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

Neighborhood Disadvantage, Built Environment, and Breast Cancer Outcomes: Disparities in Tumor Aggressiveness and Survival

BACKGROUND

Breast cancer disparities persist globally, with growing evidence implicating neighborhood and built environmental factors in disease outcomes.

METHODS

This study investigates the associations between neighborhood disadvantage, environmental exposures, and breast tumor characteristics and survival among 3041 stage I-III breast cancer patients treated at the University of Virginia Comprehensive Cancer Center (2014-2024). Neighborhood disadvantage was assessed via the Area Deprivation Index (ADI), while environmental exposures included PM2.5, green space (NDVI), and food indices (modified retail food environment index (mRFEI), retail food activity index (RFAI)). Multivariable regression and Cox models adjusted for demographic, socioeconomic, and clinical covariates were employed.

RESULTS

A higher ADI score was associated with aggressive tumor characteristics, including advanced stage (Odds Ratio (OR) = 1.06, 95% Confidence Interval (CI):1.01-1.11), poor differentiation (OR = 1.07, 1.01-1.15), ER-negative status (OR = 1.06, 1.01-1.12), and triple-negative breast cancer (TNBC) (OR = 1.08, 1.02-1.16), as well as younger diagnosis age (β = -0.22, -0.36 to -0.09). PM2.5 exposure was correlated with advanced tumor stage (OR = 1.24, 1.09-1.40 for stage III) but paradoxically predicted improved survival (Hazard Ratio (HR) = 0.71, 0.63-0.82). The food environment indices showed subtype-specific survival benefits: higher mRFEI and RFAI scores were linked to reduced mortality in ER-negative (HR = 0.45, 0.23-0.85 and HR = 0.61, 0.38-0.97) and TNBC (HR = 0.40, 0.18-0.90 and HR = 0.48, 0.26-0.87) patients. NDVI scores exhibited no significant associations.

CONCLUSION

Our findings underscore the dual role of neighborhood disadvantage and the built environmental in breast cancer outcomes. While neighborhood disadvantage and PM2.5 exposure elevate tumor aggressiveness, survival disparities may be mediated by other factors. Improved food environments may enhance survival in aggressive subtypes, highlighting the need for integrated interventions addressing socioeconomic inequities, environmental risks, and nutritional support needs.

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.

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.

Using smartphone user mobility to unveil actual travel time to healthcare: An example of mental health facilities

Travel time to health facilities is one of the most important factors in evaluating health disparity. Previous extensive research has primarily leveraged the driving time to the nearest health facility to gauge travel time. However, such ideal travel time (ITT) may not accurately represent real individual travel time to health services and is often underestimated. This study aims to systematically understand such gaps by comparing ITT to actual travel time (ATT) derived from smartphone-based human mobility data and further identifying how various population groups across regions are most likely to be affected. This study takes mental health as an example and compares ATT with ITT to mental health facilities. Results indicate that ITT and ATT demonstrate significant disparities between urban and rural areas. ITT is consistently underestimated across the contiguous US. We compare travel times among diverse sociodemographic groups across eight geographical regions. The findings suggest that different age groups have similar travel times to mental health facilities. However, racial groups exhibit varied travel times. Hispanics have a larger percentage of the population experiencing longer ATT than ITT. We also employed spatial and non-spatial regression models, such as Ordinary Least Squares, Spatial Lag Model, and Spatial Error Model, to quantify the correlation between travel times and socioeconomic status. The results revealed that the proportion of older adults and high school dropouts positively correlates with travel times in most regions. Areas with more non-Hispanics show positive correlations with both travel times. Overall, this study reveals pronounced discrepancies between ITT and ATT, underscoring the importance of using smartphone-derived ATT to measure health accessibility.

New insights into grocery store visits among east Los Angeles residents using mobility data

In this study, we employed spatially aggregated population mobility data, generated from mobile phone locations in 2021, to investigate patterns of grocery store visits among residents east and northeast of Downtown Los Angeles, in which 60% of the census tracts had previously been designated as "food deserts". Further, we examined whether the store visits varied with neighborhood sociodemographics and grocery store accessibility. We found that residents averaged 0.4 trips to grocery stores per week, with only 13% of these visits within home census tracts, and 40% within home and neighboring census tracts. The mean distance from home to grocery stores was 2.2 miles. We found that people visited grocery stores more frequently when they lived in neighborhoods with higher percentages of Hispanics/Latinos, renters and foreign-born residents, and a greater number of grocery stores. This research highlights the utility of mobility data in elucidating grocery store use, and factors that may facilitate or be a barrier to store access. The results point to limitations of using geographically constrained metrics of food access like food deserts.