American Community Survey Research Articles

Using geographic effect measure modification to examine socioeconomic-related surface temperature disparities in New York City.

Lower socioeconomic (SES) communities are more likely to be situated in urban heat islands and have higher heat exposures than their higher SES counterparts, and this inequality is expected to intensify due to climate change. To examine the relationship between surface temperatures and SES in New York City (NYC) by employing a novel analytical approach. Through incorporating modifiable features, this study aims to identify potential locations where mitigation interventions can be implemented to reduce heat disparities associated with SES. Using the 2013-2017 American Community Survey, U.S Landsat-8 Analysis Ready Data surface temperatures (measured on 8/12/2016), and the NYC Land Cover Dataset at the census tract level (2098 tracts), this study examines the association between two components of tract-level SES (percentage of individuals living below the poverty line and the percentage of individuals without a high school degree) and summer day surface temperature in NYC. First, we examine this association with an unrestricted NYC linear regression, examining the city-wide association between the two SES facets and summer surface temperature, with additional models adjusting for altitude, shoreline, and nature-cover. Then, we assess geographic effect measure modification by employing the same models to three supplemental regression model strategies (borough-restricted and community district-restricted linear regressions, and geographically weighted regression (GWR)) that examined associations within smaller intra-city areas. All regression strategies identified areas where lower neighborhood SES composition is associated with higher summer day surface temperatures. The unrestricted NYC regressions revealed widespread disparities, while the borough-restricted and community district-restricted regressions identified specific political boundaries within which these disparities existed. The GWR, addressing spatial autocorrelation, identified significant socioeconomic heat disparities in locations such as northwest Bronx, central Brooklyn, and uptown Manhattan. These findings underscore the need for targeted policies and community interventions, including equitable urban planning and cooling strategies, to mitigate heat exposure in vulnerable neighborhoods. This study redefines previous research on urban socioeconomic disparities in heat exposure by investigating both modifiable (nature cover) and non-modifiable (altitude and shoreline) built environment factors affecting local temperatures at the census tract level in New York City. Through a novel analytical approach, the research aims to highlight intervention opportunities to mitigate heat disparities related to socioeconomic status. By examining the association between surface temperatures and socioeconomic status, as well as investigating different geographic and governmental scales, this study offers actionable insights for policymakers and community members to address heat exposure inequalities effectively across different administrative boundaries. The objective is to pinpoint potential sites for reducing socioeconomic heat exposure disparities at various geographic and political levels.

Neighborhood Diversity Is Good for Your Health: An Example of Racial/Ethnic Integration and Preterm Birth in Texas.

Racial concentration of neighborhoods is often associated with the risk of preterm birth (PTB) for women. This study examined differences between racially diverse and racially concentrated neighborhoods when examining preterm birth. Individual-level data were obtained from Texas natality files for 2009-2011, and neighborhood-level (i.e., census tract) data were obtained from the decennial census in 2010 and the American Community Survey 2005-2009. We used multilevel modeling to assess the association between neighborhood racial diversity and odds of PTB, after controlling for individual characteristics, neighborhood poverty, and population density. We found that neighborhood racial diversity and concentration matter for PTB. Results suggest that systemic racism is still key to understanding PTB. Furthermore, findings support policies that prevent displacement from gentrification of diverse neighborhoods and promote equal access to health-related resources for women in predominantly Black, Hispanic, and/or immigrant neighborhoods.

The TBI Model Systems Neighborhood Socioeconomic Disadvantage Index (TBIMS-NSDI): Development and Comparison to Individual Socioeconomic Characteristics.

