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Karipidou M, Liatis S, Kyrkili A, Skoufi A, Lambadiari V, Tigas S, Liberopoulos E, Kontogianni MD. Exploring the effect of adhering to a healthy lifestyle pattern on glycemic control in adults with type 1 diabetes mellitus. Nutr Metab Cardiovasc Dis 2025; 35:103868. [PMID: 39986932 DOI: 10.1016/j.numecd.2025.103868] [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: 09/22/2024] [Revised: 01/11/2025] [Accepted: 01/17/2025] [Indexed: 02/24/2025]
Abstract
BACKGROUND AND AIMS Diet, physical activity, sleep and smoking have been individually associated with glycemic control (GC) in adults with type 1 diabetes mellitus (T1D). However, the combined effect of these factors has not been investigated. The aim of the present study was to examine the single and combined effects of lifestyle parameters on GC of people with T1D (PwT1D). METHODS AND RESULTS Dietary, physical activity and sleep habits were evaluated using validated questionnaires. Diet quality was assessed with two scores (MedDietScore and PURE Diet Score) and two healthy lifestyle indices (HLI) were constructed (MLI based on MedDietScore and PLI based on PURE score). The score of both HLI ranged from 0 to 12 with higher scores indicating greater adherence to the healthy lifestyle pattern. One hundred ninety-two adults [61 % female, median age 42 (34, 51) years] with T1D were included in the analysis. Good GC (defined as HbA1c<7 %) was observed in 31 % of study participants. Examining lifestyle components separately, only smoking was marginally inversely associated with good GC [odds ratio (OR): 0.48, (95 % confidence interval, CI:0.23-1.00; p = 0.050)]. Individuals with better GC had significantly higher HLI scores (both p < 0.05). After adjusting for age, sex, body mass index, wearing an insulin pump and using continuous glucose monitoring, one-unit increase in the PLI was associated with 16 % higher likelihood of good GC (OR:1.16, 95 % CI:1.01-1.35, p = 0.04) and a similar trend was recorded for MLI (p = 0.05). CONCLUSION Our results suggest that adherence to a healthy lifestyle, more so than single lifestyle parameters, is associated with better GC in PwT1D.
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Affiliation(s)
- Melina Karipidou
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University of Athens, Athens, Greece
| | - Stavros Liatis
- First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens Medical School, Laiko General Hospital, Athens, Greece
| | - Athanasia Kyrkili
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University of Athens, Athens, Greece
| | - Alexandra Skoufi
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University of Athens, Athens, Greece
| | - Vaia Lambadiari
- Second Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, Athens, Greece
| | - Stelios Tigas
- Department of Endocrinology, University of Ioannina, Ioannina, Greece
| | - Evangelos Liberopoulos
- First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens Medical School, Laiko General Hospital, Athens, Greece
| | - Meropi D Kontogianni
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University of Athens, Athens, Greece.
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American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Echouffo-Tcheugui JB, Eichorst B, Ekhlaspour L, Garg R, Hassanein M, Khunti K, Lal R, Lingvay I, Matfin G, Middelbeek RJ, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Tanenbaum ML, Urbanski P, Bannuru RR. 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2025. Diabetes Care 2025; 48:S86-S127. [PMID: 39651983 PMCID: PMC11635047 DOI: 10.2337/dc25-s005] [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] [Indexed: 12/14/2024]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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López-Núñez C, Fernández-Artamendi S, Ruiz-Aranda D, Resurrección DM, Navas-Campaña D. A multicomponent smoking cessation program for adults with Type 2 Diabetes Mellitus ( DiMe-SALUD2 project): A study protocol of a randomized controlled trial. Contemp Clin Trials Commun 2024; 41:101361. [PMID: 39290519 PMCID: PMC11405626 DOI: 10.1016/j.conctc.2024.101361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/29/2024] [Accepted: 08/28/2024] [Indexed: 09/19/2024] Open
Abstract
Background Tobacco use represents a significant public health burden, being especially harmful for smokers with Type 2 Diabetes Mellitus (T2DM). Effective smoking cessation interventions are required for this vulnerable population. The goal is to describe a study protocol of a randomized controlled trial (RCT) aimed at analyzing the effectiveness and efficiency of a multicomponent smoking cessation intervention for T2DM smokers, including a training protocol on healthy lifestyle habits and self-management of T2DM (DiMe-SALUD2 project). Methods This RCT will assign participants to: (1) Control Group (n = 30), including a brief psychoeducation advice about smoking cessation; (2) Cognitive-behavioral treatment (CBT) for smoking cessation (n = 30), based on a multicomponent program implemented in group-based sessions over an eight-week period; and (3) CBT plus DiMeSALUD2 protocol (n = 30), which will develop an additional psychoeducational protocol specifically designed to improve healthy lifestyle habits. Participants will be assessed at baseline, post-treatment and several follow-ups (1-, 6- and 12-months). Primary outcomes will include smoking abstinence (24-h point prevalence abstinence at post-treatment and 7-day point prevalence at follow-ups) and smoking continuous abstinence. Secondary outcomes will include treatment retention, changes in smoking patterns and nicotine dependence, as well as the impact on T2DM clinical variables, mental health, and quality of life. Discussion The DiMeSALUD2 program could assist T2DM smokers in quitting tobacco use and improving their overall quality of life. This project will help incorporating improvements in routine clinical practice with T2DM patients, offering a smoking cessation program adapted to their specific needs. Trial registration ClinicalTrials.gov. Identifier: NCT05885659. Date of registration: June 2nd, 2023.
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Affiliation(s)
- Carla López-Núñez
- Department of Personality, Assessment and Psychological Treatments, School of Psychology, University of Seville, Seville (Andalusia), Spain
| | - Sergio Fernández-Artamendi
- Department of Personality, Assessment and Psychological Treatments, School of Psychology, University of Seville, Seville (Andalusia), Spain
| | - Desirée Ruiz-Aranda
- Department of Psychology, Universidad Loyola Andalucía, Seville (Andalusia), Spain
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Xu W, Li X, Tse G, Chan JSK, Wu S, Liu T. Control for multiple risk factors and incident heart failure and mortality in patients with diabetes mellitus: Insights from the Kailuan cohort study. Curr Probl Cardiol 2024; 49:102737. [PMID: 38944222 DOI: 10.1016/j.cpcardiol.2024.102737] [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: 06/26/2024] [Accepted: 06/26/2024] [Indexed: 07/01/2024]
Abstract
BACKGROUND This study evaluated the relationship between controlling multiple risk factors and diabetes-related heart failure and all-cause mortality, and the extent to which the excess risk can be reduced. METHODS 17,676 patients with diabetes and 69,493 matched non-diabetic control subjects were included in the Kailuan study, with a median follow-up of 11.19 years. The risk factor control was defined by the attainment of target values for systolic blood pressure, body mass index, low-density lipoprotein cholesterol, fasting blood glucose, high-sensitive C-reactive protein and smoking. Fine-Gray and Cox models were used to estimate associations between the degree of risk factor control and risk of heart failure and all-cause mortality respectively. RESULTS Among diabetes patients, there was a gradual reduction in the risk of outcomes as the degree of risk factor control increased. For each additional risk factor that was controlled, there was an associated 16 % decrease in heart failure risk and a 10 % decrease in all-cause mortality risk. Among diabetes patients with ≥5 well-controlled risk factors, the adjusted hazard ratio compared to controls for heart failure and all-cause mortality was 1.25 (95 %CI: 0.99-1.56) and 1.17(95 %CI: 1.05-1.31) respectively. The protective effect of comprehensive risk factor control on the risk of heart failure was more pronounced in men and those using antihypertensive medications. CONCLUSIONS Control for multiple risk factors is associated with reduced heart failure and all-cause mortality risks in a cumulative and sex-specific manner. However, despite optimization of risk factor control, diabetes patients still face increased risks compared to the general population.
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Affiliation(s)
- Wenqi Xu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No. 57 East Xinhua Road, Tangshan, 063000, China
| | - Xinmu Li
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Hexi District, Tianjin, 300211, China
| | - Gary Tse
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Hexi District, Tianjin, 300211, China; School of Nursing and Health Studies, Hong Kong Metropolitan University, Hong Kong, China
| | - Jeffrey Shi Kai Chan
- Cardiac Electrophysiology Unit, Cardiovascular Analytics Group, PowerHealth Limited, Hong Kong, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No. 57 East Xinhua Road, Tangshan, 063000, China.
| | - Tong Liu
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Hexi District, Tianjin, 300211, China.
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Grech J, Norman I, Azzopardi C, Grixti M, Sammut R. Assessing the feasibility and acceptability of a diabetes-specific nurse-led multicomponent smoking cessation intervention in diabetes education: study protocol for an open-label pragmatic randomised controlled trial. BMJ Open 2024; 14:e083235. [PMID: 38904126 PMCID: PMC11191808 DOI: 10.1136/bmjopen-2023-083235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 05/28/2024] [Indexed: 06/22/2024] Open
Abstract
INTRODUCTION Smoking cessation is an essential, but often overlooked aspect of diabetes management. Despite the need for tailored smoking cessation support for individuals with diabetes, evidence of effective interventions for this cohort is limited. Additionally, individuals with diabetes do not easily adopt such interventions, resulting in low uptake and abstinence rates. This protocol describes a study that aims to assess the feasibility and acceptability of a unique smoking cessation intervention, based on the best evidence, theory and the needs of individuals with diabetes, among patients and service providers, the diabetes nurse educators. METHODS AND ANALYSIS This is an open-label pragmatic randomised controlled trial. Between 80 and 100 individuals with type 1 or type 2 diabetes who smoke will be recruited from the diabetes outpatients at the main acute public hospital in Malta, starting in August 2023. Participants will be randomly assigned (1:1 ratio) to the intervention or control arm for 12 weeks. The experimental intervention will consist of three to four smoking cessation behavioural support sessions based on the 5As (Ask, Advise, Assess, Assist and Arrange) algorithm, and a 6-week supply of nicotine replacement therapy. The control intervention will consist of an active referral to the Maltese National Health Service's one-to-one smoking cessation support service, which is based on motivational interviewing. The primary feasibility and acceptability outcomes include the recruitment and participation rates, resources used, problems identified by the nurses, the nurses' perceived challenges and facilitators to implementation and the nurses' and patients' acceptability of the study intervention. Data analyses will be descriptive, with quantitative feasibility and acceptability outcomes reported with 95% confidence intervals. ETHICS AND DISSEMINATION Ethical clearance was obtained from the Faculty of Health Sciences Research Ethics Committee, University of Malta. The study results will be disseminated through conference presentations and a publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER NCT05920096.
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Affiliation(s)
- Joseph Grech
- Department of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta
| | - Ian Norman
- King's College London Florence Nightingale Faculty of Nursing Midwifery & Palliative Care, London, London, UK
| | | | - Moira Grixti
- Diabetes Education Unit, Mater Dei Hospital, Msida, Malta
| | - Roberta Sammut
- Department of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta
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Kim HJ, Cho YJ. Smoking cessation and risk of metabolic syndrome: A meta-analysis. Medicine (Baltimore) 2024; 103:e38328. [PMID: 39259087 PMCID: PMC11142813 DOI: 10.1097/md.0000000000038328] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 04/26/2024] [Accepted: 05/02/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Smoking is an important risk factor for various metabolic and cardiovascular disorders, and smoking cessation reduces the risk of these conditions. However, weight gain is commonly observed when individuals quit smoking, which often leads to hesitation in pursuing smoking cessation. Weight gain increases the risk of metabolic syndrome (MS). However, previous studies that investigated the relationship between smoking cessation and MS have yielded inconsistent results. Therefore, we conducted a meta-analysis to evaluate the association between smoking cessation and MS. METHODS Medline, Embase, Cochrane Library and CINAHL databases, were comprehensively searched from inception to April 2023, to identify relevant studies examining the relationship between smoking cessation and MS, comparing such relationship to that with active smoking. The methodological quality of the selected studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. A random-effects model was used for meta-analysis. RESULTS Of 495 identified studies, 24 were reviewed. The risk of selection bias was identified in all the studies. The overall analysis of 14 studies, including data of combined results for both men and women, revealed an increased risk of MS among ex-smokers compared with that among active smokers (pooled relative risk [RR] 1.18, 95% confidence interval [CI]: 1.08-1.29). From the selected studies, 13 studies analyzing men were extracted for subgroup analysis. Among men, no significant difference in the risk of developing MS was observed between ex-smokers and smokers (pooled RR: 1.05, 95% CI: 0.95-1.17). In men, the risk of MS increased if the cessation period was ≤15 years in men (pooled RR 1.26, 95% CI: 1.01-1.56) and slightly decreased if the cessation period was > 15 years (RR 0.84, 95% CI: 0.70-1.00) in ex-smokers compared with that in current smokers. CONCLUSION An increased risk of MS was observed in the early stages of smoking cessation compared with current smoking. As the longer duration of smoking cessation, the risk of MS becomes less significant.
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Affiliation(s)
- Hyun Ji Kim
- Department of Family Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
| | - Yoon Jeong Cho
- Department of Family Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
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Walicka M, Krysiński A, La Rosa GRM, Sun A, Campagna D, Di Ciaula A, Dugal T, Kengne A, Le Dinh P, Misra A, Polosa R, Raza SA, Russo C, Sammut R, Somasundaram N. Influence of quitting smoking on diabetes-related complications: A scoping review with a systematic search strategy. Diabetes Metab Syndr 2024; 18:103044. [PMID: 38810420 DOI: 10.1016/j.dsx.2024.103044] [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: 03/21/2024] [Revised: 05/13/2024] [Accepted: 05/17/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION Smoking in people with diabetes markedly elevates their risk of developing complications and increases the likelihood of cardiovascular mortality. This review is the first to specifically provide evidence-based analysis about the influence of quitting smoking on diabetes-related complications in people with type 2 diabetes. METHOD The present review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews. All human clinical studies assessing the effects of stopping smoking cessation on diabetes-related complications were included. PubMed and Embase were screened until January 2024. References of primary studies and principal peer-reviewed scientific journals in the field were manually screened. RESULTS We identified a total of 1023 studies. Only 26 met the criteria for eligibility. In general quitting smoking is associated with decreased risks of myocardial infarction and ischemic stroke. Regarding microvascular complications, the strongest evidence for the beneficial effects of smoking cessation is observed in diabetic nephropathy. However, the relationship between smoking cessation and retinopathy, neuropathy, diabetic foot complications and diabetic-related erectile dysfunction, is poorly investigated. CONCLUSION Quitting smoking offers significant advantages in managing diabetes-related complications, significantly lowering the risks of myocardial infarction, ischemic stroke, and diabetic nephropathy. This underscores the importance of cessation. Providing evidence-based information on the benefits of stopping smoking for people with type 2 diabetes who smoke, can bolster smoking cessation efforts in the context of diabetes management.
