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Cardiovascular disease (CVD): assessment, prediction and policy implications
BACKGROUND: The study aims to predict and assess cardiovascular disease (CVD) patterns in highly affected countries such as Pakistan, India, China, Kenya, the USA, and Sweden. The data for CVD deaths was gathered from 2005 to 2019. METHODS: We utilized non-homogenous discrete grey model (NDGM) to pr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253470/ https://www.ncbi.nlm.nih.gov/pubmed/34215234 http://dx.doi.org/10.1186/s12889-021-11334-2 |
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author | Rehman, Shazia Rehman, Erum Ikram, Muhammad Jianglin, Zhang |
author_facet | Rehman, Shazia Rehman, Erum Ikram, Muhammad Jianglin, Zhang |
author_sort | Rehman, Shazia |
collection | PubMed |
description | BACKGROUND: The study aims to predict and assess cardiovascular disease (CVD) patterns in highly affected countries such as Pakistan, India, China, Kenya, the USA, and Sweden. The data for CVD deaths was gathered from 2005 to 2019. METHODS: We utilized non-homogenous discrete grey model (NDGM) to predict growth of cardiovascular deaths in selected countries. We take this process a step further by utilizing novel Synthetic Relative Growth Rate (RGR) and Synthetic Doubling Time (Dt) model to assess how many years it takes to reduce the cardiovascular deaths double in numbers. RESULTS: The results reveal that the USA and China may lead in terms of raising its number of deaths caused by CVDs till 2027. However, doubling time model suggests that USA may require 2.3 years in reducing the cardiovascular deaths. CONCLUSIONS: This study is significant for the policymakers and health practitioners to ensure the execution of CVD prevention measures to overcome the growing burden of CVD deaths. |
format | Online Article Text |
id | pubmed-8253470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82534702021-07-06 Cardiovascular disease (CVD): assessment, prediction and policy implications Rehman, Shazia Rehman, Erum Ikram, Muhammad Jianglin, Zhang BMC Public Health Research Article BACKGROUND: The study aims to predict and assess cardiovascular disease (CVD) patterns in highly affected countries such as Pakistan, India, China, Kenya, the USA, and Sweden. The data for CVD deaths was gathered from 2005 to 2019. METHODS: We utilized non-homogenous discrete grey model (NDGM) to predict growth of cardiovascular deaths in selected countries. We take this process a step further by utilizing novel Synthetic Relative Growth Rate (RGR) and Synthetic Doubling Time (Dt) model to assess how many years it takes to reduce the cardiovascular deaths double in numbers. RESULTS: The results reveal that the USA and China may lead in terms of raising its number of deaths caused by CVDs till 2027. However, doubling time model suggests that USA may require 2.3 years in reducing the cardiovascular deaths. CONCLUSIONS: This study is significant for the policymakers and health practitioners to ensure the execution of CVD prevention measures to overcome the growing burden of CVD deaths. BioMed Central 2021-07-02 /pmc/articles/PMC8253470/ /pubmed/34215234 http://dx.doi.org/10.1186/s12889-021-11334-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Rehman, Shazia Rehman, Erum Ikram, Muhammad Jianglin, Zhang Cardiovascular disease (CVD): assessment, prediction and policy implications |
title | Cardiovascular disease (CVD): assessment, prediction and policy implications |
title_full | Cardiovascular disease (CVD): assessment, prediction and policy implications |
title_fullStr | Cardiovascular disease (CVD): assessment, prediction and policy implications |
title_full_unstemmed | Cardiovascular disease (CVD): assessment, prediction and policy implications |
title_short | Cardiovascular disease (CVD): assessment, prediction and policy implications |
title_sort | cardiovascular disease (cvd): assessment, prediction and policy implications |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253470/ https://www.ncbi.nlm.nih.gov/pubmed/34215234 http://dx.doi.org/10.1186/s12889-021-11334-2 |
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