Descriptive study of causes of death and COVID-19-associated morbidities from the New York City electronic death record: first wave of the pandemic March-July 2020.

OBJECTIVE: Assessing excess deaths from benchmarks across causes of death during the first wave of the COVID-19 pandemic and identifying morbidities most frequently mentioned alongside COVID-19 deaths in the death record. METHODS: Descriptive study of death records between 11 March 2020 and 27 July 2020, from the New York City Bureau of Vital Statistics. Mortality counts and percentages were compared with the average for the same calendar period of the previous 2 years. Distributions of morbidities from among forty categories of conditions were generated citywide and by sex, race/ethnicity and four age groups. Causes of death were assumed to follow Poisson processes for Z-score construction. RESULTS: Within the study period, 46 563 all-cause deaths were reported; 132.9% higher than the average for the same period of the previous 2 years (19 989). Of those 46 563 records, 19 789 (42.5%) report COVID-19 as underlying cause of death. COVID-19 was the most prevalent cause across all demographics, with respiratory conditions (prominently pneumonia), hypertension and diabetes frequently mentioned morbidities. Black non-Hispanics had greater proportions of mentions of pneumonia, hypertension, and diabetes. Hispanics had the largest proportion of COVID-19 deaths (52.9%). Non-COVID-19 excess deaths relative to the previous 2-year averages were widely reported. CONCLUSION: Mortality directly due to COVID-19 was accompanied by significant increases across most other causes from their reference averages, potentially suggesting a sizable COVID-19 death undercount. Indirect effects due to COVID-19 may partially account for some increases, but findings are hardly dispositive. Unavailability of vaccines for the time period precludes any impact over excess deaths. Respiratory and cardiometabolic-related conditions were most frequently reported among COVID-19 deaths across demographic characteristics.

Racial and Ethnic Inequities in Development of Type 2 Diabetes After Gestational Diabetes Mellitus.

OBJECTIVE: To estimate racial and ethnic disparities in type 2 diabetes mellitus after gestational diabetes mellitus (GDM) and to investigate baseline pregnancy clinical and social or structural characteristics as mediators. METHODS: We conducted a retrospective cohort of individuals with GDM using linked 2009-2011 New York City birth and hospital data and 2009-2017 New York City A1c Registry data. We ascertained GDM and pregnancy characteristics from birth and hospital records. We classified type 2 diabetes as two hemoglobin A 1c test results of 6.5% or higher. We grouped pregnancy characteristics into clinical (body mass index [BMI], chronic hypertension, gestational hypertension, preeclampsia, preterm delivery, caesarean, breastfeeding, macrosomia, shoulder dystocia) and social or structural (education, Medicaid insurance, prenatal care, and WIC [Special Supplemental Nutrition Program for Women, Infants, and Children] participation). We used Cox proportional hazards models to estimate associations between race and ethnicity and 8-year type 2 diabetes incidence, and we tested mediation of pregnancy characteristics, additionally adjusting for age and nativity (U.S.-born vs foreign-born). RESULTS: The analytic data set included 22,338 patients with GDM. The 8-year type 2 diabetes incidence was 11.7% overall and 18.5% in Black, 16.8% in South and Southeast Asian, 14.6% in Hispanic, 5.5% in East and Central Asian, and 5.4% in White individuals with adjusted hazard ratios of 4.0 (95% CI 2.4-3.9), 2.9 (95% CI 2.4-3.3), 3.3 (95% CI 2.7-4.2), and 1.0 (95% CI 0.9-1.4) for each group compared with White individuals. Clinical and social or structural pregnancy characteristics explained 9.3% and 23.8% of Black, 31.2% and 24.7% of Hispanic, and 7.6% and 16.3% of South and Southeast Asian compared with White disparities. Associations between education, Medicaid insurance, WIC participation, and BMI and type 2 diabetes incidence were more pronounced among White than Black, Hispanic, and South and Southeast Asian individuals. CONCLUSION: Population-based racial and ethnic inequities are substantial in type 2 diabetes after GDM. Characteristics at the time of delivery partially explain disparities, creating an opportunity to intervene on life-course cardiometabolic inequities, whereas weak associations of common social or structural measures and BMI in Black, Hispanic and South and Southeast Asian individuals demonstrate the need for greater understanding of how structural racism influences postpartum cardiometabolic risk in these groups.