To create a census-based composite neighborhood socioeconomic deprivation index (NSDI) from geocoded residential addresses and to quantify how NSDI aligns with individual-level socioeconomic factors among people with traumatic brain injury (TBI). Community. People enrolled in the TBI Model Systems National Database (TBIMS NDB). Secondary analysis of a longitudinal cohort study. The TBIMS-NSDI was calculated at the census tract level for the United States population based on a principal components analysis of eight census tract-level variables from the American Community Survey. Individual socioeconomic characteristics from the TBIMS NDB were personal household income, education (years), and unemployment status. Neighborhood:Individual NSDI residuals represent the difference between predicted neighborhood disadvantage based on individual socioeconomic characteristics versus observed neighborhood disadvantage based on the TBIMS-NSDI. A single principal component was found to encompass the eight socioeconomic neighborhood-level variables. It was normally distributed across follow-up years 2, 5, and 10 post-injury in the TBIMS NDB. In all years, the TBIMS-NDSI was significantly associated with individual-level measures of household income and education but not unemployment status. Males, persons of Black and Hispanic background, Medicaid recipients, persons with TBI caused by violence, and those living in urban areas, as well as in the Northeast or Southern regions of the United States, were more likely to have greater neighborhood disadvantage than predicted based on their individual socioeconomic characteristics. The TBIMS-NSDI provides a neighborhood-level indicator of socioeconomic disadvantage, an important social determinant of outcomes from TBI. The Neighborhood:Individual NSDI residual adds another dimension to the TBIMS-NSDI by summarizing how a person's socioeconomic status aligns with their neighborhood socioeconomics. Future studies should evaluate how both measures affect TBI recovery and life quality. Research studying neighborhood socioeconomic disadvantage may improve our understanding of how systemic adversity influences outcomes after TBI.

Occupational inequalities in mortality from cardiovascular disease, 2020-2021.

In recent years previous declines in cardiovascular disease (CVD) have stalled. There are occupational risk factors for CVD mortality. This study seeks to examine inequalities in CVD mortality for working-age adults in the United States by occupation. Death certificate data for CVD deaths were obtained from the National Center for Health Statistics. Occupation data from these death certificates were coded to major occupation groups. Using information about the number of workers employed in these occupations obtained from the American Community Survey, we calculated mortality rates and rate ratios (RRs), adjusted for covariates associated with CVD mortality. After adjusting for age, sex, race/ethnicity, and educational attainment, workers in 11 occupations had significantly elevated RRs: food preparation and serving; construction and extraction; arts, design, entertainment, sports, and media; life, physical, and social science; farming, fishing, and forestry; legal; protective services; building and grounds cleaning and maintenance; healthcare practitioners and technical; personal care and service; and community and social services. Occupation appears to be a significant predictor of CVD mortality. Further research is needed to assess how occupational risk factors contribute to changing trends for CVD mortality. Interventions are needed to address workplace risk factors for CVD.

Devaluation for whom? Feminization and wages in an economically polarized labor market, 2003–2019

Abstract Scholars have found that as the proportion of female workers in an occupation grows, wages generally decline. Yet, we know little about how this gender inequality intersects with other labor market inequalities. This study evaluates the feminization-wage relationship of an increasingly economically polarized post-2000 US labor market. First, I hypothesize that the negative effect of feminization on wages has diminished in high-skilled occupations due to the declining prejudice against (highly educated) women and increasing requirements for higher education, which functions as a form of social closure. Second, because of the increasing demand for “people skills” in higher-skilled occupations and their association with women, workers in higher-skilled occupations that require these skills may experience positive effects of feminization on wages. Not all people skills, however, are associated with women and similarly rewarded. Thus, I examine three people skills—persuasion, managerial, and sociability—that have different gender stereotypes. I test hypotheses using occupational-level fixed-effects models with individual-level data from the American Community Survey 2003–2019 (N = 15,996,526) and time-varying occupational-level data from the Occupational Information Network 2003–2019 (N = 460). Results show that for workers in occupations requiring more than sixteen years of education, feminization corresponds with higher wages. Additionally, the positive feminization-wage relationship is larger in occupations with a high demand for a gender-neutral people skill, persuasion. This moderation effect is not found for sociability and managerial skills, which are associated with women and men, respectively. This study calls for greater attention to how labor market polarization has shaped gender inequality.