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Affiliation(s)
- Magdalena Walicka
- Department of Human Epigenetics, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland; Department of Internal Diseases, Endocrinology and Diabetology, National Medical Institute of the Ministry of the Interior and Administration, Warsaw, Poland.
| | - Arkadiusz Krysiński
- Department of Human Epigenetics, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland; Department of Internal Diseases, Endocrinology and Diabetology, National Medical Institute of the Ministry of the Interior and Administration, Warsaw, Poland
| | | | - Ang Sun
- Department of Biology, and Center for Biotechnology/Sbarro Institute for Cancer Research and Molecular Medicine, Temple University, Philadelphia, USA
| | - Davide Campagna
- Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Agostino Di Ciaula
- Clinica Medica "A. Murri" Department of Precision and Regenerative Medicine and Ionian Area [DiMePre-J], University "Aldo Moro" Medical School, Bari, Italy
| | - Tabinda Dugal
- Department of Endocrinology College of Physicians and Surgeons, Royal Cornwall Hospital NHS Trust, Truro, UK
| | - Andre Kengne
- Non-Communicable Diseases Research Unit, South African Medical Research Council and University of Cape Town, Cape Town, South Africa; Department of Biological and Environmental Science, Faculty of Science, Walter Sisulu University, Mthatha, South Africa
| | - Phuong Le Dinh
- General Practice, Family Medicine and Check-up Department, FV Hospital Ho Chi Minh City, Viet Nam
| | - Anoop Misra
- Diabetes Foundation [India], New Delhi, India; National Diabetes, Obesity and Cholesterol Foundation [N-DOC], New Delhi, India; Fortis C-DOC Centre for Excellence for Diabetes, Metabolic Disease, and Endocrinology, New Delhi, India
| | - Riccardo Polosa
- Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy; Center of Excellence for the acceleration of Harm Reduction [CoEHAR], University of Catania, Vietnam, Italy; Centre for the Prevention and Treatment of Tobacco Addiction (CPCT), University Teaching Hospital "Policlinico-Vittorio Emanuele", University of Catania, Catania, Italy
| | - Syed Abbas Raza
- Shaukat Khanum Cancer Hospital and Research Center, Peshawar, Pakistan
| | - Cristina Russo
- Ashford and Saint Peter's Hospitals NHS Foundation Trust, Chertsey, UK
| | - Roberta Sammut
- Department of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta
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Grech J, Norman IJ, Sammut R. Exploring the smoking cessation needs of individuals with diabetes using the Information-Motivation-Behavior Skills model. Tob Prev Cessat 2024; 10:TPC-10-07. [PMID: 38313659 PMCID: PMC10831727 DOI: 10.18332/tpc/181366] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/15/2024] [Accepted: 01/15/2024] [Indexed: 02/06/2024]
Abstract
INTRODUCTION Smoking cessation is an important aspect of diabetes management. Despite the increased risk for diabetes complications when smoking, evidence suggests that people living with type 1 and type 2 diabetes are less likely to quit smoking when compared to those without diabetes. Guided by the Information-Motivation-Behavioral Skills model, this study aimed to identify the needs of individuals living with type 1 and type 2 diabetes to quit smoking. METHODS A qualitative descriptive design was adopted. Semi-structured telephone interviews were held between April and June 2021, with 20 former and current Maltese smokers living with type 1 or type 2 diabetes, recruited from the diabetic clinics within the two main acute public hospitals. The interview transcriptions were analyzed using applied thematic analysis. RESULTS Individuals with diabetes need more information on the effects of smoking on diabetes to encourage cessation. Preventing diabetic complications was reported as a motivator to quit smoking. However, having diabetes was identified as a challenge to quitting. Participants welcomed the provision of health professional support for quitting smoking, identifying the need to provide smoking cessation support within diabetic clinics. The provision of information on tobacco-associated diabetic complications, by using video messages featuring former smokers' stories was also suggested. CONCLUSIONS To promote smoking cessation among individuals with diabetes, they need to be informed about how smoking affects their condition. Utilizing video messages featuring real-life stories of former smokers with diabetes who experienced tobacco-associated diabetic complications may be influential. Additionally, providing diabetes-specific intensive smoking cessation support is crucial to help them quit.
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Affiliation(s)
- Joseph Grech
- Department of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta
| | - Ian J. Norman
- Faculty of Nursing, Midwifery and Palliative Care, King’s College London, United Kingdom
| | - Roberta Sammut
- Department of Nursing, Faculty of Health Sciences, University of Malta, Msida, Malta
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Ahola AJ, Tikkanen-Dolenc H, Harjutsalo V, Groop PH. Clustering of risk behaviours and associations between risk behaviours and cardio-metabolic risk factors in adult individuals with type 1 diabetes. Diabetes Res Clin Pract 2024; 208:111115. [PMID: 38266825 DOI: 10.1016/j.diabres.2024.111115] [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: 12/15/2023] [Revised: 01/17/2024] [Accepted: 01/20/2024] [Indexed: 01/26/2024]
Abstract
AIMS To assess clustering of risk behaviours and their health determinants. METHODS Cross-sectional health behaviour and health data were collected from individuals with type 1 diabetes, in the FinnDiane Study. Clustering of risk behaviours was assessed and associations between behaviours and health variables were investigated. RESULTS Data were available from 956 participants (40 % men, mean age 46 years). Altogether, 4.3 % individuals reported no risk behaviours, while 25.7 %, 37.4 %, 24.7 %, 6.8 %, and 1.0 % reported 1, 2, 3, 4, and 5 risk behaviours, respectively. Reporting ≥4 risk behaviours occurred more frequently than expected by chance. Dietary non-adherence was most frequently reported (84.4 %), followed by low LTPA (54.4 %), poor sleep (41.9 %), high alcohol consumption (15.2 %), and smoking (11.2 %). Adjusted for confounders, relative to ≤1 risk behaviour, reporting ≥2 risk behaviours was associated with higher BMI, waist circumference, and diastolic blood pressure. Having ≥3 risk behaviours was associated with larger waist-hip ratio, and higher HbA1c and triglyceride concentration; ≥4 risk behaviours was associated with higher cholesterol concentration. Of the health behaviours, low LTPA had the highest number of deleterious health associations. CONCLUSIONS Accumulation of risk behaviors increases negative health outcomes. Exhibiting ≥2 risk behaviours or low LTPA was associated with multiple adverse outcomes.
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Affiliation(s)
- Aila J Ahola
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland
| | - Heidi Tikkanen-Dolenc
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland; National Institute for Health and Welfare, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland; Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland; Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
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American Diabetes Association Professional Practice Committee, ElSayed NA, Aleppo G, Bannuru RR, Beverly EA, Bruemmer D, Collins BS, Darville A, Ekhlaspour L, Hassanein M, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2024. Diabetes Care 2024; 47:S77-S110. [PMID: 38078584 PMCID: PMC10725816 DOI: 10.2337/dc24-s005] [Citation(s) in RCA: 103] [Impact Index Per Article: 103.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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Jafari N, Bahreini N, Dehghani A, Lak Y, Mirmohammadali SN, Samavat S, Shami A, Karimizand M, Goudarzi MA, Asbaghi O. The effects of purslane consumption on lipid profile and C-reactive protein: A systematic review and dose-response meta-analysis. Food Sci Nutr 2023; 11:6728-6748. [PMID: 37970383 PMCID: PMC10630813 DOI: 10.1002/fsn3.3555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 06/21/2023] [Accepted: 06/24/2023] [Indexed: 11/17/2023] Open
Abstract
Earlier investigations into the impact of purslane, Portulaca oleracea, on lipid profile and C-reactive protein (CRP) produced contradictory findings. The effect of purslane consumption on lipid profiles and CRP was assessed in this comprehensive review and meta-analysis. We conducted a thorough literature search in online databases, including PubMed, Scopus, the Cochrane library, and ISI Web of Science to find relevant randomized controlled trials up to June 2023. By incorporating 14 effect sizes from 13 RCTs, we were able to show that purslane consumption significantly decreases serum triglyceride (TG) (WMD: -16.72, 95% CI: -22.49, -10.96 mg/dL, p < .001), total cholesterol (TC) (WMD: -9.97, 95% CI: -19.86, -0.07 mg/dL, p = .048), and CRP (WMD: -1.22, 95% CI: -1.63, -0.80 mg/L, p < .001) levels in patients compared to the control group. In addition, purslane consumption significantly increases high-density lipoprotein (HDL-C) (WMD: 4.09, 95% CI: 1.77, 6.41 mg/dL, p = .001) levels. However, purslane consumption did not affect low-density lipoprotein (LDL-C) levels. According to a suggested optimal dosage, purslane consumption is considered to be safe up to 30 g/day. Purslane consumption can significantly improve cardiovascular health by improving lipid profile and inflammation status.
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Affiliation(s)
- Naser Jafari
- University of Applied Science and Technology – Allameh Tabarsi CenterTehranIran
| | - Nazgol Bahreini
- Student Research CommitteeTabriz University of Medical SciencesTabrizIran
- Nutrition Research Center, School of Nutrition and Food SciencesTabriz University of Medical SciencesTabrizIran
| | - Azadeh Dehghani
- Nutrition Research Center, Department of Community Nutrition, Faculty of Nutrition and Food ScienceTabriz University of Medical SciencesTabrizIran
| | | | | | - Simin Samavat
- Department of Cellular and Molecular Nutrition, School of Nutrition Sciences and DieteticsTehran University of Medical SciencesTehranIran
| | - Amirhossein Shami
- Student of Cellular Molecular Biology, Faculty of ScienceArdabil Branch, Islamic Azad UniversityArdabilIran
| | | | | | - Omid Asbaghi
- Cancer Research CenterShahid Beheshti University of Medical sciencesTehranIran
- Student Research CommitteeShahid Beheshti University of Medical SciencesTehranIran
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12
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Hegmann KT, Thiese MS, Wood EM, Kapellusch J, Foster JC, Drury DL, Kendall R, Merryweather AS. Cardiovascular Disease Risk Factors Predict the Development and Numbers of Common Musculoskeletal Disorders in a Prospective Cohort. J Occup Environ Med 2023; 65:e527-e533. [PMID: 37264528 PMCID: PMC10417266 DOI: 10.1097/jom.0000000000002895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
OBJECTIVE The aim of the study is to assess risk of common musculoskeletal disorders (MSDs) based on cardiovascular disease (CVD) risk scores. METHODS Data from a 9-year prospective cohort of 1224 workers in three states were analyzed. Baseline data included questionnaires, structured interviews, physical examinations, anthropometric measurements, nerve conduction studies, and individualized measurement of job physical factors. Monthly follow-ups were conducted. Framingham risk scores were calculated. A priori case definitions were constructed for carpal tunnel syndrome, lateral epicondylopathy, medial epicondylopathy, and rotator cuff tendinopathy. RESULTS Adjusted RRs for one or more MSDs increased to 3.90 (95% confidence interval, 2.20-6.90) among those with 10-year cardiovascular disease risk scores greater than 15% and 17.4 (95% confidence interval, 3.85-78.62) among those with more than 4 disorders. CONCLUSIONS Cardiovascular disease factors are strongly associated with the subsequent development of common MSDs. Risks among those with multiple MSDs are considerably stronger.
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13
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Gherasim A, Oprescu AC, Gal AM, Burlui AM, Mihalache L. Lifestyle Patterns in Patients with Type 2 Diabetes. Metabolites 2023; 13:831. [PMID: 37512538 PMCID: PMC10385226 DOI: 10.3390/metabo13070831] [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: 06/15/2023] [Revised: 07/05/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
Modern lifestyles have led to sedentary behavior, lower participation in active movement and physical activities during leisure time, unhealthy diets, and increased exposure to stress. It is important to examine the interaction of several lifestyle risk factors instead of focusing on one alone. The purpose of this study was to identify lifestyle patterns in a group of patients with type 2 diabetes and the associations of its components with certain metabolic parameters. Using principal component analysis, we identified three dietary patterns: the prudent pattern (fat, oil, cereals, potatoes, vegetables, fish, nuts, seeds and fruits), the Western pattern (meat and meat products, eggs and soft drinks) and the traditional pattern (milk and its derivatives, soups and sauces, with a low intake of sugar/snacks). In addition, using the same method of analysis, we identified two lifestyle patterns: the inadequate lifestyle pattern (Western dietary pattern, increased hours of sleep and lower levels of stress) and the traditional lifestyle pattern (traditional dietary pattern, increased physical activity (PA) and non-smoking status). The inadequate lifestyle pattern was associated with younger age, hypertension and diabetic neuropathy. The traditional lifestyle pattern was related to lower postprandial blood glucose levels. Sedentary individuals were more likely to be over 65 years old and to have higher glycated hemoglobin (HbA1c). Smokers were also more likely to have inadequate glycemic and lipid profile control.
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Affiliation(s)
- Andreea Gherasim
- Department of Internal Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Andrei C Oprescu
- Department of Morpho-Functional Studies, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ana Maria Gal
- College of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Alexandra Maria Burlui
- Department of Rheumatology and Medical Rehabilitation, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Laura Mihalache
- Department of Internal Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
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14
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Grech J, Norman IJ, Sammut R. Helping smokers with diabetes quit: A scoping review of the interventions utilised, and the challenges and barriers to smoking cessation. Prim Care Diabetes 2023; 17:119-128. [PMID: 36681570 DOI: 10.1016/j.pcd.2023.01.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 12/19/2022] [Accepted: 01/11/2023] [Indexed: 01/21/2023]
Abstract
Tobacco smoking is recognised as a priority in diabetes management, yet many individuals with diabetes continue to smoke beyond diagnosis. This paper identifies the most promising smoking cessation strategies by reviewing the literature reporting interventions carried out amongst this study population, and the challenges and barriers to smoking cessation. Stand-alone smoking cessation interventions which included pharmacotherapy were found to be more successful in achieving abstinence than interventions which included smoking cessation as part of a broader intervention for improving diabetes management. Misconceptions about smoking and diabetes management were frequently reported, undervaluing smoking cessation. This emphasizes further the need to inform smokers with diabetes about the link between tobacco use and diabetes complications.