Recent Advances in the Use of the Mortality Syndromic Surveillance System-New York City, 2015-2020.

OBJECTIVE: New York City's automated mortality syndromic surveillance system monitors temporal and spatial patterns in mortality. To describe the use of the syndromic surveillance system, we used the system to find mortality patterns for the 15 leading causes of death and for deaths from rare and reportable diseases in New York City from February 2015 through June 2020. We used results to find aberrations that indicate threats to public health. METHODS: We used unobserved components models to analyze time series of mortality counts for leading causes of death, historical limits methods for rare and reportable diseases, and SaTScan for temporal-spatial cluster analysis. We obtained data on the number of deaths from the electronic death registry system maintained by the city's Bureau of Vital Statistics. RESULTS: The mortality syndromic surveillance system detected an increase in the number of deaths from heart disease by April 1, 2020, when 75.0 deaths occurred on March 24, 2020, instead of an expected 45.8 deaths (95% upper prediction limit of 61.0) and an increase in the number of deaths from all causes on March 20, 2020, when 194.0 deaths were observed while 150.1 deaths were expected (95% upper prediction limit of 178.0). The number of deaths from all causes returned to normal the week beginning June 14, 2020, when 990.0 deaths were observed and 998.8 deaths were expected. PRACTICE IMPLICATIONS: When compared with efforts from New York City to provide yearly vital statistics, the automated mortality syndromic surveillance system can provide timely mortality data with fewer resources and raise the capacity to detect anomalous increases in mortality.

Neighborhood Food Environment and Birth Weight Outcomes in New York City.

Importance: Infants born with unhealthy birth weight are at greater risk for long-term health complications, but little is known about how neighborhood characteristics (eg, walkability, food environment) may affect birth weight outcomes. Objective: To assess whether neighborhood-level characteristics (poverty rate, food environment, and walkability) are associated with risk of unhealthy birth weight outcomes and to evaluate whether gestational weight gain mediated these associations. Design, Setting, and Participants: The population-based cross-sectional study included births in the 2015 vital statistics records from the New York City Department of Health and Mental Hygiene. Only singleton births and observations with complete birth weight and covariate data were included. Analyses were performed from November 2021 to March 2022. Exposures: Residential neighborhood-level characteristics, including poverty, food environment (healthy and unhealthy food retail establishments), and walkability (measured by both walkable destinations and a neighborhood walkability index combining walkability measures like street intersection and transit stop density). Neighborhood-level variables categorized into quartiles. Main Outcomes and Measures: The main outcomes were birth certificate birth weight measures including small for gestational age (SGA), large for gestational age (LGA), and sex-specific birth weight for gestational age z-score. Generalized linear mixed-effects models and hierarchical linear models estimated risk ratios for associations between density of neighborhood-level characteristics within a 1-km buffer of residential census block centroid and birth weight outcomes. Results: The study included 106 194 births in New York City. The mean (SD) age of pregnant individuals in the sample was 29.9 (6.1) years. Prevalence of SGA and LGA were 12.9% and 8.4%, respectively. Residence in the highest density quartile of healthy food retail establishments compared with the lowest quartile was associated with lower adjusted risk of SGA (with adjustment for individual covariates including gestational weight gain z-score: risk ratio [RR], 0.89; 95% CI 0.83-0.97). Higher neighborhood density of unhealthy food retail establishments was associated with higher adjusted risk of delivering an infant classified as SGA (fourth vs first quartile: RR, 1.12; 95% CI, 1.01-1.24). The RR for the association between density of unhealthy food retail establishments and risk of LGA was higher after adjustment for all covariates in each quartile compared with quartile 1 (second: RR, 1.12 [95% CI, 1.04-1.20]; third: RR, 1.18 [95% CI, 1.08-1.29]; fourth: RR, 1.16; [95% CI, 1.04-1.29]). There were no associations between neighborhood walkability and birth weight outcomes (SGA for fourth vs first quartile: RR, 1.01 [95% CI, 0.94-1.08]; LGA for fourth vs first quartile: RR, 1.06 [95% CI, 0.98-1.14]). Conclusions and Relevance: In this population-based cross-sectional study, healthfulness of neighborhood food environments was associated with risk of SGA and LGA. The findings support use of urban design and planning guidelines to improve food environments to support healthy pregnancies and birth weight.

