Robot-Assisted Surgery and Racial and Ethnic Disparities in Post-Prostatectomy Outcomes Among Prostate Cancer Patients.

BACKGROUND: We sought to determine whether the differences in short-term outcomes between patients undergoing robot-assisted radical prostatectomy (RARP) and those treated with open radical prostatectomy (ORP) differ by race and ethnicity. METHODS: This observational study used New York State Cancer Registry data linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer during 2008-2018. We used logistic regression to examine the association between race and ethnicity (non-Hispanic White [NHW], non-Hispanic Black [NHB], Hispanic), surgical approach (RARP, ORP), and postoperative outcomes (major events, prolonged length of stay [pLOS], 30-day re-admission). We tested interaction between race and ethnicity and surgical approach on multiplicative and additive scales. RESULTS: The analytical cohort included 18,926 patients (NHW 14,215 [75.1%], NHB 3195 [16.9%], Hispanic 1516 [8.0%]). The average age was 60.4 years (standard deviation 7.1). NHB and Hispanic patients had lower utilization of RARP and higher risks of postoperative adverse events than NHW patients. NHW, NHB, and Hispanic patients all had reduced risks of adverse events when undergoing RARP versus ORP. The absolute reductions in the risks of major events and pLOS following RARP versus ORP were larger among NHB {relative excess risk due to interaction (RERI): major events -0.32 [95% confidence interval (CI) -0.71 to -0.03]; pLOS -0.63 [95% CI -0.98 to -0.35]) and Hispanic (RERI major events -0.27 [95% CI -0.77 to 0.09]; pLOS -0.93 [95% CI -1.46 to -0.51]) patients than among NHW patients. The interaction was absent on the multiplicative scale. CONCLUSIONS: RARP use has not penetrated and benefited all racial and ethnic groups equally. Increasing utilization of RARP among NHB and Hispanic patients may help reduce disparities in patient outcomes after radical prostatectomy.

Neighborhood Deprivation and Neural Tube Defects.

BACKGROUND: Individual measures of socioeconomic status (SES) have been associated with an increased risk of neural tube defects (NTDs); however, the association between neighborhood SES and NTD risk is unknown. Using data from the National Birth Defects Prevention Study (NBDPS) from 1997 to 2011, we investigated the association between measures of census tract SES and NTD risk. METHODS: The study population included 10,028 controls and 1829 NTD cases. We linked maternal addresses to census tract SES measures and used these measures to calculate the neighborhood deprivation index. We used generalized estimating equations to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) estimating the impact of quartiles of census tract deprivation on NTDs adjusting for maternal race-ethnicity, maternal education, and maternal age at delivery. RESULTS: Quartiles of higher neighborhood deprivation were associated with NTDs when compared with the least deprived quartile (Q2: aOR = 1.2; 95% CI = 1.0, 1.4; Q3: aOR = 1.3, 95% CI = 1.1, 1.5; Q4 (highest): aOR = 1.2; 95% CI = 1.0, 1.4). Results for spina bifida were similar; however, estimates for anencephaly and encephalocele were attenuated. Associations differed by maternal race-ethnicity. CONCLUSIONS: Our findings suggest that residing in a census tract with more socioeconomic deprivation is associated with an increased risk for NTDs, specifically spina bifida.

Neighborhood-level Socioeconomic Position During Early Pregnancy and Risk of Gastroschisis.

