Trends and cardiovascular mortality effects of state-level blood pressure and uncontrolled hypertension in the United States.

BACKGROUND: Blood pressure is an important risk factor for cardiovascular disease and mortality and has lifestyle and healthcare determinants that vary across states. Only self-reported hypertension status is measured at the state level in the United States. Our aim was to estimate levels and trends in state-level mean systolic blood pressure (SBP), the prevalence of uncontrolled systolic hypertension, and cardiovascular mortality attributable to all levels of higher-than-optimal SBP. METHODS AND RESULTS: We estimated the relationship between actual SBP/uncontrolled hypertension and self-reported hypertension, use of blood pressure medication, and a set of health system and sociodemographic variables in the nationally representative National Health and Nutrition Examination Survey. We applied this relationship to identical variables from the Behavioral Risk Factor Surveillance System to estimate state-specific mean SBP and uncontrolled hypertension. We used the comparative risk assessment methods to estimate cardiovascular mortality attributable to higher-than-optimal SBP. In 2001-2003, age-standardized uncontrolled hypertension prevalence was highest in the District of Columbia, Mississippi, Louisiana, Alabama, Texas, Georgia, and South Carolina (18% to 21% for men and 24% to 26% for women) and lowest in Vermont, Minnesota, Connecticut, New Hampshire, Iowa, and Colorado (15% to 16% for men and approximately 21% for women). Women had a higher prevalence of uncontrolled hypertension than men in every state by 4 (Arizona) to 7 (Kansas) percentage points. In the 1990s, uncontrolled hypertension in women increased the most in Idaho and Oregon (by 6 percentage points) and the least in the District of Columbia and Mississippi (by 3 percentage points). For men, the worst-performing states were New Mexico and Louisiana (decrease of 0.6 and 1.3 percentage points), and the best-performing states were Vermont and Indiana (decrease of 4 and 3 percentage points). Age-standardized cardiovascular mortality attributable to higher-than-optimal SBP ranged from 200 to 220 per 100,000 (Minnesota and Massachusetts) to 360 to 370 per 100,000 (District of Columbia and Mississippi) for women and from 210 per 100,000 (Colorado and Utah) to 370 per 100,000 (Mississippi) and 410 per 100,000 (District of Columbia) for men. CONCLUSIONS: Lifestyle and pharmacological interventions for lowering blood pressure are particularly needed in the South and Appalachia, and with emphasis on control among women. Self-reported data on hypertension diagnosis from the Behavioral Risk Factor Surveillance System can be used to obtain unbiased state-level estimates of blood pressure and uncontrolled hypertension as benchmarks for priority setting and for designing and evaluating intervention programs

Robust metrics for assessing the performance of different verbal autopsy cause assignment methods in validation studies

Abstract Background Verbal autopsy (VA) is an important method for obtaining cause of death information in settings without vital registration and medical certification of causes of death. An array of methods, including physician review and computer-automated methods, have been proposed and used. Choosing the best method for VA requires the appropriate metrics for assessing performance. Currently used metrics such as sensitivity, specificity, and cause-specific mortality fraction (CSMF) errors do not provide a robust basis for comparison. Methods We use simple simulations of populations with three causes of death to demonstrate that most metrics used in VA validation studies are extremely sensitive to the CSMF composition of the test dataset. Simulations also demonstrate that an inferior method can appear to have better performance than an alternative due strictly to the CSMF composition of the test set. Results VA methods need to be evaluated across a set of test datasets with widely varying CSMF compositions. We propose two metrics for assessing the performance of a proposed VA method. For assessing how well a method does at individual cause of death assignment, we recommend the average chance-corrected concordance across causes. This metric is insensitive to the CSMF composition of the test sets and corrects for the degree to which a method will get the cause correct due strictly to chance. For the evaluation of CSMF estimation, we propose CSMF accuracy. CSMF accuracy is defined as one minus the sum of all absolute CSMF errors across causes divided by the maximum total error. It is scaled from zero to one and can generalize a method's CSMF estimation capability regardless of the number of causes. Performance of a VA method for CSMF estimation by cause can be assessed by examining the relationship across test datasets between the estimated CSMF and the true CSMF. Conclusions With an increasing range of VA methods available, it will be critical to objectively assess their performance in assigning cause of death. Chance-corrected concordance and CSMF accuracy assessed across a large number of test datasets with widely varying CSMF composition provide a robust strategy for this assessment.</p

