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Chen Y, Zhang H, Pan Y, Zhang Y, Yang Y, Liu L, Jia Q, Wang Y, Kong Y. Association between cardiovascular health and serum vitamin D and its interaction with prediabetes and diabetes. Am J Med Sci 2024:S0002-9629(24)01414-9. [PMID: 39186977 DOI: 10.1016/j.amjms.2024.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 08/19/2024] [Accepted: 08/20/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND Prediabetes and diabetes are common and serious public health problems, and high blood glucose can lead to serious cardiovascular complications. The purpose of this article was to explore the link between CVH levels and the incidence of prediabetes and diabetes in people over 20 years old, and whether serum vitamin D status could alter this relationship. MATERIALS AND METHODS Data, from six consecutive cycles of the NHANES database from 2007 to 2018 were combined, eligible participants were aged ≥20 years. After excluding missing data, a total of 19,992 subjects were enrolled in the study. Significant risk factors for prediabetes and diabetes were analyzed using univariate and multivariate logistic regression. Exploring the interaction of VD and CVH on prediabetes and diabetes based on multifactorial regression analysis. RESULTS The prevalence of prediabetes among all participants was 36.15% and the prevalence of diabetes was 16.39%. CVH and vitamin D levels are influential factors in prediabetes and diabetes, and are negatively associated with the risk of developing prediabetes and diabetes. Compared with normoglycemia, poorer CVH and vitamin D deficiency only had a synergistic multiplicative interaction on the development of diabetes, and no significant interaction was observed for the development of prediabetes. Compared with prediabetes, poorer CVH and vitamin D deficiency still had a synergistic additive interaction on the development of diabetes. CONCLUSIONS Although the cross-sectional study only determine the association and do not prove causality, the current results can be used to prompt people to improve their lifestyle and risk factors to prevent prediabetes or diabetes through higher CVH and adequate Vitamin D.
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Affiliation(s)
- Ying Chen
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Haiyu Zhang
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yanbing Pan
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yanzi Zhang
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yuxuan Yang
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Lu Liu
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Qiuting Jia
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yongle Wang
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yihui Kong
- From the Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin, China.
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Prugger C, Perier MC, Sabia S, Fayosse A, van Sloten T, Jouven X, Pentti J, Kivimäki M, Empana JP. Association between changes in cardiovascular health and the risk of multimorbidity: community-based cohort studies in the UK and Finland. THE LANCET REGIONAL HEALTH. EUROPE 2024; 42:100922. [PMID: 38764806 PMCID: PMC11098950 DOI: 10.1016/j.lanepe.2024.100922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/29/2024] [Accepted: 04/16/2024] [Indexed: 05/21/2024]
Abstract
Background Better cardiovascular health is associated with lower risk of various chronic diseases, but its association with multimorbidity is poorly understood. We aimed to examine whether change in cardiovascular health is associated with multimorbidity risk. Methods The primary analysis was conducted in the Whitehall II multiwave prospective cohort study (UK) and the validation analysis in the Finnish Public Sector cohort study (Finland). Change in cardiovascular health was assessed using the American Heart Association Life's Simple 7 (LS7) and Life's Essential 8 (LE8) at baseline and re-assessments, using objective measures in Whitehall II and self-reports and pharmacy claims in the Finnish Public Sector cohort study, respectively. Multimorbidity was defined as the presence of two or more of 12 chronic diseases during follow-up. We estimated hazard ratios (HR) and 95% confidence intervals (CI) using Cox's proportional hazard models with age as time scale, adjusting for sex, education, occupation, marital status, and ethnicity. Findings In the primary analysis among 9715 participants, mean age was 44.8 (standard deviation 6.0) years and 67.6% participants were men at baseline. During the median follow-up of 31.4 (interquartile range 26.8-32.3) years, 2751 participants developed multimorbidity. The hazard of multimorbidity decreased by 8% (HR 0.92, 95% CI 0.88-0.96) per ideal LS7 metric increment over 5 years and by 14% (HR 0.86, 95% CI 0.80-0.93) per ten points increase in LE8 score over 10 years. These findings were replicated in the validation analysis among 75,377 participants in terms of 4-year change in cardiovascular health. Interpretation Improvement in cardiovascular health was associated with lower multimorbidity risk in two community-based cohort studies. Interventions improving cardiovascular health of the community may contribute to multimorbidity prevention. Funding None.
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Affiliation(s)
- Christof Prugger
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Public Health, Seestraße 73, 13347, Berlin, Germany
| | - Marie-Cécile Perier
- Université Paris Cité, Paris, INSERM U970, Paris Cardiovascular Research Centre (PARCC), 56 rue Leblanc, 75015, Paris, France
| | - Séverine Sabia
- Université Paris Cité, INSERM U1153, Epidemiology of Aging and Neurodegenerative Diseases, 10 avenue de Verdun, 75010, Paris, France
- Department of Epidemiology and Public Health, University College London, 1-19 Torrington Pl, London, Wc1E 7Hb, United Kingdom
| | - Aurore Fayosse
- Université Paris Cité, INSERM U1153, Epidemiology of Aging and Neurodegenerative Diseases, 10 avenue de Verdun, 75010, Paris, France
| | - Thomas van Sloten
- Department of Vascular Medicine, University Medical Centre Utrecht, Lundlaan 4, 3584 EA, Utrecht, the Netherlands
| | - Xavier Jouven
- Université Paris Cité, Paris, INSERM U970, Paris Cardiovascular Research Centre (PARCC), 56 rue Leblanc, 75015, Paris, France
| | - Jaana Pentti
- Clinicum, Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, 00290, Helsinki, Finland
- Department of Public Health, University of Turku, Kiinamyllynkatu 8-10, 20520, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Kiinamyllynkatu 8-10, 20520, Turku, Finland
- Finnish Institute of Occupational Health, Topeliuksenkatu 41 b, 00250, Helsinki, Finland
| | - Mika Kivimäki
- UCL Brain Sciences, University College London, 17 Queen Square, WC1N 3AR, London, United Kingdom
- Clinicum, Faculty of Medicine, University of Helsinki, Tukholmankatu 8, 00290, Helsinki, Finland
| | - Jean-Philippe Empana
- Université Paris Cité, Paris, INSERM U970, Paris Cardiovascular Research Centre (PARCC), 56 rue Leblanc, 75015, Paris, France
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Xu W, Feng Y, Abdullah G, Li L, Fang P, Tang S, Yang H, Kong D, Huang H, Wang Y, Xue Y. Association between the AHA life's essential 8 and prediabetes/diabetes: a cross-sectional NHANES study. Front Endocrinol (Lausanne) 2024; 15:1376463. [PMID: 39086898 PMCID: PMC11289523 DOI: 10.3389/fendo.2024.1376463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 06/17/2024] [Indexed: 08/02/2024] Open
Abstract
