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01-12-2021 | Research article

Cardiovascular disease (CVD): assessment, prediction and policy implications

Authors: Shazia Rehman, Erum Rehman, Muhammad Ikram, Zhang Jianglin

Published in: BMC Public Health | Issue 1/2021

Abstract

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.

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Title: Cardiovascular disease (CVD): assessment, prediction and policy implications
Authors: Shazia Rehman
Erum Rehman
Muhammad Ikram
Zhang Jianglin
Publication date: 01-12-2021
Publisher: BioMed Central
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11334-2

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Springer Medicine

Cardiovascular disease (CVD): assessment, prediction and policy implications

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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