Criminal punishment and violent injury in Minnesota

Abstract Background Violence is one of the leading causes of injury and death in the United States. One-way society attempts to eliminate violence is through criminal punishment. Yet, in many contexts, punishment fails to reduce violence and may cause other harms. Current research on violence often suffers from same-source bias which can produce spurious associations. This study assesses the associations of different forms of criminal punishment (monetary sanctions, incarceration, and probation) with violent injuries in two unique datasets. Methods This study examines a unique combination of hospital discharge data and court administrative data, two Minnesota county-level data sources. First, we assess the spatial distribution of the three criminal punishment variables and two violent injury variables, violent injury overall and violent injury in children by county from 2010 to 2014, using Moran’s I statistic and Local Indicators of Spatial Autocorrelation. Then we assess the association of criminal punishment on violent injury and child abuse injury using a two-way fixed effects panel models. Results Child abuse injuries are relatively rare in our data but are significantly concentrated geographically, unlike violent injuries which are more dispersed throughout Minnesota. Incarceration and probation are significantly geographically concentrated in similar regions while monetary sanctions are not geographically concentrated. We find a link between probation loads and violent injury, specifically, with a 1 day increase in per capita probation supervision associated with a 0.044 increase in violent injury incidence per 1000 people. In contrast, monetary sanctions and incarceration loads have little association with either violent injury or child abuse injury incidence. Conclusions Criminal punishment is intended to reduce harm in society, but many argue that it may bring unintended consequences such as violence. This study finds that county-level probation has a modest positive association with county-level violent injury rates, but monetary sanctions and incarceration are less associated with violence injury rates. No measure of criminal punishment was associated with a reduction in violence. This study addresses a gap in previous literature by examining the association of punishment and violence in two unrelated datasets. High rates of criminal punishment and violent injury are both urgent public health emergencies. Further individual-level investigation is needed to assess potential links.

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Epidemiology of Injuries in National Collegiate Athletic Association Men's Football: 2014–2015 Through 2018–2019

Journal of Athletic Training ◽

10.4085/1062-6050-447-20 ◽

2021 ◽

Vol 56 (7) ◽

pp. 643-650

Author(s):

Avinash Chandran ◽

Sarah N. Morris ◽

Jacob R. Powell ◽

Adrian J. Boltz ◽

Hannah J. Robison ◽

...

Keyword(s):

National Collegiate Athletic Association ◽

Injury Rate ◽

The United States ◽

Lateral Ligament ◽

Surveillance Program ◽

Injury Incidence ◽

Collegiate Sports ◽

Injury Rates ◽

Rate Ratios ◽

Rules Changes

Context Football is among the most popular collegiate sports in the United States, and participation in National Collegiate Athletic Association (NCAA) football has risen in recent years. Background Continued monitoring of football injuries is important for capturing the evolving burden of injuries in NCAA football. The purpose of this study was to describe the epidemiology of football-related injuries among men's NCAA football players during the 2014–2015 through 2018–2019 academic years. Methods Exposure and injury data collected in the NCAA Injury Surveillance Program were analyzed. Injury counts, rates, and proportions were used to describe injury characteristics, and injury rate ratios were used to examine differential injury rates. Results The overall injury rate was 9.31 per 1000 athlete-exposures. Most injuries occurred during general play (17.5%), blocking (15.8%), and tackling (14.0%). Concussions (7.5%), lateral ligament complex tears (6.9%), and hamstring tears (4.7%) were the most commonly reported injuries. Conclusions Results of this study were generally consistent with previous findings, though changes over time in rates of commonly reported injuries warrant attention. Continued monitoring of injury incidence is needed to appraise the effectiveness of recently implemented rules changes.

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The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States

10.1101/2020.04.13.20063628 ◽

2020 ◽

Cited By ~ 16

Author(s):

James H. Fowler ◽

Seth J. Hill ◽

Remy Levin ◽

Nick Obradovich

Keyword(s):

