Dr Benjamin Chrisinger | Department of Social Policy and Intervention

Dr Benjamin Chrisinger is an urban planner by training. He conducts interdisciplinary research on the relationships between place and health, especially health disparities, and the role that place-based policies can improve health equity. His latest work focuses on relationships between individuals' neighborhood perceptions and health disparities, as well as the lasting legacies of historical events or policies. He is also engaged with using new technologies and community-engaged methods in his research.

Dr Chrisinger completed his PhD in City and Regional Planning at the University of Pennsylvania, and Masters and Bachelors degrees in Urban and Environmental Planning at the University of Virginia. Prior to joining the Department, Dr Chrisinger was a postdoctoral research fellow with the Stanford Prevention Research Center, a division of the Stanford University School of Medicine that specializes in behavioral research and interventions, including those at the community level.

Research

Dr Chrisinger’s interdisciplinary research spans three primary areas of inquiry:

1) How do individuals navigate different places to access different resources?;

2) How do neighborhood perceptions influence behavior?; and

3) How is community development related to health inequality?

His early work related to access examined policies and programs in the United States to open supermarkets in underserved areas ("food deserts") by considering development processes, store-level outcomes, and community and customer experiences. Through both quantitative and qualitative research on food access, Dr Chrisinger has found the influence of individual perceptions to feature prominently, which raises ciritcal questions about how one’s perceptions of resources (e.g., a particular supermarket) and the contexts around them (e.g., built and social environments around it), also influence individual behavior. In a recent project, Stress Experiences in Neighborhood and Social Environments (SENSE), he developed new protocols for using physiological data to map and contextualize understand individuals' neighborhood perceptions in different kinds of urban environments. Related to community development, Dr Chrisinger is interested in how we might inform and improve place-based policy evaluations and interventions by better understanding the histories of segregation and displacement that may underlie the places we study.

As part of his involvement with the Planners of Color Interest Group in the American Collegiate Schools of Planning, Dr Chrisinger also actively participates in research on the training of urban planners, especially those with backgrounds historically excluded from or under-represented in the profession.

Publications

Understanding Where We Are Well: Neighborhood-Level Social and Environmental Correlates of Well-Being in the Stanford Well for Life Study.

2019
|
Journal article
|
Int J Environ Res Public Health

Individual well-being is a complex concept that varies among and between individuals and is impacted by individual, interpersonal, community, organizational, policy and environmental factors. This research explored associations between select environmental characteristics measured at the ZIP code level and individual well-being. Participants (n = 3288, mean age = 41.4 years, 71.0% female, 57.9% white) were drawn from a registry of individuals who completed the Stanford WELL for Life Scale (SWLS), a 76-question online survey that asks about 10 domains of well-being: social connectedness, lifestyle and daily practices, physical health, stress and resilience, emotional and mental health, purpose and meaning, sense of self, financial security and satisfaction, spirituality and religiosity, and exploration and creativity. Based on a nationally-representative 2018 study of associations between an independent well-being measure and county-level characteristics, we selected twelve identical or analogous neighborhood (ZIP-code level) indicators to test against the SWLS measure and its ten constituent domains. Data were collected from secondary sources to describe socio-economic (median household income, percent unemployment, percent child poverty), demographic (race/ethnicity), and physical environment (commute by bicycle and public transit), and healthcare (number of healthcare facilities, percent mammogram screenings, percent preventable hospital stays). All continuous neighborhood factors were re-classified into quantile groups. Linear mixed models were fit to assess relationships between each neighborhood measure and each of the ten domains of well-being, as well as the overall SWLS well-being measure, and were adjusted for spatial autocorrelation and individual-level covariates. In models exploring associations between the overall SWLS score and neighborhood characteristics, six of the twelve neighborhood factors exhibited significant differences between quantile groups (p < 0.05). All of the ten SWLS domains had at least one instance of significant (p < 0.05) variation across quantile groups for a neighborhood factor; stress and resilience, emotional and mental health, and financial security had the greatest number of significant associations (6/12 factors), followed by physical health (5/12 factors) and social connectedness (4/12 factors). All but one of the neighborhood factors (number of Federally Qualified Health Centers) showed at least one significant association with a well-being domain. Among the neighborhood factors with the most associations with well-being domains were rate of preventable hospital stays (7/10 domains), percent holding bachelor's degrees (6/10 domains), and median income and percent with less than high school completion (5/10 domains). These observational insights suggest that neighborhood factors are associated with individuals' overall self-rated well-being, though variation exists among its constituent domains. Further research that employs such multi-dimensional measures of well-being is needed to determine targets for intervention at the neighborhood level that may improve well-being at both the individual and, ultimately, neighborhood levels.

