OBJECTIVE: This dissertation first evaluates food price variation within and between neighborhoods in order to improve our understanding of access to healthy foods and potential economic incentives and barriers to consuming a higher quality diet. The study then spatially links individuals to their nearby supermarkets to study the association between food price and dietary quality, insulin resistance (IR), and diabetes. METHODS: Prices of healthy foods (dairy, fruits, and vegetables) and unhealthy foods (soda, sweets, and salty snacks) were obtained from 1953 supermarkets across the US during 2009-2012 from the Information Resources Inc. (IRI) database. In Aim 1, prices of healthy and unhealthy foods, and the relative price of healthy foods compared with unhealthy foods (healthy-to-unhealthy price ratio) were linked to census block group socio-demographics in order to analyze associations between food prices with neighborhood SES and proportion Black/Hispanic. Linear hierarchical regression models were used to explore geospatial variation and adjust for confounders. The second and third aims of this study linked average price of healthy foods, unhealthy foods and their ratio to participants in The Multi-Ethnic Study of Atherosclerosis (MESA). For Aim 2, individuals who completed MESA exam 5 (2010-2012) and the food frequency questionnaire were included (N=2765). A Healthy Eating Index (HEI-2010) was calculated for each individual according to their FFQ. Logistic regression estimated adjusted odds ratios of a high quality diet (top quantile of HEI-2010) associated with each price exposure. Sensitivity analyses used an instrumental variable approach in which the price of brand name toilet paper served as an instrument for food prices. For Aim 3, individuals from MESA who completed exam 5 and exam 4 (administered five years prior, diabetes incidence analysis only) were included. Type 2 diabetes status was confirmed at each exam and IR was measured according to the homeostasis model assessment index of IR. Adjusted logistic, modified Poisson and linear regression models were used to model diabetes prevalence, incidence and IR, respectively. RESULTS: Overall, the price of healthy foods was nearly twice as high as the price of unhealthy foods ($0.590 vs. $0.298 per serving; healthy-to-unhealthy price ratio of 1.99). This trend was consistent across all neighborhood characteristics. After adjusting for covariates, no association was found between food prices (healthy, unhealthy, or the healthy-to-unhealthy ratio) and neighborhood SES, while small positive and negative associations were detected with the proportion Black/Hispanic, respectively. A larger healthy-to-unhealthy price ratio was associated with lower odds of having a high quality diet (Odds Ratio [OR]=0.76 per SD increase in the ratio, 95% CI=[0.64 to 0.91]). Instrumental variable analyses largely confirmed these findings although confidence intervals were wider and the result was no longer statistically significant (OR=0.82 [0.57 to 1.19]). A higher ratio of healthy-to-unhealthy food had a positive association with IR (4.8% increase in IR for each standard deviation increase in price ratio (estimate=0.048, 95% CI=[0.00 to 0.10]) after adjusting for confounders. No association with diabetes incidence (relative risk=1.11, 95% CI=[0.85 to 1.44]) or prevalence (OR=0.95, 95% CI=[0.81 to 1.11]) was observed. CONCLUSIONS: The price of healthy food was twice as expensive as unhealthy food per serving on average. A higher price of healthy food relative to unhealthy foods appears to be negatively associated with a high quality diet and with insulin resistance. There did not appear to be an association with diabetes prevalence or 5-year incidence. This study provides new insight into the relationship between food prices with diet quality, IR and diabetes. Policies to address the large price differences between healthy and unhealthy foods may help improve diet quality and downstream health effects in the U.S.