Cumulative Effects Model Research Articles

Modeling distracted driving behavior considering cognitive processes

The modeling of distracted driving behavior has been studied for many years, however, there remain many distraction phenomena that can not be fully modeled. This study proposes a new method that establishes the model using the queuing network model human processor (QN-MHP) framework. Unlike previous models that only consider distracted-driving-related human factors from a mathematical perspective, the proposed method reflects the information processing in the human brain, and simulates the distracted driver’s cognitive processes based on a model structure supported by physiological and cognitive research evidence. Firstly, a cumulative activation effect model for external stimuli is adopted to mimic the phenomenon that a driver responds only to stimuli above a certain threshold. Then, dual-task queuing and switching mechanisms are modeled to reflect the cognitive resource allocation under distraction. Finally, the driver's action is modeled by the Intelligent Driver Model (IDM). The model is developed for visual distraction auditory distraction separately. 773 distracted car-following events from the Shanghai Naturalistic Driving Study data were used to calibrate and verify the model. Results show that the model parameters are more uniform and reasonable. Meanwhile, the model accuracy has improved by 57% and 66% compared to the two baseline models respectively. Moreover, the model demonstrates its ability to generate critical pre-crash scenarios and estimate the crash rate of distracted driving. The proposed model is expected to contribute to safety research regarding new vehicle technologies and traffic safety analysis.

The effect of parental background on the potential education and employment of migrants’ children in Switzerland

ABSTRACT This paper explores the relations between parental background, the education level reached and the socioprofessional position of children during their transition to adulthood. The paper links segmented assimilation and institutional theories with a life-course approach. It tests three types of mechanisms of the relationship between parental background and children's lifecourse, which are the critical-period model; the path-dependency; and the cumulative-effect model. The paper uses data from the LIVES-FORS cohort panel survey and develops techniques of Bayesian network modelling. The sample is composed of 788 young people educated in Switzerland before the age of 10 with Swiss or non-Swiss origins interviewed five times from 2013 to 2017. The paper provides striking results of path dependency-effect models. It shows no correlation between the geographical origin of the parents and their children's success at school. The professional position of the children of migrants seems only correlated to their educational capital and gender.

Social determinants of health associated with COVID-19 severity during pregnancy: a multinational cohort study (in the International Registry of Coronavirus Exposure in Pregnancy)

BackgroundThe COVID-19 pandemic has caused morbidity and mortality, particularly among vulnerable populations. We aimed to assess social and demographic characteristics associated with COVID-19 severity among symptomatic participants during pregnancy.MethodsThe International Registry of Coronavirus Exposure in Pregnancy is a multinational, longitudinal observational cohort study of adult participants tested for SARS-CoV-2 or who received clinical diagnosis of COVID-19 during pregnancy (NCT04366986). Disease severity status of mild, moderate, or severe was determined based on symptoms and healthcare utilization. Stratified by current versus recent pregnancy at enrollment, univariate mixed-effects logistic regression modeling was used to characterize association between social and demographic characteristics with COVID-19 severity, using a cumulative mixed effect model with country as a random effect.ResultsThe odds of developing more severe COVID-19 (odds ratio [95% confidence interval]) were higher among participants with lower socioeconomic status (poor: 2.72 [2.01,3.69]; lower-middle class: 2.07 [1.62,2.65] vs wealthy), among participants with lower educational attainment (high school: 1.68 [1.39,2.03]; < high school (1.77 [1.25,2.51] vs graduate education). Participants over 25 years of age had lower odds of severe COVID-19 versus participants < 25 years (25–34: 0.69 [0.56,0.85]; 35–50: 0.62 [0.48,0.80]). Employment in food services was also associated with increased odds of more severe COVID-19, whereas employment in healthcare and within home, and primiparity were associated with lower severity.ConclusionsFindings suggest that employment setting and economic status have strong associations with COVID-19 severity, which warrants considering social determinants of health in the context of assessing risk factors of more severe COVID-19 during pregnancy.Trial registrationIRCEP was registered with the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) [EUPAS37360] and clinicaltrials.gov [NCT04366986].

