The Contribution Of Place To Disparities In Life Expectancy And Cardiovascular Outcomes

Socioeconomic disparities in health are well-documented, but the precise reasons for these disparities are poorly understood. Traditional explanations for health disparities focus on the influence of person-level disadvantages, such as those related to income, education, and health insurance status. However, the contribution of place to these health disparities is increasingly appreciated. By place , we refer to the sum of the environmental and community-level factors that may contribute to health, as distinguished from person-level disadvantages associated with low socioeconomic status (SES). These contextual factors can be categorized as 1) characteristics of the built environment (e.g. access to healthy food, space for exercise); 2) characteristics of the social environment (e.g. community norms regarding smoking, obesity, or treatment-seeking); and 3) direct psychosocial and physical stressors (e.g. pollution, crime). Such contextual factors may act independently of SES, they may mediate the effects of SES, and they may exhibit other complex relationships with SES and related factors such as income and education. Contextual factors may be modifiable, and are thus an important potential target for health policy and interventions aimed at reducing health disparities. To inform the design of such interventions, is it critical to demonstrate definitively that place is important, to identify which specific contextual factors matter, and to understand the mechanisms by which they affect health. There is currently little evidence in each of these areas. Isolating the contribution of any single environmental factor to health disparities is challenging. We have begun with a more fundamental question - to what extent does place matter in life expectancy and cardiovascular outcomes? Specifically, we sought to 1) characterize the contribution of place to life expectancy, by identifying geographic disparities in life expectancy that persist after adjusting for individual SES and race; 2) measure the effect of place - using neighborhood-level SES as a proxy - on outcomes after acute myocardial infarction (AMI); and 3) measure the relative effects of individual SES and place on delays to seeking treatment for AMI. A proposed conceptual model for these relationships is given below. We hypothesize that SES and place exhibit complex interactions. For example, the effect of a person\u27s SES on health may be modified by the context in which they live. Conversely, a person\u27s SES may modify any effects of place on health. There are a wide range of potential mechanisms for the effects of SES and place on health, which we summarize as being related to 1) direct environmental exposures (e.g. pollution, crime); 2) healthcare access and quality; and 3) health-related behaviors. Together, these factors would mediate the effect of SES and place on health outcomes and, subsequently, life expectancy. To thoroughly test this model would require a complete characterization of contextual exposures, which is outside the scope of this study. We instead limit our focus to shaded items in the diagram above. We first establish the plausibility of such a model by characterizing the association of SES and other contextual factors (i.e. place) with life expectancy. We then use acute myocardial infarction (AMI) as a model condition for measuring the contribution of SES and place to health-related behaviors and health outcomes. Our health-related behavior of interest is delay to hospital presentation in the setting of AMI. Our outcomes of interest include mortality, rehospitalization, and angina symptoms after AMI. In summary, our study aims include the following: 1) To characterize the contribution of place to life expectancy, by identifying geographic disparities in life expectancy that persist after adjusting for individual SES and race 2) To measure the effect of place - using neighborhood SES as a proxy - on outcomes after AMI 3) To measure the relative effects of individual SES and place on delays to seeking treatment for AMI. Aim 1: Characterizing the contribution of place to life expectancy We began at the macro-level, with the objective of understanding the reasons behind variation in life expectancy across the United States. This variation has been previously described, and previous studies have shown that SES is significantly associated with life expectancy at a regional level. Ours is the first study to quantify the degree to which differences in SES can account for geographic disparities in longevity nationwide. Using county as the unit of analysis, our results show that we find that SES does explain many of the striking geographic differences in life expectancy in the United States. This is consistent with traditional conceptions of health disparities as being primarily driven by socioeconomic factors. Yet despite the prevailing influence of SES, our results also reveal significant exceptions in which regional variation persists, or increases, after adjusting for SES. In particular, we identify several comparisons of areas which are virtually identical in terms of racial and SES composition, yet differ dramatically in terms of life expectancy. Based on such comparisons, along with the observation that disparities in life expectancy persist after controlling for SES, we conclude that contextual factors are important contributors to health disparities. In a secondary analysis, we applied the concept of deviance to identify places in which life expectancy is significantly higher or lower than what would be expected based on the race and SES composition of the population. Our results identified counties of significant positive and negative deviance. We conclude that the existence of these positive deviance areas - many of which have low SES, high minority populations - demonstrates that the disadvantages of SES are not insurmountable with respect to health outcomes. We further conclude that in-depth investigation of these positive deviance areas - and comparison with negative deviance areas of similar (race and SES) composition - may reveal characteristics of their environments that drive health disparities. Aim 2: Measuring the effect of place on outcomes after AMI Our second objective was to measure the independent contribution of place to outcomes after acute myocardial infarction (AMI). We employed neighborhood SES in an individual\u27s area of residence as a proxy for place. Neighborhood SES was measured as a composite of median household income and five other factors related to wealth, education, and occupation. Neighborhood SES has been previously linked with a range of cardiovascular risk factors and outcomes, including incidence of coronary heart disease. Importantly, these associations have been shown to persist after simultaneously adjusting for person-level SES (e.g. personal income, education, insurance status, and/or occupation). This suggests that neighborhood SES is not merely a proxy for individual-level SES, and that where one lives has an effect on cardiovascular health beyond that of one\u27s own resources. Using this framework, we performed an analysis among patients in the nationwide PREMIER registry, which includes 2321 patients with AMI from 19 US hospitals. Our results show that neighborhood SES is independently associated with the prevalence of angina and risk of rehospitalization in the 12 months after AMI. This association persists after accounting for individual SES variables, again demonstrating that context matters independent of a patient\u27s personal socioeconomic circumstances. The magnitude of this association is comparable to that of individual SES with outcomes. From this we conclude that context may be as important as personal resources in driving health disparities. Aim 3: Measuring the relative effects of individual SES and place on prehospital delays in AMI Having demonstrated an influence of neighborhood context on outcomes, there is a need for further studies to identify mechanisms underlying the effect of neighborhood on health. Such mechanisms may represent targets for public policy and interventions to reduce health disparities. These are summarized in the conceptual model above as involving 1) poorer health-related behaviors; 2) poorer healthcare access; or 3) the direct influence of psychosocial and environmental stressors on health. We focus on the first category, noting that features of both the physical environment (e.g. proximity to healthy food sources and space for exercise) and social environment (e.g. local norms and attitudes toward healthcare) may have a significant impact on health-related behaviors such as smoking, obesity, physical activity, and treatment-seeking, all of which could explain our above findings related to AMI outcomes. Specifically, our objective is to investigate whether place - again using neighborhood SES as a proxy - is related to delays in seeking treatment ( prehospital delays ) for AMI among patients in VIRGO, a nationwide AMI registry. Longer prehospital delays are associated with delayed revascularization, and thus can contribute to worse outcomes after AMI. Moreover, prehospital delays in AMI can be viewed as a marker for an individual\u27s propensity to seek medical care when in need, and as such serve as a proxy for overall healthcare-seeking behavior. VIRGO includes a high proportion of young and female patients with significant racial diversity. This diversity allows us to further investigate possible differences in the importance of neighborhood and person-level SES by race and sex. Our results show that both low neighborhood SES and low individual income are independently associated with delays of greater than 2 hours. Based on this observed relationship between neighborhood SES and delays, we conclude that context affects treatment-seeking in the setting of AMI. This association could in part mediate our observed effect of neighborhood on outcomes after AMI. Moreover, we find differential effects of SES variables according to race. Specifically, for black patients only individual-level SES, and not neighborhood SES, is a significant predictor of delays. Conversely, only neighborhood SES is a significant predictor of delays among non- blacks. From these observations, we conclude that different demographics have varying sensitivity to the influence of place on health-related behavior

