Do respiratory virus infections modify associations of asthma exacerbation with aeroallergens or fine particulate matter? A time series study in Philadelphia PA.

Respiratory virus infections are related to over 80% of childhood asthma exacerbations. They enhance pro-inflammatory mediator release, especially for sensitized individuals exposed to pollens/molds. Using a time-series study design, we investigated possible effect modification by respiratory virus infections of the associations between aeroallergens/PM2.5 and asthma exacerbation rates. Outpatient, emergency department (ED), and inpatient visits for asthma exacerbation among children with asthma (28,540/24,444 [warm/cold season]), as well as viral infection counts were obtained from electronic health records of the Children's Hospital of Philadelphia from 2011 to 2016. Rate ratios (RRs, 90th percentile vs. 0) for late-season grass pollen were 1.00 (0.85-1.17), 1.04 (0.95-1.15), and 1.12 (0.96-1.32), respectively, for respiratory syncytial virus (RSV) counts within each tertile. However, similar trends were not observed for weed pollens/molds or PM2.5. Overall, our study provides little evidence supporting effect modification by respiratory viral infections.

Improving Stroke Measure Compliance and Outcomes Through Hospital Collaboration.

Globally, national stroke registries have been shown to improve the quality of patient care and outcomes. However, registry utilization and implementation vary by country. In the United States, stroke-specific performance measures must be met to achieve and maintain stroke center certification awarded by the state or nationally accredited certifying bodies. The 2 stroke registries available in the United States are the American Heart Association Get With The Guidelines-Stroke registry, which is voluntary, and the Paul Coverdell National Acute Stroke Registry, funded competitively to states by the Centers for Disease Control and Prevention. Compliance with stroke processes of care is variable, and quality improvement initiatives among organizations have been shown to have an impact on improving stroke care delivery. However, the effectiveness of interorganizational continuous quality improvement approaches, especially among competing institutions, to improving stroke care is ambiguous, and no uniform governance for successful interhospital collaboration has been identified. The purpose of this article is to review national initiatives focused on interorganizational collaboration to improve stroke care delivery with a focus on interhospital collaboration in the United States to improve stroke performance measures specific to stroke center certification. The state of Kentucky's experience and utilization of the Institute for Healthcare Improvement Breakthrough Series model with key strategies for success will be discussed to serve as a foundation and empower novice stroke leaders in learning health systems. The models may be adapted internationally for application to stroke-specific care process improvement locally, regionally, and nationally; among organizations within the same health system or competing systems; and among organizations with funding or without funding to improve stroke performance measures.

Cumulative Experience of Neighborhood Walkability and Change in Weight and Waist Circumference in REGARDS.

Neighborhood walkability-features of the built environment that promote pedestrian activity-has been associated with greater physical activity and lower body mass index (BMI; calculated as weight (kg)/height (m)2) among neighborhood residents. However, much of the literature has been cross-sectional and only a few cohort studies have assessed neighborhood features throughout follow-up. Using data from the Reasons for Geographic and Racial Differences in Stroke Study (2003-2016) and a neighborhood walkability index (NWI) measured annually during follow-up, we assessed whether the cumulative experience of neighborhood walkability (NWI-years) predicted BMI and waist circumference after approximately 10 years of follow-up, controlling for these anthropometric measures at enrollment. Analyses were adjusted for individual-level sociodemographic covariates and the cumulative experience of neighborhood poverty rate and neighborhood greenspace coverage. Almost a third (29%) of participants changed address at least once during follow-up. The first change of residence, on average, brought the participants to neighborhoods with higher home values and lower NWI scores than their originating neighborhoods. Compared with those having experienced the lowest quartile of cumulative NWI-years, those who experienced the highest quartile had 0.83 lower BMI (95% confidence interval, -1.5, -0.16) and 1.07-cm smaller waist circumference (95% confidence interval, -1.96, -0.19) at follow-up. These analyses provide additional longitudinal evidence that residential neighborhood features that support pedestrian activity are associated with lower adiposity.

Improved survival in myeloma patients-a nationwide registry study of 4,647 patients ≥75 years treated in Denmark and Sweden.

