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Policy Points The Paycheck Plus randomized controlled trial tested a fourfold increase in the Earned Income Tax Credit (EITC) for single adults without dependent children over 3 years in New York and Atlanta. In New York, the intervention improved economic, mental, and physical health outcomes. In Atlanta, it had no economic benefit or impact on physical health and may have worsened mental health. In Atlanta, tax filing and bonus receipt were lower than in the New York arm of the trial, which may explain the lack of economic benefits. Lower mental health scores in the treatment group were driven by disadvantaged men, and the study sample was in good mental health., Context: The Paycheck Plus experiment examined the effects of an enhanced Earned Income Tax Credit (EITC) for single adults on economic and health outcomes in Atlanta, GA and New York City (NYC). The NYC study was completed two years prior to the Atlanta study and found mental and physical benefits for the subgroups that responded best to the economic incentives provided. In this article, we present the findings from the Atlanta study, in which the uptake of the treatment (tax filings and EITC bonus) were lower and economic and health benefits were not observed., Methods: Paycheck Plus Atlanta was an unblinded randomized controlled trial that assigned n = 3,971 participants to either the standard federal EITC (control group) or an EITC supplement of up to $2,000 (treatment group) for three tax years (2017-2019). Administrative data on employment and earnings were obtained from the Georgia Department of Labor and survey data were used to examine validated measures of health and well-being., Findings: In Atlanta, the treatment group had significantly higher earnings in the first project year but did not have significantly higher cumulative earnings than the control group overall (mean difference = $1,812, 95% CI = -150, 3,774, p = 0.07). The treatment group also had significantly lower scores on two measures of mental health after the intervention was complete: the Patient Health Questionnaire 8 (mean difference = 0.19, 95% CI = 0.06, 0.32, p = 0.005) and the Kessler 6 (mean difference = 0.15, 95% CI = 0.03, 0.27, p = 0.012). Secondary analyses suggested these results were driven by disadvantaged men, but the study sample was in good mental health., Conclusions: The EITC experiment in Atlanta was not associated with gains in earnings or improvements in physical or mental health., (© 2023 The Authors. The Milbank Quarterly published by Wiley Periodicals LLC on behalf of The Milbank Memorial Fund.)

Objectives: In the United States, Hispanics are more likely to experience financial barriers to mental health care than non-Hispanics. We used a unique survey to study the effect of these financial barriers on the severity of depressive symptoms among Hispanics who had previously been diagnosed as having depression. Methods: This cross-sectional study used data from the 2015 Washington Heights Community Survey, administered to 2,489 households in Manhattan, New York City. Multiple regression models and propensity score matching were used to estimate the association between financial barriers to mental health care and depressive symptoms and the likelihood of being clinically depressed. Results: Among those diagnosed with depression, those with financial barriers to mental health services or counseling had significantly higher (β = 0.36, 95% CI = 0.03, 0.70) depressive symptoms. When propensity score matching was utilized, those with financial barriers to mental health services had significantly greater depressive symptoms (β = 0.63, 95% CI = 0.37, 0.89) and were significantly more likely to be currently depressed (OR = 2.38, 95% CI = 1.46, 3.89), in comparison to those who had access. Conclusions: Making mental health care more affordable and therefore more accessible to Hispanics is one step toward mitigating the burden on mental illness and decreasing health disparities.

