Prospective transitions in hemoglobin A1c following gestational diabetes using Multistate Markov Models.

OBJECTIVE: We characterized the state-to-state transitions in postpartum A1c levels after gestational diabetes, including remaining in a state of normoglycemia or transitions between prediabetes or diabetes states of varying severity. METHODS: We used data from the APPLE Cohort, a postpartum population-based cohort of individuals with gestational diabetes between 2009-2011and linked HbA1c data with up to 9 years follow-up (N=34,171). We examined maternal sociodemographic and perinatal characteristics as predictors of transitions in A1c progression using Markov multistate models. RESULTS: In the first-year postpartum following gestational diabetes, 45.1% of people had no-diabetes, 43.1% had prediabetes, 4.6% had controlled diabetes and 7.2% had uncontrolled diabetes. Roughly two-thirds of individuals remained in same state in the next year. Black individuals were more likely to transition from pre-diabetes to uncontrolled diabetes (aHR: 2.32 95% CI: 1.21 ,4.47) than White persons. Perinatal risk factors were associated with disease progression and lower likelihood of improvement. For example, hypertensive disorders of pregnancy were associated with a stronger transition (aHR: 2.06 95% CI: 1.39, 3.05) from prediabetes to uncontrolled diabetes. CONCLUSIONS: We illustrate factors associated with adverse transitions in incremental A1c stages and describe patient profiles who may warrant enhanced postpartum monitoring.

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.

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.

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.

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.

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.

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.

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.

Reducing sugary drink consumption: New York City's approach.

Studies have linked the consumption of sugary drinks to weight gain, obesity, and type 2 diabetes. Since 2006, New York City has taken several actions to reduce consumption. Nutrition standards limited sugary drinks served by city agencies. Mass media campaigns educated New Yorkers on the added sugars in sugary drinks and their health impact. Policy proposals included an excise tax, a restriction on use of Supplemental Nutrition Assistance Program benefits, and a cap on sugary drink portion sizes in food service establishments. These initiatives were accompanied by a 35% decrease in the number of New York City adults consuming one or more sugary drinks a day and a 27% decrease in public high school students doing so from 2007 to 2013.

Breakfast patterns among low-income, ethnically-diverse 4th-6th grade children in an urban area.

BACKGROUND: Increasing school breakfast participation has been advocated as a method to prevent childhood obesity. However, little is known about children's breakfast patterns outside of school (e.g., home, corner store). Policies that increase school breakfast participation without an understanding of children's breakfast habits outside of school may result in children consuming multiple breakfasts and may undermine efforts to prevent obesity. The aim of the current study was to describe morning food and drink consumption patterns among low-income, urban children and their associations with relative weight. METHODS: A cross-sectional analysis was conducted of data obtained from 651 4th-6th graders (51.7% female, 61.2% African American, 10.7 years) in 2012. Students completed surveys at school that included all foods eaten and their locations that morning. Height and weight were measured by trained research staff. RESULTS: On the day surveyed, 12.4% of youth reported not eating breakfast, 49.8% reported eating one breakfast, 25.5% reported eating two breakfasts, and 12.3% reported eating three or more breakfasts. The number of breakfasts consumed and BMI percentile showed a significant curvilinear relationship, with higher mean BMI percentiles observed among children who did not consume any breakfast and those who consumed ≥ 3 breakfasts. Sixth graders were significantly less likely to have consumed breakfast compared to younger children. A greater proportion of obese youth had no breakfast (18.0%) compared to healthy weight (10.1%) and overweight youth (10.7%, p = .01). CONCLUSIONS: When promoting school breakfast, policies will need to be mindful of both over- and under-consumption to effectively address childhood obesity and food insecurity. CLINICAL TRIAL REGISTRATION: NCT01924130 from http://clinicaltrials.gov/.

Comparing sugary drinks in the food retail environment in six NYC neighborhoods.

Obesity is a national public health concern linked to numerous chronic health conditions among Americans of all age groups. Evidence suggests that discretionary calories from sugary drink consumption have been a significant contributor to excess caloric intake among both children and adults. Research has established strong links between retail food environments and purchasing habits of consumers, but little information exists on the sugary drink retail environment in urban neighborhoods. The objective of this assessment was to compare various aspects of the sugary drink retail environment across New York City (NYC) neighborhoods with disparate self-reported sugary drink consumption patterns. In-store retail audits were conducted at 883 corner stores, chain pharmacies, and grocery stores in 12 zip codes throughout NYC. Results showed that among all beverage types assessed, sugary drinks had the most prominent presence in the retail environment overall, which was even more pronounced in higher-consumption neighborhoods. In higher- versus lower-consumption neighborhoods, the mean number of sugary drink varieties available at stores was higher (11.4 vs. 10.4 varieties), stores were more likely to feature sugary drink advertising (97 vs. 89 %) and advertising at multiple places throughout the store (78 vs. 57 %), and several sugary drinks, including 20-oz Coke® or Pepsi®, were less expensive ($1.38 vs. $1.60). These results, all statistically significant, indicate that neighborhoods characterized by higher levels of sugary drink consumption expose shoppers to sugary drinks to a greater extent than lower-consumption neighborhoods. This builds upon evidence documenting the association between the environment and individual behavior.

Institution-to-institution mentoring to build capacity in 24 local US health departments: best practices and lessons learned.

