80 research outputs found
Increased Ischemic Cardiac Deaths in Central Indiana in Summer Months Compared to Winter Months
poster abstractCardiovascular diseases have been the leading cause of death in the United States for several decades. Despite sustained declines in the mortality rates from these diseases, the magnitude of the disease is still staggering. One large recent study, using data on hundreds of heart attacks documented in the National Registry of Myocardial Infarction, found that 53 percent more cases in winter than in summer. The primary culprit, many believe, is temperature. Cold weather narrows coronary arteries and raises blood pressure, stressing the heart. Physical strain and ruptured plaques caused by shoveling snow are also commonly cited.
But in a recent study, two researchers, found that the risk increases even in warm climates. Analyzing death certificates in seven regions with different climates, Los Angeles, Texas, Arizona, Pennsylvania, Massachusetts and others found that cardiovascular deaths rose up to 36 percent between summer and winter, regardless of climate and temperatures
In this study we evaluated the incidence of ischemic cardiomyopathy in the Central Indiana area in the winter months compared to the summer months for the years 1998 to 2002. Approximately 5325 deaths were seen in the Marion County Morgue in central Indiana in this time period. There were 609 ischemic cardiac deaths seen in the summer (March 15th through October 15th) compared to 434 ischemic cardiac deaths seen in the winter (October 15th through March 15th). The deaths by years in the summer were 129, 131, 92, 127, and 130 and in the winter were 95, 96, 90, 96, and 57 respectively. In conclusion, this study was consistent with the outcome as the previous study done in multiple northern and southern cities in the country
Natural Cardiac Deaths in Central Indiana
poster abstractCardiovascular disease is still the major cause of death in the USA for the past 50 to 60 years. Within cardiovascular disease there are many subtypes that cause death including hypertensive heart disease, atherosclerosis, coronary heart disease (CAD), myocardial infarction (MI), dilated cardiomyopathy, hypertrophic cardiomyopathy, cardiomegaly, and misc.). In this review study we examined the Marion County, Indianapolis, Indiana Morgue, Indiana database for the total of deaths that occurred between 2004 through 2012 and evaluated the number of cardiovascular deaths including the various CV subtypes mentioned above. There were approximately 13,000 deaths examined that were sent to the Marion County Morgue during that time frame in Central Indiana. Approximately 2950 deaths were due to CV disease (22.6%). Total ischemia (coronary artery disease) was 1939 made up the majority of the CV related deaths. This was followed by hypertensive heart disease (571) and congestive heart failure (189). Hypertrophic cardiomyopathy (89), cardiomegaly (16), and cardiac tamponade (11) made up the rest. Cardiac arrhythmias and myocarditis made up the remaining CV causes of death (131). In a previous study done at the Marion County Morgue from 1987 to 2003 focused on hypertensive CV disease and hypertrophic cardiomyopathy found 165 deaths and 134 deaths respectively.
Compared to the previous local study in the same population the incidence of hypertensive heart disease was moderately increased. There was not much difference between hypertrophic cardiomyopathy between the two studies. Both studies are fairly consistent when compared to national statistics on cardiovascular death in the country
Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation
Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas
Development of risk maps to minimize uranium exposures in the Navajo Churchrock mining district
© 2009 deLemos et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens
Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
Activation of Thiazide-Sensitive Co-Transport by Angiotensin II in the cyp1a1-Ren2 Hypertensive Rat
Transgenic rats with inducible expression of the mouse Ren2 gene were used to elucidate mechanisms leading to the development of hypertension and renal injury. Ren2 transgene activation was induced by administration of a naturally occurring aryl hydrocarbon, indole-3-carbinol (100 mg/kg/day by gastric gavage). Blood pressure and renal parameters were recorded in both conscious and anesthetized (butabarbital sodium; 120 mg/kg IP) rats at selected time-points during the development of hypertension. Hypertension was evident by the second day of treatment, being preceded by reduced renal sodium excretion due to activation of the thiazide-sensitive sodium-chloride co-transporter. Renal injury was evident after the first day of transgene induction, being initially limited to the pre-glomerular vasculature. Mircoalbuminuria and tubuloinsterstitial injury developed once hypertension was established. Chronic treatment with either hydrochlorothiazide or an AT1 receptor antagonist normalized sodium reabsorption, significantly blunted hypertension and prevented renal injury. Urinary aldosterone excretion was increased ∼20 fold, but chronic mineralocorticoid receptor antagonism with spironolactone neither restored natriuretic capacity nor prevented hypertension. Spironolactone nevertheless ameliorated vascular damage and prevented albuminuria. This study finds activation of sodium-chloride co-transport to be a key mechanism in angiotensin II-dependent hypertension. Furthermore, renal vascular injury in this setting reflects both barotrauma and pressure-independent pathways associated with direct detrimental effects of angiotensin II and aldosterone
Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019
Five insights from the Global Burden of Disease Study 2019
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe
Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens
The evolutionary psychology of leadership trait perception
Knowles, Kristen K. - ORCID 0000-0001-9664-9055
https://orcid.org/0000-0001-9664-9055Many researchers now approach the understanding of how facial characteristics shape the perception of leadership ability through the lens of human evolution. This approach considers what skills and characteristics would have been valuable for leaders to possess in our evolutionary history, including dominance, masculinity, and trustworthiness. Moreover, it gives an understanding about why rapid categorisation of these social cues from faces is adaptive. In this chapter, I present evolutionary arguments for social inferences based on faces, and discuss how our understanding of this categorisation has shifted away from purely associative phenomena towards evolved, innate processes. I explain how the perception of leadership ability in faces is linked to variance in facial morphology, and how these morphologies tell us something about the individuals who carry them. Specific facial cues relating to leadership-relevant traits are discussed, as well as the underlying biological systems that accompany these traits. I also explain the importance of context and individual differences on the prioritisation of seemingly disparate facial cues to leadership: dominance and trustworthiness. I also discuss recent findings in this area which further extend these concepts to examine cues to leadership in women’s faces, generally overlooked by evolutionary psychologists, and how political ideology can interact with these effects.https://doi.org/10.1007/978-3-319-94535-4_5pubpu
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