The prevalence of multiple myeloma (MM) is increasing in Nordic countries and the rest of the western world. Patients aged ≥75 years at diagnosis constitute an increasing proportion of all MM patients, but are underrepresented in randomized clinical trials. There is an urgent need for studies of the characteristics, treatment and outcome in this cohort. We present data from two nationwide population-based registries of all MM patients diagnosed in Denmark from January 1, 2005 until February 18, 2020, and in Sweden from January 1, 2008 until December 31, 2019, including treatment data for patients diagnosed until 2018 (Denmark) and 2019 (Sweden). In total 4,647 patients were ≥75 years at diagnosis, compared to 7,378 younger patients. Patients ≥75 years, accounting for approximately 40% of all MM patients, are a distinct cohort with more advanced disease at diagnosis, reflected by higher International Staging System (ISS) stage, and a higher proportion have renal failure and anemia. We found a more gradual introduction of modern medications in the older cohort than in the younger, despite simultaneous changes in guidelines. Compared to the cohorts in randomized controlled trials that guide the treatment of non-transplant eligible patients, we found a higher proportion of patients ≥75 years and presenting with ISS III in the real-world populations. Nevertheless, response rates and survival are increasing, indicating that modern treatment regimens are effective and well tolerated also in elderly MM patients in real-world populations.

Spatial Inequities in Life Expectancy in Small Areas of Buenos Aires, Argentina 2015-2017.

Studies of life expectancy (LE) in small areas of cities are relatively common in high-income countries but rare in Latin American countries. Small-area estimation methods can help to describe and quantify inequities in LE between neighborhoods and their predictors. Our objective was to analyze the distribution and spatial patterning of LE across small areas of Ciudad Autónoma de Buenos Aires (CABA), Argentina, and its association with socioeconomic characteristics. As part of the SALURBAL project, we used georeferenced death certificates in 2015-2017 for CABA, Argentina. We used a spatial Bayesian Poisson model using the TOPALS method to estimate age- and sex-specific mortality rates. We used life tables to estimate LE at birth. We obtained data on neighborhood socioeconomic characteristics from the 2010 census and analyzed their associations. LE at birth was higher for women (median of across neighborhoods = 81.1 years) compared to men (76.7 years). We found a gap in LE of 9.3 (women) and 14.9 years (men) between areas with the highest and the lowest LE. Better socioeconomic characteristics were associated with higher LE. For example, mean differences in LE at birth in areas with highest versus lowest values of composite SES index were 2.79 years (95% CI: 2.30 to 3.28) in women and 5.61 years (95% CI: 4.98 to 6.24) in men. We found large spatial inequities in LE across neighborhoods of a large city in Latin America, highlighting the importance of place-based policies to address this gap.

Evaluation of evidence for interaction between PM2.5 and aeroallergens on childhood asthma exacerbation in Philadelphia, PA, 2011 to 2016.

Fine particulate matter (PM2.5) and aeroallergens (i.e., pollen, molds) are known triggers of asthma exacerbation. Despite mechanistic evidence suggesting synergistic effects between PM2.5 and asthma exacerbation, little epidemiologic work has been performed in children, which has exhibited inconsistency. We conducted a time-series study to explore their interactions using electronic health records (EHR) data in Philadelphia, PA, for asthma diagnoses in outpatient, emergency department [ED], and inpatient settings. Daily asthma exacerbation cases (28,540 asthma exacerbation case encounters) were linked to daily ambient PM2.5 and daily aeroallergen levels during the aeroallergen season of a six-year period (mid-March to October 2011-2016). Asthma exacerbation counts were modeled using quasi-Poisson regression, where PM2.5 and aeroallergens were fitted with distributed lag non-linear functions (lagged from 0 to 14-days), respectively, when modeled as the primary exposure variables. Regression models were adjusted for mean daily temperature/relative humidity, long-term and seasonal trends, day-of-week, and major U.S. holidays. Increasing gradient of RR estimates were observed for only a few primary exposure risk factors [PM2.5 (90th vs. 5th percentile)/aeroallergens (90th percentile vs. 0)], across different levels of effect modifiers. For example, RRs for the association between late-season grass pollen (lag1) and asthma exacerbation were higher at higher levels of PM2.5, 5-days preceding the exacerbation event (low PM2.5: RR = 1.01, 95% CI: 0.93-1.09; medium PM2.5: 1.04, 95% CI: 0.96-1.12; high PM2.5: 1.09, 95% CI: 1.01-1.19). However, most of the highest RRs for aeroallergens were instead observed for days with low- or medium- PM2.5 levels; likewise, when PM2.5 was modeled as the primary exposure with aeroallergens as the effect modifier. Most of the RR estimates did not exhibit gradients that suggested synergism, and were of relatively high imprecision. Overall, our study suggested no evidence for interactions between PM2.5 and aeroallergens in their relationships with childhood asthma exacerbation.