BACKGROUND: Neighborhood-level socioeconomic position has been shown to influence birth outcomes, including selected birth defects. This study examines the un derstudied association between neighborhood-level socioeconomic position during early pregnancy and the risk of gastroschisis, an abdominal birth defect of increasing prevalence. METHODS: We conducted a case-control study of 1,269 gastroschisis cases and 10,217 controls using data from the National Birth Defects Prevention Study (1997-2011). To characterize neighborhood-level socioeconomic position, we conducted a principal component analysis to construct two indices-Neighborhood Deprivation Index (NDI) and Neighborhood Socioeconomic Position Index (nSEPI). We created neighborhood-level indices using census socioeconomic indicators corresponding to census tracts associated with addresses where mothers lived the longest during the periconceptional period. We used generalized estimating equations to estimate odds ratios (ORs) and 95% confidence intervals (CIs), with multiple imputations for missing data and adjustment for maternal race-ethnicity, household income, education, birth year, and duration of residence. RESULTS: Mothers residing in moderate (NDI Tertile 2 aOR = 1.23; 95% CI = 1.03, 1.48 and nSEPI Tertile 2 aOR = 1.24; 95% CI = 1.04, 1.49) or low socioeconomic neighborhoods (NDI Tertile 3 aOR = 1.28; 95% CI = 1.05, 1.55 and nSEPI Tertile 3 aOR = 1.32, 95% CI = 1.09, 1.61) were more likely to deliver an infant with gastroschisis compared with mothers residing in high socioeconomic neighborhoods. CONCLUSIONS: Our findings suggest that lower neighborhood-level socioeconomic position during early pregnancy is associated with elevated odds of gastroschisis. Additional epidemiologic studies may aid in confirming this finding and evaluating potential mechanisms linking neighborhood-level socioeconomic factors and gastroschisis.

Assessing associations between residential proximity to greenspace and birth defects in the National Birth Defects Prevention Study.

BACKGROUND: Residential proximity to greenspace is associated with various health outcomes. OBJECTIVES: We estimated associations between maternal residential proximity to greenspace (based on an index of vegetation) and selected structural birth defects, including effect modification by neighborhood-level factors. METHODS: Data were from the National Birth Defects Prevention Study (1997-2011) and included 19,065 infants with at least one eligible birth defect (cases) and 8925 without birth defects (controls) from eight Centers throughout the United States. Maternal participants reported their addresses throughout pregnancy. Each address was systematically geocoded and residences around conception were linked to greenspace, US Census, and US Department of Agriculture data. Greenspace was estimated using the normalized difference vegetation index (NDVI); average maximum NDVI was estimated within 100 m and 500 m concentric buffers surrounding geocoded addresses to estimate residential NDVI. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals comparing those in the highest and lowest quartiles of residential NDVI and stratifying by rural/urban residence and neighborhood median income. RESULTS: After multivariable adjustment, for the 500 m buffer, inverse associations were observed for tetralogy of Fallot, secundum atrial septal defects, anencephaly, anotia/microtia, cleft lip ± cleft palate, transverse limb deficiency, and omphalocele, (aORs: 0.54-0.86). Results were similar for 100 m buffer analyses and similar patterns were observed for other defects, though results were not significant. Significant heterogeneity was observed after stratification by rural/urban for hypoplastic left heart, coarctation of the aorta, and cleft palate, with inverse associations only among participants residing in rural areas. Stratification by median income showed heterogeneity for atrioventricular and secundum atrial septal defects, anencephaly, and anorectal atresia, with inverse associations only among participants residing in a high-income neighborhood (aORs: 0.45-0.81). DISCUSSION: Our results suggest that perinatal residential proximity to more greenspace may contribute to a reduced risk of certain birth defects, especially among those living in rural or high-income neighborhoods.

Public Health Response to a Case of Paralytic Poliomyelitis in an Unvaccinated Person and Detection of Poliovirus in Wastewater - New York, June-August 2022.

On July 18, 2022, the New York State Department of Health (NYSDOH) notified CDC of detection of poliovirus type 2 in stool specimens from an unvaccinated immunocompetent young adult from Rockland County, New York, who was experiencing acute flaccid weakness. The patient initially experienced fever, neck stiffness, gastrointestinal symptoms, and limb weakness. The patient was hospitalized with possible acute flaccid myelitis (AFM). Vaccine-derived poliovirus type 2 (VDPV2) was detected in stool specimens obtained on days 11 and 12 after initial symptom onset. To date, related Sabin-like type 2 polioviruses have been detected in wastewater* in the patient's county of residence and in neighboring Orange County up to 25 days before (from samples originally collected for SARS-CoV-2 wastewater monitoring) and 41 days after the patient's symptom onset. The last U.S. case of polio caused by wild poliovirus occurred in 1979, and the World Health Organization Region of the Americas was declared polio-free in 1994. This report describes the second identification of community transmission of poliovirus in the United States since 1979; the previous instance, in 2005, was a type 1 VDPV (1). The occurrence of this case, combined with the identification of poliovirus in wastewater in neighboring Orange County, underscores the importance of maintaining high vaccination coverage to prevent paralytic polio in persons of all ages.