Background and aims The American Heart Association (AHA) recently introduced the Life's Essential 8 (LE8) to improve cardiovascular health (CVH). However, the association between LE8 and the risk of prediabetes or diabetes is not yet fully understood. Consequently, this study aims to assess the association between CVH, as evaluated by LE8, and the risk of prediabetes and diabetes. Methods and Results This cross-sectional study encompassed 7,739 participants aged ≥20 years from the 2007-2018 National Health and Nutrition Examination Surveys (NHANES). The CVH of participants was evaluated using the LE8, combining four health behaviors and three health factors. Glucose metabolic status categories included normal glucose metabolism, prediabetes including isolated impaired fasting glucose, isolated impaired glucose tolerance, both IFG and IGT, and diabetes. The associations between CVH and prediabetes and diabetes were analyzed using logistic regression, linear regression, restricted cubic splines, and subgroup analyses. Among 7,739 participants, 1,949 had iIFG, 1,165 were diagnosed with iIGT, 799 were IFG+IGT, and 537 were diagnosed with diabetes. After multivariable adjustments, CVH scores were inversely associated with prediabetes and diabetes, with the most robust inverse association observed between IFG+IGT and CVH across all prediabetes subgroups. Of all CVH components not directly in the causal pathway, body mass index (BMI) had the most robust associations with prediabetes and diabetes. Subgroup analyses indicated that the negative correlation between CVH and prediabetes was stronger among those with university or higher education. Conclusion CVH, as defined by LE8, showed a significant negative association with prediabetes and diabetes.
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Affiliation(s)
- Wei Xu
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yuntao Feng
- Department of Cardiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Guzalnur Abdullah
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ling Li
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ping Fang
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Sijing Tang
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Huanhuan Yang
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Dehong Kong
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Hemin Huang
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yang Wang
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ying Xue
- Department of Endocrinology and Metabolism, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
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Te Hoonte F, Spronk M, Sun Q, Wu K, Fan S, Wang Z, Bots ML, Van der Schouw YT, Uijl A, Vernooij RWM. Ideal cardiovascular health and cardiovascular-related events: a systematic review and meta-analysis. Eur J Prev Cardiol 2024; 31:966-985. [PMID: 38149986 DOI: 10.1093/eurjpc/zwad405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/07/2023] [Accepted: 12/21/2023] [Indexed: 12/28/2023]
Abstract
AIMS The aim of this study was to systematically review and quantitatively summarize the evidence on the association between Life Simple's 7 (LS7) and multiple cardiovascular diseases (CVDs) and cardiometabolic diseases (CMDs). METHODS AND RESULTS EMBASE and PubMed were searched from January 2010 to March 2022 for observational studies that investigated the association between ideal cardiovascular health (CVH) with CVD or CMD outcomes in an adult population. Two reviewers independently selected studies according to the eligibility criteria, extracted data, and evaluated risk of bias. Data were analysed with a random-effects meta-analysis. This meta-analysis included 59 studies (1 881 382 participants). Participants with ideal CVH had a considerably lower risk of a variety of CVDs and CMDs as compared with those with poor CVH, varying from 40% lower risk for atrial fibrillation (AF) {hazard ratio [HR] = 0.60 [95% confidence interval (CI) 0.44-0.83]} to 82% lower risk for myocardial infarction [HR = 0.18 (95% CI 0.12-0.28)]. Intermediate CVH was associated with 27-57% lower risk in CVDs and CMDs compared with poor CVH, with the highest hazard for AF [HR = 0.73 (95% CI 0.59-0.91)] and the lowest hazard for peripheral arterial disease [HR = 0.43 (95% CI 0.30-0.60)]. CONCLUSION Ideal and moderate CVH were associated with a lower incidence of CVDs and CMDs than poor CVH. Life Simple's 7 holds significant potential for promoting overall CVH and thereby contributing to the prevention of CVDs.
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Affiliation(s)
- Femke Te Hoonte
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Merve Spronk
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Qi Sun
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Kangrui Wu
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Shiqi Fan
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Ziyi Wang
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Michiel L Bots
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Yvonne T Van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Alicia Uijl
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
- Department of Cardiology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- Division of Cardiology, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Robin W M Vernooij
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
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5
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Jing L, Chen T, Yang Z, Dong W. Association of the blood levels of specific volatile organic compounds with nonfatal cardio-cerebrovascular events in US adults. BMC Public Health 2024; 24:616. [PMID: 38408965 PMCID: PMC10898104 DOI: 10.1186/s12889-024-18115-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 02/15/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND Cardio-cerebrovascular diseases constitute a major global public health burden. Volatile organic compounds (VOCs) exposure has become progressively severe, endangering human health and becoming one of the main concerns in environmental pollution. The associations of VOCs exposure with nonfatal cardio-cerebrovascular events have not been identified in observational study with a large sample size, so we aim to examine the association in US adult population. METHODS Adults aged > 18 years with complete data regarding selected blood levels of VOCs (including benzene, ethylbenzene, o-xylene, and m-/p-xylene) and nonfatal cardio-cerebrovascular events were included in the analysis (n = 3,968, National Health and Nutrition Examination Survey, NHANES, 2013-2018 survey cycle). Participants were classified into low- and high-exposure based on whether above selected VOCs low limit detect concentration or median value. Weighted multivariate logistic analyses and subgroup analyses were used to detect the association between selected VOCs exposure and nonfatal cardio-cerebrovascular events in US adults. RESULTS Weighted multivariate logistic analyses showed that the high-VOCs exposure group had an increased risk of nonfatal cardio-cerebrovascular events compared with the low-VOCs exposure group; the adjusted odds ratios (OR) and 95% confidence intervals (CI) of nonfatal cardio-cerebrovascular events for the high-VOCs exposure group were 1.41 (0.91, 2.19), 1.37 (0.96, 1.95), 1.32 (0.96, 1.82), and 1.17 (0.82, 1.67) for benzene, ethylbenzene, o-xylene, and m-/p-xylene, respectively, which was not significant assuming statistical significance at a 0.05 significance level (95% CI) for a two-tailed test. Lastly, we found high-VOCs exposure was associated with increased incidence of nonfatal cardio-cerebrovascular events in both daily smokers an non-daily smokers (p-interaction > 0.01), but the association was not statistically significant in non-daily smokers. CONCLUSIONS This study found that VOCs (benzene, ethylbenzene, o-xylene, and m-/p-xylene) exposure was associated with increased incidence of nonfatal cardio-cerebrovascular events in US adults, and the results need to be confirmed by larger cohort studies.
