Mortality Implications of Increased Active Mobility for a Proposed Regional Transportation Emission Cap-and-Invest Program.
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ABSTRACT:
SUBMITTER: Raifman M
PROVIDER: S-EPMC7816754 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundClimate mitigation policies that focus on the transportation sector yield near-term health co-benefits that could motivate policy action.ObjectiveWe quantified CO2 emission reductions as well as the air pollution and health benefits of urban transportation policies promoting electric vehicles (EV) and walking and bicycling in Seattle, Washington.MethodsWe compared a business-as-usual scenario projected to 2035 with intervention scenarios in which 35% of gasoline vehicles were switched to EV, and 50% of car trips less than 8 kilometers were replaced by walking or bicycling. We modeled changes in primary traffic-generated oxides of nitrogen (NOx) and fine particulate matter (PM2.5) as well as walking and bicycling activity, CO2 emissions from traffic, and fatal traffic injuries due to the transportation policy scenarios. We estimated the impacts of these changes on annual cases of asthma and premature mortality in the Seattle population.ResultsIncreasing the use of EV, walking, and bicycling is estimated to reduce CO2 emissions by 744 tons/year (30%) and lower annual average concentrations of primary traffic-generated NOx and PM2.5 by 0.32 ppb (13%) and 0.08 μg/m3 (19%), respectively. In Seattle, the lower air pollutant concentrations, greater active transportation, and lower fatal traffic injuries would prevent 13 (95% CI: -1, 28), 49 (95% CI: 19, 71), and 5 (95% CI: 0, 14) premature deaths per year, respectively and 20 (95% CI: 8, 27) cases of asthma per year.SignificanceMoving towards cleaner vehicles and active transportation can reduce CO2 emissions, improve air quality, and population health. The resulting public health benefits provide important motivation for urban climate action plans.Impact statementUsing key components of the health impact assessment framework, we quantify the environmental and health benefits of urban transportation policy scenarios that promote electric vehicle use and replace short car trips with walking and bicycling as compared with a business as usual scenario in 2035. Our findings demonstrate that transportation scenarios promoting cleaner vehicles and active transportation can reduce CO2 emissions, improve air quality, and increase physical activity levels, resulting in significant public health benefits.
| S-EPMC8919173 | biostudies-literature
Project description:BackgroundActive transportation (AT), independent mobility (IM), and outdoor time are promising ways to increase children's physical activity. However, in order to create interventions to increase those forms of physical activity, it is important to understand the relationships between area-level socioeconomic status (SES) and type of urbanization with AT, IM, outdoor time, and physical activity, and this was the aim of the study.MethodsOne thousand six hundred ninety-nine children in grades 4 to 6 (mean age: 10.2 ± 1.0 years) from three Canadian regions participated. AT, IM, and outdoor time were assessed using questionnaires and physical activity was measured using the SC-StepRX pedometer. Area-level SES was assessed using the median household income of the census tract in which the school was located and type of urbanization was determined for each school using standardized procedures. Generalized linear and general linear mixed models were used to examine the relationships.ResultsArea-level SES and the type of urbanization were generally not related to AT, IM, or physical activity for either gender. However, we observed that both boys and girls living in lower SES areas had decreased odds of spending > 2 h outdoors on weekend days compared to their peers from higher SES areas. Girls living in suburban or rural areas were more likely to spend > 2 h outdoors on weekdays compared to their urban counterparts.ConclusionsAT, IM, and physical activity are generally not associated with area-level SES or the type of urbanization in this sample of Canadian children. The finding regarding outdoor time showing that both boys and girls of lower SES areas had decreased odds of spending > 2 h outdoors on weekends compared to their peers from higher SES areas suggest that additional efforts should be implemented to offer outdoor play opportunities in lower SES areas.
