An activity space approach to understanding how food access is associated with dietary intake and BMI among urban, low-income African American women

Association of activity-based food environment index with obesity-related cancer mortality in the US

BACKGROUND

Obesity and obesity-related cancers contribute to rising healthcare costs and declining life expectancy in the US and improving diet quality plays a crucial role in reversing such trends. Existing studies on the relationship between healthy food access and obesity-related cancer mortality present mixed findings, whereas food procurement activities are largely overlooked. The paper aims to construct a novel food environment index based on residents' food retailer visits, and then compare it with the location-based food environment index regarding the strength of associations with obesity-related cancer mortality rates.

METHODS

This cross-sectional ecologic study used business location data from InfoGroup and aggregated GPS-based food retailer visit data from SafeGraph in 2018-2019, and mortality data from the Centers for Disease Control and Prevention in 2015-2020. A total of 2925 counties or equivalents with complete information were included. Activity-based index was calculated as the percentage of visits to healthy food retailers out of total visits to all qualified food retailers for residents in each county. Location-based index was calculated as the percentage of healthy food retailers out of all qualified food retailers in each county. The main outcome is age-adjusted obesity-related cancer (13 types of cancer based on evidence from the International Agency for Research on Cancer) mortality rates, which were calculated for each county and counties were further categorized into high- and low-risk (≥ 60.2 and < 60.2 cases per 100,000 population) areas. Linear, non-linear, logistic, and spatial regression analyses were performed to examine the association between each food environment index and obesity-related cancer mortality rates.

RESULTS

The activity-based index demonstrated significant negative association with the 2015-2020 obesity-related cancer mortality rates (coefficient [95% CI]: - 0.980 [- 1.385, - 0.575], P < 0.001), and each standard deviation increase in the activity-based index was associated with an 18% decrease in the odds of being in a high-risk area (odds ratio [95% CI]: 0.821 [0.749, 0.900], P < 0.001), while the location-based index showed much weaker and non-significant effects.

CONCLUSIONS

Our findings suggest that health policies and initiatives that combat obesity and obesity-related cancers should consider incorporating food retailer visits into policy formation.

Association between neighbourhood food environment and dietary quality among adolescents in Kuala Lumpur, Malaysia

The neighbourhood food environment has been found to influence the dietary quality of adolescents. Therefore, this study aims to investigate the association between neighbourhood food environment and dietary quality among adolescents that come from low-income families in Kuala Lumpur. This cross-sectional study involves 184 adolescents from six public secondary schools in Kuala Lumpur. The online self-administered questionnaire through Google Forms was used to obtain information regarding adolescents' sociodemographic characteristics, dietary quality, and perceived availability, accessibility, and affordability of the neighbourhood food environment. Food stores and home addresses were geocoded using Google Earth. Geographic Information System (GIS) was used to identify the status of neighbourhood food environment, map the food stores and home addresses, and determine 1000m buffer zones around respondents' addresses. Associations between neighbourhood food environment statuses and dietary quality were examined using Pearson correlation, Chi-Square Test and Multivariable Linear Regression (MLR). The most reported response for dietary quality status is it 'requires improvement' (62.0 %), compared to having a 'poor diet' (23.9 %) and 'good' (14.1 %). The majority (60.3 %) resided in a healthy food environment, while the minority lived in food swamps (37.0 %) and food deserts (2.7 %). Although the majority of respondents perceived While a higher number of them perceived high food availability (76.6 %) and affordability (64.7 %) of healthy food stores in their neighbourhood, over half (51.7 %) reported low accessibility to these stores. About 33.2 % of them never use food delivery services, followed by at least once per month (31.5 %), once every two weeks (16.3 %), and once per week (19.0 %). Age (rs = -0.19), ethnicity (X 2 = 5.75), fathers' educational level (rs = 0.15), non-fast-food restaurants (r = -0.16) and convenience stores (rs = -0.20) were significantly correlated with adolescents' dietary quality (p < 0.05). However, after adjustment for covariates, ethnicity (β = 0.180, t = 2.283, p = 0.020), father's educational level (β = 0.177, t = 2.113, p = 0.036) and monthly household income (β = -0.169, t = -2.160, p = 0.032) were identified as significantly associated with dietary quality. The dietary quality of urban poor adolescents in Kuala Lumpur requires further improvement in terms of awareness and intervention. Interventions should focus on increasing fathers' awareness of healthy food choices and addressing ethnic dietary. Enhancing nutrition education in schools may also help improve dietary habits among low-income urban adolescents.