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Affiliation(s)
- Joseph Grech
- Department of Nursing, Faculty of Health Sciences, University of Malta, Mater Dei Hospital, Msida MSD 2080, Malta.
| | - Ian James Norman
- Faculty of Nursing, Midwifery & Palliative Care, King's College London, United Kingdom
| | - Roberta Sammut
- Department of Nursing, Faculty of Health Sciences, University of Malta, Mater Dei Hospital, Msida MSD 2080, Malta
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15
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ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, Collins BS, Hilliard ME, Isaacs D, Johnson EL, Kahan S, Khunti K, Leon J, Lyons SK, Perry ML, Prahalad P, Pratley RE, Seley JJ, Stanton RC, Young-Hyman D, Gabbay RA, on behalf of the American Diabetes Association. 5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2023. Diabetes Care 2023; 46:S68-S96. [PMID: 36507648 PMCID: PMC9810478 DOI: 10.2337/dc23-s005] [Citation(s) in RCA: 199] [Impact Index Per Article: 99.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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16
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Grech J, Norman IJ, Sammut R. Effectiveness of intensive stand-alone smoking cessation interventions for individuals with diabetes: A systematic review and intervention component analysis. Tob Induc Dis 2023; 21:57. [PMID: 37181460 PMCID: PMC10170650 DOI: 10.18332/tid/162329] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/20/2023] [Accepted: 03/16/2023] [Indexed: 05/16/2023] Open
Abstract
INTRODUCTION Tobacco smoking poses a significant threat to the health of individuals living with diabetes. Intensive stand-alone smoking cessation interventions, such as multiple or long (>20 minutes) behavioral support sessions focused solely on smoking cessation, with or without the use of pharmacotherapy, increase abstinence when compared to brief advice or usual care in the general population. However, there is limited evidence so far for recommending the use of such interventions amongst individuals with diabetes. This study aimed to assess the effectiveness of intensive stand-alone smoking cessation interventions for individuals living with diabetes and to identify their critical features. METHODS A systematic review design with the addition of a pragmatic intervention component analysis using narrative methods was adopted. The key terms 'diabetes mellitus' and 'smoking cessation' and their synonyms were searched in 15 databases in May 2022. Randomized controlled trials which assessed the effectiveness of intensive stand-alone smoking cessation interventions by comparing them to controls, specifically amongst individuals with diabetes, were included. RESULTS A total of 15 articles met the inclusion criteria. Generally, the identified studies reported on the delivery of a multi-component behavioral support smoking cessation intervention for individuals with type I and type II diabetes, providing biochemically verified smoking abstinence rates at follow-up at six months. The overall risk-of-bias of most studies was judged to be of some concern. Despite observing inconsistent findings across the identified studies, interventions consisting of three to four sessions, lasting more than 20 min each, were found to be more likely to be associated with smoking cessation success. The additional use of visual aids depicting diabetes-related complications may also be useful. CONCLUSIONS This review provides evidence-based smoking cessation recommendations for use by individuals with diabetes. Nonetheless, given that the findings of some studies were found to be possibly at risk-of-bias, further research to establish the validity of the provided recommendations is suggested.
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Affiliation(s)
- Joseph Grech
- Department of Nursing, Faculty of Health Sciences, University of Malta, Mater Dei Hospital, Msida, Malta
| | - Ian J. Norman
- Faculty of Nursing, Midwifery and Palliative Care, King’s College London, London, United Kingdom
| | - Roberta Sammut
- Department of Nursing, Faculty of Health Sciences, University of Malta, Mater Dei Hospital, Msida, Malta
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17
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Hong X, Wu Z, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Gao W, Li L. Longitudinal Association of DNA Methylation With Type 2 Diabetes and Glycemic Traits: A 5-Year Cross-Lagged Twin Study. Diabetes 2022; 71:2804-2817. [PMID: 36170668 DOI: 10.2337/db22-0513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/20/2022] [Indexed: 01/11/2023]
Abstract
Investigators of previous cross-sectional epigenome-wide association studies (EWAS) in adults have reported hundreds of 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with type 2 diabetes mellitus (T2DM) and glycemic traits. However, the results from EWAS have been inconsistent, and longitudinal observations of these associations are scarce. Furthermore, few studies have investigated whether DNA methylation (DNAm) could be modified by smoking, drinking, and glycemic traits, which have broad impacts on genome-wide DNAm and result in altering the risk of T2DM. Twin studies provide a valuable tool for epigenetic studies, as twins are naturally matched for genetic information. In this study, we conducted a systematic literature search in PubMed and Embase for EWAS, and 214, 33, and 117 candidate CpG sites were selected for T2DM, HbA1c, and fasting blood glucose (FBG). Based on 1,070 twins from the Chinese National Twin Registry, 67, 17, and 16 CpG sites from previous studies were validated for T2DM, HbA1c, and FBG. Longitudinal review and blood sampling for phenotypic information and DNAm were conducted twice in 2013 and 2018 for 308 twins. A cross-lagged analysis was performed to examine the temporal relationship between DNAm and T2DM or glycemic traits in the longitudinal data. A total of 11 significant paths from T2DM to subsequent DNAm and 15 paths from DNAm to subsequent T2DM were detected, suggesting both directions of associations. For glycemic traits, we detected 17 cross-lagged associations from baseline glycemic traits to subsequent DNAm, and none were from the other cross-lagged direction, indicating that CpG sites may be the consequences, not the causes, of glycemic traits. Finally, a longitudinal mediation analysis was performed to explore the mediation effects of DNAm on the associations of smoking, drinking, and glycemic traits with T2DM. No significant mediations of DNAm in the associations linking smoking and drinking with T2DM were found. In contrast, our study suggested a potential role of DNAm of cg19693031, cg00574958, and cg04816311 in mediating the effect of altered glycemic traits on T2DM.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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18
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Durlach V, Vergès B, Al-Salameh A, Bahougne T, Benzerouk F, Berlin I, Clair C, Mansourati J, Rouland A, Thomas D, Thuillier P, Tramunt B, Le Faou AL. Smoking and diabetes interplay: A comprehensive review and joint statement. DIABETES & METABOLISM 2022; 48:101370. [PMID: 35779852 DOI: 10.1016/j.diabet.2022.101370] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
Evidence shows that smoking increases the risk of pre-diabetes and diabetes in the general population. Among persons with diabetes, smoking has been found to increase the risk of all-cause mortality and aggravate chronic diabetic complications and glycemic control. The current paper, which is a joint position statement by the French-Speaking Society on Tobacco (Société Francophone de Tabacologie) and the French-Speaking Society of Diabetes (Société Francophone du Diabète), summarizes the data available on the association between smoking and diabetes and on the impact of smoking and smoking cessation among individuals with type 1, type 2, and gestational diabetes mellitus. It also provides evidence-based information about the pharmacological and behavioral strategies for smoking cessation in these patients.
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Affiliation(s)
- Vincent Durlach
- Champagne-Ardenne University, UMR CNRS 7369 MEDyC & Cardio-Thoracic Department, Reims University Hospital, Reims, France.
| | - Bruno Vergès
- Department of Endocrinology, Diabetology and Metabolic Diseases, CHU Dijon, Dijon, France; INSERM LNC-UMR1231, University of Burgundy, Dijon, France
| | - Abdallah Al-Salameh
- Department of Endocrinology, Diabetes Mellitus and Nutrition, Amiens University Hospital, Amiens, France; PériTox = UMR-I 01, University of Picardy Jules Verne, Amiens, France
| | - Thibault Bahougne
- Department of Endocrinology and Diabetology, Strasbourg University Hospital, Strasbourg, France; Institute of Cellular and Integrative Neuroscience, CNRS UPR-3212, Strasbourg, France
| | - Farid Benzerouk
- Cognition Health and Society Laboratory (EA 6291), University of Reims Champagne-Ardenne, Reims, France; Department of Psychiatry, Reims University Hospital, Reims, France
| | - Ivan Berlin
- Department of Pharmacology, Hôpital Pitié-Salpêtrière, AP-HP, Paris, France
| | - Carole Clair
- Department of Training, Research and Innovation, Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
| | - Jacques Mansourati
- EA 4324 ORPHY, University of Western Brittany, Brest, France; Department of Cardiology, University Hospital of Brest, Brest, France
| | - Alexia Rouland
- Department of Endocrinology, Diabetology and Metabolic Diseases, CHU Dijon, Dijon, France
| | - Daniel Thomas
- Institute of Cardiology, Hôpital Pitié-Salpêtrière, Sorbonne University, Paris, France
| | - Philippe Thuillier
- Department of Endocrinology, Diabetology and Metabolic Diseases, University Hospital of Brest, Brest, France
| | - Blandine Tramunt
- Institute of Metabolic and Cardiovascular Diseases, UMR1297 INSERM/UPS, Toulouse University, Toulouse, Franc; Department of Diabetology, Metabolic Diseases and Nutrition, Toulouse University Hospital, Toulouse, France
| | - Anne-Laurence Le Faou
- Outpatient Addiction Center, Georges Pompidou European Hospital, AP-HP, Sorbonne Paris Cité, Paris, France
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Daniels TE, Zitkovsky EK, Kunicki ZJ, Price DJ, Peterson AL, Dennery PA, Kao HT, Price LH, Tyrka AR, Abrantes AM. Associations of circulating cell-free DNA, C-reactive protein, and cardiometabolic risk among low-active smokers with elevated depressive symptoms. Brain Behav Immun Health 2022; 25:100519. [PMID: 36164463 PMCID: PMC9508337 DOI: 10.1016/j.bbih.2022.100519] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/13/2022] [Accepted: 09/18/2022] [Indexed: 01/31/2023] Open
Abstract
Background and aims Cell-free DNA (cfDNA) is elevated in several disease states. Metabolic syndrome is a constellation of factors associated with poor cardiometabolic outcomes. This study examined associations of cfDNA from the nucleus (cf-nDNA) and mitochondria (cf-mtDNA), C-reactive protein (CRP), and metabolic syndrome risk, in low-active smokers with depressive symptoms. Methods Participants (N = 109; mean age 47) self-reported medical history. Physical activity was determined by accelerometry and anthropometrics were measured. Blood was collected and analyzed for cf-nDNA, cf-mtDNA, CRP, triglycerides, high-density lipoprotein, hemoglobin A1c. A continuous metabolic syndrome composite risk score was calculated. Relationships of cf-nDNA, cf-mtDNA, CRP, and cardiometabolic risk were examined with correlations and linear regression. Results CRP and cf-nDNA were significantly associated with metabolic syndrome risk (r = .39 and r = .31, respectively), cf-mtDNA was not (r = .01). In a linear regression, CRP and cf-nDNA significantly predicted the metabolic syndrome risk score, findings that remained significant controlling for age, gender, nicotine dependence, and physical activity. Conclusions Associations of cf-nDNA with both CRP and metabolic risk suggest a role for cf-nDNA in inflammatory processes associated with metabolic syndrome. The negative findings for cf-mtDNA suggest distinct roles for cf-nDNA and cf-mtDNA in these processes.
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Affiliation(s)
- Teresa E. Daniels
- Mood Disorders Research Program and Laboratory for Clinical and Translational, Neuroscience, Butler Hospital, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Initiative on Stress, Trauma, and Resilience (STAR), Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA,Corresponding author. 1011 Veterans Memorial Parkway, Riverside, RI, 02915, USA.
| | - Emily K. Zitkovsky
- Mood Disorders Research Program and Laboratory for Clinical and Translational, Neuroscience, Butler Hospital, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Zachary J. Kunicki
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Destiny J. Price
- Department of Psychiatry, New York State Psychiatric Institute and Columbia University Irving Medical Center, 1051 Riverside Dr, New York, NY, 10032, USA
| | - Abigail L. Peterson
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, USA
| | - Phyllis A. Dennery
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, USA,Department of Pediatrics, Warren Alpert Medical School of Brown University, 593 Eddy St, Providence, RI, 02903, USA
| | - Hung-Teh Kao
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Lawrence H. Price
- Mood Disorders Research Program and Laboratory for Clinical and Translational, Neuroscience, Butler Hospital, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Audrey R. Tyrka
- Mood Disorders Research Program and Laboratory for Clinical and Translational, Neuroscience, Butler Hospital, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Initiative on Stress, Trauma, and Resilience (STAR), Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Ana M. Abrantes
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI, 02906, USA,Behavioral Medicine and Addictions Research Department, Butler Hospital, 345 Blackstone Boulevard, Providence, RI, 02906, USA
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20
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Kar D, El-Wazir A, Delanerolle G, Forbes A, Sheppard JP, Nath M, Joy M, Cole N, Arnold JR, Lee A, Feher M, Davies MJ, Khunti K, de Lusignan S, Goyder E. Predictors and determinants of albuminuria in people with prediabetes and diabetes based on smoking status: A cross-sectional study using the UK Biobank data. EClinicalMedicine 2022; 51:101544. [PMID: 35813092 PMCID: PMC9256818 DOI: 10.1016/j.eclinm.2022.101544] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 06/11/2022] [Accepted: 06/14/2022] [Indexed: 11/28/2022] Open
Abstract
Background Smoking is attributed to both micro- and macrovascular complications at any stage of metabolic deregulation including prediabetes. Current global diabetes prevention programmes appear to be glucocentric, and do not fully acknowledge the ramifications of cardiorenal risk factors in smokers and ex-smokers. A more holistic approach is needed to prevent vascular complications in people with prediabetes and diabetes before and after quitting. Methods A cross-sectional study was carried out on participants who agreed to take part in the UK Biobank dataset at the time of their first attendances between March 01, 2006, and December 31, 2010. Those who had their urinary albumin concentration (UAC) data available were included, and those who did not have this data, were excluded. A logistic regression model was fitted to explore the relationship between cardiorenal risk factors and albuminuria in people with prediabetes and diabetes, based on smoking status. Findings A total of 502,490 participants were included in the UK Biobank dataset. Of them, 30.4% (n=152,896) had their UAC level recorded. Compared with non-smokers, the odds of albuminuria in smokers with prediabetes and diabetes were 1.21 (95% CI 1.05 - 1.39, p=0.009), and 1.26 (95% CI 1.10 - 1.44, p=0.001), respectively. The odds declined after quitting in both groups, but it was not statistically significant (p>0.05). Each unit increase in HbA1c was associated with equivalent increased odds of albuminuria in current and ex-smokers, OR 1.035 (95% CI 1.030 - 1.039, p<0.001), and 1.026 (95% CI 1.023 - 1.028, p <0.001), respectively. Compared to females, male ex-smokers were at 15% increased odds of albuminuria. In ex-smokers, each unit increase in waist circumference was associated with 1% increased risk of albuminuria. Compared with the least deprived quintiles, the odds of albuminuria in the most deprived quintiles, in current and ex-smokers were identical, OR 1.18 (95% CI 1.04-1.324, p=0.010), and 1.19 (95% CI 1.11 - 1.27, p<0.001), respectively. Interpretation Male smokers are at a higher risk of albuminuria after smoking cessation. Monitoring waist circumference in quitters may identify those who are at a higher risk of albuminuria. Combining smoking cessation intervention in smokers with prediabetes in the current diabetes prevention programmes may offset post-cessation weight gain and reduce the risk of albuminuria. Funding University of Sheffield.