geography, neighborhoods, social determinants of health, spatial analysis, well-being, wellness, Adolescent, Adult, Aged, Child, Environment, Ethnic Groups, Female, Humans, Income, Male, Middle Aged, Personal Satisfaction, Poverty, Residence Characteristics, Social Determinants of Health, Socioeconomic Factors, Spatial Analysis, Surveys and Questionnaires, Transportation, Young Adult
“If you Build it with them, they will come”: What makes a supermarket intervention successful in a food desert?

2019
|
Journal article
|
Journal of Public Affairs
Maximizing the promise of citizen science to advance health and prevent disease.

2019
|
Journal article
|
Prev Med

Built environment, Citizen science, Community engagement, Population health
How Well Do Seniors Estimate Distance to Food? The Accuracy of Older Adults’ Reported Proximity to Local Grocery Stores

2019
|
Journal article
|
Geriatrics

<jats:p>(1) Background: Findings from observational studies of relations between neighborhood environments and health outcomes underscore the importance of both objective and perceived experiences of those environments. A clearer understanding of the factors associated with discrepancies between these two assessment approaches is needed to tailor public health interventions to specific populations. This study examined how individual and neighborhood characteristics affect perceptions of supermarket distance, particularly when perceptions do not match objective measures. (2) Methods: Participants were older adults (n = 880) participating in the Senior Neighborhood Quality of Life Study in the Seattle/King County, WA or Baltimore/Washington, DC regions. Two main analyses were conducted. The primary outcome for Analysis I was participants’ geographic information systems (GIS)-based objective network distance to the closest supermarket. Generalized linear mixed models with block group-level random effects were used to assess associations between objective supermarket distance and individual/neighborhood characteristics. The primary outcome for Analysis II was a categorical “accuracy” variable, based on participants’ perceived distance to the nearest supermarket/grocery store relative to the objective distance, assuming a walking speed of 1.0 m/s. Multivariate log-linear models fit neural networks were used to assess influential covariates. (3) Results: Several significant associations with objective distance to the nearest supermarket were observed, including a negative relationship with body mass index (BMI) (95% CI = −45.56, −0.23), having walked to the supermarket in the last 30 days (−174.86, −59.42), living in a high-walkability neighborhood, and residing in Seattle/King County (−707.69, −353.22). In terms of participants’ distance accuracy, 29% were classified as accurate, 33.9% were “Underestimators”, 24.0% “Overestimators”, and 13.2% responded “Don’t Know”. Compared to Accurate participants, Overestimators were significantly less likely to have walked to the supermarket in the last 30 days, and lived objectively closer to a supermarket; Underestimators perceived significantly higher pedestrian safety and lived objectively further from a supermarket; and Don’t Know were more likely to be women, older, not living independently, and not having recently walked to the supermarket. (4) Conclusions: Both modifiable and nonmodifiable factors influence the accuracy of older adults’ perceptions of their proximity to the nearest supermarket. Recent experience in walking to the closest supermarket, along with personal safety, represent potentially modifiable perceived environmental factors that were related to older adults’ accuracy of perceptions of their neighborhood food environment.</jats:p>
All Talk No Walk: Student Perceptions on Integration of Diversity and Practice in Planning Programs

2018
|
Journal article
|
Planning Practice & Research
Where Are We Going? Where Have We Been?: The Climate for Diversity within Urban Planning Educational Programs

2018
|
Journal article
|
Journal of Planning Education and Research
Diet Quality Over the Monthly Supplemental Nutrition Assistance Program Cycle.

