Estimating a preference-based index from the Japanese SF-36

Objective: The main objective of the study was to estimate a preference-bascd Short Form (SF)-6D index from the SF-36 for Japan and compare it with the UK results. Study Design and Setting: The SF-6D was translated into Japanese. Two hundred and forty-nine health states defined by this version of the SF-6D were then valued by a representative sample of 600 members of the Japanese general population using standard gamble (SG). These health-state values were modeled using classical parametric random-effect methods with individual-level data and ordinary least squares (OLS) on mean health-state values, together with a new nonparametric approach using Bayesian methods of estimation. Results: All parametric models estimated on Japanese data were found to perform less well than their UK counterparts in terms of poorer goodness of fit, more inconsistencies, larger prediction errors and bias, and evidence of systematic bias in the predictions. Nonparametric models produce a substantial improvement in out-of-sample predictions. The physical, role, and social dimensions have relatively larger decrements than pain and mental health compared with those in the United Kingdom. Conclusion: The differences between Japanese and UK valuations of the SF-6D make it important to use the Japanese valuation data set estimated using the nonparametric Bayesian technique presented in this article. (C) 2009 Elsevier Inc. All rights reserved

Usporedba hranidbenog i funkcionalnog potencijala sirupa od rogača sa sirupima od datulja i javora

Research background. The carob tree (Ceratonia siliqua L.) is grown primarily for its seeds that are utilized in the production of the highly prized locust bean gum. The material left after the separation of seeds from the pods is utilized in the production of a range of traditional products including carob syrup, usually in cottage-type industries. The international market penetration of carob syrups is rather limited and, accordingly, scant information exists on their composition and phytochemical properties compared to mainstream syrups. The present study aims to determine key chemical parameters, phenolic profiles and antioxidant properties of carob syrups and benchmark these against those of date and maple syrups. Experimental approach. Carob syrups were prepared from 19 accessions of the carob, under laboratory conditions, by a similar procedure to those practiced by small-scale producers. The pH, browning index, the content of proteins, minerals, hydroxymethylfurfural, sugar composition, total phenols, antioxidant capacity and phenolic profiles of the produced syrups along with branded samples of date and maple syrups were analyzed. Results and conclusions. The pH and sugar composition of the carob syrups were comparable to those of date and maple syrups. In general, the carob syrups contained more proteins, minerals, phenolic acids, flavonoids and total phenols, and exhibited higher antioxidant capacity than the date and maple syrups. The carob syrups exhibited excessive browning and contained more, or comparable content of hydroxymethylfurfural, than the date and maple syrups. The data indicate that carob syrups provide more nutrients and possess superior antioxidant potential to date and maple syrups. The high contents of the carcinogenic hydroxymethylfurfural of the carob syrups warrant milder heating regimens in the concentration step during production. Novelty and scientific contribution. In contrast to studies based on commercial and/or homemade syrups, this work utilized a relatively large number of laboratory-prepared samples for creating a robust database for carob syrup. The results indicated that carob syrups possess superior health promotion and disease prevention effects than the widely traded date and maple syrups. In addition to their potential positive contribution to public health, carob syrups have been shown to be promising candidates for bolstering the economic returns of farmers in carob-producing countries.Pozadina istraživanja. Stablo rogača (Ceratonia siliqua L.) se uzgaja primarno zbog sjemenki koje se koriste u proizvodnji visoko cijenjene karuba gume. Materijal koji zaostaje nakon izdvajanja sjemenki iz mahuna koristi se za proizvodnju različitih tradicijskih proizvoda poput sirupa od rogača, najčešće u kućnoj proizvodnji. Probitak na međunarodno tržište je ograničen, pa su i informacije o sastavu i fitokemijskim svojstvima ovog proizvoda nedostatne u usporedbi s komercijalnim sirupima. Svrha je ovoga rada bila odrediti glavne kemijske parametre, fenolni profil i antioksidacijska svojstva sirupa od rogača, te ih usporediti s onima sirupa od datulja i javora. Eksperimentalni pristup. Sirupi od rogača su pripremljeni u laboratorijskim uvjetima od 19 uzoraka rogača, i to postupkom sličnim onima koje koriste mali proizvođači. U dobivenim sirupima te u komercijalnim sirupima od javora i datulje ispitani su: pH-vrijednost, indeks posmeđivanja, udjeli proteina, mineralnih tvari i hidroksimetilfurfurala, sastavi šećera i ukupnih fenola, antioksidacijska sposobnost i fenolni profil. Rezultati i zakjučci. Vrijednosti pH i sastav šećera dobivenih sirupa od rogača bili su slični onima sirupa od datulja i javora. Sirupi rogača su općenito imali veće udjele proteina, mineralnih tvari, fenolnih kiselina, flavonoida i ukupnih fenola, te izraženiju antioksidacijsku aktivnost od sirupa od javora i datulja. Vrijednosti indeksa posmeđivanja sirupa od rogača su bile visoke, a u usporedbi sa sirupima od datulja i javora sadržavali su više ili otprilike jednako hidroksimetilfurfurala. Dobivene vrijednosti pokazuju da sirupi od rogača imaju veći udjel hranjivih tvari i bolji antioksidacijski potencijal od sirupa od datulja i javora. Zaključeno je da bi zbog velikog udjela kancerogenog hidroksimetilfurfurala u sirupu od rogača temperatura zagrijavanja tijekom zgušnjavanja trebala biti niža. Novina i znanstveni doprinos. Za razliku od istraživanja koja koriste komercijalne uzorke i/ili one domaće proizvodnje, u ovom je radu korišten relativno velik broj uzoraka pripremljenih u laboratoriju radi izrade sveobuhvatne baze podataka o sirupu od rogača. Rezultati pokazuju da sirupi od rogača imaju pozitivniji učinak na zdravlje od na tržištu znatno više zastupljenih sirupa od datulja i javora. Osim njihovog potencijalnog pozitivnog učinka na zdravlje ljudi, sirupi od rogača mogu povećati prihod uzgajivača rogača

