Yuta Suzuki1,2, Hidehiro Kaneko1,3, Akira Okada4, Hidetaka Itoh1, Kojiro Morita5, Katsuhito Fujiu1,3, Nobuaki Michihata6, Taisuke Jo6, Norifumi Takeda1, Hiroyuki Morita1, Satoko Yamaguchi4, Kentaro Kamiya7, Atsuhiko Matsunaga7, Junya Ako8, Akira Fukui9, Akira Nishiyama10, Takashi Yokoo9, Koichi Node11, Toshimasa Yamauchi12, Masaomi Nangaku13, Hideo Yasunaga14, Issei Komuro1. 1. The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan. 2. Department of Rehabilitation Science, Graduate School of Medical Sciences, Kitasato University, Kanagawa, Japan. 3. The Department of Advanced Cardiology, The University of Tokyo, Tokyo, Japan. 4. Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 5. Global Nursing Research Center, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 6. The Department of Health Services Research, The University of Tokyo, Tokyo, Japan. 7. Department of Rehabilitation, School of Allied Health Sciences, Kitasato University, Kanagawa, Japan. 8. Department of Cardiovascular Medicine, Kitasato University School of Medicine, Sagamihara, Japan. 9. Division of Nephrology and Hypertension, Department of Internal Medicine, Jikei University School of Medicine, Tokyo, Japan. 10. Department of Pharmacology, Faculty of Medicine, Kagawa University, Kagawa, Japan. 11. Department of Cardiovascular Medicine, Saga University, Saga, Japan. 12. Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 13. Division of Nephrology and Endocrinology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan. 14. The Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan.
Abstract
INTRODUCTION: Evidence is lacking regarding the association between cardiovascular health (CVH) metrics and the risk for proteinuria. METHODS: We performed this observational cohort study including 865,087 participants (median age, 46 years, 60.7% men) with negative proteinuria at the initial health check-up, who underwent repeated health check-ups within 4 years. Ideal CVH metrics included nonsmoking, body mass index <25 kg/m2, physical activity at goal, eating breakfast, blood pressure <120/80 mm Hg, fasting plasma glucose <100 mg/dL, and total cholesterol <200 mg/dL. The primary outcome was incident proteinuria, defined as ≥1 + on the urine dipstick test. RESULTS: Participants were categorized as having low CVH metrics defined as having 0-2 ideal CVH metrics (n = 84,439), middle CVH metrics defined as having 3-4 ideal CVH metrics (n = 335,773), and high CVH metrics defined as having 5-7 ideal CVH metrics (n = 444,875). Compared with low CVH metrics, middle CVH metrics (odds ratio (OR): 0.61, 95% CI: 0.59-0.63) and high CVH metrics (OR: 0.45, 95% CI: 0.43-0.46) were associated with a lower risk of proteinuria. The OR of a one-point increase in the ideal number of CVH metrics was 0.83 (95% CI: 0.82-0.83). All CVH metrics components except for ideal total cholesterol were associated with a decreased risk of proteinuria. A one-point improvement in the number of ideal CVH metrics at 1 year after the initial health check-up was associated with a decreased incidence of proteinuria (OR: 0.90, 95% CI: 0.89-0.92). CONCLUSION: Not only maintaining better CVH metrics but also improving CVH metrics would prevent developing proteinuria in a general population.
INTRODUCTION: Evidence is lacking regarding the association between cardiovascular health (CVH) metrics and the risk for proteinuria. METHODS: We performed this observational cohort study including 865,087 participants (median age, 46 years, 60.7% men) with negative proteinuria at the initial health check-up, who underwent repeated health check-ups within 4 years. Ideal CVH metrics included nonsmoking, body mass index <25 kg/m2, physical activity at goal, eating breakfast, blood pressure <120/80 mm Hg, fasting plasma glucose <100 mg/dL, and total cholesterol <200 mg/dL. The primary outcome was incident proteinuria, defined as ≥1 + on the urine dipstick test. RESULTS: Participants were categorized as having low CVH metrics defined as having 0-2 ideal CVH metrics (n = 84,439), middle CVH metrics defined as having 3-4 ideal CVH metrics (n = 335,773), and high CVH metrics defined as having 5-7 ideal CVH metrics (n = 444,875). Compared with low CVH metrics, middle CVH metrics (odds ratio (OR): 0.61, 95% CI: 0.59-0.63) and high CVH metrics (OR: 0.45, 95% CI: 0.43-0.46) were associated with a lower risk of proteinuria. The OR of a one-point increase in the ideal number of CVH metrics was 0.83 (95% CI: 0.82-0.83). All CVH metrics components except for ideal total cholesterol were associated with a decreased risk of proteinuria. A one-point improvement in the number of ideal CVH metrics at 1 year after the initial health check-up was associated with a decreased incidence of proteinuria (OR: 0.90, 95% CI: 0.89-0.92). CONCLUSION: Not only maintaining better CVH metrics but also improving CVH metrics would prevent developing proteinuria in a general population.
Authors: Bethany J Howard; Beverley Balkau; Alicia A Thorp; Dianna J Magliano; Jonathan E Shaw; Neville Owen; David W Dunstan Journal: Br J Sports Med Date: 2014-02-18 Impact factor: 13.800
Authors: Keiichi Sumida; Girish N Nadkarni; Morgan E Grams; Yingying Sang; Shoshana H Ballew; Josef Coresh; Kunihiro Matsushita; Aditya Surapaneni; Nigel Brunskill; Steve J Chadban; Alex R Chang; Massimo Cirillo; Kenn B Daratha; Ron T Gansevoort; Amit X Garg; Licia Iacoviello; Takamasa Kayama; Tsuneo Konta; Csaba P Kovesdy; James Lash; Brian J Lee; Rupert W Major; Marie Metzger; Katsuyuki Miura; David M J Naimark; Robert G Nelson; Simon Sawhney; Nikita Stempniewicz; Mila Tang; Raymond R Townsend; Jamie P Traynor; José M Valdivielso; Jack Wetzels; Kevan R Polkinghorne; Hiddo J L Heerspink Journal: Ann Intern Med Date: 2020-07-14 Impact factor: 25.391