The National High Blood Pressure Education Program presents the complete Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Like its predecessors, the purpose is to provide an evidence-based approach to the prevention and management of hypertension. The key messages of this report are these: in those older than age 50, systolic blood pressure (BP) of greater than 140 mm Hg is a more important cardiovascular disease (CVD) risk factor than diastolic BP; beginning at 115/75 mm Hg, CVD risk doubles for each increment of 20/10 mm Hg; those who are normotensive at 55 years of age will have a 90% lifetime risk of developing hypertension; prehypertensive individuals (systolic BP 120-139 mm Hg or diastolic BP 80-89 mm Hg) require health-promoting lifestyle modifications to prevent the progressive rise in blood pressure and CVD; for uncomplicated hypertension, thiazide diuretic should be used in drug treatment for most, either alone or combined with drugs from other classes; this report delineates specific high-risk conditions that are compelling indications for the use of other antihypertensive drug classes (angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, beta-blockers, calcium channel blockers); two or more antihypertensive medications will be required to achieve goal BP (<140/90 mm Hg, or <130/80 mm Hg) for patients with diabetes and chronic kidney disease; for patients whose BP is more than 20 mm Hg above the systolic BP goal or more than 10 mm Hg above the diastolic BP goal, initiation of therapy using two agents, one of which usually will be a thiazide diuretic, should be considered; regardless of therapy or care, hypertension will be controlled only if patients are motivated to stay on their treatment plan. Positive experiences, trust in the clinician, and empathy improve patient motivation and satisfaction. This report serves as a guide, and the committee continues to recognize that the responsible physician's judgment remains paramount.

Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure

https://hull-repository.worktribe.com/preview/1797952/1-s2.0-S0140673618322797-main.pdf

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

The metabolic syndrome has received increased attention in the past few years. This statement from the American Heart Association (AHA) and the National Heart, Lung, and Blood Institute (NHLBI) is intended to provide up-to-date guidance for professionals on the diagnosis and management of the metabolic syndrome in adults.

The metabolic syndrome is a constellation of interrelated risk factors of metabolic origin— metabolic risk factors —that appear to directly promote the development of atherosclerotic cardiovascular disease (ASCVD).1 Patients with the metabolic syndrome also are at increased risk for developing type 2 diabetes mellitus. Another set of conditions, the underlying risk factors , give rise to the metabolic risk factors. In the past few years, several expert groups have attempted to set forth simple diagnostic criteria to be used in clinical practice to identify patients who manifest the multiple components of the metabolic syndrome. These criteria have varied somewhat in specific elements, but in general they include a combination of both underlying and metabolic risk factors.

The most widely recognized of the metabolic risk factors are atherogenic dyslipidemia, elevated blood pressure, and elevated plasma glucose. Individuals with these characteristics commonly manifest a prothrombotic state and a pro-inflammatory state as well. Atherogenic dyslipidemia consists of an aggregation of lipoprotein abnormalities including elevated serum triglyceride and apolipoprotein B (apoB), increased small LDL particles, and a reduced level of HDL cholesterol (HDL-C). The metabolic syndrome is often referred to as if it were a discrete entity with a single cause. Available data suggest that it truly is a syndrome, ie, a grouping of ASCVD risk factors, but one that probably has more than one cause. Regardless of cause, the syndrome identifies individuals at an elevated risk for ASCVD. The magnitude of the increased risk can vary according to which components of the syndrome are …

https://www.lipidcenter.com/pdf/metabolic.pdf

Diagnosis and Management of the Metabolic Syndrome An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement

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

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

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

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

Objective: To estimate the association between body mass index (BMI) and health-related quality of life (HRQL) and examine whether joint pain and obesity-related comorbidities mediate the BMI-HRQL association.



Research Methods and Procedures: Population-based survey data from the 1999 Behavioral Risk Factor Surveillance Survey. Adults (N = 155, 989) were classified according to BMI as underweight (<18.5 kg/m2), desirable weight (18.5 to 24.9 kg/m2), overweight (25 to 29.9 kg/m2), obese class I (30 to 34.9 kg/m2), obese class II (35 to 39.9 kg/m2), and obese class III (≥40 kg/m2). Data including general health status, unhealthy days in the past 30 caused by physical problems and mental problems, and total unhealthy days in the past 30 were collected.



