Methodology for Determining the Appropriateness of a Linear Dose-Response Function

Risk Analysis ◽  
2010 ◽  
Vol 31 (3) ◽  
pp. 345-350 ◽  
Author(s):  
Michael S. Williams ◽  
Eric D. Ebel ◽  
David Vose
2022 ◽  
Vol 7 ◽  
pp. 7
Author(s):  
Robert Smith ◽  
Chloe Thomas ◽  
Hazel Squires ◽  
Elizabeth Goyder

IntroductionThe WHO-Europe’s Health Economic Assessment Tool is a tool used to estimatethe costs and benefits of changes in walking and cycling. Due to data limitationsthe tool’s physical activity module assumes a linear dose response relationship be-tween physical activity and mortality.MethodsThis study estimates baseline population physical activity distributions for 44 coun-tries included in the HEAT. It then compares, for three different scenarios, the re-sults generated by the current method, using a linear dose-response relationship,with results generated using a non-linear dose-response relationship.ResultsThe study finds that estimated deaths averted are relatively higher (lower) using thenon-linear effect in countries with less (more) active populations. This difference islargest for interventions which affect the activity levels of the least active the most.Since more active populations, e.g. in Eastern Europe, also tend to have lowerValue of a Statistical Life estimates the net monetary benefit estimated by the sce-narios are much higher in western-Europe than eastern-Europe.ConclusionsUsing a non-linear dose response function results in materially different estimateswhere populations are particularly inactive or particularly active. Estimating base-line distributions is possible with limited additional data requirements, although themethod has yet to be validated. Given the significant role of the physical activitymodule within the HEAT tool it is likely that in the evaluation of many interventionsthe monetary benefit estimates will be sensitive to the choice of the physical activitydose response function.


2020 ◽  
Vol 375 (1800) ◽  
pp. 20190271 ◽  
Author(s):  
Jasper H. B. de Groot ◽  
Peter A. Kirk ◽  
Jay A. Gottfried

Humans, like other animals, have an excellent sense of smell that can serve social communication. Although ample research has shown that body odours can convey transient emotions like fear, these studies have exclusively treated emotions as categorical , neglecting the question whether emotion quantity can be expressed chemically. Using a unique combination of methods and techniques, we explored a dose–response function: Can experienced fear intensity be encoded in fear sweat? Specifically, fear experience was quantified using multivariate pattern classification (combining physiological data and subjective feelings with partial least-squares-discriminant analysis), whereas a photo-ionization detector quantified volatile molecules in sweat. Thirty-six male participants donated sweat while watching scary film clips and control (calming) film clips. Both traditional univariate and novel multivariate analysis (100% classification accuracy; Q 2 : 0.76; R 2 : 0.79) underlined effective fear induction. Using their regression-weighted scores, participants were assigned significantly above chance (83% > 33%) to fear intensity categories (low–medium–high). Notably, the high fear group ( n = 12) produced higher doses of armpit sweat, and greater doses of fear sweat emitted more volatile molecules ( n = 3). This study brings new evidence to show that fear intensity is encoded in sweat (dose–response function), opening a field that examines intensity coding and decoding of other chemically communicable states/traits. This article is part of the Theo Murphy meeting issue ‘Olfactory communication in humans’.


Atmósfera ◽  
2017 ◽  
Vol 30 (1) ◽  
pp. 53-61 ◽  
Author(s):  
John Fredy Ríos Rojas ◽  
◽  
David Aperador Rodríguez ◽  
Edwin Arbey Hernández García ◽  
Carlos Enrique Arroyave Posada ◽  
...  

2013 ◽  
Vol 1 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Haoqian Zhang ◽  
Ying Sheng ◽  
Qianzhu Wu ◽  
Ao Liu ◽  
Yuheng Lu ◽  
...  

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