The "uneven road" to food: Socioeconomic disparities in the mobility burden of food purchasing behavior in major US cities, 2019-2023

Socioeconomic factors contribute to distinct patterns of food-purchasing behaviors, placing a higher burden of mobility on vulnerable, deprived populations. Traditional approaches often overlook the dynamics of human activity as contextual influences, simulating a perceived food environment that contradicts the actual use thereof. The rise of large-scale mobile phone data presents a unique opportunity to capture real behavioral patterns and their mobility implications at a fine-grained level. Using a Time-Weighted Kernel Density Estimation (TWKDE) model on mobile phone data, this study introduces two novel measures - the Spatial Engel's Coefficient (SEC) index and the Distance-to-Activity Curve (DAC) - to assess the equity of food-purchasing travel across nine U.S. cities over five years, analyzed by socioeconomic status, time period, and location. Our findings reveal that lower socioeconomic status is strongly associated with greater mobility burdens in food-purchasing travel. This mobility gap between the highest and lowest socioeconomic groups was further exacerbated during the COVID-19 pandemic, manifesting in the form of spatial segregation of opportunities within cities. This paper contributes to the literature by developing novel activity-based tools that offer a more nuanced understanding of the behavioral characteristics of food-purchasing activities. These empirical insights can help policymakers identify the communities facing the greatest mobility burdens and guide targeted, place-based interventions to promote equity in food access.

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention

OBJECTIVE

To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity.

METHODS

Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks.

RESULTS

According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence.

CONCLUSIONS

A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

Is home where the heat is? comparing residence-based with mobility-based measures of heat exposure in San Diego, California

BACKGROUND

Heat can vary spatially within an urban area. Individual-level heat exposure may thus depend on an individual's day-to-day travel patterns (also called mobility patterns or activity space), yet heat exposure is commonly measured based on place of residence.

OBJECTIVE

In this study, we compared measures assessing exposure to two heat indicators using place of residence with those defined considering participants' day-to-day mobility patterns.

METHODS

Participants (n = 599; aged 35-80 years old [mean =59 years]) from San Diego County, California wore a GPS device to measure their day-to-day travel over 14-day intervals between 2014-10-17 and 2017-10-06. We measured exposure to two heat indicators (land-surface temperature [LST] and air temperature) using an approach considering their mobility patterns and an approach considering only their place of residence. We compared participant mean and maximum exposure values from each method for each indicator.

RESULTS

The overall mobility-based mean LST exposure (34.7 °C) was almost equivalent to the corresponding residence-based mean (34.8 °C; mean difference in means = -0.09 °C). Similarly, the mean difference between the overall mobility-based mean air temperature exposure (19.2 °C) and the corresponding residence-based mean (19.2 °C) was negligible (-0.02 °C). Meaningful differences emerged, however, when comparing maximums, particularly for LST. The mean mobility-based maximum LST was 40.3 °C compared with a mean residence-based maximum of 35.8 °C, a difference of 4.51 °C. The difference in maximums was considerably smaller for air temperature (mean = 0.40 °C; SD = 1.41 °C) but nevertheless greater than the corresponding difference in means.

IMPACT

As the climate warms, assessment of heat exposure both at and away from home is important for understanding its health impacts. We compared two approaches to estimate exposure to two heat measures (land surface temperature and air temperature). The first approach only considered exposure at home, and the second considered day-to-day travel. Considering the average exposure estimated by each approach, the results were almost identical. Considering the maximum exposure experienced (specific definition in text), the differences between the two approaches were more considerable, especially for land surface temperature.

Measuring access to food banks and food pantries: A scoping review of spatial analysis approaches

Food banks and food pantries are crucial in supporting access to food and addressing food insecurity for millions of people. This scoping review identified eighteen articles that applied spatial analysis approaches to measure access to food banks and food pantries. The review summarizes the methods and primary findings of these studies, and examines how these address different dimensions of food access. Findings suggest that the majority of studies measured the accessibility and availability dimensions of food access, and two addressed accommodation. Through a discussion of these studies' methods and broader literature on food environments, we highlight opportunities to integrate advanced geospatial and mixed methods to support an empirically grounded and broader understanding of food bank and pantry access in future research. This will yield a more holistic picture of food environments and provide practical implications for site selection, resource allocation, and food assistance operations.

Integrating human activity into food environments can better predict cardiometabolic diseases in the United States

The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.

BMI and the Food Retail Environment in Melbourne, Australia: Associations and Temporal Trends

Research into the link between food environments and health is scarce. Research in this field has progressed, and new comprehensive methods (i.e., incorporating all food retail outlets) for classifying food retail environments have been developed and are yet to be examined alongside measures of obesity. In this study, we examine the association and temporal trends between the food environment and BMI of a repeated cross-sectional sample of the adult population between 2008 and 2016. Methods: Food retail data for 264 postal areas of Greater Melbourne was collected for the years 2008, 2012, 2014, and 2016, and a container-based approach was used to estimate accessibility to supermarkets, healthy and unhealthy outlets. Data on BMI for postal areas was obtained from the Victorian Population Health Survey (n = 47,245). We estimated the association between the food environment and BMI using linear mixed models. Results indicated that BMI increased as accessibility to healthy outlets decreased by up to -0.69 kg/m2 (95%CI: -0.95, -0.44). BMI was lower with high and moderate access to supermarkets compared to low access by -0.33 kg/m2 (-0.63, -0.04) and -0.32 kg/m2 (-0.56, -0.07), and with high access to unhealthy outlets compared to low access (-0.38 kg/m2: -0.64, -0.12) and moderate access (-0.54 kg/m2: -0.78, -0.30). Conclusion: Our results show that increasing access and availability to a diverse range of food outlets, particularly healthy food outlets, should be an important consideration for efforts to support good health. This research provides evidence that Australia needs to follow suit with other countries that have adopted policies giving local governments the power to encourage healthier food environments.