Supplementing Environmental Assessments with Cumulative Effects Scenario Modeling for Grizzly Bear Connectivity in the Bow Valley, Alberta, Canada

Persistence of sensitive wildlife in populated regions requires conservation strategies that address gradual expansion of development footprint and human activity. The project-based environmental assessment regime for municipal development is poorly suited to provide necessary strategic perspective, given its focus on local and short-term impacts. We used the ALCES cumulative effects model to strategically assess impacts to grizzly bears (Ursus arctos) in the Bow Valley of Alberta, Canada. Landscape simulation mapped expansion of past and potential future development footprint in the region over multiple decades. Consequences to movement connectivity for grizzly bears were estimated by applying a least cost path analysis to the landscape simulation. An index of recreational activity was derived from fitness tracking data and integrated with the landscape simulation to model change in recreational activity through time. Maps of grizzly bear connectivity and recreational activity were combined to calculate human-bear conflict risk. The analysis suggests that connectivity has been altered through displacement to upslope areas by settlement expansion, such that surrounding natural areas have become important for grizzly bear connectivity. These areas are also popular for outdoor recreation, resulting in elevated human-bear conflict risk which can be expected to increase if development and human activity continue to expand in high connectivity areas. Conservation of wildlife in populated regions will be supported by broadening the scope of environmental assessment to address cumulative effects of development footprint and human activity over large spatial and temporal scales.

Size-segregated particle number concentrations and outpatient-department visits for pediatric respiratory diseases in Shanghai, China

BackgroundFew studies have simultaneously explored which size of particles has the greatest impact on the risk for pediatric asthma, bronchitis and upper respiratory tract infections (URTIs). ObjectivesTo investigate the short-term association between size-segregated particle number concentrations (PNCs) and outpatient-department visits (ODVs) for major pediatric respiratory diseases. MethodsDaily counts of pediatric ODVs for asthma, bronchitis and URTIs were obtained from 66 hospitals in Shanghai, China, from 2016 to 2018. Pollutant effects were estimated using Poisson generalized additive models combined with polynomial distributed lag models. We also fitted co-pollutant cumulative effects models included six criteria air pollutants and conducted stratifying analyses by gender, age, season and geographic distances. ResultsWe identified a total of 430,103 patients with asthma, 1,547,013 patients with bronchitis, and 2,155,738 patients with URTIs from the hospitals. Effect estimates increased with decreasing particle size. Ultrafine particle (UFP) and PNCs of 0.10–0.40 µm particles (PNC0.10–0.40) were associated with increased ODVs for asthma, bronchitis and URTIs at cumulative lags up to 3d. Associations tended to appear stable after adjusting for criteria air pollutants. At the cumulative lag 0–2d, each interquartile range increase in UFP was associated with increased ODVs due to asthma (relative risk 1.21, 95% CI: 1.07, 1.38), bronchitis (1.20, 95% CI: 1.07, 1.34) and URTI (1.17, 95% CI: 1.06, 1.30), whereas the associations for PNC0.10–0.40 remained significant but attenuated in magnitude. ConclusionsUFP may be a leading contributor to the adverse respiratory effects of particulate air pollution and the effects increased with decreasing particle size.

Revisiting the hypothesis that friends buffer against diminished self-esteem arising from poor quality parent-adolescent relationships: A replication study.

This replication study revisited conclusions from 2 previous investigations (Gauze, Bukowski, Aquan-Assee, & Sippola, 1996; van Aken & Asendorpf, 1997), which suggested that support from friends buffers against diminished self-esteem arising from poor quality relationships with mothers during the transition into adolescence. The aim of this replication study was to conduct an independent test of these findings with both concurrent and longitudinal data. Concurrent data for replication analyses were drawn from 4 projects, involving a total of 959 boys and 1,119 girls (ages 10 to 14) from Canada and the United States. Three samples reported participant ethnic descent: Africa (12.1%), Asia (5.6%), Europe (65.3%), Latin America (12.1%), and Native North America (0.9%). Child and mother reports of mother-child relationship quality assayed (a) maternal social support (in 3 data sets), and (b) family cohesion and adaptability (in 2 data sets). Main effects were replicated but hypothesized buffering effects were not. Maternal social support and friend social support were independently associated with adolescent self-esteem, concurrently, but not longitudinally. Family cohesion (but not adaptability) was associated with adolescent self-esteem, concurrently and longitudinally. Friend social support did not moderate associations between mother-child relationship quality and adolescent self-esteem, concurrently or longitudinally. The findings are consistent with a cumulative effects model wherein friends uniquely contribute to adolescent self-worth, over and above the contribution of mothers. The findings do not support claims that friends moderate associations between mother-child relationship quality and adolescent self-esteem. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A cumulative effects model for population trajectories of resident killer whales in the Northeast Pacific