Road traffic density and recurrent asthma emergency department visits among Medicaid enrollees in New York State 2005-2015.

BACKGROUND: Environmental exposures such as traffic may contribute to asthma morbidity including recurrent emergency department (ED) visits. However, these associations are often confounded by socioeconomic status and health care access. OBJECTIVE: This study aims to assess the association between traffic density and recurrence of asthma ED visits in the primarily low income Medicaid population in New York State (NYS) between 2005 and 2015. METHODS: The primary outcome of interest was a recurrent asthma ED visit within 1-year of index visit. Traffic densities (weighted for truck traffic) were spatially linked based on home addresses. Bivariate and multivariate logistic regression analyses were conducted to identify factors predicting recurrent asthma ED visits. RESULTS: In a multivariate model, Medicaid recipients living within 300-m of a high traffic density area were at a statistically significant risk of a recurrent asthma ED visit compared to those in a low traffic density area (OR = 1.31; 95% CI:1.24,1.38). Additionally, we evaluated effect measure modification for risk of recurrent asthma visits associated with traffic exposure by socio-demographic factors. The highest risk was found for those exposed to high traffic and being male (OR = 1.87; 95% CI:1.46,2.39), receiving cash assistance (OR = 2.11; 95% CI:1.65,2.72), receiving supplemental security income (OR = 2.21; 95% CI:1.66,2.96) and being in the 18.44 age group (OR = 1.59;95% CI 1.48,1.70) was associated with the highest risk of recurrent asthma ED visit. Black non-Hispanics (OR = 2.35; 95% CI:1.70,3.24), Hispanics (OR = 2.13; 95% CI:1.49,3.04) and those with race listed as "Other" (OR = 1.89 95% CI:1.13,3.16) in high traffic areas had higher risk of recurrent asthma ED visits as compared to White non-Hispanics in low traffic areas. CONCLUSION: We observed significant persistent disparities in asthma morbidity related to traffic exposure and race/ethnicity in a low-income population. Our findings suggest that even within a primarily low-income study population, socioeconomic differences persist. These differences in susceptibility in the extremely low-income group may not be apparent in health studies that use Medicaid enrollment as a proxy for low SES.

Access to cardiac surgery centers for cardiac and non-cardiac hospitalizations in adolescents and adults with congenital heart defects- a descriptive case series study.

BACKGROUND: Individuals with congenital heart defects (CHDs) are recommended to receive all inpatient cardiac and noncardiac care at facilities that can offer specialized care. We describe geographic accessibility to such centers in New York State and determine several factors associated with receiving care there. METHODS: We used inpatient hospitalization data from the Statewide Planning and Research Cooperative System (SPARCS) in New York State 2008-2013. In the absence of specific adult CHD care center designations during our study period, we identified pediatric/adult and adult-only cardiac surgery centers through the Cardiac Surgery Reporting System to estimate age-based specialized care. We calculated one-way drive and public transit time (in minutes) from residential address to centers using R gmapsdistance package and the Google Maps Distance Application Programming Interface (API). We calculated prevalence ratios using modified Poisson regression with model-based standard errors, fit with generalized estimating equations clustered at the hospital level and subclustered at the individual level. RESULTS: Individuals with CHDs were more likely to seek care at pediatric/adult or adult-only cardiac surgery centers if they had severe CHDs, private health insurance, higher severity of illness at encounter, a surgical procedure, cardiac encounter, and shorter drive time. These findings can be used to increase care receipt (especially for noncardiac care) at pediatric/adult or adult-only cardiac surgery centers, identify areas with limited access, and reduce disparities in access to specialized care among this high-risk population.

Using social security number to identify sub-populations vulnerable to the health impacts from extreme heat in Florida, U.S.

