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.

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: Understanding determinants of high consumption of sugar-sweetened beverages (SSBs), a highly prevalent obesogenic behavior, will help build effective customized public health interventions.

Objective: Our aim was to identify child and parent lifestyle and household demographic factors predictive of high SSB consumption frequency in children from low-income, ethnically diverse communities that may help inform public health interventions.

Design: We used a cross-sectional telephone household survey.

Participants/setting: Participants were 717 boys and 686 girls aged 3 to 18 years old from the New Jersey Childhood Obesity Study living in five low-income cities (Camden, New Brunswick, Newark, Trenton, and Vineland). The adult most knowledgeable about household food shopping completed a questionnaire over the telephone inquiring about their and their child's dietary and physical activity habits, and household-, parent-, and child-level demographics.

Main outcome measures: Child's SSB consumption frequency was measured.

Statistical analysis performed: Multivariate ordered logit models were designed to investigate a variety of variables hypothesized to affect the frequency of SSB consumption. Exploratory stratified analyses by race, sex, and age were also conducted.

Results: Eight percent of our study participants never consumed SSBs, 45% consumed SSBs at least once per day, and 23% consumed twice or more per day. SSB consumption was higher among children 12 to 18 years vs 3 to 5 years (P<0.0001), of non-Hispanic black vs non-Hispanic white race/ethnicity (P=0.010), who were moderate fast food consumers vs never consumers (P=0.003), and those whose parents were high vs low SSB consumers (P<0.0001). Living in a non-English-speaking household (P=0.030), having a parent with a college or higher education vs less than high school (P=0.003), and having breakfast 6 to 7 days/wk vs never to 2 days/wk or less were associated with lower SSB consumption (P=0.001).

Conclusions: We identified a number of household-, parent-, and child-level predictors of SSB consumption, which varied by race, sex, and age, useful for building customized interventions targeting certain behaviors in ethnically diverse, low-income children.

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.