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Johannes Siegrist

Bio: Johannes Siegrist is an academic researcher from University of Düsseldorf. The author has contributed to research in topics: Psychosocial & Job strain. The author has an hindex of 85, co-authored 403 publications receiving 30489 citations. Previous affiliations of Johannes Siegrist include University of Marburg & German Institute for Economic Research.


Papers
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TL;DR: The effort-reward imbalance model is proposed to assess adverse health effects of stressful experience at work: reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful.
Abstract: In addition to the person-environment fit model (J. R. French, R. D. Caplan, & R. V. Harrison, 1982) and the demand-control model (R. A. Karasek & T. Theorell, 1990), a third theoretical concept is proposed to assess adverse health effects of stressful experience at work: the effort-reward imbalance model. The focus of this model is on reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Variables measuring low reward in terms of low status control (e.g., lack of promotion prospects, job insecurity) in association with high extrinsic (e.g., work pressure) or intrinsic (personal coping pattern, e.g., high need for control) effort independently predict new cardiovascular events in a prospective study on blue-collar men. Furthermore, these variables partly explain prevalence of cardiovascular risk factors (hypertension, atherogenic lipids) in 2 independent studies. Studying adverse health effects of high-effort/low-reward conditions seems well justified, especially in view of recent developments of the labor market.

4,550 citations

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TL;DR: A psychometrically well-justified measure of work-related stress (ERI) grounded in sociological theory is available for comparative socioepidemiologic investigations in advanced societies within and beyond Europe.

1,921 citations

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TL;DR: The findings suggest that prevention of workplace stress might decrease disease incidence; however, this strategy would have a much smaller effect than would tackling of standard risk factors, such as smoking.

853 citations

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TL;DR: This is apparently the first report showing independent effects of components of two alternative job stress models-the effort-reward imbalance model and the job strain model (job control only)-on coronary heart disease.
Abstract: OBJECTIVES: This study examined the association between two alternative job stress models-the effort-reward imbalance model and the job strain model-and the risk of coronary heart disease among male and female British civil servants. METHODS: The logistic regression analyses were based on a prospective cohort study (Whitehall II study) comprising 6895 men and 3413 women aged 35 to 55 years. Baseline measures of both job stress models were related to new reports of coronary heart disease over a mean 5.3 years of follow-up. RESULTS: The imbalance between personal efforts (competitiveness, work-related overcommitment, and hostility) and rewards (poor promotion prospects and a blocked career') was associated with a 2.15-fold higher risk of new coronary heart disease. Job strain and high job demands were not related to coronary heart disease; however, low job control was strongly associated with new disease. The odds ratios for low job control were 2.38 and 1.56 for self-reported and externally assessed job co...

837 citations

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TL;DR: CAC scoring results in a high reclassification rate in the intermediate-risk cohort, demonstrating the benefit of imaging of subclinical coronary atherosclerosis and supporting its application, especially in carefully selected individuals with intermediate risk.

690 citations


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01 Jan 2014
TL;DR: These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care.
Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

9,618 citations

Journal ArticleDOI
TL;DR: In this paper, the authors give a state-of-the-art overview of the job demands resources (JD•R) model and discuss the strengths and weaknesses of the demand control model and the effort reward imbalance model regarding their predictive value for employee well being.
Abstract: Purpose – The purpose of this paper is to give a state‐of‐the art overview of the Job Demands‐Resources (JD‐R) modelDesign/methodology/approach – The strengths and weaknesses of the demand‐control model and the effort‐reward imbalance model regarding their predictive value for employee well being are discussed. The paper then introduces the more flexible JD‐R model and discusses its basic premises.Findings – The paper provides an overview of the studies that have been conducted with the JD‐R model. It discusses evidence for each of the model's main propositions. The JD‐R model can be used as a tool for human resource management. A two‐stage approach can highlight the strengths and weaknesses of individuals, work groups, departments, and organizations at large.Originality/value – This paper challenges existing stress models, and focuses on both negative and positive indicators of employee well being. In addition, it outlines how the JD‐R model can be applied to a wide range of occupations, and be used to i...