Influence of Gestational Diabetes Mellitus on Diabetes Risk and Glycemic Control in a Retrospective Population-Based Cohort.

OBJECTIVE: Racial/ethnic-specific estimates of the influence of gestational diabetes mellitus (GDM) on type 2 diabetes remain underexplored in large population-based cohorts. We estimated racial/ethnic differences in the influence of GDM on diabetes risk and glycemic control in a multiethnic, population-based cohort of postpartum women. RESEARCH DESIGN AND METHODS: Hospital discharge and vital registry data for New York City (NYC) births between 2009 and 2011 were linked with NYC A1C Registry data between 2009 and 2017. Women with baseline diabetes (n = 2,810) were excluded for a final birth cohort of 336,276. GDM on time to diabetes onset (two A1C tests of ≥6.5% from 12 weeks postpartum onward) or glucose control (first test of A1C <7.0% following diagnosis) was assessed using Cox regression with a time-varying exposure. Models were adjusted for sociodemographic and clinical factors and stratified by race/ethnicity. RESULTS: The cumulative incidence for diabetes was 11.8% and 0.6% among women with and without GDM, respectively. The adjusted hazard ratio (aHR) of GDM status on diabetes risk was 11.5 (95% CI 10.8, 12.3) overall, with slight differences by race/ethnicity. GDM was associated with a lower likelihood of glycemic control (aHR 0.85; 95% CI 0.79, 0.92), with the largest negative influence among Black (aHR 0.77; 95% CI 0.68, 0.88) and Hispanic (aHR 0.84; 95% CI 0.74, 0.95) women. Adjustment for screening bias and loss to follow-up modestly attenuated racial/ethnic differences in diabetes risk but had little influence on glycemic control. CONCLUSIONS: Understanding racial/ethnic differences in the influence of GDM on diabetes progression is critical to disrupt life course cardiometabolic disparities.

Collateral Impacts of the COVID-19 Pandemic: The New York City Experience.

OBJECTIVE: To adapt an existing surveillance system to monitor the collateral impacts of the COVID-19 pandemic on health outcomes in New York City across 6 domains: access to care, chronic disease, sexual/reproductive health, food/economic insecurity, mental/behavioral health, and environmental health. DESIGN: Epidemiologic assessment. Public health surveillance system. SETTING: New York City. PARTICIPANTS: New York City residents. MAIN OUTCOME MEASURES: We monitored approximately 30 indicators, compiling data from 2006 to 2022. Sources of data include clinic visits, surveillance surveys, vital statistics, emergency department visits, lead and diabetes registries, Medicaid claims, and public benefit enrollment. RESULTS: We observed disruptions across most indicators including more than 50% decrease in emergency department usage early in the pandemic, which rebounded to prepandemic levels by late 2021, changes in reporting levels of probable anxiety and depression, and worsening birth outcomes for mothers who identified as Asian/Pacific Islander or Black. Data are processed in SAS and analyzed using the R Surveillance package to detect possible inflections. Data are updated monthly to an internal Tableau Dashboard and shared with agency leadership. CONCLUSIONS: As the COVID-19 pandemic continues into its third year, public health priorities are returning to addressing non-COVID-19-related diseases and conditions, their collateral impacts, and postpandemic recovery needs. Substantial work is needed to return even to a suboptimal baseline across multiple health topic areas. Our surveillance framework offers a valuable starting place to effectively allocate resources, develop interventions, and issue public communications.

Neighbourhood walkability is associated with risk of gestational diabetes: A cross-sectional study in New York City.