Development of Composite Measures of Neighborhood Economic Factors for Use in Spinal Cord Injury Outcomes Studies: A Spinal Cord Injury Model Systems Database Study

ObjectiveTo develop composite measures of neighborhood economic factors for use with the national Spinal Cord Injury Model Systems (SCIMSs) database in cross-sectional and longitudinal investigations of the social determinants of health. DesignSecondary data analysis of administrative data from the 2009, 2014, and 2019 American Community Survey (ACS) 5-year estimates and survey data collected for the SCIMS database. SettingCommunity. ParticipantsThe validity of the neighborhood economic measures developed from the ACS data was tested with a sample of SCIMS participants who completed a follow-up interview between 2017 and 2021 (N=8,130). The predictive validity of the neighborhood measures was assessed with a subsample of cases with complete data on the outcome and covariate measures (N=6,457). InterventionsNot applicable. Main Outcome MeasuresA binary measure of self-rated health status (1=poor/fair health; 0=good/very good/excellent). ResultsA combination of panel review and data reduction techniques yielded 2 distinct measuring neighborhood socioeconomic status (SES) and neighborhood socioeconomic disadvantage that were validated using 3 waves of ACS data and the SCIMS data. The odds of reporting poor health were lower among people living in moderate- and high-SES neighborhoods and highest among people living in moderately and highly disadvantaged neighborhoods. The negative association between neighborhood SES and poor health was fully attenuated by differences in participants’ individual demographic and economic characteristics whereas the positive association between neighborhood disadvantage and poor health persisted after adjusting for individual differences. ConclusionsThe two composite measures of neighborhood economic factors developed by this study are robust in samples from different periods of time and valid for use with the SCIMS database. Future investigations conducting surveillance of the needs of the SCI population using this resource may consider using these measures to assess the effect of the social determinants of health in outcomes after SCI.

Race/Ethnicity and Employment Insecurity: Impacts of COVID-19 on the US Labor Force and Beyond

Using the Household Pulse Survey and American Community Survey, this study examines employment insecurity experienced across different racial/ethnic groups of the U.S. labor force under the pandemic disruptions. It highlights significant employment security disparities based on race, ethnicity, and income during the pandemic. However, there are no significant gender and racial disparities within the lowest income group when controlling for other conditions. In contrast, gender and racial disparities in EI are much more pronounced among mid-to-high income groups. Non-White individuals were disproportionately affected by job loss due to health and COVID-related employment issues, unlike Whites who faced unemployment more due to other factors. This pattern was more evident among lower-income groups. The trends shifted in later stages, with high-income Black and Hispanic workers becoming more likely to be unemployed due to non-health and non-employment reasons. Middle-income workers across all races were least likely to stop working for reasons other than COVID-related health or employment issues. In addition, regardless race or ethnicity, women more likely to be unemployed due to health reasons and less so due to employment issues compared to men, and the gender disparities increased with higher household incomes. We propose that the apparent immediate effects of the pandemic are actually indicative of deeper, systemic issues within the U.S. labor market, specifically the occupational segregation tied to race/ethnicity, gender, and class. Recovery efforts must take a holistic approach and integrate economic development policies, workforce development strategies, and social policies targeting poverty alleviation, health disparities, and people of color.

Maintaining disorder: estimating the association between policing and psychiatric hospitalization among youth in New York City by neighborhood racial composition, 2006-2014.

To assess whether neighborhood-level measures of policing are spatio-temporally associated with psychiatric hospialization among adolescents and young adults in New York City, and whether this association varies by neighborhood racial composition. We derived population-based measures of policing from the New York City Police Department (NYPD), psychiatric hospitalization from Statewide Planning and Research Cooperative System (SPARCS) data, and socio-demographic data from the American Community Survey (ACS), aggregated by month and ZIP Code Tabulation Area (ZCTA) from 2006 to 2014. Multi-level negative binomial regression models assessed hospitalization-time of youth aged 10-24 as the dependent variable and the rate of policing events as the primary independent variable, adjusting for neighborhood poverty, unemployment, and educational attainment. Multiplicative interaction was assessed between policing and tertiles of the percentage of Black residents. A total of 11,900,192 policing incidents and 2,118,481 person-days of hospitalization were aggregated to 19,440 ZCTA-months. After adjusting for neighborhood-level sociodemographic characteristics, an increase in one policing incident per 1,000 residents was associated with a 0.3% increase in the rate of youth psychiatric hospitalization time (IRR 1.003 [1.001-1.005]). Neighborhood racial composition modified this effect; not only was the rate of psychiatric hospitalization and policing higher in neighborhoods with a higher proportion of Black residents, but the association between these was also significantly higher in neighorhoods with a larger share of Black residents compared with predominantly non-Black neighborhoods. Neighborhoods experiencing higher rates of policing during the study period experienced higher burdens of psychiatric hospitalization among adolescent and young adult residents. This association was larger in neighborhoods of color which have been disproportionately targeted by "hot spot" and order-maintenance policing practices and policies.