7,681 citations

Journal ArticleDOI
TL;DR: In this paper, a randomized clinical trial was conducted to evaluate the effect of preterax and Diamicron Modified Release Controlled Evaluation (MDE) on the risk of stroke.
Abstract: ABI : ankle–brachial index ACCORD : Action to Control Cardiovascular Risk in Diabetes ADVANCE : Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation AGREE : Appraisal of Guidelines Research and Evaluation AHA : American Heart Association apoA1 : apolipoprotein A1 apoB : apolipoprotein B CABG : coronary artery bypass graft surgery CARDS : Collaborative AtoRvastatin Diabetes Study CCNAP : Council on Cardiovascular Nursing and Allied Professions CHARISMA : Clopidogrel for High Athero-thrombotic Risk and Ischemic Stabilisation, Management, and Avoidance CHD : coronary heart disease CKD : chronic kidney disease COMMIT : Clopidogrel and Metoprolol in Myocardial Infarction Trial CRP : C-reactive protein CURE : Clopidogrel in Unstable Angina to Prevent Recurrent Events CVD : cardiovascular disease DALYs : disability-adjusted life years DBP : diastolic blood pressure DCCT : Diabetes Control and Complications Trial ED : erectile dysfunction eGFR : estimated glomerular filtration rate EHN : European Heart Network EPIC : European Prospective Investigation into Cancer and Nutrition EUROASPIRE : European Action on Secondary and Primary Prevention through Intervention to Reduce Events GFR : glomerular filtration rate GOSPEL : Global Secondary Prevention Strategies to Limit Event Recurrence After MI GRADE : Grading of Recommendations Assessment, Development and Evaluation HbA1c : glycated haemoglobin HDL : high-density lipoprotein HF-ACTION : Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing HOT : Hypertension Optimal Treatment Study HPS : Heart Protection Study HR : hazard ratio hsCRP : high-sensitivity C-reactive protein HYVET : Hypertension in the Very Elderly Trial ICD : International Classification of Diseases IMT : intima-media thickness INVEST : International Verapamil SR/Trandolapril JTF : Joint Task Force LDL : low-density lipoprotein Lp(a) : lipoprotein(a) LpPLA2 : lipoprotein-associated phospholipase 2 LVH : left ventricular hypertrophy MATCH : Management of Atherothrombosis with Clopidogrel in High-risk Patients with Recent Transient Ischaemic Attack or Ischaemic Stroke MDRD : Modification of Diet in Renal Disease MET : metabolic equivalent MONICA : Multinational MONItoring of trends and determinants in CArdiovascular disease NICE : National Institute of Health and Clinical Excellence NRT : nicotine replacement therapy NSTEMI : non-ST elevation myocardial infarction ONTARGET : Ongoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial OSA : obstructive sleep apnoea PAD : peripheral artery disease PCI : percutaneous coronary intervention PROactive : Prospective Pioglitazone Clinical Trial in Macrovascular Events PWV : pulse wave velocity QOF : Quality and Outcomes Framework RCT : randomized clinical trial RR : relative risk SBP : systolic blood pressure SCORE : Systematic Coronary Risk Evaluation Project SEARCH : Study of the Effectiveness of Additional Reductions in Cholesterol and SHEP : Systolic Hypertension in the Elderly Program STEMI : ST-elevation myocardial infarction SU.FOL.OM3 : SUpplementation with FOlate, vitamin B6 and B12 and/or OMega-3 fatty acids Syst-Eur : Systolic Hypertension in Europe TNT : Treating to New Targets UKPDS : United Kingdom Prospective Diabetes Study VADT : Veterans Affairs Diabetes Trial VALUE : Valsartan Antihypertensive Long-term Use VITATOPS : VITAmins TO Prevent Stroke VLDL : very low-density lipoprotein WHO : World Health Organization ### 1.1 Introduction Atherosclerotic cardiovascular disease (CVD) is a chronic disorder developing insidiously throughout life and usually progressing to an advanced stage by the time symptoms occur. It remains the major cause of premature death in Europe, even though CVD mortality has …

7,482 citations

Journal ArticleDOI
TL;DR: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Jiménez, ScD, SM Lori Chaffin Jordan,MD, PhD Suzanne E. Judd, PhD
Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

7,190 citations