BACKGROUND: Some socioeconomically vulnerable groups may experience disproportionately higher risk of extreme heat illness than other groups, but no study has utilized the presence/absence of a social security number (SSN) as a proxy for vulnerable sub-populations. METHODS: This study focused on the warm season from 2008 to 2012 in Florida, U.S. With a total number of 8,256,171 individual level health outcomes, we devised separate case-crossover models for five heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease), type of health care visit (emergency department (ED) and hospitalization), and patients reporting/not reporting an SSN. Each stratified model also considered potential effect modification by sex, age, or race/ethnicity. RESULTS: Mean temperature raised the odds of five heat-sensitive health outcomes with the highest odds ratios (ORs) for heat-related illness. Sex significantly modified heat exposure effects for dehydration ED visits (Males: 1.145, 95 % CI: 1.137-1.153; Females: 1.110, 95 % CI: 1.103-1.117) and hospitalization (Males: 1.116, 95 % CI: 1.110-1.121; Females: 1.100, 95 % CI: 1.095-1.105). Patients not reporting an SSN between 25 and 44 years (1.264, 95 % CI: 1.192-1.340) exhibited significantly higher dehydration ED ORs than those reporting an SSN (1.146, 95 % CI: 1.136-1.157). We also observed significantly higher ORs for cardiovascular disease hospitalization from the no SSN group (SSN: 1.089, 95 % CI: 1.088-1.090; no SSN: 1.100, 95 % CI: 1.091-1.110). CONCLUSIONS: This paper partially supports the idea that individuals without an SSN could experience higher risks of dehydration (for those 25-45 years), renal disease, and cardiovascular disease than those with an SSN.

Short-term PM2.5 and cardiovascular admissions in NY State: assessing sensitivity to exposure model choice.

BACKGROUND: Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model. METHODS: We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM2.5) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM2.5 dataset. RESULTS: For all PM2.5 datasets, we observed positive associations between PM2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m3 increase in daily PM2.5. We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available. CONCLUSIONS: Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM2.5 and CVD admissions, regardless of model choice.

Maternal occupational exposure to polycyclic aromatic hydrocarbons and the risk of isolated congenital heart defects among offspring.

BACKGROUND: Although there is evidence in experimental model systems that exposure to polycyclic aromatic hydrocarbons (PAHs) is linked with congenital heart defects (CHDs), few studies have examined the association in humans. We conducted a case-control study to examine the association between maternal exposure to PAHs and CHDs in offspring using data from the National Birth Defects Prevention Study (NBDPS) (1997-2011). METHODS: We obtained detailed information on maternal occupation during the month before to three months after conception. Expert raters, masked to case-control status, assessed job descriptions to assign categorical levels of exposure. Categories were quantitatively mapped to estimate cumulative exposure to PAHs, incorporating exposure intensity, frequency, work duration, and work hours. Quartiles were generated for cumulative maternal exposure to PAHs. Crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using unconditional logistic regression for quartiles of PAH exposure and six CHD groupings (e.g. conotruncal) and specific subtypes (e.g. tetralogy of Fallot [ToF]). Final models were adjusted for maternal age, race/ethnicity, education, smoking, anticonvulsant use, folic acid supplementation, and study center. RESULTS: There were 4,775 case and 7,734 control infants eligible for the study. The prevalence of occupational exposure to PAHs was 10.2% among both case and control mothers. In adjusted analysis, compared to mothers with no occupational PAH exposure, those in the highest quartile of exposure were more likely to have offspring in the conotruncal heart defects group (OR 1.41; 95% CI 1.00-2.00), and with ToF (OR 1.83; 95% CI 1.21-2.78). CONCLUSIONS: Women in the highest quartile of estimated cumulative occupational PAH exposure during early pregnancy were more likely to have offspring with conotruncal heart defects, specifically ToF, compared to women with no occupational PAH exposure. Other comparisons between PAHs and other CHDs subgroups did not show any statistically precise associations.

Proximity to risk-appropriate perinatal hospitals for pregnant women with congenital heart defects in New York state.

