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

Dual-energy x-ray absorptiometry (DXA) is widely applied for estimating body fat. The percentage of body mass as fat (%fat) is predicted from a DXA-estimated RST value defined as the ratio of soft tissue attenuation at two photon energies (e.g., 40 keV and 70 keV). Theoretically, the RST concept depends on the mass of each major element in the human body. The DXA RST values, however, have never been fully evaluated by measured human elemental composition. The present investigation evaluated the DXA RST value by the total body mass of 11 major elements and the DXA %fat by the five-component (5C) model, respectively. Six elements (i.e. C, N, Na, P, Cl and Ca) were measured by in vivo neutron activation analysis, and potassium (i.e. K) by whole-body 40K counting in 27 healthy adults. Models were developed for predicting the total body mass of four additional elements (i.e. H, O, Mg and S). The elemental content of soft tissue, after correction for bone mineral elements, was used to predict the RST values. The DXA RST values were strongly associated with the RST values predicted from elemental content (r = 0.976, P < 0.001), although there was a tendency for the elemental-predicted RST to systematically exceed the DXA-measured RST (mean ± SD, 1.389 ± 0.024 versus 1.341 ± 0.024). DXA-estimated %fat was strongly associated with 5C %fat (24.4 ± 12.0% versus 24.9 ± 11.1%, r = 0.983, P < 0.001). DXA RST is evaluated by in vivo elemental composition, and the present study supports the underlying physical concept and accuracy of the DXA method for estimating %fat.

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Estimation of percentage body fat by dual-energy x-ray absorptiometry: evaluation by in vivo human elemental composition

Aims: To review the evidence on moderate alcohol intake and motor vehicle crash (MVC) risk, and discuss the possible public health tension in balancing risk reduction and increment with respect to moderate alcohol intake. Method: A Medline review was conducted on moderate alcohol intake, MVC, and cardiovascular disease (CVD) risks. Result: Moderate alcohol intake (24 g ethanol, two US standard drinks, or less a day) is associated with 20% reduction in risk of CVD. Public awareness of this may contribute to why rates of driving with blood alcohol content (BAC) <0.08 g/dl in the United States are static. Studies show 3- to 17-fold increased risk of a fatal MVC with BAC < 0.08 g/dl compared to sober drivers. The United States has 0.08 g/dl BAC laws, higher than that reached by a driver drinking two drinks per day or less. Conclusion: The public should be educated that although moderate alcohol drinking may not violate BAC laws, it still carries significant risk of MVC. Current BAC laws in some countries needs re-evaluation.

/pdf/moderate-alcohol-intake-and-motor-vehicle-crashes-the-43njtldc68.pdf

Moderate alcohol intake and motor vehicle crashes: the conflict between health advantage and at-risk use

OBJECTIVE: The purpose of this study is to investigate the relationships among motorcycle rider helmet, alcohol use and the full spectrum of health outcomes following crashes. METHODS: Data from the National Highway Traffic Safety Administration-sponsored Crash Outcome Data Evaluation System (CODES) for Wisconsin, 2002, were used to study 2462 motorcycle crash victims. Logistic regression models were used to assess the relationship of helmet and alcohol use with outcomes. RESULTS: Compared to helmeted motorcycle riders, unhelmeted riders were more likely to require inpatient hospitalization (Relative Risk Ratio [RRR] = 1.4; 95% confidence interval [CI]:1.1-1.8) or die (RR = 1.9, 95% CI:1.0-3.7) but equally likely to be treated in emergency departments. Injury patterns differed by helmet use. Unhelmeted riders were more likely to suffer injuries of the head (odds ratio [OR] = 2.3, 95% CI:1.5-3.3) or face (OR = 3.0, 95% CI:2.1-4.2) than helmeted riders. No difference was observed in other injuries, including spine/neck injuries. Reported alcohol use was more prevalent among patients who were inpatients or died, and was associated with higher likelihood of not wearing a helmet (OR = 7.0, 95% CI:4.8-12.9). CONCLUSION: Motorcycle riders who are inpatients or die in a crash are less likely to be helmeted and more likely to sustain head or face injuries. Alcohol use is associated with unhelmeted riding and increased risk of poor outcomes. These findings support policy and educational efforts promoting helmet use, which seek to decrease these tragedies.