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Affiliation(s)
- Li Jing
- Department of Nursing, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tiancong Chen
- Department of Nursing, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zhiyong Yang
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Weiwei Dong
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China.
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Badrooj N, Jayedi A, Shab-Bidar S. Ideal cardiovascular health metrics and risk of type 2 diabetes: A systematic review and dose-response meta-analysis of prospective cohort studies. Nutr Metab Cardiovasc Dis 2023; 33:2067-2075. [PMID: 37563068 DOI: 10.1016/j.numecd.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 05/03/2023] [Accepted: 07/04/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND AND AIMS Studies suggest a potential link between ideal cardiovascular health (CVH) and the risk of type 2 diabetes (T2D). However, systematic reviews are lacking to pool these data and present a balanced review about this association. METHODS AND RESULTS We performed a systematic search of PubMed/Medline, Web of Sciences, and Scopus from inception until November 2022 to search for prospective observational studies assessing the link between ideal CVH metrics, as introduced by the American Heart Association, and the risk of T2D in adults. Nine cohort studies with 78,912 participants and 6242 cases of T2D were included. The pooled relative risk of T2D for the highest versus the lowest category of ideal CVH metrics was 0.36 (95% confidence interval [CI]: 0.25, 0.47; risk difference: 5 fewer per 100 patients, 95% CI: 6 fewer, 4 fewer; Grading of Recommendations Assessment, Development and Evaluation certainty = high). Each unit increase in the components of the ideal CVH metrics was associated with a 20% lower risk of T2D. Dose-response meta-analysis indicated a monotonic inverse association between ideal CVH metrics and the risk of T2D. Results from analysis of individual components showed that having a normal weight, adopting a healthy diet, and having normal blood pressure levels were associated with a reduced risk of T2D. CONCLUSIONS Having an ideal CVH profile and a unit increase in any CVH metric are inversely associated with the risk of T2D. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42022376934.
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Affiliation(s)
- Negin Badrooj
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Jayedi
- Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran
| | - Sakineh Shab-Bidar
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
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7
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van Sloten TT, Climie RED, Deraz O, Périer MC, Valentin E, Fayosse A, Sabia S, Weiderpass E, Jouven X, Goldberg M, Zins M, Touvier M, Deschasaux-Tanguy M, Fezeu L, Hercberg S, Singh-Manoux A, Empana JP. Is the number of ideal cardiovascular health metrics in midlife associated with lower risk of cancer? Evidence from 3 European prospective cohorts. CMAJ Open 2023; 11:E774-E781. [PMID: 37607746 PMCID: PMC10449017 DOI: 10.9778/cmajo.20220175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023] Open
Abstract
BACKGROUND Primordial prevention may be a relevant strategy for the prevention of cancer. Given the commonality of risk factors and mechanisms between cancer and cardiovascular disease, we examined the associations between the number of ideal cardiovascular health metrics in midlife and incident cancer. METHODS In 3 European cohorts (NutriNet-Santé and GAZEL, France; Whitehall II, United Kingdom), the number of ideal cardiovascular health metrics was determined at baseline (range 0-7). Follow-up for cancer events was until October 2020 (NutriNet-Santé), March 2017 (Whitehall II) and December 2015 (GAZEL). Cox regression was conducted in each cohort, and results were thereafter pooled using a random-effects model. RESULTS Data were available on 39 718 participants. A total of 16 237 were from NutriNet-Santé (mean age 51.3 yr; 28% men), 9418 were from Whitehall II (mean age 44.8 yr; 68% men) and 14 063 were from GAZEL (mean age 45.2 yr; 75% men). The median follow-up was 8.1 years in NutriNet-Santé, 29.6 years in Whitehall II and 24.8 years in GAZEL, and yielded a total of 4889 cancer events. A greater number of ideal cardiovascular health metrics was associated with a lower overall cancer risk in each cohort, with an aggregate hazard ratio (HR) per 1 increment in number of ideal metrics of 0.91 (95% confidence interval [CI] 0.88-0.93). This association remained after removal of the smoking metric (aggregate HR per unit increment in number of ideal metrics: 0.94, 95% CI 0.90-0.97), and site-specific analysis demonstrated a significant association with lung cancer. INTERPRETATION A greater number of ideal cardiovascular health metrics in midlife was associated with lower cancer risk, notably lung cancer. Primordial prevention of cardiovascular risk factors in midlife may be a complementary strategy to prevent the onset of cancer.