2018
|
Journal article
|
Am J Prev Med

INTRODUCTION: Supplemental Nutrition Assistance Program (SNAP) benefits, which are distributed monthly, help low-income families put food on their tables. Both food spending and caloric intake among recipients decrease over the month following benefit receipt. This pattern, termed the "SNAP-cycle," has serious implications for health and food security of low-income households. To understand better the SNAP-cycle, this study explored (1) differences in diet quality between SNAP and non-SNAP households and (2) the association between the SNAP-cycle and diet quality. METHODS: Multivariate linear regression with SNAP households in the U.S. Department of Agriculture's Food Acquisition and Purchase Survey to evaluate changes in diet quality as time from SNAP distribution increased. Diet quality of food purchases was measured by Healthy Eating Index-2010 total and component scores. Data were collected 2012-2013 and analyzed 2016-2017. RESULTS: Overall dietary quality was low throughout the SNAP-cycle (n=1,377, mean Healthy Eating Index 46.14 of 100). SNAP households had significantly lower Healthy Eating Index scores compared with eligible and ineligible nonparticipants (p<0.05). After controlling for covariates, households in the final 10 days of the benefit cycle had Healthy Eating Index-2010 total scores 2.95 points lower than all other SNAP households (p=0.02). Significant declines in Healthy Eating Index fruit and vegetable scores contributed to worsening diet quality over the SNAP-cycle. CONCLUSIONS: This study provides evidence of low dietary quality throughout the SNAP-cycle with significantly lower Healthy Eating Index scores in the final 10 days of the benefit month. This suggests less healthy purchasing occurs when resources are diminished, but overall that current SNAP levels are insufficient to consistently purchase foods according to dietary guidelines.

Adolescent, Adult, Diet, Energy Intake, Family Characteristics, Food Assistance, Humans, Middle Aged, Nutrition Policy, Nutrition Surveys, Poverty, Young Adult
Where do U.S. households purchase healthy foods? An analysis of food-at-home purchases across different types of retailers in a nationally representative dataset.

2018
|
Journal article
|
Prev Med

Food shopping decisions are pathways between food environment, diet and health outcomes, including chronic diseases such as diabetes and obesity. The choices of where to shop and what to buy are interrelated, though a better understanding of this dynamic is needed. The U.S. Department of Agriculture's nationally representative Food Acquisitions and Purchase Survey food-at-home dataset was joined with other databases of retailer characteristics and Healthy Eating Index-2010 (HEI) of purchases. We used linear regression models with general estimating equations to assess relationships between trip, store, and shopper characteristics with trip HEI scores. We examined HEI component scores for conventional supermarkets and discount/limited assortment retailers with descriptive statistics. Overall, 4962 shoppers made 11,472 shopping trips over one-week periods, 2012-2013. Trips to conventional supermarkets were the most common (53.6%), followed by supercenters (18.6%). Compared to conventional supermarkets, purchases at natural/gourmet stores had significantly higher HEI scores (β = 6.48, 95% CI = [4.45, 8.51], while those from "other" retailers (including corner and convenience stores) were significantly lower (-3.89, [-5.87, -1.92]). Older participants (versus younger) and women (versus men) made significantly healthier purchases (1.19, [0.29, 2.10]). Shoppers with less than some college education made significantly less-healthy purchases, versus shoppers with more education, as did households participating in SNAP, versus those with incomes above 185% of the Federal Poverty Level. Individual, trip, and store characteristics influenced the healthfulness of foods purchased. Interventions to encourage healthy purchasing should reflect these dynamics in terms of how, where, and for whom they are implemented.

Diet, Food access, Food choice, Food environment, Food shopping, FoodAPS, Nutrition, SNAP, Store choice, Adult, Choice Behavior, Commerce, Consumer Behavior, Databases, Factual, Diet, Healthy, Family Characteristics, Female, Food Supply, Humans, Male, Middle Aged, Residence Characteristics, Socioeconomic Factors, United States
Stress experiences in neighborhood and social environments (SENSE): a pilot study to integrate the quantified self with citizen science to improve the built environment and health.

