Author
Sarah H. Wild
Other affiliations: University of London, Western General Hospital, National University of Rwanda
Bio: Sarah H. Wild is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Population & Type 2 diabetes. The author has an hindex of 93, co-authored 392 publications receiving 63253 citations. Previous affiliations of Sarah H. Wild include University of London & Western General Hospital.
Papers published on a yearly basis
Papers
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TL;DR: Findings indicate that the "diabetes epidemic" will continue even if levels of obesity remain constant, and given the increasing prevalence of obesity, it is likely that these figures provide an underestimate of future diabetes prevalence.
Abstract: OBJECTIVE —The goal of this study was to estimate the prevalence of diabetes and the number of people of all ages with diabetes for years 2000 and 2030. RESEARCH DESIGN AND METHODS —Data on diabetes prevalence by age and sex from a limited number of countries were extrapolated to all 191 World Health Organization member states and applied to United Nations’ population estimates for 2000 and 2030. Urban and rural populations were considered separately for developing countries. RESULTS —The prevalence of diabetes for all age-groups worldwide was estimated to be 2.8% in 2000 and 4.4% in 2030. The total number of people with diabetes is projected to rise from 171 million in 2000 to 366 million in 2030. The prevalence of diabetes is higher in men than women, but there are more women with diabetes than men. The urban population in developing countries is projected to double between 2000 and 2030. The most important demographic change to diabetes prevalence across the world appears to be the increase in the proportion of people >65 years of age. CONCLUSIONS —These findings indicate that the “diabetes epidemic” will continue even if levels of obesity remain constant. Given the increasing prevalence of obesity, it is likely that these figures provide an underestimate of future diabetes prevalence.
16,648 citations
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Elizabeth K. Speliotes1, Elizabeth K. Speliotes2, Cristen J. Willer3, Sonja I. Berndt +410 more•Institutions (86)
TL;DR: Genetic loci associated with body mass index map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor, which may provide new insights into human body weight regulation.
Abstract: Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
2,632 citations
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Cristen J. Willer1, Ellen M. Schmidt1, Sebanti Sengupta1, Gina M. Peloso2 +316 more•Institutions (87)
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
Abstract: Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
2,585 citations
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TL;DR: It is demonstrated that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.
Abstract: Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.
2,022 citations
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TL;DR: It is suggested that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
Abstract: African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
1,957 citations
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28,685 citations
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TL;DR: In this article, a randomized controlled trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly people was presented. But the authors did not discuss the effect of the combination therapy in patients living with systolic hypertension.
Abstract: ABCD
: Appropriate Blood pressure Control in Diabetes
ABI
: ankle–brachial index
ABPM
: ambulatory blood pressure monitoring
ACCESS
: Acute Candesartan Cilexetil Therapy in Stroke Survival
ACCOMPLISH
: Avoiding Cardiovascular Events in Combination Therapy in Patients Living with Systolic Hypertension
ACCORD
: Action to Control Cardiovascular Risk in Diabetes
ACE
: angiotensin-converting enzyme
ACTIVE I
: Atrial Fibrillation Clopidogrel Trial with Irbesartan for Prevention of Vascular Events
ADVANCE
: Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation
AHEAD
: Action for HEAlth in Diabetes
ALLHAT
: Antihypertensive and Lipid-Lowering Treatment to Prevent Heart ATtack
ALTITUDE
: ALiskiren Trial In Type 2 Diabetes Using Cardio-renal Endpoints
ANTIPAF
: ANgioTensin II Antagonist In Paroxysmal Atrial Fibrillation
APOLLO
: A Randomized Controlled Trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly People
ARB
: angiotensin receptor blocker
ARIC
: Atherosclerosis Risk In Communities
ARR
: aldosterone renin ratio
ASCOT
: Anglo-Scandinavian Cardiac Outcomes Trial
