scholarly journals Network analysis of firearm movement among US states

2020 ◽  
Author(s):  
Sae Takada ◽  
Kristen Choi ◽  
Shaw Natsui ◽  
Altaf Saadi ◽  
Liza Buchbinder ◽  
...  
Keyword(s):  
Time Series ◽  
Network Analysis ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Similar Model ◽  
Cross Sectional ◽  
Us States ◽  
Binomial Regression ◽  
The Relationship

Abstract Background: The movement of firearm across state lines may decrease the effectiveness of state-level firearm laws. Yet how state-level firearm policies affect cross-state movement have not yet been widely explored. This study aims to characterize the interstate movement of firearms and its relationship with state-level firearm policies. Methods: Cross-sectional time series network analysis of interstate firearm movement using Bureau of Alcohol, Tobacco, Firearms, and Explosives firearm trace data (2010 -2017). We constructed the network of firearm movement between 50 states. We used zero-inflated negative binomial regression to estimate the relationship between the number of a state’s firearm laws and number of states for which it was the source of 100 or more firearms, adjusting for state characteristics. We used a similar model to examine the relationship between firearm laws and the number of states for which a given state was the destination of 100 or more firearms.Results: Over the 8-year period, states had an average of 26 (SD 25.2) firearm laws. On average, a state was the source of 100 or more crime-related firearms for 2.2 (SD 2.7) states and was the destination of 100 or more crime-related firearms for 2.2 (SD 3.4) states. Greater number of firearm laws was associated with states being the source of 100 or more firearms to fewer states (IRR0.67 per SD, p<0.001), higher odds of not being a source to any states (aOR1.56 per SD, p<0.001), and states being the destination of 100 or more firearms from more states (IRR1.83 per SD, p<0.001).Conclusions: Restrictive firearm policies are associated with less movement of firearms to other states, but with more movement of firearms from outside states. The effectiveness of state-level firearm-restricting laws is complicated by a network of interstate firearm movement.

scholarly journals Network analysis of firearm movement among US states

2020 ◽  
Author(s):  
Sae Takada ◽  
Kristen Choi ◽  
Shaw Natsui ◽  
Altaf Saadi ◽  
Liza Buchbinder ◽  
...  
Keyword(s):  
Time Series ◽  
Network Analysis ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Similar Model ◽  
Cross Sectional ◽  
Us States ◽  
Binomial Regression ◽  
The Relationship

Abstract Background: The movement of firearm across state lines may decrease the effectiveness of state-level firearm laws. Yet how state-level firearm policies affect cross-state movement have not yet been widely explored. This study aims to characterize the interstate movement of firearms and its relationship with state-level firearm policies. Methods : Cross-sectional time series network analysis of interstate firearm movement using Bureau of Alcohol, Tobacco, Firearms, and Explosives firearm trace data (2010 -2017). We constructed the network of firearm movement between 50 states. We used zero-inflated negative binomial regression to estimate the relationship between the number of a state’s firearm laws and number of states for which it was the source of 100 or more firearms, adjusting for state characteristics. We used a similar model to examine the relationship between firearm laws and the number of states for which a given state was the destination of 100 or more firearms. Results : Over the 8-year period, states had an average of 26 (SD 25.2) firearm laws. On average, a state was the source of 100 or more crime-related firearms for 2.2 (SD 2.7) states and was the destination of 100 or more crime-related firearms for 2.2 (SD 3.4) states. Greater number of firearm laws was associated with states being the source of 100 or more firearms to fewer states (IRR0.67 per SD, p<0.001), higher odds of not being a source to any states (aOR1.56 per SD, p<0.001), and states being the destination of 100 or more firearms from more states (IRR1.83 per SD, p<0.001). Conclusions: Restrictive firearm policies are associated with less movement of firearms to other states, but with more movement of firearms from outside states. The effectiveness of state-level firearm-restricting laws is complicated by a network of interstate firearm movement.