Like numerous species at risk, the resident killer whale populations of the Northeast Pacific are vulnerable to the cumulative effects of anthropogenic threats. A Pathways of Effects conceptual model summarised the current understanding of each threat (prey availability, acoustic and physical disturbance, and contaminants), threat interactions, and potential impacts to fecundity and mortality. A Population Viability Analysis utilised the most recent available data to quantify impacts of threats on population parameters. The impacts of individual and cumulative threat scenarios on modelled Southern and Northern Resident Killer Whale populations were compared to the observed population demographics to define a model that best captured the real world dynamics. Of the individual and combined threat models tested, the cumulative model incorporating all threats predicted demographic rates closest to those observed for both populations. Recent low Chinook salmon abundance and its interactions with vessel disturbance and contamination strongly influenced modelled killer whale population dynamics. The cumulative effects population viability analysis model projected a mean increase in the modelled Northern Resident Killer Whale population to the carrying capacity within 25 years. In contrast, the mean modelled Southern Resident Killer Whale population trajectory was projected to decline under current conditions, with a 26% probability of population extinction, and in those projections, extinction was estimated to occur after 86 (± 11) years. Our results highlight the importance of considering the collective impact of multiple threats to imperilled species and the necessity of testing management and mitigation measures aimed at recovery using a holistic, validated model.

A longitudinal exploration of mental health resilience, cognitive impairment and loneliness.

There is a growing interest in how people living with dementia may achieve good outcomes and be resilient despite their health challenges. Understanding what might be important for resilience in this population is largely untested theory. The analysis draws a subsample with cognitive impairment (N=579) from two waves of the Cognitive Function and Ageing Studies Wales study, a nationally representative study of community-dwelling people aged 65+ in Wales. We constructed a measure of mental health resilience (MHR) defined as no depression, no anxiety and high well-being. Drawing on a resilience framework, we tested univariate and cumulative effects models of the factors that enable MHR, and then examined whether MHR is important for reducing loneliness over time. Across both waves of data 22% (n=121) met the criteria for MHR. The cumulative effects model found the odds of MHR were greater for male gender, higher self-esteem, greater social resources and no subjective memory complaints. Controlling for these significant predictors, MHR significantly predicted lower total and sub-scale scores for loneliness at wave 2. Sensitivity analysis shows these effects held at lower levels of cognitive function when the Mini-Mental State Examination score was <25, but not at <23. This paper addresses a gap in research regarding the conceptualisation and measurement of resilience when facing cognitive impairment. Understanding what aspects of a person's life might enable good mental health despite cognitive impairment-to be resilient-could inform effective strategies for friends and families, along with health, and social policy and practice.

KAJIAN SEJARAH DAN PERKEMBANGAN TEORI EFEK MEDIA

Media is one of the important needs for the community, but the media has an effect on the community both directly and indirectly. In Media Effects Theory three paradigms are used by the media to find out the effects of these media. The first paradigm, called the powerful effects paradigm (Direct Effects Models), the media is said to have enormous power so that members of the isolated and anonymous audience of this mass audience will surrender immediately. The second paradigm is the minimalist effect or the limited effects paradigm (Limited Effects Models), the media seen in audience control over selectivity. The third paradigm of cumulative effects (Cumulative Effects Models), the community has too much potential for media in limited exposure. At present, the research on the theory of media effects has developed sufficiently to the extent of several specific sub-areas of research&#x0D; Key word : Theory of media effects