National trends and disparities in retail food environments in the USA between 1990 and 2014.

OBJECTIVE: To describe national disparities in retail food environments by neighbourhood composition (race/ethnicity and socio-economic status) across time and space. DESIGN: We examined built food environments (retail outlets) between 1990 and 2014 for census tracts in the contiguous USA (n 71 547). We measured retail food environment as counts of all food stores, all unhealthy food sources (including fast food, convenience stores, bakeries and ice cream) and healthy food stores (including supermarkets, fruit and vegetable markets) from National Establishment Time Series business data. Changes in food environment were mapped to display spatial patterns. Multi-level Poisson models, clustered by tract, estimated time trends in counts of food stores with a land area offset and independent variables population density, racial composition (categorised as predominantly one race/ethnicity (>60 %) or mixed), and inflation-adjusted income tertile. SETTING: The contiguous USA between 1990 and 2014. PARTICIPANTS: All census tracts (n 71 547). RESULTS: All food stores and unhealthy food sources increased, while the subcategory healthy food remained relatively stable. In models adjusting for population density, predominantly non-Hispanic Black, Hispanic, Asian and mixed tracts had significantly more destinations of all food categories than predominantly non-Hispanic White tracts. This disparity increased over time, predominantly driven by larger increases in unhealthy food sources for tracts which were not predominantly non-Hispanic White. Income and food store access were inversely related, although disparities narrowed over time. CONCLUSIONS: Our findings illustrate a national food landscape with both persistent and shifting spatial patterns in the availability of establishments across neighbourhoods with different racial/ethnic and socio-economic compositions.

Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice.

BACKGROUND: Missed appointments diminish the continuity and quality of care. OBJECTIVE: To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside. DESIGN: Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient's census tract of residence. PATIENTS: A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014-2015 at a multispecialty outpatient practice. MAIN MEASURES: We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients' census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients' age, gender, type of insurance, and type of clinic service. KEY RESULTS: Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety. CONCLUSIONS: Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care.

Does Living near Trees and Other Vegetation Affect the Contemporaneous Odds of Asthma Exacerbation among Pediatric Asthma Patients?

Vegetation may influence asthma exacerbation through effects on aeroallergens, localized climates, air pollution, or children's behaviors and stress levels. We investigated the association between residential vegetation and asthma exacerbation by conducting a matched case-control study based on electronic health records of asthma patients, from the Children's Hospital of Philadelphia (CHOP). Our study included 17,639 exacerbation case events and 34,681 controls selected from non-exacerbation clinical visits for asthma, matched to cases by age, sex, race/ethnicity, public payment source, and residential proximity to the CHOP main campus ED and hospital. Overall greenness, tree canopy, grass/shrub cover, and impervious surface were assessed near children's homes (250 m) using satellite imagery and high-resolution landcover data. We used generalized estimating equations to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between each vegetation/landcover measure and asthma exacerbation, with adjustment for seasonal and sociodemographic factors-for all cases, and for cases defined by diagnosis setting and exacerbation frequency. Lower odds of asthma exacerbation were observed in association with greater levels of tree canopy near the home, but only for children who experienced multiple exacerbations in a year (OR = 0.94 per 10.2% greater tree canopy coverage, 95% CI = 0.90-0.99). Our findings suggest possible protection for asthma patients from tree canopy, but differing results by case frequency suggest that potential benefits may be specific to certain subpopulations of asthmatic children.

Are Women's Empowerment and Income Inequality Associated with Excess Weight in Latin American Cities?

