scholarly journals The Impact of Violent Crime on Obesity

2019 ◽  
Vol 8 (12) ◽  
pp. 329
Author(s):  
Lisa Stolzenberg ◽  
Stewart J. D’Alessio ◽  
Jamie L. Flexon
Keyword(s):  
New York ◽  
New York City ◽  
Violent Crime ◽  
Ethnic Differences ◽  
Crime Rate ◽  
Neighborhood Factors ◽  
Racial And Ethnic Differences ◽  
Violent Crime Rate ◽  
Race Ethnicity ◽  
The Impact

Dwelling in a violence-plagued neighborhood may amplify obesity by engendering psychological distress or by cultivating a sedentary, homebound lifestyle. This relationship is speculated to be especially relevant for black and Hispanic citizens because they are much more likely than whites to live in violence-beleaguered neighborhoods. Results from two multilevel analyses of 12,645 residents living in 34 New York City neighborhoods show that, while the violent crime rate does not have a direct effect on obesity, it does condition the relationships between race, ethnicity, and obesity. As the violent crime rate rises in a neighborhood, the probability of both a black and Hispanic resident being obese increases, controlling for both individual and neighborhood factors. The BMI of black and Hispanic residents is also higher in neighborhoods beset by violence. These findings suggest that violent crime may be a salient but unappreciated factor in explaining both racial and ethnic differences in obesity.

scholarly journals COVID-Net: A deep learning based and interpretable predication model for the county-wise trajectories of COVID-19 in the United States

2020 ◽  
Author(s):  
Ting Tian ◽  
Yuknag Jiang ◽  
Yuting Zhang ◽  
Zhongfei Li ◽  
Xueqin Wang ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
New York ◽  
Population Size ◽  
Violent Crime ◽  
Crime Rate ◽  
The United States ◽  
Hospitalization Rate ◽  
Preventable Hospitalization ◽  
Violent Crime Rate

AbstractThe confirmed cases of novel coronavirus disease (COVID-19) have been reported in the United States since late January 2020. There were over 4.8 million confirmed cases and about 320,000 deaths as of May 19, 2020 in the world. We examined the characteristics of the confirmed cases and deaths of COVID-19 in all affected counties of the United States. We proposed a COVID-Net combining the architecture of both Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) by using the trajectories of COVID-19 during different periods until May 19, 2020, as the training data. The validation of the COVID-Net was performed by predicting the numbers of confirmed cases and deaths in subsequent 3-day, 5-day, and 7-day periods. The COVID-Net produced relatively smaller Mean Relative Errors (MREs) for the 10 counties with the most severe epidemic as of May 19, 2020. On average, MREs were 0.01 for the number of confirmed cases in all validation periods, and 0.01, 0.01, and 0.03 for the number of deaths in the 3-day, 5-day, and 7-day periods, respectively. The COVID-Net incorporated five risk factors of COVID-19 and was used to predict the trajectories of COVID-19 in Hudson County, New Jersey and New York County, New York until June 28, 2020. The risk factors include the percentage of the population with access to exercise opportunities, average daily PM2.5, population size, preventable hospitalization rate, and violent crime rate. The expected number of cumulative confirmed cases and deaths depends on the dynamics of these five risk factors.Significance StatementA COVID-Net model was built to predict the trajectories of COVID-19, based on the percentage of the population with access to exercise opportunities, average daily PM2.5, population size, preventable hospitalization rate and violent crime rate in the metropolises areas. The increasing awareness of how these risk factors affect the pandemic helps policymakers develop plans that mitigate the spread of COVID-19.

scholarly journals Impact of COVID-19 on residency choice: A survey of New York City medical students

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258088
Author(s):  
Kate E. Lee ◽  
Francesca Lim ◽  
Elisabeth R. Silver ◽  
Adam S. Faye ◽  
Chin Hur
Keyword(s):  
New York ◽  
New York City ◽  
Medical Student ◽  
Medical Students ◽  
York City ◽  
Multivariable Analysis ◽  
Specialty Choice ◽  
Personal Impact ◽  
Race Ethnicity ◽  
The Impact