| S-EPMC6688238 | biostudies-literature
Project description:Policies that stimulate active transportation (walking and bicycling) have been related to heath benefits. This study aims to assess the potential health risks and benefits of promoting active transportation for commuting populations (age groups 16-64) in six European cities. We conducted a health impact assessment using two scenarios: increased cycling and increased walking. The primary outcome measure was all-cause mortality related to changes in physical activity level, exposure to fine particulate matter air pollution with a diameter <2.5 ?m, as well as traffic fatalities in the cities of Barcelona, Basel, Copenhagen, Paris, Prague, and Warsaw. All scenarios produced health benefits in the six cities. An increase in bicycle trips to 35% of all trips (as in Copenhagen) produced the highest benefits among the different scenarios analysed in Warsaw 113 (76-163) annual deaths avoided, Prague 61 (29-104), Barcelona 37 (24-56), Paris 37 (18-64) and Basel 5 (3-9). An increase in walking trips to 50% of all trips (as in Paris) resulted in 19 (3-42) deaths avoided annually in Warsaw, 11(3-21) in Prague, 6 (4-9) in Basel, 3 (2-6) in Copenhagen and 3 (2-4) in Barcelona. The scenarios would also reduce carbon dioxide emissions in the six cities by 1,139 to 26,423 (metric tonnes per year). Policies to promote active transportation may produce health benefits, but these depend of the existing characteristics of the cities. Increased collaboration between health practitioners, transport specialists and urban planners will help to introduce the health perspective in transport policies and promote active transportation.
| S-EPMC4773008 | biostudies-literature
Project description:BACKGROUND: Past studies of associations between measures of the built environment, particularly street connectivity, and active transportation (AT) or leisure walking/bicycling have largely failed to account for spatial autocorrelation of connectivity variables and have seldom examined both the propensity for AT and its duration in a coherent fashion. Such efforts could improve our understanding of the spatial and behavioral aspects of AT. We analyzed spatially identified data from Los Angeles and San Diego Counties collected as part of the 2001 California Health Interview Survey. RESULTS: Principal components analysis indicated that ~85% of the variance in nine measures of street connectivity are accounted for by two components representing buffers with short blocks and dense nodes (PRIN1) or buffers with longer blocks that still maintain a grid like structure (PRIN2). PRIN1 and PRIN2 were positively associated with active transportation (AT) after adjustment for diverse demographic and health related variables. Propensity and duration of AT were correlated in both Los Angeles (r = 0.14) and San Diego (r = 0.49) at the zip code level. Multivariate analysis could account for the correlation between the two outcomes.After controlling for demography, measures of the built environment and other factors, no spatial autocorrelation remained for propensity to report AT (i.e., report of AT appeared to be independent among neighborhood residents). However, very localized correlation was evident in duration of AT, particularly in San Diego, where the variance of duration, after accounting for spatial autocorrelation, was 5% smaller within small neighborhoods (approximately 0.01 square latitude/longitude degrees = 0.6 mile diameter) compared to within larger zip code areas. Thus a finer spatial scale of analysis seems to be more appropriate for explaining variation in connectivity and AT. CONCLUSIONS: Joint analysis of the propensity and duration of AT behavior and an explicitly geographic approach can strengthen studies of the built environment and physical activity (PA), specifically AT. More rigorous analytical work on cross-sectional data, such as in the present study, continues to support the need for experimental and longitudinal study designs including the analysis of natural experiments to evaluate the utility of environmental interventions aimed at increasing PA.
| S-EPMC2876088 | biostudies-other
Project description:With the booming economy in China, many researches have pointed out that the improvement of regional transportation infrastructure among other factors had an important effect on economic growth. Utilizing a large-scale dataset which includes 3.5 billion entry and exit records of vehicles along highways generated from toll collection systems, we attempt to establish the relevance of mid-distance land transport patterns to regional economic status through transportation network analyses. We apply standard measurements of complex networks to analyze the highway transportation networks. A set of traffic flow features are computed and correlated to the regional economic development indicator. The multi-linear regression models explain about 89% to 96% of the variation of cities' GDP across three provinces in China. We then fit gravity models using annual traffic volumes of cars, buses, and freight trucks between pairs of cities for each province separately as well as for the whole dataset. We find the temporal changes of distance-decay effects on spatial interactions between cities in transportation networks, which link to the economic development patterns of each province. We conclude that transportation big data reveal the status of regional economic development and contain valuable information of human mobility, production linkages, and logistics for regional management and planning. Our research offers insights into the investigation of regional economic development status using highway transportation big data.