BACKGROUND: Despite the links between neighbourhood walkability and physical activity, body size and risk of diabetes, there are few studies of neighbourhood walkability and risk of gestational diabetes (GD). OBJECTIVES: Assess whether higher neighbourhood walkability is associated with lower risk of GD in New York City (NYC). METHODS: Cross-sectional analyses of a neighbourhood walkability index (NWI) score and density of walkable destinations (DWD) and risk of GD in 109,863 births recorded in NYC in 2015. NWI and DWD were measured for the land area of 1 km radius circles around the geographic centroid of each Census block of residence. Mixed generalised linear models, with robust standard error estimation and random intercepts for NYC Community Districts, were used to estimate risk ratios for GD for increasing quartiles of each of the neighbourhood walkability measures after adjustment for the pregnant individual's age, race and ethnicity, parity, education, nativity, and marital status and the neighbourhood poverty rate. RESULTS: Overall, 7.5% of pregnant individuals experienced GD. Risk of GD decreased across increasing quartiles of NWI, with an adjusted risk ratio of 0.81 (95% Confidence Interval (CI) 0.75, 0.87) comparing those living in areas in the 4th quartile of NWI to those in the first quartile. Similarly, for comparisons of the 4th to 1st quartile of DWD, the adjusted risk ratio for GD was 0.77 (95% CI 0.71, 0.84). CONCLUSIONS: These analyses find support for the hypothesis that higher neighbourhood walkability is associated with a lower risk of GD. The analyses provide further health related support for urban design policies to increase walkability.

Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City.

Objective: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for internal use by other surveillance and epidemiology experts. Materials and methods: Existing surveillance databases and systems were leveraged to create daily analytic datasets of COVID-19 case and testing information, aggregated by week and key demographics. The dashboard was developed iteratively using R, and includes interactive graphs, tables, and maps summarizing recent COVID-19 epidemiologic trends. Additional data and interactive features were incorporated to provide further information on the spread of COVID-19 in NYC. Results: The dashboard allows key staff to quickly review situational data, identify concerning trends, and easily maintain granular situational awareness of COVID-19 epidemiology in NYC. Discussion: The dashboard is used to inform weekly surveillance summaries and alleviated the burden of manual report production on infectious disease epidemiologists. The system was built by and for epidemiologists, which is critical to its utility and functionality. Interactivity allows users to understand broad and granular data, and flexibility in dashboard development means new metrics and visualizations can be developed as needed. Conclusions: Additional investment and development of public health informatics tools, along with standardized frameworks for local health jurisdictions to analyze and visualize data in emergencies, are warranted.

Neighborhood walkability and poverty predict excessive gestational weight gain: A cross-sectional study in New York City.

OBJECTIVE: This study evaluated associations between neighborhood-level characteristics and gestational weight gain (GWG) in a population-level study of 2015 New York City births. METHODS: Generalized linear mixed-effects models were used to estimate odds ratios (ORs) for associations between neighborhood-level characteristics (poverty, food environment, walkability) within 1 km of a residential Census block centroid and excessive or inadequate GWG compared with recommended GWG. All models were adjusted for individual-level sociodemographic characteristics. RESULTS: Among the sample of 106,285 births, 41.8% had excessive GWG, and 26.3% had inadequate GWG. Residence in the highest versus lowest quartile of neighborhood poverty was associated with greater odds of excessive GWG (OR: 1.17, 95% CI: 1.08-1.26). Residence in neighborhoods in the quartile of highest walkability compared with the quartile of lowest walkability was associated with lower odds of excessive GWG (OR: 0.87, 95% CI: 0.81-0.93). Adjustment for prepregnancy BMI attenuated the associations for neighborhood poverty, but not for walkability. Neighborhood variables were not associated with inadequate GWG. CONCLUSIONS: These analyses indicate that greater neighborhood walkability is associated with lower odds of excessive GWG, potentially from differences in pedestrian activity during pregnancy. This research provides further evidence for using urban design to support healthy weight status during pregnancy.

Estimating the infection-fatality risk of SARS-CoV-2 in New York City during the spring 2020 pandemic wave: a model-based analysis.

BACKGROUND: As the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear. METHODS: In this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening). FINDINGS: During the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older. INTERPRETATION: Our results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds. FUNDING: National Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.

