Neighborhood Walkability and Crime: Does the Relationship Vary by Crime Type?

2020 ◽  
pp. 001391652092184
Author(s):  
Narae Lee ◽  
Christopher Contreras
Keyword(s):  
Los Angeles ◽  
Low Income ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Crime Patterns ◽  
Linear Effect ◽  
Neighborhood Walkability ◽  
Point Increase ◽  
Walk Score ◽  
Crime Types

We draw on theoretical insights from criminology in using the Walk Score index to analyze walkability’s relationship to spatial crime patterns on Los Angeles city blocks. Results from our first set of negative binomial regression models show that walkability had an especially strong linear effect on robbery rates: a 24% increase in the robbery rate accompanied a 10-point increase in Walk Score on a block, controlling for the effects of local businesses and sociodemographic characteristics. Our second set of models reveals that walkability exerted variable nonlinear influences on spatial crime patterns. Our final set of models suggests that the walkability–crime relationship might depend on neighborhood social organization: When walkability is high, low-income blocks might experience sharp rises in rates of predatory violence as compared with more advantaged blocks. This research highlights the importance of considering the mechanisms involved in walkability’s impact on the spatial distribution of individual crime types.

Revisiting the Crime Control Benefits of Voluntary Organizations: Organizational Presence, Organizational Capacity, and Crime Rates in Los Angeles Neighborhoods

2018 ◽  
Vol 65 (7) ◽  
pp. 916-940 ◽  
Author(s):  
James C. Wo
Keyword(s):  
Los Angeles ◽  
Fixed Effects ◽  
Negative Binomial ◽  
Crime Control ◽  
Organizational Capacity ◽  
Negative Binomial Regression ◽  
Crime Rates ◽  
Voluntary Organizations ◽  
Crime Types ◽  
Independent Effects

This study examines the independent effects that the number of voluntary organizations and the total amount of income they possess have on neighborhood crime, over time. Drawing upon a sample of Los Angeles census blocks from 2000 to 2010, I utilize fixed-effects negative binomial regression to estimate crime models. The number of voluntary organizations and the total amount of income they possess in the focal block, respectively, are not related to most crime types the following year. Yet, both aspects of voluntary organizations exhibit crime-reducing influences when accounting for their broader spatial impact, and controlling for numerous factors that have been shown to be associated with crime rates. The implications for communities and crime research are discussed.

scholarly journals Trends in Opioid Prescribing Among Hemodialysis Patients, 2007–2014

2018 ◽  
Vol 49 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Matthew Daubresse ◽  
G. Caleb Alexander ◽  
Deidra C. Crews ◽  
Dorry L. Segev ◽  
Mara A. McAdams-DeMarco
Keyword(s):  
Low Income ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
The United States ◽  
Incidence Rates ◽  
Opioid Prescription ◽  
Opioid Prescribing ◽  
Hispanic Patients ◽  
Estimate Annual Incidence ◽  
National Trends

Background: Hemodialysis (HD) patients frequently experience pain. Previous studies of HD patients suggest increased opioid prescribing through 2010. It remains unclear if this trend continued after 2010 or declined with national trends. Methods: Longitudinal cohort study of 484,745 HD patients in the United States Renal Data System/Medicare data. We used Poisson/negative binomial regression to estimate annual incidence rates of opioid prescribing between 2007 and 2014. We compared prescribing rates with the general US population using IQVIA’s National Prescription Audit data. Outcomes included the following: percent of HD patients receiving an opioid prescription, rate of opioid prescriptions, quantity, days supply, morphine milligram equivalents (MME) dispensed per 100 person-days, and prescriptions per person. Results: In 2007, 62.4% of HD patients received an opioid prescription. This increased to 63.2% in 2010 then declined to 53.7% by 2014. Opioid quantity peaked in 2011 at 73.5 pills per 100 person-days and declined to 62.6 pills per 100 person-days in 2014. MME peaked between 2010 and 2012 then declined through 2014. In 2014, MME rates were 1.8-fold higher among non-Hispanic patients and 1.6-fold higher among low-income patients. HD patients received 3.2-fold more opioid prescriptions per person compared to the general US population and were primarily prescribed oxycodone and hydrocodone. Between 2012 and 2014, HD patients experienced greater declines in opioid prescriptions per person (18.2%) compared to the general US population (7.1%). Conclusion: Opioid prescribing among HD patients declined between 2012 and 2014. However, HD patients continue receiving substantially more opioids than the general US population.

