Green stormwater infrastructure in New Haven, CT and socioeconomic variables within neighborhoods and census block groups

2021 ◽  
Author(s):  
Dexter H. Locke
Keyword(s):  
New Haven ◽  
Census Block ◽  
Socioeconomic Variables ◽  
Green Stormwater Infrastructure ◽  
Block Groups

scholarly journals Environmental Justice and Factors that Influence Participation in Tree Planting Programs in Portland, Oregon, U.S.

2014 ◽  
Vol 40 (2) ◽  
Author(s):  
Geoffrey Donovan ◽  
John Mills
Keyword(s):  
High School ◽  
Environmental Justice ◽  
High School Graduation ◽  
Tree Planting ◽  
Census Block ◽  
Environmental Inequality ◽  
High School Graduation Rates ◽  
Local Program ◽  
School Graduation ◽  
Block Groups

Many cities have policies encouraging homeowners to plant trees. For these policies to be effective, it is important to understand what motivates a homeowner’s tree-planting decision. Researchers address this question by identifying variables that influence participation in a tree-planting program in Portland, Oregon, U.S. According to the study, homeowners with street trees, and those living in older homes, are more likely to participate in the local program. Homeowners who had owned their homes for longer, and those who live in census-block groups with lower high-school graduation rates, are less likely to participate in the program. Results suggest that tree-planting programs may inadvertently exacerbate environmental inequality.

scholarly journals The Neighborhood Deprivation Index and Provider Geocoding Identify Critical Catchment Areas for Diabetes Outreach

2020 ◽  
Vol 105 (9) ◽  
pp. 3069-3075
Author(s):  
Ashby F Walker ◽  
Hui Hu ◽  
Nicolas Cuttriss ◽  
Claudia Anez-Zabala ◽  
Katarina Yabut ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Primary Care Providers ◽  
Deprivation Index ◽  
Care Providers ◽  
Census Block ◽  
Neighborhood Deprivation ◽  
Census Tracts ◽  
Targeted Interventions ◽  
Catchment Areas ◽  
Block Groups

Abstract Purpose In designing a Project ECHO™ type 1 diabetes (T1D) program in Florida and California, the Neighborhood Deprivation Index (NDI) was used in conjunction with geocoding of primary care providers (PCPs) and endocrinologists in each state to concurrently identify areas with low endocrinology provider density and high health risk/poverty areas. The NDI measures many aspects of poverty proven to be critical indicators of health outcomes. Methods The data from the 2013-2017 American Community Survey (ACS) 5-year estimates were used to create NDI maps for California and Florida. In addition, geocoding and 30-minute drive-time buffers were performed using publicly available provider directories for PCPs and endocrinologists in both states by Google Geocoding API and the TravelTime Search Application Programming Interface (API). Results Based on these findings, we defined high-need catchment areas as areas with (1) more than a 30-minute drive to the nearest endocrinologist but within a 30-minute drive to the nearest PCP; (2) an NDI in the highest quartile; and (3) a population above the median (5199 for census tracts, and 1394 for census block groups). Out of the 12 181 census tracts and 34 490 census block groups in California and Florida, we identified 57 tracts and 215 block groups meeting these criteria as high-need catchment areas. Conclusion Geospatial analysis provides an important initial methodologic step to effectively focus outreach efforts in diabetes program development. The integration of the NDI with geocoded provider directories enables more cost-effective and targeted interventions to reach the most vulnerable populations living with T1D.

Abstract 17079: Lower Socioeconomic Status Portends Higher Long Term Mortality Following Isolated Mitral Valve Surgery

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Mark R Helmers ◽  
William Patrick ◽  
Cody Fowler ◽  
Amit Iyengar ◽  
Jason J Han ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Mitral Valve ◽  
Census Block ◽  
Lower Socioeconomic Status ◽  
Term Survival ◽  
Lower Socioeconomic ◽  
Address Data ◽  
Block Groups ◽  
Long Term Mortality

