Does Land Use Matter? Understanding Homicide Counts Beyond the Effects of Social Disorganization

2019 ◽  
Vol 24 (4) ◽  
pp. 311-332
Author(s):  
Alana R. Inlow
Keyword(s):  
Land Use ◽  
Social Disorganization ◽  
Negative Binomial ◽  
Positive Association ◽  
Criminological Theory ◽  
Neighborhood Characteristics ◽  
Single Family ◽  
Mixed Use ◽  
The Relationship ◽  
Binomial Models

This study assesses the relationship between land use, measured as percent zoning designation per square kilometer in a census tract, and homicide counts in Portland, Oregon, while controlling for other neighborhood characteristics. Negative binomial models are implemented to account for the overdispersed homicide count indicator. Results suggest that some land use variables—specifically, mixed-use residential (positive association) and single-family residential (negative association)—have significant predictive value for homicide counts beyond neighborhood characteristics and socioeconomic variables deemed important by criminological theory and research.

scholarly journals Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019 ◽  
Vol 11 (23) ◽  
pp. 6643 ◽  
Author(s):  
Lee ◽  
Guldmann ◽  
Choi
Keyword(s):  
Negative Binomial ◽  
Age Groups ◽  
Urban Environments ◽  
Vehicle Miles Traveled ◽  
Crash Frequency ◽  
Rural Environments ◽  
Lower Likelihood ◽  
Conditional Autoregressive ◽  
The Relationship ◽  
Binomial Models

As a characteristic of senior drivers aged 65 +, the low-mileage bias has been reported in previous studies. While it is thought to be a well-known phenomenon caused by aging, the characteristics of urban environments create more opportunities for crashes. This calls for investigating the low-mileage bias and scrutinizing whether it has the same impact on other age groups, such as young and middle-aged drivers. We use a crash database from the Ohio Department of Public Safety from 2006 to 2011 and adopt a macro approach using Negative Binomial models and Conditional Autoregressive (CAR) models to deal with a spatial autocorrelation issue. Aside from the low-mileage bias issue, we examine the association between the number of crashes and the built environment and socio-economic and demographic factors. We confirm that the number of crashes is associated with vehicle miles traveled, which suggests that more accumulated driving miles result in a lower likelihood of being involved in a crash. This implies that drivers in the low mileage group are involved in crashes more often, regardless of the driver’s age. The results also confirm that more complex urban environments have a higher number of crashes than rural environments.

Do Denser Neighborhoods Have Safer Streets? Population Density and Traffic Safety in the Philadelphia Region

2019 ◽  
pp. 0739456X1984504 ◽  
Author(s):  
Erick Guerra ◽  
Xiaoxia Dong ◽  
Michelle Kondo
Keyword(s):  
Population Density ◽  
Traffic Safety ◽  
Urban Form ◽  
Urban Areas ◽  
Negative Binomial ◽  
Pedestrian Safety ◽  
Negative Binomial Models ◽  
The Relationship ◽  
Binomial Models ◽  
Density Results

This study uses multilevel negative binomial models to investigate relationships between neighborhood socio-demographics, urban form, roadway characteristics, traffic collisions, injuries, and fatalities on the Philadelphia region’s streets from 2010 to 2014. We pay particular attention to neighborhood population density. Results indicate that streets in denser neighborhoods have fewer overall collisions, injuries, and fatalities. The association with pedestrian safety is mixed and somewhat uncertain across urban areas and model specifications. This study highlights the importance of population density in traffic safety and helps explain some of the variation in findings across studies examining the relationship between urban form and pedestrian safety.