While income gradients and gender inequalities in excess weight have been noted elsewhere, data from Latin American cities is lacking. We analyzed gender-specific associations between city-level women's empowerment and income inequality with individual-level overweight/obesity, assessing how these associations vary by individual education or living conditions within cities in Latin America. Data came from national surveys and censuses, and was compiled by the SALURBAL project (Urban Health in Latin America). The sample included 79,422 individuals (58.0% women), living in 538 sub-cities, 187 cities, and 8 countries. We used gender-stratified Poisson multilevel models to estimate the Prevalence Rate Ratios (PRR) for overweight/obesity (body mass index ≥ 25 kg/m2) per a unit change in city-level women's empowerment (proxied by a score that measures gender inequalities in employment and education) and income inequality (proxied by income-based Gini coefficient). We also tested whether individual education or sub-city living conditions modified such associations. Higher city labor women's empowerment (in women) and higher city Gini coefficient (in men) were associated with a lower prevalence of overweight/obesity (PRR = 0.97 (95%CI 0.94, 0.99) and PRR = 0.94 (95%CI 0.90, 0.97), respectively). The associations varied by individual education and sub-city living conditions. For labor women's empowerment, we observed weakened associations towards the null effect in women with lower education and in residents of sub-cities with worse living conditions (men and women). For the Gini coefficient, the association was stronger among men with primary education, and a negative association was observed in women with primary education. Our findings highlight the need for promoting equity-based policies and interventions to tackle the high prevalence of excess weight in Latin American cities.

Associations between high ambient temperatures and asthma exacerbation among children in Philadelphia, PA: a time series analysis.

OBJECTIVES: High ambient temperatures may contribute to acute asthma exacerbation, a leading cause of morbidity in children. We quantified associations between hot-season ambient temperatures and asthma exacerbation in children ages 0-18 years in Philadelphia, PA. METHODS: We created a time series of daily counts of clinical encounters for asthma exacerbation at the Children's Hospital of Philadelphia linked with daily meteorological data, June-August of 2011-2016. We estimated associations between mean daily temperature (up to a 5-day lag) and asthma exacerbation using generalised quasi-Poisson distributed models, adjusted for seasonal and long-term trends, day of the week, mean relative humidity,and US holiday. In secondary analyses, we ran models with adjustment for aeroallergens, air pollutants and respiratory virus counts. We quantified overall associations, and estimates stratified by encounter location (outpatient, emergency department, inpatient), sociodemographics and comorbidities. RESULTS: The analysis included 7637 asthma exacerbation events. High mean daily temperatures that occurred 5 days before the index date were associated with higher rates of exacerbation (rate ratio (RR) comparing 33°C-13.1°C days: 1.37, 95% CI 1.04 to 1.82). Associations were most substantial for children ages 2 to <5 years and for Hispanic and non-Hispanic black children. Adjustment for air pollutants, aeroallergens and respiratory virus counts did not substantially change RR estimates. CONCLUSIONS: This research contributes to evidence that ambient heat is associated with higher rates of asthma exacerbation in children. Further work is needed to explore the mechanisms underlying these associations.

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts. METHODS: We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers. RESULTS: Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers. CONCLUSION: This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Is city-level travel time by car associated with individual obesity or diabetes in Latin American cities? Evidence from 178 cities in the SALURBAL project.

There is growing evidence that longer travel time by private car poses physical and mental risks. Individual-level obesity and diabetes, two of the main public health challenges in low- and middle-income contexts, could be associated to city-level travel times by car. We used individual obesity and diabetes data from national health surveys from individuals in 178 Latin American cities, compiled and harmonized by the SALURBAL project. We calculated city-level travel times by car using the Google Maps Distance Matrix API. We estimated associations between peak hour city-level travel time by car and obesity and diabetes using multilevel logistic regression models, while adjusting for individual characteristics and other city-level covariates. In our study we did not observe a relationship between city-level peak-hour travel time by car and individual obesity and diabetes, as reported in previous research for individual time spent in vehicles in high-income settings. Our results suggest that this relationship may be more complex in Latin America compared to other settings, especially considering that cities in the region are characterized by high degrees of population density and compactness and by a higher prevalence of walking and public transportation use.

Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology.

Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research.

Effects of ambient air pollution on childhood asthma exacerbation in the Philadelphia metropolitan Region, 2011-2014.

