Dataset Information

Anger while driving in Mexico City.

ABSTRACT: This study aims to analyze the level of anger developed by drivers in Mexico City and also understand the behavior that those drivers use to express that anger, using four different survey methods. The first focuses on personal information, the second Driving Anger Expression Inventory (DAX), the third refers to a shorten version of Driving Anger Scale (DAS) and the fourth being the Dula Dangerous Driving Index (DDDI). These have previously been applied and validated in several different countries. The questionnaires were filled out online by 626 drivers. Using the data collected through the online platform, it was possible to identify the kind of reactions volunteers displayed while driving. Also, it was possible to identify that people in Mexico City developed anger depending on their driving area. Our analyses shows that in the Adaptive/Constructive Expression subscale, males and females show a significant difference in their mean score, with women express their anger in a more constructive way than males.

SUBMITTER: Hernandez-Hernandez AM

PROVIDER: S-EPMC6768538 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Anger while driving in Mexico City.

Hernández-Hernández Ana María AM Siqueiros-García Jesús M JM Robles-Belmont Eduardo E Gershenson Carlos C

PloS one 20190930 9

This study aims to analyze the level of anger developed by drivers in Mexico City and also understand the behavior that those drivers use to express that anger, using four different survey methods. The first focuses on personal information, the second Driving Anger Expression Inventory (DAX), the third refers to a shorten version of Driving Anger Scale (DAS) and the fourth being the Dula Dangerous Driving Index (DDDI). These have previously been applied and validated in several different countri ...[more]

PMID: 31568529

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Project description:UNLABELLED:Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. IMPLICATIONS:Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Project description:BackgroundParticulate matter ≤10 μm in aerodynamic diameter (PM10) and diet quality are risk factors for systemic inflammation, which is associated with preterm birth (PTB). PM10 and a pro-inflammatory diet (assessed by the Dietary Inflammatory Index [DII®]) have been individually evaluated as causes of PTB and differences by offspring sex have been reported for the DII. However, additional studies are needed to evaluate joint effects of these associations to inform intervention efforts.ObjectivesTo evaluate the independent and joint effects of PM10 and energy-adjusted DII (E-DII) on PTB risks.MethodsPM10 estimates were generated from daily citywide averages for 1216 pregnant women from three subcohorts of the Early Life Exposures in Mexico to Environmental Toxicants study using data from the Mexico City Outdoor Air Monitoring Network. Among a subset of participants (N = 620), E-DII scores were calculated using a validated food frequency questionnaire. Cox Proportional Hazards models were run for select periods during pregnancy and entire pregnancy averages for E-DII and PM10. We assessed for potential non-linear associations using natural splines.ResultsIn adjusted models, PM10 exposure was associated with increased risks of PTB for a range of values (58-72 μg/m3) during the second trimester, while negative associations were seen during the second (≥74 μg/m3) and third trimesters (55-65 μg/m3). Analyses conducted using distributed lag models for periods closer to delivery (max lag = 90) did not show negative associations between PM10 exposure and preterm birth, and indeed positive significant associations were observed (estimates and figures). E-DII was not associated with PTB and there was no evidence of effect modification by infant sex. There was no evidence of interaction between PM10 and E-DII and the risk of preterm birth.DiscussionAssociations between PM10 and PTB in Mexico City varied over time and across levels of PM10. Our findings of negative associations in the second and third trimesters, which are contrary to the hypothesized relationship between PM10 and PTB, may be due to a number of factors, including live birth bias and the exposure period evaluated. Differences in results for the periods evaluated suggest that PM10 from shorter exposure windows may play a more proximal role in initiating preterm labor.

Dataset Information

Anger while driving in Mexico City.

Publications

Anger while driving in Mexico City.

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