scholarly journals Exploring Disparities in Maternal Residential Proximity to Unconventional Gas Development in the Barnett Shale in North Texas

2019 ◽  
Vol 16 (3) ◽  
pp. 298
Author(s):  
Jennifer Ish ◽  
Elaine Symanski ◽  
Kristina Whitworth
Keyword(s):  
Low Income ◽  
White Women ◽  
Negative Binomial ◽  
Secondary Analysis ◽  
Negative Binomial Regression ◽  
Barnett Shale ◽  
North Texas ◽  
Unconventional Gas ◽  
Residential Proximity ◽  
Unconventional Gas Development

Background: This study explores sociodemographic disparities in residential proximity to unconventional gas development (UGD) among pregnant women. Methods: We conducted a secondary analysis using data from a retrospective birth cohort of 164,658 women with a live birth or fetal death from November 2010 to 2012 in the 24-county area comprising the Barnett Shale play, in North Texas. We considered both individual- and census tract-level indicators of sociodemographic status and computed Indexes of Concentration at the Extremes (ICE) to quantify relative neighborhood-level privilege/disadvantage. We used negative binomial regression to investigate the relation between these variables and the count of active UGD wells within 0.8 km of the home during gestation. We calculated count ratios (CR) and 95% confidence intervals (CI) to describe associations. Results: There were fewer wells located near homes of women of color living in low-income areas compared to non-Hispanic white women living in more privileged neighborhoods (ICE race/ethnicity + income: CR = 0.51, 95% CI = 0.48–0.55). Conclusions: While these results highlight a potential disparity in residential proximity to UGD in the Barnett Shale, they do not provide evidence of an environmental justice (EJ) issue nor negate findings of environmental injustice in other regions.

Abstract 285: Higher Walk Score Associated With Higher Rates of Bystander AED Use in Street-Level Cardiac Arrest

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
John Chen ◽  
Valery Effoe ◽  
John Lisko ◽  
Nabil Sabbak ◽  
Shawn Reginauld ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Low Income ◽  
Household Income ◽  
Bystander Behavior ◽  
Black Neighborhoods ◽  
Point Increase ◽  
Life Saving ◽  
Walk Score ◽  
Income Data ◽  
Bystander Cpr

Introduction: Bystander CPR (BCPR) and AED use are crucial life-saving measures in out-of-hospital cardiac arrest (OHCA). OHCA occurring in low-income black neighborhoods are less likely to receive bystander assistance. In addition to socioeconomic disparities, characteristics of the built environment may also contribute to large variation in BCPR and bystander AED rates. Hypothesis: We hypothesized that pedestrian-friendly spaces have higher rates of BCPR and bystander AED use. Methods: Using the Cardiac Arrest Registry to Enhance Survival, we studied OHCA occurring in street/highway locations in the US in 2016. We excluded cardiac arrests that were witnessed by a 911 responder. Each incident address was assigned a 0-100 Walk Score® using an open-source algorithm and linked to census tract race and income data. We analyzed the relationship between Walk Score and key elements of bystander behavior: witness of arrest, provision of BCPR, and use of AED. Results: Of 3225 OHCA, 1666 (51.7%) were witnessed, 934 (29.0%) received BCPR, and 165 (5.1%) used an AED. After adjusting for age, gender, neighborhood median household income, and neighborhood percent black, every 10-point increase in Walk Score was associated with higher odds of bystander AED use (OR, 1.23; 95% CI, 1.14 to 1.32) but lower odds of witnessed arrest (OR, 0.95; 95% CI, 0.93 to 0.97) and BCPR (OR, 0.92; 95% CI, 0.90 to 0.95) (Table). Lower neighborhood household income predicted less BCPR and AED use; higher neighborhood black composition also predicted less BCPR. Conclusions: After adjusting for neighborhood-level race and income, OHCA occurring in walkable areas had higher rates of bystander AED use but lower rates of witnessed arrest and BCPR. The effects of built environments on bystander behavior and AED availability warrant closer investigation.