2018
|
Journal article
|
Int J Health Geogr

BACKGROUND: Identifying elements of one's environment-observable and unobservable-that contribute to chronic stress including the perception of comfort and discomfort associated with different settings, presents many methodological and analytical challenges. However, it also presents an opportunity to engage the public in collecting and analyzing their own geospatial and biometric data to increase community member understanding of their local environments and activate potential environmental improvements. In this first-generation project, we developed a methodology to integrate geospatial technology with biometric sensing within a previously developed, evidence-based "citizen science" protocol, called "Our Voice." Participants used a smartphone/tablet-based application, called the Discovery Tool (DT), to collect photos and audio narratives about elements of the built environment that contributed to or detracted from their well-being. A wrist-worn sensor (Empatica E4) was used to collect time-stamped data, including 3-axis accelerometry, skin temperature, blood volume pressure, heart rate, heartbeat inter-beat interval, and electrodermal activity (EDA). Open-source R packages were employed to automatically organize, clean, geocode, and visualize the biometric data. RESULTS: In total, 14 adults (8 women, 6 men) were successfully recruited to participate in the investigation. Participants recorded 174 images and 124 audio files with the DT. Among captured images with a participant-determined positive or negative rating (n = 131), over half were positive (58.8%, n = 77). Within-participant positive/negative rating ratios were similar, with most participants rating 53.0% of their images as positive (SD 21.4%). Significant spatial clusters of positive and negative photos were identified using the Getis-Ord Gi* local statistic, and significant associations between participant EDA and distance to DT photos, and street and land use characteristics were also observed with linear mixed models. Interactive data maps allowed participants to (1) reflect on data collected during the neighborhood walk, (2) see how EDA levels changed over the course of the walk in relation to objective neighborhood features (using basemap and DT app photos), and (3) compare their data to other participants along the same route. CONCLUSIONS: Participants identified a variety of social and environmental features that contributed to or detracted from their well-being. This initial investigation sets the stage for further research combining qualitative and quantitative data capture and interpretation to identify objective and perceived elements of the built environment influence our embodied experience in different settings. It provides a systematic process for simultaneously collecting multiple kinds of data, and lays a foundation for future statistical and spatial analyses in addition to more in-depth interpretation of how these responses vary within and between individuals.

Allostatic load, Built environment, Chronic stress, Citizen science, Electrodermal activity, Leaflet, Quantified self, Sensors, Accelerometry, Adult, Biometry, Built Environment, Environment Design, Feasibility Studies, Female, Health Status, Humans, Male, Pilot Projects, Residence Characteristics, Social Environment, Stress, Psychological, Walking
Family food purchases of high- and low-calorie foods in full-service supermarkets and other food retailers by Black women in an urban US setting.

2018
|
Journal article
|
Prev Med Rep

Public health interventions to increase supermarket access assume that shopping in supermarkets is associated with healthier food purchases compared to other store types. To test this assumption, we compared purchasing patterns by store-type for certain higher-calorie, less healthy foods (HCF) and lower-calorie, healthier foods (LCF) in a sample of 35 black women household shoppers in Philadelphia, PA. Data analyzed were from 450 food shopping receipts collected by these shoppers over four-week periods in 2012. We compared the likelihood of purchasing the HCF (sugar-sweetened beverages, sweet/salty snacks, and grain-based snacks) and LCF (low-fat dairy, fruits, and vegetables) at full-service supermarkets and six other types of food retailers, using generalized estimating equations. Thirty-seven percent of participants had household incomes at or below the poverty line, and 54% had a BMI >30. Participants shopped primarily at full-service supermarkets (55%) or discount/limited assortment supermarkets (22%), making an average of 11 shopping trips over a 4-week period and spending mean (SD) of $350 ($222). Of full-service supermarket receipts, 64% included at least one HCF item and 58% at least one LCF. Most trips including HCF (58%) and LCF (60%) expenditures were to full-service or discount/limited assortment supermarkets rather than smaller stores. Spending a greater percent of total dollars in full-service supermarkets was associated with spending more on HCF (p = 0.03) but not LCF items (p = 0.26). These findings in black women suggest a need for more attention to supermarket interventions that change retailing practices and/or consumer shopping behaviors related to foods in the HCF categories examined.

