4,053 research outputs found
AN INVESTIGATION OF CHANGES IN DIABETES TRENDS AFTER THE AFFORDABLE CARE ACT
INTRODUCTION: Diabetes Mellitus (DM) is one of the fastest growing and most costly chronic diseases in the United States. DM is severely underdiagnosed, resulting in increased complications, costs, and mortality. Primary goals of the Affordable Care Act (ACA) were to increase health insurance coverage and access to care, and to improve chronic disease outcomes. However, the effects of the legislation have not been widely studied, particularly the relationship between proper diabetes diagnosis and a variety of health related factors.
AIM: Determine the relationship between DM prevalence and under-diagnosis, to healthcare utilization, usual source of care, insurance, type of insurance, and population characteristics have changed since the implementation of the ACA.
METHODS: Data collected between 2005 and 2016 in the National Health and Nutrition Examination Survey were used for this work. The Andersen behavioral health model was used as a theoretical framework and selection of study variables. Descriptive statistics and advanced statistical modeling techniques were applied. Distinct multilevel models were used to model the logit of the probability of DM and the logit of the probability of a proper DM diagnosis each as a function of study variables with an indicator of pre- or post-ACA included as a fixed effect. Marginal models are multilevel models that apply population averaged estimates for parameters. Marginal models were specified to account for clustering by time, and generalized estimating equations used to estimate model parameters. The quasi-likelihood under the null (QIC) statistic was estimated for model comparisons. The SAS Software System was used for data analysis and the level of significance set at .05.
RESULTS: The sample consisted of 31,225 participants, with half pre-ACA (n=15,612) and half post-ACA. Females comprised 51.64% of the study sample with 43.50% White, 25.82% Hispanic, and 20.65% Black and a mean (standard deviation) age of 49.3 (17.9) years. About 11.45% of those in the Pre ACA period had a diagnosis of DM, while 13.5% of those in the Post ACA period had a diagnosis of DM. The percentage of uninsured was 23.95% in the Pre ACA period and 20.69% in the Post ACA time period. The prevalence of undiagnosed DM patients was 26.7% before the ACA, and 21.3% after. A multilevel model with DM status as the dependent outcome showed that sex (females vs males: OR=0.83, 95%CI=0.78,0.89,p =.02), USC (yes vs no: OR=1.28, 95%CI=1.03,1.59, p=.03), health insurance (yes vs no: OR=1.21, 95%CI=1.17,1.26, p =.02), and education level(college graduate vs less than high school: OR=0.79, 95%CI=0.64,0.97, p=.05, high school graduate vs less than high school: OR=0.97, 95%CI=0.93,1.03, p=.05) were significantly associated with presence of DM. Participants were more likely to have their DM properly diagnosed after the ACA: in the final multivariable multilevel model, only ACA time period had a significant effect on correct DM diagnosis (OR=1.51, 95%CI=1.24,1.85, p=.04).
CONCLUSIONS: Although prevalence of DM has increased in recent years, under-diagnosis is less of an issue after the ACA. In the multivariable model comparing DM status (having the disease) to selected covariates, sex, health insurance, education, and USC were related to DM status. The ACA time period had no significant relationship with DM status in the multivariable model. However, in the multivariable model for correctly diagnosed DM, ACA time period was the only independent variable that had a significant association with correct DM diagnosis
The Domestic Sublime
An investigation of the art of Tara Donovan, Liza Lou, Dave Cole, and Wolfgang Laib precipitated an articulation of a unique concept, the domestic sublime. The use of non-traditional art materials employed by each artist is one of the unifying characteristics that makes their work illustrations of the domestic sublime. Each artist presents work that is familiar yet uncomfortable, comforting yet disturbing, and lastly, finite yet immeasurable. The combination of repetitive labor, vast quantities of physical materials, and forms that present the unknown reveal characteristics of the domestic sublime.