COVID-19 Outbreak - New York City, February 29-June 1, 2020.

New York City (NYC) was an epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States during spring 2020 (1). During March-May 2020, approximately 203,000 laboratory-confirmed COVID-19 cases were reported to the NYC Department of Health and Mental Hygiene (DOHMH). To obtain more complete data, DOHMH used supplementary information sources and relied on direct data importation and matching of patient identifiers for data on hospitalization status, the occurrence of death, race/ethnicity, and presence of underlying medical conditions. The highest rates of cases, hospitalizations, and deaths were concentrated in communities of color, high-poverty areas, and among persons aged ≥75 years or with underlying conditions. The crude fatality rate was 9.2% overall and 32.1% among hospitalized patients. Using these data to prevent additional infections among NYC residents during subsequent waves of the pandemic, particularly among those at highest risk for hospitalization and death, is critical. Mitigating COVID-19 transmission among vulnerable groups at high risk for hospitalization and death is an urgent priority. Similar to NYC, other jurisdictions might find the use of supplementary information sources valuable in their efforts to prevent COVID-19 infections.

Structural Racism, Historical Redlining, and Risk of Preterm Birth in New York City, 2013-2017.

Objectives. To assess if historical redlining, the US government's 1930s racially discriminatory grading of neighborhoods' mortgage credit-worthiness, implemented via the federally sponsored Home Owners' Loan Corporation (HOLC) color-coded maps, is associated with contemporary risk of preterm birth (< 37 weeks gestation).Methods. We analyzed 2013-2017 birth certificate data for all singleton births in New York City (n = 528 096) linked by maternal residence at time of birth to (1) HOLC grade and (2) current census tract social characteristics.Results. The proportion of preterm births ranged from 5.0% in grade A ("best"-green) to 7.3% in grade D ("hazardous"-red). The odds ratio for HOLC grade D versus A equaled 1.6 and remained significant (1.2; P < .05) in multilevel models adjusted for maternal sociodemographic characteristics and current census tract poverty, but was 1.07 (95% confidence interval = 0.92, 1.20) after adjustment for current census tract racialized economic segregation.Conclusions. Historical redlining may be a structural determinant of present-day risk of preterm birth.Public Health Implications. Policies for fair housing, economic development, and health equity should consider historical redlining's impacts on present-day residential segregation and health outcomes.

Surveillance to Monitor the Impact of the Trump Administration on the Health of New York City Residents.

CONTEXT: The Trump administration has enacted or proposed many policies that could impact public health. These include attempts to dismantle or repeal the Patient Protection and Affordable Care Act (ACA), restricting funding for women's health care, and loosening of environmental regulations. OBJECTIVE: To develop a surveillance system to monitor the public health impacts of the Trump administration in New York City. DESIGN: Epidemiologic assessment. Public health surveillance system. SETTING: New York City. PARTICIPANTS: New York City residents. MAIN OUTCOMES MEASURES: We identified approximately 25 indicators across 5 domains: access to care, food insecurity, reproductive health, environmental health, and general physical and mental health. Sources of data include the New York City Department of Health and Mental Hygiene's (DOHMH's) health and risk behavior telephone survey, vital statistics, emergency department visits, DOHMH sexual health clinics, Federally Qualified Health Centers, lead and diabetes registries, Medicaid claims, Supplementary Nutrition Assistance Program enrollment, Women, Infant, and Children program enrollment, and 311 call records. Data are collected monthly or quarterly where possible. We identified measures to stratify indicators by individual and area-based measures of immigration and poverty. RESULTS: Since April 2017, we have compiled quarterly reports, including establishing a historical baseline of 10 years to account for secular trends and encompass the establishment and enactment of the ACA. Indicators are interpreted within the context of changes in programming or local policy that might explain trends. CONCLUSIONS: We have successfully established an adaptive surveillance system that is poised to rapidly detect changes in the health of New York City residents resulting from changes by the Trump administration to public health policy. The development of such systems is a critical function for health departments across the country to play a role in the current political and policy environment.

