Prenatal Risks to Healthy Food Access and High Birthweight Outcomes.

OBJECTIVE: Infants with high birthweight have increased risk for adverse outcomes at birth and across childhood. Prenatal risks to healthy food access may increase odds of high birthweight. We tested whether having a poor neighborhood food environment and/or food insecurity had associations with high birthweight. METHODS: We analyzed cross-sectional baseline data in Greenlight Plus, an obesity prevention trial across six US cities (n = 787), which included newborns with a gestational age greater than 34 weeks and a birthweight greater than 2500 g. We assessed neighborhood food environment using the Place-Based Survey and food insecurity using the US Household Food Security Module. We performed logistic regression analyses to assess the individual and additive effects of risk factors on high birthweight. We adjusted for potential confounders: infant sex, race, ethnicity, gestational age, birthing parent age, education, income, and study site. RESULTS: Thirty-four percent of birthing parents reported poor neighborhood food environment and/or food insecurity. Compared to those without food insecurity, food insecure families had greater odds of delivering an infant with high birthweight (adjusted odds ratios [aOR] 1.96, 95% confidence intervals [CI]: 1.01, 3.82) after adjusting for poor neighborhood food environment, which was not associated with high birthweight (aOR 1.35, 95% CI: 0.78, 2.34). Each additional risk to healthy food access was associated with a 56% (95% CI: 4%-132%) increase in high birthweight odds. CONCLUSIONS: Prenatal risks to healthy food access may increase high infant birthweight odds. Future studies designed to measure neighborhood factors should examine infant birthweight outcomes in the context of prenatal social determinants of health.

COVID-19 vaccines for children: Racial and ethnic disparities in New York City.

Vaccination is an indispensable tool to reduce negative outcomes due to COVID-19. Although COVID-19 disproportionately affected lower income and Black and Hispanic communities, these groups have had lower population-level uptake of vaccines. Using detailed cross-sectional data, we examined racial and ethnic group differences in New York City schoolchildren becoming fully vaccinated (two doses) within 6 months of vaccine eligibility. We matched school enrollment data to vaccination data in the Citywide Immunization Registry, a census of all vaccinations delivered in New York City. We used ordinary least squares regression models to predict fully vaccinated status, with key predictors of race and ethnicity using a variety of different control variables, including residential neighborhood or school fixed effects. We also stratified by borough and by age. The sample included all New York City public school students enrolled during the 2021-2022 school year. Asian students were most likely to be vaccinated and Black and White students least likely. Controlling for student characteristics, particularly residential neighborhood or school attended, diminished some of the race and ethnicity differences. Key differences were also present by borough, both overall and by racial and ethnic groups. In sum, racial and ethnic disparities in children's COVID-19 vaccination were present. Vaccination rates varied by the geographic unit of borough; controlling for neighborhood characteristics diminished some disparities by race and ethnicity. Neighborhood demographics and resources, and the attributes, culture and preferences of those who live there may affect vaccination decisions and could be targets of future efforts to increase vaccination rates.

The Prenatal Neighborhood Environment and Geographic Hotspots of Infants with At-risk Birthweights in New York City.

Infants born with low or high ("at-risk") birthweights are at greater risk of adverse health outcomes across the life course. Our objective was to examine whether geographic hotspots of low and high birthweight prevalence in New York City had different patterns of neighborhood risk factors. We performed census tract-level geospatial clustering analyses using (1) birthweight prevalence and maternal residential address from an all-payer claims database and (2) domains of neighborhood risk factors (socioeconomic and food environment) from national and local datasets. We then used logistic regression analysis to identify specific neighborhood risk factors associated with low and high birthweight hotspots. This study examined 2088 census tracts representing 419,025 infants. We found almost no overlap (1.5%) between low and high birthweight hotspots. The majority of low birthweight hotspots (87.2%) overlapped with a socioeconomic risk factor and 95.7% overlapped with a food environment risk factor. Half of high birthweight hotspots (50.0%) overlapped with a socioeconomic risk factor and 48.8% overlapped with a food environment risk factor. Low birthweight hotspots were associated with high prevalence of excessive housing cost, unemployment, and poor food environment. High birthweight hotspots were associated with high prevalence of uninsured persons and convenience stores. Programs and policies that aim to prevent disparities in infant birthweight should examine the broader context by which hotspots of at-risk birthweight overlap with neighborhood risk factors. Multi-level strategies that include the neighborhood context are needed to address prenatal pathways leading to low and high birthweight outcomes.

Prospective Assessment of an Automated Intraprocedural 12-Lead ECG-Based System for Localization of Early Left Ventricular Activation.

