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Self-rated health trajectories: A dynamic time warp analysis

Self-rated health (SRH), individuals’ overall perception of their health, is a key predictor of health events. To target disease prevention efforts, it is important to understand how SRH develops over time. The goal of this short communication is to find prototypic SRH trajectories by applying dynam...

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Detalles Bibliográficos
Autores principales: Doornenbal, Brian M., Bakx, Renz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371205/
https://www.ncbi.nlm.nih.gov/pubmed/34430192
http://dx.doi.org/10.1016/j.pmedr.2021.101510
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author Doornenbal, Brian M.
Bakx, Renz
author_facet Doornenbal, Brian M.
Bakx, Renz
author_sort Doornenbal, Brian M.
collection PubMed
description Self-rated health (SRH), individuals’ overall perception of their health, is a key predictor of health events. To target disease prevention efforts, it is important to understand how SRH develops over time. The goal of this short communication is to find prototypic SRH trajectories by applying dynamic time warping, a time series comparison technique initially developed for speech recognition. Revealing prototypic SRH trajectories can help direct disease prevention efforts towards trajectories that are more likely to result in adverse health events. Based on data from a Dutch representative sample of 2,154 individuals, our dynamic time warp analysis suggests that Dutch individuals do not typically show a steady growth or decline in SRH. Instead, we identified four relatively stable SRH trajectories that differed in average SRH. One of these trajectories is a path of consistent low SRH.
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spelling pubmed-83712052021-08-23 Self-rated health trajectories: A dynamic time warp analysis Doornenbal, Brian M. Bakx, Renz Prev Med Rep Short Communication Self-rated health (SRH), individuals’ overall perception of their health, is a key predictor of health events. To target disease prevention efforts, it is important to understand how SRH develops over time. The goal of this short communication is to find prototypic SRH trajectories by applying dynamic time warping, a time series comparison technique initially developed for speech recognition. Revealing prototypic SRH trajectories can help direct disease prevention efforts towards trajectories that are more likely to result in adverse health events. Based on data from a Dutch representative sample of 2,154 individuals, our dynamic time warp analysis suggests that Dutch individuals do not typically show a steady growth or decline in SRH. Instead, we identified four relatively stable SRH trajectories that differed in average SRH. One of these trajectories is a path of consistent low SRH. 2021-08-10 /pmc/articles/PMC8371205/ /pubmed/34430192 http://dx.doi.org/10.1016/j.pmedr.2021.101510 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Short Communication
Doornenbal, Brian M.
Bakx, Renz
Self-rated health trajectories: A dynamic time warp analysis
title Self-rated health trajectories: A dynamic time warp analysis
title_full Self-rated health trajectories: A dynamic time warp analysis
title_fullStr Self-rated health trajectories: A dynamic time warp analysis
title_full_unstemmed Self-rated health trajectories: A dynamic time warp analysis
title_short Self-rated health trajectories: A dynamic time warp analysis
title_sort self-rated health trajectories: a dynamic time warp analysis
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371205/
https://www.ncbi.nlm.nih.gov/pubmed/34430192
http://dx.doi.org/10.1016/j.pmedr.2021.101510
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