Table 1.
Sources and methods used to measure characteristics of United Hospital Fund districts.
| Construct | Sources & operationalization |
|---|---|
| Food Access Environment | The percent of food-distressed residents was calculated from 2010 U.S. Department of Agriculture Food Access Research Atlas data (Food Access Research Atlas, 2010) as the percent of residents who were both low-income (< 200% of federal poverty limit) and who lived in a food desert area (> 0.5 mile from a large grocery store or supermarket). |
| Racial/Ethnic Composition | The percent of residents who self-identified a; non Hispanic Black/African-American was calculated using 2007–2011 American Community Survey (AG) data (U.S. Census Bureau’s American Community Survey Office, 2011). This variable was skewed, and therefore three categories reflecting its multimodal distribution were created based upon review of the variable’s distribution: low (<5% of residents were Black), medium (5–29%), and high (>30%). |
| Age composition | The percent of residents who were 21–54 years old was calculated using 2007–2011 ACS data (U.S. Census Bureau’s American Community Survey Office, 2011). |
| Residential Stability | We used principal components analysis (PCA) to create a dimension of neighborhood stability (see Appendix A for component loadings). Constituent variables were: the percent of residents residing in the same home as one year ago, from 2007–2011 ACS data (U.S. Census Bureau’s American Community Survey Office, 2011); and the male:female sex ratio for 18–64 year old non-institutionalized residents from 2010 decennial census data (United States Census Bureau, 2010). |
| Affluence | We used PCA to create a dimension of neighborhood affluence using 2007–2011 ACS data (U.S. Census Bureau’s American Community Survey Office, 2011). Constituent variables were: the percent of residents ≥25 years old who were college educated; the percent of high income households (> 400% of 2009 U.S, median household income); and the percent of expensive homes (> 400% of 2009 U.S. median home value) (see Appendix A). |
| Economic disadvantage | We used PCA to create a dimension of UHF-level economic disadvantage using 2007–2011 ACS data (U.S. Census Bureau’s American Community Survey Office, 2011) (see Appendix A). Constituent variables were UHF-level median income and the percentages of people aged >16 years in the civilian workforce who were unemployed; of individuals living at or below the federal poverty level; of households that had received public assistance in the last 12 months; and of adults >25 years old who did not have a high school degree/GED. |
| Healthcare access | We used PCA to create a dimension of poor access to healthcare, using pooled 2009 and 2010 NYC DOHMH Community Health Survey data, weighted to adjust for selection in both years (see Appendix A). Constituent variables were the percent of UHF residents without health insurance and the percent of UHF residents who reported an unmet need for health care in the last 12 months (New York City Department of Health and Mental Hygiene, 2009–2010). |
| Social disorder | To assess dimensions of social disorder we created measures of the number of businesses licensed to sell alcohol for off-premises consumption per square mile in 2009 (Keen, Dyer, Whitehead, &; Latimer, 2014; United States Census Bureau, 2009), and the number of residences that had once been occupied and now were empty per square mile in 2009 (United States Postal Service/Department of Housing and Urban Development, 2009). |
| Police stop and frisk rates | We used 2009 NYC Police Department Stop, Question, and Frisk (SQF) data to measure the rate of stops per 100,000 adult residents and the rate of stops without an arrest per 100,000 adult residents (New York Police Department, 2009). Both rates were skewed and three categories reflecting multimodal distributions were created for each variable, based upon each variable’s distribution. Stops per 100,000 adult residents were categorized: low (<4,000 stops without anest per 100,000 residents), medium (4,000-<20,000), and high (>20,000). Stops without an arrest per 100,000 adult residents were categorized: low (<6,000 stops without arrest per 100,000 residents), medium (6,000-<22,000), and high (≥22,000). |
Keen, Dyer, Whitehead, & Latimer, (2014)
New York City Department of Health and Mental Hygiene. (2009–2010).
New York Police Department (2009).
United States Census Bureau’s American Community Survey Office. (2011).
United States Census Bureau. (2009).
United States Census Bureau. (2010).
United States Postal Service/Department of Housing and Urban Development (2009).