Severe sociopolitical stressors and preterm births in New York City: 1 September 2015 to 31 August 2017.

BACKGROUND: Severe stressors can induce preterm birth (PTB; gestation <37 weeks), with such stressors including social and economic threats, interpersonal violence, hate crimes and severe sociopolitical stressors (ie, arising from political leaders' threatening rhetoric or from political legislation). We analysed temporal changes in risk of PTB among immigrant, Hispanic and Muslim populations targeted in the US 2016 presidential election and its aftermath. METHODS: Trend analysis of all singleton births in New York City from 1 September 2015 to 31 August 2017 (n=230 105). RESULTS: Comparing the period before the US presidential nomination (1 September 2015 to 31 July 2016) to the post-inauguration period (1 January 2017 to 31 August 2017), the overall PTB rate increased from 7.0% to 7.3% (relative risk (RR): 1.04; 95% CI 1.00 to 1.07). Among Hispanic women, the highest post-inauguration versus pre-inauguration increase occurred among foreign-born Hispanic women with Mexican or Central American ancestry (RR: 1.15; 95% CI 1.01 to 1.31). The post-inauguration versus pre-inauguration PTB rate also was higher for women from the Middle East/North Africa and from the travel ban countries, although non-significant due to the small number of events. CONCLUSION: Severe sociopolitical stressors may contribute to increases in the risk of PTB among targeted populations.

Examination of Cause-of-Death Data Quality Among New York City Deaths Due to Cancer, Pneumonia, or Diabetes From 2010 to 2014.

The cause-of-death (COD) statement on the standard US death certificate is a valuable tool for public health practice, but its utility is impaired by reporting inaccuracies. To assess the quality of CODs reported in New York City, we developed and applied a quality measure to 3 leading CODs: cancer, pneumonia, and diabetes. The COD quality measure characterized 5 common issues with COD completion: nonspecific conditions as the underlying COD (UCOD); UCOD discrepancies; the presence of only 1 informative cause on the entire certificate; competing causes listed together on 1 line; and clinically improbable sequences. COD statements with more than 1 quality issue were defined as statements of "limited" quality. Of 82,116 deaths with cancer, diabetes, or pneumonia assigned as the UCOD in New York City from 2010 to 2014, 66.8% of pneumonia certificates were classified as "limited" quality as compared with 45.6% of cancer certificates and 32.3% of diabetes certificates. Forty percent of cancer certificates listed only 1 informative condition on the death certificate. Almost half of pneumonia certificates (45.9%) contained only enough information to assign International Classification of Diseases, Tenth Revision, code J18.9 ("unspecified pneumonia") as the UCOD, whereas most diabetes certificates contained UCOD discrepancies (25.2%). These limitations affect the quality of mortality data but may be reduced through quality improvement efforts.

An Evaluation of New York City's 2015 Birth Certificate Gender Marker Regulation.

PURPOSE: In 1971, the New York City (NYC) Department of Health and Mental Hygiene amended Section 207.05 of the NYC Health Code to allow individuals who had undergone "convertive surgery" (interpreted by the code to mean genital surgery) to amend the gender on their birth certificates. This surgery requirement was removed in 2015. In a survey evaluating the regulation change, we sought to characterize the transgender population newly eligible to obtain a gender-congruent NYC birth certificate by comparing respondents with and without genital surgery. METHODS: We mailed a 42-question survey with each newly issued birth certificate. We compared respondents across current gender identity, race, Hispanic ethnicity, age, insurance status, income, current general health status, other transition-related care obtained, and healthcare access, stigma, and discrimination. RESULTS: Of 642 applicants, 219 responded and were thus enrolled in our 5-year study (34.1%). Most (n = 158 out of 203 who answered, 77.8%) had not received genital surgery. Compared to respondents with genital surgery, respondents without surgery were significantly more likely to be transgender men (50.0% vs. 20.0%); younger (median age 32 vs. 56.5); on Medicaid (31.6% vs. 11.1%); identify as Hispanic (28.5% vs. 8.9%); and live in households making <$20,000 annually (35.3% vs. 12.8%). CONCLUSIONS: Removing a genital surgery requirement more equitably enables transgender men and those with limited resources to obtain a gender-congruent birth certificate. Jurisdictions with such requirements should consider similar regulation changes to address the inequities that this requirement likely imposes in accessing birth certificates.