The Effects of Land Use, Design and Environment on Traffic Fatalities

2013 ◽  
Vol 838-841 ◽  
pp. 2081-2087
Author(s):  
Jian Xu ◽  
Ke Si You
Keyword(s):  
Land Use ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Positive Impact ◽  
Statistical Tests ◽  
Segment Length ◽  
Severe Injuries ◽  
Excess Zeros ◽  
Effects Of Land Use ◽  
Binomial Models

Developing statistics methods to distinguish significant factors associated with roadways is one of the most feasible accesses to understand the nature of traffic accidents. In this study, zero-inflated negative binomial (ZINB) model was developed to allow for overdispersion and excess zeros, as well as the factors of land use, design and environment to examine the effects. The statistical tests show that ZINB model is preferred to zero-inflated Poisson and negative binomial models due to its ability to describe crash counts associated with severe injuries and fatalities more effectively. The results show that fatalities are positively associated with segment length, surface width, land use variables and rainfall. For example, an increase of one inch rainfall will result in an increase of 0.02% in fatalities. Interestingly, distances to hospitals yield positive impact, which suggests that longer distances lead to higher fatalities, presumably due to time lost in transporting crash victims to hospitals.

Influences of Neighborhood Characteristics and Personal Attitudes on University Commuters’ Public Transit Use

2015 ◽  
Vol 2500 (1) ◽  
pp. 93-101 ◽  
Author(s):  
Mi Namgung ◽  
Gulsah Akar
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Public Transit ◽  
Principal Component ◽  
Neighborhood Characteristics ◽  
Single Family ◽  
Mixed Use ◽  
Personal Attitudes ◽  
Intersection Density ◽  
Transit Use

This study examined the links between attitudes, the built environment, and travel behavior on the basis of data from the Ohio State University's 2012 Campus Transportation Survey. The analysis results indicated that attitudes might have explained travel behavior better than the built environment. Survey respondents were asked questions about their attitudes on public transit use, and their answers were grouped into new attitudinal factors by using principal component analysis. Then, new neighborhood categories were created by K-means cluster analysis by means of built-environment and land use variables (population density, employment density, housing density, median age of structures, percentage of single-family housing, and intersection density). As a result of this analysis, discrete neighborhood categories, such as urban high-density and residential neighborhoods, and urban low-density and mixed-use neighborhoods, were created. Then, differences in attitudes toward public transit were analyzed across these new neighborhood categories. Binary logit models were estimated to determine the influence of these neighborhood categories as well as personal attitudes on public transit use after sociodemographic characteristics were controlled for. The results indicated that attitudes were more strongly associated with travel behavior than with neighborhood characteristics. The findings of this study will aid in the formation of a better understanding of public transit use by highlighting the effects of attitudes and neighborhood characteristics in transit use as well as differences in attitudes between neighborhood types.

The relationship between citations, downloads and alternative metrics in rheumatology publications: a bibliometric study

Rheumatology ◽  
2019 ◽  
Vol 59 (2) ◽  
pp. 277-280 ◽  
Author(s):  
Winnie M Y Chen ◽  
Marwan Bukhari ◽  
Francesca Cockshull ◽  
James Galloway
Keyword(s):  
Negative Binomial ◽  
Positive Association ◽  
Negative Binomial Regression ◽  
Significant Positive Association ◽  
H Index ◽  
Binomial Regression ◽  
Number Of Citations ◽  
The Impact ◽  
The Relationship ◽  
Alternative Metrics

Abstract Objective Scientific journals and authors are frequently judged on ‘impact’. Commonly used traditional metrics are the Impact Factor and H-index. However, both take several years to formulate and have many limitations. Recently, Altmetric—a metric that measures impact in a non-traditional way—has gained popularity. This project aims to describe the relationships between subject matter, citations, downloads and Altmetric within rheumatology. Methods Data from publications in Rheumatology were used. Articles published from 2010 to 2015 were reviewed. Data were analysed using Stata 14.2 (StataCorp, College Station, TX, USA). Correlation between citations, downloads and Altmetric were quantified using linear regression, comparing across disease topics. Relationship between downloads and months since publications were described using negative binomial regression, clustering on individual articles. Results A total of 1460 Basic Science and Clinical Science articles were identified, with the number of citations, downloads and Altmetric scores. There were no correlations between disease topic and downloads (R2 = 0.016, P = 0.03), citations (R2 = 0.011, P = 0.29) or Altmetric (R2 = 0.025, P = 0.02). A statistically significant positive association was seen between the number of citations and downloads (R2 = 0.29, P < 0.001). No correlations were seen between Altmetric and downloads (R2 = 0.028, P < 0.001) or citations (R2 = 0.004, P = 0.445). Conclusion Disease area did not correlate with any of the metrics compared. Correlations were apparent with clear links between downloads and citations. Altmetric identified different articles as high impact compared with citation or download metrics. In conclusion: tweeting about your research does not appear to influence citations.