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Affiliation(s)
- Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
- School of Health and Related Research, The University of Sheffield, Sheffield, UK
- National Institute for Health and Care Excellence, UK
- NHS England and Improvement, UK
| | - Aya El-Wazir
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
- Centre of Excellence in Molecular and Cellular Medicine, Suez Canal University, Ismailia, Egypt
| | | | - Anna Forbes
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
- Renal Unit, Epsom and St. Helier University Hospital NHS Trust, London, UK
| | - James P. Sheppard
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Mintu Nath
- Medical Statistics Team, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
| | - Nicholas Cole
- Renal Unit, Epsom and St. Helier University Hospital NHS Trust, London, UK
| | - J. Ranjit Arnold
- Department of Cardiovascular Sciences, Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Andrew Lee
- School of Health and Related Research, The University of Sheffield, Sheffield, UK
| | - Michael Feher
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
- Department of Clinical Chemistry, Chelsea and Westminster Hospital, London, UK
| | - Melanie J. Davies
- Leicester Diabetes Research Centre, University of Leicester, Leicester, UK
- University Hospitals of Leicester NHS Trust, Leicester, UK
- Department of Diabetes, Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Kamlesh Khunti
- Leicester Diabetes Research Centre, University of Leicester, Leicester, UK
- Department of Diabetes, Leicester NIHR Biomedical Research Centre, Leicester, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
- Royal College of General Practitioners, London, UK
| | - Elizabeth Goyder
- School of Health and Related Research, The University of Sheffield, Sheffield, UK
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21
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Walicka M, Russo C, Baxter M, John I, Caci G, Polosa R. Impact of stopping smoking on metabolic parameters in diabetes mellitus: A scoping review. World J Diabetes 2022; 13:422-433. [PMID: 35800409 PMCID: PMC9210544 DOI: 10.4239/wjd.v13.i6.422] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/01/2022] [Accepted: 05/21/2022] [Indexed: 02/06/2023] Open
Abstract
The purpose of this scoping review is to create a single narrative that describes the impact of smoking cessation on metabolic parameters in people with diabetes. It is generally well accepted that smoking enhances the harmful effects of elevated blood glucose levels, accelerating the vascular damage seen in patients with diabetes. Smoking cessation has clear benefits in terms of reducing cardiovascular morbidity and mortality. However, there is less evidence for the impact of smoking cessation on other diabetes-related complications. Studies in people with diabetes have shown improvement as well as temporary deterioration in glycemic control after ceasing smoking. Only a few studies have described the effect of quitting smoking on insulin resistance and lipid parameters, however, their results have been inconclusive. In this situation, healthcare professionals should not assume that cessation of smoking will improve metabolic parameters in patients with diabetes. It seems they should, first of all, emphasize the prevention of weight gain that may be associated with quitting smoking. The lack of data regarding the metabolic effects of smoking and smoking cessation in diabetes is very disappointing and this area needs to be addressed.
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Affiliation(s)
- Magdalena Walicka
- Department of Human Epigenetics, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw 02-106, Poland
- Department of Internal Diseases, Endocrinology and Diabetology, Central Clinical Hospital of the Ministry of Interior and Administration in Warsaw, Warsaw 02-507, Poland
- Department of Clinical and Experimental Medicine, University of Catania, Catania 95123, Italy
| | - Cristina Russo
- Ashford and Saint Peter's Hospitals NHS Foundation Trust, Chertsey KT16 0PZ, United Kingdom
| | - Michael Baxter
- Ashford and Saint Peter's Hospitals NHS Foundation Trust, Chertsey KT16 0PZ, United Kingdom
| | - Isaac John
- Ashford and Saint Peter's Hospitals NHS Foundation Trust, Chertsey KT16 0PZ, United Kingdom
| | - Grazia Caci
- Department of Clinical and Experimental Medicine, University of Messina, Messina 98124, Italy
| | - Riccardo Polosa
- Department of Clinical and Experimental Medicine, University of Catania, Catania 95123, Italy
- Center of Excellence for The Acceleration of HArm Reduction (CoEHAR), University of Catania, Cataia 95123, Italy
- Centre for The Prevention and Treatment of Tobacco Addiction (CPCT), Teaching Hospital "Policlinico-V. Emanuele", Catania 95123, Italy
- ECLAT Srl, Spin-off of the University of Catania, Catania 95123, Italy
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22
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Arnesen EK, Retterstøl K. Secular trends in serum lipid profiles in young adults in Norway, 2001-19. ATHEROSCLEROSIS PLUS 2022; 48:60-67. [PMID: 36644560 PMCID: PMC9833235 DOI: 10.1016/j.athplu.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/09/2022] [Accepted: 03/21/2022] [Indexed: 01/18/2023]
Abstract
Background Lower prevalence of major cardiovascular disease (CVD) risk factors, such as dyslipidemia, hypertension and smoking, can explain a substantial part of the decline in CVD mortality and incidence for the past decades in Western countries. However, some studies have indicated less favorable trends in risk factors in recent years. We have assessed time trends in lipid profiles among young adults in Norway measured between 2001 and 2019. Methods Samples of serum lipids analyzed at one large medical laboratory in Oslo, Norway, mainly requisitioned by primary care physicians, were analyzed cross-sectionally to estimate year-to-year trends among men and women aged 18-49 years. We also assessed the lipid distributions and proportions with adverse lipid levels. Results In total, more than 2,6 million blood samples, comprising more than 1 million individuals (mean age 37.7 years) from all regions of Norway were included. All measures improved among all age groups in both women and men, especially in total and non-HDL cholesterol (-0.22 and -0.25 mmol/l per decade, respectively). There were downward shifts in the population distribution of total, non-HDL-C and LDL-C. The overall prevalences of total cholesterol ≥5.0 mmol/l and non-HDL-C ≥3.9 mmol/l similarly decreased, from ∼63 to 46% and from ∼52 to 34%, respectively. More than 1/3 had elevated levels of total and/or non-HDL-C in 2019. Conclusion In a large proportion of the Norwegian population aged 18-49 years old, the lipid profiles improved during the last two decades. As the use of lipid-lowering medications is low in this age group, this likely reflects favorable secular trends.
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Affiliation(s)
- Erik Kristoffer Arnesen
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O.Box 1046 Blindern, 0317, Oslo, Norway,Corresponding author.
| | - Kjetil Retterstøl
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, P.O.Box 1046 Blindern, 0317, Oslo, Norway,The Lipid Clinic, Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital Aker, PO Box 4959, Nydalen, 0424, Oslo, Norway
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23
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Jende JME, Mooshage C, Kender Z, Kopf S, Groener JB, Heiland S, Juerchott A, Nawroth P, Bendszus M, Kurz FT. Magnetic Resonance Neurography Reveals Smoking-Associated Decrease in Sciatic Nerve Structural Integrity in Type 2 Diabetes. Front Neurosci 2022; 15:811085. [PMID: 35242003 PMCID: PMC8886720 DOI: 10.3389/fnins.2021.811085] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/17/2021] [Indexed: 12/23/2022] Open
Abstract
Objective It is controversially discussed in how far smoking contributes to diabetic polyneuropathy (DPN) in type 2 diabetes (T2D). Diffusion-weighted magnetic resonance neurography (MRN) at 3 Tesla has been shown to provide objective values for structural nerve integrity in patients with T2D. The aim of this study was to investigate the contribution of cigarette smoking on structural nerve integrity in T2D. Methods This cross-sectional prospective cohort study investigated the structural integrity of the sciatic nerve in 10 smokers, 40 never-smokers, and 20 ex-smokers with T2D and 10 healthy control subjects, using diffusion tensor imaging MRN at 3 Tesla and semi-automated nerve fiber tracking. Results were correlated with clinical, electrophysiological, and serological data. Results The sciatic nerve’s fractional anisotropy (FA), a parameter for structural nerve integrity, was significantly lower in smokers with T2D when compared to controls (p = 0.002) and never-smokers (p = 0.015), and lower in ex-smokers when compared to controls (p = 0.015). In addition, sciatic nerve radial diffusivity, a marker of myelin damage, was increased in smokers versus controls and never-smokers (p = 0.048, p = 0.049, respectively). Furthermore, FA in T2D patients was negatively correlated with clinical and electrophysiological markers of DPN. FA also showed negative correlations with the pulse wave velocity, a marker of arterial stiffness and associated microangiopathy, in controls (r = −0.70; p = 0.037), never-smokers (r = −0.45; p = 0.004), ex-smokers (r = −0.55; p = 0.009), and a similar trend in smokers (r = −0.63; p = 0.076). Negative correlations were found between FA and skin auto-fluorescence, a marker of tissue advanced glycation end product accumulation and therefore long-term glycemic stress in T2D, in never-smokers (r = −0.39; p = 0.020) and smokers (r = −0.84; p = 0.004), but not in ex-smokers (r = −0.07; p = 0.765). Conclusion The findings indicate that smoking contributes to sciatic nerve damage in T2D, potentially worsening DPN due to glycemic stress and less microangiopathy-associated myelin damage in active smokers, while angiopathic effects predominate in ex-smokers. To stop smoking may therefore pose a promising preventive measure to slow the progression of DPN in T2D.
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Affiliation(s)
- Johann M E Jende
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Christoph Mooshage
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Zoltan Kender
- Department of Endocrinology, Diabetology and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany
| | - Stefan Kopf
- Department of Endocrinology, Diabetology and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany.,German Center of Diabetes Research, München-Neuherberg, Germany
| | - Jan B Groener
- Department of Endocrinology, Diabetology and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany.,German Center of Diabetes Research, München-Neuherberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.,Division of Experimental Radiology, Department of Neuroradiology, Heidelberg, Germany
| | - Alexander Juerchott
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Peter Nawroth
- Department of Endocrinology, Diabetology and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany.,German Center of Diabetes Research, München-Neuherberg, Germany.,Joint Institute for Diabetes and Cancer at Helmholtz-Zentrum Munich and Heidelberg University, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Felix T Kurz
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.,Department of Radiology (E010), German Cancer Research Center, Heidelberg, Germany
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24
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Rash CJ, Alessi SM, Foster N, Tamborlane W, Van Name MA, Wagner JA. Tobacco use patterns and clinical outcomes in the T1D exchange. J Diabetes Complications 2022; 36:108128. [PMID: 35058139 PMCID: PMC8881793 DOI: 10.1016/j.jdiacomp.2022.108128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/23/2021] [Accepted: 01/07/2022] [Indexed: 02/03/2023]
Abstract
AIMS This study examined associations between tobacco use and diabetes outcomes using the T1D Exchange Registry. METHODS Adult participants (N = 933) completed standardized questionnaires including self-reported outcomes: past year serious hypoglycemic and diabetic ketoacidosis episodes, diabetes self-care, diabetes distress, and self-monitoring of blood glucose. Chart-extracted outcomes included HbA1c, nephrology and neuropathy diagnoses, and BMI. We examined the relation of tobacco use status (never, former, current) and frequency of use (daily versus less than daily) to these outcomes. RESULTS The majority had never used tobacco (55%, n = 515); 27% (n = 252) were former users and 18% (n = 166) were current users (with 31% using daily). Tobacco status was associated with HbA1c, BMI, self-care, distress, and blood glucose monitoring frequency. Across most outcomes, current users evidenced worse values relative to never users, and former users were largely similar to never users. Daily use was associated with significantly worse outcomes on HbA1c, diabetes self-care, and distress scores relative to less than daily use. CONCLUSIONS These cross-sectional comparisons suggest that current tobacco use is associated with worse status on important clinical diabetes indicators. Former users did not evidence these deleterious associations. Findings point to potential diabetes-specific motivators that could inform tobacco cessation interventions.
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25
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Joseph JJ, Deedwania P, Acharya T, Aguilar D, Bhatt DL, Chyun DA, Di Palo KE, Golden SH, Sperling LS. Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association. Circulation 2022; 145:e722-e759. [PMID: 35000404 DOI: 10.1161/cir.0000000000001040] [Citation(s) in RCA: 301] [Impact Index Per Article: 100.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cardiovascular disease remains the leading cause of death in patients with diabetes. Cardiovascular disease in diabetes is multifactorial, and control of the cardiovascular risk factors leads to substantial reductions in cardiovascular events. The 2015 American Heart Association and American Diabetes Association scientific statement, "Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence," highlighted the importance of modifying various risk factors responsible for cardiovascular disease in diabetes. At the time, there was limited evidence to suggest that glucose-lowering medications reduce the risk of cardiovascular events. At present, several large randomized controlled trials with newer antihyperglycemic agents have been completed, demonstrating cardiovascular safety and reduction in cardiovascular outcomes, including cardiovascular death, myocardial infarction, stroke, and heart failure. This AHA scientific statement update focuses on (1) the evidence and clinical utility of newer antihyperglycemic agents in improving glycemic control and reducing cardiovascular events in diabetes; (2) the impact of blood pressure control on cardiovascular events in diabetes; and (3) the role of newer lipid-lowering therapies in comprehensive cardiovascular risk management in adults with diabetes. This scientific statement addresses the continued importance of lifestyle interventions, pharmacological therapy, and surgical interventions to curb the epidemic of obesity and metabolic syndrome, important precursors of prediabetes, diabetes, and comorbid cardiovascular disease. Last, this scientific statement explores the critical importance of the social determinants of health and health equity in the continuum of care in diabetes and cardiovascular disease.