The Impact of Social Deprivation on Anterior Urethral Stricture Recurrence After Urethroplasty - A Trauma and Urologic Reconstructive Network of Surgeons (TURNS) Analysis.

Several factors influence recurrence after urethral stricture repair. The impact of socioeconomic factors on stricture recurrence after urethroplasty is poorly understood. This study aims to assess the impact that social deprivation, an area-level measure of disadvantage, has on urethral stricture recurrence after urethroplasty. We performed a retrospective review of patients undergoing urethral reconstruction by surgeons participating in a collaborative research group. Home zip code was used to calculate Social Deprivation Indices (SDI; 0-100), which quantifies the level of disadvantage across several sociodemographic domains collected in the American Community Survey. Patients without zip code data were excluded from the analysis. The Cox Proportional Hazards model was used to study the association between SDI and the hazard of functional recurrence, adjusting for stricture characteristics as well as age and body mass index. Median age was 46.0 years with a median follow up of 367 days for the 1452 men included in the study. Patients in the fourth SDI quartile (worst social deprivation) were more likely to be active smokers with traumatic and infectious strictures compared to the first SDI quartile. Patients in the fourth SDI quartile had 1.64 times the unadjusted hazard of functional stricture recurrence vs patients in the first SDI quartile (95% CI 1.04-2.59). Compared to anastomotic ± excision, substitution only repair had 1.90 times the unadjusted hazard of recurrence. The adjusted hazard of recurrence was 1.08 per 10-point increase in SDI (95% CI 1.01-1.15, P = .027). Patient social deprivation identifies those at higher risk for functional recurrence after anterior urethral stricture repair, offering an opportunity for preoperative counseling and postoperative surveillance. Addressing these social determinants of health can potentially improve outcomes in reconstructive surgery.

Associations between Structural Racism, Environmental Burden, and Cancer Rates: An Ecological Study of US Counties.

In this study, we examined associations between county-level measures of structural racism and county-level cancer incidence and mortality rates between race groups while accounting for factors associated with cancer rates and county-level measures of environmental burden. To explore this relationship, we conducted multiple linear regression analyses. Data for these analyses came from an index of county-level structural racism and publicly available data on 2015 to 2019 age-adjusted cancer rates from the US Cancer Statistics Data Visualization Tool, 2019 County Health Rankings and Roadmaps, the Environmental Protection Agency's 2006 to 2010 Environmental Quality Index, and 2015 to 2019 estimates from the US Census American Community Survey. County-level structural racism was associated with higher county cancer incidence rates among Black (adjusted incidence rate: 17.4, 95% confidence interval [95% CI]: 9.3, 25.5) and Asian/Pacific Islander populations (adjusted incidence rate: 9.3, 95% CI: 1.8, 16.9) and higher mortality rates for American Indian/Alaskan Native (adjusted mortality rate [AMR]: 17.4, 95% CI: 4.2, 30.6), Black (AMR: 11.9, 95% CI: 8.9, 14.8), and Asian/Pacific Islander (AMR: 4.7, 95% CI: 1.3, 8.1) populations than White populations. Our findings highlight the detrimental impact of structural racism on cancer outcomes among minoritized populations. Strategies aiming to mitigate cancer disparities must embed processes to recognize and address systems, policies, laws, and norms that create and reproduce patterns of discrimination.