BACKGROUND: Women with congenital heart defects (CHDs) experiencing pregnancies require specialized delivery care and extensive monitoring that may not be available at all birthing hospitals. In this study, we examined proximity to, and delivery at, a hospital with an appropriate level of perinatal care for pregnant women with CHDs and evaluated predictors of high travel distance to appropriate care. Appropriate care was defined as Level 3 perinatal hospitals and Regional Perinatal Centers (RPCs). METHODS: Inpatient delivery records for women with CHD in New York State (NYS) between 2008 and 2013 were obtained. Driving time and transit time were calculated between the pregnant woman's residence and the actual delivery hospital as well as the closest Level 3 or RPC hospital using Geographic Information Systems (GIS). Linear and logistic regression models evaluated predictors of high distance to, and utilization of, appropriate delivery care respectively. RESULTS: From 2008 to 2013, there were 909 deliveries in a NYS hospital by women with CHDs. Approximately 75% of women delivered at a Level 3 or RPC hospital. Younger women, those who reside in rural and smaller urban areas, and those who are non-Hispanic White had a greater drive time to an appropriate care facility. After adjustment for geographic differences, racial/ethnic minorities and poor women were less likely to deliver at an appropriate delivery care center. CONCLUSIONS: Although most women with CHDs in NYS receive appropriate delivery care, there are some geographic and socio-demographic differences that require attention to ensure equitable access.

Prenatal and early life exposures to ambient air pollution and development.

BACKGROUND: Residential proximity to major roadways, and prenatal exposures to particulate matter <2.5 µm (PM2.5) and ozone (O3) are linked to poor fetal outcomes but their relationship with childhood development is unclear. OBJECTIVES: We investigated whether proximity to major roadways, or prenatal and early-life exposures to PM2.5 and O3 increase the risk of early developmental delays. STUDY DESIGN: Prospective cohort. SETTINGS: New York State excluding New York City. PARTICIPANTS: 4089 singletons and 1016 twins born between 2008 and 2010. EXPOSURES: Proximity to major roadway was calculated using road network data from the NY Department of Transportation. Concentrations of PM2.5 and O3 estimated by the Environmental Protection Agency Downscaler models were spatiotemporally linked to each child's prenatal and early-life addresses incorporating residential history, and locations of maternal work and day-care. OUTCOMES: Parents reported their children's development at ages 8, 12, 18, 24, 30 and 36 months in five domains using the Ages and Stages Questionnaire. Generalized mixed models estimated the relative risk (RR) and 95% CI for failing any developmental domain per 10 units increase in PM2.5 and O3, and for those living <1000 m away from a major roadway compared to those living further. Models adjusted for potential confounders. RESULTS: Compared to those >1000 m away from a major roadway, those resided 50-100 m [RR: 2.12 (1.00-4.52)] and 100-500 m [RR: 2.07 (1.02-4.22)] away had twice the risk of failing the communication domain. Prenatal exposures to both PM2.5 and ozone during various pregnancy windows had weak but significant associations with failing any developmental domain with effects ranging from 1.6% to 2.7% for a 10 µg/m3 increase in PM2.5 and 0.7%-1.7% for a 10 ppb increase in ozone. Average daily postnatal ozone exposure was positively associated with failing the overall screening by 8 months [3.3% (1.1%-5.5%)], 12 months [17.7% (10.4%-25.5%)], and 30 months [7.6%, (1.3%-14.3%)]. Findings were mixed for postnatal PM2.5 exposures. CONCLUSIONS: In this prospective cohort study, proximity to major roadway and prenatal/early-life exposures to PM2.5 and O3 were associated with developmental delays. While awaiting larger studies with personal air pollution assessment, efforts to minimize air pollution exposures during critical developmental windows may be warranted.

Estimating policy-relevant health effects of ambient heat exposures using spatially contiguous reanalysis data.

BACKGROUND: Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes. METHODS: We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (Tmax) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression. RESULTS: We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in Tmax on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria. CONCLUSION: Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Identifying areas at risk of low birth weight using spatial epidemiology: A small area surveillance study.

