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A small area estimation model of comorbidity for England
Abstract Background Cardiovascular disease, diabetes, and obesity as single health conditions are rising in prevalence, but a growing body of evidence suggests that individuals are increasingly experiencing two or more of these conditions at the same time. Previous research on comorbidity has focuse...
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Published in: | The Lancet (British edition) 2016-11, Vol.388, p.S80-S80 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Abstract Background Cardiovascular disease, diabetes, and obesity as single health conditions are rising in prevalence, but a growing body of evidence suggests that individuals are increasingly experiencing two or more of these conditions at the same time. Previous research on comorbidity has focused on identifying the most common groupings of illnesses among elderly health-care users by use of hospital administrative data. Using small area estimation techniques, we developed a population-wide dataset of comorbidity of cardiovascular disease, diabetes, and obesity for England at the small area level. Methods Matching data from the 2011 Health Survey for England and the 2011 Census in England and Wales, we proposed a new global optimisation (GO) survey calibration method for the estimation of small area estimates of comorbidity. Unlike previous small area estimation methods, the GO method is time efficient and always convergent, uses initial weights a priori for the small area distribution, and allows the user to confirm the best solution. Validation of the newly simulated data involved comparison of the fit (as measured by the relative difference of the sum of squared Z-scores, Z2rel |
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ISSN: | 0140-6736 1474-547X |
DOI: | 10.1016/S0140-6736(16)32316-9 |