US County-Level Variation in Availability and Prevalence of Black Physicians in 1906.

Importance: Black physicians are substantially underrepresented in the US health care workforce, with detrimental effects on the health and health care experiences of Black individuals. These contemporary gaps can be traced to the early days of the medical profession using the first edition of the American Medical Directory (AMD). Objective: To identify state- and county-level patterns related to the training and availability of Black physicians relative to their White counterparts in the 1906 AMD. Design, Setting, and Participants: For this cross-sectional study, data for 41 828 physician entries in 18 US states in or adjacent to the South as well as the District of Columbia were extracted from the 1906 AMD and aggregated to 1570 counties. Data analysis was performed between September 2023 and January 2024. Exposures: County-level exposure variables included population density, racial composition, and illiteracy rate among US-born White residents as well as an index of terrain ruggedness and the number of lynchings in the previous decade. Median values of physicians' distance from place of practice to place of medical training (by race of physician) were also used as an exposure variable. Main Outcomes and Measures: There were 4 county-level outcomes: (1) presence of any Black physician, (2) proportion of Black physicians per Black population, (3) proportion of White physicians per White population, and (4) community representativeness (reported as the community representativeness ratio). The cross-sectional analysis used generalized additive mixed models with state-level random effects. Results: Across 1570 counties, Black physicians comprised 746 (1.8%) of the 41 828 physicians in the dataset. Black physicians tended to train further from their place of practice than their White counterparts. The proportion of Black physicians per 1000 Black residents was 0.08 compared with 1.62 for White physicians; these proportions varied substantially by state. At the county level, the presence of any Black physician was associated with percentage Black population (odds ratio [OR], 28.94 [95% CI, 9.77 to 85.76]; P ≤ .001), population density (OR, 2.63 [95% CI, 2.03 to 3.40]; P ≤ .001), and distance to the nearest Black medical school (OR, 0.62 [95% CI, 0.42 to 0.92]; P = .02). Conclusions and Relevance: A variety of structural disadvantages are illustrated in this cross-sectional study of county-level sociodemographic and geographic characteristics associated with the prevalence of Black physicians in the earliest days of the profession. To demonstrate its broader utility for health disparities research, the dataset has been made publicly available with a visualization platform.

Neighborhood Socioeconomic Status, Green Space, and Walkability and Risk for Falls Among Postmenopausal Women: The Women's Health Initiative.

PURPOSE: This study estimated associations between neighborhood socioeconomic status (NSES), walkability, green space, and incident falls among postmenopausal women and evaluated modifiers of these associations, including study arm, race and ethnicity, baseline household income, baseline walking, age at enrollment, baseline low physical functioning, baseline fall history, climate region, and urban-rural residence. METHODS: The Women's Health Initiative recruited a national sample of postmenopausal women (50-79 years) across 40 U.S. clinical centers and conducted yearly assessments from 1993 to 2005 (n = 161,808). Women reporting a history of hip fracture or walking limitations were excluded, yielding a final sample of 157,583 participants. Falling was reported annually. NSES (income/wealth, education, occupation), walkability (population density, diversity of land cover, nearby high-traffic roadways), and green space (exposure to vegetation) were calculated annually and categorized into tertiles (low, intermediate, high). Generalized estimating equations assessed longitudinal relationships. RESULTS: NSES was associated with falling before adjustment (high vs. low, odds ratio, 1.01; 95% confidence interval, 1.00-1.01). Walkability was significantly associated with falls after adjustment (high vs. low, odds ratio, 0.99; 95% confidence interval, 0.98-0.99). Green space was not associated with falling before or after adjustment. Study arm, race and ethnicity, household income, age, low physical functioning, fall history, and climate region modified the relationship between NSES and falling. Race and ethnicity, age, fall history, and climate region modified relationships between walkability and green space and falling. CONCLUSIONS: Our results did not show strong associations of NSES, walkability, or green space with falling. Future research should incorporate granular environmental measures that may directly relate to physical activity and outdoor engagement.

Contemplative Practices Behavior Is Positively Associated with Well-Being in Three Global Multi-Regional Stanford WELL for Life Cohorts.

