U.S. national, regional, and state-specific socioeconomic factors correlate with child and adolescent ADHD diagnoses pre-COVID-19 pandemic

AbstractAttention-deficit/hyperactivity disorder (ADHD), the most diagnosed emerging neurodevelopmental disorder in children, is a growing health crisis in the United States. Due to the potential increase in ADHD severity during and post the COVID-19 pandemic, we analyzed recent national and two state-specific ADHD data distribution among U.S. children and adolescents by investigating a broad range of socioeconomic status (SES) factors. Child and adolescent ADHD diagnosis and treatment data were parent-reported via National Survey of Children’s Health (NSCH). The nationwide childhood prevalence of ADHD is 8.7%, and 62.1% of diagnosed children are taking medication. Louisiana (15.7%) has the highest percentage of children diagnosed with ADHD and California (5.6%) has the lowest, followed by Nevada (5.9%). Multiple correspondence analysis (MCA, n = 51,939) examining 30 factors highlights four areas of interest at the national and state level: race/ethnicity, financial status, family structure, and neighborhood characteristics. Positive correlations between ADHD diagnosis and unsafe school, unsafe neighborhood, and economic hardship are evident nationally and statewide, while the association between a lack of ADHD diagnosis and higher urban neighborhood amenities are evident nationally, but not in two opposing outlier states—Louisiana or Nevada. National and state-specific hierarchical analyses demonstrate significant correlations between the various SES factors and ADHD outcomes. Since the national analysis does not account for the demographic heterogeneity within regions or individual states, the U.S. should rely on comprehensive, county-specific, near real-time data reporting to effectively model and mitigate the ADHD epidemic and similar national health crises.

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Short-term change in air pollution following the COVID-19 state of emergency: A national analysis for the United States

10.1101/2020.08.04.20168237 ◽

2020 ◽

Cited By ~ 1

Author(s):

Pooja Tyagi ◽

Danielle Braun ◽

Benjamin Sabath ◽

Lucas Henneman ◽

Francesca Dominici

Keyword(s):

Air Pollution ◽

Moving Average ◽

State Level ◽

The United States ◽

Mobile Source ◽

Economic Changes ◽

Short Term Change ◽

Term Change ◽

National Analysis ◽

Almost All

Lockdown measures taken in response to the COVID-19 pandemic produced sudden social and economic changes. We examined the extent of air pollution reduction that was attained under these extreme circumstances, whether these reductions occurred everywhere in the US, and the local factors that drove them. Employing counterfactual time series analysis based on seasonal autoregressive integrated moving average models, we found that these extreme lockdown measures led to a reduction in the weekly PM2.5 average by up to 3.4 micrograms per cubic meter and the weekly NO2 average by up to 11 ppb. These values represent a substantial fraction of the annual mean NAAQS values of 12 micrograms per cubic meter and 53 ppb, respectively. We found evidence of a statistically significant decline in NO2 concentrations following the state-level emergency declaration in almost all states. However, statistically significant declines in PM2.5 occurred mostly in the West Coast and the Northeast. Certain states experienced a decline in NO2 but an increase in PM2.5 concentrations, indicating that these two pollutants arise from dissimilar sources in these states. Finally, we found evidence that states with a higher percentage of mobile source emissions prior to the emergency measures experienced a greater decline in NO2 levels during the pandemic. Although the current social and economic restrictions are not sustainable, our results provide a benchmark to estimate the extent to which air pollution reductions can be achieved. We also identify factors that contributed to the magnitude of pollutant reductions, which can help guide future state-level policies to sustainably reduce air pollution.

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Surveilling Influenza Incidence With Centers for Disease Control and Prevention Web Traffic Data: Demonstration Using a Novel Dataset (Preprint)

10.2196/preprints.14337 ◽

2019 ◽

Author(s):

Wendy K Caldwell ◽

Geoffrey Fairchild ◽

Sara Y Del Valle

Keyword(s):