BACKGROUND: To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy. METHODS: The automated site of origin localization system consists of 3 steps: (1) localization of ventricular segment based on population templates, (2) population-based localization within a segment, and (3) patient-specific site localization. Localization error was assessed by the distance between the known reference site and the estimated site. RESULTS: In 19 patients undergoing 21 catheter ablation procedures of scar-related VT, site of origin localization accuracy was estimated using 552 left ventricular endocardial pacing sites pooled together and 25 VT-exit sites identified by contact mapping. For the 25 VT-exit sites, localization error of the population-based localization steps was within 10 mm. Patient-specific site localization achieved accuracy of within 3.5 mm after including up to 11 pacing (training) sites. Using 3 remotes (67.8±17.0 mm from the reference VT-exit site), and then 5 close pacing sites, resulted in localization error of 7.2±4.1 mm for the 25 identified VT-exit sites. In 2 emulated clinical procedure with 2 induced VTs, the site of origin localization system achieved accuracy within 4 mm. CONCLUSIONS: In this prospective validation study, the automated localization system achieved estimated accuracy within 10 mm and could thus provide clinical utility.

When Crises Converge: Hospital Visits Before And After Shelter Use Among Homeless New Yorkers.

People who are homeless use more hospital-based care than average, yet little is known about how hospital and shelter use are interrelated. We examined the timing of emergency department (ED) visits and hospitalizations relative to entry into and exit from New York City homeless shelters, using an analysis of linked health care and shelter administrative databases. In the year before shelter entry and the year following shelter exit, 39.3 percent and 43.3 percent, respectively, of first-time adult shelter users had an ED visit or hospitalization. Hospital visits-particularly ED visits-began to increase several months before shelter entry and declined over several months after shelter exit, with spikes in ED visits and hospitalizations in the days immediately before shelter entry and following shelter exit. We recommend cross-system collaborations to better understand and address the co-occurring health and housing needs of vulnerable populations.

Age Disparities Among Patients With Type 2 Diabetes and Associated Rates of Hospital Use and Diabetic Complications.

INTRODUCTION: Although screening for diabetes is recommended at age 45, some populations may be at greater risk at earlier ages. Our objective was to quantify age disparities among patients with type 2 diabetes in New York City. METHODS: Using all-payer hospital claims data for New York City, we performed a cross-sectional analysis of patients with type 2 diabetes identified from emergency department visits during the 5-year period 2011-2015. We estimated type 2 diabetes prevalence at each year of life, the age distribution of patients stratified by decade, and the average age of patients by sex, race/ethnicity, and geographic location. RESULTS: We identified 576,306 unique patients with type 2 diabetes. These patients represented more than half of all people with type 2 diabetes in New York City. Patients in racial/ethnic minority groups were on average 5.5 to 8.4 years younger than non-Hispanic white patients. At age 45, type 2 diabetes prevalence was 10.9% among non-Hispanic black patients and 5.2% among non-Hispanic white patients. In our geospatial analyses, patients with type 2 diabetes were on average 6 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was also 1 to 2 years younger in hotspots of microvascular diabetic complications. CONCLUSION: We identified profound age disparities among patients with type 2 diabetes in racial/ethnic minority groups and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetic complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control.

Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data.

Geographic surveillance can identify hotspots of disease and reveal associations between health and the environment. Our study used emergency department surveillance to investigate geographic disparities in type 1 and type 2 diabetes prevalence among adults and children. Using all-payer emergency claims data from 2009 to 2013, we identified unique New York City residents with diabetes and geocoded their location using home addresses. Geospatial analysis was performed to estimate diabetes prevalence by New York City Census tract. We also used multivariable regression to identify neighborhood-level factors associated with higher diabetes prevalence. We estimated type 1 and type 2 diabetes prevalence at 0.23% and 10.5%, respectively, among adults and 0.20% and 0.11%, respectively, among children in New York City. Pediatric type 1 diabetes was associated with higher income (P = 0.001), whereas adult type 2 diabetes was associated with lower income (P < 0.001). Areas with a higher proportion of nearby restaurants categorized as fast food had a higher prevalence of all types of diabetes (P < 0.001) except for pediatric type 2 diabetes. Type 2 diabetes among children was only higher in neighborhoods with higher proportions of African American residents (P < 0.001). Our findings identify geographic disparities in diabetes prevalence that may require special attention to address the specific needs of adults and children living in these areas. Our results suggest that the food environment may be associated with higher type 1 diabetes prevalence. However, our analysis did not find a robust association with the food environment and pediatric type 2 diabetes, which was predominantly focused in African American neighborhoods.