United States ◽

Temporal Variation ◽

Fixed Effects ◽

National Level ◽

The United States ◽

Spatial And Temporal Variation ◽

Full Potential ◽

County Level ◽

Fixed Effects Model ◽

At Home

SummaryBackgroundIn March and April 2020, public health authorities in the United States acted to mitigate transmission of and hospitalizations from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). These actions were not coordinated at the national level, which raises the question of what might have happened if they were. It also creates an opportunity to use spatial and temporal variation to measure their effect with greater accuracy.MethodsWe combine publicly available data sources on the timing of stay-at-home orders and daily confirmed COVID-19 cases at the county level in the United States (N = 124,027). We then derive from the classic SIR model a two-way fixed-effects model and apply it to the data with controls for unmeasured differences between counties and over time. This enables us to estimate the effect of stay-at-home orders while accounting for local variation in factors like health systems and demographics, and temporal variation in national mitigation actions, access to tests, or exposure to media reports that could influence the course of the disease.FindingsMean county-level daily growth in COVID-19 infections peaked at 17.2% just before stay-at-home orders were issued. Two way fixed-effects regression estimates suggest that orders were associated with a 3.9 percentage point (95% CI 1.2 to 6.6) reduction in the growth rate after one week and a 6.9 percentage point (2.4 to 11.5) reduction after two weeks. By day 27 the reduction (22.6 percentage points, 14.8 to 30.5) had surpassed the growth at the peak, indicating that growth had turned negative and the number of new daily infections was beginning to decline. A hypothetical national stay-at-home order issued on March 13, 2020 when a national emergency was declared might have reduced cumulative infections by 63.3%, and might have helped to reverse exponential growth in the disease by April 10.InterpretationAlthough stay-at-home orders impose great costs to society, delayed responses and piecemeal application of these orders generate similar costs without obtaining the full potential benefits suggested by this analysis. The results here suggest that a coordinated nationwide stay-at-home order might have reduced by hundreds of thousands the current number of infections and by tens of thousands the total number of deaths from COVID-19. Future efforts in the United States and elsewhere to control pandemics should coordinate stay-at-home orders at the national level, especially for diseases for which local spread has already occurred and testing availability is delayed. Since stay-at-home orders reduce infection growth rates, early implementation when infection counts are still low would be most beneficial.FundingNone.

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Abstract 13360: The Association Between Food Insecurity and Cardiovascular Mortality in the United States From 2011 to 2017 - A Longitudinal Analysis

Circulation ◽

10.1161/circ.142.suppl_3.13360 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Stephen Y Wang ◽

Atheendar S Venkataramani ◽

Christina A Roberto ◽

Lauren A Eberly ◽

Peter W Groeneveld ◽

...

Keyword(s):

Food Insecurity ◽

Fixed Effects ◽

The United States ◽

Mortality Rates ◽

County Level ◽

Elderly Adults ◽

Mortality Trends ◽

Annual Percent Change ◽

Cross Sectional ◽

Longitudinal Changes

Introduction: Prior analyses suggest a link between food insecurity and cardiovascular (CV) health but are limited by cross-sectional designs. We investigated whether longitudinal changes in food insecurity are independently associated with CV mortality. Methods: Using National Center for Health Statistics data, we determined annual U.S. county-level age-adjusted CV mortality rates for non-elderly (20-64 years old) and elderly (65 years and older) adults. County-level food insecurity rates were obtained from the Map the Meal Gap project. We examined CV mortality trends by quartiles of average annual percent change (APC) in food insecurity. Using a Poisson fixed effects estimator, we assessed the association between longitudinal changes in food insecurity and CV mortality rates after accounting for time-varying demographic (proportion of residents who were male, black, Hispanic), economic (median household income, unemployment, poverty, education attainment, and housing vacancy rates), and healthcare access (insurance coverage, density of healthcare providers and hospital beds) variables. Results: Between 2011 and 2017, mean food insecurity rates decreased from 14.7% to 13.3%. In counties in the highest quartile of APC for absolute value change in food insecurity, non-elderly CV mortality increased from 82.2(SD=33.9) to 87.4(SD=37.3) per 100,000 individuals (p<0.001), while in counties in the lowest quartile of APC, mortality was stable [60.8(SD=22.2) to 60.0(SD=23.0) per 100,000 individuals, p=0.64]. Elderly CV mortality significantly declined in all quartiles [1643.3(SD=315.7) to 1542.7(SD=299.4) per 100,000 (p<0.001) in the highest quartile and 1408.3(SD=225.9) to 1338.6(SD=213.8) per 100,000 (p<0.001) in the lowest quartile). A 1 percentage point increase in food insecurity was independently associated with a 0.83% (95% CI 0.42 - 1.25, P<0.001) increase in CV mortality for non-elderly adults. This was not significant for elderly adults (-0.06%, 95% CI -0.39 - 0.28, P=0.74). Conclusion: From 2011 to 2017, an increase in food insecurity was independently associated with an increase in CV mortality rates for non-elderly adults in the U.S. Interventions targeting food insecurity may play a role in improving community CV health.