Modeling causes of death: an integrated approach using CODEm

Abstract Background Data on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting. Methods We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance. Results Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers. Conclusions CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death. </jats:sec

Direct estimation of cause-specific mortality fractions from verbal autopsies: multisite validation study using clinical diagnostic gold standards

Abstract Background Verbal autopsy (VA) is used to estimate the causes of death in areas with incomplete vital registration systems. The King and Lu method (KL) for direct estimation of cause-specific mortality fractions (CSMFs) from VA studies is an analysis technique that estimates CSMFs in a population without predicting individual-level cause of death as an intermediate step. In previous studies, KL has shown promise as an alternative to physician-certified verbal autopsy (PCVA). However, it has previously been impossible to validate KL with a large dataset of VAs for which the underlying cause of death is known to meet rigorous clinical diagnostic criteria. Methods We applied the KL method to adult, child, and neonatal VA datasets from the Population Health Metrics Research Consortium gold standard verbal autopsy validation study, a multisite sample of 12,542 VAs where gold standard cause of death was established using strict clinical diagnostic criteria. To emulate real-world populations with varying CSMFs, we evaluated the KL estimations for 500 different test datasets of varying cause distribution. We assessed the quality of these estimates in terms of CSMF accuracy as well as linear regression and compared this with the results of PCVA. Results KL performance is similar to PCVA in terms of CSMF accuracy, attaining values of 0.669, 0.698, and 0.795 for adult, child, and neonatal age groups, respectively, when health care experience (HCE) items were included. We found that the length of the cause list has a dramatic effect on KL estimation quality, with CSMF accuracy decreasing substantially as the length of the cause list increases. We found that KL is not reliant on HCE the way PCVA is, and without HCE, KL outperforms PCVA for all age groups. Conclusions Like all computer methods for VA analysis, KL is faster and cheaper than PCVA. Since it is a direct estimation technique, though, it does not produce individual-level predictions. KL estimates are of similar quality to PCVA and slightly better in most cases. Compared to other recently developed methods, however, KL would only be the preferred technique when the cause list is short and individual-level predictions are not needed.</p

National and subnational mortality effects of metabolic risk factors and smoking in Iran: a comparative risk assessment

Abstract Background Mortality from cardiovascular and other chronic diseases has increased in Iran. Our aim was to estimate the effects of smoking and high systolic blood pressure (SBP), fasting plasma glucose (FPG), total cholesterol (TC), and high body mass index (BMI) on mortality and life expectancy, nationally and subnationally, using representative data and comparable methods. Methods We used data from the Non-Communicable Disease Surveillance Survey to estimate means and standard deviations for the metabolic risk factors, nationally and by region. Lung cancer mortality was used to measure cumulative exposure to smoking. We used data from the death registration system to estimate age-, sex-, and disease-specific numbers of deaths in 2005, adjusted for incompleteness using demographic methods. We used systematic reviews and meta-analyses of epidemiologic studies to obtain the effect of risk factors on disease-specific mortality. We estimated deaths and life expectancy loss attributable to risk factors using the comparative risk assessment framework. Results In 2005, high SBP was responsible for 41,000 (95% uncertainty interval: 38,000, 44,000) deaths in men and 39,000 (36,000, 42,000) deaths in women in Iran. High FPG, BMI, and TC were responsible for about one-third to one-half of deaths attributable to SBP in men and/or women. Smoking was responsible for 9,000 deaths among men and 2,000 among women. If SBP were reduced to optimal levels, life expectancy at birth would increase by 3.2 years (2.6, 3.9) and 4.1 years (3.2, 4.9) in men and women, respectively; the life expectancy gains ranged from 1.1 to 1.8 years for TC, BMI, and FPG. SBP was also responsible for the largest number of deaths in every region, with age-standardized attributable mortality ranging from 257 to 333 deaths per 100,000 adults in different regions. Discussion Management of blood pressure through diet, lifestyle, and pharmacological interventions should be a priority in Iran. Interventions for other metabolic risk factors and smoking can also improve population health. </jats:sec

Ischaemic heart disease in the former Soviet Union 1990-2015 according to the Global Burden of Disease 2015 Study.