African Americans, Food choice, Food shopping, Obesity, Store choice, Supermarkets
Leveraging Citizen Science for Healthier Food Environments: A Pilot Study to Evaluate Corner Stores in Camden, New Jersey.

2018
|
Journal article
|
Front Public Health

Over the last 6 years, a coordinated "healthy corner store" network has helped an increasing number of local storeowners stock healthy, affordable foods in Camden, New Jersey, a city with high rates of poverty and unemployment, and where most residents have little or no access to large food retailers. The initiative's funders and stakeholders wanted to directly engage Camden residents in evaluating this effort to increase healthy food access. In a departure from traditional survey- or focus group-based evaluations, we used an evidence-based community-engaged citizen science research model (called Our Voice) that has been deployed in a variety of neighborhood settings to assess how different features of the built environment both affect community health and wellbeing, and empower participants to create change. Employing the Our Voice model, participants documented neighborhood features in and around Camden corner stores through geo-located photos and audio narratives. Eight adult participants who lived and/or worked in a predefined neighborhood of Camden were recruited by convenience sample and visited two corner stores participating in the healthy corner store initiative (one highly-engaged in the initiative and the other less-engaged), as well as an optional third corner store of their choosing. Facilitators then helped participants use their collected data (in total, 134 images and 96 audio recordings) to identify and prioritize issues as a group, and brainstorm and advocate for potential solutions. Three priority themes were selected by participants from the full theme list (n = 9) based on perceived importance and feasibility: healthy product selection and display, store environment, and store outdoor appearance and cleanliness. Participants devised and presented a set of action steps to community leaders, and stakeholders have begun to incorporate these ideas into plans for the future of the healthy corner store network. Key elements of healthy corner stores were identified as positive, and other priorities, such as improvements to safety, exterior facades, and physical accessibility, may find common ground with other community development initiatives in Camden. Ultimately, this pilot study demonstrated the potential of citizen science to provide a systematic and data-driven process for public health stakeholders to authentically engage community residents in program evaluation.

citizen science, community engagement, empowerment, food access, food deserts, healthy corner stores, program evaluation
Interdisciplinary food-related academic programs: A 2015 snapshot of the United States landscape.

2017
|
Journal article
|
Journal of agriculture, food systems, and community development

Interdisciplinary food-related research and study is a growing field in academia. Each year, more universities add departments, courses, majors, and minors focused on studying food and society and the complexities of growing, processing, distributing, accessing, and consuming food. In this commentary, we present our exploratory findings about interdisciplinary food-related academic programs, including food studies and food systems programs in the United States. This cross-sectional research developed a snapshot of the 2015 land-scape of interdisciplinary food-related academic programs, provided a preliminary examination of their educational offerings, and will inform future research opportunities. In this formative study, we found 82 interdisciplinary food-related under-graduate programs focused on food. Nineteen program majors, minors, or concentrations had a core disciplinary focus on sustainable agriculture. "Food studies" and "food systems" were the primary focus of 15 undergraduate programs. We found 58 interdisciplinary food-related graduate programs and extracted information on their course offerings. Organizing courses into nine course categories, 78 percent of the programs offered courses in two to five categories, and 22 percent offered courses in six to eight categories. Few courses integrated material from multiple disciplines into a single course, suggesting that these interdisciplinary programs stemmed from traditional academic silos. Based on this preliminary work, we propose to further investigate the interdisciplinary nature of food-related academic programs, map their growth trajectory, and solicit feedback from faculty and administrators about their challenges in establishing and maintaining these programs. In future research, we are also interested in exploring job options for graduates of food-related academic programs to inform recruitment strategies and courses of study.
Discrete Choice Model of Food Store Trips Using National Household Food Acquisition and Purchase Survey (FoodAPS).