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26
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American Diabetes Association Professional Practice Committee. 5. Facilitating Behavior Change and Well-being to Improve Health Outcomes: Standards of Medical Care in Diabetes-2022. Diabetes Care 2022; 45:S60-S82. [PMID: 34964866 DOI: 10.2337/dc22-s005] [Citation(s) in RCA: 155] [Impact Index Per Article: 51.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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27
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Effectiveness of quality of care for patients with type 2 diabetes in China: findings from the Shanghai Integration Model (SIM). Front Med 2021; 16:126-138. [PMID: 34705246 DOI: 10.1007/s11684-021-0897-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/23/2021] [Indexed: 12/23/2022]
Abstract
This cross-sectional study aimed to investigate the quality of care of diabetes in Shanghai, China. A total of 173 235 patients with type 2 diabetes in 2017 were included in the analysis. Profiles of risk factors and intermediate outcomes were determined. The patients had a mean age of 66.43 ± 8.12 (standard deviation (SD)) years and a mean diabetes duration of 7.95 ± 5.53 (SD) years. The percentage of patients who achieved the target level for HbA1c (< 7.0%) was 48.6%. Patients who achieved the target levels for blood pressure (BP) < 130/80 mmHg and low-density lipoprotein-cholesterol (LDL-c) < 2.6 mmol/L reached 17.5% and 34.0%, respectively. A total of 3.8% achieved all three target levels, and the value increased to 6.8% with an adaptation of the BP target level (< 140/90 mmHg) for those over 65 years. Multivariable analysis identified the factors associated with a great likelihood of achieving all three target levels: male, young age, short diabetes duration, low body mass index, macrovascular complications, no microvascular complications, prescribed with lipid-lowering medication, and no prescription of antihypertensive medication. In conclusion, nearly 50% and one-third of the patients with diabetes met the target levels for HbA1c and LDL-c, respectively, with a low percentage achieving the BP target level. The percentage of patients who achieved all three target levels needs significant improvement.
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28
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Kim SW, Kim HJ, Min K, Lee H, Lee SH, Kim S, Kim JS, Oh B. The relationship between smoking cigarettes and metabolic syndrome: A cross-sectional study with non-single residents of Seoul under 40 years old. PLoS One 2021; 16:e0256257. [PMID: 34411160 PMCID: PMC8376018 DOI: 10.1371/journal.pone.0256257] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 08/03/2021] [Indexed: 12/23/2022] Open
Abstract
Introduction Young adults receive health screenings at lower rates than other age groups, and it may be difficult to detect diseases in the early stages for this group. We examined differences in health status relative to smoking in a young age group using the results of health screenings conducted in engaged and newly married couples in a cross-sectional database. Methods The participants in this study were 808 young adults who visited a municipal hospital health screening center from July 2017 to March 2019. They completed a self-administered questionnaire, and physical measurements and a blood test were taken. They were classified into non-cigarette smokers, past cigarette smokers, and current cigarette smokers according to smoking behavior. In this study, we compared metabolic syndrome, the main components of which include obesity, high blood pressure, high blood triglycerides, low levels of HDL cholesterol and insulin resistance, with smoking behavior. Results The mean age of the participants was 30.9±3.3 years (males 32.0±3.2, females 29.8±3.1), and 13.9% were current cigarette smokers (males 22.8%, females 5.1%). The proportion of men in their 30s was 76.6% for male group and 50.0% for female group, indicating that the male group had a relatively higher proportion of older and current smokers. Significant differences were found in age, sex, blood pressure, metabolic abnormalities, and drinking status according to smoking status. Cigarette smokers had a 2.4-fold greater risk of metabolic syndrome (95% confidence interval [CI], 1.43–3.96) than non-cigarette smokers; in particular, they had a 2.6-fold (95% CI, 1.44–4.55) greater risk of hypertriglyceridemia and a three-fold (95% CI, 1.45–6.35) greater risk of low HDL cholesterol. Conclusions In comparison with non-single, young and generally healthy city dwellers, the risk of metabolic syndrome was significantly higher in smokers than in non-smokers, and in particular, it was confirmed that the risk of hypertriglyceridemia and low HDL cholesterolemia was higher. Smoking cessation is necessary, even for the young, because smoking may cause changes in blood lipids even if the smoking duration is short.
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Affiliation(s)
- Sun Woo Kim
- Department of Family Medicine, Bumin Hospital, Seoul, Republic of Korea
| | - Ho Jun Kim
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Kyungha Min
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Hobeom Lee
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Sung-Ha Lee
- Center for Happiness Studies, Seoul National University, Seoul, Republic of Korea
| | - Sunyoung Kim
- Department of Family Medicine, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Jong Seung Kim
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Bumjo Oh
- Department of Family Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
- * E-mail:
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29
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Watanabe J, Hamasaki M, Kotani K. The Effect of Helicobacter pylori Eradication on Lipid Levels: A Meta-Analysis. J Clin Med 2021; 10:jcm10050904. [PMID: 33668848 PMCID: PMC7956592 DOI: 10.3390/jcm10050904] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 02/18/2021] [Accepted: 02/21/2021] [Indexed: 12/23/2022] Open
Abstract
Introduction:Helicobacter pylori (H. pylori) infection is positively associated with cardiovascular diseases, but the involvement of lipids in this association remains unclear. The present study reviewed the changes in circulating lipid levels following H. pylori eradication. Methods: A PubMed database was searched until December 2020 to identify randomized control trials (RCTs) and non-RCTs investigating the effect of H. pylori eradication on the lipid levels in inverse variance-weighted, random-effects meta-analyses. Results: A total of 24 studies (four RCTs and 20 non-RCTs) with 5270 participants were identified. The post-eradication levels were increased for high-density lipoprotein cholesterol (HDL-C; mean difference (MD) 2.28 mg/dL, 95% confidence interval (CI) 1.90 to 2.66) and triglyceride (TG; MD 3.22 mg/dL, 95% CI 1.13 to 5.31) compared with the pre-eradication levels. H. pylori eradication resulted in little to no difference in the low-density lipoprotein-cholesterol levels (MD −2.33 mg/dL, 95% CI −4.92 to 0.26). In the analyses of RCTs only, the findings for elevated HDL-C levels, but not TG, were robust. Conclusions:H. pylori eradication increases the HDL-C levels. Further studies are needed to elucidate the effects of lipid changes following H. pylori eradication on cardiovascular diseases.
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Affiliation(s)
| | | | - Kazuhiko Kotani
- Correspondence: ; Tel.: +81-285-58-7394; Fax: +81-285-44-0628
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30
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5. Facilitating Behavior Change and Well-being to Improve Health Outcomes: Standards of Medical Care in Diabetes-2021. Diabetes Care 2021; 44:S53-S72. [PMID: 33298416 DOI: 10.2337/dc21-s005] [Citation(s) in RCA: 180] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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31
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Kos K. Cardiometabolic Morbidity and Mortality with Smoking Cessation, Review of Recommendations for People with Diabetes and Obesity. Curr Diab Rep 2020; 20:82. [PMID: 33289870 PMCID: PMC7722253 DOI: 10.1007/s11892-020-01352-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/26/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE OF REVIEW Obesity is closely linked with the pathogenesis of type 2 diabetes (T2DM) and cardiovascular disease (CVD), and whilst smoking cessation is associated with weight gain, there are concerns that this weight gain may offset the benefit of CVD risk reduction especially in those with considerable post-cessation weight gain. The aim of this narrative review is to evaluate recent evidence on smoking cessation and cardiometabolic outcomes and discuss limitations of current knowledge and studies. RECENT FINDINGS Nicotine is a key player in modulating energy balance by influencing lipid storage in adipose tissue by affecting lipolysis, energy input by modulating appetite and energy output by increasing sympathetic drive and thermogenesis. It also increases insulin resistance and promotes abdominal obesity. The CVD risk and mortality associated with cigarette smoking potentiate the CVD risks in patients with diabetes. Evidence supports the benefit of quitting cigarette smoking regardless of any subsequent weight gain. Data suggests that the cardiometabolic risk is limited to the first few years and that cardiovascular health and mortality benefit of smoking cessation outweighs the harm related to weight gain. This weight gain can be limited by nicotine replacement of which e-cigarettes (vaping) are increasingly popular if it is not an alternative to cigarette smoking. However, long-term health data on e-cigarettes is needed prior to formal recommendation for its use in smoking cessation. The recommendation for cessation of cigarette smoking is justified for those at high risk of weight gain and diabetes. However, for most benefit, consideration should be given for personalized weight management to limit weight gain. Awareness of a 'lean paradox' by which lower weight is associated with increased CVD risk may help to improve motivation and insight into the bias of smoking, health and body composition otherwise known to epidemiologists as the 'obesity paradox'.
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Affiliation(s)
- Katarina Kos
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, University of Exeter, Exeter, Devon, UK.
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32
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Nakamura M, Yamamoto Y, Imaoka W, Kuroshima T, Toragai R, Ito Y, Kanda E, J Schaefer E, Ai M. Relationships between Smoking Status, Cardiovascular Risk Factors, and Lipoproteins in a Large Japanese Population. J Atheroscler Thromb 2020; 28:942-953. [PMID: 33116031 PMCID: PMC8532056 DOI: 10.5551/jat.56838] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Aims:
Smoking is a major risk factor for cardiovascular disease (CVD), a leading cause of death and disability. Other CVD risk factors include age, gender, hypertension, diabetes, increased low-density lipoprotein cholesterol (LDL-C) and decreased high-density lipoprotein cholesterol (HDL-C). Our goal was to assess relationships between smoking status and CVD risk factors, with a focus on direct LDL-C, HDL-C, triglycerides (TG) and small dense LDL-C (sdLDL-C).
Methods:
A total of 34,497 Japanese men and women, mean age 51 years, had their CVD risk factors including fasting serum total cholesterol, TG, HDL-C, sdLDL-C, and direct LDL-C assessed. One-way ANOVA and multiple linear regression analyses were carried to assess the interrelationships of these parameters with smoking.
Results:
In both men and women, current smokers had significantly (
p
＜0.001) higher median TG (+19.6%, +16.9%) and sdLDL-C levels (+12.7%, +4.2%) levels, and significantly (
p
＜0.001) lower HDL-C levels (-7.3%, -4.3%) than non-smokers. They were also significantly (
p
＜0.05) more likely to have TG values ＞150 mg/dL (+56.8%, +116.3%), sdLDL-C ＞40.1 mg/dL (+28.8%, +44.9%), and HDL-C ＜40 mg/dL (+89.8%, +114.3%). Ex-smokers generally had lipid values that were intermediate between non-smokers and current smokers. Multivariate analysis confirmed the significance of these relationships.
Conclusion:
Our data indicate that current cigarette smoking is associated with increased TG and sdLDL-C levels, as well as decreased HDL-C levels. Furthermore, smoking effect on lipid profiles remain after cessation. These data provide further justification for smoking cessation.
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Affiliation(s)
- Marie Nakamura
- Department of Insured Medical Care Management, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU)
| | - Yasushi Yamamoto
- Kansai Occupational Health Association, ACTY Health Evaluation Center
| | - Wataru Imaoka
- Kansai Occupational Health Association, ACTY Health Evaluation Center
| | - Toshio Kuroshima
- Kansai Occupational Health Association, Senri LC Health Evaluation Center
| | - Ryoko Toragai
- Kansai Occupational Health Association, Senri LC Health Evaluation Center
| | - Yasuki Ito
- Reagent R&D department, Research and development Division, Denka Co.,Ltd
| | | | - Ernst J Schaefer
- Cardiovascular Nutrition Laboratory, Human Nutrition Research Center on Aging at Tufts University, and Tufts University School of Medicine
| | - Masumi Ai
- Department of Insured Medical Care Management, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU)
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Patoulias D, Stavropoulos K, Imprialos K, Athyros V, Doumas M, Karagiannis A. Pharmacological Management of Cardiac Disease in Patients with Type 2 Diabetes: Insights into Clinical Practice. Curr Vasc Pharmacol 2020; 18:125-138. [PMID: 32013815 DOI: 10.2174/1570161117666190426162746] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 10/18/2018] [Accepted: 10/26/2018] [Indexed: 01/16/2023]
Abstract
BACKGROUND Type 2 Diabetes Mellitus (T2DM) has emerged as a growing pandemic. Cardiovascular disease (CVD) constitutes another major health problem, with coronary heart disease being the leading cause of cardiovascular death. Patients with T2DM require a multilevel therapeutic approach, both for primary and secondary prevention of CVD. OBJECTIVE To present and summarize the most recent, highest level evidence retrieved from literature, relevant to the pharmaceutical management of CVD in T2DM. METHODS We conducted a comprehensive search of the literature on MEDLINE from its inception till today, primarily for relevant systematic reviews, meta-analyses and randomized controlled trials. RESULTS There is a trend towards more intensified therapeutic interventions in T2DM, concerning glycemic, lipid and blood pressure control. New drugs, such as sodium-glucose co-transporter 2 (SGLT-2) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs) and proprotein convertase subtilisin/ kexin type 9 (PCSK9) inhibitors might evolve as key players in the management of diabetes and its complications within the next years. Classic drugs, such as those targeting the renin-angiotensinaldosterone system, statins and aspirin remain first-line treatment options, both for primary and secondary prevention of CVD. Lifestyle interventions should always be integrated into a complete therapeutic strategy in diabetic patients. Novel drugs, such as finerenone and LCZ696 have provided significant results in cardiovascular outcome studies; however, their role in T2DM has to be further elucidated. CONCLUSION Pharmaceutical approach of CVD in T2DM is multilevel and complex. Drug classes featuring pleiotropic effects may boost our armamentarium in the fight against CVD.
