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Adjustment of BMI models for indices of central obesity did not affect the estimation of diabetes risk in men, but led to an attenuation of risk estimates in women.
In general, estimation of diabetes mortality is challenging due to various reasons.
Sensitivity analyses indicate the uncertainty within the estimation of diabetes prevalence and burden in South Africa.
In 2007, for the first time blood glucose was measured allowing for the estimation of diabetes prevalence.
Consistently, with application in other field of analysis [ 28– 32], the evaluation of the best model for cost estimation of diabetes is not immediate.
25 For epidemiological studies, however, estimation of diabetes prevalence and incidence using a single elevated HbA1c or FPG measurement is considered acceptable.
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A model that does not have sufficient calibration will have significant over- or under-estimation of diabetes risk in the overall population and/or within certain subgroups.
In countries with adequate data quality, combination of routine data may provide valid and reliable estimations of diabetes prevalence.
Therefore, the results provided real-life estimations of diabetes risk associated with individual ARB, which have important clinical implications.
A total of 16 500 people were selected assuming an estimation prevalence of diabetes of 5.5% with 90% power and α=0.05 and allowing for a drop out of 10%.
METSIM is a population-based cohort providing both non-diabetic and type 2 diabetic individuals, and was employed for estimation of SGK diabetes-risk alleles.
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