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Hide and Seek

Legal and Ethical Issues in Emergency Medicine ◽

10.1093/med/9780190066420.003.0010 ◽

2020 ◽

pp. 75-82

Author(s):

Purva Grover

Keyword(s):

United States ◽

Child Abuse ◽

Patient Autonomy ◽

The United States ◽

Mandatory Reporting ◽

Unintended Consequences ◽

Adult Patients ◽

Negative Effects ◽

Legal Obligations ◽

Mandated Reporters

The system of mandatory reporting was created in response to a growing recognition of devastation that child abuse was causing in the United States. All states designate people in certain professions as “mandated reporters.” This has led to discussion regarding unintended consequences or negative effects of mandatory reporting. What are our obligations toward adult patients who confide that they were abused as a child but are unsure if they want to report this now? Are we still the mandated reporters? How does patient autonomy factor into this? These laws and statutes are complex, and our legal obligations must be weighed against various ethical and practical considerations.

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Population Change and Income Inequality in Rural America

10.31235/osf.io/g3yhe ◽

2020 ◽

Author(s):

Jaclyn L.W. Butler ◽

Grace Wildermuth ◽

Brian C. Thiede ◽

David L. Brown

Keyword(s):

Income Inequality ◽

Population Growth ◽

Rural Areas ◽

Fixed Effects ◽

Population Change ◽

Population Decline ◽

The United States ◽

County Level ◽

Level Data ◽

The Relationship

This paper examines the effects of population growth and decline on county-level income inequality in the United States from 1980 to 2016. Findings from previous research have shown that income inequality is positively associated with population change, but these studies have not explicitly tested for differences between the impacts of population growth and decline. Understanding the implications of population dynamics is particularly important given that many rural areas are characterized by population decline. We analyze county-level data (n=15,375 county-decades) from the Decennial Census and American Community Survey (ACS), applying fixed effects models to estimate the respective effects of population growth and decline on income inequality, to identify the processes that mediate the links between population change and inequality, and to assess whether these effects are moderated by county-level economic and demographic characteristics. We find evidence that population decline is associated with increased levels of income inequality relative to counties experiencing stable and high rates of population growth. This relationship remains robust across a variety of model specifications, including models that account for changes in counties’ employment, sociodemographic, and ethnoracial composition. We also find that the relationship between income inequality and population change varies by metropolitan status, baseline level of inequality, and region.

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Individualistic culture increases economic mobility in the United States

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2107273118 ◽

2021 ◽

Vol 118 (37) ◽

pp. e2107273118

Author(s):

Bryan Leonard ◽

Steven M. Smith

Keyword(s):

United States ◽

Fixed Effects ◽

Causal Effect ◽

The United States ◽

County Level ◽

Growing Up ◽

Formal Policy ◽

Modern Economic ◽

Rugged Individualism ◽

The 19Th Century

Where an individual grows up has large implications for their long-term economic outcomes, including earnings and intergenerational mobility. Even within the United States, the “causal effect of place” varies greatly and cannot be fully explained by socioeconomic conditions. Across different nations, variation in growth and mobility have been linked to more individualistic cultures. We assess how variation of historically driven individualism within the United States affects mobility. Areas in the United States that were isolated on the frontier for longer periods of time during the 19th century have a stronger culture of “rugged individualism” [S. Bazzi, M. Fiszbein, M. Gebresilasse, Econometrica 88, 2329–2368 (2020)]. We combine county-level measures of frontier experience with modern measures of the causal effect of place on mobility—the predicted percentage change in an individual’s earnings at age 26 y associated with “growing up” in a particular county [R. Chetty, N. Hendren, Q. J. Econ. 133, 1163–1228 (2018)]. Using commuting zone fixed effects and a suite of county-level controls to absorb regional variation in frontier experience and modern economic conditions, we find an additional decade of frontier experience results in 25% greater modern-day income mobility for children of parents in the 25th percentile of income and 14% for those born to parents in the 75th percentile. We use mediation analysis to present suggestive evidence that informal manifestations of “rugged individualism”—those embodied by the individuals themselves—are more strongly associated with upward mobility than formal policy or selective migration.