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Affiliation(s)
- Dimitrios Patoulias
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Konstantinos Stavropoulos
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Konstantinos Imprialos
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vasilios Athyros
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Michael Doumas
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece.,VA Medical Center, and George Washington University, Washington, DC, United States
| | - Asterios Karagiannis
- Second Propedeutic Department of Internal Medicine, General Hospital "Hippokration", Aristotle University of Thessaloniki, Thessaloniki, Greece
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Chertok IRA. Perceived risk of infection and smoking behavior change during COVID-19 in Ohio. Public Health Nurs 2020; 37:854-862. [PMID: 32981125 PMCID: PMC7537299 DOI: 10.1111/phn.12814] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 07/28/2020] [Accepted: 09/04/2020] [Indexed: 12/31/2022]
Abstract
Objective The recent COVID‐19 pandemic may catalyze smoking behavior modification. The purpose of the study was to examine factors associated with reducing smoking exposure during the COVID‐19 outbreak. Design Cross‐sectional design using the Health Belief Model to develop an online survey distributed throughout Ohio early during the outbreak. Sample 810 adults in Ohio (77.9% non‐smokers, 22.1% current smokers). Measurements Sociodemographic factors, smoking and behavior changes since the COVID‐19 outbreak, and perceived risk of infection were collected. Logistic regression analyses were conducted to determine factors associated with indoor smoking bans and factors associated with desire to quit smoking since the outbreak. Results For the overall sample, the odds of indoor smoking bans were significantly associated with never smoked, college education, single‐family residence, not living with smokers, and perceived importance of avoiding public places. For smokers, the desire to quit smoking since the COVID‐19 outbreak was associated with diabetes and perceived risk of severe infection. Conclusions Identified factors inform residential smoking exposure reduction through indoor smoking bans. Having an increased perceived risk of severe infection among smokers may motivate cessation. Public health nurses can provide accurate and accessible resources for smoking cessation during the COVID‐19 pandemic to promote healthy lifestyle modification.
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Szwarcbard N, Villani M, Earnest A, Flack J, Andrikopoulos S, Wischer N, Soldatos G, Gasevic D, Zoungas S. The association of smoking status with glycemic control, metabolic profile and diabetic complications- Results of the Australian National Diabetes Audit (ANDA). J Diabetes Complications 2020; 34:107626. [PMID: 32527672 DOI: 10.1016/j.jdiacomp.2020.107626] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 05/13/2020] [Accepted: 05/13/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Tobacco smoking and diabetes mellitus contribute significantly to the overall health burden and mortality of Australians. We aimed to assess the relationship of smoking with glycemic control, metabolic profile and complications in Australian patients living with diabetes. METHODS We analysed the 2011-2017 biennial Australian National Diabetes Audit cross-sectional data. Patients were classified as current, past or never smokers. Linear (or quantile) and logistic regression models were used to assess for associations. RESULTS Data from 15,352 patients were analysed, including 72.2% with type 2 diabetes. Current smokers comprised 13.5% of the study population. Current and past smokers had a median HbA1c that was 0.49% and 0.14% higher than never smokers, respectively, as well as higher triglyceride and lower HDL levels (all p values < .0001). Compared to never smokers, current smokers had higher odds of severe hypoglycemia and current and past smokers had higher odds of myocardial infarction, stroke, peripheral vascular disease, lower limb amputation, erectile dysfunction and peripheral neuropathy (all p values ≤.001), with no significant change over time. CONCLUSION When compared to never smokers, current and past smokers had poorer glycemic and lipid control and higher odds of macrovascular and microvascular complications. Despite this, current smoking remains prevalent among Australians with diabetes.
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Affiliation(s)
- N Szwarcbard
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - M Villani
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia; Research and Evaluation, Ambulance Victoria, Blackburn, VIC 3130, Australia
| | - A Earnest
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - J Flack
- Department of Diabetes and Endocrinology, Bankstown-Lidcombe Hospital, Bankstown, NSW 2200, Australia; Faculty of Medicine, University of New South Wales, Sydney, NSW,Australia; School of Medicine, Western Sydney University, Sydney, NSW,Australia
| | - S Andrikopoulos
- Department of Medicine, University of Melbourne, Parkville, VIC 3010, Australia; Australian Diabetes Society, Sydney, NSW 2000, Australia
| | - N Wischer
- National Association of Diabetes Centres, Sydney, NSW, 2000, Australia
| | - G Soldatos
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia; Diabetes and Vascular Medicine Unit, Monash Health, Clayton, VIC,Australia, 3168
| | - D Gasevic
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia; Usher Institute, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, United Kingdom
| | - S Zoungas
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia; Diabetes and Vascular Medicine Unit, Monash Health, Clayton, VIC,Australia, 3168.
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Molla GJ, Ismail-Beigi F, Larijani B, Khaloo P, Moosaie F, Alemi H, Mansournia MA, Ghadimi T, Ghaemi F, Nakhjavani M, Esteghamati A. Smoking and Diabetes Control in Adults With Type 1 and Type 2 Diabetes: A Nationwide Study From the 2018 National Program for Prevention and Control of Diabetes of Iran. Can J Diabetes 2020; 44:246-252. [DOI: 10.1016/j.jcjd.2019.07.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 06/29/2019] [Accepted: 07/08/2019] [Indexed: 02/06/2023]
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5. Facilitating Behavior Change and Well-being to Improve Health Outcomes: Standards of Medical Care in Diabetes-2020. Diabetes Care 2020; 43:S48-S65. [PMID: 31862748 DOI: 10.2337/dc20-s005] [Citation(s) in RCA: 223] [Impact Index Per Article: 44.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc20-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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Kao YH, Celestin MD, Walker CD, Yu Q, Couk J, Moody-Thomas S, Zhang H, Tseng TS. Smoking Relapse and Type 2 Diabetes Mellitus-Related Emergency Department Visits Among Senior Patients with Diabetes. Prev Chronic Dis 2019; 16:E164. [PMID: 31858955 PMCID: PMC6936672 DOI: 10.5888/pcd16.190027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION Quitting smoking has been proven to benefit smokers with diabetes. However, among older patients with diabetes, the evidence regarding an association between smoking status and the risk of type 2 diabetes mellitus-related emergency department (ED) visits has not been well investigated. METHODS A retrospective cohort study was performed by using the Louisiana State University Health Care Services Division electronic health records from 2009 to 2011. Patients aged 65 years or older with type 2 diabetes and smoking status recorded at least twice in 2010 were selected. Selected patients with diabetes were classified into nonsmokers, former smokers, continuing smokers, and relapsed smokers. Cox proportional hazards regression models were used to estimate the adjusted hazard ratio (aHR) of 1-year type 2 diabetes-related ED visits for each group compared with nonsmokers. RESULTS There were 174 (8.2%) continuing smokers and 77 (3.6%) relapsed smokers in 2,114 patients with diabetes who were studied. Rates of type 2 diabetes-related ED visits were highest in relapsed smokers (28.6%). Compared with nonsmokers, relapsed smokers had a significantly higher risk of type 2 diabetes-related ED visits (aHR = 1.62; 95% confidence interval [CI], 1.04-2.50). After stratifying by sex, a significantly increased risk of type 2 diabetes-related ED visits was shown only in male relapsed smokers (aHR = 2.05; 95% CI, 1.13-3.71) and female continuing smokers (aHR = 1.65; 95% CI, 1.10-2.47) compared with nonsmokers. CONCLUSION Older men with diabetes who were relapsed smokers had a higher risk of type 2 diabetes-related ED visits. Future research and clinical practice should focus on these patients and create more effective interventions for smoking cessation and diabetes management.
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Affiliation(s)
- Yu-Hsiang Kao
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - Michael D Celestin
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - Carl D Walker
- Health Care Services Division, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - Qingzhao Yu
- Biostatistics, School of Public Health, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - John Couk
- Health Care Services Division, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - Sarah Moody-Thomas
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center New Orleans, New Orleans, Louisiana
| | - Huijie Zhang
- Nafang Hospital of Southern Medical University, Guangzhou, Guangzhou, China
| | - Tung-Sung Tseng
- Behavioral and Community Health Sciences, School of Public Health, Louisiana State University Health Sciences Center New Orleans, 2020 Gravier St, Room 213, New Orleans, LA 70112.
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Valerio G, Mozzillo E, Zito E, De Nitto E, Maltoni G, Marigliano M, Zucchini S, Maffeis C, Franzese A. Alcohol consumption or cigarette smoking and cardiovascular disease risk in youth with type 1 diabetes. Acta Diabetol 2019; 56:1315-1321. [PMID: 31493030 DOI: 10.1007/s00592-019-01415-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 08/27/2019] [Indexed: 12/23/2022]
Abstract
AIM To assess the association between alcohol consumption and/or cigarette smoking with other unhealthy behaviors and clinical cardiovascular risk factors in youth with type 1 diabetes. METHODS Two hundred and twenty-eight youth with type 1 diabetes (age 13-19 years) were consecutively enrolled in three Regional Pediatric Diabetes Centers in Italy. Demographic, anthropometric, lifestyle (adherence to the Mediterranean diet pattern and sports participation) and laboratory parameters were compared among youth reporting isolated or combined alcohol consumption and/or cigarette smoking. RESULTS Ten percent of the youth reported alcohol consumption, 10% cigarette smoking and 6% both alcohol and cigarette use; 74% did not report alcohol or cigarette use. Compared to non-drinker non-smoker youth, smokers showed significantly higher percentages of each of the behavioral and clinical cardiovascular risk factors. Drinkers showed a significantly higher proportion of abdominal adiposity, dyslipidemia and poor adherence to the Mediterranean diet. Alcohol consumption was independently associated with both dyslipidemia and high glycosylated hemoglobin. CONCLUSIONS Our findings emphasize the need to increase the awareness of youth with T1D about the negative impact of alcohol drinking on cardiovascular risk, since the effects of alcohol might be underestimated with respect to the well-known detrimental effects of smoking. Clustering of unhealthy lifestyle should be discouraged in type 1 diabetes youth in order to promote cardiovascular protection.
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Affiliation(s)
- Giuliana Valerio
- Department of Movement Sciences and Wellbeing, University of Naples Parthenope, Naples, Italy
| | - Enza Mozzillo
- Department of Translational Medical Science, Section of Pediatrics, Regional Center for Pediatric Diabetes, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy.
| | - Eugenio Zito
- Department of Social Sciences, University of Naples Federico II, Naples, Italy
| | - Elena De Nitto
- Department of Translational Medical Science, Section of Pediatrics, Regional Center for Pediatric Diabetes, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Giulio Maltoni
- Endocrine Unit, Department of Pediatrics, S. Orsola-Malpighi Hospital, Bologna, Italy
| | - Marco Marigliano
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital of Verona, Verona, Italy
| | - Stefano Zucchini
- Endocrine Unit, Department of Pediatrics, S. Orsola-Malpighi Hospital, Bologna, Italy
| | - Claudio Maffeis
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital of Verona, Verona, Italy
| | - Adriana Franzese
- Department of Translational Medical Science, Section of Pediatrics, Regional Center for Pediatric Diabetes, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
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Shi S, Yu B, Li W, Shan J, Ma T. Corn silk decoction for blood lipid in patients with angina pectoris: A systematic review and meta-analysis. Phytother Res 2019; 33:2862-2869. [PMID: 31423665 DOI: 10.1002/ptr.6474] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 07/02/2019] [Accepted: 07/26/2019] [Indexed: 02/05/2023]
Abstract
The aims of this study were to evaluate the efficacy of corn silk decoction on lipid profile in patients with angina pectoris. PubMed, Cochrane, Embase, Google Scholar, Chongqing VIP Chinese Science and Technology Periodical Database, China National Knowledge Infrastructure, and Wanfang database were searched up to January 2019 for randomized controlled trials that assessed the impact of corn silk decoction on total cholesterol, triglycerides, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol in patients with angina pectoris. Study evaluation and synthesis methods were in accordance with the Cochrane Handbook, and data were analyzed using Review Manager (version 5.3) software. Random effects model was applied in this systematic review and meta-analysis to compensate for potential heterogeneity among the included studies. A total of four randomized controlled trials were eligible for meta-analysis. Pooled results of these studies indicated that corn silk decoction might improve high-density lipoprotein cholesterol and reduce total cholesterol, triglycerides, and low-density lipoprotein cholesterol in patients with angina pectoris. Subgroup analyses showed that corn silk decoction or modified corn silk decoction plus conventional pharmaceutical treatment could have favorable effects on blood lipids. However, the lack of blinding in most studies may have led to overestimation of these effects. Further studies with better design are needed to confirm these findings.
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Affiliation(s)
- Shihua Shi
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Baili Yu
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Weihao Li
- Cardiology Division, West China Hospital, Sichuan University, Chengdu, China
| | - Jiayue Shan
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Tianhong Ma
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Kar D, Gillies C, Nath M, Khunti K, Davies MJ, Seidu S. Association of smoking and cardiometabolic parameters with albuminuria in people with type 2 diabetes mellitus: a systematic review and meta-analysis. Acta Diabetol 2019; 56:839-850. [PMID: 30799525 PMCID: PMC6597612 DOI: 10.1007/s00592-019-01293-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 01/23/2019] [Indexed: 02/08/2023]
Abstract
AIMS Smoking is a strong risk factor for albuminuria in people with type 2 diabetes mellitus (T2DM). However, it is unclear whether this sequela of smoking is brought about by its action on cardiometabolic parameters or the relationship is independent. The aim of this systematic review is to explore this relationship. METHODS Electronic databases on cross-sectional and prospective studies in Medline and Embase were searched from January 1946 to May 2018. Adult smokers with T2DM were included, and other types of diabetes were excluded. RESULTS A random effects meta-analysis of 20,056 participants from 13 studies found that the odds ratio (OR) of smokers developing albuminuria compared to non-smokers was 2.13 (95% CI 1.32, 3.45). Apart from smoking, the odds ratio of other risk factors associated with albuminuria were: age 1.24 (95% CI 0.84, 1.64), male sex 1.39 (95% CI 1.16, 1.67), duration of diabetes 1.78 (95% CI 1.32, 2.23), HbA1c 0.63 (95% CI 0.45, 0.81), SBP 6.03 (95% CI 4.10, 7.97), DBP 1.85 (95% CI 1.08, 2.62), total cholesterol 0.06 (95% CI - 0.05, 0.17) and HDL cholesterol - 0.01 (95% CI - 0.04, 0.02), triglyceride 0.22 (95% CI 0.12, 0.33) and BMI 0.40 (95% CI 0.00-0.80). When the smoking status was adjusted in a mixed effect meta-regression model, the duration of diabetes was the only statistically significant factor that influenced the prevalence of albuminuria. In smokers, each year's increase in the duration of T2DM was associated with an increased risk of albuminuria of 0.19 units (95% CI 0.07, 0.31) on the log odds scale or increased the odds approximately by 23%, compared to non-smokers. Prediction from the meta-regression model also suggested that the odds ratios of albuminuria in smokers after a diabetes duration of 9 years and 16 years were 1.53 (95% CI 1.10, 2.13) and 5.94 (95% CI 2.53, 13.95), respectively. CONCLUSIONS Continuing to smoke and the duration of diabetes are two strong predictors of albuminuria in smokers with T2DM. With a global surge in younger smokers developing T2DM, smoking cessation interventions at an early stage of disease trajectory should be promoted.