Introduction: Lower socioeconomic status (SES) has been associated with worse outcomes in patients undergoing cardiac surgery; however, this has not been fully elucidated in mitral valve (MV) surgery. We sought to determine the effect of SES on short-term outcomes and long-term mortality following MV surgery. Hypothesis: Lower SES is associated with higher mortality following isolated MV surgery. Methods: Retrospective analysis of our institution’s MV database was performed between November 1998 and March 2019 for all adult patients undergoing isolated MV surgery in our state and 4 neighboring states. Patients for whom address data was missing were excluded. SES was determined by the Area Deprivation Index (ADI). The ADI uses 17 social determinants of heath to estimate the average SES for all US Census Block Groups (mean 1500 people). This score is then nationally indexed from 1 to 100, with lower SES represented by higher scores. Patients were stratified by ADI quartiles. Baseline characteristics and postoperative outcomes were compared between quartiles. Results: Overall, 3,860 surgeries met inclusion criteria during the study period. Of these, 1,795 (46.5%) patients fell into the lowest ADI quartile, 1,216 (31.5%) in the second quartile, 476 (12.3%) in the third quartile, and 344 (8.9%) in the highest quartile. 30-day mortality was not significantly different between ADI quartiles and ADI was not a significant determinate of 30-day survival in a multivariable logistical regression. Figure 1 show the distribution of patient addresses within Census Block Groups as well as 10-year survival by Kaplan-Meier estimates, stratified by ADI quartiles. Cox proportional hazards model revealed that lower SES as determined by ADI was associated with increased 10-year mortality (P = 0.008). Conclusions: Lower SES is associated with worse long-term survival in patients undergoing isolated MV surgery. Social interventions to bridge this survival gap are warranted.

A Socioeconomic Edge Effect: Rational Crime in Small Areas of Sharp Socioeconomic Contrast

2020 ◽  
pp. 002242782094500
Author(s):  
Robert Drew Heinzeroth
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Economic Incentive ◽  
Future Research ◽  
Census Block ◽  
Pattern Theory ◽  
Crime Pattern Theory ◽  
Dependent Variables ◽  
Block Groups ◽  
Crime Pattern

Objectives: To determine whether criminogenic “edges,” as defined by crime pattern theory, exist at points of sharp contrast of socioeconomic status (SES). Methods: The study uses a quasi-experimental design with pattern matching logic. A series of negative binomial regression models separately examine five different crimes with an economic incentive as dependent variables, and five crimes without an economic incentive as nonequivalent dependent variables, to determine whether census block groups of predominantly and comparatively higher SES than the wider surrounding area experience greater reported rational crime than would otherwise be expected. Results: The census block groups of comparatively higher SES located within and/or near areas of predominantly lower SES experienced one of the five crimes with an economic incentive, robberies by firearm, 40 percent more frequently than would otherwise be expected. Conclusions: The study’s findings are partially consistent with its hypothesis, which is grounded in crime pattern, rational choice, routine activities, and social disorganization theories. The findings encourage future research that may extend the definition of an “edge” under crime pattern theory as well as research at the intersection of criminological theories.

Neighbourhood income inequality and property crime

Urban Studies ◽  
2016 ◽  
Vol 55 (1) ◽  
pp. 133-150 ◽  
Author(s):  
Neil Metz ◽  
Mariya Burdina
Keyword(s):  
Income Inequality ◽  
Property Crime ◽  
Block Group ◽  
Census Block ◽  
Census Block Group ◽  
Income Gap ◽  
Group Data ◽  
Block Groups ◽  
The Relationship ◽  
Us Cities

This paper examines the relationship between income inequality and property crime using Census block group data from three US cities: Nashville, TN, Portland, OR and Tucson, AZ. This paper is one of very few to examine this relationship at such a fine geographic level, which is typically less than one square mile in size. We find that income inequality across block groups plays a key role in determining the level of property crime. As the income gap with one’s poorest neighbouring block group widens, the level of property crime in the richer block group increases. Also, the poorest block group in an area tends to experience less property crime, holding all else constant.

scholarly journals U.S. Regional Differences in Physical Distancing: Evaluating Racial and Socioeconomic Divides During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Emma Zang ◽  
Jessica West ◽  
Nathan Kim ◽  
Christina Pao
Keyword(s):  
Urban Areas ◽  
Regional Differences ◽  
Census Block ◽  
The South ◽  
Regional Heterogeneity ◽  
Census Block Group ◽  
South West ◽  
Region Of Residence ◽  
Block Groups ◽  
At Home

