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Background: Incidence rates of gastric cancer are increasing in young adults (age <50 years), particularly among Hispanic persons. We estimated incidence rates of early-onset gastric cancer (EOGC) among Hispanic and non-Hispanic White persons by census tract poverty level and county-level metro/non-metro residence. Methods: We used population-based data from the California and Texas Cancer Registries from 1995-2016 to estimate age-adjusted incidence rates of EOGC among Hispanic and non-Hispanic White persons by year, sex, tumor stage, census tract poverty level, metro vs. non-metro county, and state. We used logistic regression models to identify factors associated with distant stage diagnosis. Results: Of 3047 persons diagnosed with EOGC, 73.2% were Hispanic White. Incidence rates were 1.29 (95% CI 1.24, 1.35) and 0.31 (95% CI 0.29, 0.33) per 100,000 Hispanic White and non-Hispanic White persons, respectively, with consistently higher incidence rates among Hispanic persons at all levels of poverty. There was no statistically significant associations between ethnicity and distant stage diagnosis in adjusted analysis. Conclusion: There are ethnic disparities in EOGC incidence rates that persist across poverty levels. Impact: EOGC incidence rates vary by ethnicity and poverty; these factors should be considered when assessing disease risk and targeting prevention efforts.

Since its first use for describing a neighborhood lacking access to food in the 1990's, "food deserts" has been widely addressed by researchers and adopted as an indicator of neighborhood-level food insecurity by governmental agencies, such as USDA. However, mostly due to cost and difficulty in collecting georeferenced data and characteristics of grocery stores, the USDA Food Access Research Atlas is infrequently released, and considers only income, vehicle ownership, and distance to the nearest grocery store. In this paper, we explored the feasibility of a crowdsourced geospatial data source, coupled with additional measures, in supplementing the USDA's current designation of food deserts. We used Yelp data to map food deserts in the city of Dallas and compared them with those based on the 2015 USDA food retailer database. Although direct comparison was not possible due to time mismatch between the two data sources, the discrepancies highlighted the need of a more frequent identification of food deserts for timely policy intervention. Furthermore, we extended mapping to reveal other potential areas of concerns, by adding the Transit Score metric and Yelp's price descriptor of businesses. The resulting maps illustrated the areas with grocery stores nearby but with limited accessibility due to lack of public transit or potential financial barriers in purchasing foods due to high prices. Our findings demonstrate the current status and future potential of up-to-date crowdsourced, georeferenced data as a complement of official government data, which could serve to extend food access research and guide health policies.