Association Between Greater Social Vulnerability and Delayed Glaucoma Surgery

PurposeTiming of surgical intervention in glaucoma is crucial to preserving sight. While ocular characteristics that increase surgical risk are known, the impact of neighborhood-level social risk factors such as the Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) on time to glaucoma surgery is unknown. The objective of this study was to evaluate the association between SVI or ADI scores and the timing of glaucoma surgical intervention. DesignRetrospective cohort study. MethodsAdult subjects with open-angle glaucoma were identified from the Bascom Palmer Glaucoma Repository using International Classification of Disease-10 codes. Subject demographics, ocular characteristics, and standard automated perimetry (SAP) data were extracted. Geocoded data were obtained using subject residences and American Community Survey data. Univariable and multivariable time-to-event survival analyses using accelerated failure time (AFT) models were completed to evaluate whether geocoded SVI and ADI scores accelerated or delayed time to glaucoma surgery from initial glaucoma diagnosis in the electronic health record. ResultsA total of 10,553 eyes from 6,934 subjects were evaluated, of which 637 eyes (6.0%) from 568 subjects (8.2%) underwent glaucoma surgery. Mean age was 68.3±13.5 years, with 57.9% female, 21.5% Black, and 34.5% Hispanic subjects. Mean follow-up time was 5.0±2.1 years, with time to surgery of 3.2±1.9 years. Multivariable AFT models demonstrated that higher mean intraocular pressure (time ratio (TR) 0.27 per 5 mmHg higher; 95% CI: 0.23-0.31, p<0.001), faster SAP rate of progression (TR 0.74 per 0.5 dB/year faster; 95% CI: 0.69-0.78, p<0.001), moderate (TR 0.69; 95% CI: 0.56-0.85, p<0.001) or severe baseline severity (TR 0.39; 95% CI: 0.32-0.47, p<0.001), and thinner central corneal thickness (TR 0.85 per 50µm thinner; 95% CI: 0.77-0.95, p=0.003) all accelerated time to surgery. In contrast, overall SVI delayed surgery (TR 1.11 per 25% increase; 95% CI: 1.03-1.20, p=0.006). Specifically, SVI Themes 1 (TR 1.08; 95% CI: 1.01-1.17, p=0.037) and 4 (TR 1.11; 95% CI: 1.03-1.19, p=0.006) were significant. Patients from the most deprived neighborhoods (highest national ADI quartile) had a 68% increase in time to surgery compared to the least deprived quartile (TR 1.68; 95% CI: 1.20-2.36, p=0.002). ConclusionsResidence in areas with higher SVI or ADI scores was associated with delayed glaucoma surgery after controlling for demographic and ocular parameters. Awareness of such disparities can guide initiatives aimed at achieving parity in health outcomes.

Downscaling occupational employment data from the state to the Census tract level

The lack of detailed occupational employment data at more granular geographic levels presents significant challenges in forecasting and analyzing local and regional employment changes in the era of the new technological revolution. This study aims to develop detailed occupational employment data by downscaling state-level employment information to the Census tract level. We introduce two downscaling algorithms that leverage employment, population, and sociodemographic composition data sourced from the American Community Survey, the Current Population Survey, and the Occupational Employment and Wage Statistics. This approach allows us to create a tract-level employment dataset covering 808 occupations. Such data are crucial for examining the effects of expected technological and demographic shifts on employment at this scale, which is critical for understanding tax base implications and job mobility opportunities. We demonstrate the value of these datasets by examining employment projections for two occupations anticipated to decline due to technological advancements in the near future.

From Service to Struggle: Exploring the Link Between Service-Connected Disability and Poverty Among Veteran Households

ABSTRACT I examine the relationship between service-connected disability and poverty among veteran households using data from the 2009–2019 1-year American Community Survey. I find that service-connected disability is an important mechanism that helps veteran households avoid poverty. This is evidenced by a strong monotonic relationship whereby veteran households with the most severe service-connected disability have the lowest predicted likelihood of poverty. However, evidence suggests service-connected disability is associated with an increased likelihood of deep poverty among already impoverished households. Within this context, veteran households with the most severe service-connected disability have the highest predicted likelihood of deep poverty.

