Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey
Abstract Background In many countries, the prevalence of non-communicable diseases risk factors is commonly assessed through self-reported information from health interview surveys. It has been shown, however, that self-reported instead of objective data lead to an underestimation of the prevalence of obesity, hypertension and hypercholesterolemia. This study aimed to assess the agreement between self-reported and measured height, weight, hypertension and hypercholesterolemia and to identify an adequate approach for valid measurement error correction. Methods Nine thousand four hundred thirty-... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2023 |
Reihe/Periodikum: | BMC Medical Research Methodology ; volume 23, issue 1 ; ISSN 1471-2288 |
Verlag/Hrsg.: |
Springer Science and Business Media LLC
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Schlagwörter: | Health Informatics / Epidemiology |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26498103 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://dx.doi.org/10.1186/s12874-023-01892-x |