scholarly journals Network analysis of firearm movement among US states

2020 ◽  
Author(s):  
Sae Takada ◽  
Kristen Choi ◽  
Shaw Natsui ◽  
Altaf Saadi ◽  
Liza Buchbinder ◽  
...  
Keyword(s):  
Time Series ◽  
Network Analysis ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Similar Model ◽  
Cross Sectional ◽  
Us States ◽  
Binomial Regression ◽  
The Relationship

Abstract Background: The movement of firearm across state lines may decrease the effectiveness of state-level firearm laws. Yet how state-level firearm policies affect cross-state movement have not yet been widely explored. This study aims to characterize the interstate movement of firearms and its relationship with state-level firearm policies. Methods: Cross-sectional time series network analysis of interstate firearm movement using Bureau of Alcohol, Tobacco, Firearms, and Explosives firearm trace data (2010 -2017). We constructed the network of firearm movement between 50 states. We used zero-inflated negative binomial regression to estimate the relationship between the number of a state’s firearm laws and number of states for which it was the source of 100 or more firearms, adjusting for state characteristics. We used a similar model to examine the relationship between firearm laws and the number of states for which a given state was the destination of 100 or more firearms.Results: Over the 8-year period, states had an average of 26 (SD 25.2) firearm laws. On average, a state was the source of 100 or more crime-related firearms for 2.2 (SD 2.7) states and was the destination of 100 or more crime-related firearms for 2.2 (SD 3.4) states. Greater number of firearm laws was associated with states being the source of 100 or more firearms to fewer states (IRR0.67 per SD, p<0.001), higher odds of not being a source to any states (aOR1.56 per SD, p<0.001), and states being the destination of 100 or more firearms from more states (IRR1.83 per SD, p<0.001).Conclusions: Restrictive firearm policies are associated with less movement of firearms to other states, but with more movement of firearms from outside states. The effectiveness of state-level firearm-restricting laws is complicated by a network of interstate firearm movement.

scholarly journals Firearm laws and the network of firearm movement among US states

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sae Takada ◽  
Kristen R. Choi ◽  
Shaw Natsui ◽  
Altaf Saadi ◽  
Liza Buchbinder ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Rate Ratio ◽  
Negative Binomial ◽  
Incidence Rate Ratio ◽  
State Level ◽  
Negative Binomial Regression ◽  
Similar Model ◽  
Us States ◽  
Binomial Regression ◽  
The Relationship

Abstract Background The movement of firearm across state lines may decrease the effectiveness of state-level firearm laws. Yet, how state-level firearm policies affect cross-state movement have not yet been widely explored. This study aims to characterize the interstate movement of firearms and its relationship with state-level firearm policies. Methods We analyzed the network of interstate firearm movement using Bureau of Alcohol, Tobacco, Firearms, and Explosives firearm trace data (2010–2017). We constructed the network of firearm movement between 50 states. We used zero-inflated negative binomial regression to estimate the relationship between the number of a state’s firearm laws and number of states for which it was the source of 100 or more firearms, adjusting for state characteristics. We used a similar model to examine the relationship between firearm laws and the number of states for which a given state was the destination of 100 or more firearms. Results Over the 8-year period, states had an average of 26 (Standard Deviation [SD] 25.2) firearm laws. On average, a state was the source of 100 or more crime-related firearms for 2.2 (SD 2.7) states and was the destination of 100 or more crime-related firearms for 2.2 (SD 3.4) states. Greater number of firearm laws was associated with states being the source of 100 or more firearms to fewer states (Incidence Rate Ratio [IRR] 0.58 per SD, p < 0.001) and being the destination of 100 or more firearms from more states (IRR1.73 per SD, p < 0.001). Conclusions Restrictive state-level firearm policies are associated with less movement of firearms to other states, but with more movement of firearms from outside states. The effectiveness of state-level firearm-restricting laws is complicated by a network of interstate firearm movement.