Determination of the time-dependent association between ciprofloxacin consumption and ciprofloxacin resistance using a weighted cumulative exposure model compared with standard models

To obtain comprehensive insight into the association of ciprofloxacin use at different times in the past with the current risk of detecting resistance. This retrospective nested case-control study of ciprofloxacin users used Dutch data from the PHARMO Database Network and one laboratory for the period 2003-14. Cases and controls were selected as patients with an antibiotic susceptibility test (AST) indicating ciprofloxacin resistance or susceptibility, respectively. We performed univariable and multivariable conditional logistic regression analyses, defining time-dependent exposure using standard definitions (current ciprofloxacin use, used 0-30, 31-90, 91-180 and 181-360 days ago) and a flexible weighted cumulative effect (WCE) model with four alternative time windows of past doses (0-30, 0-90, 0-180 and 0-360 days). The study population consisted of 230 cases and 909 controls. Under the standard exposure definitions, the association of ciprofloxacin use with resistance decreased with time [current use: adjusted OR 6.8 (95% CI 3.6-12.4); used 181-360 days ago: 1.3 (0.8-1.9)]. Under the 90 day WCE model (best-fitting model), more recent doses were more strongly associated with resistance than past doses, as was longer or repeated treatment. The 180 day WCE model, which fitted the data equally well, suggested that doses taken 91-180 days ago were also significantly associated with resistance. The estimates for the association between ciprofloxacin use at different times and resistance show that ciprofloxacin prescribers should consider ciprofloxacin use 0-180 days ago to ensure that patients receive suitable treatment. The OR of ciprofloxacin resistance could be reduced by eliminating repeated ciprofloxacin prescription within 180 days and by treating for no longer than necessary.

Modeling of cumulative effects of time-varying drug exposures on within-subject changes in a continuous outcome.

An accurate assessment of the safety or effectiveness of drugs in pharmaco-epidemiological studies requires defining an etiologically correct time-varying exposure model, which specifies how previous drug use affects the outcome of interest. To address this issue, we develop, and validate in simulations, a new approach for flexible modeling of the cumulative effects of time-varying exposures on repeated measures of a continuous response variable, such as a quantitative surrogate outcome, or a biomarker. Specifically, we extend the linear mixed effects modeling to estimate how past and recent drug exposure affects the way individual values of the outcome change throughout the follow-up. To account for the dosage, duration and timing of past exposures, we rely on a flexible weighted cumulative exposure methodology to model the cumulative effects of past drug use, as the weighted sum of past doses. Weights, modeled with unpenalized cubic regression B-splines, reflect the relative importance of doses taken at different times in the past. In simulations, we evaluate the performance of the model under different assumptions concerning (i) the shape of the weight function, (ii) the sample size, (iii) the number of the longitudinal observations and (iv) the intra-individual variance. Results demonstrate the accuracy of our estimates of the weight function and of the between- and within-patients variances, and good correlation between the observed and predicted longitudinal changes in the outcome. We then apply the proposed method to re-assess the association between time-varying glucocorticoid exposure and weight gain in people living with rheumatoid arthritis.

Multi-city study on air pollution and hospital outpatient visits for asthma in China

BackgroundThe proportion of asthma patients with mild to moderate exacerbations is far greater than the number who experience episodes that are severe enough to require emergency room visits or hospital admission. However the routinely collected data from hospitals is absent in the past. ObjectiveTo evaluate associations between short-term exposures to air pollutants and hospital outpatient visits for asthma in China. MethodsWe obtained data for 143,057 asthma outpatient visits from the largest hospitals in 17 Chinese cities, between Jan 01 2013 and Dec 31 2015. We used daily concentrations of air pollutants measured by the China National Environmental Monitoring Centre. We used a time-stratified case-crossover design, and fitted conditional logistic regression models to determine the associations. ResultsParticulate matter ≤10μm in diameter (PM10) and nitrogen dioxide (NO2) were associated with increased risks of hospital outpatient visits for asthma on the same day, while the effects were delayed for particulate matter ≤2.5μm in diameter (PM2.5) and sulphur dioxide (SO2). For the cumulative effect model at lag05 days, 10 μg/m3 increase in air pollutants concentrations were correlated with hospital outpatient visits for asthma with odds ratios (ORs) and 95% confidence intervals 1.004 (1.000-1.008) for PM2.5, 1.005 (1.002-1.008) for PM10, 1.030 (1.021-1.040) for NO2, and 1.015 (1.008-1.021) for SO2. Almost one in nine (10.9%; 7.7, 13.9%) hospital outpatient visits for asthma were attributable to NO2. ConclusionShort-term exposures to PM2.5, PM10, NO2 and SO2 were associated with hospital outpatient visits for asthma in China.