scholarly journals Does Income Inequality Explain the Geography of Residential Burglaries? The Case of Belo Horizonte, Brazil

2019 ◽  
Vol 8 (10) ◽  
pp. 439 ◽  
Author(s):  
Ramos
Keyword(s):  
Income Inequality ◽  
Household Income ◽  
Criminological Theory ◽  
Independent Effect ◽  
Single Family ◽  
Average Household Income ◽  
Local Exposure ◽  
Residential Burglaries ◽  
Belo Horizonte ◽  
The Relationship

The relationship between crime and income inequality is a complex and controversial issue. While there is some consensus that a relationship exists, the nature of it is still the subject of much debate. In this paper, this relationship is investigated in the context of urban geography and whether income inequality can explain the geography of crime within cities. This question is examined for the specific case of residential burglaries in the city of Belo Horizonte, Brazil, where I tested how much burglary rates are affected by local average household income and by local exposure to poverty, while I controlled for other variables relevant to criminological theory, such as land-use type, density and accessibility. Different scales were considered for testing the effect of exposure to poverty. This study reveals that, in Belo Horizonte, the rate of burglaries per single family house is significantly and positively related to income level, but a higher exposure to poverty has no significant independent effect on these rates at any scale tested. The rate of burglaries per apartment, on the other hand, is not significantly affected by either average household income or exposure to poverty. These results seem consistent with a description where burglaries follow a geographical distribution based on opportunity, rather than being a product of localized income disparity and higher exposure between different economic groups.

scholarly journals Temporal relationship between rainfall, temperature and occurrence of dengue cases in São Luís, Maranhão, Brazil

2016 ◽  
Vol 21 (2) ◽  
pp. 641-646 ◽  
Author(s):  
Fabrício Drummond Silva ◽  
Alcione Miranda dos Santos ◽  
Rita da Graça Carvalhal Frazão Corrêa ◽  
Arlene de Jesus Mendes Caldas
Keyword(s):  
Ecological Study ◽  
Negative Binomial ◽  
Positive Association ◽  
Information Criterion ◽  
Distributed Lag ◽  
Distributed Lag Models ◽  
Dengue Prevention ◽  
And Control ◽  
The Relationship ◽  
Monthly Incidence

Abstract This study analyzed the relationship between rainfall, temperature and occurrence of dengue cases. Ecological study performed with autochthonous dengue cases reported during 2003 to 2010 in São Luís, Maranhão. Data of rainfall and temperature were collected monthly. The monthly incidence of dengue cases was calculated by year/100,000 inhabitants. In order to identify the influence of climate variables and dengue cases different distributed lag models using negative binomial distribution were considered. Model selection was based on the lowest AIC (Akaike Information Criterion). Thirteen thousand, four hundred forty-four cases of dengue between 2003 and 2010 were reported, with peaks in 2005, 2007 and 2010. The correlation between rainfall and the occurrence of dengue cases showed increase in the first months after the rainy months. Occurrence of dengue cases was observed during all the period of study. Only rainfall-lag per three months showed a positive association with the number of cases dengue. Thus, this municipality is considered as an endemic and epidemic site. In addition, the relation between rainfall and dengue cases was significant with a lag of three months. These results should be useful to the future development of politics healthy for dengue prevention and control.

scholarly journals Understanding the relationship between land use and land cover and malaria in Nepal