Fine particulate matter (PM2.5) and ozone (O3) air pollutants are known risk factors for asthma exacerbation. We studied the association of these air pollutants with pediatric asthma exacerbation in the Philadelphia metropolitan region, and evaluated potential effect modification by children's characteristics (e.g., race/ethnicity, atopic conditions) and environmental factors (e.g., neighborhood tree canopy, meteorological factors, aeroallergens). We conducted a time-stratified case-crossover study of 54,632 pediatric (age ≤18 years) asthma exacerbation cases occurring from 2011 to 2014, identified through electronic health records (EHR) of the Children's Hospital of Philadelphia (CHOP) health system. We applied conditional logistic regression to estimate associations between air pollution and asthma exacerbation, using daily census-tract level pollutant concentrations estimated from the EPA Fused Air Quality Surface Using Downscaling (FAQSD) files. The associations were estimated within warm (Apr-Sep) and cold (Oct-Mar) months for unlagged exposure and for cumulative effects up to 5 days after exposure, with adjustment for temperature, relative humidity, and holidays. We found small increases in odds of asthma exacerbation with higher pollutant concentrations, with positive associations (OR, comparing concentrations of 75th to 25th percentile) observed for PM2.5 during both warm (1.03, 95% CI: 0.98-1.08) and cold months (1.05, 95% CI: 1.02-1.07), and for O3 during cold months (1.08, 95% CI: 1.02-1.14). The exposure-response relationship with PM2.5 during the cold months was essentially linear, whereas thresholds of effect were observed for the other associations at low-medium pollutant concentrations. Results were robust to multi-pollutant modeling and adjustment for additional covariates. We found no effect modification by most children's characteristics, while effect sizes were higher on days with detected tree and grass pollens during warm months. Our results suggest that even small decreases in pollutant concentrations could potentially reduce risk of childhood asthma exacerbation - an important finding, given the high burden of childhood asthma and known disparities in asthma control.

Are neighbourhood restaurants related to frequency of restaurant meals and dietary quality? Prevalence and changes over time in the Multi-Ethnic Study of Atherosclerosis.

OBJECTIVE: To examine whether the density of neighbourhood restaurants affected the frequency of eating restaurant meals and subsequently affected diet quality. DESIGN: Cross-sectional and longitudinal designs. Structural equation models assessed the indirect relationship between restaurant density (≤3 miles (4·8 km) of participant addresses) and dietary quality (Healthy Eating Index 2010 (HEI)) via the frequency of eating restaurant meals, after adjustment for sociodemographics, select health conditions, region, residence duration and area-level income. SETTING: Urbanised areas in multiple regions of the USA, years 2000-2002 and 2010-2012. PARTICIPANTS: Participants aged 45-84 years were followed for 10 years (n 3567). RESULTS: Median HEI (out of 100) was fifty-nine at baseline and sixty-two at follow-up. The cross-sectional analysis found that residing in areas with a high density of restaurants (highest-ranked quartile) was associated with 52 % higher odds of frequently eating restaurant meals (≥3 times/week, OR: 1·52, 95 % CI 1·18, 1·98) and 3 % higher odds of having lower dietary quality (HEI lowest quartile < 54, OR: 1·03, 95 % CI 1·01, 1·06); associations were not sustained in longitudinal analyses. The cross-sectional analysis found 34 % higher odds of having lower dietary quality for those who frequently ate at restaurants (OR: 1·34, 95 % CI 1·12, 1·61), and more restaurant meals (over time increase ≥ 1 time/week) were associated with higher odds of having worse dietary quality at follow-up (OR: 1·21, 95 % CI 1·00, 1·46). CONCLUSIONS: Restaurant density was associated with frequently eating out in cross-sectional and longitudinal analyses but was associated with the lower dietary quality only in cross-sectional analyses. Frequent restaurant meals were negatively related to dietary quality. Interventions that encourage less frequent eating out may improve population dietary quality.

The Great Recession worsened blood pressure and blood glucose levels in American adults.

Longitudinal, individual-specific data from the Multi-Ethnic Study of Atherosclerosis (MESA) provide support for the hypothesis that the 2008 to 2010 Great Recession (GR) negatively impacted the health of US adults. Results further advance understanding of the relationship by (i) illuminating hypothesized greater negative impacts in population subgroups exposed to more severe impacts of the GR and (ii) explicitly controlling for confounding by individual differences in age-related changes in health over time. Analyses overcome limitations of prior work by (i) employing individual-level data that avoid concerns about ecological fallacy associated with prior reliance on group-level data, (ii) using four waves of data before the GR to estimate and control for underlying individual-level age-related trends, (iii) focusing on objective, temporally appropriate health outcomes rather than mortality, and (iv) leveraging a diverse cohort to investigate subgroup differences in the GR's impact. Innovative individual fixed-effects modeling controlling for individual-level age-related trajectories yielded substantively important insights: (i) significant elevations post-GR for blood pressure and fasting glucose, especially among those on medication pre-GR, and (ii) reductions in prevalence and intensity of medication use post-GR. Important differences in the effects of the GR are seen across subgroups, with larger effects among younger adults (who are likely still in the labor force) and older homeowners (whose declining home wealth likely reduced financial security, with less scope for recouping losses during their lifetime); least affected were older adults without a college degree (whose greater reliance on Medicare and Social Security likely provided more protection from the recession).