scholarly journals General Healthcare Utilization and Out-of-Pocket Expenditures Associated with Depression in Adults: A Cross-Sectional Analysis in Nepal

2019 ◽  
Author(s):  
Selina Rajan ◽  
Sujit D Rathod ◽  
Nagendra P Luitel ◽  
Adrianna Murphy ◽  
Tessa Roberts ◽  
...  
Keyword(s):  
Healthcare Utilization ◽  
Low Income ◽  
Negative Binomial ◽  
Mental Healthcare ◽  
Negative Binomial Regression ◽  
Population Based ◽  
Low Income Countries ◽  
Cross Sectional ◽  
Universal Healthcare ◽  
Probable Depression

Abstract Background: Despite attempts to improve universal healthcare coverage (UHC) in low income countries like Nepal, most healthcare utilization is still financed by out-of-pocket (OOP) payments, with detrimental effects on the poorest and most in need. Evidence from high income countries shows that depression is associated with increased healthcare utilization, which may lead to increased OOP expenditures, placing greater stress on families. To inform policies for integrating mental healthcare into UHC in LMIC, we must understand general healthcare utilization and OOP expenditure patterns in people with depression. Aims: We examined associations between symptoms of depression and frequency and type of general healthcare utilization and OOP expenditure among adults in Chitwan District, Nepal. Methods: We analysed data from a population-based survey of 2040 adults in 2013, who completed the PHQ-9 screening tool for depression and answered questions about general healthcare utilization. We modelled associations between increasing PHQ-9 score and healthcare utilization frequency and OOP expenditure using negative binomial regression. We also compared sector-specific utilization of outpatient healthcare and their related costs among adults with and without probable depression, determined by a PHQ-9 score of 10 or more. Results: We classified 80 (3.6%) participants with probable depression, 70.9% of whom used some form of general healthcare in the past year compared to 43.9% of people without probable depression. Mean annual OOP healthcare expenditures were $118 USD in people with probable depression, compared to $110 USD in people without. With each unit increase in PHQ-9 score, there was a 14% increase in total healthcare visits (95% CI 7%-22%, p<0.0001) and $9 USD increase in OOP expenditures (95% CI $2-$17; p<0.0001). People with depression sought most general healthcare from pharmacists (30.1%) but reported the greatest expenditure on specialist doctors ($36 USD). Conclusions: In this population-based sample from Central Nepal, we identified dose-dependent increases in healthcare utilization and OOP expenditure with increasing PHQ-9 scores. Strengthening UHC to include early detection and treatment for people affected by depression as an integrated component of general healthcare should lead to a reduction in financial pressures on families, which is likely to reduce the incidence of depression in Nepal.

scholarly journals Healthcare Utilization and Out-of-Pocket Expenditures Associated with Depression in Adults: A Cross-Sectional Analysis in Nepal

2019 ◽  
Author(s):  
Selina Rajan ◽  
Sujit D Rathod ◽  
Nagendra P Luitel ◽  
Adrianna Murphy ◽  
Tessa Roberts ◽  
...  
Keyword(s):  
Healthcare Utilization ◽  
Low Income ◽  
Negative Binomial ◽  
Mental Healthcare ◽  
Negative Binomial Regression ◽  
Population Based ◽  
Low Income Countries ◽  
Cross Sectional ◽  
Universal Healthcare ◽  
Probable Depression

