Food Choices and Hypertension Among Rural Thais: Evidence From a Discrete Choice Experiment.

Objective: The rural northern region of Thailand exhibits the highest rate of hypertension. This study explored hypertensive-related food choices between normotensive and hypertensive people residing in rural northern Thailand to determine which food attributes influence their choices. Methods: The study conducted a discrete choice experiment (DCE) survey among Thai adults residing in rural northern Thailand (n = 403) to estimate the relative importance of four food attributes, including food preparation, price, taste, and amount of salt. A mixed logit model was used to analyze the data from the DCE. Results: The first and second most important attributes in both hypertensive and normotensive groups were the amount of salt and food preparation at home, respectively, followed by price and taste. Specifically, the normotensive group was more attentive to the amount of salt in their food than their hypertensive counterparts. Conclusion: Intervention programs in rural communities may benefit from focusing their attention on embracing low-salt cultural foods and providing guidance on how to add flavor without additional salt or reduce high sodium seasonings without losing flavor when cooking.

Orthogonal array composite designs for drug combination experiments with applications for tuberculosis.

The aim of this article is to provide an overview of the orthogonal array composite design (OACD) methodology, illustrate the various advantages, and provide a real-world application. An OACD combines a two-level factorial design with a three-level orthogonal array and it can be used as an alternative to existing composite designs for building response surface models. We compare the D$$ D $$ -efficiencies of OACDs relative to the commonly used central composite design (CCD) when there are a few missing observations and demonstrate that OACDs are more robust to missing observations for two scenarios. The first scenario assumes one missing observation either from one factorial point or one additional point. The second scenario assumes two missing observations either from two factorial points or from two additional points, or from one factorial point and one additional point. Furthermore, we compare OACDs and CCDs in terms of I$$ I $$ -optimality for precise predictions. Lastly, a real-world application of an OACD for a tuberculosis drug combination study is provided.

Which snack factors and nutritional ingredients influence college students' snack choices? Evidence from discrete choice experiments.

Objective: The study examined which snack factors and nutritional ingredients influence college students' snack choices using a discrete choice experiment (DCE). Participants: In November 2016, a total of 1,624 undergraduate students participated in the study. Methods: Two DCEs were constructed using a unique approach of block fractional factorial designs. The first DCE examined four three-level snack factors: healthiness, taste, convenience, and price. The second DCE focused on six two-level nutritional ingredients: sugar, salt, calories, fat, all natural, and fiber. Results: Students preferred quick and cheap snacks, but higher prices on healthy snacks did not affect their decision significantly. Healthiness and sugar had the highest relative importance of snack factors and nutritional ingredients, respectively. High-sugar snacks were less favored if students considered themselves educated in nutrition. Conclusion: Thus, potential ways to improve the snack choices for college students are to offer healthier snacks on college campuses and to promote nutrition education.

Using blocked fractional factorial designs to construct discrete choice experiments for healthcare studies.

Discrete choice experiments (DCEs) are increasingly used for studying and quantifying subjects preferences in a wide variety of healthcare applications. They provide a rich source of data to assess real-life decision-making processes, which involve trade-offs between desirable characteristics pertaining to health and healthcare and identification of key attributes affecting healthcare. The choice of the design for a DCE is critical because it determines which attributes' effects and their interactions are identifiable. We apply blocked fractional factorial designs to construct DCEs and address some identification issues by utilizing the known structure of blocked fractional factorial designs. Our design techniques can be applied to several situations including DCEs where attributes have different number of levels. We demonstrate our design methodology using two healthcare studies to evaluate (i) asthma patients' preferences for symptom-based outcome measures and (ii) patient preference for breast screening services. Copyright © 2016 John Wiley & Sons, Ltd.

Application of fractional factorial designs to study drug combinations.

Herpes simplex virus type 1 (HSV-1) is known to cause diseases of various severities. There is increasing interest to find drug combinations to treat HSV-1 by reducing drug resistance and cytotoxicity. Drug combinations offer potentially higher efficacy and lower individual drug dosage. In this paper, we report a new application of fractional factorial designs to investigate a biological system with HSV-1 and six antiviral drugs, namely, interferon alpha, interferon beta, interferon gamma, ribavirin, acyclovir, and tumor necrosis factor alpha. We show how the sequential use of two-level and three-level fractional factorial designs can screen for important drugs and drug interactions, as well as determine potential optimal drug dosages through the use of contour plots. Our initial experiment using a two-level fractional factorial design suggests that there is model inadequacy and that drug dosages should be reduced. A follow-up experiment using a blocked three-level fractional factorial design indicates that tumor necrosis factor alpha has little effect and that HSV-1 infection can be suppressed effectively by using the right combination of the other five antiviral drugs. These observations have practical implications in the understanding of antiviral drug mechanism that can result in better design of antiviral drug therapy.