Positive associations between well-being and a single contemplative practice (e.g., mindfulness meditation) are well documented, yet prior work may have underestimated the strength of the association by omitting consideration of multiple and/or alternative contemplative practices. Moreover, little is known about how contemplative practice behavior (CPB) impacts different dimensions of well-being. This study investigates the relationship of CPB, consisting of four discrete practices (embodied somatic-observing, non-reactive mindfulness, self-compassion, and compassion for others), with multiple dimensions of well-being. As with other canonical lifestyle behaviors, multiple contemplative practices can be integrated into one's daily routine. Thus, it is critical to holistically consider these behaviors, extending them beyond a simple uni-dimensional measure (e.g., daily mindfulness meditation practice). We developed an integrative measure of four types of contemplative practice and found it to be significantly associated with a multi-dimensional measure of well-being. Importantly, our findings were from three large global multi-regional cohorts and compared against better-understood lifestyle behaviors (physical activity). Data were drawn from California/San Francisco Bay Area, (n = 6442), Hangzhou City (n = 10,268), and New Taipei City (n = 3033). In all three cohorts, we found statistically significant (p < 0.05) positive associations between CPB and well-being, both overall and with all of the constituent domains of well-being, comparable to or stronger than the relationship with physical activity across most well-being outcomes. These findings provide robust and cross-cultural evidence for a positive association between CPB and well-being, illuminate dimensions of well-being that could be most influenced by CPB, and suggest CPB may be useful to include as part of fundamental lifestyle recommendations for health and well-being.

The Association of Neighborhood Changes with Health-Related Quality of Life in the Women's Health Initiative.

Longitudinal studies can help us understand the effects of long-term neighborhood changes, as these can capture individual self-appraisal of current and future circumstances. We analyzed the association between neighborhood changes and health-related quality of life (HRQoL) outcomes among older women from the Women's Health Initiative (WHI) study. We used a subset (n = 49,254) of the longitudinal WHI dataset of female participants, aged 50-79 at baseline, recruited from 40 clinical centers across the U.S. beginning in 1993. Two HRQoL outcomes were explored: self-rated quality of life (SRQoL), and physical functioning-related quality of life (PFQoL). We used U.S. census tract-level changes in median household income between the 2000 census and 2007-2011 American Community Survey to classify neighborhoods as "upgrading," "declining," or "stable." Multi-level models were used to identify significant associations between neighborhood change and HRQoL outcomes over time. Compared to participants residing in upgrading neighborhoods, participants in stable and declining neighborhoods reported significantly lower PFQoL. A significant interaction was observed with income such that the effect of neighborhood change was greater at lower levels of income.

Philadelphia's Excise Tax on Sugar-Sweetened and Artificially Sweetened Beverages and Supplemental Nutrition Assistance Program Benefit Redemption.

Objectives. To assess the effect of a 2017 excise tax on sugar and artificially sweetened beverages in Philadelphia, Pennsylvania, on the shopping patterns of low-income populations using Supplemental Nutrition Assistance Program (SNAP) data. Methods. I used a synthetic controls approach to estimate the effect of the tax on Philadelphia and neighboring Pennsylvania counties (Bucks, Delaware, and Montgomery) as measured by total SNAP sales ("SNAP redemption") and SNAP redemption per SNAP participant. I assembled biannual data (2005-2019) from all US counties for SNAP redemption and relevant predictors. I performed placebo tests to estimate statistically significant effects and conducted robustness checks. Results. Detectable increases in SNAP spending occurred in all 3 Philadelphia neighboring counties. Per-participant SNAP spending increased in 2 of the neighboring counties and decreased in Philadelphia. These effects were robust across multiple specifications and placebo tests. Conclusions. The tax contributed to increased SNAP shopping in Philadelphia's neighboring counties across both outcome measures, and decreased spending in Philadelphia (at least by 1 measure). This raises questions about retailer behavior, the effectiveness of the tax's public health aim of reducing sugar-sweetened beverage consumption, and policy aims of investing in low-income communities. (Am J Public Health. 2021;111(11):1986-1996. https://doi.org/10.2105/AJPH.2021.306464).

Coping with the COVID-19 pandemic: Contemplative practice behaviors are associated with better mental health outcomes and compliance with shelter-in-place orders in a prospective cohort study.

Psychosocial health can influence the development and experience of several chronic diseases, and has been negatively affected for many individuals amid the COVID-19 global pandemic. To understand the impact of contemplative practices on emotional and mental health during COVID-19, the Stanford WELL for Life Study (US component), incorporated a series of additional surveys into its ongoing study. A total of 1,097 participants residing in California who responded to at least one of three COVID-19 surveys were included in this analysis. Linear and generalized mixed-effects regression models were used to investigate relationships between individual contemplative practice behaviors (CPB) (embodied observing meditation, non-reactive mindfulness meditation, self-compassion cultivation, cultivation of compassion for others) and four psychosocial outcomes measured in the original WELL questionnaire (resilience, dealing with stress, positive emotions, and negative emotions). In addition, the associations between CPB and depression, distress, and compliance with local Shelter-In-Place orders were also investigated. Participants who engaged in any contemplative practice reported significantly more resilience and positive emotions, dealing better with stress, lower distress, and were less likely to report an experience with depression in the last week. Similar findings held when CPB was modeled as a continuous variable. Significant interactions between the duration of the SIP and CPB were also observed for resilience and SIP compliance outcomes, indicating that steeper declines were observed among participants with little or no CPB across the study period. Further investigation into the potential protective benefits of CPB during times of major disruption and uncertainty is warranted.