Abstract Background: Despite attempts to improve universal healthcare coverage (UHC) in low income countries like Nepal, most healthcare utilization is still financed by out-of-pocket (OOP) payments, with detrimental effects on the poorest and most in need. Evidence from high income countries shows that depression is associated with increased healthcare utilization, which may lead to increased OOP expenditures, placing greater stress on families. To inform policies for integrating mental healthcare into UHC in LMIC, we must understand healthcare utilization and OOP expenditure patterns in people with depression. Aims: We examined associations between symptoms of depression and frequency and type of healthcare utilization and OOP expenditure among adults in Chitwan District, Nepal. Methods: We analysed data from a population-based survey of 2040 adults in 2013, who completed the PHQ-9 screening tool for depression and answered questions about healthcare utilization. We modelled associations between increasing PHQ-9 score and healthcare utilization frequency and OOP expenditure using negative binomial regression. We also compared sector-specific utilization of outpatient healthcare and their related costs among adults with and without probable depression, determined by a PHQ-9 score of 10 or more. Results: We classified 80 (3.6%) participants with probable depression, 70.9% of whom used some form of healthcare in the past year compared to 43.9% of people without probable depression. Mean annual OOP healthcare expenditures were $118 USD in people with probable depression, compared to $110 USD in people without. With each unit increase in PHQ-9 score, there was a 14% increase in total healthcare visits (95% CI 7%-22%, p<0.0001) and $9 USD increase in OOP expenditures (95% CI $2-$17; p<0.0001). People with depression sought most healthcare from pharmacists (30.1%) but reported the greatest expenditure on specialist doctors ($36 USD). Conclusions: In this population-based sample from Central Nepal, we identified dose-dependent increases in healthcare utilization and OOP expenditure with increasing PHQ-9 scores. Strengthening UHC to include early detection and treatment for people affected by depression as an integrated component of healthcare should lead to a reduction in financial pressures on families, which is likely to reduce the incidence of depression in Nepal.

scholarly journals Inequalities in COVID19 mortality related to ethnicity and socioeconomic deprivation

2020 ◽  
Author(s):  
Tanith C. Rose ◽  
Kate Mason ◽  
Andy Pennington ◽  
Philip McHale ◽  
Iain Buchan ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Low Income ◽  
Negative Binomial ◽  
Mortality Rates ◽  
Ethnic Composition ◽  
Effective Control ◽  
Local Authorities ◽  
Cross Sectional ◽  
Percentage Point Increase ◽  
Point Increase

AbstractBackgroundInitial reports suggest that ethnic minorities may be experiencing more severe coronavirus disease 2019 (COVID19) outcomes. We therefore assessed the association between ethnic composition, income deprivation and COVID19 mortality rates in England.MethodsWe performed a cross-sectional ecological analysis across England’s upper-tier local authorities. We assessed the association between the proportion of the population from Black, Asian and Minority Ethnic (BAME) backgrounds, income deprivation and COVID19 mortality rates using multivariable negative binomial regression, adjusting for population density, proportion of the population aged 50–79 and 80+ years, and the duration of the epidemic in each area.FindingsLocal authorities with a greater proportion of residents from ethnic minority backgrounds had statistically significantly higher COVID19 mortality rates, as did local authorities with a greater proportion of residents experiencing deprivation relating to low income. After adjusting for income deprivation and other covariates, each percentage point increase in the proportion of the population from BAME backgrounds was associated with a 1% increase in the COVID19 mortality rate [IRR=1.01, 95%CI 1.01–1.02]. Each percentage point increase in the proportion of the population experiencing income deprivation was associated with a 2% increase in the COVID19 mortality rate [IRR=1.02, 95%CI 1.01–1.04].InterpretationThis study provides evidence that both income deprivation and ethnicity are associated with greater COVID19 mortality. To reduce these inequalities, Government needs to target effective control and recovery measures at these disadvantaged communities, proportionate to their greater needs and vulnerabilities, during and following the pandemic.FundingNational Institute of Health Research; Medical Research Council

Low-Income Housing and Crime: The Influence of Housing Development and Neighborhood Characteristics

2018 ◽  
Vol 65 (7) ◽  
pp. 969-993 ◽  
Author(s):  
Marie Skubak Tillyer ◽  
Rebecca J. Walter
Keyword(s):  
Low Income ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Housing Development ◽  
Interactive Effects ◽  
Neighborhood Characteristics ◽  
Neighborhood Conditions ◽  
Housing Developments ◽  
Binomial Regression ◽  
Low Income Housing