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Lyme Disease Misinterpreted as Child Abuse

Case Reports in Orthopedics ◽

10.1155/2021/6665935 ◽

2021 ◽

Vol 2021 ◽

pp. 1-5

Author(s):

Tommy Pan ◽

Adam Nasreddine ◽

Myra Trivellas ◽

William L. Hennrikus

Keyword(s):

Differential Diagnosis ◽

Child Abuse ◽

Lyme Disease ◽

Endemic Area ◽

The United States ◽

Unintended Consequences ◽

Fracture Care ◽

Child Fatality ◽

Common Causes ◽

Scarcity Of Resources

Child abuse is one of the most common causes for child fatality in the United States. Inaccurate reporting of child abuse combined with scarcity of resources for child abuse evaluations can lead to unintended consequences for children and their families. The differential diagnosis of child abuse is varied. To our knowledge, there are no reports in the literature on Lyme disease mimicking child abuse. The current study presents the case of a child from an endemic area for Lyme disease presenting with skin bruising, fracture, and swollen knee. The child was reported for child abuse by the pediatrician and then referred to the orthopaedic surgeon for fracture care.

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Quantifying the mortality impact of the 1935 old-age assistance

European Review of Economic History ◽

10.1093/ereh/heab001 ◽

2021 ◽

Author(s):

Gregori Galofré-Vilà ◽

Martin McKee ◽

David Stuckler

Keyword(s):

United States ◽

Old Age ◽

Event Study ◽

Fixed Effects ◽

Older Persons ◽

The Elderly ◽

The United States ◽

County Level ◽

Level Data ◽

Old Age Assistance

Abstract In 1935, the United States introduced the old-age assistance (OAA) program, a means-tested program to help the elderly poor. The OAA improved retirement conditions and aimed to enable older persons to live independently. We use the transition from early elderly plans to OAA and the large differences in payments and eligibility across states to show that OAA reduced mortality by between 30 and 39 percent among those older than 65 years. This finding, based on an event study design, is robust to a range of specifications, a range of fixed effects, placebo tests, and a border-pair policy discontinuity design using county-level data. The largest mortality reductions came from drops in communicable and infectious diseases, such as influenza and nephritis, and mostly affected white citizens.

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Are All Politics National? County-Level Social Contexts and Inequality Remediation Attitudes, 2006 to 2012

Socius Sociological Research for a Dynamic World ◽

10.1177/23780231211009990 ◽

2021 ◽

Vol 7 ◽

pp. 237802312110099

Author(s):

Andrew M. Lindner ◽

Jason N. Houle

Keyword(s):

Income Inequality ◽

Fixed Effects ◽

Government Intervention ◽

Local Level ◽

General Social Survey ◽

The United States ◽

Social Contexts ◽

County Level ◽

Social Survey ◽

Individual Level

Despite growing economic inequality in recent decades, public support for government intervention to address it has been stable. A substantial literature has documented the individual-level demographic, social, and political characteristics that are associated with the extent to which individuals favor government intervention to reduce inequality. However, less work has examined how the local social environments that individuals are embedded in shape attitudes regarding inequality remediation. Using data from the General Social Survey (2006–2012) and other data sources, the authors examine whether local economic and social characteristics are associated with individuals’ support for government intervention to address income inequality in the United States during the Great Recession. Specifically, the authors link restricted General Social Survey data with place-level identifiers to county-level data on local income inequality, racial segregation, and partisan leanings. Broadly, the authors find that although individual-level conditions and year fixed effects are strongly correlated with perceptions about inequality remediation, most local-level characteristics were not strongly nor significantly associated with individual attitudes regarding government intervention to address inequality. These findings suggest that individuals formulate policy stances regarding inequality on the basis of national messaging rather than on observations within their own communities.

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The association of opening K–12 schools with the spread of COVID-19 in the United States: County-level panel data analysis

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2103420118 ◽

2021 ◽

Vol 118 (42) ◽

pp. e2103420118

Author(s):

Victor Chernozhukov ◽

Hiroyuki Kasahara ◽

Paul Schrimpf

Keyword(s):

United States ◽

Panel Data ◽

Growth Rates ◽

Fixed Effects ◽

Panel Data Analysis ◽

The United States ◽

Dynamic Panel Data ◽

County Level ◽

Past Infection ◽

K 12

This paper empirically examines how the opening of K–12 schools is associated with the spread of COVID-19 using county-level panel data in the United States. As preliminary evidence, our event-study analysis indicates that cases and deaths in counties with in-person or hybrid opening relative to those with remote opening substantially increased after the school opening date, especially for counties without any mask mandate for staff. Our main analysis uses a dynamic panel data model for case and death growth rates, where we control for dynamically evolving mitigation policies, past infection levels, and additive county-level and state-week “fixed” effects. This analysis shows that an increase in visits to both K–12 schools and colleges is associated with a subsequent increase in case and death growth rates. The estimates indicate that fully opening K–12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the association of K–12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These findings support policies that promote masking and other precautionary measures at schools and giving vaccine priority to education workers.

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