scholarly journals Neighborhood Change and Residential Instability in Oakland

2021 ◽  
pp. 1-107
Author(s):  
Jackelyn Hwang ◽  
◽  
Vineet Gupta ◽  
Bina Shrimali ◽  
◽  
...  

Affordable housing is critical to ensuring healthy and resilient communities and broad access to economic opportunity. In this report, we examine neighborhood change and residential instability in the City of Oakland over the past two decades. We employ multiple data sources, including individual-level data from the Federal Reserve Bank of New York Consumer Credit Panel/Equifax data. We analyze historical and contemporary data to understand patterns of residential instability, and we identify which residents and areas are most likely to experience heightened challenges in the context of the COVID-19 pandemic. Our results show that lower-SES residents experience residential instability in different ways in different parts of Oakland, suggesting the need for more geographically targeted strategies that focus on stabilizing lower-SES residents and address the multiple ways in which lower-SES residents navigate limited affordable housing.

2007 ◽  
Vol 2 (4) ◽  
pp. 319-340 ◽  
Author(s):  
Jay P. Greene ◽  
Marcus A. Winters

In 2002, Florida adopted a test-based promotion policy in the third grade in an attempt to end social promotion. Similar policies are currently operating in Texas, New York City, and Chicago and affect at least 17 percent of public school students nationwide. Using individual-level data on the universe of public school students in Florida, we analyze the impact of grade retention on student proficiency in reading one and two years after the retention decision. We use an instrumental variable (IV) approach made available by the relatively objective nature of Florida's policy. Our findings suggest that retained students slightly outperformed socially promoted students in reading in the first year after retention, and these gains increased substantially in the second year. Results were robust across two distinct IV comparisons: an across-year approach comparing students who were essentially separated by the year in which they happened to have been born, and a regression discontinuity design.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Jennifer Dolatshahi ◽  
Lara Maldjian ◽  
Alice Welch ◽  
Casey Fulmer ◽  
Emily Winkelstein

ObjectiveDescribe the development of an individual-level tracking system for community-based naloxone dispensing as part of New York City’s (NYC) comprehensive plan to reduce overdose deaths. We present data from the first year of the initiative to illustrate results of the tracking system and describe the potential impact on naloxone dispensing program.IntroductionThe number of unintentional overdose deaths in New York City (NYC) has increased for seven consecutive years. In 2017, there were 1,487 unintentional drug overdose deaths in NYC. Over 80% of these deaths involved an opioid, including heroin, fentanyl, and prescription pain relievers.1 As part of a comprehensive strategy to reduce overdose mortality in NYC, the NYC Department of Health and Mental Hygiene’s (DOHMH) Overdose Education and Naloxone Distribution (OEND) Program makes naloxone kits available to laypeople free-of-charge through registered Opioid Overdose Prevention Programs (OOPPs). Naloxone kits contain two doses of naloxone and educational materials. The OEND Program distributes kits to registered OOPPs, which then dispense kits to individuals via community-based trainings. In this context, distribution refers to kits shipped to programs, whereas dispensing refers to kits given to individuals. Increased NYC funding has enabled recruitment of more OOPPs—including syringe exchange programs, public safety agencies, shelters, drug treatment programs, health care facilities, and other community-based programs—and greater dispensing of naloxone kits to laypeople. Naloxone distribution has undergone a dramatic expansion, from 2,500 kits in 2009 to 61,706 kits in 2017.2 In 2018, DOHMH aims to distribute more than 100,000 kits to OOPPs.In order to target naloxone dispensing to neighborhoods in NYC with the highest overdose burden, we developed a tracking system able to capture individual-level geographic data about naloxone kit recipients. Prior to the development of the tracking system, DOHMH collected quarterly, aggregate-level naloxone dispensing data from OOPPs. These data included only the OOPPs’ ZIP Codes but not recipient residence. OOPP ZIP Code was used as a proxy for kits dispensed to individuals. Without individual-level geographic information, however, we could not determine whether naloxone kit dispensing reached people in neighborhoods with high overdose mortality rates. To overcome these barriers, DOHMH developed a comprehensive but flexible individual-level data collection method.MethodsTo both capture individual-level data from each naloxone recipient in NYC and meet the needs of OOPPs’ varying capacities, dispensing settings, and any existing organizational data requirements, DOHMH devised a two-pronged data collection system. The Naloxone Recipient Form (NRF) system, launched January 1, 2018, primarily employs a short paper form (or NRF) to collect dispensing data. The NRF is a one-page document designed with the OpenText™ TeleForm processing application. It captures individual data and OOPP information. Individual data include: reason for obtaining a kit, whether first-time receipt of a kit, age, and ZIP Code of residence. OOPP information includes: program name and ZIP Code of dispensing location. Forms are completed by OOPPs and recipients at OEND trainings, compiled by the OOPP, then scanned back to DOHMH. We then import forms into TeleForm, which reads the NRF data directly into a database without need for manual data entry and only moderate need for data verification. The second component of the NRF system allows larger organizations and dispensers in clinical settings with electronic health records to submit data extracts to DOHMH that are pulled directly from organizations’ data systems. Together with these organizations, we customized these data extracts for direct importation into the master NRF database.To demonstrate improvements in our tracking of naloxone dispensing after the development of the NRF system, we mapped the geographic spread of naloxone kits in NYC during the first three months of 2018 (Q1 2018) by recipients’ ZIP Code of residence and OOPPs’ ZIP Codes.ResultsA total of 138 OOPPs2 reported any dispensing from January to June, 2018, of which 107 reported individual-level data using the NRF system, accounting for 27,899 kits dispensed to 23,610 individual recipients.3 Logistical barriers to implementing the NRF system varied among OOPPs, thus the data underestimate citywide dispensing during this time period. Some OOPPs experienced delays in reporting recipient-level data until a more-tailored data collection strategy was devised. Visual inspection of OOPP-level distribution and individual-level dispensing maps using Q1 2018 data (See Figures 1 and 2) demonstrate the difference between OOPP-level distribution data and individual-level dispensing data. Mapping data indicate that the largest numbers of naloxone kits were dispensed to people in neighborhoods with the highest burden of overdose in NYC.ConclusionsThe NRF system provides DOHMH, as well as OOPPs in NYC, with individual-level data to more accurately track naloxone dispensing citywide. The simplicity and flexibility of the NRF system allows for timely and geographically precise data collection from dozens of organizations across NYC with little or no additional cost to OOPPs. As new organizations have registered as OOPPs, particularly large health care or human services systems, DOHMH has developed new methods for incorporating dispensing data into the NRF system. Ongoing communication with OOPPs of all types and an iterative data collection improvement process have ensured that the system remains comprehensive while also being responsive to individual program’s capacities and data needs.References1. Nolan ML, Tuazon E, Blachman-Forshay J, Paone D. Unintentional Drug Poisoning (Overdose) Deaths in New York City, 2000-2017. New York City Department of Health and Mental Hygiene: Epi Data Brief (104); September 2018.2. NYC DOHMH Opioid Overdose Prevention Program (OOPP) Database. All data is provisional.3. NYC DOHMH Naloxone Recipient Form (NRF) Database. All data is provisional. 