Results: After adjusting for age, sex, race, smoking, education, and income, we observed J-shaped associations between BMI and HRQL. Compared with desirable weight adults, underweight, overweight, and obesity classes I, II, and III adults [odds ratio (OR) = 1.57, 1.19, 1.95, 2.72, and 4.36, respectively] were significantly (p < 0.001) more likely to report fair/poor general health status. For unhealthy days caused by physical problems, the corresponding ORs were 1.51, 1.15, 1.66, 2.27, and 3.61 (p < 0.001). For unhealthy days caused by mental problems, the ORs were 1.35, 1.14 1.43, 1.57, and 2.25 (p < 0.001). For total unhealthy days, the corresponding ORs were 1.27, 1.09, 1.37, 1.73, and 2.46 (p < 0.01). Adding joint pain and obesity-related comorbidities into models attenuated BMI-HRQL associations.



Discussion: Associations between BMI and HRQL indices were J-shaped. Joint pain and comorbidities may mediate BMI-HRQL associations.

https://onlinelibrary.wiley.com/doi/pdf/10.1038/oby.2003.33

Obesity and quality of life: mediating effects of pain and comorbidities.

Effect of n−3 PUFA supplementation on cognitive function throughout the life span from infancy to old age: a systematic review and meta-analysis of randomized controlled trials

Sleep and obesity in preschool children.

Objectives. We examined the role of body mass index (BMI) and other factors in driver deaths within 30 days after motor vehicle crashes.Methods. We collected data for 22 107 drivers aged 16 years and older who were involved in motor vehicle crashes from the Crashworthiness Data System of the National Automotive Sampling System (1997–2001). We used logistic regression and adjusted for confounding factors to analyze associations between BMI and driver fatality and the associations between BMI and gender, age, seatbelt use, type of collision, airbag deployment, and change in velocity during a crash.Results. The fatality rate was 0.87% (95% confidence interval [CI]=0.50, 1.24) among men and 0.43% (95% CI=0.31, 0.56) among women involved as drivers in motor vehicle crashes. Risk for death increased significantly at both ends of the BMI continuum among men but not among women (P<.05). The association between BMI and male fatality increased significantly with a change in velocity and was modified by the type of ...

Obesity and risk for death due to motor vehicle crashes

Objective To investigate ethnic difference in the associations of BMI with comorbidity, mortality, and body composition between mainland Chinese and U.S. whites. Methods Ethnic-comparison study using data from China Health and Nutrition Survey, U.S. National Health and Nutrition Examination Survey, and data from Zhejiang University (China) and Columbia University (U.S.). Results Chinese people experienced greater odds of comorbidities than whites for a given BMI after standardizing for age and sex: 43% for diabetes, 30% for dyslipidemia, 28% for hypertension, 38% for metabolic syndrome, and 48% for hyperuricemia. Comparisons of BMI-mortality associations found that the U-shaped BMI-mortality curve shifted 1-2 kg m(-2) to the left in Chinese compared to whites. Compared to whites at BMIs of 25 and 30 kg m(-2), corresponding cutoffs in Chinese were 22.5 and 25.9 kg m(-2) in men, and 22.8 and 26.6 kg m(-2) in women after both fat and fat distribution were taken into account. Conclusions Comorbidity, mortality, and body composition data consistently support the use of lower BMI cutoffs in Chinese than those in whites.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/oby.20995

Shankuan Zhu

Papers

Obesity and quality of life: mediating effects of pain and comorbidities.

Effect of n−3 PUFA supplementation on cognitive function throughout the life span from infancy to old age: a systematic review and meta-analysis of randomized controlled trials

Sleep and obesity in preschool children.

Obesity and risk for death due to motor vehicle crashes

Lower BMI cutoffs to define overweight and obesity in China