Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model

Abstract Background Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and ex...

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Main Authors: Xue Feng Hu, Kue Young, Hing Man Chan
Format: Article
Language:English
Published: BMC 2017-01-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12874-016-0288-y
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spelling doaj-2c4931a7c3b148f7a3c8c994c0c982552020-11-25T00:59:56ZengBMCBMC Medical Research Methodology1471-22882017-01-0117111210.1186/s12874-016-0288-yEstimating cardiovascular disease incidence from prevalence: a spreadsheet based modelXue Feng Hu0Kue Young1Hing Man Chan2Department of Biology, University of OttawaSchool of Public Health, University of AlbertaDepartment of Biology, University of OttawaAbstract Background Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence. Methods We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD), with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI) in the U.S. population and incidence of heart disease in the Canadian population. Results Model-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence. Conclusion It is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.http://link.springer.com/article/10.1186/s12874-016-0288-yIncidencePrevalenceModelCardiovascular diseaseNHANES, Canadian CommunityHealth Survey
collection DOAJ
language English
format Article
sources DOAJ
author Xue Feng Hu
Kue Young
Hing Man Chan
spellingShingle Xue Feng Hu
Kue Young
Hing Man Chan
Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
BMC Medical Research Methodology
Incidence
Prevalence
Model
Cardiovascular disease
NHANES, Canadian Community
Health Survey
author_facet Xue Feng Hu
Kue Young
Hing Man Chan
author_sort Xue Feng Hu
title Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
title_short Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
title_full Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
title_fullStr Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
title_full_unstemmed Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
title_sort estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
publisher BMC
series BMC Medical Research Methodology
issn 1471-2288
publishDate 2017-01-01
description Abstract Background Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence. Methods We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD), with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI) in the U.S. population and incidence of heart disease in the Canadian population. Results Model-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence. Conclusion It is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.
topic Incidence
Prevalence
Model
Cardiovascular disease
NHANES, Canadian Community
Health Survey
url http://link.springer.com/article/10.1186/s12874-016-0288-y
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