AbstractHealth varies by U.S. region of residence. Despite regional heterogeneity in the outbreak of COVID-19, regional differences in physical distancing behaviors over time are relatively unknown. This study examines regional variation in physical distancing trends during the COVID-19 pandemic and investigates variation by race and socioeconomic status (SES) within regions.Data from the 2015-2019 five-year American Community Survey were matched with anonymized location pings data from over 20 million mobile devices (SafeGraph, Inc.) at the Census block group level. We visually present trends in the stay-at-home proportion by Census region, race, and SES throughout 2020 and conduct regression analyses to statistically examine these patterns.From March to December, the stay-at-home proportion was highest in the Northeast (0.25 in March to 0.35 in December) and lowest in the South (0.24 to 0.30). Across all regions, the stay-at-home proportion was higher in block groups with a higher percentage of Blacks, as Blacks disproportionately live in urban areas where stay-at-home rates were higher (0.009 [CI: 0.008, 0.009]). In the South, West, and Midwest, higher-SES block groups stayed home at the lowest rates pre-pandemic; however, this trend reversed throughout March before converging in the months following. In the Northeast, lower-SES block groups stayed home at comparable rates to higher-SES block groups during the height of the pandemic but diverged in the months following.Differences in physical distancing behaviors exist across U.S. regions, with a pronounced Southern and rural disadvantage. Results can be used to guide reopening and COVID-19 mitigation plans.

scholarly journals Spatial variation of pneumonia hospitalization risk in Twin Cities metro area, Minnesota

2017 ◽  
Vol 145 (15) ◽  
pp. 3274-3283 ◽  
Author(s):  
P. Y. IROH TAM ◽  
B. KRZYZANOWSKI ◽  
J. M. OAKES ◽  
L. KNE ◽  
S. MANSON
Keyword(s):  
Environmental Factors ◽  
Ethnic Diversity ◽  
Poisson Regression ◽  
Diversity Index ◽  
Targeted Prevention ◽  
Census Block ◽  
Solar Insolation ◽  
Increased Risk ◽  
Block Groups ◽  
Fourth Quartile

SUMMARYFine resolution spatial variability in pneumonia hospitalization may identify correlates with socioeconomic, demographic and environmental factors. We performed a retrospective study within the Fairview Health System network of Minnesota. Patients 2 months of age and older hospitalized with pneumonia between 2011 and 2015 were geocoded to their census block group, and pneumonia hospitalization risk was analyzed in relation to socioeconomic, demographic and environmental factors. Spatial analyses were performed using Esri's ArcGIS software, and multivariate Poisson regression was used. Hospital encounters of 17 840 patients were included in the analysis. Multivariate Poisson regression identified several significant associations, including a 40% increased risk of pneumonia hospitalization among census block groups with large, compared with small, populations of ⩾65 years, a 56% increased risk among census block groups in the bottom (first) quartile of median household income compared to the top (fourth) quartile, a 44% higher risk in the fourth quartile of average nitrogen dioxide emissions compared with the first quartile, and a 47% higher risk in the fourth quartile of average annual solar insolation compared to the first quartile. After adjusting for income, moving from the first to the second quartile of the race/ethnic diversity index resulted in a 21% significantly increased risk of pneumonia hospitalization. In conclusion, the risk of pneumonia hospitalization at the census-block level is associated with age, income, race/ethnic diversity index, air quality, and solar insolation, and varies by region-specific factors. Identifying correlates using fine spatial analysis provides opportunities for targeted prevention and control.

scholarly journals The Redistributional Impact of Nonlinear Electricity Pricing

2012 ◽  
Vol 4 (3) ◽  
pp. 56-90 ◽  
Author(s):  
Severin Borenstein
Keyword(s):  
Low Income ◽  
Census Data ◽  
Electricity Pricing ◽  
Census Block ◽  
Billing Data ◽  
Household Level ◽  
Price Increases ◽  
Wealth Redistribution ◽  
Block Groups ◽  
Marginal Price

Electricity regulators often mandate increasing-block pricing (IBP)—i.e., marginal price increases with the customer's average daily usage—to protect low-income households from rising costs. IBP has no cost basis, raising a classic conflict between efficiency and distributional goals. Combining household-level utility billing data with census data on income, I find that IBP in California results in modest wealth redistribution, but creates substantial deadweight loss relative to the transfers. I also show that a common approach to studying income distribution effects by using median household income within census block groups may be misleading. (JEL D31, L11, L51, L94, L98, Q41, Q48)

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