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G. David Batty

Bio: G. David Batty is an academic researcher from University College London. The author has contributed to research in topics: Cohort study & Risk factor. The author has an hindex of 88, co-authored 451 publications receiving 23826 citations. Previous affiliations of G. David Batty include Finnish Institute of Occupational Health & University of London.


Papers
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Journal ArticleDOI
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

Journal ArticleDOI
31 Jul 2012-BMJ
TL;DR: A dose-response association between psychological distress across the full range of severity and an increased risk of mortality was found and this association remained after adjustment for somatic comorbidity plus behavioural and socioeconomic factors.
Abstract: Objective To quantify the link between lower, subclinically symptomatic, levels of psychological distress and cause-specific mortality in a large scale, population based study. Design Individual participant meta-analysis of 10 large prospective cohort studies from the Health Survey for England. Baseline psychological distress measured by the 12 item General Health Questionnaire score, and mortality from death certification. Participants 68 222 people from general population samples of adults aged 35 years and over, free of cardiovascular disease and cancer, and living in private households in England at study baseline. Main outcome measures Death from all causes (n=8365), cardiovascular disease including cerebrovascular disease (n=3382), all cancers (n=2552), and deaths from external causes (n=386). Mean follow-up was 8.2 years (standard deviation 3.5). Results We found a dose-response association between psychological distress across the full range of severity and an increased risk of mortality (age and sex adjusted hazard ratio for General Health Questionnaire scores of 1-3 v score 0: 1.20, 95% confidence interval 1.13 to 1.27; scores 4-6: 1.43, 1.31 to 1.56; and scores 7-12: 1.94, 1.66 to 2.26; P Conclusions Psychological distress is associated with increased risk of mortality from several major causes in a dose-response pattern. Risk of mortality was raised even at lower levels of distress.

509 citations

Journal ArticleDOI
TL;DR: Employees who work long hours have a higher risk of stroke than those working standard hours; the association with coronary heart disease is weaker; these findings suggest that more attention should be paid to the management of vascular risk factors in individuals whoWork long hours.

497 citations

Journal ArticleDOI
TL;DR: In all studies, higher IQ in the first two decades of life was related to lower rates of total mortality in middle to late adulthood, and an inverse IQ-mortality relation was shown.

468 citations

Journal ArticleDOI
02 Nov 2006-BMJ
TL;DR: Breast feeding has little or no effect on intelligence in children and the mother's IQ was more highly predictive of breastfeeding status than were her race, education, age, poverty status, smoking, the home environment, or the child's birth weight or birth order.
Abstract: Objective To assess the importance of maternal intelligence, and the effect of controlling for it and other important confounders, in the link between breast feeding and children’s intelligence. Design Examination of the effect of breast feeding on cognitive ability and the impact of a range of potential confounders, in particular maternal IQ, within a national database. Additional analyses compared pairs of siblings from the sample who were and were not breast fed. The results are considered in the context of other studies that have also controlled for parental intelligence via meta-analysis. Setting 1979 US national longitudinal survey of youth. Subjects Data on 5475 children, the offspring of 3161 mothers in the longitudinal survey. Main outcome measure IQ in children measured by Peabody individual achievement test. Results The mother’s IQ was more highly predictive of breastfeeding status than were her race, education, age, poverty status, smoking, the home environment, or the child’s birth weight or birth order. One standard deviation advantage in maternal IQ more than doubled the odds of breast feeding. Before adjustment, breast feeding was associated with an increase of around 4 points in mental ability. Adjustment for maternal intelligence accounted for most of this effect. When fully adjusted for a range of relevant confounders, the effect was small (0.52) and non-significant (95% confidence interval − 0.19 to 1.23). The results of the sibling comparisons and meta-analysis corroborated these findings. Conclusions Breast feeding has little or no effect on intelligence in children. While breast feeding has many advantages for the child and mother, enhancement of the child’s intelligence is unlikely to be among them.

425 citations


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TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations

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, 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

Journal ArticleDOI
TL;DR: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne
Abstract: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee

6,181 citations