Using Geospatial Analysis and Emergency Claims Data to Improve Minority Health Surveillance.

Traditional methods of health surveillance often under-represent racial and ethnic minorities. Our objective was to use geospatial analysis and emergency claims data to estimate local chronic disease prevalence separately for specific racial and ethnic groups. We also performed a regression analysis to identify associations between median household income and local disease prevalence among Black, Hispanic, Asian, and White adults in New York City. The study population included individuals who visited an emergency department at least once from 2009 to 2013. Our main outcomes were geospatial estimates of diabetes, hypertension, and asthma prevalence by Census tract as stratified by race and ethnicity. Using emergency claims data, we identified 4.9 million unique New York City adults with 28.5% of identifying as Black, 25.2% Hispanic, and 6.1% Asian. Age-adjusted disease prevalence was highest among Black and Hispanic adults for diabetes (13.4 and 13.1%), hypertension (28.7 and 24.1%), and asthma (9.9 and 10.1%). Correlation between disease prevalence maps demonstrated moderate overlap between Black and Hispanic adults for diabetes (0.49), hypertension (0.57), and asthma (0.58). In our regression analysis, we found that the association between low income and high disease prevalence was strongest for Hispanic adults, whereas increases in income had more modest reductions in disease prevalence for Black adults, especially for diabetes. Our geographically detailed maps of disease prevalence generate actionable evidence that can help direct health interventions to those communities with the highest health disparities. Using these novel geographic approaches, we reveal the underlying epidemiology of chronic disease for a racially and culturally diverse population.

Vulnerability of Older Adults in Disasters: Emergency Department Utilization by Geriatric Patients After Hurricane Sandy.

OBJECTIVE: Older adults are a potentially medically vulnerable population with increased mortality rates during and after disasters. To evaluate the impact of a natural disaster on this population, we performed a temporal and geospatial analysis of emergency department (ED) use by adults aged 65 years and older in New York City (NYC) following Hurricane Sandy's landfall. METHODS: We used an all-payer claims database to analyze demographics, insurance status, geographic distribution, and health conditions for post-disaster ED visits among older adults. We compared ED patterns of use in the weeks before and after Hurricane Sandy throughout NYC and the most afflicted evacuation zones. RESULTS: We found significant increases in ED utilization by older adults (and disproportionately higher in those aged ≥85 years) in the 3 weeks after Hurricane Sandy, especially in NYC evacuation zone one. Primary diagnoses with notable increases included dialysis, electrolyte disorders, and prescription refills. Secondary diagnoses highlighted homelessness and care access issues. CONCLUSIONS: Older adults display heightened risk for worse health outcomes with increased ED visits after a disaster. Our findings suggest the need for dedicated resources and planning for older adults following a natural disaster by ensuring access to medical facilities, prescriptions, dialysis, and safe housing and by optimizing health care delivery needs to reduce the burden of chronic disease. (Disaster Med Public Health Preparedness. 2018;12:184-193).

The Epidemiology of Emergency Department Trauma Discharges in the United States.

OBJECTIVE: Injury-related morbidity and mortality is an important emergency medicine and public health challenge in the United States. Here we describe the epidemiology of traumatic injury presenting to U.S. emergency departments (EDs), define changes in types and causes of injury among the elderly and the young, characterize the role of trauma centers and teaching hospitals in providing emergency trauma care, and estimate the overall economic burden of treating such injuries. METHODS: We conducted a secondary retrospective, repeated cross-sectional study of the Nationwide Emergency Department Data Sample (NEDS), the largest all-payer ED survey database in the United States. Main outcomes and measures were survey-adjusted counts, proportions, means, and rates with associated standard errors (SEs) and 95% confidence intervals. We plotted annual age-stratified ED discharge rates for traumatic injury and present tables of proportions of common injuries and external causes. We modeled the association of Level I or II trauma center care with injury fatality using a multivariable survey-adjusted logistic regression analysis that controlled for age, sex, injury severity, comorbid diagnoses, and teaching hospital status. RESULTS: There were 181,194,431 (SE = 4,234) traumatic injury discharges from U.S. EDs between 2006 and 2012. There was a mean year-to-year decrease of 143 (95% CI = -184.3 to -68.5) visits per 100,000 U.S. population during the study period. The all-age, all-cause case-fatality rate for traumatic injuries across U.S. EDs during the study period was 0.17% (SE = 0.001%). The case-fatality rate for the most severely injured averaged 4.8% (SE = 0.001%), and severely injured patients were nearly four times as likely to be seen in Level I or II trauma centers (relative risk = 3.9 [95% CI = 3.7 to 4.1]). The unadjusted risk ratio, based on group counts, for the association of Level I or II trauma centers with mortality was risk ratio = 4.9 (95% CI = 4.5 to 5.3); however, after sex, age, injury severity, and comorbidities were accounted for, Level I or II trauma centers were not associated with an increased risk of fatality (odds ratio = 0.96 [95% CI = 0.79 to 1.18]). There were notable changes at the extremes of age in types and causes of ED discharges for traumatic injury between 2009 and 2012. Age-stratified rates of diagnoses of traumatic brain injury increased 29.5% (SE = 2.6%) for adults older than 85 and increased 44.9% (SE = 1.3%) for children younger than 18. Firearm-related injuries increased 31.7% (SE = 0.2%) in children 5 years and younger. The total inflation-adjusted cost of ED injury care in the United States between 2006 and 2012 was $99.75 billion (SE = $0.03 billion). CONCLUSIONS: Emergency departments are a sensitive barometer of the continuing impact of traumatic injury as an important cause of morbidity and mortality in the United States. Level I or II trauma centers remain a bulwark against the tide of severe trauma in the United States, but the types and causes of traumatic injury in the United States are changing in consequential ways, particularly at the extremes of age, with traumatic brain injuries and firearm-related trauma presenting increased challenges.

