An accurate estimate of resource use by an animal can be summarized by regressing local- and land... more An accurate estimate of resource use by an animal can be summarized by regressing local- and landscape- level resources on an individual animal's or population's utilization distribution (UD) in a spatially explicit way. The resulting equation is termed a Resource Utilization Function and the regression coefficients indicate the intensity, direction, and consistency of resource use. However, using the UD as
This study examined the correlates of injury severity using police records of pedestrian-motor-ve... more This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increased the risk of injury or death. No other road or neighborhood environment variable remained significant, suggesting that pedestrians were not safer in areas with high pedestrian activity.
Studies have tried to link obesity rates and physical activity with multiple aspects of the built... more Studies have tried to link obesity rates and physical activity with multiple aspects of the built environment. To determine the relation between residential property values and multiple perceived (self-reported) measures of the obesogenic environment. The Seattle Obesity Study (SOS) used a telephone survey of a representative, geographically distributed sample of 2,001 King County adults, collected in 2008-2009 and analyzed in 2012-2013. Home addresses were geocoded. Residential property values at the tax parcel level were obtained from the King County tax assessor. Mean residential property values within a 10-minute walk (833-m buffer) were calculated for each respondent. Data on multiple perceived measures of the obesogenic environment were collected by self-report. Correlations and multivariable linear regression analyses, stratified by residential density, were used to examine the associations among perceived environmental measures, property values, and BMI. Perceived measures o...
This individual-level case control study analyzed the risk of occurrence of a pedestrian–motor ve... more This individual-level case control study analyzed the risk of occurrence of a pedestrian–motor vehicle collision at a given location on a state route in King County, Washington. With the full sample of collisions (1999–2004), binomial logit models estimated the odds of collision occurrence as related to the road and the neighborhood environments and adjusting for exposure. Separate models were run
The role of the built environment on walking in rural United States (U.S.) locations is not well ... more The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly…
This study developed and tested an algorithm to classify accelerometer data as walking or nonwalk... more This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean ± SD duration of PA bouts classified as walking was 15.2 ± 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
This study examined the correlates of injury severity using police records of pedestrian-motor-ve... more This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increased the risk of injury or death. No other road or neighborhood environment variable remained significant, suggesting that pedestrians were not safer in areas with high pedestrian activity.
International Journal of Environmental Research and Public Health, 2016
Walking is the most popular choice of aerobic physical activity to improve health among U.S. adul... more Walking is the most popular choice of aerobic physical activity to improve health among U.S. adults. Physical characteristics of the home neighborhood can facilitate or hinder walking. The purpose of this study was to quantify neighborhood walking, using objective methods and to examine the association between counts of walking bouts in the home neighborhood and neighborhood walkability. This was a cross-sectional study of 106 adults who wore accelerometers and GPS devices for two weeks. Walking was quantified within 1, 2, and 3 km Euclidean (straight-line) and network buffers around the geocoded home location. Walkability was estimated using a commercially available index. Walking bout counts increased with buffer size and were associated with walkability, regardless of buffer type or size (p < 0.001). Quantification of walking bouts within (and outside) of pre-defined neighborhood buffers of different sizes and types allowed for the specification of walking locations to better describe and elucidate walking behaviors. These data support the concept that neighborhood characteristics can influence walking among adults.
An accurate estimate of resource use by an animal can be summarized by regressing local- and land... more An accurate estimate of resource use by an animal can be summarized by regressing local- and landscape- level resources on an individual animal's or population's utilization distribution (UD) in a spatially explicit way. The resulting equation is termed a Resource Utilization Function and the regression coefficients indicate the intensity, direction, and consistency of resource use. However, using the UD as
This study examined the correlates of injury severity using police records of pedestrian-motor-ve... more This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increased the risk of injury or death. No other road or neighborhood environment variable remained significant, suggesting that pedestrians were not safer in areas with high pedestrian activity.
Studies have tried to link obesity rates and physical activity with multiple aspects of the built... more Studies have tried to link obesity rates and physical activity with multiple aspects of the built environment. To determine the relation between residential property values and multiple perceived (self-reported) measures of the obesogenic environment. The Seattle Obesity Study (SOS) used a telephone survey of a representative, geographically distributed sample of 2,001 King County adults, collected in 2008-2009 and analyzed in 2012-2013. Home addresses were geocoded. Residential property values at the tax parcel level were obtained from the King County tax assessor. Mean residential property values within a 10-minute walk (833-m buffer) were calculated for each respondent. Data on multiple perceived measures of the obesogenic environment were collected by self-report. Correlations and multivariable linear regression analyses, stratified by residential density, were used to examine the associations among perceived environmental measures, property values, and BMI. Perceived measures o...
This individual-level case control study analyzed the risk of occurrence of a pedestrian–motor ve... more This individual-level case control study analyzed the risk of occurrence of a pedestrian–motor vehicle collision at a given location on a state route in King County, Washington. With the full sample of collisions (1999–2004), binomial logit models estimated the odds of collision occurrence as related to the road and the neighborhood environments and adjusting for exposure. Separate models were run
The role of the built environment on walking in rural United States (U.S.) locations is not well ... more The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly…
This study developed and tested an algorithm to classify accelerometer data as walking or nonwalk... more This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean ± SD duration of PA bouts classified as walking was 15.2 ± 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
This study examined the correlates of injury severity using police records of pedestrian-motor-ve... more This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increased the risk of injury or death. No other road or neighborhood environment variable remained significant, suggesting that pedestrians were not safer in areas with high pedestrian activity.
International Journal of Environmental Research and Public Health, 2016
Walking is the most popular choice of aerobic physical activity to improve health among U.S. adul... more Walking is the most popular choice of aerobic physical activity to improve health among U.S. adults. Physical characteristics of the home neighborhood can facilitate or hinder walking. The purpose of this study was to quantify neighborhood walking, using objective methods and to examine the association between counts of walking bouts in the home neighborhood and neighborhood walkability. This was a cross-sectional study of 106 adults who wore accelerometers and GPS devices for two weeks. Walking was quantified within 1, 2, and 3 km Euclidean (straight-line) and network buffers around the geocoded home location. Walkability was estimated using a commercially available index. Walking bout counts increased with buffer size and were associated with walkability, regardless of buffer type or size (p < 0.001). Quantification of walking bouts within (and outside) of pre-defined neighborhood buffers of different sizes and types allowed for the specification of walking locations to better describe and elucidate walking behaviors. These data support the concept that neighborhood characteristics can influence walking among adults.
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Papers by Philip Hurvitz