This study examines the distribution of crime across various types of low-income housing developments and estimates the main and interactive effects of housing development and neighborhood characteristics on crime. Negative binomial regression models were estimated to observe the influence of security and design features, neighborhood concentrated disadvantage, residential stability, and nearby nonresidential land use on crime at the housing developments. The findings suggest that low-income housing developments are not uniformly criminogenic, and both development characteristics and neighborhood conditions are relevant for understanding crime in low-income housing developments. Implications for prevention are discussed.

scholarly journals Impact of community piped water coverage on re-infection with urogenital schistosomiasis in rural South Africa

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Polycarp Mogeni ◽  
Alain Vandormael ◽  
Diego Cuadros ◽  
Christopher Appleton ◽  
Frank Tanser
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Primary School Children ◽  
Effective Control ◽  
Urogenital Schistosomiasis ◽  
Percentage Point Increase ◽  
Piped Water ◽  
Point Increase ◽  
Binomial Regression

Previously, we demonstrated that coverage of piped water in the seven years preceding a parasitological survey was strongly predictive of Schistosomiasis haematobium infection in a nested cohort of 1976 primary school children (Tanser, 2018). Here, we report on the prospective follow up of infected members of this nested cohort (N = 333) for two successive rounds following treatment. Using a negative binomial regression fitted to egg count data, we found that every percentage point increase in piped water coverage was associated with 4.4% decline in intensity of re-infection (incidence rate ratio = 0.96, 95% CI: 0.93–0.98, p=0.004) among the treated children. We therefore provide further compelling evidence in support of the scaleup of piped water as an effective control strategy against Schistosoma haematobium transmission.

scholarly journals 2317. Excess Influenza-Attributable Mortality in Los Angeles County (LAC) for the 2013–2014 Through 2017–2018 Seasons

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S794-S795
Author(s):  
Elizabeth Traub ◽  
Louise Rollin ◽  
Prabhu Gounder
Keyword(s):  
Public Health ◽  
Los Angeles ◽  
Los Angeles County ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Median Number ◽  
Vital Statistics ◽  
Attributable Mortality ◽  
Negative Binomial Regression Model ◽  
Syncytial Virus

Abstract Background Deaths caused by seasonal influenza are impossible to measure directly and are typically estimated using statistical models. We applied a previously developed model to Los Angeles County (LAC) data for the 2013–2014 through 2017–2018 influenza seasons. Methods Excess deaths attributable to influenza were estimated using a negative binomial regression model incorporating laboratory surveillance data and weekly counts of deaths with an underlying respiratory or circulatory cause of death. We obtained death data from the National Vital Statistics System. Population estimates for LAC were prepared by Hedderson Demographic Services for LAC Internal Services Department. The weekly total number of respiratory specimens tested and number positive for influenza or respiratory syncytial virus were provided by nine healthcare systems in LAC. Influenza-associated deaths in all ages are reportable to LAC Department of Public Health; confirmed reports are counted as observed deaths. Results The midyear LAC population increased from 10,019,362 in 2013 to 10,272,648 in 2017. The median number of observed influenza deaths reported to public health was 81 in 2015–2016 (minimum [min]: 56 in 2015–2015, maximum [max]: 288 in 2017–2018). The median number of seasonal deaths with an underlying respiratory or circulatory cause was 27,455 (min: 25,828, max: 28,732). The median estimate of influenza-attributable deaths was 1,478 (95% confidence interval [CI]: 823–2,613) in 2015–2016, with a min of 1,045 deaths (CI: 629–2,258) in 2013–2014 and a max of 1,905 (CI: 1,075–3,269) in 2017–2018. Conclusion Although influenza-associated deaths at all ages are reportable in LAC, a variety of barriers to reporting exist. Our estimates indicate that influenza-associated deaths in LAC are underreported. The more comprehensive modeled estimate of the burden of influenza can better inform local policy and planning decisions. Disclosures All authors: No reported disclosures.

Sign in / Sign up

Export Citation Format

Share Document