Abstract P91: Excess Cerebrovascular Mortality in the U.S. During the Covid-19 Pandemic

Introduction: The magnitude and drivers of excess cerebrovascular-specific mortality during the coronavirus-19 (COVID-19) pandemic are unknown. We aim to quantify excess stroke-related death and characterize its association with psychosocial factors and emerging COVID-19 related mortality. Methods: U.S. and state-level excess cerebrovascular deaths from January-May 2020 were quantified by Poisson regression models built using National Center for Health Statistic (NCHS) data. Weekly excess cerebrovascular deaths in the U.S. were analyzed as functions of time-varying, weekly stroke-related EMS calls and weekly COVID-19 deaths by univariable linear regression. A state-level negative binomial regression analysis was performed to determine the association between excess cerebrovascular deaths and social distancing (degree of change in mobility per Google COVID-19 Community Mobility Reports) during the height of the pandemic after the first COVID-19 death (February 29, 2020), adjusting for cumulative COVID-19 related deaths and completeness of deaths attributable to COVID-19 in NCHS. Findings: There were 918 more cerebrovascular deaths than expected from January 1-May 16 th , 2020 in the U.S. Excess cerebrovascular mortality occurred during every week between March 28-May 2 nd , 2020, up to 7.8% during the week of April 18 th . Decreased stroke-related EMS calls were associated with excess stroke deaths one (β -0.06, 95% CI -0.11, -0.02) and two weeks (β -0.08, 95% CI -0.12, -0.04) later. There was no significant association between weekly excess stroke death and COVID-19 death. Twenty-three states and NYC experienced excess cerebrovascular mortality during the pandemic height. At the state level, a 10% increase in social distancing was associated with a 4.3% increase in stroke deaths (IRR 1.043, 95% CI 1.001–1.085) after adjusting for COVID-19 mortality. Conclusions: Excess U.S. cerebrovascular deaths during the COVID-19 pandemic were observed with decreases in stroke-related EMS calls nationally and less mobility at the state level. Public health measures are needed to identify and counter the reticence to seeking medical care for acute stroke during the COVID-19 pandemic.

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

American Journal of Epidemiology ◽

10.1093/aje/kwx362 ◽

2017 ◽

Vol 187 (7) ◽

pp. 1449-1455 ◽

Cited By ~ 32

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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Statewide Interventions and Covid-19 Mortality in the United States: An Observational Study

Clinical Infectious Diseases ◽

10.1093/cid/ciaa923 ◽

2020 ◽

Cited By ~ 2

Author(s):

Nadir Yehya ◽

Atheendar Venkataramani ◽

Michael O Harhay

Keyword(s):

United States ◽

Negative Binomial ◽

State Level ◽

Negative Binomial Regression ◽

The United States ◽

School Closure ◽

Sensitivity Analyses ◽

Test Model ◽

School Closures ◽

Social Distancing

ABSTRACT Background Social distancing is encouraged to mitigate viral spreading during outbreaks. However, the association between distancing and patient-centered outcomes in Covid-19 has not been demonstrated. In the United States social distancing orders are implemented at the state level with variable timing of onset. Emergency declarations and school closures were two early statewide interventions. Methods To determine whether later distancing interventions were associated with higher mortality, we performed a state-level analysis in 55,146 Covid-19 non-survivors. We tested the association between timing of emergency declarations and school closures with 28-day mortality using multivariable negative binomial regression. Day 1 for each state was set to when they recorded ≥ 10 deaths. We performed sensitivity analyses to test model assumptions. Results At time of analysis, 37 of 50 states had ≥ 10 deaths and 28 follow-up days. Both later emergency declaration (adjusted mortality rate ratio [aMRR] 1.05 per day delay, 95% CI 1.00 to 1.09, p=0.040) and later school closure (aMRR 1.05, 95% CI 1.01 to 1.09, p=0.008) were associated with more deaths. When assessing all 50 states and setting day 1 to the day a state recorded its first death, delays in declaring an emergency (aMRR 1.05, 95% CI 1.01 to 1.09, p=0.020) or closing schools (aMRR 1.06, 95% CI 1.03 to 1.09, p<0.001) were associated with more deaths. Results were unchanged when excluding New York and New Jersey. Conclusions Later statewide emergency declarations and school closure were associated with higher Covid-19 mortality. Each day of delay increased mortality risk 5 to 6%.

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Network analysis of firearm movement among US states

10.21203/rs.3.rs-37154/v3 ◽

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.

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Network analysis of firearm movement among US states

10.21203/rs.3.rs-37154/v2 ◽

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.

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Injustices in pandemic vulnerability: A spatial-statistical analysis of the CDC Social Vulnerability Index and COVID-19 outcomes in the U.S.