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Affiliation(s)
- Thomas T van Sloten
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Rachel E D Climie
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Omar Deraz
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Marie-Cécile Périer
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Eugenie Valentin
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Aurore Fayosse
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Séverine Sabia
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Elisabete Weiderpass
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Xavier Jouven
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Marcel Goldberg
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Marie Zins
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Mathilde Touvier
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Mélanie Deschasaux-Tanguy
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Léopold Fezeu
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Serge Hercberg
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Archana Singh-Manoux
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
| | - Jean-Philippe Empana
- Paris Cardiovascular Research Center, Integrative Epidemiology of Cardiovascular Disease (Team 4), Institut national de la santé et de la recherche médicale, (INSERM) Unité Mixte de Recherche (UMR) S970 (van Sloten, Deraz, Périer, Valentin, Jouven, Empana), Université Paris Cité, Paris, France; Cardiovascular Research Institute Maastricht and Department of Internal Medicine (van Sloten), Maastricht University Medical Center, Maastricht, the Netherlands; Menzies Institute for Medical Research (Climie), University of Tasmania, Hobart, Australia; Baker Heart and Diabetes Institute (Climie), Melbourne, Australia; Centre for Research in Epidemiology and Statistics, INSERM, UMR 1153 (Fayosse, Sabia, Singh-Manoux), Université Paris Cité, Paris, France; Department of Epidemiology and Public Health (Sabia, Singh-Manoux), University College London, London, UK; International Agency for Research in Cancer (Weiderpass), Lyon, France; Population-based Cohorts Unit (Goldberg, Zins), INSERM, Unité Mixte de Service (UMS) 011, Université Paris Cité, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France; Sorbonne Paris Nord University (Touvier, Deschasaux-Tanguy, Fezeu, Hercberg), INSERM, UMR 1153, Institut national de la recherche agronomique (INRAE) U1125, National Conservatory of Arts and Crafts, Nutritional Epidemiology Research Team, Epidemiology and Statistics Research Center - University of Paris, Bobigny, France
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Zhao Z, Cao Q, Lu J, Lin H, Gao Z, Xu M, Xu Y, Wang T, Li M, Chen Y, Wang S, Zeng T, Hu R, Yu X, Chen G, Su Q, Mu Y, Chen L, Tang X, Yan L, Qin G, Wan Q, Wang G, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Zhao J, Shi L, Ning G, Wang W, Bi Y. Association of Spousal Diabetes Status and Ideal Cardiovascular Health Metrics With Risk of Incident Diabetes Among Chinese Adults. JAMA Netw Open 2023; 6:e2319038. [PMID: 37351887 PMCID: PMC10290251 DOI: 10.1001/jamanetworkopen.2023.19038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/03/2023] [Indexed: 06/24/2023] Open
Abstract
Importance Spouses share common socioeconomic, environmental, and lifestyle factors, and multiple studies have found that spousal diabetes status was associated with diabetes prevalence. But the association of spousal diabetes status and ideal cardiovascular health metrics (ICVHMs) assessed by the American Heart Association's Life's Essential 8 measures with incident diabetes has not been comprehensively characterized, especially in large-scale cohort studies. Objective To explore the association of spousal diabetes status and cardiovascular health metrics with risk of incident diabetes in Chinese adults. Design, Setting, and Participants This cohort study included individuals in the China Cardiovascular Disease and Cancer Cohort without diabetes who underwent baseline and follow-up glucose measurements and had spouses with baseline glucose measurements. The data were collected in January 2011 to December 2012 and March 2014 to December 2016. The spousal study had a mean (SD) follow-up of 3.6 (0.9) years (median [IQR], 3.2 [2.9-4.5] years). Statistical analysis was performed from July to November 2022. Exposure Spousal diabetes status was diagnosed according to the 2010 American Diabetes Association (ADA) criteria. All participants provided detailed clinical, sociodemographic, and lifestyle information included in cardiovascular health metrics. Main Outcomes and Measures Incident diabetes, diagnosed according to 2010 ADA criteria. Results Overall, 34 821 individuals were included, with a mean (SD) age of 56.4 (8.3) years and 16 699 (48.0%) male participants. Spousal diabetes diagnosis was associated with an increased risk of incident diabetes (hazard ratio [HR], 1.15; 95% CI, 1.03-1.30). Furthermore, participants whose spouses had uncontrolled glycated hemoglobin (HbA1c) had a higher risk of diabetes (HR, 1.20; 95% CI, 1.04-1.39) but the risk of diabetes in participants whose spouses had controlled HbA1c did not increase significantly (HR, 1.10; 95% CI, 0.92-1.30). Moreover, this association varied with composite cardiovascular health status. Diabetes risk in individuals who had poor cardiovascular health status (<4 ICVHMs) was associated with spousal diabetes status (3 ICVHMs: HR, 1.50; 95% CI, 1.15-1.97), while diabetes risk in individuals who had intermediate to ideal cardiovascular health status (≥4 ICVHMs) was not associated with it (4 ICVHMs: HR, 1.01; 95% CI, 0.69-1.50). Conclusions and Relevance In this study, spousal diabetes diagnosis with uncontrolled HbA1c level was associated with increased risk of incident diabetes, but strict management of spousal HbA1c level and improving ICVHM profiles may attenuate the association of spousal diabetes status with diabetes risk. These findings suggest the potential benefit of couple-based lifestyle or pharmaceutical interventions for diabetes.
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Affiliation(s)
- Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiuyu Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhengnan Gao
- Dalian Municipal Central Hospital, Dalian, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianshu Zeng
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruying Hu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xuefeng Yu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Chen
- Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Qing Su
- Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiming Mu
- Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Lulu Chen
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xulei Tang
- The First Hospital of Lanzhou University, Lanzhou, China
| | - Li Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guijun Qin
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qin Wan
- The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Guixia Wang
- The First Hospital of Jilin University, Changchun, China
| | - Feixia Shen
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zuojie Luo
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yingfen Qin
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Li Chen
- Qilu Hospital of Shandong University, Jinan, China
| | - Yanan Huo
- Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, China
| | - Qiang Li
- The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhen Ye
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Yinfei Zhang
- Central Hospital of Shanghai Jiading District, Shanghai, China
| | - Chao Liu
- Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Youmin Wang
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shengli Wu
- Karamay Municipal People’s Hospital, Xinjiang, China
| | - Tao Yang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huacong Deng
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiajun Zhao
- Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Lixin Shi
- Guiqian International General Hospital, Guiyang, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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9
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Wu C, Ren C, Song Y, Gao H, Pang X, Zhang L. Gender-specific effects of oxidative balance score on the prevalence of diabetes in the US population from NHANES. Front Endocrinol (Lausanne) 2023; 14:1148417. [PMID: 37214249 PMCID: PMC10194026 DOI: 10.3389/fendo.2023.1148417] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/28/2023] [Indexed: 05/24/2023] Open
Abstract
Background The relationship between oxidative balance score (OBS) and diabetes remains poorly understood and may be gender-specific. We conducted a cross-sectional study to investigate the complex association between OBS and diabetes among US adults. Methods Overall, 5,233 participants were included in this cross-sectional study. The exposure variable was OBS, composed of scores for 20 dietary and lifestyle factors. Multivariable logistic regression, subgroup analysis, and restricted cubic spline (RCS) regression were applied to examine the relationship between OBS and diabetes. Results Compared to the lowest OBS quartile group (Q1), the multivariable-adjusted odds ratio (OR) (95% confidence interval (CI) for the highest OBS quartile group (Q4) was 0.602 (0.372-0.974) (p for trend = 0.007), and for the highest lifestyle, the OBS quartile group was 0.386 (0.223-0.667) (p for trend < 0.001). Moreover, gender effects were found between OBS and diabetes (p for interaction = 0.044). RCS showed an inverted-U relationship between OBS and diabetes in women (p for non-linear = 6e-04) and a linear relationship between OBS and diabetes in men. Conclusions In summary, high OBS was negatively associated with diabetes risk in a gender-dependent manner.