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Affiliation(s)
- Debasish Kar
- Diabetes Research Centre, Univerisity of Leicester, Leicester, UK
- Academic Unit of Diabetes and Endocrinology, University of Sheffield, Sheffield, UK
| | - Clare Gillies
- Diabetes Research Centre, Univerisity of Leicester, Leicester, UK
| | - Mintu Nath
- Diabetes Research Centre, Univerisity of Leicester, Leicester, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, Univerisity of Leicester, Leicester, UK
| | | | - Samuel Seidu
- Diabetes Research Centre, Univerisity of Leicester, Leicester, UK
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Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, Guo X, Liu J, Lu Y, Cheng CY, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Baker J, Chen G, Aschard H, Bartz TM, Ding J, Dorajoo R, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Zhao W, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Hung YJ, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lin KH, Luan J, Lyytikäinen LP, Matoba N, Nolte IM, Pietzner M, Prins B, Riaz M, Robino A, Said MA, Schupf N, Scott RA, Sofer T, Stancáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang TD, Wang Y, Ware EB, Wen W, Xiang YB, Yanek LR, Zhang W, Zhao JH, Adeyemo A, Afaq S, Amin N, Amini M, Arking DE, Arzumanyan Z, Aung T, Ballantyne C, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Broeckel U, Brown M, Cade BE, Campbell A, Canouil M, Charumathi S, Chen YDI, Christensen K, et alBentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, Guo X, Liu J, Lu Y, Cheng CY, Sim X, Vojinovic D, Huffman JE, Musani SK, Li C, Feitosa MF, Richard MA, Noordam R, Baker J, Chen G, Aschard H, Bartz TM, Ding J, Dorajoo R, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Zhao W, Graff M, Alver M, Boissel M, Chai JF, Chen X, Divers J, Evangelou E, Gao C, Goel A, Hagemeijer Y, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Hung YJ, Jackson AU, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lin KH, Luan J, Lyytikäinen LP, Matoba N, Nolte IM, Pietzner M, Prins B, Riaz M, Robino A, Said MA, Schupf N, Scott RA, Sofer T, Stancáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Wang TD, Wang Y, Ware EB, Wen W, Xiang YB, Yanek LR, Zhang W, Zhao JH, Adeyemo A, Afaq S, Amin N, Amini M, Arking DE, Arzumanyan Z, Aung T, Ballantyne C, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Broeckel U, Brown M, Cade BE, Campbell A, Canouil M, Charumathi S, Chen YDI, Christensen K, Concas MP, Connell JM, de las Fuentes L, de Silva HJ, de Vries PS, Doumatey A, Duan Q, Eaton CB, Eppinga RN, Faul JD, Floyd JS, Forouhi NG, Forrester T, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gharib SA, Gigante B, Giulianini F, Grabe HJ, Gu CC, Harris TB, Heikkinen S, Heng CK, Hirata M, Hixson JE, Ikram MA, Jia Y, Joehanes R, Johnson C, Jonas JB, Justice AE, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Kolcic I, Kooperberg C, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Liang J, Lin S, Liu CT, Liu J, Liu K, Loh M, Lohman KK, Louie T, Luzzi A, Mägi R, Mahajan A, Manichaikul AW, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Morris AP, Murray AD, Nalls MA, Nauck M, Nelson CP, North KE, O'Connell JR, Palmer ND, Papanicolau GJ, Pedersen NL, Peters A, Peyser PA, Polasek O, Poulter N, Raitakari OT, Reiner AP, Renström F, Rice TK, Rich SS, Robinson JG, Rose LM, Rosendaal FR, Rudan I, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Shi Y, Sidney S, Sims M, Smith JA, Snieder H, Starr JM, Strauch K, Stringham HM, Tan NYQ, Tang H, Taylor KD, Teo YY, Tham YC, Tiemeier H, Turner ST, Uitterlinden AG, van Heemst D, Waldenberger M, Wang H, Wang L, Wang L, Wei WB, Williams CA, Wilson G, Wojczynski MK, Yao J, Young K, Yu C, Yuan JM, Zhou J, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Cooper RS, de Faire U, Deary IJ, Elliott P, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Juang JMJ, Kamatani Y, Kammerer CM, Kato N, Kooner JS, Laakso M, Laurie CC, Lee IT, Lehtimäki T, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Pereira AC, Rauramaa R, Redline S, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wang JS, Wang YX, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zeggini E, Zheng W, Bouchard C, Evans MK, Gudnason V, Kardia SLR, Liu Y, Psaty BM, Ridker PM, van Dam RM, Mook-Kanamori DO, Fornage M, Province MA, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Loos RJF, Franceschini N, Rotter JI, Zhu X, Bierut LJ, Gauderman WJ, Rice K, Munroe PB, Morrison AC, Rao DC, Rotimi CN, Cupples LA. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat Genet 2019; 51:636-648. [PMID: 30926973 PMCID: PMC6467258 DOI: 10.1038/s41588-019-0378-y] [Show More Authors] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 02/07/2019] [Indexed: 12/08/2022]
Abstract
The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
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Affiliation(s)
- Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA.
| | - Yun J Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Aldi T Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Xuan Deng
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jingmin Liu
- Women's Health Initiative Clinical Coordinating Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yingchang Lu
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Quantitative Medicine, Academic Medicine Research Institute, Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jennifer E Huffman
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Solomon K Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Changwei Li
- Epidemiology and Biostatistics, University of Georgia at Athens College of Public Health, Athens, GA, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Melissa A Richard
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Raymond Noordam
- Internal Medicine, Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jenna Baker
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Hugues Aschard
- Centre de Bioinformatique, Biostatistique, et Biologie Intégrative (C3BI), Institut Pasteur, Paris, France
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Biostatistics, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jingzhong Ding
- Center on Diabetes, Obesity, and Metabolism, Gerontology and Geriatric Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Alisa K Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Albert V Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Salman M Tajuddin
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, US National Institutes of Health, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maris Alver
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mathilde Boissel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jasmin Divers
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Yanick Hagemeijer
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Fernando P Hartwig
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Andrea R V R Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yi-Jen Hung
- Endocrinology and Metabolism, Tri-Service General Hospital, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Pirjo Komulainen
- Foundation for Research in Health, Exercise, and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Karin Leander
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Keng-Hung Lin
- Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jian'an Luan
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Technology, Tampere University, Tampere, Finland
| | - Nana Matoba
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Ilja M Nolte
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Maik Pietzner
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Bram Prins
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Muhammad Riaz
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Antonietta Robino
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - M Abdullah Said
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Nicole Schupf
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Robert A Scott
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Alena Stancáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Peter J van der Most
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Tibor V Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Tzung-Dau Wang
- Cardiovascular Center, National Taiwan University Hospital, Taipei, Taiwan
- National Taiwan University College of Medicine, Taipei, Taiwan
- Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Yajuan Wang
- Department of Population Quantitative and Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yong-Bing Xiang
- SKLORG and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Weihua Zhang
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UK
| | - Jing Hua Zhao
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Saima Afaq
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marzyeh Amini
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zorayr Arzumanyan
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Christie Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX, USA
- Houston Methodist Debakey Heart and Vascular Center, Houston, TX, USA
| | - R Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Erwin P Bottinger
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ulrich Broeckel
- Section of Genomic Pediatrics, Departments of Pediatrics, Medicine, and Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Morris Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Mickaël Canouil
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Sabanayagam Charumathi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Quantitative Medicine, Academic Medicine Research Institute, Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kaare Christensen
- Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - John M Connell
- Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Lisa de las Fuentes
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ayo Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles B Eaton
- Department of Family Medicine and Epidemiology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Ruben N Eppinga
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Terrence Forrester
- UWI Solutions for Developing Countries, University of the West Indies, Kingston, Jamaica
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Ilaria Gandin
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - He Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Bruna Gigante
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - C Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, US National Institutes of Health, Bethesda, MD, USA
| | - Sami Heikkinen
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Makoto Hirata
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, University of Tokyo, Minato-ku, Japan
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Yucheng Jia
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Roby Joehanes
- Hebrew SeniorLife, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Craig Johnson
- Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA
| | - Jost Bruno Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing Tongren Eye Center, Capital Medical University, Beijing, China
| | - Anne E Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, Japan
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Ivana Kolcic
- Department of Public Health, Department of Medicine, University of Split, Split, Croatia
| | - Charles Kooperberg
- Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, WA, USA
| | - Jose E Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
| | - Stephen B Kritchevsky
- Sticht Center for Healthy Aging and Alzheimer's Prevention, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Timo A Lakka
- Foundation for Research in Health, Exercise, and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, US National Institutes of Health, Bethesda, MD, USA
| | - Benjamin Lehne
- Institute of Clinical Sciences, Department of Molecular Sciences, Imperial College, London, UK
| | - Cora E Lewis
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yize Li
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jingjing Liang
- Department of Population Quantitative and Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Shiow Lin
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kiang Liu
- Epidemiology, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Marie Loh
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology, and Research, Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Kurt K Lohman
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anna Luzzi
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Colin A McKenzie
- Tropical Metabolism Research Unit, Caribbean Institute for Health Research, University of the West Indies, Mona, Jamaica
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
- Technische Universität München, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, the Netherlands
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Andrew P Morris
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Alison D Murray
- Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - Mike A Nalls
- Data Tecnica International, Glen Echo, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - George J Papanicolau
- Epidemiology Branch, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Epidemiology, Faculty of Medicine, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig Maximilian University, Munich, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ozren Polasek
- Department of Public Health, Department of Medicine, University of Split, Split, Croatia
- Psychiatric Hospital 'Sveti Ivan', Zagreb, Croatia
- Gen-info, Ltd, Zagreb, Croatia
| | - Neil Poulter
- School of Public Health, Imperial College, London, UK
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Alex P Reiner
- Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, WA, USA
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Treva K Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jennifer G Robinson
- Department of Epidemiology and Medicine, University of Iowa, Iowa City, IA, USA
| | - Lynda M Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Frits R Rosendaal
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Carsten O Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - William R Scott
- Institute of Clinical Sciences, Department of Molecular Sciences, Imperial College, London, UK
- National Heart and Lung Institute, Imperial College, London, UK
| | - Peter Sever
- National Heart and Lung Institute, Imperial College, London, UK
| | - Yuan Shi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Mario Sims
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Konstantin Strauch
- Genetic Epidemiology, Faculty of Medicine, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig Maximilian University, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Y Q Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
| | - Yih Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Diana van Heemst
- Internal Medicine, Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Heming Wang
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Lan Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Christine A Williams
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Gregory Wilson
- Jackson Heart Study, School of Public Health, Jackson State University, Jackson, MS, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kristin Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Caizheng Yu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Min Yuan
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Alan B Zonderman
- Behavioral Epidemiology Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, US National Institutes of Health, Baltimore, MD, USA
| | - Diane M Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Donald W Bowden
- Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Imperial College Healthcare NHS Trust, London, UK
| | - Richard S Cooper
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Ulf de Faire
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- OCDEM, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Barry I Freedman
- Nephrology, Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Philippe Froguel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
- Department of Genomics of Common Disease, Imperial College, London, UK
| | - Paolo Gasparini
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Bernardo L Horta
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Jyh-Ming Jimmy Juang
- National Taiwan University College of Medicine, Taipei, Taiwan
- Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Candace M Kammerer
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jaspal S Kooner
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UK
- National Heart and Lung Institute, Imperial College, London, UK
- Imperial College Healthcare NHS Trust, London, UK
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - I-Te Lee
- Endocrinology and Metabolism, Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Technology, Tampere University, Tampere, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Albertine J Oldehinkel
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Groningen, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, the Netherlands
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil
| | - Rainer Rauramaa
- Foundation for Research in Health, Exercise, and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - James Scott
- National Heart and Lung Institute, Imperial College, London, UK
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands
| | - Lynne E Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jun-Sing Wang
- Endocrinology and Metabolism, Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing Tongren Eye Center, Capital Medical University, Beijing, China
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | | | - Tangchun Wu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Eleftheria Zeggini
- Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Michele K Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, US National Institutes of Health, Baltimore, MD, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yongmei Liu
- Public Health Sciences, Epidemiology and Prevention, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Dennis O Mook-Kanamori
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Tanika N Kelly
- Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Ervin R Fox
- Cardiology, Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xiaofeng Zhu
- Department of Population Quantitative and Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Laura J Bierut
- Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - W James Gauderman
- Biostatistics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA.
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Framingham Heart Study, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA.