OBJECTIVES: To assess the geographic distribution of Low Birth Weight (LBW) in New York State among singleton births using a spatial regression approach in order to identify priority areas for public health actions. METHODS: LBW was defined as birth weight less than 2500g. Geocoded data from 562,586 birth certificates in New York State (years 2008-2012) were merged with 2010 census data at the tract level. To provide stable estimates and maintain confidentiality, data were aggregated to yield 1268 areas of analysis. LBW prevalence among singleton births was related with area-level behavioral, socioeconomic and demographic characteristics using a Poisson mixed effects spatial error regression model. RESULTS: Observed low birth weight showed statistically significant auto-correlation in our study area (Moran's I 0.16 p value 0.0005). After over-dispersion correction and accounting for fixed effects for selected social determinants, spatial autocorrelation was fully accounted for (Moran's I-0.007 p value 0.241). The proportion of LBW was higher in areas with larger Hispanic or Black populations and high smoking prevalence. Smoothed maps with predicted prevalence were developed to identify areas at high risk of LBW. Spatial patterns of residual variation were analyzed to identify unique risk factors. CONCLUSION: Neighborhood racial composition contributes to disparities in LBW prevalence beyond differences in behavioral and socioeconomic factors. Small-area analyses of LBW can identify areas for targeted interventions and display unique local patterns that should be accounted for in prevention strategies.

Assessing the impact of fine particulate matter (PM2.5) on respiratory-cardiovascular chronic diseases in the New York City Metropolitan area using Hierarchical Bayesian Model estimates.

An enhanced research paradigm is presented to address the spatial and temporal gaps in fine particulate matter (PM2.5) measurements and generate realistic and representative concentration fields for use in epidemiological studies of human exposure to ambient air particulate concentrations. The general approach for research designed to analyze health impacts of exposure to PM2.5 is to use concentration data from the nearest ground-based air quality monitor(s), which typically have missing data on the temporal and spatial scales due to filter sampling schedules and monitor placement, respectively. To circumvent these data gaps, this research project uses a Hierarchical Bayesian Model (HBM) to generate estimates of PM2.5 in areas with and without air quality monitors by combining PM2.5 concentrations measured by monitors, PM2.5 concentration estimates derived from satellite aerosol optical depth (AOD) data, and Community-Multiscale Air Quality (CMAQ) model predictions of PM2.5 concentrations. This methodology represents a substantial step forward in the approach for developing representative PM2.5 concentration datasets to correlate with inpatient hospitalizations and emergency room visits data for asthma and inpatient hospitalizations for myocardial infarction (MI) and heart failure (HF) using case-crossover analysis. There were two key objective of this current study. First was to show that the inputs to the HBM could be expanded to include AOD data in addition to data from PM2.5 monitors and predictions from CMAQ. The second objective was to determine if inclusion of AOD surfaces in HBM model algorithms results in PM2.5 air pollutant concentration surfaces which more accurately predict hospital admittance and emergency room visits for MI, asthma, and HF. This study focuses on the New York City, NY metropolitan and surrounding areas during the 2004-2006 time period, in order to compare the health outcome impacts with those from previous studies and focus on any benefits derived from the changes in the HBM model surfaces. Consistent with previous studies, the results show high PM2.5 exposure is associated with increased risk of asthma, myocardial infarction and heart failure. The estimates derived from concentration surfaces that incorporate AOD had a similar model fit and estimate of risk as compared to those derived from combining monitor and CMAQ data alone. Thus, this study demonstrates that estimates of PM2.5 concentrations from satellite data can be used to supplement PM2.5 monitor data in the estimates of risk associated with three common health outcomes. Results from this study were inconclusive regarding the potential benefits derived from adding AOD data to the HBM, as the addition of the satellite data did not significantly increase model performance. However, this study was limited to one metropolitan area over a short two-year time period. The use of next-generation, high temporal and spatial resolution satellite AOD data from geostationary and polar-orbiting satellites is expected to improve predictions in epidemiological studies in areas with fewer pollutant monitors or over wider geographic areas.

Lifecourse socioeconomic position and 16 year body mass index trajectories: differences by race and sex.