| S-EPMC7021790 | biostudies-literature
Project description:Vehicular emissions have been playing a pivotal role in deteriorating air quality in many urban parts of Nepal causing adverse impacts upon the health of commuters and pedestrians attributed to severe respiratory diseases. Primary data such as the number of vehicles (N) were obtained using two-hour peak (8 am to 10 am) and two-hour nonpeak (1 pm to 3 pm) count, after which average annual vehicle kilometer (VKT) and fuel economy (F) required for emission load estimation were obtained from vehicle survey using the simple random sampling method, sampling size taken statistically under 5% margin of error. Secondary data in this study include emission factors and derived equations from a published article. The vehicular emission load of Bhaktapur Municipality were found to be 3,310 tons/year including CO2, CO, NOx, HC, and PM10 of which CO2 accounts for 94.36% of total emissions followed by CO (4.39%), HC (0.72%), NOx (0.35%), and PM10 (0.18%), respectively. Significant positive correlation was found (r = 0.92, p=0.002) between CO2 and PM10 (r = 0.87, p=0.009), between CO2 and NOx (r = 0.90, p=0.004), between CO and HC (r = 0.74, p=0.05), and between NOx and PM10, respectively. The scenario analysis shows that the introduction of electric vehicles at different rates within the municipality can reduce the emissions to a significant amount. Exponential growth in vehicular gaseous pollutants potent to jeopardize the environment and welfare can become inevitable in the future if clean energy technology is not promoted early.
| S-EPMC7665925 | biostudies-literature
Project description:To compare the prevalence of periodontal disease between two randomly selected population-based studies (the Oral Infections and Vascular Disease Epidemiology Study (INVEST) and the Study of Health in Pomerania (SHIP)) and address relevant methodological issues.Comparison was restricted to 55- to 81-year olds. Attachment loss (AL), probing depth (PD) and tooth count were assessed in INVEST (full-mouth, six sites) and SHIP (half-mouth, four sites). Subjects were classified according to the CDC/AAP case definition. Recording protocols were standardized. Mixed linear or logistic models were used to compare INVEST with SHIP.Mean half-mouth AL was lower in INVEST versus SHIP (INVEST: 2.9 mm versus SHIP: 4.0 mm, p < 0.05). Findings were similar across multiple periodontal disease definitions. After equalization of recording protocols and adjustment for periodontal risk factors, mean AL and PD were 1.2 and 0.3 mm lower in INVEST versus SHIP (p < 0.001). The odds for severe periodontitis (CDC/AAP) was 0.2-fold in INVEST versus SHIP (p < 0.001). Confounding effects of age, gender, race/ethnicity, education and use of interdental care devices were highest as indicated by change-in-estimate for study.Implementation of the proposed method for comparison of epidemiological studies revealed that periodontitis was less prevalent in INVEST compared with SHIP, even after extensive risk-factor adjustment.
| S-EPMC3499632 | biostudies-literature
Project description:Human mobility has been empirically observed to exhibit Lévy flight characteristics and behaviour with power-law distributed jump size. The fundamental mechanisms behind this behaviour has not yet been fully explained. In this paper, we propose to explain the Lévy walk behaviour observed in human mobility patterns by decomposing them into different classes according to the different transportation modes, such as Walk/Run, Bike, Train/Subway or Car/Taxi/Bus. Our analysis is based on two real-life GPS datasets containing approximately 10 and 20 million GPS samples with transportation mode information. We show that human mobility can be modelled as a mixture of different transportation modes, and that these single movement patterns can be approximated by a lognormal distribution rather than a power-law distribution. Then, we demonstrate that the mixture of the decomposed lognormal flight distributions associated with each modality is a power-law distribution, providing an explanation to the emergence of Lévy Walk patterns that characterize human mobility patterns.
| S-EPMC5375979 | biostudies-literature
Project description:BackgroundThere is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation.MethodsSelf-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008.ResultsGeographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC.ConclusionsThe use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.
| S-EPMC2739375 | biostudies-literature
Project description:Active transportation to school (ATS) is a recognized way to increase physical activity (PA). However, girls and young women do not regularly use ATS despite the many documented physical, mental, and community health benefits. Social Marketing (SM) may provide a framework for understanding girls' perspectives of and experience with ATS and inform messages for use in a public health marketing campaign. Focus groups with 79 girls between the ages of 7 and 15 were conducted in Spring 2017 in Victoria, Canada. Transcripts and poster data were initially categorized using the '4Ps' from social marking (Product, Price, Place and Promotion). Participant groups were segmented into three age categories for designing tailored messaging. Thematic analysis revealed elementary school aged participants identified health and fun while middle school participants valued socializing and helping the environment as reasons for engaging in ATS. For secondary school students, ATS was seen as a way to become more independent. All three highlighted fun and enjoyment as important benefits of ATS, and suggested positive and lighthearted messaging. Segmenting into different audiences highlighted how campaign segmentation would resonate with different audiences based on core values and beliefs. Further segmentation of the audience could result in different core values and beliefs held by diverse groups.
| S-EPMC6383329 | biostudies-literature