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Affiliation(s)
- Cuiling Wu
- Department of Biochemistry, Changzhi Medical College, Changzhi, China
| | - Chenxia Ren
- Central Laboratory, Changzhi Medical College, Changzhi, China
| | - Yingda Song
- Department of Thoracic Surgery, Shanxi Provincial People’s Hospital, Taiyuan, China
- Fifth Clinical Medical College, Shanxi Medical University, Taiyuan, China
| | - Huifang Gao
- Department of Biochemistry, Changzhi Medical College, Changzhi, China
| | - Xin Pang
- Department of Biochemistry, Changzhi Medical College, Changzhi, China
| | - Lianyun Zhang
- Department of Biochemistry, Changzhi Medical College, Changzhi, China
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10
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Choi Y, Jacobs DR, Bancks MP, Lewis CE, Cha E, Yan F, Carnethon MR, Schreiner PJ, Duprez DA. Association of Cardiovascular Health Score With Early- and Later-Onset Diabetes and With Subsequent Vascular Complications of Diabetes. J Am Heart Assoc 2023; 12:e027558. [PMID: 36565184 PMCID: PMC9973601 DOI: 10.1161/jaha.122.027558] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Little attention has been paid to how well the American Heart Association's cardiovascular health (CVH) score predicts early-onset diabetes in young adults. We investigated the association of CVH score with early- and later-onset diabetes and with subsequent complications of diabetes. METHODS AND RESULTS Our sample included 4547 Black and White adults in the CARDIA (Coronary Artery Risk Development in Young Adults) study without diabetes at baseline (1985-1986; aged 18-30 years) with complete data on the CVH score at baseline, including smoking, body mass index, physical activity, diet quality, total cholesterol, blood pressure, and fasting blood glucose. Incident diabetes was determined based on fasting glucose, 2-hour postload glucose, hemoglobin A1c, or self-reported medication use throughout 8 visits for 30 years. Multinomial logistic regression was used to assess the association between CVH score and diabetes onset at age <40 years (early onset) versus age ≥40 years (later onset). Secondary analyses assessed the association between CVH score and risk of complications (coronary artery calcium, clinical cardiovascular disease, kidney function markers, diabetic retinopathy, and diabetic neuropathy) among a subsample with diabetes. We identified 116 early- and 502 later-onset incident diabetes cases. Each 1-point higher CVH score was associated with lower odds of developing early-onset (odds ratio [OR], 0.64 [95% CI, 0.58-0.71]) and later-onset diabetes (OR, 0.78 [95% CI, 0.74-0.83]). Lower estimates of diabetic complications were observed per 1-point higher CVH score: 19% for coronary artery calcification≥100, 18% for cardiovascular disease, and 14% for diabetic neuropathy. CONCLUSIONS Higher CVH score in young adulthood was associated with lower early- and later-onset diabetes as well as diabetic complications.
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Affiliation(s)
- Yuni Choi
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN
| | - Michael Patrick Bancks
- Department of Epidemiology and Prevention Wake Forest School of Medicine Winston-Salem NC
| | - Cora E Lewis
- Department of Epidemiology University of Alabama at Birmingham Birmingham AL
| | - EunSeok Cha
- College of Nursing Chungnam National University Daejeon South Korea.,Nell Hodgson Woodruff School of Nursing Emory University Atlanta GA
| | - Fengxia Yan
- Department of Community Health and Preventive Medicine Morehouse School of Medicine Atlanta GA
| | - Mercedes R Carnethon
- Department of Preventive Medicine, Feinberg School of Medicine Northwestern University Chicago IL
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health University of Minnesota Minneapolis MN
| | - Daniel A Duprez
- Cardiovascular Division, Department of Medicine University of Minnesota-Twin Cities Minneapolis MN
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12
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Wu X, Bao L, Liu X, Liao W, Kang N, Sang S, Abdulai T, Zhai Z, Wang C, Li Y. Ideal Cardiovascular Health Metrics Attenuated Association of Age at Menarche With Type 2 Diabetes in Rural China. Int J Public Health 2022; 67:1604261. [PMID: 36111199 PMCID: PMC9469086 DOI: 10.3389/ijph.2022.1604261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 06/10/2022] [Indexed: 11/13/2022] Open
Abstract
Objective: It is not clear whether ideal cardiovascular health (ICH) metrics have an impact on the association between age at menarche and type 2 diabetes (T2DM) in rural postmenopausal Chinese women. Methods: In all, 15,450 postmenopausal women were enrolled from the Henan Rural Cohort study. Logistic regression models and interaction plots were used to analyze associations between age at menarche, ICH metrics and T2DM and interactive effects. Results: Age at menarche was inversely associated with risk of T2DM, with adjusted OR of 1.224, 1.116, 1.00 and 0.971, 0.850 for those with age at menarche ≤13, 14, 15–16 (reference), 17, and ≥18 years, respectively, and each year of delay in menarche age correlated with a 5.1% lower risk of T2DM. Negative interaction effects of age at menarche and number of ICH metrics on the risk of T2DM was observed. Conclusion: Meeting more ICH metrics might attenuate the association between early menstrual age and increased risk of T2DM, implying that meeting a higher number of ICH metrics may be an effective way to prevent T2DM for women of early menarche age.