Integrating coordination of food purchasing into activity space-based food environment research: Toward a household perspective

Despite the advances in person-based approaches to studying food environments, most studies using these approaches have relied on individual-centered activity space measures and largely ignored cohabiting household members who play crucial roles in shaping an individual's food access, food behaviors, and diet. This can be problematic for completely capturing food environments relevant to an individual and add uncertainties to explorations of how individuals' food environments relate to their food behaviors. This viewpoint discusses the need for, and implications of, considering household members when measuring food access and disentangling the behavioral pathways connecting the food environment to diet. Ultimately, a conceptual framework and potential questions are proposed to integrate household members into food environment research.

Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

The community food environment has potential influences on community members' dietary health outcomes, such as obesity and Type II diabetes. However, most existing studies evaluating such health effects neglect human mobility. In food patrons' daily travels, certain locations may be preferred and patronized more frequently than others. This behavioral uncertainty, known as the selective daily mobility bias (SDMB), is less explored in community-food-environment research. In this paper, we aim to confirm the existence of the SDMB by systematically exploring the large-scale GPS-based restaurant-visit patterns in the Greater Harford region, Connecticut. Next, we explore the restaurant and neighborhood characteristics that are associated with the restaurant-visit patterns. Our primary results demonstrate that (1) most restaurant customers originate from areas outside of the census tract where the restaurant is located, and (2) restaurants located in socially vulnerable areas attract more customers in total, more customers from local areas, and more customers from other socially vulnerable areas. These results confirm the relevance of the SDMB to the community food environment, and suggest ways that the SDMB can be moderated by an uneven socio-economic landscape. The findings demonstrate the necessity of incorporating human-mobility data into the study of the community food environment.

Barriers to Creating Healthier Home Food Environments: Process Evaluation Results From 2 Home Food Environment Intervention Studies

Few studies have identified barriers to creating a home environment more supportive of healthy eating. We examined barriers faced by participants in a randomized controlled trial and an adaptation study of the Healthy Homes/Healthy Families intervention, which uses health coaches to support low-income families in creating healthier home food environments. Coaches maintained logs of participant interactions as part of a process evaluation. We thematically analyzed logs from interactions with participants, mostly lower-income African American women (n = 114), to identify barriers for each of 8 healthy actions that serve as core elements of the intervention. Difficulty of changing current habits was a barrier for 5 of the healthy actions. No time/convenience and limited family support each influenced 2 of the healthy actions, with interpersonal barriers also stemming from social situations and visitors, including grandchildren. Cost and economic challenges were barriers for 3 of the actions. Hunger, cravings, and limited access to resources (eg, transportation, fresh fruits and vegetables) were each noted as barriers for 1 healthy action. Overall, these findings provide insight for how to better support families who are trying to improve their home food environments and highlight the need for multilevel interventions.

Using aggregated mobile phone location data to compare the realised foodscapes of different socio-economic groups

The foodscape (the built food environment) is considered one of the driving factors of the higher burden of obesity and chronic disease observed in low socio-economic status (SES) groups. Traditional data collection methods struggle to accurately capture actual access and exposure to the foodscape (realised foodscape). We assess the use of anonymised mobile phone location data (location data) in foodscape studies by applying them to a case study in Perth, Western Australia to test the hypothesis that lower SES groups have poorer realised foodscapes than high SES groups. Kernel density estimation was used to calculate realised foodscapes of different SES groups and home foodscape typologies, which were compared to home foodscapes of the different groups. The location data enabled us to measure realised foodscapes of multiple groups over an extended period and at the city scale. Low SES groups had poor availability of food outlets, including unhealthy outlets, in their home and realised foodscapes and may be more susceptible to a poor home foodscape because of low mobility.

The Roots of Structural Racism in the United States and their Manifestations During the COVID-19 Pandemic

During the COVID-19 pandemic, the disproportionate morbidity and mortality borne by racial minorities, patients of lower socioeconomic status, and patients lacking health insurance reflect pre-existing structural inequities. Structural racism is racial discrimination rooted in history, perpetuated through policies, and manifested in disparities in healthcare, housing, education, employment, and wealth. Although these disparities exert greater impacts on health outcomes than do genetics or behavior, scientists, and policy makers are only beginning to name structural racism as a key determinant of population health and take the necessary steps to dismantle it. In radiology, structural racism impacts how imaging services are utilized. Here we review the history and policies that contribute to structural racism and predispose minority and disadvantaged communities to inferior outcomes during the COVID-19 pandemic in order to identify policy changes that could promote more equitable access to radiologic services.