Association of cardiovascular health metrics with annual incidence of prediabetes or diabetes: Analysis of a nationwide real‐world database. Issue 3 (10th December 2022)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Journal of diabetes investigation. Volume 14:Issue 3(2023)
• Page Start: 452
• Page End: 462
• Publication Date: 2022-12-10
• Subjects: Cardiovascular health metrics -- Diabetes -- Prediabetes; Diabetes -- Periodicals; Diabetes -- Research -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1111/jdi.13958
• Languages: English
• ISSNs: 2040-1116

Abstract

ABSTRACT: 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. Abstract : CVH metrics can be used to stratify the risk of the annual development of prediabetes or diabetes. Improving CVH metrics may reduce the risk of prediabetes or diabetes.