Journal of Epidemiology
Online ISSN : 1349-9092
Print ISSN : 0917-5040
ISSN-L : 0917-5040
Jcvrisk: An R Package for Population-Level Estimation of Cardiovascular Risk Scores in Japanese Adults
Hiroshi OkumiyamaRyosuke FujiiYoshiki TsuboiKazuma MurakamiRiku UmematsuYoshitaka AndoHiroaki IshikawaGenki MizunoKoji OhashiHiroya YamadaMirai YamazakiKoji Suzuki
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JOURNAL OPEN ACCESS Advance online publication
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Article ID: JE20250292

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Abstract

Background: Cardiovascular disease (CVD) remains a leading cause of death in Japan. Although several CVD risk scores tailored for Japanese individuals have been developed, no tools are available to estimate these scores at the population level. We developed the “Jcvrisk” R package, which integrates four major Japanese CVD risk models recommended by the clinical guideline. As a showcase, we applied the Jcvrisk package to longitudinal population-based study to evaluate trends in estimated different risk scores.

Methods: We used longitudinal data from the Yakumo Study, an annual health checkup for residents in Yakumo, Hokkaido. This package includes four risk models with 14 risk scores from representative cardiovascular cohort studies, including three EPOCH scores, one Hisayama score, two Suita scores, and eight JALS scores. For temporal comparisons of CVD risk scores, we summarized scores from 2000 to 2020 every five years.

Results: The mean age of participants throughout all study years was around 60 years old. Most risk factors did not change remarkably over the 20 years, with only a decrease in smoking prevalence and an increase in high density lipoprotein cholesterol (HDL-C). However, all CVD risk scores consistently indicated an upward trend in 10-year CVD risk.

Conclusions: Jcvrisk package includes functions to calculate CVD risk scores for Japanese adults. The package serves as a valuable tool for researchers and policymakers aiming to assess and monitor cardiovascular risk at both individual and population levels in Japan.

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© 2025 Hiroshi Okumiyama et al.

This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
https://creativecommons.org/licenses/by/4.0/
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