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Affiliation(s)
- Xueyan Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Lei Bao
- The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Shengxiang Sang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Tanko Abdulai
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhihan Zhai
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yuqian Li
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, China
- *Correspondence: Yuqian Li,
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13
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The impact of diabetes on postoperative outcomes following spine surgery: A meta-analysis of 40 cohort studies with 2.9 million participants. Int J Surg 2022; 104:106789. [PMID: 35918006 DOI: 10.1016/j.ijsu.2022.106789] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 07/06/2022] [Accepted: 07/10/2022] [Indexed: 11/22/2022]
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14
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Asgari S, Masrouri S, Hosseinpour‐Niazi S, Moslehi N, Azizi F, Hadaegh F. The Association of Ideal Cardiovascular Health Metrics and Incident Type 2 Diabetes Mellitus Among an urban population of Iran: a decade follow-up in Tehran Lipid and Glucose Study. J Diabetes Investig 2022; 13:1711-1722. [PMID: 35588067 PMCID: PMC9533049 DOI: 10.1111/jdi.13839] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/15/2022] [Accepted: 05/18/2022] [Indexed: 12/01/2022] Open
Abstract
AIMS To evaluate the association between ideal cardiovascular health metrics (ICVHM) and incident type diabetes (T2DM) among Iranian men and women. METHODS The study population included 7,488 Iranian adults aged ≥20 years (4236 women) free from diabetes at baseline. The ICVHM was defined according to the 2020-American Heart Association. The multivariable Cox proportional hazards regression analysis was used to calculate the hazard ratios (HRs) for ICVHM both as continuous and categorical variables. RESULTS Over the median of 9.1 years of follow-up, we identified 922 new cases of T2DM (526 women). Body mass index <30 kg/m2 , untreated systolic/diastolic blood pressure <120/80 mmHg in both genders, and physical activity ≥1500 MET mins/wk (only among men) were significantly associated with a lower risk of T2DM. Each additional unit in the ICVHM was associated with a 21% and 15% lower risk of T2DM in men and women, respectively (p-values<0.05). Compared with participants having poor cardiovascular health (CVH), the HR (95% confidence interval) for T2DM risk was 0.69 (0.56-0.85) and 0.35 (0.21-0.59) for men with intermediate and ideal CVHM, respectively. The corresponding values for women were 0.79 (0.65-0.97) and 0.30 (0.15-0.60), respectively. in a subpopulation with nutritional data (n=2236), ideal and intermediate nutritional status was associated with 83% and 77% lower risk of T2DM only among women (p-values<0.05). CONCLUSION We found a strong inverse association between having higher global ICVHM with incident T2DM; the issue is mainly attributable to normal blood pressure, normal body weight, and intensive physical activity (only for men).
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Affiliation(s)
- Samaneh Asgari
- Prevention of Metabolic Disorders Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Soroush Masrouri
- Prevention of Metabolic Disorders Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Somaye Hosseinpour‐Niazi
- Nutrition and Endocrine Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Nazanin Moslehi
- Nutrition and Endocrine Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Fereidoun Azizi
- Endocrine Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research CenterResearch Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
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15
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Xu C, Zhang P, Cao Z. Cardiovascular health and healthy longevity in people with and without cardiometabolic disease: A prospective cohort study. EClinicalMedicine 2022; 45:101329. [PMID: 35284807 PMCID: PMC8904213 DOI: 10.1016/j.eclinm.2022.101329] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/10/2022] [Accepted: 02/16/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Existing evidence suggest an association of cardiovascular health (CVH) level with cardiometabolic disease (CMD) and mortality, but the effect of CVH on life expectancy, particularly survival years in CMD patients, has not been well-established. This study aimed to investigate the association of CVH defined using the 7-item tool from the American Heart Association (AHA) with life expectancy in people with and without CMD. METHODS Between 2006 and 2010, a total of 341,331 participants (age 37-73 years) in the UK Biobank were examined and thereafter followed up to 2020. The CVH raised by the AHA included 4 behavioral (smoking, diet, physical activity, body mass index) and 3 biological (fasting glucose, blood cholesterol, blood pressure) metrics, coded on a three-point scale (0, 1, 2). The CVH score was the sum of 7 metrics (score range 0-14) and was then categorized into poor (scores 0-6), intermediate (7-11), and ideal (12-14) CVH. The flexible parametric survival models were applied to estimate life expectancy. FINDINGS During a median follow-up of 11.4 years, 18,420 (5.4%) deaths occurred. The multivariable-adjusted hazard ratio (HRs) of all-cause mortality were 2.21 (95% CI: 1.77 to 2.75) for male and 2.63 (95% CI: 2.22 to 3.12) for female with prevalent CMD and a poor CVH compared with CMD-free and ideal CVH group, an ideal CVH attenuated the CMD-related risk of mortality by approximately 62% for male and 53% for female. In CMD patients, an ideal CVH compared to poor CVH was associated with additional life years gain of 5.50 (95% CI: 3.94-7.05) for male 4.20 (95% CI: 2.77-5.62) for female at the age of 45 years. Corresponding estimates in those without CMD were 4.55 (95% CI: 3.62-5.48) and 4.89 (95% CI: 3.99-5.79), respectively. Ideal smoking status, fasting glucose and physical activity for male and ideal smoking status, cholesterol level and physical activity for female contributed to the greatest survival benefit. INTERPRETATION An ideal CVH is associated with a lower risk of premature mortality and longer life expectancy whether in general population or CMD patients. Our study highlights the benefits of maintaining better CVH across the life course and calls attention to the need for comprehensive strategies (healthy behavioral lifestyle and biological phenotypes) to preserve and restore a higher CVH level. FUNDING Scientific Research Foundation for Scholars of HZNU (Grant No. 4265C50221204119).
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Affiliation(s)
- Chenjie Xu
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Pengjie Zhang
- School of Public Health, Fudan University, Shanghai, China
| | - Zhi Cao
- School of Public Health, Zhejiang University School of Medicine, Yuhangtang Road 866, Hangzhou 310058, China
- Corresponding author.
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16
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Lassale C, Cene C, Asselin A, Sims M, Jouven X, Gaye B. Sociodemographic determinants of change in cardiovascular health in middle adulthood in a bi-racial cohort. Atherosclerosis 2022; 346:98-108. [DOI: 10.1016/j.atherosclerosis.2022.01.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/25/2021] [Accepted: 01/14/2022] [Indexed: 12/24/2022]
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17
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Dietary Approaches to Stop Hypertension (DASH) diet, Mediterranean diet and blood lipid profiles in less-developed ethnic minority regions. Br J Nutr 2021; 128:1137-1146. [PMID: 34605387 DOI: 10.1017/s0007114521004013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Different from developed countries, there is a paucity of research examining how the Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets relate to lipids in less-developed ethnic minority regions (LEMR). A total of 83 081 participants from seven ethnic groups were retrieved from the baseline data of the China Multi-Ethnic Cohort study, which was conducted in less-developed Southwest China between May 2018 and September 2019. Multivariable linear regression models were then used to examine the associations of the DASH and alternative Mediterranean diet (AMED) scores, assessed by modified DASH score and AMED, as well as their components with total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, TAG and TC/HDL-cholesterol. The DASH scores were negatively associated with TC, HDL-cholesterol and TAG. Comparing the highest quintiles with the lowest DASH scores, TC decreased 0·0708 (95 % CI -0·0923, -0·0493) mmol/l, HDL-cholesterol decreased 0·0380 (95 % CI -0·0462, -0·0299) mmol/l and TAG decreased 0·0668 (95 % CI -0·0994, -0·0341) mmol/l. The AMED scores were negatively associated with TC, LDL-cholesterol and HDL-cholesterol. Comparing the highest quintiles with the lowest AMED scores, TC decreased 0·0816 (95 % CI -0·1035, -0·0597) mmol/l, LDL-cholesterol decreased 0·0297 (95 % CI -0·0477, -0·0118) mmol/l and HDL-cholesterol decreased 0·0275 (95 % CI -0·0358, -0·0192) mmol/l. Although both the DASH diet and the Mediterranean diet were negatively associated with blood lipids, those associations showed different patterns in LEMR, particularly for TAG and HDL-cholesterol.