Traumatic injury in the United States: In-patient epidemiology 2000-2011.

BACKGROUND: Trauma is a leading cause of death and disability in the United States (US). This analysis describes trends and annual changes in in-hospital trauma morbidity and mortality; evaluates changes in age and gender specific outcomes, diagnoses, causes of injury, injury severity and surgical procedures performed; and examines the role of teaching hospitals and Level 1 trauma centres in the care of severely injured patients. METHODS: We conducted a retrospective descriptive and analytic epidemiologic study of an inpatient database representing 20,659,684 traumatic injury discharges from US hospitals between 2000 and 2011. The main outcomes and measures were survey-adjusted counts, proportions, means, standard errors, and 95% confidence intervals. We plotted time series of yearly data with overlying loess smoothing, created tables of proportions of common injuries and surgical procedures, and conducted survey-adjusted logistic regression analysis for the effect of year on the odds of in-hospital death with control variables for age, gender, weekday vs. weekend admission, trauma-centre status, teaching-hospital status, injury severity and Charlson index score. RESULTS: The mean age of a person discharged from a US hospital with a trauma diagnosis increased from 54.08 (s.e.=0.71) in 2000 to 59.58 (s.e.=0.79) in 2011. Persons age 45-64 were the only age group to experience increasing rates of hospital discharges for trauma. The proportion of trauma discharges with a Charlson Comorbidity Index score greater than or equal to 3 nearly tripled from 0.048 (s.e.=0.0015) of all traumatic injury discharges in 2000 to 0.139 (s.e.=0.005) in 2011. The proportion of patients with traumatic injury classified as severe increased from 22% of all trauma discharges in 2000 (95% CI 21, 24) to 28% in 2011 (95% CI 26, 30). Level 1 trauma centres accounted for approximately 3.3% of hospitals. The proportion of severely injured trauma discharges from Level 1 trauma centres was 39.4% (95% CI 36.8, 42.1). Falls, followed by motor-vehicle crashes, were the most common causes of all injuries. The total cost of trauma-related inpatient care between 2001 and 2011 in the US was $240.7 billion (95% CI 231.0, 250.5). Annual total US inpatient trauma-related hospital costs increased each year between 2001 and 2011, more than doubling from $12.0 billion (95% CI 10.5, 13.4) in 2001 to 29.1 billion (95% CI 25.2, 32.9) in 2011. CONCLUSIONS: Trauma, which has traditionally been viewed as a predicament of the young, is increasingly a disease of the old. The strain of managing the progressively complex and costly care associated with this shift rests with a small number of trauma centres. Optimal care of injured patients requires a reappraisal of the resources required to effectively provide it given a mounting burden.

Prehospital Indicators for Disaster Preparedness and Response: New York City Emergency Medical Services in Hurricane Sandy.