Gang organization and violence in youth correctional facilities

2016 ◽  
Vol 2 (2) ◽  
pp. 81-94 ◽  
Author(s):  
Daniel Walter Scott ◽  
Cheryl Lee Maxson
Keyword(s):  
Negative Binomial ◽  
Violent Behavior ◽  
Negative Binomial Regression ◽  
Correctional Facilities ◽  
Cross Sectional ◽  
Content Type ◽  
Institutional Violence ◽  
Binomial Regression ◽  
Gang Organization ◽  
The Relationship

Purpose – The purpose of this paper is to examine characteristics of gang organization in youth correctional facilities as reported by youth and staff as well as to analyze the relationship between institutional violence and level of gang organization. Design/methodology/approach – The data were collected through interviews with staff and youth in correctional facilities. Gang organization level averages are compared across youth and official perspectives, and the variability of responses among youth is also examined. Negative binomial regression models are conducted to determine the association between perceived level of gang organization and officially recorded violent behavior, both prior to and subsequent to the interview. Findings – Perceptions of institutional gang organization vary notably depending on who is reporting. In contrast with prior studies of street gangs, controlling for youth demographics and offense characteristics, the authors find no significant relationship between gang organization and violence. Research limitations/implications – The sample size is small and the data are cross-sectional. Future studies will need to be conducted in order to confirm these findings, as they contradict prior studies. The analysis of street gang organization may need to be approached differently by scholars. Originality/value – Research has not been conducted on the organizational structure of gangs in youth correctional facilities or its relationship to institutional violence.

Effect of Maximum Average Temperature on Suicide Rates in California, 2008-2017: Public Health Implications of Climate Change

2020 ◽  
Author(s):  
Mavra Qamar ◽  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie Nanos ◽  
David N Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Time Series ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Maximum Temperature ◽  
Suicide Rates ◽  
Binomial Regression ◽  
The Relationship ◽  
Heat Events

Abstract BackgroundSuicide prevention is a salient public health responsibility, as it is one of the top ten leading causes of premature mortality in the United States. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. Previous studies have been country-based. Currently, studies focused solely on regions, provinces, or states, such as California, are limited. The present study holds two purposes: i) to assess the effect of maximum temperature on suicides, and ii) to evaluate the effect of number of monthly heat events on suicide rates, in California from 2008-2017.MethodsThe exposure was measured as the average Californian daily maximum temperature within each month, and the number of monthly heat events, which was calculated as a count of the days exhibiting a >15% increase from the historical monthly temperature. The outcome was measured as California’s monthly suicide rate. Negative binomial regression models assessed the relationship between maximum temperature and suicides, and heat events and suicide. A seasonal decomposition of a time series and auto-correlogram further analyzed the seasonality of suicide and the trend from 2008-2017. ResultsThere were 40,315 deaths by suicide in California between 2008-2017. Negative binomial regression indicated a 6.1% increase in suicide incidence rate ratio (IRR) per 10°F increase in maximum temperature (IRR=1.00590 per 1°F, 95% CI: 1.00387, 1.00793, p<0.0001) and a positive, non-significant association between suicide rates and number of heat events adjusted for month of occurrence (IRR 1.00148 per heat event, 95% CI: 0.99636, 1.00661, p=0.572). The time series analysis and auto-correlogram suggested seasonality of deaths by suicide.ConclusionThe present study provided preliminary evidence that will generate future directions for research. We must seek to further illuminate the relationship of interest and apply our findings to public health interventions that will lower the rates of death by suicide as we are confronted with the effects of climate change.

scholarly journals Homicide and impunity: an ecological analysis at state level in Brazil

2009 ◽  
Vol 43 (5) ◽  
pp. 733-742 ◽  
Author(s):  
Paulo Nadanovsky ◽  
Roger Keller Celeste ◽  
Margo Wilson ◽  
Martin Daly
Keyword(s):  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Study Data ◽  
Development Economic ◽  
Cross Sectional ◽  
Homicide Rates ◽  
Young Males ◽  
Binomial Regression ◽  
Homicide Victim