Additive and interactive cumulative effects on boreal landbirds: winners and losers in a multi‐stressor landscape

Stressors created by multiple resource industries can result in cumulative effects over time and space. Many studies have evaluated single stressors and assumed that cumulative effects can be understood by adding stressors together. However, there is growing evidence that interactive effects are important in structuring biological communities. We evaluated whether the effects of multiple stressors in the boreal forest (linear features, energy, forestry) combine additively or interactively by testing a candidate model set of 12 cumulative effects models of abundance for 27 landbird species. We fitted paired additive and interactive Generalized Additive Models and examined model predictions in the Athabasca Oil Sands Area of Alberta, Canada, and a theoretical no‐disturbance version of the study area. Of the 27 species examined, an additive disturbance model was the best for nine species, while an interactive disturbance model was the best for 11 species. In the current study area, disturbance models predicted strong increases in abundance for species associated with deciduous forest and open habitats (winning species) and moderate decreases for species associated with conifer forest (losing species). We found a 15% change in landbird community composition between the current study area, with 8.4% disturbance, and the theoretical no‐disturbance study area. Complex synergistic and antagonistic interactions among stressors were observed for 39% of landbird species, with the majority of interactions observed being synergistic. Stressors with relatively small disturbance areas, such as narrow linear disturbances, frequently interacted with other stressors to affect species’ responses, and energy sector stressors often had additive or interactive effects with forestry stressors. Interactive cumulative effects from multiple sectors will make it increasingly difficult for industry and land managers to manage impacts unless interactions among stressors are incorporated into cumulative effects assessments and regional land use planning processes.

Estimating cumulative wastewater treatment plant discharge influences on acesulfame and Escherichia coli in a highly impacted watershed with a fully-integrated modelling approach

Wastewater treatment plant (WWTP) discharge is often considered a principal source of surface water contamination. In this study, a three-dimensional fully-integrated groundwater–surface water model was used to simulate the transport characteristics and cumulative loading of an artificial sweetener (acesulfame) and fecal indicator bacteria (Escherichia coli) from WWTPs within a 6800 km2 mixed-use, highly impacted watershed in Ontario, Canada. The model, which employed 3.5 × 106 computational nodes and 15 layers, facilitated a comprehensive assessment of groundwater–surface water interactions under high and low flow conditions; processes typically not accounted for in WWTP cumulative effects models. Simulations demonstrate that the model had significant capacity in reproducing the average and transient multi-year groundwater and surface water flow conditions in the watershed. As a proxy human-specific conservative tracer, acesulfame was useful for model validation and to help inform the representation of watershed-scale transport processes. Using a uniform WWTP acesulfame loading rate of 7.14 mg person−1 day−1, the general spatial trends and magnitudes of the acesulfame concentration profile along the main river reach within the watershed were reproduced; however, model performance was improved by tuning individual WWTP loading rates. Although instream dilution and groundwater–surface water interactions were strongly dependent on flow conditions, the main reach primarily consisted of groundwater discharge zones. For this reason, hydrodynamic dispersion in the hyporheic zone is shown as the predominant mechanism driving acesulfame into near-stream shallow groundwater, while under high flow conditions, the simulations demonstrate the potential for advective flushing of the shallow groundwater. Regarding the cumulative impact of the WWTPs on E. coli concentrations in the surface flow system, simulated transient E. coli levels downstream of WWTPs in the watershed were significantly lower than observed values, thus highlighting the potential importance of other sources of E. coli in the watershed.