Author(s):  
Jingjing Wang ◽  
Xueying Wu ◽  
Ruoyu Wang ◽  
Dongsheng He ◽  
Dongying Li ◽  
...  

The coronavirus disease 2019 pandemic has stimulated intensive research interest in its transmission pathways and infection factors, e.g., socioeconomic and demographic characteristics, climatology, baseline health conditions or pre-existing diseases, and government policies. Meanwhile, some empirical studies suggested that built environment attributes may be associated with the transmission mechanism and infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, no review has been conducted to explore the effect of built environment characteristics on the infection risk. This research gap prevents government officials and urban planners from creating effective urban design guidelines to contain SARS-CoV-2 infections and face future pandemic challenges. This review summarizes evidence from 25 empirical studies and provides an overview of the effect of built environment on SARS-CoV-2 infection risk. Virus infection risk was positively associated with the density of commercial facilities, roads, and schools and with public transit accessibility, whereas it was negatively associated with the availability of green spaces. This review recommends several directions for future studies, namely using longitudinal research design and individual-level data, considering multilevel factors and extending to diversified geographic areas.


Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 557
Author(s):  
Elena Raptou

This study investigated the relationship of behavioral factors, such as snack choices, obesity stereotypes and smoking with adolescents’ body weight. Individual-level data for 1254 Greek youths were selected via a formal questionnaire. Snack choices seem to be gender specific with girls showing a stronger preference for healthier snacks. Frequent consumption of high-calorie and more filling snacks was found to increase Body Mass Index (BMI) in both genders. Fruit/vegetable snacks were associated with lower body weight in females, whereas cereal/nut snacks had a negative influence in males’ BMI. The majority of participants expressed anti-fat attitudes and more boys than girls assigned positive attributes to lean peers. The endorsement of the thin-ideal was positively associated with the BMI of both adolescent boys and girls. This study also revealed that neglecting potential endogeneity issues can lead to biased estimates of smoking. Gender may be a crucial moderator of smoking–BMI relationships. Male smokers presented a higher obesity risk, whereas female smokers were more likely to be underweight. Nutrition professionals should pay attention to increase the acceptance of healthy snack options. Gender differences in the influence of weight stereotypes and smoking on BMI should be considered in order to enhance the efficacy of obesity prevention interventions.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Chen ◽  
Wei Hou ◽  
Sina Rashidian ◽  
Yu Wang ◽  
Xia Zhao ◽  
...  

AbstractOpioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP). To discover trends and patterns of opioid poisoning and the demographic and regional disparities, we analyzed large scale patient visits data in New York State (NYS). Demographic, spatial, temporal and correlation analyses were performed for all OP patients extracted from the claims data in the New York Statewide Planning and Research Cooperative System (SPARCS) from 2010 to 2016, along with Decennial US Census and American Community Survey zip code level data. 58,481 patients with at least one OP diagnosis and a valid NYS zip code address were included. Main outcome and measures include OP patient counts and rates per 100,000 population, patient level factors (gender, age, race and ethnicity, residential zip code), and zip code level social demographic factors. The results showed that the OP rate increased by 364.6%, and by 741.5% for the age group > 65 years. There were wide disparities among groups by race and ethnicity on rates and age distributions of OP. Heroin and non-heroin based OP rates demonstrated distinct temporal trends as well as major geospatial variation. The findings highlighted strong demographic disparity of OP patients, evolving patterns and substantial geospatial variation.


2021 ◽  
pp. 001041402110243
Author(s):  
Carolina Plescia ◽  
Sylvia Kritzinger

Combining individual-level with event-level data across 25 European countries and three sets of European Election Studies, this study examines the effect of conflict between parties in coalition government on electoral accountability and responsibility attribution. We find that conflict increases punishment for poor economic performance precisely because it helps clarify to voters parties’ actions and responsibilities while in office. The results indicate that under conditions of conflict, the punishment is equal for all coalition partners when they share responsibility for poor economic performance. When there is no conflict within a government, the effect of poor economic evaluations on vote choice is rather low, with slightly more punishment targeted to the prime minister’s party. These findings have important implications for our understanding of electoral accountability and political representation in coalition governments.


Author(s):  
Catalina Amuedo-Dorantes ◽  
Neeraj Kaushal ◽  
Ashley N. Muchow

AbstractUsing county-level data on COVID-19 mortality and infections, along with county-level information on the adoption of non-pharmaceutical interventions (NPIs), we examine how the speed of NPI adoption affected COVID-19 mortality in the United States. Our estimates suggest that adopting safer-at-home orders or non-essential business closures 1 day before infections double can curtail the COVID-19 death rate by 1.9%. This finding proves robust to alternative measures of NPI adoption speed, model specifications that control for testing, other NPIs, and mobility and across various samples (national, the Northeast, excluding New York, and excluding the Northeast). We also find that the adoption speed of NPIs is associated with lower infections and is unrelated to non-COVID deaths, suggesting these measures slowed contagion. Finally, NPI adoption speed appears to have been less effective in Republican counties, suggesting that political ideology might have compromised their efficacy.


2021 ◽  
pp. 003329412110268
Author(s):  
Jaime Ballard ◽  
Adeya Richmond ◽  
Suzanne van den Hoogenhof ◽  
Lynne Borden ◽  
Daniel Francis Perkins

Background Multilevel data can be missing at the individual level or at a nested level, such as family, classroom, or program site. Increased knowledge of higher-level missing data is necessary to develop evaluation design and statistical methods to address it. Methods Participants included 9,514 individuals participating in 47 youth and family programs nationwide who completed multiple self-report measures before and after program participation. Data were marked as missing or not missing at the item, scale, and wave levels for both individuals and program sites. Results Site-level missing data represented a substantial portion of missing data, ranging from 0–46% of missing data at pre-test and 35–71% of missing data at post-test. Youth were the most likely to be missing data, although site-level data did not differ by the age of participants served. In this dataset youth had the most surveys to complete, so their missing data could be due to survey fatigue. Conclusions Much of the missing data for individuals can be explained by the site not administering those questions or scales. These results suggest a need for statistical methods that account for site-level missing data, and for research design methods to reduce the prevalence of site-level missing data or reduce its impact. Researchers can generate buy-in with sites during the community collaboration stage, assessing problematic items for revision or removal and need for ongoing site support, particularly at post-test. We recommend that researchers conducting multilevel data report the amount and mechanism of missing data at each level.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Takashi Oshio ◽  
Hiromi Kimura ◽  
Toshimi Nishizaki ◽  
Takashi Omori

Abstract Background Area-level deprivation is well known to have an adverse impact on mortality, morbidity, or other specific health outcomes. This study examined how area-level deprivation may affect self-rated health (SRH) and life satisfaction (LS), an issue that is largely understudied. Methods We used individual-level data obtained from a nationwide population-based internet survey conducted between 2019 and 2020, as well as municipality-level data obtained from a Japanese government database (N = 12,461 living in 366 municipalities). We developed multilevel regression models to explain an individual’s SRH and LS scores using four alternative measures of municipality-level deprivation, controlling for individual-level deprivation and covariates. We also examined how health behavior and interactions with others mediated the impact of area-level deprivation on SRH and LS. Results Participants in highly deprived municipalities tended to report poorer SRH and lower LS. For example, when living in municipalities falling in the highest tertile of municipality-level deprivation as measured by the z-scoring method, SRH and LS scores worsened by a standard deviation of 0.05 (p < 0.05) when compared with those living in municipalities falling in the lowest tertile of deprivation. In addition, health behavior mediated between 17.6 and 33.1% of the impact of municipality-level deprivation on SRH and LS, depending on model specifications. Conclusion Results showed that area-level deprivation modestly decreased an individual’s general health conditions and subjective well-being, underscoring the need for public health policies to improve area-level socioeconomic conditions.


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