Purpose: To assess the association of neighborhood demographic and socioeconomic characteristics with COVID-19 incidence and mortality in New York City (NYC) over the first two waves of outbreak., Methods: This retrospective study used neighborhood-level data from 177 modified ZIP code tabulation areas in NYC between March 01, 2020 and April 30, 2021., Results: Neighborhoods that were most severely impacted in wave 1 were also more affected in wave 2. Neighborhoods with a higher percentage of seniors (≥75 years), males, Black and Hispanic population, and large-size households had higher incidence rates of COVID-19 in wave 1 but not in wave 2. Neighborhoods with higher percentage of Black and Hispanic population and lower insurance coverage had higher death rate per capita and case fatality ratio in wave 1, and neighborhoods with higher percentage of Black and Asian population had elevated case fatality ratio in wave 2. Median household income was negatively associated with incidence rate and death rate per capita but not associated with case fatality ratio in both waves. Neighborhoods with more seniors had higher death rate and case fatality ratio in both waves., Conclusions: Neighborhood disparities in COVID-19 incidence and mortality across NYC neighborhoods were dynamic during the first two waves of outbreak., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Antipoverty policies may hold promise as tools to improve health and reduce mortality rates among low-income Americans. We examined the health effects of the New York City Paycheck Plus randomized controlled trial. Paycheck Plus tests the impact of a potential fourfold increase in the Earned Income Tax Credit for low-income Americans without dependent children. Starting in 2015, Paycheck Plus offered 5,968 study participants a credit of up to $2,000 at tax time (treatment) or the standard credit of about $500 (control). Health-related quality of life and other outcomes for a representative subset of these participants ( n = 3,289) were compared to those of a control group thirty-two months after randomization. The intervention had a modest positive effect on employment and earnings, particularly among women. It had no effect on health-related quality of life for the overall sample, but women realized significant improvements.

Background: Using the 140 speed cameras in New York City (NYC) as a case study, we explore how to optimise the number of cameras such that the most lives can be saved at the lowest cost., Methods: A Markov model was built to explore the economic and health impacts of speed camera installations in NYC as well as the optimal number and placement. Both direct and indirect medical savings associated with speed cameras are weighed against their cost. Health outcomes are measured in terms of quality-adjusted life years (QALYs)., Results: Over the lifetime of an average NYC resident, the existing 140 speed cameras increase QALYs by 0.00044 units (95% credible interval (CrI) 0.00027 to 0.00073) and reduce costs by US$70 (95% CrI US$21 to US$131) compared with no speed cameras. The return on investment would be maximised where the number of cameras more than doubled to 300. This would further increase QALY gains per resident by 0.00083 units (95% CrI 0.00072 to 0.00096) while reducing medical costs by US$147 (95% CrI US$70 to US$221) compared with existing speed cameras. Overall, this increase in cameras would save 7000 QALYs and US$1.2 billion over the lifetime of the current cohort of New Yorkers., Conclusion: Speed cameras rank among the most cost-effective social policies, saving both money and lives., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

The "Citi Bike" bike share program in New York City is the largest bike share program in the USA. We ask whether expanding this program to lower-income communities is cost-effective means of encouraging exercise and reducing pollution in New York City. We built a stochastic Markov model to evaluate the cost-effectiveness of the Citi Bike expansion program, an effort to extend bike share to areas with higher costs and risks over a 10-year time horizon. We used one-way sensitivity analyses and Monte Carlo simulation to test the model uncertainty. The incremental cost-effectiveness ratio of the Citi Bike expansion program relative to the current program (status quo) was $7869/quality-adjusted life year gained. The Citi Bike expansion program in New York City offers good value relative to most health interventions.

Opportunity NYC-Family Rewards was the first conditional cash transfer, randomized controlled trial for low-income families in the United States. From 2007 to 2010, Family Rewards offered 2,377 New York City families cash transfers that were conditional upon their investments in education, preventive health care, and parental employment. Their health and other outcomes were compared to those of a control group of 2,372 families. The experiment led to a modest improvement in health insurance coverage and a large increase in the use of preventive dental care. It improved parents' perception of their own health and levels of hope, mainly through improvements in reported financial well-being. While the program's impacts on physical health were weaker, our study might not have captured effects on chronic disease risk that take longer to accrue. In the context of New York City's operating social-safety-net programs, conditional cash transfers may have led to positive, albeit modest, improvements in the health of poor families.

