Highlights 1 2 3 • Over the past 10 years, the population age 65 and over increased from 37.2 million in 2006 to 49.2 million in 2016 (a 33% increase) and is projected to almost double to million in 2060. • Between and 2016 the population age 60 and over increased 36% from 50.7 million to 68.7 million. • The 85 and over population is projected to more than double from 6.4 million in 2016 to 14.6 million in 2040 (a 129% increase). • Racial and ethnic minority populations have increased from 6.9 million in 2006 (19% of the older adult population) to 11.1 million in 2016 (23% of older adults) and are projected to increase to 21.1 million in 2030 (28% of older adults).

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Purpose: Most residents in rural regions of the United States consume fewer amounts of fruits and vegetables (FVs) compared with their urban counterparts. Difficulties in access to FVs often contribute to different consumption patterns in rural regions, aside from a lack of education or motivation for eating healthy foods. This article uses simulation methods to estimate the relationship between increasing food access and FV consumption levels in a targeted rural community. Methods: An agent-based model previously developed to predict individual dietary behaviors was used. We adapted it to a rural community in west Texas following a two-step process. First, we validated the model with observed data. Second, we simulated the impact of increasing access on FV consumption. We estimated model parameters from the 2010 census and other sources. Results: We found that decreasing the driving distance to FV outlets would increase FV consumption in the community. For example, a one-mile decrease in driving distance to the nearest FV store could lead to an 8.9% increase in FV consumption; a five-mile decrease in driving distance could lead to a 25% increase in FV consumption in the community. We found that the highest marginal increase in FV consumption was when the driving distance decreased from 3.5 miles to 3 miles. Conclusions: Analysis to inform policy alternatives is a challenge in rural settings due to lack of data. This study highlights the potential of simulation modeling to inform and analyze policy alternatives in settings with scarce data. The findings from modeling can be used to evaluate alternative policies in addressing chronic diseases through dietary interventions in rural regions.