Disease Control ◽

Disease Surveillance ◽

State Level ◽

The United States ◽

Influenza Surveillance ◽

Traffic Data ◽

Time Data ◽

Control And Prevention ◽

Data Source ◽

Centers For Disease Control

BACKGROUND Influenza epidemics result in a public health and economic burden worldwide. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1 to 2 weeks. A means of obtaining real-time data and forecasting future outbreaks is desirable to provide more timely responses to influenza epidemics. OBJECTIVE This study aimed to present the first implementation of a novel dataset by demonstrating its ability to supplement traditional disease surveillance at multiple spatial resolutions. METHODS We used internet traffic data from the Centers for Disease Control and Prevention (CDC) website to determine the potential usability of this data source. We tested the traffic generated by 10 influenza-related pages in 8 states and 9 census divisions within the United States and compared it against clinical surveillance data. RESULTS Our results yielded an <i>r</i><sup>2</sup> value of 0.955 in the most successful case, promising results for some cases, and unsuccessful results for other cases. In the interest of scientific transparency to further the understanding of when internet data streams are an appropriate supplemental data source, we also included negative results (ie, unsuccessful models). Models that focused on a single influenza season were more successful than those that attempted to model multiple influenza seasons. Geographic resolution appeared to play a key role, with national and regional models being more successful, overall, than models at the state level. CONCLUSIONS These results demonstrate that internet data may be able to complement traditional influenza surveillance in some cases but not in others. Specifically, our results show that the CDC website traffic may inform national- and division-level models but not models for each individual state. In addition, our results show better agreement when the data were broken up by seasons instead of aggregated over several years. We anticipate that this work will lead to more complex nowcasting and forecasting models using this data stream.

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A National Analysis of Shackling Laws and Policies as They Relate to Pregnant Incarcerated Women

Feminist Criminology ◽

10.1177/1557085117737617 ◽

2017 ◽

Vol 14 (2) ◽

pp. 263-284 ◽

Cited By ~ 1

Author(s):

Sarah Y. Thomas ◽

Jennifer L. Lanterman

Keyword(s):

United States ◽

Content Analysis ◽

State Level ◽

The United States ◽

Incarcerated Women ◽

Potential Outcomes ◽

Laws And Policies ◽

National Analysis ◽

Gender Specific ◽

Specific Orientation

Pregnant incarcerated women pose unique challenges in jails and prisons. Many states still require or permit the shackling of pregnant incarcerated women throughout the pregnancy and during labor, delivery, and recovery. This study includes a content analysis of shackling laws and policies currently in effect throughout the United States. The findings identify the range of shackling laws and policies at the state level and whether these laws and policies adhere to a female indifferent or gender-specific orientation. Finally, the implications are discussed to assist lawmakers and correctional administrators in understanding the effects and potential outcomes of certain types of laws and policies.

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Surveilling Influenza Incidence With Centers for Disease Control and Prevention Web Traffic Data: Demonstration Using a Novel Dataset

Journal of Medical Internet Research ◽

10.2196/14337 ◽

2020 ◽

Vol 22 (7) ◽

pp. e14337

Author(s):

Wendy K Caldwell ◽

Geoffrey Fairchild ◽

Sara Y Del Valle

Keyword(s):

Disease Control ◽

Disease Surveillance ◽

State Level ◽

The United States ◽

Influenza Surveillance ◽

Traffic Data ◽

Time Data ◽

Control And Prevention ◽

Data Source ◽

Centers For Disease Control

Background Influenza epidemics result in a public health and economic burden worldwide. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1 to 2 weeks. A means of obtaining real-time data and forecasting future outbreaks is desirable to provide more timely responses to influenza epidemics. Objective This study aimed to present the first implementation of a novel dataset by demonstrating its ability to supplement traditional disease surveillance at multiple spatial resolutions. Methods We used internet traffic data from the Centers for Disease Control and Prevention (CDC) website to determine the potential usability of this data source. We tested the traffic generated by 10 influenza-related pages in 8 states and 9 census divisions within the United States and compared it against clinical surveillance data. Results Our results yielded an r2 value of 0.955 in the most successful case, promising results for some cases, and unsuccessful results for other cases. In the interest of scientific transparency to further the understanding of when internet data streams are an appropriate supplemental data source, we also included negative results (ie, unsuccessful models). Models that focused on a single influenza season were more successful than those that attempted to model multiple influenza seasons. Geographic resolution appeared to play a key role, with national and regional models being more successful, overall, than models at the state level. Conclusions These results demonstrate that internet data may be able to complement traditional influenza surveillance in some cases but not in others. Specifically, our results show that the CDC website traffic may inform national- and division-level models but not models for each individual state. In addition, our results show better agreement when the data were broken up by seasons instead of aggregated over several years. We anticipate that this work will lead to more complex nowcasting and forecasting models using this data stream.