OBJECTIVE: The objective of this study was to compare ischaemic heart disease (IHD) mortality and risk factor burden across former Soviet Union (fSU) and satellite countries and regions in 1990 and 2015. METHODS: The fSU and satellite countries were grouped into Central Asian, Central European and Eastern European regions. IHD mortality data for men and women of any age were gathered from national vital registration, and age, sex, country, year-specific IHD mortality rates were estimated in an ensemble model. IHD morbidity and mortality burden attributable to risk factors was estimated by comparative risk assessment using population attributable fractions. RESULTS: In 2015, age-standardised IHD death rates in Eastern European and Central Asian fSU countries were almost two times that of satellite states of Central Europe. Between 1990 and 2015, rates decreased substantially in Central Europe (men -43.5% (95% uncertainty interval -45.0%, -42.0%); women -42.9% (-44.0%, -41.0%)) but less in Eastern Europe (men -5.6% (-9.0, -3.0); women -12.2% (-15.5%, -9.0%)). Age-standardised IHD death rates also varied within regions: within Eastern Europe, rates decreased -51.7% in Estonian men (-54.0, -47.0) but increased +19.4% in Belarusian men (+12.0, +27.0). High blood pressure and cholesterol were leading risk factors for IHD burden, with smoking, body mass index, dietary factors and ambient air pollution also ranking high. CONCLUSIONS: Some fSU countries continue to experience a high IHD burden, while others have achieved remarkable reductions in IHD mortality. Control of blood pressure, cholesterol and smoking are IHD prevention priorities

Aspirin use and knowledge in the community: a population- and health facility based survey for measuring local health system performance

BACKGROUND: Little is known about the relationship between cardiovascular risk, disease and actual use of aspirin in the community. METHODS: The Measuring Disparities in Chronic Conditions (MDCC) study is a community and health facility-based survey designed to track disparities in the delivery of health interventions for common chronic diseases. MDCC includes a survey instrument designed to collect detailed information about aspirin use. In King County, WA between 2011 and 2012, we surveyed 4633 white, African American, or Hispanic adults (45% home address-based sample, 55% health facility sample). We examined self-reported counseling on, frequency of use and risks of aspirin for all respondents. For a subgroup free of CAD or cerebral infarction that underwent physical examination, we measured 10-year coronary heart disease risk and blood salicylate concentration. RESULTS: Two in five respondents reported using aspirin routinely while one in five with a history of CAD or cerebral infarction and without contraindication did not report routine use of aspirin. Women with these conditions used less aspirin than men (65.0% vs. 76.5%) and reported more health problems that would make aspirin unsafe (29.4% vs. 21.2%). In a subgroup undergoing phlebotomy a third of respondents with low cardiovascular risk used aspirin routinely and only 4.6% of all aspirin users had no detectable salicylate in their blood. CONCLUSIONS: In this large urban county where health care delivery should be of high quality, there is insufficient aspirin use among those with high cardiovascular risk or disease and routine aspirin use by many at low risk. Further efforts are needed to promote shared-decision making between patients and clinicians as well as inform the public about appropriate use of routine aspirin to reduce the burden of atherosclerotic vascular disease

Prioritising Infectious Disease Mapping.

BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited

La política antidrogas: nuevos horizontes de cambio en el control de la oferta y la demanda

96 p.De acuerdo con la Organización Mundial de la Salud (OMS, 1994) una sustancia o droga psicoactiva es aquella que, al ingerirse, afecta procesos mentales, como la cognición o la memoria. El término es asemejado generalmente con el de psicotrópico y ambas expresiones refieren al grupo de sustancias, legales e ilegales, de interés para la política en materia de drogas. En general, la literatura refiere con el término psicotrópico, a medicamentos utilizados principalmente en el tratamiento de los trastornos mentales, como los ansiolíticos, sedantes, antidepresivos, anti maníacos y neurolépticos. Bajo la categoría de sustancias psicotrópicas se encuentran los estupefacientes, acepción utilizada para referirse a sustancias cuya acción sedante, analgésica, narcótica y euforizante puede conducir al acostumbramiento y a la toxicomanía, por lo cual tienen un elevado potencial de abuso y / o dependencia psíquica/física. Entre ellos, se cuentan los estimulantes -cocaína, cafeína, nicotina-, los alucinógenos -Peyote y Psilocybes, los opiáceos -morfina, heroína-, y los sedantes/hipnóticos -alcohol- (OMS, 1994).Prólogo Introducción Capítulo 1. El panorama global: evolución reciente del fenómeno del consumo de sustancias psicoactivas Capítulo 2. La junta internacional de fiscalización de estupefacientes y la eficacia de la política antidrogas: el caso colombiano Capítulo 3. Hacia nuevos horizontes del análisis de política antidrogas Conclusiones Bibliografí