OBJECTIVE: The aim of this study is to evaluate the association between lifecourse socioeconomic position (SEP) and changes in body mass index (BMI), and assess disparities in these associations across racial/ethnic groups. METHODS: With longitudinal data from 4 waves of the Americans' Changing Lives Study (1986-2002), we employed mixed-effects modeling to estimate BMI trajectories for 1174 Blacks and 2323 White adults. We also estimated associations between these trajectories and lifecourse SEP variables, including father's education, perceived childhood SEP, own education, income, wealth, and financial security. RESULTS: Blacks had higher baseline BMIs, and steeper increases in BMI, compared to Whites. Childhood SEP, as measured by high father's education, was associated with lower baseline BMI among Whites. High education was associated with a lower baseline BMI within both race and sex categories. Income had contrasting effects among men and women. Higher income was associated with higher BMI only among males. Associations between indicators of SEP and BMI trajectories were only found for Whites. CONCLUSIONS: Our study demonstrates that lifecourse SEP may influence adult BMI differently within different racial and sex groups.

Racial and Ethnic Disparities in Robot-Assisted Radical Prostatectomy: Testing the Physician-level Segregated and Differential Treatment Hypotheses.

BACKGROUND: Mechanisms underlying racial and ethnic disparities in robot-assisted radical prostatectomy (RARP) vs open radical prostatectomy (ORP) are unclear. We sought to test two physician-level hypotheses: (1)-Segregated Treatment and (2)-Differential Treatment. METHODS: This observational study used the New York State Cancer Registry linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer during 10/1/2008-12/31/2018. For hypothesis-(1), we examined the association between patient race and ethnicity and treating surgeon RARP use (high-use surgeons, low-use surgeons, and surgeons at non-RARP facilities). For hypothesis-(2), we determined the association between patient race and ethnicity and receipt of RARP when matching on treating surgeon, age, year of procedure, and Gleason group. We explored the role of insurance in both analyses. RESULTS: This study included 18,926 patients (8.0% Hispanic, 16.9% non-Hispanic Black, 75.1% non-Hispanic White), with a mean age of 60.4 ± 7.1 years. Compared with non-Hispanic White patients, Hispanic and non-Hispanic Black patients had higher odds of being treated by low-RARP-use surgeons (OR[95% CI]: 2.16[1.20-3.88] and 1.76[1.06-2.94], respectively) and by surgeons at non-RARP facilities (OR[95% CI]: 4.19[2.18-8.07] and 4.60[2.58-8.23], respectively). In the matched cohorts, Hispanic and non-Hispanic Black patients were less likely to receive RARP than non-Hispanic White patients (OR[95% CI]: 0.78[0.62-0.98] and 0.75[0.57-1.00], respectively). These associations were partially attenuated after accounting for insurance. CONCLUSIONS: Racial and ethnic disparities in RARP use are related to patients being treated by different surgeons and treated differently by the same surgeons. Identifying and addressing multilevel barriers to equitable surgical treatment is needed to reduce disparities among prostate cancer patients.

Reporting tumor genomic test results to SEER registries via linkages.

BACKGROUND: Precision medicine has become a mainstay of cancer care in recent years. The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program has been an authoritative source of cancer statistics and data since 1973. However, tumor genomic information has not been adequately captured in the cancer surveillance data, which impedes population-based research on molecular subtypes. To address this, the SEER Program has developed and implemented a centralized process to link SEER registries' tumor cases with genomic test results that are provided by molecular laboratories to the registries. METHODS: Data linkages were carried out following operating procedures for centralized linkages established by the SEER Program. The linkages used Match*Pro, a probabilistic linkage software, and were facilitated by the registries' trusted third party (an honest broker). The SEER registries provide to NCI limited datasets that undergo preliminary evaluation prior to their release to the research community. RESULTS: Recently conducted genomic linkages included OncotypeDX Breast Recurrence Score, OncotypeDX Breast Ductal Carcinoma in Situ, OncotypeDX Genomic Prostate Score, Decipher Prostate Genomic Classifier, DecisionDX Uveal Melanoma, DecisionDX Preferentially Expressed Antigen in Melanoma, DecisionDX Melanoma, and germline tests results in Georgia and California SEER registries. CONCLUSIONS: The linkages of cancer cases from SEER registries with genomic test results obtained from molecular laboratories offer an effective approach for data collection in cancer surveillance. By providing de-identified data to the research community, the NCI's SEER Program enables scientists to investigate numerous research inquiries.