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Abstract: Canadian national health surveys regularly ask respondents to rate their sense of belonging to their local community. Health studies commonly use this question as a social capital indicator, but what social capital domains community belonging is measuring remains unclear. Analyzing Canadian General Social Survey data, we evaluate the validity of this measure with respect to network-based social capital and health. Results indicate that sense of community belonging is associated positively with several network-based social capital measures. Neighborhood network-based social capital most substantially reduced associations between sense of community belonging and health measures, but results differed by urban and rural settings. These findings indicate the need for public health surveys to include specific measures of respondents'' networks. [Copyright &y& Elsevier]

Background: Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results: Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 µg/m³ to 35 µg/m³ of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion: The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether training in a hyperoxic environment would result in greater increases in VO2max and performance at 90% VO2max as compared with training in normoxia., Methods: In a single blind design nine athletes trained for 6 wk on a cycle ergometer 3 d.wk(-1), 1 h.d(-1) (10 x 4-min intervals, with 2 min of rest between intervals) at 90% HR(max). Training HR range was maintained by adjusting the power output. Subjects were randomly assigned to H (60% O2) or N (21% O2) breathing conditions for training. After 12 wk of detraining, a second 6-wk training protocol was completed with the breathing conditions reversed. VO2max, performance time at 90% VO2max and cardiorespiratory response to a steady-state exercise at 80% VO2max were measured pre- and posttraining. All pre- and posttraining tests were conducted under normoxic conditions., Results: There were no significant differences between pretraining results for any of the parameters. Power output was 8.1% higher while training in H compared with N, to maintain training HR. Both H and N training resulted in increased performance time, with H being greater than N. Although there was a trend for a greater increase in VO2max after H versus N training, this difference was not significant. HR(max) did not change for H or N. HR VE at 80% VO2max decreased posttraining with no differences between H and N., Conclusion: The data showed that a higher power output was required to maintain HR during H training. This increased training intensity during H resulted in improved exercise performance whereas cycling at 90% VO2max in room air and may be due to peripheral factors because cardiorespiratory responses were similar.