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COVID-19 predictability in the United States using Google Trends time series

Scientific Reports ◽

10.1038/s41598-020-77275-9 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

Amaryllis Mavragani ◽

Konstantinos Gkillas

Keyword(s):

United States ◽

Robust Regression ◽

Preliminary Investigation ◽

Health Resources ◽

State Level ◽

The United States ◽

Small Sample ◽

Google Trends ◽

Time Data ◽

Monitoring And Forecasting

AbstractDuring the unprecedented situation that all countries around the globe are facing due to the Coronavirus disease 2019 (COVID-19) pandemic, which has also had severe socioeconomic consequences, it is imperative to explore novel approaches to monitoring and forecasting regional outbreaks as they happen or even before they do so. To that end, in this paper, the role of Google query data in the predictability of COVID-19 in the United States at both national and state level is presented. As a preliminary investigation, Pearson and Kendall rank correlations are examined to explore the relationship between Google Trends data and COVID-19 data on cases and deaths. Next, a COVID-19 predictability analysis is performed, with the employed model being a quantile regression that is bias corrected via bootstrap simulation, i.e., a robust regression analysis that is the appropriate statistical approach to taking against the presence of outliers in the sample while also mitigating small sample estimation bias. The results indicate that there are statistically significant correlations between Google Trends and COVID-19 data, while the estimated models exhibit strong COVID-19 predictability. In line with previous work that has suggested that online real-time data are valuable in the monitoring and forecasting of epidemics and outbreaks, it is evident that such infodemiology approaches can assist public health policy makers in addressing the most crucial issues: flattening the curve, allocating health resources, and increasing the effectiveness and preparedness of their respective health care systems.

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COVID-19 lockdowns and demographically-relevant Google Trends: A cross-national analysis

PLoS ONE ◽

10.1371/journal.pone.0248072 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248072

Author(s):

Lawrence M. Berger ◽

Giulia Ferrari ◽

Marion Leturcq ◽

Lidia Panico ◽

Anne Solaz

Keyword(s):

Family Formation ◽

State Level ◽

The United States ◽

Google Trends ◽

Economic Uncertainty ◽

Demographic Trends ◽

Family Demography ◽

National Analysis ◽

The U.S ◽

Cross National

The spread of COVID-19 and resulting local and national lockdowns have a host of potential consequences for demographic trends. While impacts on mortality and, to some extent, short-term migration flows are beginning to be documented, it is too early to measure actual consequences for family demography. To gain insight into potential future consequences of the lockdown for family demography, we use cross-national Google Trends search data to explore whether trends in searches for words related to fertility, relationship formation, and relationship dissolution changed following lockdowns compared to average, pre-lockdown levels in Europe and the United States. Because lockdowns were not widely anticipated or simultaneous in timing or intensity, we exploit variability over time and between countries (and U.S. states). We use a panel event-study design and difference-in-differences methods, and account for seasonal trends and average country-level (or state-level) differences in searches. We find statistically significant impacts of lockdown timing on changes in searches for terms such as wedding and those related to condom use, emergency contraception, pregnancy tests, and abortion, but little evidence of changes in searches related to fertility. Impacts for union formation and dissolution tended to only be statistically significant at the start of a lockdown with a return to average-levels about 2 to 3 months after lockdown initiation, particularly in Europe. Compared to Europe, returns to average search levels were less evident for the U.S., even 2 to 3 months after lockdowns were introduced. This may be due to the fact, in the U.S., health and social policy responses were less demarcated than in Europe, such that economic uncertainty was likely of larger magnitude. Such pandemic-related economic uncertainty may therefore have the potential to slightly increase already existing polarization in family formation behaviours in the U.S. Alongside contributing to the wider literature on economic uncertainty and family behaviors, this paper also proposes strategies for efficient use of Google Trends data, such as making relative comparisons and testing sensitivity to outliers, and provides a template and cautions for their use in demographic research when actual demographic trends data are not yet available.