OBJECTIVE: We aimed to evaluate emergency medical services (EMS) data as disaster metrics and to assess stress in surrounding hospitals and a municipal network after the closure of Bellevue Hospital during Hurricane Sandy in 2012. METHODS: We retrospectively reviewed EMS activity and call types within New York City's 911 computer-assisted dispatch database from January 1, 2011, to December 31, 2013. We evaluated EMS ambulance transports to individual hospitals during Bellevue's closure and incremental recovery from urgent care capacity, to freestanding emergency department (ED) capability, freestanding ED with 911-receiving designation, and return of inpatient services. RESULTS: A total of 2,877,087 patient transports were available for analysis; a total of 707,593 involved Manhattan hospitals. The 911 ambulance transports disproportionately increased at the 3 closest hospitals by 63.6%, 60.7%, and 37.2%. When Bellevue closed, transports to specific hospitals increased by 45% or more for the following call types: blunt traumatic injury, drugs and alcohol, cardiac conditions, difficulty breathing, "pedestrian struck," unconsciousness, altered mental status, and emotionally disturbed persons. CONCLUSIONS: EMS data identified hospitals with disproportionately increased patient loads after Hurricane Sandy. Loss of Bellevue, a public, safety net medical center, produced statistically significant increases in specific types of medical and trauma transports at surrounding hospitals. Focused redeployment of human, economic, and social capital across hospital systems may be required to expedite regional health care systems recovery. (Disaster Med Public Health Preparedness. 2016;10:333-343).

Comprehensive Assessment of Osteoporosis and Bone Fragility with CT Colonography.

PURPOSE: To evaluate the ability of additional analysis of computed tomographic (CT) colonography images to provide a comprehensive osteoporosis assessment. MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act-compliant study was approved by our institutional review board with a waiver of informed consent. Diagnosis of osteoporosis and assessment of fracture risk were compared between biomechanical CT analysis and dual-energy x-ray absorptiometry (DXA) in 136 women (age range, 43-92 years), each of whom underwent CT colonography and DXA within a 6-month period (between January 2008 and April 2010). Blinded to the DXA data, biomechanical CT analysis was retrospectively applied to CT images by using phantomless calibration and finite element analysis to measure bone mineral density and bone strength at the hip and spine. Regression, Bland-Altman, and reclassification analyses and paired t tests were used to compare results. RESULTS: For bone mineral density T scores at the femoral neck, biomechanical CT analysis was highly correlated (R(2) = 0.84) with DXA, did not differ from DXA (P = .15, paired t test), and was able to identify osteoporosis (as defined by DXA), with 100% sensitivity in eight of eight patients (95% confidence interval [CI]: 67.6%, 100%) and 98.4% specificity in 126 of 128 patients (95% CI: 94.5%, 99.6%). Considering both the hip and spine, the classification of patients at high risk for fracture by biomechanical CT analysis--those with osteoporosis or "fragile bone strength"--agreed well against classifications for clinical osteoporosis by DXA (T score ≤-2.5 at the hip or spine), with 82.8% sensitivity in 24 of 29 patients (95% CI: 65.4%, 92.4%) and 85.7% specificity in 66 of 77 patients (95% CI: 76.2%, 91.8%). CONCLUSION: Retrospective biomechanical CT analysis of CT colonography for colorectal cancer screening provides a comprehensive osteoporosis assessment without requiring changes in imaging protocols.

Determining Chronic Disease Prevalence in Local Populations Using Emergency Department Surveillance.

OBJECTIVES: We sought to improve public health surveillance by using a geographic analysis of emergency department (ED) visits to determine local chronic disease prevalence. METHODS: Using an all-payer administrative database, we determined the proportion of unique ED patients with diabetes, hypertension, or asthma. We compared these rates to those determined by the New York City Community Health Survey. For diabetes prevalence, we also analyzed the fidelity of longitudinal estimates using logistic regression and determined disease burden within census tracts using geocoded addresses. RESULTS: We identified 4.4 million unique New York City adults visiting an ED between 2009 and 2012. When we compared our emergency sample to survey data, rates of neighborhood diabetes, hypertension, and asthma prevalence were similar (correlation coefficient = 0.86, 0.88, and 0.77, respectively). In addition, our method demonstrated less year-to-year scatter and identified significant variation of disease burden within neighborhoods among census tracts. CONCLUSIONS: Our method for determining chronic disease prevalence correlates with a validated health survey and may have higher reliability over time and greater granularity at a local level. Our findings can improve public health surveillance by identifying local variation of disease prevalence.

Reading and understanding employee benefit plan financial statements.

If your employee benefit plan has more than 100 participants, chances are you've had to work your way through the audited financial statements you're required to include with your Form 5500 filing. These statements contain a wealth of information about the financial health of your plan, and understanding them is an important fiduciary responsibility. To strengthen your grasp of financial statements, this article gives an overview that will make a plan's financial statements more informative, explains their basic structure and provides information on some of the more arcane aspects (such as actuarial tables). While this article focuses on Taft-Hartley (multiemployer) plans, much of it applies to other types of employee benefit plans.