Competing risks modeling of cumulative effects of time-varying drug exposures.

An accurate assessment of drug safety or effectiveness in pharmaco-epidemiology requires defining an etiologically correct time-varying exposure model, which specifies how previous drug use affects the hazard of the event of interest. An additional challenge is to account for the multitude of mutually exclusive events that may be associated with the use of a given drug. To simultaneously address both challenges, we develop, and validate in simulations, a new approach that combines flexible modeling of the cumulative effects of time-varying exposures with competing risks methodology to separate the effects of the same drug exposure on different outcomes. To account for the dosage, duration and timing of past exposures, we rely on a spline-based weighted cumulative exposure modeling. We also propose likelihood ratio tests to test if the cumulative effects of past exposure on the hazards of the competing events are the same or different. Simulation results indicate that the estimated event-specific weight functions are reasonably accurate, and that the proposed tests have acceptable type I error rate and power. In real-life application, the proposed method indicated that recent use of antihypertensive drugs may reduce the risk of stroke but has no effect on the hazard of coronary heart disease events.

Random forests as cumulative effects models: A case study of lakes and rivers in Muskoka, Canada

Cumulative effects assessment (CEA) ― a type of environmental appraisal ― lacks effective methods for modeling cumulative effects, evaluating indicators of ecosystem condition, and exploring the likely outcomes of development scenarios. Random forests are an extension of classification and regression trees, which model response variables by recursive partitioning. Random forests were used to model a series of candidate ecological indicators that described lakes and rivers from a case study watershed (The Muskoka River Watershed, Canada). Suitability of the candidate indicators for use in cumulative effects assessment and watershed monitoring was assessed according to how well they could be predicted from natural habitat features and how sensitive they were to human land-use. The best models explained 75% of the variation in a multivariate descriptor of lake benthic-macroinvertebrate community structure, and 76% of the variation in the conductivity of river water. Similar results were obtained by cross-validation. Several candidate indicators detected a simulated doubling of urban land-use in their catchments, and a few were able to detect a simulated doubling of agricultural land-use. The paper demonstrates that random forests can be used to describe the combined and singular effects of multiple stressors and natural environmental factors, and furthermore, that random forests can be used to evaluate the performance of monitoring indicators. The numerical methods presented are applicable to any ecosystem and indicator type, and therefore represent a step forward for CEA.

Folate Deficiency and Gene Polymorphisms of MTHFR, MTR and MTRR Elevate the Hyperhomocysteinemia Risk.

Hyperhomocysteinemia (HHcy) is an independent risk factor for cardiovascular diseases (CVDs). We aimed to investigate the joint effect of homocysteine metabolism gene polymorphisms, as well as the folate deficiency on the risk of HHcy in a Chinese hypertensive population. This study enrolled 480 hypertensive patients aged 28 - 75 from six hospitals in different Chinese regions from 9/2005 - 12/2005. Known genotypes of methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, methionine synthase (MTR) A2756G, and methionine synthase reductase (MTRR) A66G were detected by PCRRFLP methods. Serum Hcy was measured by high-performance liquid chromatography and serum folate was measured by chemiluminescent immunoassay. MTHFR C677T and MTR A2756G can independently elevate the risk of HHcy (TT vs. CC + CT, p < 0.001 and AG + GG vs. AA, p = 0.026, respectively), whereas MTHFR A1298C decreased HHcy risk (AC + CC vs. AA, p < 0.001) and showed a protective effect against HHcy risk. Importantly, the joint effect of these risk genotypes showed significantly higher odds of HHcy than non-risk genotypes, especially the patients with four risk genotypes. It is noteworthy that this deleterious effect was aggravated by folate deficiency. These findings were verified by generalized multifactor dimensionality reduction model (p = 0.001) and a cumulative effects model (p < 0.001). We have first demonstrated that the joint effect of homocysteine metabolism gene polymorphisms and folate deficiency lead to dramatic elevations in the HHcy risk.