Background: In the United States incidence of sepsis and pneumonia differ by race, but it is unclear whether this is due to intrinsic factors or health care factors., Methods: We conducted a study of 52,006 patients hospitalized during 2006-2008 at a referral hospital in upper Manhattan. We examined how the prevalence of present-on-admission and health care-associated infection compared between non-Hispanic blacks, Hispanics, and non-Hispanic whites adjusting for sociodemographic factors, admission through the emergency department, and comorbid conditions., Results: Non-Hispanic blacks had 1.59-fold (95% confidence interval [CI], 1.29-1.96) and 1.55-fold (95% CI, 1.35-1.77) risk of community-acquired bloodstream infection and urinary tract infection compared with non-Hispanic whites. Hispanic patients had 1.31-fold (95% CI, 1.15-1.49) risk of presenting with community-acquired urinary tract infection compared with non-Hispanic whites. Controlling for admission through the emergency department, comorbidity, and neighborhood income attenuated the differences in prevalence of infections., Conclusions: We found that health disparities in present-on-admission infections might be largely explained by potential lack of ambulatory care, socioeconomic factors, and comorbidity., (Copyright © 2014 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Introduction: Data on hospitalization of immigrants to the United States are sparse, but small area analysis may improve the utility of existing data., Methods: Applying logistic regression analysis to 2000 census and hospitalization data for New York City, we examined the odds of hospital admission by major diagnostic category and global region of birth after controlling for covariates. We used individual-level covariates to control for age, race, and gender. By matching the patient's zip code of residence to census data, we then added median household income, the proportion of persons born in a particular global region, and the proportion of foreign-born persons living in the same zip code as independent variables., Results: The total proportion of foreign-born persons in a zip code predicts a lower hospitalization rate for most major diagnostic categories and most foreign-born groups. However, Africa-born persons have a higher odds of hospitalization for most major diagnostic categories - up to 1.79 (95% confidence interval 1.73, 1.86) for blood and blood forming disorders - relative to native-born persons. The odds of hospitalization among Africa-born persons for most conditions are over 3 times higher than other foreign-born groups. Hospitalization odds for Latin American-born persons were also higher than native-born persons across major diagnostic categories., Conclusion: Small area analysis generally predicts hospitalization rates that coincide with mortality studies and may serve as a useful tool for hypothesis testing in immigrant health.

Since the World Health Organization declared the global outbreak of severe acute respiratory syndrome (SARS) contained in July 2003, new cases have periodically reemerged in Asia. This situation has placed hospitals and health officials worldwide on heightened alert. In a future outbreak, rapidly and accurately distinguishing SARS from other common febrile respiratory illnesses (FRIs) could be difficult. We constructed a decision-analysis model to identify the most efficient strategies for managing undifferentiated FRIs within a hypothetical SARS outbreak in New York City during the season of respiratory infections. If establishing reliable epidemiologic links were not possible, societal costs would exceed 2.0 billion US dollars per month. SARS testing with existing polymerase chain reaction assays would have harmful public health and economic consequences if SARS made up <0.1% of circulating FRIs. Increasing influenza vaccination rates among the general population before the onset of respiratory season would save both money and lives.

Background: We set out to describe the risk of hospitalization from heart disease, stroke, and diabetes among persons born in India, all foreign-born persons, and U.S.-born persons residing in New York City., Methods: We examined billing records of 1,083,817 persons hospitalized in New York City during the year 2000. The zip code of each patient's residence was linked to corresponding data from the 2000 U.S. Census to obtain covariates not present in the billing records. Using logistic models, we evaluated the risk of hospitalization for heart disease, stroke and diabetes by country of origin., Results: After controlling for covariates, Indian-born persons are at similar risk of hospitalization for heart disease (RR = 1.02, 95% confidence interval 1.02, 1.03), stroke (RR = 1.00, 95% confidence interval, 0.99, 1.01), and diabetes mellitus (RR = 0.96 95% confidence interval 0.94, 0.97) as native-born persons. However, Indian-born persons are more likely to be hospitalized for these diseases than other foreign-born persons. For instance, the risk of hospitalization for heart disease among foreign-born persons is 0.70 (95% confidence interval 0.67, 0.72) and the risk of hospitalization for diabetes is 0.39 (95% confidence interval 0.37, 0.42) relative to native-born persons., Conclusions: South Asians have considerably lower rates of hospitalization in New York than reported in countries with national health systems. Access may play a role. Clinicians working in immigrant settings should nonetheless maintain a higher vigilance for these conditions among Indian-born persons than among other foreign-born populations.