ASCOT-LLA
: Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm
ASTRAL
: Angioplasty and STenting for Renal Artery Lesions
A-V
: atrioventricular
BB
: beta-blocker
BMI
: body mass index
BP
: blood pressure
BSA
: body surface area
CA
: calcium antagonist
CABG
: coronary artery bypass graft
CAPPP
: CAPtopril Prevention Project
CAPRAF
: CAndesartan in the Prevention of Relapsing Atrial Fibrillation
CHD
: coronary heart disease
CHHIPS
: Controlling Hypertension and Hypertension Immediately Post-Stroke
CKD
: chronic kidney disease
CKD-EPI
: Chronic Kidney Disease—EPIdemiology collaboration
CONVINCE
: Controlled ONset Verapamil INvestigation of CV Endpoints
CT
: computed tomography
CV
: cardiovascular
CVD
: cardiovascular disease
D
: diuretic
DASH
: Dietary Approaches to Stop Hypertension
DBP
: diastolic blood pressure
DCCT
: Diabetes Control and Complications Study
DIRECT
: DIabetic REtinopathy Candesartan Trials
DM
: diabetes mellitus
DPP-4
: dipeptidyl peptidase 4
EAS
: European Atherosclerosis Society
EASD
: European Association for the Study of Diabetes
ECG
: electrocardiogram
EF
: ejection fraction
eGFR
: estimated glomerular filtration rate
ELSA
: European Lacidipine Study on Atherosclerosis
ESC
: European Society of Cardiology
ESH
: European Society of Hypertension
ESRD
: end-stage renal disease
EXPLOR
: Amlodipine–Valsartan Combination Decreases Central Systolic Blood Pressure more Effectively than the Amlodipine–Atenolol Combination
FDA
: U.S. Food and Drug Administration
FEVER
: Felodipine EVent Reduction study
GISSI-AF
: Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico-Atrial Fibrillation
HbA1c
: glycated haemoglobin
HBPM
: home blood pressure monitoring
HOPE
: Heart Outcomes Prevention Evaluation
HOT
: Hypertension Optimal Treatment
HRT
: hormone replacement therapy
HT
: hypertension
HYVET
: HYpertension in the Very Elderly Trial
IMT
: intima-media thickness
I-PRESERVE
: Irbesartan in Heart Failure with Preserved Systolic Function
INTERHEART
: Effect of Potentially Modifiable Risk Factors associated with Myocardial Infarction in 52 Countries
INVEST
: INternational VErapamil SR/T Trandolapril
ISH
: Isolated systolic hypertension
JNC
: Joint National Committee
JUPITER
: Justification for the Use of Statins in Primary Prevention: an Intervention Trial Evaluating Rosuvastatin
LAVi
: left atrial volume index
LIFE
: Losartan Intervention For Endpoint Reduction in Hypertensives
LV
: left ventricle/left ventricular
LVH
: left ventricular hypertrophy
LVM
: left ventricular mass
MDRD
: Modification of Diet in Renal Disease
MRFIT
: Multiple Risk Factor Intervention Trial
MRI
: magnetic resonance imaging
NORDIL
: The Nordic Diltiazem Intervention study
OC
: oral contraceptive
OD
: organ damage
ONTARGET
: ONgoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial
PAD
: peripheral artery disease
PATHS
: Prevention And Treatment of Hypertension Study
PCI
: percutaneous coronary intervention
PPAR
: peroxisome proliferator-activated receptor
PREVEND
: Prevention of REnal and Vascular ENdstage Disease
PROFESS
: Prevention Regimen for Effectively Avoiding Secondary Strokes
PROGRESS
: Perindopril Protection Against Recurrent Stroke Study
PWV
: pulse wave velocity
QALY
: Quality adjusted life years
RAA
: renin-angiotensin-aldosterone
RAS
: renin-angiotensin system
RCT
: randomized controlled trials
RF
: risk factor
ROADMAP
: Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention
SBP
: systolic blood pressure
SCAST
: Angiotensin-Receptor Blocker Candesartan for Treatment of Acute STroke
SCOPE
: Study on COgnition and Prognosis in the Elderly
SCORE
: Systematic COronary Risk Evaluation
SHEP
: Systolic Hypertension in the Elderly Program
STOP
: Swedish Trials in Old Patients with Hypertension
STOP-2
: The second Swedish Trial in Old Patients with Hypertension
SYSTCHINA
: SYSTolic Hypertension in the Elderly: Chinese trial
SYSTEUR
: SYSTolic Hypertension in Europe
TIA
: transient ischaemic attack
TOHP
: Trials Of Hypertension Prevention
TRANSCEND
: Telmisartan Randomised AssessmeNt Study in ACE iNtolerant subjects with cardiovascular Disease
UKPDS
: United Kingdom Prospective Diabetes Study
VADT
: Veterans' Affairs Diabetes Trial
VALUE
: Valsartan Antihypertensive Long-term Use Evaluation
WHO
: World Health Organization
### 1.1 Principles
The 2013 guidelines on hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology …
14,173 citations
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TL;DR: These projections represent a set of three visions of the future for population health, based on certain explicit assumptions, which enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends.