Engaging citizen scientists to build healthy park environments in Colombia.

Colombia's Recreovía program offers community-based free physical activity (PA) classes in parks. We evaluated built and social environmental factors influencing Recreovía local park environments, and facilitated a consensus-building and advocacy process among community members, policymakers and academic researchers aimed at improving uptake and impact of the Recreovía program. We used a mixed-methods approach, with individual and contextual PA measurements and a resident-enabled participatory approach (the Our Voice citizen science engagement model). Recreovía participants were likely to be women meeting PA recommendations, and highly satisfied with the Recreovía classes. Reported facilitators of the Recreovía included its role in enhancing social and individual well-being through PA classes. Reported barriers to usage were related to park maintenance, cleanliness and safety. The Our Voice process elicited community reflection, empowerment, advocacy and action. Our Voice facilitated the interplay among stakeholders and community members to optimize the Recreovía program as a facilitator of active living, and to make park environments more welcoming.

Urban Emotion Sensing Beyond 'Affective Capture': Advancing Critical Interdisciplinary Methods.

The use of mobile sensor methodologies in urban analytics to study 'urban emotions' is currently outpacing the science required to rigorously interpret the data generated. Interdisciplinary research on 'urban stress' could help inform urban wellbeing policies relating to healthier commuting and alleviation of work stress. The purpose of this paper is to address-through methodological experimentation-ethical, political and conceptual issues identified by critical social scientists with regards to emotion tracking, wearables and data analytics. We aim to encourage more dialogue between the critical approach and applied environmental health research. The definition of stress is not unambiguous or neutral and is mediated by the very technologies we use for research. We outline an integrative methodology in which we combine pilot field research using biosensing technologies, a novel method for identifying 'moments of stress' in a laboratory setting, psychometric surveys and narrative interviews on workplace and commuter stress in urban environments.

Contemplation by Design: Leveraging the "Power of the Pause" on a Large University Campus Through Built and Social Environments.

College and university campuses have long been designed as embodied places of societal values and aspirations, reflecting both academic traditions and heritages alongside social and scientific change and innovation. More pragmatically, these spaces share some commonalities with other living and working environments, and must adapt to changing technological and social norms. Since the 1970's, workplace adaptations included employer-sponsored health promotion programs and facilities. While campus environments such as fitness centers and dining halls have been incorporated into health promotion initiatives, other aspects of human well-being have been neglected. In this paper, we describe an initiative, Contemplation By Design, to incorporate contemplation and mindfulness into the daily lives of all members of the Stanford University community, including students, faculty, staff, and their families, as well as alumni and retirees who live close by. This case study highlights ways that physical planning and programmatic initiatives for contemplative practices have been integrated to deliver generalizable, community-based well-being resources that can be emulated in diverse settings throughout the Stanford University campuses, including the main campus and local satellite campuses. Based on experience drawn from Contemplation By Design, practical recommendations for designing contemplative practice spaces and programs are offered.

SNAP judgments into the digital age: Reporting on food stamps varies significantly with time, publication type, and political leaning.

The Supplemental Nutrition Assistance Program (SNAP) is the second-largest and most contentious public assistance program administered by the United States government. The media forums where SNAP discourse occurs have changed with the advent of social and web-based media. We used machine learning techniques to characterize media coverage of SNAP over time (1990-2017), between outlets with national readership and those with narrower scopes, and, for a subset of web-based media, by the outlet's political leaning. We applied structural topic models, a machine learning methodology that categorizes and summarizes large bodies of text that have document-level covariates or metadata, to a corpus of print media retrieved via LexisNexis (n = 76,634). For comparison, we complied a separate corpus via web-scrape algorithm of the Google News API (2012-2017), and assigned political alignment metadata to a subset documents according to a recent study of partisanship on social media. A similar procedure was used on a subset of the print media documents that could be matched to the same alignment index. Using linear regression models, we found some, but not all, topics to vary significantly with time, between large and small media outlets, and by political leaning. Our findings offer insights into the polarized and partisan nature of a major social welfare program in the United States, and the possible effects of new media environments on the state of this discourse.

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

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.

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

(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.

Diet Quality Over the Monthly Supplemental Nutrition Assistance Program Cycle.

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.

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.

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.

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.

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.

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

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.

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.

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 (ß = 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.

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

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.

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

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.