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Shreejana Bhattarai ◽  
Korine N. Kolivras ◽  
Kabita Ghimire ◽  
Yang Shao
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Negative Binomial ◽  
Temporal Trend ◽  
Malaria Incidence ◽  
Water Bodies ◽  
Rice Paddies ◽  
Lulc Change ◽  
Mortality And Morbidity ◽  
The Relationship

Malaria is a leading cause of mortality and morbidity globally. Land Use and Land Cover (LULC) change have been found to affect the transmission of malaria in other regions, but no study has examined such relationships in Nepal. Therefore, this study has three aims: first, to analyze the spatial and temporal trend of Malaria Incidence Rate (MIR) between 1999 and 2015, second to assess LULC change between 2000 and 2010, and finally to understand the relationship between LULC and malaria in Nepal. The land cover types examined are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas, and rice paddies. The temporal trend of MIR and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, and built-up area increased in Nepal by 0.8%, 8.2%, and 28.4% respectively, while other LULC variables decreased between 2000 and 2010. MIR decreased significantly in 21 districts; however, four districts, namely Pyuthan, Kaski, Rupandehi, and Siraha, had a significantly increasing MIR trend between 1999 and 2015. MIR was positively related to water bodies and rice paddies during 2001, 2002, and 2003 but negatively related to grassland during 2010. However, there was no relationship between LULC and MIR during 2000, 2011, 2012 and 2013. This information will be helpful for public health officials to increase control efforts in those districts and in areas near water bodies and rice paddies to aid in their effort to eliminate malaria from Nepal.

State Failure and Transnational Terrorism

2016 ◽  
Vol 62 (3) ◽  
pp. 471-495 ◽  
Author(s):  
Justin George
Keyword(s):  
Negative Binomial ◽  
Estimating Equation ◽  
State Failure ◽  
Generalized Estimating Equation ◽  
Failed States ◽  
Transnational Terrorism ◽  
States Experience ◽  
The Relationship ◽  
Concentration Curves ◽  
Binomial Models

Based on a country panel from 1995 to 2013, this study examines the relationship between state failure and transnational terrorism with respect to perpetrator’s proximity to the target and logistical complexity of attacks. Using concentration curves and generalized estimating equation negative binomial models, the study shows that failed states experience significantly more transnational terrorism when the perpetrators are from the home country. But these states do not produce terrorists who cross borders and carry out attacks in other countries, neither do they attract foreign perpetrators. The latter suggests that conditions in failed states present major operational challenges to foreign terrorists. State failure also causes more logistically complex attacks due to lack of effective counterterrorism measures by failed states. The main results hold true for both relative and dichotomous measures of state failure.

scholarly journals Mixed Land Use: Implications for Violence and Property Crime

2018 ◽  
Vol 17 (4) ◽  
pp. 1119-1142 ◽  
Author(s):  
Renee Zahnow
Keyword(s):  
Land Use ◽  
Ethnic Diversity ◽  
Negative Binomial ◽  
Property Crime ◽  
Negative Binomial Regression ◽  
Gas Stations ◽  
Neighborhood Contexts ◽  
Mixed Land Use ◽  
The Impact ◽  
The Relationship

This study investigates the effect of mixed land use on violence and property crime in neighborhood block groups while simultaneously considering the presence of criminogenic facilities and sociodemographic conditions. We conduct negative binomial regression to examine the relationship between mixed land use and crime and investigate whether the relationship is moderated by sociodemographic characteristics or the presence of criminogenic facilities. The results suggest that mixed land use may reduce property crime while violent crime is influenced by mixed land use in nearby neighborhoods. There was an additional effect of the presence of particular facilities, notably bars, transportation stations, schools, stores, and gas stations in the neighborhood. There was some evidence that the impact of land use mix on crime varies dependent on residential mobility, ethnic diversity and the presence of bars, transport stations, and schools. Our findings indicate that those responsible for planning urban spaces and developing land use policies should consider differential effects of land use characteristics across neighborhood contexts.

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