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, Vol 23, Iss 1, Pp 1-15 (2023) |
Verlag/Hrsg.: |
BMC
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Schlagwörter: | Measurement error / Multiple imputation / Health interview survey / Health examination survey / Obesity / Hypertension / Medicine (General) / R5-920 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26511171 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.1186/s12874-023-01892-x |