Abstract New York City is notorious for its high cost of living. Much attention is devoted to its exorbitant rent prices, but its food costs are also incredibly high. Access to affordable, quality food options is a crucial feature of any sustainable city. This issue of access is particularly relevant in a city like New York, where residents rely heavily on public transportation or walking as their primary means of navigation—many New Yorkers will likely be carrying their groceries home. I wanted to investigate if there is a linear correlation between socioeconomic factors like income and education and access to healthy and unhealthy food venues. I chose to aggregate at the PUMA level (Public Use Microdata Area) because PUMA’s are designed to 1) contain at least 100,000 residents, 2) are geographically contiguous and 3) are built on census tracts and are intended to be demographically homogenous. I ran two regression analyses for three target variables: healthy venues per person, average minimum distance to a healthy venue and average minimum distance to an unhealthy venue. I regressed healthy venues per person against the exogenous variables of median income, proportion of residents over age 25 with a bachelor’s degree, proportion of non-white residents, proportion of residents below the poverty line and proportion of residents receiving any sort of public assistance (including SNAP benefits). I then regress average minimum distance to healthy venues against median income, proportion of residents over 25 with a bachelor’s degree, proportion of non-white residents, proportion of residents below the poverty line, proportion of residents receiving public assistance and, finally, population density; the same is done for average minimum distance to unhealthy venues. The models all have modest R-squared values (<.5); the only significant estimates are for population density in both regressions involving minimum distance. The estimate for population density’s impact on average minimum distance to an unhealthy venue is -.4744 (p < .05) and the estimate for population density’s impact on average minimum distance to a healthy venue is -.3441 (p < .05). IntroductionThe question of access to healthy, fresh food options is a growing concern in the United States. A literature review entitled “Neighborhood Disparities in Access to Healthy Foods and Their Effects on Environmental Justice,” authors Hilmers et al. examine the impact of racial and socioeconomic demographics on access to healthy and unhealthy food sources. The authors frame their literature review by the principle of environmental justice, defined as “fair treatment and meaningful involvement of all people regardless of race, ethnicity, income, national origin, or educational level in the development, implementation, and enforcement of environmental laws, regulations, and policies”. The authors identified 501 relevant studies that evaluated access to healthy food based on socioeconomic factors and conducted 24 to review in depth. In both urban, suburban and rural communities across the globe, cross-sectional studies usually find similar results: lower income areas have ready access to unhealthy food options high in saturated fats and sodium, but relatively little access to healthy choices. Hilmer et al. note that Accessibility is a key determinant of consumption and can act as a barrier to or a facilitator for healthy eating, as well as a component of environmental justice. Accessibility of healthful food sources may lower the risk of overweight and obesity by facilitating healthier diets, and easy access to nutritionally inappropriate food sources may contribute to excessive and harmful weight gain.Most of the analyses evaluated by the authors was performed at the level of census tract or zip code, but I wanted to see if the observed trends persisted at the NYC PUMA level. Data
I wanted to investigate whether or not there was a relationship between a Citibike rider's age and trip duration. I hypothesized that younger riders would take longer Citibike trips--perhaps because they are more comfortable riding a bicycle over longer distances in New York City. I categorized a subset of my Citibike trips into "Young" (aged 18 - 35) and "Old" (aged 43-60) in order to determine if there was a statistically significant difference in mean trip duration. I employ an unpaired t-test which yielded a t statistic of 29.448 with a p-value of 0.00. This indicates a statistically significant difference in sample means between old and young riders.