Biological Control of Three Major Cucumber and Pepper Pests: Whiteflies, Thrips, and Spider Mites, in High Plastic Tunnels Using Two Local Phytoseiid Mites

To enhance food security, food safety, and environmental health, a bio-based integrated pest management (BIPM) strategy was evaluated at two coastal locations in Lebanon as an alternative to toxic pesticide sprays in commercial high-arched plastic tunnels common in many countries. The evaluation occurred during two cucumber and pepper cropping seasons: spring and fall. At each site, two commercial tunnels were used; farmers’ conventional practices were applied in one tunnel, while the BIPM approach was followed in the second tunnel. In the farmers’ practices, a total of 14 sprays of insecticide/acaricide mixtures were applied during the spring growing season, and 6 sprays were applied during the fall. In the BIPM tunnels, hotspot releases of local strains of Amblyseius swirskii and Phytoseiulus persimilis were applied. By the end of the spring season, the number of whitefly nymphs (WFNs)/leaf and thrips/leaf in the pesticide treatment were 4.8 and 0.06, respectively, compared to 0.1 and 0.33, respectively, in the BIPM treatment. Similarly, at the end of the fall season, the WFNs reached 19.7/leaf in the pesticide control as compared to 1.2/leaf in the BIPM treatment, proving the efficacy of A. swirskii. Farmers using conventional acaricides during both cropping seasons failed to control Tetranychus urticae, the two-spotted spider mite (TSSM). However, hotspot releases of P. persimilis were successful in controlling TSSM. By the end of June, the number of TSSMs reached 7.8/leaf in the BIPM treatment compared to 53/leaf in the pesticide treatment. Likewise, in December, TSSM numbers reached 9/leaf in the BIPM treatment compared to 40/leaf in the pesticide treatment. Preliminary observations of pepper showed that both predatory mites (A. swirskii and P. persimilis) gave similar or better efficacy against the three pests. The two local predatory phytoseiid mites seem to be effective in controlling these three major pests and to be adapted to local environmental conditions. A rate of increase of 0.86 was observed for P. persimilis and 0.22 for A. swirskii, in June, when maximum temperatures were close to 40 °C. This also shows a compatibility between the two predators. In conclusion, our BIPM approach was efficient under a Mediterranean climate in arched plastic tunnels with relatively poor aeration

Valuation of preference-based measures: Can existing preference data be used to select a smaller sample of health states?

Background Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates. Methods We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error. Results The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features. Conclusions The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged

Calculating partial expected value of perfect information via Monte Carlo sampling algorithms

Partial expected value of perfect information (EVPI) calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. Published case studies have used different computational approaches. This article examines the computation of partial EVPI estimates via Monte Carlo sampling algorithms. The mathematical definition shows 2 nested expectations, which must be evaluated separately because of the need to compute a maximum between them. A generalized Monte Carlo sampling algorithm uses nested simulation with an outer loop to sample parameters of interest and, conditional upon these, an inner loop to sample remaining uncertain parameters. Alternative computation methods and shortcut algorithms are discussed and mathematical conditions for their use considered. Maxima of Monte Carlo estimates of expectations are biased upward, and the authors show that the use of small samples results in biased EVPI estimates. Three case studies illustrate 1) the bias due to maximization and also the inaccuracy of shortcut algorithms 2) when correlated variables are present and 3) when there is nonlinearity in net benefit functions. If relatively small correlation or nonlinearity is present, then the shortcut algorithm can be substantially inaccurate. Empirical investigation of the numbers of Monte Carlo samples suggests that fewer samples on the outer level and more on the inner level could be efficient and that relatively small numbers of samples can sometimes be used. Several remaining areas for methodological development are set out. A wider application of partial EVPI is recommended both for greater understanding of decision uncertainty and for analyzing research priorities