Tracing the concept of the sublime from its origins to today allows for its evolution from a transcendental experience to a tangible, material manifestation in contemporary discourse. Key figures in this argument include Immanuel Kant, Jean-François Lyotard, and Jacques Derrida. Domesticity commonly refers to any labor, activity or material related to, in or around the home and has numerous social, historical, and philosophical contexts. Situated in notion of modernity, the domestic’s foundation is comprised of layers of discourse that include the politics of labor, economic implications, boundaries, technology, and identity. Contributing philosophers to the domestic include Gaston Bachelard, Witold Rybczynski, Simone de Beauvoir, Kathleen M. Kirby, Henri Lefebvre, and Martin Heidegger.
Characteristics from both the domestic and the sublime meld to a framework that supports the paradoxes and complexities inherent in both notions, while simultaneously revealing the overlapping notions that inextricably create the domestic sublime. The artwork that illustrates the notion of the domestic sublime combines domestic materials, labor, and space with the uncanny relationships inherent in the sublime such attraction and repulsion, interior and exterior, and comfort and terror.https://digitalmaine.com/academic/1050/thumbnail.jp
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Sensitivity of Concentrating Solar Power Trough Performance, Cost and Financing with Solar Advisor Model
A comprehensive solar technology systems analysis model, the Solar Advisor Model (SAM) was developed to support the federal R&D community and the solar industry. This model, developed by staff at NREL and Sandia National Laboratory, is able to model the costs, finances, and performance of concentrating solar power and photovoltaics (PV). Currently, parabolic troughs and concentrating PV are the two concentrating technologies modeled within the SAM environment
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Modeling Photovoltaic and Concentrating Solar Power Trough Performance, Cost, and Financing with the Solar Advisor Model: Preprint
A comprehensive solar technology systems analysis model, the Solar Advisor Model (SAM), has been developed to support the federal R&D community and the solar industry by staff at the National Renewable Energy Laboratory (NREL) and Sandia National Laboratory. This model is able to model the finances, incentives, and performance of flat-plate photovoltaic (PV), concentrating PV, and concentrating solar power (specifically, parabolic troughs). The primary function of the model is to allow users to investigate the impact of variations in performance, cost, and financial parameters to better understand their impact on key figures of merit. Figures of merit related to the cost and performance of these systems include, but aren't limited to, system output, system efficiencies, levelized cost of energy, return on investment, and system capital and O&M costs. There are several models within SAM to model the performance of photovoltaic modules and inverters. This paper presents an overview of each PV and inverter model, introduces a new generic model, and briefly discusses the concentrating solar power (CSP) parabolic trough model. A comparison of results using the different PV and inverter models is also presented
Cancer risk in relation to body fat distribution, evaluated by DXA-scans, in postmenopausal women – the Prospective Epidemiological Risk Factor (PERF) study
Abstract Studies with direct measures of body fat distribution are required to explore the association between central and general obesity to cancer risk in postmenopausal women. This study investigates the association between central obesity and general obesity to overall/site-specific cancer risk in postmenopausal women. The analysis included 4,679 Danish postmenopausal women. Body fat distribution was evaluated by whole-body dual-energy X-ray absorptiometry scanners. Cancer diagnoses were extracted from the Danish Cancer Registry and multivariable Cox regression models explored the association between cancer risk and central obesity after adjusting for BMI. Our results showed that high central obese women had a 50% increased risk of overall cancer relative to low central obese women (Q1vs.Q4: [HR:1.50, CI:1.20–1.88]). For site-specific cancers, central obesity was significantly associated with Respiratory (Q1vs.Q4: [HR:2.01, CI:1.17–3.47]), Gastrointestinal (Q1vs.Q4: [HR:1.55, CI:0.99–2.41]) and Female genital organs (Q1vs.Q4: [HR:1.95, CI:1.00–3.78]) cancer diagnoses. Sub-analyses stratified by smoking-habits found a significant association between central obesity and a cancer diagnosis for current (Q1vs.Q4: [HR:1.93, CI:1.25–2.99]) and former smokers (Q1vs.Q4: [HR:1.90, CI:1.23–2.94]). These analyses suggest that central obesity is associated with some cancers in postmenopausal women independent of BMI
