Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.

The maps in this chartbook describe the physical activity environment in Camden in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.

• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of Camden and for a 1 mile buffer area around Camden.

• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.

• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.

• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.

• Crime rates in Camden are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.

The maps in this chartbook describe the physical activity environment in New Brunswick in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.

• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of New Brunswick and for a 1 mile buffer area around New Brunswick.

• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.

• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.

• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.

• Crime rates in New Brunswick are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.

The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.

Effective interventions for addressing childhood obesity require community specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.

Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy Kids and the five communities to address these information needs. The main components of the study include:

• A household survey of 1700 families with 3 -18 year old children

• De-identified heights and weights data from public school districts

• Assessment of the food and physical activity environments using objective data

Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.

Recently the domestic aviation industry has been influenced by rapidly growing ultra low-cost carriers (ULCCs). The pattern of airport markets served by ULCCs is incongruous with legacy carriers and low-cost airlines alike. Existing literature, however, is limited for North American ULCCs: research has only recently begun to identify them separately from mainstream low-cost carriers. This study sought to understand the market factors that influence ULCC service decisions. The relationship between ULCC operations and airport market factors was analyzed using three methods: mapping 2019 flight data for four ULCCs combined, two regression analyses to evaluate variables, and three case studies examining distinct scenarios through interviews with airport managers. Enplanement data were assembled for every domestic airport offering scheduled service in 2019. Independent variables were collected for each Part 139 airport. The first model estimated an ordinary least squares regression model to analyze ULCC enplanements. The second model estimated a binary logistic equation for presence of ULCC service. Case studies for Bellingham, Waco, and Lincoln were selected using compelling airport factors and relevant ULCC experience. Maps of ULCC enplanements revealed concentrations of operations on the East Coast. Both regression analyses showed strong relationships between population and non-ULCC enplanements (two measures of airport market size) and ULCC operations. A significant relationship also existed between tourism and enplanements. In the logit model, distance and competition variables were associated with ULCC presence. Case studies emphasized the importance of airport fees and competition in ULCC preferences, although aeronautical costs were generally not significant in the regressions.

The maps in this chartbook describe the physical activity environment in Vineland in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.

• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of Vineland and for a 1 mile buffer area around Vineland.

• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.

• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.

• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.

• Crime rates in Vineland are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.

The maps in this chartbook describe the physical activity environment in Newark in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.

• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of Newark and for a 1 mile buffer area around Newark.

• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.

• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.

• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.

• Crime rates in Newark are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.

The maps in this chartbook describe the physical activity environment in Trenton in terms of geographic distribution of parks and physical activity facilities. Research shows that people who have access to these facilities are more likely to be physically active.

• The maps in this chartbook were created using physical activity facilities data from a commercial database (lnfoUSA, 2008), data from city departments, as well as information obtained from systematic web searches. The maps present data for the city of Trenton and for a 1 mile buffer area around Trenton.

• Physical activity centers include private and public facilities which offer physical activity opportunities for children 3-18 years of age.

• Physical activity environment maps are compared with Census 2000 data to visualize accessibility of physical activity opportunities in neighborhoods with different characteristics.

• Poverty level presented in this chartbook are based on the 2000 Federal Poverty Guidelines.

• Crime rates in Trenton are presented at the census block group level as relative crime risk (CrimeRisk) obtained from a commercial data source (Applied Geographic Solutions, 2008). CrimeRisk - an index value derived from modeling the relationship between crime rates and demographics data - is expressed as the risk of crime occurring in a specific block group relative to the national average. For this chartbook, data on total CrimeRisk, which includes personal and property crimes, are reported.

Background

Few children accumulate the recommended ≥60 minutes of physical activity each day. Active travel to and from school (ATS) is a potential source of increased activity for children, accounting for 22% of total trips and time spent traveling by school-aged children.

Purpose

This study identifies the association of parents’ perceptions of the neighborhood, geospatial variables, and demographic characteristics with ATS among students in four low-income, densely populated urban communities with predominantly minority populations.

Methods

Data were collected in 2009–2010 from households with school-attending children in four low-income New Jersey cities. Multivariate logistic regression analyses (n=765) identified predictors of ATS. Analyses were conducted in 2012.

Results

In all, 54% of students actively commuted to school. Students whose parents perceived the neighborhood as very unpleasant for activity were less likely (OR=0.39) to actively commute, as were students living farther from school, with a 6% reduction in ATS for every 0.10 mile increase in distance to school. Perceptions of crime, traffic, and sidewalk conditions were not predictors of ATS.

Conclusions

Parents’ perceptions of the pleasantness of the neighborhood, independent of the effects of distance from school, may outweigh concerns about crime, traffic, or conditions of sidewalks in predicting active commuting to school in the low-income urban communities studied. Efforts such as cleaning up graffiti, taking care of abandoned buildings, and providing shade trees to improve neighborhood environments are likely to increase ATS, as are efforts that encourage locating schools closer to the populations they serve.