INTRODUCTION: Institutional mentoring may be a useful capacity-building model to support local health departments facing public health challenges. The New York City Department of Health and Mental Hygiene conducted a qualitative evaluation of an institutional mentoring program designed to increase capacity of health departments seeking to address chronic disease prevention. The mentoring program included 2 program models, a one-to-one model and a collaborative model, developed and implemented for 24 Communities Putting Prevention to Work grantee communities nationwide. METHODS: We conducted semi-structured telephone interviews to assess grantees' perspectives on the effectiveness of the mentoring program in supporting their work. Two interviews were conducted with key informants from each participating community. Three evaluators coded and analyzed data using ATLAS.ti software and using grounded theory to identify emerging themes. RESULTS: We completed 90 interviews with 44 mentees. We identified 7 key program strengths: learning from the New York City health department's experience, adapting resources to local needs, incorporating new approaches and sharing strategies, developing the mentor-mentee relationship, creating momentum for action, establishing regular communication, and encouraging peer interaction. CONCLUSION: Participants overwhelmingly indicated that the mentoring program's key strengths improved their capacity to address chronic disease prevention in their communities. We recommend dissemination of the results achieved, emphasizing the need to adapt the institutional mentoring model to local needs to achieve successful outcomes. We also recommend future research to consider whether a hybrid programmatic model that includes regular one-on-one communication and in-person conferences could be used as a standard framework for institutional mentoring.

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.

Preconception HbA1c Levels in Adolescents and Young Adults and Adverse Birth Outcomes.

Importance: Subclinical hyperglycemia before pregnancy may be associated with the likelihood of maternal morbidity but is understudied among young people. Objective: To explore the association of preconception hemoglobin A1c (HbA1c) levels among adolescents and young adults with risk of gestational diabetes at first live birth. Design, Setting, and Participants: This retrospective cohort study used linked 2009 to 2017 birth registry, hospital discharge, and New York City Department of Health A1C Registry data for birthing individuals aged 10 to 24 years with no history of diabetes and at least 1 preconception HbA1c test in New York, New York. Statistical analysis was performed from August to November 2022. Exposure: Preconception HbA1c values categorized as no diabetes (HbA1c <5.7%) or prediabetes (HbA1c ≥5.7% to <6.5%). Main Outcomes and Measures: The primary outcome was gestational diabetes at first birth. Secondary outcomes included hypertensive disorders of pregnancy, preterm birth, cesarean delivery, and macrosomia. Log binomial regression was used to estimate the relative risk (RR) of gestational diabetes at first birth by preconception HbA1c level, adjusting for prepregnancy characteristics. The optimal HbA1c threshold for gestational diabetes was examined using receiver operating curve regression. Results: A total of 14 302 individuals (mean [SD] age, 22.10 [1.55] years) met study eligibility criteria. Of these, 5896 (41.0%) were Hispanic, 4149 (29.0%) were Black, 2583 (18.1%) were White, 1516 (10.6%) were Asian, and 185 (1.3%) had other or unknown race and ethnicity. Most (11 407 individuals [79.7%]) had normoglycemia before pregnancy, and 2895 individuals (20.2%) had prediabetes. Adjusting for prepregnancy characteristics, those with preconception prediabetes had more than twice the risk of gestational diabetes vs those with normoglycemia (adjusted RR [aRR], 2.21; 95% CI, 1.91-2.56). Preconception prediabetes was associated with small increases in the likelihood of a hypertensive disorder of pregnancy (aRR, 1.18; 95% CI, 1.03-1.35) and preterm delivery (aRR, 1.18; 95% CI, 1.02-1.37). The aRRs for cesarean delivery (aRR, 1.09; 95% CI, 0.99-1.20) and macrosomia (aRR, 1.13; 95% CI, 0.93-1.37) were increased but not statistically significant. The optimal HbA1c threshold to identify gestational diabetes among adolescents and young adults was 5.6%. The threshold did not vary by obesity status but was slightly lower among Hispanic individuals (HbA1c of 5.5%). Conclusions and Relevance: In this study of adolescents and young adults with at least 1 preconception HbA1c test, prediabetes was associated with increased likelihood of maternal cardiometabolic morbidity at first birth. Efforts to optimize cardiometabolic health before pregnancy may avert excess maternal risk.

Evaluation of the New York City breakfast in the classroom program.

OBJECTIVES: We determined the impact of Breakfast in the Classroom (BIC) on the percentage of children going without morning food, number of locations where food was consumed, and estimated calories consumed per child. METHODS: We used a cross-sectional survey of morning food consumed among elementary school students offered BIC and not offered BIC in geographically matched high-poverty-neighborhood elementary schools. RESULTS: Students offered BIC (n = 1044) were less likely to report not eating in the morning (8.7%) than were students not offered BIC (n = 1245; 15.0%) and were more likely to report eating in 2 or more locations during the morning (51.1% vs 30%). Overall, students offered BIC reported consuming an estimated 95 more calories per morning than did students not offered BIC. CONCLUSIONS: For every student for whom BIC resolved the problem of starting school with nothing to eat, more than 3 students ate in more than 1 location. Offering BIC reduced the percentage of students not eating in the morning but may contribute to excess calorie intake. More evaluation of BIC's impact on overweight and obesity is needed before more widespread implementation.

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.

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.