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Abstract
The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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Sonmez A, Haymana C, Bayram F, Salman S, Dizdar OS, Gurkan E, Kargili Carlıoglu A, Barcin C, Sabuncu T, Satman I. Turkish nationwide survEy of glycemic and other Metabolic parameters of patients with Diabetes mellitus (TEMD study). Diabetes Res Clin Pract 2018; 146:138-147. [PMID: 30244051 DOI: 10.1016/j.diabres.2018.09.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 09/04/2018] [Accepted: 09/13/2018] [Indexed: 12/12/2022]
Abstract
AIMS Turkey has the highest prevalence of diabetes in Europe. It is therefore essential to know the overall cardiovascular risk and reveal the predictors of metabolic control in Turkish adults with diabetes mellitus. METHODS A nationwide, multicenter survey consecutively enrolled patients who were under follow up for at least a year. Optimal control was defined as HbA1c < 7%, home arterial blood pressure (ABP) < 135/85 mmHg, or LDL-C < 100 mg/dL. Achieving all parameters indicated triple metabolic control. RESULTS HbA1c levels of patients (n = 5211) were 8.6 ± 1.9% (71 ± 22 mmol/mol) and 7.7 ± 1.7% (61 ± 19 mmol/mol), in Type 1 and Type 2 diabetes, respectively. Glycemic control was achieved in 15.3% and 40.2%, and triple metabolic control was achieved in 5.5% and 10.1%, respectively. Only 1.5% of patients met all the criteria of being non-obese, non-smoker, exercising, and under triple metabolic control. Low education level was a significant predictor of poor glycemic control in both groups. CONCLUSIONS Few patients with Type 2, and even fewer with Type 1 diabetes have optimal metabolic control in Turkey. TEMD study will provide evidence-based information to policy makers to focus more on the quality and sustainability of diabetes care in order to reduce the national burden of the disease.
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Affiliation(s)
- Alper Sonmez
- Health Sciences University, Gulhane Faculty of Medicine, Department of Endocrinology and Metabolism, Ankara, Turkey
| | - Cem Haymana
- Gulhane Training and Research Hospital, Department of Endocrinology and Metabolism, Ankara, Turkey.
| | - Fahri Bayram
- Erciyes University, Faculty of Medicine, Department of Endocrinology and Metabolism, Kayseri, Turkey
| | - Serpil Salman
- Istinye University, Faculty of Medicine, Department of Endocrinology and Metabolism, Istanbul, Turkey
| | - Oguzhan Sitki Dizdar
- Kayseri Training and Research Hospital, Department of Endocrinology and Metabolism, Kayseri, Turkey
| | - Eren Gurkan
- Mustafa Kemal University, Faculty of Medicine, Department of Endocrinology and Metabolism, Hatay, Turkey
| | - Ayse Kargili Carlıoglu
- Erzurum Training and Research Hospital, Department of Endocrinology and Metabolism, Erzurum, Turkey
| | - Cem Barcin
- Health Sciences University, Gulhane Faculty of Medicine, Department of Cardiology, Ankara, Turkey
| | - Tevfik Sabuncu
- Harran University, Faculty of Medicine, Sanliurfa, Turkey
| | - Ilhan Satman
- Istanbul University, Faculty of Medicine, Istanbul, Turkey
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Hadi A, Pourmasoumi M, Najafgholizadeh A, Kafeshani M, Sahebkar A. Effect of purslane on blood lipids and glucose: A systematic review and meta‐analysis of randomized controlled trials. Phytother Res 2018; 33:3-12. [DOI: 10.1002/ptr.6203] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Revised: 07/28/2018] [Accepted: 09/05/2018] [Indexed: 01/28/2023]
Affiliation(s)
- Amir Hadi
- School of Nutrition and Food Science, Food Security Research Center Isfahan University of Medical Sciences Isfahan Iran
| | - Makan Pourmasoumi
- Gastrointestinal and Liver Diseases Research Center (GLDRC) Guilan University of Medical Sciences Rasht Iran
| | | | - Marziyeh Kafeshani
- School of Nutrition and Food Science, Food Security Research Center Isfahan University of Medical Sciences Isfahan Iran
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran
- Neurogenic Inflammation Research Center Mashhad University of Medical Sciences Mashhad Iran
- School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran
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Najder A. Sense of Coherence, Smoking Status, Biochemical Cardiovascular Risk Factors and Body Mass in Blue Collar Workers-Short Report. Am J Mens Health 2018; 12:894-899. [PMID: 29313407 PMCID: PMC6131468 DOI: 10.1177/1557988317748393] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Revised: 10/20/2017] [Accepted: 11/14/2017] [Indexed: 11/30/2022] Open
Abstract
The crucial cause of cardiovascular disorders is atherosclerosis developed by abnormal cholesterols levels or disorders affecting blood glucose. One of the best-known cardiovascular risk factors is also tobacco smoking. Simultaneously, sense of coherence (SoC) as a personal resource motivating to managing one's own health behaviors, such as avoiding tobacco smoking, was reported to be protective against coronary heart disease. Such association was observed in white-collar workers but not in blue-collar workers. According to the above, the present article aims to establish relationships between SoC, smoking behaviors, biochemical markers (BM): lipids and glucose levels and body mass index (BMI) in blue-collar workers. Sense of Coherence Questionnaire (SOC-29), fasting blood test, and BMI were used to assess such relationships. The study group consisted of 304 Polish males working 8-hr shifts in a 4-brigade rotating system. The analysis revealed that SoC level did not differ depending on smoking behavior. The analysis also showed no differences in BMI and BM depending on SoC. Concerning smoking status, the study group was divided into three subgroups which differed regarding triglycerides and glucose levels. The present findings considering SoC indicate that any psychological construct should not be studied separately because probably only some sets of different features may influence one's behavior and BM as well.
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Affiliation(s)
- Anna Najder
- Department of Health and Work
Psychology, Nofer Institute of Occupational Medicine, Łódź, Poland
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Willers C, Iderberg H, Axelsen M, Dahlström T, Julin B, Leksell J, Lindberg A, Lindgren P, Looström Muth K, Svensson AM, Lilja M. Sociodemographic determinants and health outcome variation in individuals with type 1 diabetes mellitus: A register-based study. PLoS One 2018; 13:e0199170. [PMID: 29958293 PMCID: PMC6025867 DOI: 10.1371/journal.pone.0199170] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 06/01/2018] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Socioeconomic status, origin or demographic attributes shall not determine the quality of healthcare delivery, according to e.g. United Nations and European Union rules. Health equity has been defined as the absence of systematic disparities and unwarranted differences between groups defined by differences in social advantages. A study was performed to investigate whether this was applicable to type 1 diabetes mellitus (T1D) care in a setting with universal, tax-funded healthcare. METHODS This retrospective registry-study was based on patient-level data from individuals diagnosed with T1D during 2010-2011 (n = 16,367) in any of seven Swedish county councils (covering ~65% of the Swedish population). Health equity in T1D care was analysed through multivariate regression analyses on absolute HbA1c level at one-year follow-up, one-year change in estimated glomerular filtration rate (eGFR) and one-year change in cardiovascular risk score, using selected sociodemographic dimensions as case-mix factors. RESULTS Higher educational level was consistently associated with lower levels of HbA1c, and so was being married. Never married was associated with worse eGFR development, and lower educational level was associated with higher cardiovascular risk. Women had higher HbA1c levels than men, and glucose control was significantly worse in patients below the age of 25. CONCLUSION Patients' sociodemographic profile was strongly associated with absolute levels of risk factor control in T1D, but also with an increased annual deterioration in eGFR. Whether these systematic differences stem from patient-related problems or healthcare organisational shortcomings is a matter for further research. The results, though, highlight the need for intensified diabetes management education and secondary prevention directed towards T1D patients, taking sociodemographic characteristics into account.
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Affiliation(s)
- Carl Willers
- Dept for Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
- Ivbar Institute, Stockholm, Sweden
| | - Hanna Iderberg
- Ivbar Institute, Stockholm, Sweden
- Medical Management Centre, Karolinska Institutet, Stockholm, Sweden
| | - Mette Axelsen
- Department of Internal Medicine at Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Tobias Dahlström
- Department of Public Health and Caring Sciences, Health Services Research, Uppsala university, Uppsala, Sweden
| | | | - Janeth Leksell
- School of Education, Health and Social Studies, Dalarna University, Dalarna and Clinical diabetology and metabolism, Department of medical sciences, Uppsala University, Uppsala, Sweden
| | | | - Peter Lindgren
- Medical Management Centre, Karolinska Institutet, Stockholm, Sweden
- The Swedish Institute for Health Economics, Lund, Sweden
| | | | - Ann-Marie Svensson
- The Swedish National Diabetes Register, Västra Götalandsregionen, Gothenburg, Sweden
| | - Mikael Lilja
- Department of Public Health and Clinical Medicine, Unit of Research, Education, and Development, Östersund Hospital, Umeå University, Umeå, Sweden
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Borsari L, Malagoli C, Werler MM, Rothman KJ, Malavolti M, Rodolfi R, De Girolamo G, Nicolini F, Vinceti M. Joint Effect of Maternal Tobacco Smoking and Pregestational Diabetes on Preterm Births and Congenital Anomalies: A Population-Based Study in Northern Italy. J Diabetes Res 2018; 2018:2782741. [PMID: 30050951 PMCID: PMC6046136 DOI: 10.1155/2018/2782741] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 06/04/2018] [Accepted: 06/11/2018] [Indexed: 12/21/2022] Open
Abstract
Smoking and pregestational diabetes (PGD) are recognized risk factors for adverse pregnancy outcomes, but to date, no population-based study has investigated their joint effects. Using hospital discharges, we identified all women with PGD delivering in Emilia-Romagna region during 2007-2010 matched 1 : 5 with parturients without diabetes. Our study endpoints were preterm births and congenital anomalies. We measured interaction between PGD and maternal smoking, by calculating excess prevalence and prevalence ratio due to interaction, relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (S). Analyses were performed in the overall study population and in the subgroup whose PGD was validated through diabetes registers. The study included 992 women with PGD (10.5% smokers) and 4788 comparison women (11.9% smokers). The effects of PGD and maternal tobacco smoking were greater than additive for both preterm birth (excess prevalence due to interaction = 11.7%, excess ratio due to interaction = 1.5, RERI = 2.39, AP = 0.51, S = 2.82) and congenital anomalies (excess prevalence due to interaction = 2.2%, excess ratio due to interaction = 1.3, RERI = 1.33, AP = 0.49, S = 5.03). Joint effect on both endpoints was confirmed in the subgroup whose PGD status was validated. In conclusion, we found that maternal tobacco smoking and PGD intensify each other's effect on preterm birth and congenital anomalies.
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Affiliation(s)
- Lucia Borsari
- Department of Biomedical, Metabolic and Neural Sciences, Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Carlotta Malagoli
- Department of Biomedical, Metabolic and Neural Sciences, Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Martha M. Werler
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Modena, Italy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Kenneth J. Rothman
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Modena, Italy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- Research Triangle Institute, Research Triangle Park, NC 27709, USA
| | - Marcella Malavolti
- Department of Biomedical, Metabolic and Neural Sciences, Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Rossella Rodolfi
- Local Health Authority of Reggio Emilia, Reggio Emilia 42122, Italy
| | - Gianfranco De Girolamo
- Department of Public Health, Unit of Epidemiology and Risk Communication, Local Health Authority of Modena, Modena 41126, Italy
| | - Fausto Nicolini
- Local Health Authority of Reggio Emilia, Reggio Emilia 42122, Italy
| | - Marco Vinceti
- Department of Biomedical, Metabolic and Neural Sciences, Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), University of Modena and Reggio Emilia, Modena 41125, Italy
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Modena, Italy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
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Pourmasoumi M, Hadi A, Rafie N, Najafgholizadeh A, Mohammadi H, Rouhani MH. The effect of ginger supplementation on lipid profile: A systematic review and meta-analysis of clinical trials. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2018; 43:28-36. [PMID: 29747751 DOI: 10.1016/j.phymed.2018.03.043] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 01/30/2018] [Accepted: 03/18/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND Elevated levels of blood lipids are a major cause of atherosclerosis and consequently cardiovascular disease. Several studies used ginger as a lipid lowering agent. PURPOSE The aim of the present systematic review and meta-analysis was to clarify the effect of ginger supplementation on lipid parameters. METHODS PubMed, Scopus, Science Direct, ISI Web of Science and Google Scholar were systematically searched until May 2017 to find clinical trials which examined effect of ginger supplementation on level of lipid parameters in adult participants. Means for blood lipids and potential sources of heterogeneity were extracted. A subgroup analysis was applied to find out potential sources of inter-study heterogeneity. RESULTS A total of 12 trials (586 participants) were included in the meta-analysis. Pooled analysis suggested that ginger supplementation reduced triacylglycerol (TAG) (-17.59 mg/dl; 95% CI: -29.32 to -5.87) and low density lipoprotein cholesterol (LDL-C) (-4.90 mg/dl; 95% CI: -22.30 to -6.17). Ginger had no significant effect on total cholesterol (TC) (-5.13 mg/dl, 95% CI: -11.05 to 0.78; P = 0.089) and high density lipoprotein cholesterol (HDL-C) (2.18 mg/dl, 95% CI: -0.08 to 4.45; P = 0.059). As inter-study heterogeneity was high, studies were classified by ginger dosage. Stratified analysis showed a significant reduction in TC (-12.26 mg/dl; 95% CI: -22.37 to -2.16) and TAG (-38.42 mg/dl; 95% CI: -57.01 to -19.82) in studies which used ≤2 g/day of ginger. However, a similar significant effect was not observed in trials with >2 g/day of ginger. Neither studies which used ≤2 g/day nor trials which used >2 g/day of ginger showed significant changes in LDL-C or HDL-C. CONCLUSION The present systematic review and meta-analysis suggests that ginger had a favorable effect on TAG and LDL-C. Also, the result revealed that low dose of ginger (≤2 g/day) had greater lowering impact on TAG and TC. Further studies with large-scale and better design are needed to confirm this result.
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Affiliation(s)
- Makan Pourmasoumi
- Gastrointestinal & Liver Diseases Research Center (GLDRC), Guilan University of Medical Sciences, Rasht, Iran
| | - Amir Hadi
- Gastrointestinal & Liver Diseases Research Center (GLDRC), Guilan University of Medical Sciences, Rasht, Iran
| | - Nahid Rafie
- Gastrointestinal & Liver Diseases Research Center (GLDRC), Guilan University of Medical Sciences, Rasht, Iran
| | | | - Hamed Mohammadi
- Student Research Committee, Department of Clinical Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Hossein Rouhani
- Department of Community Nutrition, School of Nutrition and Food Science, Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
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Oktay AA, Akturk HK, Esenboğa K, Javed F, Polin NM, Jahangir E. Pathophysiology and Prevention of Heart Disease in Diabetes Mellitus. Curr Probl Cardiol 2018; 43:68-110. [DOI: 10.1016/j.cpcardiol.2017.05.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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