Individualism and stock market participation

ABSTRACT This paper investigates the relation between a cultural orientation toward individualism and household stock market participation. We adopt an epidemiological approach to establish causality. Employing large samples of second-generation immigrants in the U.S. and Europe, we focus on how the cultural heritage of individuals from different origins influences their engagement in stock market participation. To verify this relationship, we utilize data from the the Current Population Survey (CPS) and the Survey of Health, Ageing and Retirement in Europe (SHARE). Our findings reveal that immigrants from countries with a stronger individualistic cultural orientation are more likely to participate in the stock market. Furthermore, by leveraging data from the U.S. Census and American Community Survey (ACS), we demonstrate that the positive effect of individualistic cultural heritage is amplified for immigrants whose parents have made significant cultural investments. Additionally, utilizing data from the General Social Survey (GSS) to identify cultural mechanisms, we uncover that individualism culture shapes immigrants’ beliefs by fostering trust and optimism. Overall, our empirical evidence underscores the profound and persistent of culture on household stock market participation.

Racial/ethnic disparities in the distribution of heatwave frequency and expected economic losses in the US

Previous research on social disparities in heat exposure has not examined heatwave frequency or economic damage at the local or neighborhood level. Additionally, most US studies have focused on specific cities or regions, and few national-scale studies encompassing both urban and rural areas have been conducted. These gaps are addressed here by analyzing racial/ethnic disparities in the distribution of annual heatwave frequency and expected economic losses from heatwave occurrence in the contiguous US. Census tract-level data on annualized heatwave frequency and expected loss from the FEMA’s National Risk Index are linked to relevant variables from the American Community Survey. Results indicate that all racial/ethnic minority groups except non-Hispanic Black are significantly overrepresented in neighborhoods with greater annual heatwave frequency (top 10% nationally), and all minority groups are overrepresented in neighborhoods with greater total expected annual loss from heatwaves, compared to non-Hispanic Whites. Multivariable models that control for spatial clustering, climate zone, and relevant socio-demographic factors reveal similar racial/ethnic disparities, and suggest significantly greater heatwave frequency and economic losses in neighborhoods with higher percentages of Hispanics and American Indians. These findings represent an important starting point for more detailed investigations on the adverse impacts of heatwaves for US minority populations and formulating appropriate policy interventions.

Racial and economic segregation and diabetes mortality in the USA, 2016–2020

BackgroundThe purpose of this study was to examine the association between racial and economic segregation and diabetes mortality among US counties from 2016 to 2020.MethodsWe conducted a cross-sectional ecological study...

Using the Index of Concentration at the Extremes to Evaluate Associations of Economic and Hispanic/Latino-White Racial Segregation with HIV Outcomes Among Adults Aged ≥ 18 Years with Diagnosed HIV - United States, 2021.

To examine associations between Index of Concentration at the Extremes (ICE) measures (proxy for structural racism) for economic and Hispanic/Latino-White racial segregation and HIV outcomes among adults in the U.S. Census tract-level HIV diagnoses, linkage to HIV medical care within 1 month of diagnosis (linkage), and viral suppression within 6 months of diagnosis (viral suppression) data for 2021 from the National HIV Surveillance System were used. Three ICE measures were obtained from the American Community Survey: ICEincome (income segregation), ICErace (Hispanic/Latino-White racial segregation), and ICEincome + race (Hispanic/Latino-White racialized economic segregation). Rate ratios (RRs) for HIV diagnosis and prevalence ratios (PRs) for linkage and viral suppression were used to examine differences in HIV outcomes across ICE quintiles with Quintile5 (Q5: most privileged) as reference group and adjusted by selected characteristics. Among the 32,529 adults, diagnosis rates were highest in Quintile1 (Q1: most deprived) for ICEincome (28.7) and ICEincome + race (28.4) and Q2 for ICErace (27.0). We also observed higher RRs in HIV diagnosis and lower PRs in linkage and viral suppression (except for ICErace for linkage) in Q1 compared to Q5. Higher RRs and lower PRs in ICE measures were observed among males (diagnosis), adults aged 18‒34 (diagnosis and linkage) and aged ≥ 45 (viral suppression), and among adults in the South (all 3 HIV outcomes). Barriers in access to care/treatment in more Hispanic/Latino-White racialized economic segregated communities perpetuate the disproportionate impact of HIV on the population. Removing barriers to HIV care/treatment created by systemic racism/segregation may improve HIV outcomes and reduce disparities.