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18
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Wang K, Kavousi M, Voortman T, Ikram MA, Ghanbari M, Ahmadizar F. Cardiovascular health, genetic predisposition, and lifetime risk of type 2 diabetes. Eur J Prev Cardiol 2021; 28:1850-1857. [PMID: 34583386 DOI: 10.1093/eurjpc/zwab141] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/27/2021] [Accepted: 08/10/2021] [Indexed: 11/14/2022]
Abstract
AIMS Data on the lifetime risk of type 2 diabetes (T2D) incidence across different cardiovascular health (CVH) categories are scarce. Moreover, it remains unclear whether a genetic predisposition modifies this association. METHODS AND RESULTS Using data from the prospective population-based Rotterdam Study, a CVH score (body mass index, blood pressure, total cholesterol, smoking status, diet, and physical activity) was calculated and further categorized at baseline. Genetic predisposition to T2D was assessed and divided into tertiles by creating a genetic risk score (GRS). We estimated the lifetime risk for T2D within different CVH and GRS categories. Among 5993 individuals free of T2D at baseline [mean (standard deviation) age, 69.1 (8.5) years; 58% female], 869 individuals developed T2D during follow-up. At age 55 years, the remaining lifetime risk of T2D was 22.6% (95% CI: 19.4-25.8) for ideal, 28.3% (25.8-30.8) for intermediate, and 32.6% (29.0-36.2) for poor CVH. After further stratification by GRS tertiles, the lifetime risk for T2D was still the lowest for ideal CVH in the lowest GRS tertiles [21.5% (13.7-29.3)], in the second GRS tertile [20.8% (15.9-25.8)], and in the highest tertile [23.5% (18.5-28.6)] when compared with poor and intermediate CVH. CONCLUSION Our results highlight the importance of favourable CVH in preventing T2D among middle-aged individuals regardless of their genetic predisposition.
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Affiliation(s)
- Kan Wang
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus University Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
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Hu C, Zhang Y, Zhang J, Huo Y, Wan Q, Li M, Qi H, Du R, Zhu Y, Qin Y, Hu R, Shi L, Su Q, Yu X, Yan L, Qin G, Tang X, Chen G, Xu M, Wang T, Zhao Z, Chen Y, Gao Z, Wang G, Shen F, Luo Z, Chen L, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Chen L, Zhao J, Mu Y, Wang W, Xu Y, Bi Y, Lu J, Ning G. Age at menarche, ideal cardiovascular health metrics, and risk of diabetes in adulthood: Findings from the REACTION study. J Diabetes 2021; 13:458-468. [PMID: 33135296 DOI: 10.1111/1753-0407.13128] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 10/08/2020] [Accepted: 10/29/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Age at menarche was reported to be associated with the risk of diabetes. However, the impact of ideal cardiovascular health metrics (ICVHMs) on the association between age at menarche and adulthood diabetes risk was unclear. METHODS We included 121 431 women from the nationwide, population-based cohort of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals: a Longitudinal Study). The diagnosis of diabetes was based on the oral glucose tolerance test (OGTT) and glycosylated hemoglobin (HbA1c) measurement. Logistic regression and multiplicative interaction analysis were conducted to investigate the potential interaction effect between age at menarche and ICVHMs on the development of diabetes. RESULTS The multivariable-adjusted odds ratios of diabetes across categories of age at menarche (<14, 14-17, and > 17 years) were 1.22 (95% confidence interval [CI]: 1.17, 1.28), 1.00 (reference), and 0.89 (95% CI: 0.85, 0.93), respectively. In subgroup analysis, significant interactions were detected between total cholesterol/blood pressure levels and age at menarche regarding the risk of diabetes (P for interaction = .0091 and .0019, respectively). The increased risk associated with age at menarche <14 years was observed in participants with three or fewer ICVHMs, but not in women with four or more ICVHMs (P for interaction = .0001). CONCLUSIONS Age at menarche was inversely associated with the risk of diabetes in adulthood in Chinese women, and it appeared to be modified by the presence of ICVHMs. Further studies are needed to clarify the precise interrelationship and the generalizability of our results.