Increased risk of death or disability in unhelmeted Wisconsin motorcyclists.

Introduction: To describe the relationship between bicycle helmet use and injury pattern sustained by patients presenting to an emergency department (ED) in Singapore for bicycle-related trauma. Methods: Data was collected from all individuals treated for bicycle-related trauma between September 1, 2004 and May 31, 2005 using a closed-ended questionnaire. Results: 160 bicyclists with mean age of 34.4 years (range 10 to 89 years) were surveyed. Among them, 80 percent were male and 30.6 percent were non-residents. Helmets were worn by 10.6 percent of the patients. Alcohol was clinically detected in 11.3 percent of bicyclists. There was no difference in bicycle helmet use between Singaporeans and non-residents (p-value is 0.275). However, compared to younger bicyclists, bicyclists aged 30 years or older (p-value is less than 0.05), and compared to recreational or sport bicyclists, those who commute by bicycle, tended not to wear helmets (p-value is less than 0.01). Compared to Singaporeans (p-value helmets did not protect against head injury. Comparing the helmeted group with the non-helmeted group, injury patterns by body region were: head injury 5.9 percent versus 40.0 percent (p-value is less is less than 0.05), non-residents and bicyclists aged 30 years or older (p-value is 0.011) believed that than 0.01); facial injury 5.9 percent versus 37.1 percent (p-value is less than 0.05). Not wearing a helmet, being hit by a motor vehicle and age were significantly associated with higher injury severity scores, after adjusting for several potential confounding factors. Conclusion: Bicycle helmet use was low in our sample of injured patients. When worn, protection against injury was demonstrated. A campaign to promote use of bicycle helmets should be targeted at non-residents and older bicyclists. Authorities should consider compulsory helmet laws for bicyclists and expanding anti-drunk driving campaigns to target alcohol-intoxicated bicyclists. Language: en

Helmet use and bicycle-related trauma in patients presenting to an acute hospital in Singapore.

OBJECTIVE: To investigate whether long-term weight fluctuation is associated with the fasting serum insulin concentration. DESIGN AND SUBJECTS: Weight histories of 1932 male Japanese workers aged 40–59 y were analyzed in relation to their current fasting serum insulin concentration. MEASUREMENTS:Individual weight fluctuation was calculated by root mean square error (RMSE) along the linear regression line of weight measured at five to six different ages. RESULTS: The mean RMSE and fasting insulin concentration were 1.22 kg and 4.5 μU/ml, respectively. The multivariate adjusted insulin level became higher with the increase in weight fluctuation. Subanalysis stratified by current body mass index (BMI) showed that the multivariate adjusted insulin level in individuals in the top quartile of fluctuation was 4.3 μU/ml, against 3.9 μU/ml in those in the bottom quartile (P=0.018, analysis of covariance (ANCOVA)) in the normal weight subgroup with current BMI below 25 kg/m2. In the overweight subgroup with BMI 25 kg/m2 or above, the level was 6.9 μU/ml in individuals in the top quartile and 6.2 μU/ml in those in the bottom quartile (P=0.054, ANCOVA). CONCLUSION: The results suggest that weight fluctuation increases the risk of developing hyperinsulinemia. Prospective observations together with measurement of changes in adiposity are needed for confirmation.

Shankuan Zhu

Papers

Estimation of percentage body fat by dual-energy x-ray absorptiometry: evaluation by in vivo human elemental composition

Moderate alcohol intake and motor vehicle crashes: the conflict between health advantage and at-risk use

Increased risk of death or disability in unhelmeted Wisconsin motorcyclists.

Helmet use and bicycle-related trauma in patients presenting to an acute hospital in Singapore.

Association between weight fluctuation and fasting insulin concentration in Japanese men.