From representing views to representativeness of views: illustrating a new (Q2S) approach in the context of health care priority setting in nine European countries

Governments across Europe are required to make decisions about how best to allocate scarce health care resources. There are legitimate arguments for eliciting societal vales in relation to health care resource allocation given the roles of the general public as payers and potential patients. However, relatively little is known about the views of the general public on general principles which could guide these decisions. In this paper we present five societal viewpoints on principles for health care resources allocation and develop a new approach, Q2S, designed to investigate the extent to which these views are held across a range of European countries. An online survey was developed, based on a previously completed study Q methodology, and delivered between November 2009 and February 2010 across nine countries to 33,515 respondents. The largest proportion of our respondents (44%), were found to most associate themselves with an egalitarian perspective. Differences in views were more strongly associated with countries than with socio-demographic characteristics. These results provide information which could be useful for decision makers in understanding the pluralistic context in which they are making health care resource allocation decisions and how different groups in society may respond to such decisions

First Nation-Wide Analysis of Food Safety and Acceptability Data in Lebanon

The challenges to food safety in Lebanon are numerous and have coalesced to pose a serious public health concern. This is evident in well-documented food poisoning outbreaks and adulteration cases. In response, the Lebanese government initiated an unprecedented food safety campaign (2015–2017) that aimed to test food samples that were randomly collected from foodservices and industries across the country. The data were made available publicly, but they were never analyzed to prioritize and determine high risk foods and most prevalent contaminants nationally or across governorates. To answer these questions, we performed an in-depth statistical analysis of the data, which included 11,625 individual food samples. Our analysis showed that water (55% of tested water samples), spices (49.3%), red meat (34.4%), poultry (30.9%) and dairy (28.3%) were the main foods associated with the highest rejection rates. The most common biological contaminants detected in rejected foods were sulfate-reducing bacteria (34.7%), Escherichia coli (32.1%), coliforms (19.6%), Staphylococcus aureus (12.8%), and Salmonella (11.6%). We conclude that Lebanon needs rigorous and sustainable programs to monitor the quality and safety of foods. Given the lack of resources, we recommend putting emphasis on extensive outreach programs that aim at enhancing food safety knowledge from farm to fork

Use of Bayesian methods to model the SF-6D health state preference based data

Abstract Background Conventionally, models used for health state valuation data have been frequentists. Recently a number of researchers have investigated the use of Bayesian methods in this area. The aim of this paper is to put on the map of modelling a new approach to estimating SF-6D health state utility values using Bayesian methods. This will help health care professionals in deriving better health state utilities of the original UK SF-6D for their specialized applications. Methods The valuation study is composed of 249 SF-6D health states valued by a representative sample of the UK population using the standard gamble technique. Throughout this paper, we present four different models, including one simple linear regression model and three random effect models. The predictive ability of these models is assessed by comparing predicted and observed mean SF-6D scores, R2/adjusted R2 and RMSE. All analyses were carried out using Bayesian Markov chain Monte Carlo (MCMC) simulation methods freely available in the specialist software WinBUGS. Results The random effects model with interaction model performs best under all criterions, with mean predicted error of 0.166, R2/adjusted R2 of 0.683 and RMSE of 0.218. Conclusions The Bayesian models provide flexible approaches to estimate mean SF-6D utility estimates, including characterizing the full range of uncertainty inherent in these estimates. We hope that this work will provide applied researchers with a practical set of tools to appropriately model outcomes in cost-effectiveness analysis

Analysis of SF-6D Health State Utility Scores: Is Beta Regression Appropriate?

Background: Typically, modeling of health-related quality of life data is often troublesome since its distribution is positively or negatively skewed, spikes at zero or one, bounded and heteroscedasticity. Objectives: In the present paper, we aim to investigate whether Bayesian beta regression is appropriate for analyzing the SF-6D health state utility scores and respondent characteristics. Methods: A sample of 126 Lebanese members from the American University of Beirut valued 49 health states defined by the SF-6D using the standard gamble technique. Three different models were fitted for SF-6D via Bayesian Markov chain Monte Carlo (MCMC) simulation methods. These comprised a beta regression, random effects and random effects with covariates. Results from applying the three Bayesian beta regression models were reported and compared based on their predictive ability to previously used linear regression models, using mean prediction error (MPE), root mean squared error (RMSE) and deviance information criterion (DIC). Results: For the three different approaches, the beta regression model was found to perform better than the normal regression model under all criteria used. The beta regression with random effects model performs best, with MPE (0.084), RMSE (0.058) and DIC (−1621). Compared to the traditionally linear regression model, the beta regression provided better predictions of observed values in the entire learning sample and in an out-of-sample validation. Conclusions: Beta regression provides a flexible approach to modeling health state values. It also accounted for the boundedness and heteroscedasticity of the SF-6D index scores. Further research is encouraged