The Effect of Parenthood on Care Workers’ Earnings: Exploring Identity Mobilization’s Applicability

ABSTRACT The parenthood wage gap is well-documented in professional work, but we know little about parenthood’s effects on earnings among care workers. As employers may use stereotypes linked to parental identity to determine rewards, care workers may leverage their parental identity to signal appropriateness for work, possibly leading to higher, rather than lower, earnings. At the same time, gender and racial identity may signal different levels of appropriateness to employers according to how they fulfill employer-held gender and racial stereotypes. Using data from the American Community Survey (ACS), we test the applicability of identity mobilization to show that mothers experience wage penalties compared to fathers and non-mothers, while fathers experience wage premiums. Additionally, mothers of color experience smaller penalties than White women, while fathers of color experience smaller premiums compared to White fathers. We also show differences across occupations. Overall, this study showcases the ways in which gender and racial inequality remain entrenched in society, rejecting identity mobilization’s applicability to care work wage gaps.

The Impact of Neighborhood Characteristics on Routine and Gang-Involved Gun Violence: Are Structural Covariates Salient?

ABSTRACT An extensive body of literature has described the influence of neighborhood characteristics, including socio-economic deprivation, residential turnover, and racial/ethnic composition on gun crime. There have been limited efforts, however, to examine the extent to which these effects might vary based on the nature of gun crime – particularly in communities outside of major cities like Chicago or St. Louis. This study attempts to address this issue through application of negative binomial regression and equality of coefficients tests to data obtained from the crime logs and American Community Survey data of a medium-sized city in the Southeastern U.S. Specifically, this study examines (in)equality in the structural covariates of gun crimes when these offenses are disaggregated by gang-involved gun crime versus non-gang-involved gun crime across a sample of 153 census block groups in Chattanooga. Results indicate that the relative influence of neighborhood structural characteristics varies, to some extent, by type of gun crime, illustrating the need for disaggregated measures as a matter of exploring relationships between sub-crime types.

Using Nighttime Light Data to Explore the Extent of Power Outages in the Florida Panhandle after 2018 Hurricane Michael

The destructive forces of tropical cyclones can have significant impacts on the land, contributing to degradation through various mechanisms such as erosion, debris, loss of vegetation, and widespread damage to infrastructure. Storm surge and flooding can wash away buildings and other structures, deposit debris and sediments, and contaminate freshwater resources, making them unsuitable for both human use and agriculture. High winds and flooding often damage electrical disubstations and transformers, leading to disruptions in electricity supply. Restoration can take days or even weeks, depending on the extent of the damage and the resources available. In the meantime, communities affected by power outages may experience difficulties accessing essential services and maintaining communication. In this study, we used a weighted maximum likelihood classification algorithm to reclassify NOAA’s National Geodetic Survey Emergency Response Imagery scenes into debris, sand, water, trees, and roofs to assess the extent of the damage around Mexico Beach, Florida, following the 2018 Hurricane Michael. NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) was processed to estimate power outage duration and rate of restoration in the Florida Panhandle based on the 7-day moving averages. Percent loss of electrical service at a neighborhood level was estimated using the 2013–2017 American Community Survey block group data. Spatial lag models were employed to examine the association between restoration rates and socioeconomic factors. The analysis revealed notable differences in power-restoration rates between urbanized and rural areas and between disadvantaged and more affluent communities. The findings indicated that block groups with higher proportions of minorities, multi-family housing units, rural locations, and households receiving public assistance experienced slower restoration of power compared to urban and more affluent neighborhoods. These results underscore the importance of integrating socioeconomic factors into disaster preparedness and recovery-planning efforts, emphasizing the need for targeted interventions to mitigate disparities in recovery times following natural disasters.