10.1101/2021.05.27.21257889 ◽

2021 ◽

Author(s):

Jamie Song ◽

Douglas Wiebe ◽

Sara Solomon ◽

Eugenia South

Keyword(s):

Logistic Regression ◽

Social Vulnerability ◽

Negative Binomial ◽

Hot Spot ◽

Negative Binomial Regression ◽

Vulnerability Index ◽

Social Vulnerability Index ◽

Binomial Regression ◽

Average Annual Temperature ◽

The U.S

Background: The COVID-19 pandemic has exacerbated health injustices in the U.S. driven by racism and other forms of structural violence. Research has shown the disproportionate impacts of COVID-19 morbidity and mortality in the most marginalized communities. Objectives: We examined the associations between COVID-19 cumulative incidence (CI) and case-fatality risk (CFR) and the CDC's Social Vulnerability Index (SVI), a composite score assessing historical marginalization and thus vulnerability to disaster events. Methods: Using county-level data from national databases, we used population density, Gini index, percent uninsured, and average annual temperature as covariates, and employed negative binomial regression to evaluate relationships between SVI and COVID-19 outcomes. Optimized hot spot analysis identified hot spots of COVID-19 CI and CFR, which were compared in terms of SVI using logistic regression. Results: As of 2/3/21, 26,452,031 cases of and 448,786 deaths from COVID-19 had been reported in the U.S. Negative binomial regression showed that counties in the top SVI quintile reported 13.7% higher CI (p<0.001) than those in the bottom SVI quintile. Additionally, each unit increase in a county's SVI score was associated with a 0.2% increase in CFR (p<0.001). Logistic regression analysis showed that counties in the lowest SVI quintile had significantly greater odds of being in a CI hot spot than all other counties, yet counties in the highest SVI quintile had 63% greater odds (p=0.008) of being in a CFR hot spot than counties in the lowest SVI quintile. Conclusion: We demonstrated a significant relationship between SVI and CFR, but the relationship between SVI and CI is complex and warrants further investigation. SVI may help elucidate unequal impacts of COVID-19 and guide prioritization of vaccines to communities most impacted by structural injustices.

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

Revista de Saúde Pública ◽

10.1590/s0034-89102009000500001 ◽

2009 ◽

Vol 43 (5) ◽

pp. 733-742 ◽

Cited By ~ 12

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.

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Perceived Benefits Matter the Most in COVID-19 Preventive Behaviors: Empirical Evidence from Okara District, Pakistan

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18136772 ◽

2021 ◽

Vol 18 (13) ◽

pp. 6772

Author(s):

Gulzar H. Shah ◽

Ansar Ali Faraz ◽

Hina Khan ◽

Kristie C. Waterfield

Keyword(s):

Negative Binomial ◽

Negative Binomial Regression ◽

Cluster Sampling ◽

Perceived Benefits ◽

Cross Sectional ◽

Social Distancing ◽

Binomial Regression ◽

Prevention Behavior ◽

Behavior Scale ◽

The City

The 2019 coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus has affected the social determinants of health, worsening health inequities and deteriorating healthcare capacities around the globe. The objective of this study is to investigate the COVID-19 prevention behaviors within the framework of the Health Belief Model in the city of Depalpur in the Okara District of Pakistan in May 2020. Using an observational, cross-sectional, and quantitative study design, a face-to-face field survey was conducted during the epidemic of COVID-19 in district Okara, Pakistan. A sample of 500 adults was selected from the city of Depalpur the in Okara district of Pakistan, using a two-stage sampling design with cluster sampling in stage one and systematic random sampling at stage two. A COVID-19 prevention behavior scale was computed based on twelve dichotomous items. Descriptive statistics, analysis of variance (ANOVA), and negative binomial regression analyses were performed. The most common prevention behavior among study participants was avoiding going for walks in the parks (81.0%), followed by not leaving home during the lockdown (72.6%), and washing hands every day with soap and water for 20 s after going out of their home (64.0%). Fewer people exhibited prevention behaviors such as social distancing (e.g., staying at least six feet away from other people) which in the EU was recommended to be a minimum of 1.5–2 m (44.4%) and following all of the basic protective measures (e.g., hand washing, use of a face covering in public, social distancing) in order to protect against COVID-19 (33.0%). The results from the negative binomial regression analysis showed that after controlling for the other HBM constructs and sociodemographic factors, only the perceived benefits of preventative actions showed significant association with the prevention behavior scale (IRR, 1.16; CI, 1.061–1.276; p < 0.001). The study findings show that public health interventions attempting to control the spread of COVID-19 in Pakistan may want to affect a change in people’s perceived benefits of preventative actions through mass awareness-raising campaigns.

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Firearm laws and the network of firearm movement among US states

BMC Public Health ◽

10.1186/s12889-021-11772-y ◽

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.

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Network analysis of firearm movement among US states

10.21203/rs.3.rs-37154/v1 ◽

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

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School Physical Education Policies and Practices and Student Physical Education Attendance

American Journal of Health Studies ◽

10.47779/ajhs.2016.142 ◽

2020 ◽

Vol 31 (2) ◽

Author(s):

Jinsook Kim ◽

Lynn Herrmann

Keyword(s):

High School ◽

High School Students ◽

Physical Education ◽

Negative Binomial ◽

State Level ◽

Negative Binomial Regression ◽

Education Policies ◽

School Students ◽

Binomial Regression ◽

Using Data

This study examined how state-level measures of school-reported physical education (PE) provisions and exemption practices correlated to student-reported PE attendance among high school students, using data (n=50077) from state-representative schools and students from multiple states. Negative binomial regression was used to examine the association of the frequency of PE attendance with schools’ PE provision and exemption, controlling for student characteristics. The percentage of schools offering PE for all grades was positively associated with PE attendance more strongly among girls and higher-grade students. Permissive exemption policies were not associated with PE attendance. Offering PE for all grades may enhance PE attendance.

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