OBJECTIVE: To assess a new impunity index and variables that have been found to predict variation in homicide rates in other geographical levels as predictive of state-level homicide rates in Brazil. METHODS: This was a cross-sectional ecological study. Data from the mortality information system relating to the 27 Brazilian states for the years 1996 to 2005 were analyzed. The outcome variables were taken to be homicide victim rates in 2005, for the entire population and for men aged 20-29 years. Measurements of economic and social development, economic inequality, demographic structure and life expectancy were analyzed as predictors. An "impunity index", calculated as the total number of homicides between 1996 and 2005 divided by the number of individuals in prison in 2007, was constructed. The data were analyzed by means of simple linear regression and negative binomial regression. RESULTS: In 2005, state-level crude total homicide rates ranged from 11 to 51 per 100,000; for young men, they ranged from 39 to 241. The impunity index ranged from 0.4 to 3.5 and was the most important predictor of this variability. From negative binomial regression, it was estimated that the homicide victim rate among young males increased by 50% for every increase of one point in this ratio. CONCLUSIONS: Classic predictive factors were not associated with homicides in this analysis of state-level variation in Brazil. However, the impunity index indicated that the greater the impunity, the higher the homicide rate.

scholarly journals The Effect of Maximum Average Temperature on Suicide Rates in California, 2008-2017: An Ecological Study

2020 ◽  
Author(s):  
Mavra Qamar ◽  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie Nanos ◽  
David N Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Suicide Rates ◽  
Binomial Regression ◽  
The Relationship ◽  
Heat Events

Abstract Background: Suicide prevention is a salient public health responsibility, as it is one of the top ten leading causes of premature mortality in the United States. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. Previous studies have been country-based. Currently, studies focused solely on regions, provinces, or states, such as California, are limited. The present study holds two purposes: i) to assess the effect of maximum temperature on suicides, and ii) to evaluate the effect of number of monthly heat events on suicide rates, in California from 2008-2017.Methods: The exposure was measured as the average Californian daily maximum temperature within each month, and the number of monthly heat events, which was calculated as a count of the days exhibiting a >15% increase from the historical monthly temperature. The outcome was measured as California’s monthly suicide rate. Negative binomial regression models assessed the relationship between maximum temperature and suicides, and heat events and suicide. A seasonal decomposition of a time series and auto-correlogram further analyzed the seasonality of suicide and the trend from 2008-2017. Results: There were 40,315 deaths by suicide in California between 2008-2017. Negative binomial regression indicated a 6.1% increase in suicide incidence rate ratio (IRR) per 10°F increase in maximum temperature (IRR=1.00590 per 1°F, 95% CI: 1.00387, 1.00793, p<0.0001) and a positive, non-significant association between suicide rates and number of heat events adjusted for month of occurrence (IRR 1.00148 per heat event, 95% CI: 0.99636, 1.00661, p=0.572). The time series analysis and auto-correlogram suggested seasonality of deaths by suicide.Conclusion: The present study provided preliminary evidence that will generate future directions for research. We must seek to further illuminate the relationship of interest and apply our findings to public health interventions that will lower the rates of death by suicide as we are confronted with the effects of climate change.

scholarly journals NATO between Exclusivity and Inclusivity: Measuring NATO’s Partnerships

2021 ◽  
pp. 1-32
Author(s):  
Branislav Mičko
Keyword(s):  
Human Rights ◽  
Fixed Effects ◽  
International Institutions ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Original Dataset ◽  
Strategic Approach ◽  
Binomial Regression ◽  
The Given ◽  
The Relationship