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Applicability of management guidelines for surfing resources in California

Shore & Beach ◽

10.34237/1008835 ◽

2020 ◽

pp. 53-64

Author(s):

Edward Atkin ◽

Dan Reineman ◽

Jesse Reiblich ◽

David Revell

Keyword(s):

New Zealand ◽

National Level ◽

State Level ◽

The United States ◽

Management Guidelines ◽

For Profit ◽

Aotearoa New Zealand ◽

Coastal Marine ◽

Management Measures ◽

Legal Frameworks

Surf breaks are finite, valuable, and vulnerable natural resources, that not only influence community and cultural identities, but are a source of revenue and provide a range of health benefits. Despite these values, surf breaks largely lack recognition as coastal resources and therefore the associated management measures required to maintain them. Some countries, especially those endowed with high-quality surf breaks and where the sport of surfing is accepted as mainstream, have recognized the value of surfing resources and have specific policies for their conservation. In Aotearoa New Zealand surf breaks are included within national environmental policy. Aotearoa New Zealand has recently produced Management Guidelines for Surfing Resources (MGSR), which were developed in conjunction with universities, regional authorities, not-for-profit entities, and government agencies. The MGSR provide recommendations for both consenting authorities and those wishing to undertake activities in the coastal marine area, as well as tools and techniques to aid in the management of surfing resources. While the MGSR are firmly aligned with Aotearoa New Zealand’s cultural and legal frameworks, much of their content is applicable to surf breaks worldwide. In the United States, there are several national-level and state-level statutes that are generally relevant to various aspects of surfing resources, but there is no law or policy that directly addresses them. This paper describes the MGSR, considers California’s existing governance frameworks, and examines the potential benefits of adapting and expanding the MGSR in this state.

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The Emerging Education Reversal in the United States: National and State-Level Trends

SSRN Electronic Journal ◽

10.2139/ssrn.1652520 ◽

2010 ◽

Author(s):

M. D. R. Evans ◽

Nate Breznau

Keyword(s):

United States ◽

State Level ◽

The United States

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Can increases in Twitter posts predict increases in cumulative incidence of COVID-19 in the United States? Evidence that social media can inform epidemic surveillance. (Preprint)

10.2196/preprints.21132 ◽

2020 ◽

Author(s):

Ruoyan Sun ◽

Henna Budhwani

Keyword(s):

Public Health ◽

United States ◽

Cumulative Incidence ◽

Hot Spots ◽

Adult Population ◽

State Level ◽

The United States ◽

Education Attainment ◽

Public Health Systems ◽

Per Capita

BACKGROUND Though public health systems are responding rapidly to the COVID-19 pandemic, outcomes from publicly available, crowd-sourced big data may assist in helping to identify hot spots, prioritize equipment allocation and staffing, while also informing health policy related to “shelter in place” and social distancing recommendations. OBJECTIVE To assess if the rising state-level prevalence of COVID-19 related posts on Twitter (tweets) is predictive of state-level cumulative COVID-19 incidence after controlling for socio-economic characteristics. METHODS We identified extracted COVID-19 related tweets from January 21st to March 7th (2020) across all 50 states (N = 7,427,057). Tweets were combined with state-level characteristics and confirmed COVID-19 cases to determine the association between public commentary and cumulative incidence. RESULTS The cumulative incidence of COVID-19 cases varied significantly across states. Ratio of tweet increase (p=0.03), number of physicians per 1,000 population (p=0.01), education attainment (p=0.006), income per capita (p = 0.002), and percentage of adult population (p=0.003) were positively associated with cumulative incidence. Ratio of tweet increase was significantly associated with the logarithmic of cumulative incidence (p=0.06) with a coefficient of 0.26. CONCLUSIONS An increase in the prevalence of state-level tweets was predictive of an increase in COVID-19 diagnoses, providing evidence that Twitter can be a valuable surveillance tool for public health.

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Dissent in the Atlantic World, 1787–1830

10.1093/oso/9780198702245.003.0011 ◽

2018 ◽

Author(s):

Katherine Carté Engel

Keyword(s):

United States ◽

African Americans ◽

First Amendment ◽

Church And State ◽

State Level ◽

The United States ◽

American Population ◽

Simple Fact ◽

General Role

The very term ‘Dissenter’ became problematic in the United States, following the passing of the First Amendment. The formal separation of Church and state embodied in the First Amendment was followed by the ending of state-level tax support for churches. None of the states established after 1792 had formal religious establishments. Baptists, Congregationalists, Presbyterians, and Methodists accounted for the majority of the American population both at the beginning and end of this period, but this simple fact masks an important compositional shift. While the denominations of Old Dissent declined relatively, Methodism grew quickly, representing a third of the population by 1850. Dissenters thus faced several different challenges. Primary among these were how to understand the idea of ‘denomination’ and also the more general role of institutional religion in a post-establishment society. Concerns about missions, and the positions of women and African Americans are best understood within this context.

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