Is a land use regression model capable of predicting the cleanest route to school?

Land Use Regression (LUR) modeling is a widely used technique to model the spatial variability of air pollutants in epidemiology. In this study, we explore whether a LUR model can predict home-to-school commuting exposure to black carbon (BC). During January and February 2019, 43 children walking to school were involved in a personal monitoring campaign measuring exposure to BC and tracking their home-to-school routes. At the same time, a previously developed LUR model for the study area was applied to estimate BC exposure on points along the route. Personal BC exposure varied widely with mean \ub1 SD of 9003 \ub1 4864 ng/m3. The comparison between the two methods showed good agreement (Pearson\u2019s r = 0.74, Lin\u2019s Concordance Correlation Coefficient = 0.6), suggesting that LUR estimates are capable of catching differences among routes and predicting the cleanest route. However, the model tends to underestimate absolute concentrations by 29% on average. A LUR model can be useful in predicting personal exposure and can help urban planners in Milan to build a healthier city for schoolchildren by promoting less polluted home-to-school routes

Cycling exposure and infrastructural correlates in a Flemish adolescent population

Introduction: Infrastructure adjusted to cyclists can be used as a tool to reduce cycling crashes and injuries. To increase cycling frequency and safety, a population's cycling exposure to different infrastructure needs to be known. Since cycling behavior of adolescents cannot be compared to adults, the objective of this study is to describe the cycling exposure and the characteristics of routes used by adolescents for bicycle commuting. Methods: We used an online travel diary to collect bicycle route information and an exposure matrix to collect cycling frequency data. Data were collected in Flanders (Belgium) from an adolescent population (15-18 years). Results: From the 1345 participating adolescents, 47% used their bicycle at least once a week. Infrastructural correlates were based on 467,000 km of cycled roads with a mean trip distance of 5.7 +/- 4.5 km; 91% of cycling exposure is on infrastructure with speed limits of 50 km/h or more and 32.7% on dedicated cycle lanes. Lower motorized traffic density was related to higher odds of daily bicycle commuting. Higher traffic densities or speed limits were related to lower odds of daily bicycle commuting, but this relationship disappeared after adjusting for presence of a dedicated cycle lane. Conclusions: Many adolescents who commute by bicycle cycle along streets with high speed limits and no dedicated cycle lanes probably because of the low motorized traffic densities on these roads. Adolescents should avoid roads without dedicated cycling infrastructure and high speed limits since these roads have been identified as high risk. The results are region specific and therefore this study should be replicated in other contexts

Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study.

BACKGROUND: In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health. METHODS: Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively. RESULTS: Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802). CONCLUSIONS: Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility

The importance of sedimenting organic matter, relative to oxygen and temperature, in structuring lake profundal macroinvertebrate assemblages

We quantified the role of a main food resource, sedimenting organic matter (SOM), relative to oxygen (DO) and temperature (TEMP) in structuring profundal macroinvertebrate assemblages in boreal lakes. SOM from 26 basins of 11 Finnish lakes was analysed for quantity (sedimentation rates), quality (C:N:P stoichiometry) and origin (carbon stable isotopes, d13C). Hypolimnetic oxygen and temperature were measured from each site during summer stratification. Partial canonical correspondence analysis (CCA) and partial regression analyses were used to quantify contributions of SOM, DO and TEMP to community composition and three macroinvertebrate metrics. The results suggested a major contribution of SOM in regulating the community composition and total biomass. Oxygen best explained the Shannon diversity, whereas TEMP had largest contribution to the variation of Benthic Quality Index. Community composition was most strongly related to d13C of SOM. Based on additional d13C and stoichiometric analyses of chironomid taxa, marked differences were apparent in their utilization of SOM and body stoichiometry; taxa characteristic of oligotrophic conditions exhibited higher C:N ratios and lower C:P and N:P ratios compared to the species typical of eutrophic lakes. The results highlight the role of SOM in regulating benthic communities and the distributions of individual species, particularly in oligotrophic systems

Evaluation of Different Recruitment Methods: Longitudinal, Web-Based, Pan-European Physical Activity Through Sustainable Transport Approaches (PASTA) Project

BACKGROUND: Sufficient sample size and minimal sample bias are core requirements for empirical data analyses. Combining opportunistic recruitment with a Web-based survey and data-collection platform yields new benefits over traditional recruitment approaches. OBJECTIVE: This paper aims to report the success of different recruitment methods and obtain data on participants' characteristics, participation behavior, recruitment rates, and representativeness of the sample. METHODS: A longitudinal, Web-based survey was implemented as part of the European PASTA (Physical Activity through Sustainable Transport Approaches) project, between November 2014 and December 2016. During this period, participants were recruited from 7 European cities on a rolling basis. A standardized guide on recruitment strategy was developed for all cities, to reach a sufficient number of adult participants. To make use of the strengths and minimize weakness, a combination of different opportunistic recruitment methods was applied. In addition, the random sampling approach was applied in the city of Örebro. To reduce the attrition rate and improve real-time monitoring, the Web-based platform featured a participant's and a researchers' user interface and dashboard. RESULTS: Overall, 10,691 participants were recruited; most people found out about the survey through their workplace or employer (2300/10691, 21.51%), outreach promotion (2219/10691, 20.76%), and social media (1859/10691, 17.39%). The average number of questionnaires filled in per participant varied significantly between the cities (P<.001), with the highest number in Zurich (11.0, SE 0.33) and the lowest in Örebro (4.8, SE 0.17). Collaboration with local organizations, the use of Facebook and mailing lists, and direct street recruitment were the most effective approaches in reaching a high share of participants (P<.001). Considering the invested working hours, Facebook was one of the most time-efficient methods. Compared with the cities' census data, the composition of study participants was broadly representative in terms of gender distribution; however, the study included younger and better-educated participants. CONCLUSIONS: We observed that offering a mixed recruitment approach was highly effective in achieving a high participation rate. The highest attrition rate and the lowest average number of questionnaires filled in per participant were observed in Örebro, which also recruited participants through random sampling. These findings suggest that people who are more interested in the topic are more willing to participate and stay in a survey than those who are selected randomly and may not have a strong connection to the research topic. Although direct face-to-face contacts were very effective with respect to the number of recruited participants, recruiting people through social media was not only effective but also very time efficient. The collected data are based on one of the largest recruited longitudinal samples with a common recruitment strategy in different European cities