Theoretical Behaviorism, Economic Theory, and Choice

Choice behavior is studied differently in humans and in animals, and different theories have arisen to explain the results. I suggest that an approach derived from animal studies is also appropriate for human choice. Daniel Kahneman and Amos Tversky's prospect theory, a popular two-part account of human choice, is a functional theory amounting, after some years of evolution, to a classification of types of deviation from “rational” reward maximization. Animal choice, on the other hand, can be explained causally as the outcome of competition between a set of possible responses with different “strengths.” The strength of each response is directly related to its historical payoff probability, and responses compete in winner-take-all fashion. An “active” response occurs and is strengthened or weakened depending on its outcome. If it is sufficiently weakened, it will be supplanted by the strongest “silent” response. This cumulative effects (CE) model has been tested in operant conditioning experiments that show, for example, that when choosing between two identical probabilistic choices in a “two-armed bandit” situation, animals will fixate on one if the payoff probabilities are high, but be indifferent if they are low, a pattern not easily deducible from any kind of optimality theory. Kahneman's distinction between “fast” and “slow” systems is indistinguishable from the distinction between active and silent responses in the CE model, which therefore offers a causal account of human as well as animal choice behavior.

Short-term Effects of Ambient Air Pollution on Emergency Department Visits for Asthma: An Assessment of Effect Modification by Prior Allergic Disease History.

ObjectivesThe goal of this study was to investigate the short-term effect of ambient air pollution on emergency department (ED) visits in Seoul for asthma according to patients’ prior history of allergic diseases.MethodsData on ED visits from 2005 to 2009 were obtained from the Health Insurance Review and Assessment Service. To evaluate the risk of ED visits for asthma related to ambient air pollutants (carbon monoxide [CO], nitrogen dioxide [NO2], ozone [O3], sulfur dioxide [SO2], and particulate matter with an aerodynamic diameter <10 μm [PM10]), a generalized additive model with a Poisson distribution was used; a single-lag model and a cumulative-effect model (average concentration over the previous 1-7 days) were also explored. The percent increase and 95% confidence interval (CI) were calculated for each interquartile range (IQR) increment in the concentration of each air pollutant. Subgroup analyses were done by age, gender, the presence of allergic disease, and season.ResultsA total of 33 751 asthma attack cases were observed during the study period. The strongest association was a 9.6% increase (95% CI, 6.9% to 12.3%) in the risk of ED visits for asthma per IQR increase in O3 concentration. IQR changes in NO2 and PM10 concentrations were also significantly associated with ED visits in the cumulative lag 7 model. Among patients with a prior history of allergic rhinitis or atopic dermatitis, the risk of ED visits for asthma per IQR increase in PM10 concentration was higher (3.9%; 95% CI, 1.2% to 6.7%) than in patients with no such history.ConclusionsAmbient air pollutants were positively associated with ED visits for asthma, especially among subjects with a prior history of allergic rhinitis or atopic dermatitis.

Watershed Planning within a Quantitative Scenario Analysis Framework.

There is a critical need for tools and methodologies capable of managing aquatic systems within heavily impacted watersheds. Current efforts often fall short as a result of an inability to quantify and predict complex cumulative effects of current and future land use scenarios at relevant spatial scales. The goal of this manuscript is to provide methods for conducting a targeted watershed assessment that enables resource managers to produce landscape-based cumulative effects models for use within a scenario analysis management framework. Sites are first selected for inclusion within the watershed assessment by identifying sites that fall along independent gradients and combinations of known stressors. Field and laboratory techniques are then used to obtain data on the physical, chemical, and biological effects of multiple land use activities. Multiple linear regression analysis is then used to produce landscape-based cumulative effects models for predicting aquatic conditions. Lastly, methods for incorporating cumulative effects models within a scenario analysis framework for guiding management and regulatory decisions (e.g., permitting and mitigation) within actively developing watersheds are discussed and demonstrated for 2 sub-watersheds within the mountaintop mining region of central Appalachia. The watershed assessment and management approach provided herein enables resource managers to facilitate economic and development activity while protecting aquatic resources and producing opportunity for net ecological benefits through targeted remediation.