21 research outputs found
Health insurance is associated with decreased odds for undiagnosed prediabetes and type 2 diabetes in American adults
Over a third of adults in the United States have prediabetes, and many of those with prediabetes will progress to type 2 diabetes within 3–5 years. Health insurance status may factor into a proper diagnosis of prediabetes and diabetes. This study sought to determine the associations between health insurance and undiagnosed prediabetes and diabetes in a national sample of American adults. Publicly available data from 13,029 adults aged 18–64 years from the 2005–2016 waves of the National Health and Nutrition Examination Survey were analyzed. Health insurance type (Medicaid, Private, Other, None) was self-reported. Prediabetes and diabetes status were assessed with measures of self-report, glycohemoglobin, fasting plasma glucose, and two-hour glucose. Covariate-adjusted logistic models were used for the analyses. Overall, 5976 (45.8%) participants had undiagnosed prediabetes, while 897 (6.8%) had undiagnosed diabetes. Having health insurance was associated with decreased odds ratios for undiagnosed prediabetes: 0.87 (95% confidence interval (CI: 0.79, 0.95)) for private insurance, 0.84 (CI: 0.73, 0.95) for other insurance, and 0.78 (CI: 0.67, 0.90) for Medicaid. Moreover, having private health insurance was associated with 0.82 (CI: 0.67, 0.99) decreased odds for undiagnosed diabetes. Health insurance coverage and screening opportunities for uninsured individuals may reduce prediabetes and diabetes misclassifications
Computational shelf-life dating : complex systems approaches to food quality and safety
Shelf-life is defined as the time that a product is acceptable and meets the consumers expectations regarding food quality. It is the result of the conjunction of all services in production, distribution, and consumption. Shelf-life dating is one of the most difficult tasks in food engineering. Market pressure has lead to the implementation of shelf-life by sensory analyses, which may not reflect the full quality spectra. Moreover, traditional methods for shelf-life dating and small-scale distribution chain tests cannot reproduce in a laboratory the real conditions of storage, distribution, and consumption on food quality. Today, food engineers are facing the challenges to monitor, diagnose, and control the quality and safety of food products. The advent of nanotechnology, multivariate sensors, information systems, and complex systems will revolutionize the way we manage, distribute, and consume foods. The informed consumer demands foods, under the legal standards, at low cost, high standards of nutritional, sensory, and health benefits. To accommodate the new paradigms, we herein present a critical review of shelf-life dating approaches with special emphasis in computational systems and future trends on complex systems methodologies applied to the prediction of food quality and safety.Fundo Europeu de Desenvolvimento Regional (FEDER) - Programa POS-ConhecimentoFundação para a Ciência e a Tecnologia (FCT) - SFRH/BPD/26133/2005, SFRH/ BPD/20735/200
Hydrostatischer Hochdruck als alternative Prozessierungsmethode für knöcherne Allografts - tierexperimentelle Charakterisierung
VARIATION OF SUGARS AND ACIDS DURING RIPENING OF PEARS AND IN THE PRODUCTION AND STORAGE OF PEAR CONCENTRATE
In Vivo Phycocyanin Flourometry as a Potential Rapid Screening Tool for Predicting Elevated Microcystin Concentrations at Eutrophic Lakes
Current approaches for assessing human health risks associated with cyanotoxins often rely on the quantification of microcystin. Significant limitations of current approaches are cost and time to obtain a result. To address these challenges, a numerical index for screening microcystin risks above the World Health Organization’s (WHO) low-risk threshold for microcystin was developed for eutrophic Midwestern U.S. lakes based on water quality results from 182 beach water samples collected from seven Ohio lakes. In 48 (26.4%) samples we observed microcystin concentrations as measured by ELISA that exceeded the 4 μg/L microcystin threshold. A multivariable logistic regression model using practical real-time measures of in vivo phycocyanin (by fluorometry) and secchi depth was constructed to estimate the probability of a beach sample exceeding 4 μg/L microcystin. The final model achieved statistical significance (p = 0.030) as well as good calibration (as measured by the goodness-of-fit test comparing observed to expected counts within deciles of risk based on the model, p = 0.329) and discrimination (as indicated by the area under the receiver-operator-curve (0.795)). These results demonstrate two rapid and practical measures of recreational water quality are effective in identifying “at risk” lake conditions warranting additional management (e.g., advisory and/or advanced testing)
In Vivo Phycocyanin Flourometry as a Potential Rapid Screening Tool for Predicting Elevated Microcystin Concentrations at Eutrophic Lakes
Current approaches for assessing human health risks associated
with cyanotoxins often rely on the quantification of microcystin.
Significant limitations of current approaches are cost and time to
obtain a result. To address these challenges, a numerical index for
screening microcystin risks above the World Health Organization’s
(WHO) low-risk threshold for microcystin was developed for eutrophic
Midwestern U.S. lakes based on water quality results from 182 beach
water samples collected from seven Ohio lakes. In 48 (26.4%) samples
we observed microcystin concentrations as measured by ELISA that exceeded
the 4 ÎĽg/L microcystin threshold. A multivariable logistic regression
model using practical real-time measures of in vivo phycocyanin (by
fluorometry) and secchi depth was constructed to estimate the probability
of a beach sample exceeding 4 ÎĽg/L microcystin. The final model
achieved statistical significance (<i>p</i> = 0.030) as
well as good calibration (as measured by the goodness-of-fit test
comparing observed to expected counts within deciles of risk based
on the model, <i>p</i> = 0.329) and discrimination (as indicated
by the area under the receiver-operator-curve (0.795)). These results
demonstrate two rapid and practical measures of recreational water
quality are effective in identifying “at risk” lake
conditions warranting additional management (e.g., advisory and/or
advanced testing)