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Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database
AIMS/INTRODUCTION: Little is known about the relationship between cardiovascular health (CVH) metrics and the risk of developing prediabetes or diabetes. We examined the association of CVH metrics with the annual risk of developing prediabetes or diabetes. MATERIALS AND METHODS: We carried out this...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951564/ https://www.ncbi.nlm.nih.gov/pubmed/36495057 http://dx.doi.org/10.1111/jdi.13958 |
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author | Okada, Akira Kaneko, Hidehiro Matsuoka, Satoshi Itoh, Hidetaka Suzuki, Yuta Fujiu, Katsuhito Michihata, Nobuaki Jo, Taisuke Takeda, Norifumi Morita, Hiroyuki Yamaguchi, Satoko Node, Koichi Yamauchi, Toshimasa Yasunaga, Hideo Komuro, Issei |
author_facet | Okada, Akira Kaneko, Hidehiro Matsuoka, Satoshi Itoh, Hidetaka Suzuki, Yuta Fujiu, Katsuhito Michihata, Nobuaki Jo, Taisuke Takeda, Norifumi Morita, Hiroyuki Yamaguchi, Satoko Node, Koichi Yamauchi, Toshimasa Yasunaga, Hideo Komuro, Issei |
author_sort | Okada, Akira |
collection | PubMed |
description | AIMS/INTRODUCTION: Little is known about the relationship between cardiovascular health (CVH) metrics and the risk of developing prediabetes or diabetes. We examined the association of CVH metrics with the annual risk of developing prediabetes or diabetes. MATERIALS AND METHODS: We carried out this study including 403,857 participants aged 18–71 years with available data on fasting plasma glucose (FPG) data for five consecutive years and with normal FPG (<100 mg/dL) at the initial health checkup. We identified the following ideal CVH metrics: non‐smoking, body mass index of <25 kg/m(2), maintaining physical activity, taking breakfast, untreated blood pressure of <120/80 mmHg and untreated total cholesterol of <200 mg/dL. We defined the primary end‐point as prediabetes (FPG 100–125 mg/dL) or diabetes (FPG ≥126 mg/dL or use of antihyperglycemic medications). We examined the relationship of CVH metrics with the annual incidence of prediabetes or diabetes. Additionally, we examined the association of 1‐year changes in CVH metrics with the risk for prediabetes or diabetes. RESULTS: The median age was 44 years, and 65.6% were men. An increasing number of non‐ideal CVH metrics was associated with an elevated risk of prediabetes or diabetes. A non‐ideal body mass index was most strongly associated with the risk of prediabetes or diabetes. The risk of developing prediabetes or diabetes rose as the number of non‐ideal CVH metrics increased over 1 year. CONCLUSIONS: CVH metrics could stratify the risk of the annual development of prediabetes or diabetes. The risk of developing prediabetes or diabetes might be reduced by improving CVH metrics. |
format | Online Article Text |
id | pubmed-9951564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99515642023-02-25 Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database Okada, Akira Kaneko, Hidehiro Matsuoka, Satoshi Itoh, Hidetaka Suzuki, Yuta Fujiu, Katsuhito Michihata, Nobuaki Jo, Taisuke Takeda, Norifumi Morita, Hiroyuki Yamaguchi, Satoko Node, Koichi Yamauchi, Toshimasa Yasunaga, Hideo Komuro, Issei J Diabetes Investig Articles AIMS/INTRODUCTION: Little is known about the relationship between cardiovascular health (CVH) metrics and the risk of developing prediabetes or diabetes. We examined the association of CVH metrics with the annual risk of developing prediabetes or diabetes. MATERIALS AND METHODS: We carried out this study including 403,857 participants aged 18–71 years with available data on fasting plasma glucose (FPG) data for five consecutive years and with normal FPG (<100 mg/dL) at the initial health checkup. We identified the following ideal CVH metrics: non‐smoking, body mass index of <25 kg/m(2), maintaining physical activity, taking breakfast, untreated blood pressure of <120/80 mmHg and untreated total cholesterol of <200 mg/dL. We defined the primary end‐point as prediabetes (FPG 100–125 mg/dL) or diabetes (FPG ≥126 mg/dL or use of antihyperglycemic medications). We examined the relationship of CVH metrics with the annual incidence of prediabetes or diabetes. Additionally, we examined the association of 1‐year changes in CVH metrics with the risk for prediabetes or diabetes. RESULTS: The median age was 44 years, and 65.6% were men. An increasing number of non‐ideal CVH metrics was associated with an elevated risk of prediabetes or diabetes. A non‐ideal body mass index was most strongly associated with the risk of prediabetes or diabetes. The risk of developing prediabetes or diabetes rose as the number of non‐ideal CVH metrics increased over 1 year. CONCLUSIONS: CVH metrics could stratify the risk of the annual development of prediabetes or diabetes. The risk of developing prediabetes or diabetes might be reduced by improving CVH metrics. John Wiley and Sons Inc. 2022-12-10 /pmc/articles/PMC9951564/ /pubmed/36495057 http://dx.doi.org/10.1111/jdi.13958 Text en © 2022 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Articles Okada, Akira Kaneko, Hidehiro Matsuoka, Satoshi Itoh, Hidetaka Suzuki, Yuta Fujiu, Katsuhito Michihata, Nobuaki Jo, Taisuke Takeda, Norifumi Morita, Hiroyuki Yamaguchi, Satoko Node, Koichi Yamauchi, Toshimasa Yasunaga, Hideo Komuro, Issei Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title | Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title_full | Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title_fullStr | Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title_full_unstemmed | Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title_short | Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database |
title_sort | association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: analysis of a nationwide real‐world database |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951564/ https://www.ncbi.nlm.nih.gov/pubmed/36495057 http://dx.doi.org/10.1111/jdi.13958 |
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