Objectives The Coronavirus disease 2019 (COVID-19) pandemic disrupted medical student education, particularly in New York City (NYC). We aimed to assess the impact of the COVID-19 pandemic on medical students’ residency choices. Methods The authors conducted a cross-sectional survey of medical students in all years of study at four NYC medical schools (Columbia, Cornell, NYU, and SUNY Downstate). The survey was fielded from 19 Aug 2020 to 21 Sep 2020. Survey questions included items assessing COVID-19 impact on residency choices, personal impact of COVID-19, residency/specialty choices, and factors influencing these choices. Results A total of 2310 students received the survey, with 547 (23.7%) providing partial responses and 212 (9.2%) providing valid responses for our primary analysis. 59.0% of participants thought that COVID-19 influenced their choice of residency/specialty, with 0.9% saying the influence was to a great extent, 22.2% to some extent, and 35.8% very little. On multivariable analysis, factors that were independently associated with COVID-19 impacting residency choice included low debt ($1 to $99,999: adjOR 2.23, 95%CI 1.02–5.03) compared with no debt and Other race/ethnicity (adjOR 0.26, 95%CI 0.10–0.63) compared with White race/ethnicity. On secondary analysis of all participants answering survey items for logistic regression regardless of survey completion, direct personal impact of COVID-19 was significantly associated with COVID-19 impacting specialty choice (adjOR 1.90, 95%CI 1.04–3.52). Moreover, 24 students (11.6%) reported a change in their top residency choice from before to during/after COVID-19, citing concerns about frontline work, work-life balance, and risk of harm. Conclusions Our study found that 3 in 5 (59.0%) participants felt that COVID-19 impacted their residency choice, with 11.6% of respondents explicitly changing their top specialty choice. Investigating the impact of the pandemic on medical student residency considerations is crucial to understand how medical career outlooks may change in the future.

The Impact of Customer Loyalty and Restaurant Sanitation Grades on Revisit Intention and the Importance of Narrative Information: The Case of New York Restaurant Sanitation Grading System

2017 ◽  
Vol 59 (3) ◽  
pp. 275-284 ◽  
Author(s):  
Min Gyung Kim ◽  
Hyunjoo Yang ◽  
Anna S. Mattila
Keyword(s):  
New York ◽  
New York City ◽  
Customer Loyalty ◽  
York City ◽  
Letter Grades ◽  
The Difference ◽  
Revisit Intentions ◽  
Using Data ◽  
The Impact ◽  
Loyal Customers

New York City launched a restaurant sanitation letter grade system in 2010. We evaluate the impact of customer loyalty on restaurant revisit intentions after exposure to a sanitation grade alone, and after exposure to a sanitation grade plus narrative information about sanitation violations (e.g., presence of rats). We use a 2 (loyalty: high or low) × 4 (sanitation grade: A, B, C, or pending) between-subjects full factorial design to test the hypotheses using data from 547 participants recruited from Amazon MTurk who reside in the New York City area. Our study yields three findings. First, loyal customers exhibit higher intentions to revisit restaurants than non-loyal customers, regardless of sanitation letter grades. Second, the difference in revisit intentions between loyal and non-loyal customers is higher when sanitation grades are poorer. Finally, loyal customers are less sensitive to narrative information about sanitation violations.

Do Stock Markets Catch the Flu?

2013 ◽  
Vol 48 (3) ◽  
pp. 979-1000 ◽  
Author(s):  
Brian C. McTier ◽  
Yiuman Tse ◽  
John K. Wald
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
Stock Markets ◽  
The United States ◽  
Trading Activity ◽  
Market Makers ◽  
International Data ◽  
The Impact ◽  
Bid Ask Spreads

AbstractWe examine the impact of influenza on stock markets. For the United States, a higher incidence of flu is associated with decreased trading, decreased volatility, decreased returns, and higher bid-ask spreads. Consistent with the flu affecting institutional investors and market makers, the decrease in trading activity and volatility is primarily driven by the incidence of influenza in the greater New York City area. However, the effect of the flu on bid-ask spreads and returns is related to the incidence of flu nationally. International data confirm our findings of a decrease in trading activity and returns when flu incidence is high.

scholarly journals The Impact of Covid‐19 on Certified Nursing Assistants in New York City: A Cross‐Sectional Study

2021 ◽  
Vol 56 (S2) ◽  
pp. 41-42
Author(s):  
Sanjay Pinto ◽  
Madeline Sterling ◽  
Faith Wiggins ◽  
Rebecca Hall ◽  
Chenjuan Ma
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Cross Sectional Study ◽  
Nursing Assistants ◽  
Certified Nursing Assistants ◽  
Sectional Study ◽  
Cross Sectional ◽  
The Impact
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