2017
|
Journal article
|
Int J Environ Res Public Health

Where households across income levels shop for food is of central concern within a growing body of research focused on where people live relative to where they shop, what they purchase and eat, and how those choices influence the risk of obesity and chronic disease. We analyzed data from the National Household Food Acquisition and Purchase Survey (FoodAPS) using a conditional logit model to determine where participants shop for food to be prepared and eaten at home and how individual and household characteristics of food shoppers interact with store characteristics and distance from home in determining store choice. Store size, whether or not it was a full-service supermarket, and the driving distance from home to the store constituted the three significant main effects on store choice. Overall, participants were more likely to choose larger stores, conventional supermarkets rather than super-centers and other types of stores, and stores closer to home. Interaction effects show that participants receiving Supplemental Nutrition Assistance Program (SNAP) were even more likely to choose larger stores. Hispanic participants were more likely than non-Hispanics to choose full-service supermarkets while White participants were more likely to travel further than non-Whites. This study demonstrates the value of explicitly spatial discrete choice models and provides evidence of national trends consistent with previous smaller, local studies.

FoodAPS, discrete choice, food retail, food shopping, supermarkets, Adult, Choice Behavior, Commerce, Data Collection, Female, Food Preferences, Food Supply, Humans, Logistic Models, Residence Characteristics, Socioeconomic Factors
Letter Regarding “Improving the Nutritional Impact of the Supplemental Nutrition Assistance Program”

2017
|
Journal article
|
American Journal of Preventive Medicine
Ethical imperatives against item restriction in the Supplemental Nutrition Assistance Program.

2017
|
Journal article
|
Prev Med

The Supplemental Nutrition Assistance Program (SNAP, formerly known as food stamps) is the federal government's largest form of food assistance, and a frequent focus of political and scholarly debate. Previous discourse in the public health community and recent proposals in state legislatures have suggested limiting the use of SNAP benefits on unhealthy food items, such as sugar-sweetened beverages (SSBs). This paper identifies two possible underlying motivations for item restriction, health and morals, and analyzes the level of empirical support for claims about the current state of the program, as well as expectations about how item restriction would change participant outcomes. It also assesses how item restriction would reduce individual agency of low-income individuals, and identifies mechanisms by which this may adversely affect program participants. Finally, this paper offers alternative policies to promote healthier purchasing and eating among SNAP participants that can be pursued without reducing individual agency. Health advocates and officials must more fully weigh the attendant risks of implementing SNAP item restrictions, including the reduction of individual agency of a vulnerable population.

Food assistance, Food choice, Food security, Food shopping, Nutrition, Policy, Sugar-sweetened beverages, Supplemental Nutrition Assistance Program, USDA, Welfare, Food Assistance, Food Supply, Humans, Nutrition Policy, Poverty

Find out more

News

Understanding Where We Are Well: Neighborhood-Level Social and Environmental Correlates of Well-Being in the Stanford Well for Life Study.

“If you Build it with them, they will come”: What makes a supermarket intervention successful in a food desert?

Maximizing the promise of citizen science to advance health and prevent disease.

How Well Do Seniors Estimate Distance to Food? The Accuracy of Older Adults’ Reported Proximity to Local Grocery Stores

All Talk No Walk: Student Perceptions on Integration of Diversity and Practice in Planning Programs

Where Are We Going? Where Have We Been?: The Climate for Diversity within Urban Planning Educational Programs

Diet Quality Over the Monthly Supplemental Nutrition Assistance Program Cycle.

Where do U.S. households purchase healthy foods? An analysis of food-at-home purchases across different types of retailers in a nationally representative dataset.

Stress experiences in neighborhood and social environments (SENSE): a pilot study to integrate the quantified self with citizen science to improve the built environment and health.

Family food purchases of high- and low-calorie foods in full-service supermarkets and other food retailers by Black women in an urban US setting.

Leveraging Citizen Science for Healthier Food Environments: A Pilot Study to Evaluate Corner Stores in Camden, New Jersey.

Interdisciplinary food-related academic programs: A 2015 snapshot of the United States landscape.

Discrete Choice Model of Food Store Trips Using National Household Food Acquisition and Purchase Survey (FoodAPS).

Letter Regarding “Improving the Nutritional Impact of the Supplemental Nutrition Assistance Program”

Ethical imperatives against item restriction in the Supplemental Nutrition Assistance Program.

Dr Benjamin Chrisinger joins DSPI