Throat swabs in children with respiratory tract infection:associations with clinical presentation, and potential targets for point-of-care testing
Impact of antibiotics for children presenting to general practice with cough on adverse outcomes: secondary analysis from a multicentre prospective cohort study
BACKGROUND: Clinicians commonly prescribe antibiotics to prevent major adverse outcomes in children presenting in primary care with cough and respiratory symptoms, despite limited meaningful evidence of impact on these outcomes. AIM: To estimate the effect of children's antibiotic prescribing on adverse outcomes within 30 days of initial consultation. DESIGN AND SETTING: Secondary analysis of 8320 children in a multicentre prospective cohort study, aged 3 months to <16 years, presenting in primary care across England with acute cough and other respiratory symptoms. METHOD: Baseline clinical characteristics and antibiotic prescribing data were collected, and generalised linear models were used to estimate the effect of antibiotic prescribing on adverse outcomes within 30 days (subsequent hospitalisations and reconsultation for deterioration), controlling for clustering and clinicians' propensity to prescribe antibiotics. RESULTS: Sixty-five (0.8%) children were hospitalised and 350 (4%) reconsulted for deterioration. Clinicians prescribed immediate and delayed antibiotics to 2313 (28%) and 771 (9%), respectively. Compared with no antibiotics, there was no clear evidence that antibiotics reduced hospitalisations (immediate antibiotic risk ratio [RR] 0.83, 95% confidence interval [CI] = 0.47 to 1.45; delayed RR 0.70, 95% CI = 0.26 to 1.90, overall P = 0.44). There was evidence that delayed (rather than immediate) antibiotics reduced reconsultations for deterioration (immediate RR 0.82, 95% CI = 0.65 to 1.07; delayed RR 0.55, 95% CI = 0.34 to 0.88, overall P = 0.024). CONCLUSION: Most children presenting with acute cough and respiratory symptoms in primary care are not at risk of hospitalisation, and antibiotics may not reduce the risk. If an antibiotic is considered, a delayed antibiotic prescription may be preferable as it is likely to reduce reconsultation for deterioration
Detecting a stochastic background of gravitational radiation: Signal processing strategies and sensitivities
We analyze the signal processing required for the optimal detection of a
stochastic background of gravitational radiation using laser interferometric
detectors. Starting with basic assumptions about the statistical properties of
a stochastic gravity-wave background, we derive expressions for the optimal
filter function and signal-to-noise ratio for the cross-correlation of the
outputs of two gravity-wave detectors. Sensitivity levels required for
detection are then calculated. Issues related to: (i) calculating the
signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii)
performing the data analysis in the presence of nonstationary detector noise,
(iii) combining data from multiple detector pairs to increase the sensitivity
of a stochastic background search, (iv) correlating the outputs of 4 or more
detectors, and (v) allowing for the possibility of correlated noise in the
outputs of two detectors are discussed. We briefly describe a computer
simulation which mimics the generation and detection of a simulated stochastic
gravity-wave signal in the presence of simulated detector noise. Numerous
graphs and tables of numerical data for the five major interferometers
(LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. The treatment
given in this paper should be accessible to both theorists involved in data
analysis and experimentalists involved in detector design and data acquisition.Comment: 81 pages, 30 postscript figures, REVTE
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Solar Advisor Model User Guide for Version 2.0
The Solar Advisor Model (SAM) provides a consistent framework for analyzing and comparing power system costs and performance across the range of solar technologies and markets, from photovoltaic systems for residential and commercial markets to concentrating solar power and large photovoltaic systems for utility markets. This manual describes Version 2.0 of the software, which can model photovoltaic and concentrating solar power technologies for electric applications for several markets. The current version of the Solar Advisor Model does not model solar heating and lighting technologies
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