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Affiliation(s)
- Chunyan Hu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanan Huo
- Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China
| | - Qin Wan
- The Affiliated Hospital of Luzhou Medical College, Luzhou, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongyan Qi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui Du
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanyue Zhu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingfen Qin
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Ruying Hu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Lixin Shi
- Affiliated Hospital of Guiyang Medical College, Guiyang, China
| | - Qing Su
- Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xuefeng Yu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guijun Qin
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xulei Tang
- The First Hospital of Lanzhou University, Lanzhou, China
| | - Gang Chen
- Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhengnan Gao
- Dalian Municipal Central Hospital, Dalian, China
| | - Guixia Wang
- The First Hospital of Jilin University, Changchun, China
| | - Feixia Shen
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zuojie Luo
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Li Chen
- Qilu Hospital of Shandong University, Jinan, China
| | - Qiang Li
- The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhen Ye
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Yinfei Zhang
- Central Hospital of Shanghai Jiading District, Shanghai, China
| | - Chao Liu
- Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Youmin Wang
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shengli Wu
- Karamay Municipal People's Hospital, Xinjiang, China
| | - Tao Yang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huacong Deng
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lulu Chen
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiajun Zhao
- Shandong Provincial Hospital affiliated to Shandong University, Jinan, China
| | - Yiming Mu
- Chinese People's Liberation Army General Hospital, Beijing, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Cao Z, Li S, Yang H, Xu C, Zhang Y, Yang X, Yan T, Liu T, Wang Y. Associations of behaviors, biological phenotypes and cardiovascular health with risks of stroke and stroke subtypes: A prospective cohort study. EClinicalMedicine 2021; 33:100791. [PMID: 33842871 PMCID: PMC8020159 DOI: 10.1016/j.eclinm.2021.100791] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 02/20/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Although many cardiovascular risk factors for stroke have been reported before, it has not been investigated comprehensively for all major stroke types in large datasets. This study aimed to evaluate the associations of healthy behaviors, biological phenotypes and cardiovascular health (CVH) with long-term risks of strokes events, overall and stroke subtypes (ischemic stroke [IS], intracerebral hemorrhage [ICH], subarachnoid hemorrhage [SAH], and unspecified stroke). METHODS Between 2006 and 2010, a total of 354,976 participants (age 40-70 years) in the UK Biobank free of stroke and coronary heart disease were examined and thereafter followed up to 2020. According to American Heart Association guideline, the global CVH included four behavioral (smoking, diet, physical activity, body mass index) and three biological (blood glucose, blood cholesterol, blood pressure) metrics. The behavioral, biological and global CVH score was the sum of four, three, and seven metrics, respectively, and then was categorized into poor, intermediate and ideal group. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of stroke events. FINDINGS A total of 5804 incident stroke cases, including 3664 IS, 714 ICH and 453 SAH, were documented over a median follow-up of 11 years. The risk of stroke decreased significantly and linearly with both increasing behavioral CVH score and biological CVH score. Ideal behavioral CVH group was significantly associated with lower risks of all stroke subtypes, biological CVH was related to stroke events except for SAH. Additionally, the 1-point increment in global CVH score was associated with 11%,13%, 8% and 13% lower risks of stroke, IS, ICH and unspecified stroke, however, there was no significant dose-dependent association between global CVH and SAH. INTERPRETATION Our findings suggest inverse linear associations of behavioral, biological and global CVH with long-term risks of stroke and stroke subtypes, except for SAH, highlighting the benefits of maintaining better CVH status as a primordial prevention strategy of stroke. FUNDING The National Natural Science Foundation of China (71,910,107,004, 91,746,205).
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Affiliation(s)
- Zhi Cao
- School of Public Health, Tianjin Medical University, Tianjin, China
- Department of Big Data in Health Science, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Shu Li
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hongxi Yang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Chenjie Xu
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xueli Yang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Tao Yan
- Department of Neurology, Tianjin Neurological and Gerontology Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Tong Liu
- Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China
- Corresponding author.
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21
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Lu J, Li M, Xu Y, Bi Y, Qin Y, Li Q, Wang T, Hu R, Shi L, Su Q, Xu M, Zhao Z, Chen Y, Yu X, Yan L, Du R, Hu C, Qin G, Wan Q, Chen G, Dai M, Zhang D, Gao Z, Wang G, Shen F, Luo Z, Chen L, Huo Y, Ye Z, Tang X, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Li D, Lai S, Bloomgarden ZT, Chen L, Zhao J, Mu Y, Ning G, Wang W. Early Life Famine Exposure, Ideal Cardiovascular Health Metrics, and Risk of Incident Diabetes: Findings From the 4C Study. Diabetes Care 2020; 43:1902-1909. [PMID: 32499384 DOI: 10.2337/dc19-2325] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 04/23/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We aim to investigate the impact of ideal cardiovascular health metrics (ICVHMs) on the association between famine exposure and adulthood diabetes risk. RESEARCH DESIGN AND METHODS This study included 77,925 participants from the China Cardiometabolic Disease and Cancer Cohort (4C) Study who were born around the time of the Chinese Great Famine and free of diabetes at baseline. They were divided into three famine exposure groups according to the birth year, including nonexposed (1963-1974), fetal exposed (1959-1962), and childhood exposed (1949-1958). Relative risk regression was used to examine the associations between famine exposure and ICVHMs on diabetes. RESULTS During a mean follow-up of 3.6 years, the cumulative incidence of diabetes was 4.2%, 6.0%, and 7.5% in nonexposed, fetal-exposed, and childhood-exposed participants, respectively. Compared with nonexposed participants, fetal-exposed but not childhood-exposed participants had increased risks of diabetes, with multivariable-adjusted risk ratios (RRs) (95% CIs) of 1.17 (1.05-1.31) and 1.12 (0.96-1.30), respectively. Increased diabetes risks were observed in fetal-exposed individuals with nonideal dietary habits, nonideal physical activity, BMI ≥24.0 kg/m2, or blood pressure ≥120/80 mmHg, whereas significant interaction was detected only in BMI strata (P for interaction = 0.0018). Significant interactions have been detected between number of ICVHMs and famine exposure on the risk of diabetes (P for interaction = 0.0005). The increased risk was observed in fetal-exposed participants with one or fewer ICVHMs (RR 1.59 [95% CI 1.24-2.04]), but not in those with two or more ICVHMs. CONCLUSIONS The increased risk of diabetes associated with famine exposure appears to be modified by the presence of ICVHMs.
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Affiliation(s)
- Jieli Lu
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingfen Qin
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Qiang Li
- The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tiange Wang
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruying Hu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Lixin Shi
- Affiliated Hospital of Guiyang Medical College, Guiyang, China
| | - Qing Su
- Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuefeng Yu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Li Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Rui Du
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunyan Hu
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guijun Qin
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qin Wan
- The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Gang Chen
- Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Meng Dai
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Zhang
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhengnan Gao
- Dalian Municipal Central Hospital Affiliated to Dalian Medical University, Dalian, China
| | - Guixia Wang
- The First Hospital of Jilin University, Changchun, China
| | - Feixia Shen
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zuojie Luo
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Li Chen
- Qilu Hospital of Shandong University, Jinan, China
| | - Yanan Huo
- Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China
| | - Zhen Ye
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xulei Tang
- The First Hospital of Lanzhou University, Lanzhou, China
| | - Yinfei Zhang
- Central Hospital of Shanghai Jiading District, Shanghai, China
| | - Chao Liu
- Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Youmin Wang
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shengli Wu
- Karamay Municipal People's Hospital, Xinjiang, China
| | - Tao Yang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huacong Deng
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Shenghan Lai
- Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - Lulu Chen
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiajun Zhao
- Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Yiming Mu
- Chinese People's Liberation Army General Hospital, Beijing, China
| | - Guang Ning
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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