Abstract: Background Global and regional projections of mortality and burden of disease by cause for the years 2000, 2010, and 2030 were published by Murray and Lopez in 1996 as part of the Global Burden of Disease project. These projections, which are based on 1990 data, continue to be widely quoted, although they are substantially outdated; in particular, they substantially underestimated the spread of HIV/AIDS. To address the widespread demand for information on likely future trends in global health, and thereby to support international health policy and priority setting, we have prepared new projections of mortality and burden of disease to 2030 starting from World Health Organization estimates of mortality and burden of disease for 2002. This paper describes the methods, assumptions, input data, and results. Methods and Findings Relatively simple models were used to project future health trends under three scenarios—baseline, optimistic, and pessimistic—based largely on projections of economic and social development, and using the historically observed relationships of these with cause-specific mortality rates. Data inputs have been updated to take account of the greater availability of death registration data and the latest available projections for HIV/AIDS, income, human capital, tobacco smoking, body mass index, and other inputs. In all three scenarios there is a dramatic shift in the distribution of deaths from younger to older ages and from communicable, maternal, perinatal, and nutritional causes to noncommunicable disease causes. The risk of death for children younger than 5 y is projected to fall by nearly 50% in the baseline scenario between 2002 and 2030. The proportion of deaths due to noncommunicable disease is projected to rise from 59% in 2002 to 69% in 2030. Global HIV/AIDS deaths are projected to rise from 2.8 million in 2002 to 6.5 million in 2030 under the baseline scenario, which assumes coverage with antiretroviral drugs reaches 80% by 2012. Under the optimistic scenario, which also assumes increased prevention activity, HIV/AIDS deaths are projected to drop to 3.7 million in 2030. Total tobacco-attributable deaths are projected to rise from 5.4 million in 2005 to 6.4 million in 2015 and 8.3 million in 2030 under our baseline scenario. Tobacco is projected to kill 50% more people in 2015 than HIV/AIDS, and to be responsible for 10% of all deaths globally. The three leading causes of burden of disease in 2030 are projected to include HIV/AIDS, unipolar depressive disorders, and ischaemic heart disease in the baseline and pessimistic scenarios. Road traffic accidents are the fourth leading cause in the baseline scenario, and the third leading cause ahead of ischaemic heart disease in the optimistic scenario. Under the baseline scenario, HIV/AIDS becomes the leading cause of burden of disease in middle- and low-income countries by 2015. Conclusions These projections represent a set of three visions of the future for population health, based on certain explicit assumptions. Despite the wide uncertainty ranges around future projections, they enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, the continued spread of HIV/AIDS in many regions, and the continuation of the epidemiological transition in developing countries. The results depend strongly on the assumption that future mortality trends in poor countries will have a relationship to economic and social development similar to those that have occurred in the higher-income countries.
10,090 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
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TL;DR: Since the 1990 NIH-sponsored conference on polycystic ovary syndrome, it has become appreciated that the syndrome encompasses a broader spectrum of signs and symptoms of ovarian dysfunction than those defined by the original diagnostic criteria.
8,217 citations