Constructing Within-City Neighborhood Health Rankings in Philadelphia by Using Data From the 500 Cities Project.

INTRODUCTION: Profound geographic disparities in health exist in many US cities. Most reporting on these disparities is based on predetermined administrative districts that may not reflect true neighborhoods. We undertook a ranking project to describe health at the neighborhood level and used Philadelphia, Pennsylvania, as our case study. METHODS: To create neighborhood health rankings, we first divided the city into neighborhoods according to groups of contiguous census tracts. Modeling our ranking methods and indicators on the Robert Wood Johnson Foundation County Health Rankings, we gathered census tract-level data from the Centers for Disease Control and Prevention's 500 Cities Project and local sources and aggregated these data, as needed, to each neighborhood. We assigned composite scores and rankings for both health outcomes and health factors to each neighborhood. RESULTS: Scores for health outcomes and health factors were highly correlated. We found clusters of neighborhoods with low rankings in Philadelphia's northern, lower northeastern, western, and southwestern regions. We disseminated information on rankings throughout the city, including through a comprehensive webpage, public communication, and a museum exhibit. CONCLUSION: The Philadelphia neighborhood health rankings were designed to be accessible to people unfamiliar with public health, facilitating education on drivers of health in communities. Our methods can be used as a model for other cities to create and communicate data on within-city geographic health disparities.

Trends in Tract-Level Prevalence of Obesity in Philadelphia by Race-Ethnicity, Space, and Time.

The growing recognition of often substantial neighborhood variation in health within cities has motivated greater demand for reliable data on small-scale variations in health outcomes. The goal of this article is to explore temporal changes in geographic disparities in obesity prevalence in the City of Philadelphia by race and sex over the period 2000-2015. Our data consist of self-reported survey responses of non-Hispanic whites, non-Hispanic blacks, and Hispanics from the Southeastern Pennsylvania Household Health Survey. To analyze these data-and to obtain more reliable estimates of the prevalence of obesity-we apply a Bayesian model that simultaneously accounts for spatial-, temporal-, and between-race/ethnicity dependence structures. This approach yields estimates of the obesity prevalence by age, race/ethnicity, sex, and poverty status for each census tract at all time-points in our study period. While the data suggest that the prevalence of obesity has increased at the city-level for men and women of all three race/ethnicities, the magnitude and geographic distribution of these increases differ substantially by race/ethnicity and sex. The method can be flexibly used to describe and visualize spatial heterogeneities in levels, trends, and in disparities. This is useful for targeting, surveillance, and etiologic research.

Reducing Cardiovascular Disparities Through Community-Engaged Implementation Research: A National Heart, Lung, and Blood Institute Workshop Report.

Cardiovascular disparities remain pervasive in the United States. Unequal disease burden is evident among population groups based on sex, race, ethnicity, socioeconomic status, educational attainment, nativity, or geography. Despite the significant declines in cardiovascular disease mortality rates in all demographic groups during the last 50 years, large disparities remain by sex, race, ethnicity, and geography. Recent data from modeling studies, linked micromap plots, and small-area analyses also demonstrate prominent variation in cardiovascular disease mortality rates across states and counties, with an especially high disease burden in the southeastern United States and Appalachia. Despite these continued disparities, few large-scale intervention studies have been conducted in these high-burden populations to examine the feasibility of reducing or eliminating cardiovascular disparities. To address this challenge, on June 22 and 23, 2017, the National Heart, Lung, and Blood Institute convened experts from a broad range of biomedical, behavioral, environmental, implementation, and social science backgrounds to summarize the current state of knowledge of cardiovascular disease disparities and propose intervention strategies aligned with the National Heart, Lung, and Blood Institute mission. This report presents the themes, challenges, opportunities, available resources, and recommended actions discussed at the workshop.