Building on an original dataset, this article focuses on the interactions between NATO and its declared worldwide partners. It argues that the analysis of these interactions can reveal NATO’s strategic approach to partnerships, but it can also provide a tool for its classification as an organisation that is either exclusive – defined by the focus on defence of its members, or inclusive – emphasising the global protection of democracies and human rights. The relationship between types of interactions and NATO categorisation is estimated using an unconditional negative binomial regression with fixed effects as well as a within-between (hybrid) model. Furthermore, they are illustrated on two brief case studies of Sweden and Japan. The results of the study suggest that NATO engages primarily with countries that are powerful relative to their neighbourhood, even though they are not the most powerful among the partners. The given country’s level of democracy, integration into the international institutions, and stability, do not seem to play any overarching role here.

scholarly journals The Relationship between Near-Repeat Street Robbery and the Environment: Evidence from Malmö, Sweden

2020 ◽  
Vol 9 (4) ◽  
pp. 188
Author(s):  
Markus Rasmusson ◽  
Marco Helbich
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Socioeconomic Indicators ◽  
Law Enforcement Agencies ◽  
Environmental Characteristics ◽  
Binomial Regression ◽  
Using Data ◽  
Near Repeat ◽  
The Relationship ◽  
Crime Event

Near-repeat crime refers to a pattern whereby one crime event is soon followed by a similar crime event at a nearby location. Existing research on near-repeat crime patterns is inconclusive about where near-repeat patterns emerge and which physical and social factors influence them. The present research addressed this gap by examining the relationship between initiator events (i.e., the first event in a near-repeat pattern) and environmental characteristics to estimate where near-repeat patterns are most likely to emerge. A two-step analysis was undertaken using data on street robberies reported in Malmö, Sweden, for the years 2006–15. After determining near-repeat patterns, we assessed the correlations between initiator events and criminogenic places and socioeconomic indicators using a negative binomial regression at a street segment level. Our results show that both criminogenic places and socioeconomic indicators have a significant influence on the spatial variation of initiator events, suggesting that environmental characteristics can be used to explain the emergence of near-repeat patterns. Law enforcement agencies can utilize the findings in efforts to prevent further street robberies from occurring.

scholarly journals Retracted: Analysis of the Strength of Legal Firearms Restrictions for Perpetrators of Domestic Violence and Their Associations With Intimate Partner Homicide

2017 ◽  
Vol 187 (7) ◽  
pp. 1449-1455 ◽  
Author(s):  
April M Zeoli ◽  
Alexander McCourt ◽  
Shani Buggs ◽  
Shannon Frattaroli ◽  
David Lilley ◽  
...  
Keyword(s):  
Domestic Violence ◽  
Fixed Effects ◽  
Negative Binomial ◽  
State Level ◽  
Negative Binomial Regression ◽  
Intimate Partner ◽  
Restraining Order ◽  
Level Data ◽  
Binomial Regression ◽  
Firearms Restrictions

Abstract In this research, we estimate the association of firearm restrictions for domestic violence offenders with intimate partner homicides (IPHs) on the basis of the strength of the policies. We posit that the association of firearm laws with IPHs depends on the following characteristics of the laws: 1) breadth of coverage of high-risk individuals and situations restricted; 2) power to compel firearm surrender or removal from persons prohibited from having firearms; and 3) systems of accountability that prevent those prohibited from doing so from obtaining guns. We conducted a quantitative policy evaluation using annual state-level data from 1980 through 2013 for 45 US states. Based on the results of a series of robust, negative binomial regression models with state fixed effects, domestic violence restraining order firearm-prohibition laws are associated with 10% reductions in IPH. Statistically significant protective associations were evident only when restraining order prohibitions covered dating partners (−11%) and ex parte orders (−12%). Laws prohibiting access to those convicted of nonspecific violent misdemeanors were associated with a 24% reduction in IPH rates; there was no association when prohibitions were limited to domestic violence. Permit-to-purchase laws were associated with 10% reductions in IPHs. These findings should inform policymakers considering laws to maximize protections against IPH.

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