Evaluating the Effectiveness of New York City Health Policy Initiatives in Reducing Cardiovascular Disease Mortality, 1990-2011.

Beginning in 2002, New York City (NYC) implemented numerous policies and programs targeting cardiovascular disease (CVD) risk factors. Using death certificates, we analyzed trends in NYC-specific and US mortality rates from 1990 to 2011 for all causes, any CVD, atherosclerotic CVD (ACVD), coronary artery disease (CAD), and stroke. Joinpoint analyses quantified annual percent change (APC) and evaluated whether decreases in CVD mortality accelerated after 2002 in either NYC or the total US population. Our analyses included 1,149,217 NYC decedents. The rates of decline in mortality from all causes, any CVD, and stroke in NYC did not change after 2002. Among men, the decline in ACVD mortality accelerated during 2002-2011 (APC = -4.8%, 95% confidence interval (CI): -6.1, -3.4) relative to 1990-2001 (APC = -2.3%, 95% CI: -3.1, -1.5). Among women, ACVD rates began declining more rapidly in 1993 (APC = -3.2%, 95% CI: -3.8, -2.7) and again in 2006 (APC = -6.6%, 95% CI: -8.9, -4.3) as compared with 1990-1992 (APC = 1.6%, 95% CI: -2.7, 6.0). In the US population, no acceleration of mortality decline was observed in either ACVD or CAD mortality rates after 2002. Relative to 1990-2001, atherosclerotic CVD and CAD rates began to decline more rapidly during the 2002-2011 period in both men and women-a pattern not observed in the total US population, suggesting that NYC initiatives might have had a measurable influence on delaying or reducing ACVD mortality.

Estimating Potential Reductions in Premature Mortality in New York City From Raising the Minimum Wage to $15.

OBJECTIVES: To assess potential reductions in premature mortality that could have been achieved in 2008 to 2012 if the minimum wage had been $15 per hour in New York City. METHODS: Using the 2008 to 2012 American Community Survey, we performed simulations to assess how the proportion of low-income residents in each neighborhood might change with a hypothetical $15 minimum wage under alternative assumptions of labor market dynamics. We developed an ecological model of premature death to determine the differences between the levels of premature mortality as predicted by the actual proportions of low-income residents in 2008 to 2012 and the levels predicted by the proportions of low-income residents under a hypothetical $15 minimum wage. RESULTS: A $15 minimum wage could have averted 2800 to 5500 premature deaths between 2008 and 2012 in New York City, representing 4% to 8% of total premature deaths in that period. Most of these avertable deaths would be realized in lower-income communities, in which residents are predominantly people of color. CONCLUSIONS: A higher minimum wage may have substantial positive effects on health and should be considered as an instrument to address health disparities.

Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes.

OBJECTIVES: We evaluated use of the Index of Concentration at the Extremes (ICE) for public health monitoring. METHODS: We used New York City data centered around 2010 to assess cross-sectional associations at the census tract and community district levels, for (1) diverse ICE measures plus the US poverty rate, with (2) infant mortality, premature mortality (before age 65 years), and diabetes mortality. RESULTS: Point estimates for rate ratios were consistently greatest for the novel ICE that jointly measured extreme concentrations of income and race/ethnicity. For example, the census tract-level rate ratio for infant mortality comparing the bottom versus top quintile for an ICE contrasting low-income Black versus high-income White equaled 2.93 (95% confidence interval [CI] = 2.11, 4.09), but was 2.19 (95% CI = 1.59, 3.02) for low versus high income, 2.77 (95% CI = 2.02, 3.81) for Black versus White, and 1.56 (95% CI = 1.19, 2.04) for census tracts with greater than or equal to 30% versus less than 10% below poverty. CONCLUSIONS: The ICE may be a useful metric for public health monitoring, as it simultaneously captures extremes of privilege and deprivation and can jointly measure economic and racial/ethnic segregation.