statements about the burden of this disease in relative and absolute terms are not robust.
There has been only one study of sufficient reliability of the prevalence of diabetes in the UAE and this was undertaken in 2000. Hence the calculation and reporting of trends is problematic. Population estimates for the UAE are based on out of date data and are extremely variable. Population projections for the UAE and other Middle East countries with large expatriate labour forces are improbable.
The clinical and other implications of accurate population-based metrics are wide reaching. If prevalence rates are to be used to guide public policy and infrastructure planning, then we need to use valid data, including population and population-based data.
Whilst specific reference is made to diabetes, and the issues affecting the United Arab Emirates and the Gulf Cooperation Council Countries of the Middle East; the impact of inaccurate population–based metrics have application in other regions, and other diseases.

Item Type: Journal article
Uncontrolled Keywords: diabetes, population, population-based, metrics, stimates, projections, prevalence, incidence, mortality, united arab emirates
Subjects: R Medicine > RZ Other systems of medicine
Divisions: Schools > Centre for Health & Social Practice
Depositing User: Lisa Cox
Date Deposited: 17 Nov 2020 23:14
Last Modified: 21 Jul 2023 08:59
URI: http://researcharchive.wintec.ac.nz/id/eprint/7533

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