The use of google trends in health care research: a systematic review.

BACKGROUND: Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research. METHODS AND FINDINGS: PRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ≥0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source. CONCLUSION: Google Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool

Most important outcomes research papers on stroke and transient ischemic attack

The following are highlights from the new series, Circulation: Cardiovascular Quality and Outcomes Topic Review. This series will summarize the most important manuscripts, as selected by the Editor, that have published in the Circulation portfolio. The objective of this new series is to provide our readership with a timely, comprehensive selection of important papers that are relevant to the quality and outcomes, and general cardiology audience. The studies included in this article represent the most significant research related to stroke and transient ischemic attack. (Circ Cardiovasc Quality and Outcomes. 2014; 7:191-204.

Disparities in donor heart acceptance between the USA and Europe:clinical implications

Background and Aims Given limited evidence and lack of consensus on donor acceptance for heart transplant (HT), selection practices vary widely Aims across HT centres in the USA. Similar variation likely exists on a broader scale—across countries and HT systems—but remains largely unexplored. This study characterized differences in heart donor populations and selection practices between the USA and Eurotransplant—a consortium of eight European countries—and their implications for system-wide outcomes. Methods Characteristics of adult reported heart donors and their utilization (the percentage of reported donors accepted for HT) were compared between Eurotransplant (n = 8714) and the USA (n = 60 882) from 2010 to 2020. Predictors of donor acceptance were identified using multivariable logistic regression. Additional analyses estimated the impact of achieving Eurotransplant-level utilization in the USA amongst donors of matched quality, using probability of acceptance as a marker of quality. Results Eurotransplant reported donors were older with more cardiovascular risk factors but with higher utilization than in the USA (70% vs. 44%). Donor age, smoking history, and diabetes mellitus predicted non-acceptance in the USA and, by a lesser magnitude, in Eurotransplant; donor obesity and hypertension predicted non-acceptance in the USA only. Achieving Eurotransplant-level utilization amongst the top 30%–50% of donors (by quality) would produce an additional 506–930 US HTs annually. Conclusions Eurotransplant countries exhibit more liberal donor heart acceptance practices than the USA. Adopting similar acceptance practices could help alleviate the scarcity of donor hearts and reduce waitlist morbidity in the USA.</p

Data from: Publication and reporting of clinical trial results: cross sectional analysis across academic medical centers

Objective: To determine rates of publication and reporting of results within two years for all completed clinical trials registered in ClinicalTrials.gov across leading academic medical centers in the United States. Design: Cross sectional analysis. Setting: Academic medical centers in the United States. Participants: Academic medical centers with 40 or more completed interventional trials registered on ClinicalTrials.gov. Methods: Using the Aggregate Analysis of ClinicalTrials.gov database and manual review, we identified all interventional clinical trials registered on ClinicalTrials.gov with a primary completion date between October 2007 and September 2010 and with a lead investigator affiliated with an academic medical center. Main outcome measures: The proportion of trials that disseminated results, defined as publication or reporting of results on ClinicalTrials.gov, overall and within 24 months of study completion. Results: We identified 4347 interventional clinical trials across 51 academic medical centers. Among the trials, 1005 (23%) enrolled more than 100 patients, 1216 (28%) were double blind, and 2169 (50%) were phase II through IV. Overall, academic medical centers disseminated results for 2892 (66%) trials, with 1560 (35.9%) achieving this within 24 months of study completion. The proportion of clinical trials with results disseminated within 24 months of study completion ranged from 16.2% (6/37) to 55.3% (57/103) across academic medical centers. The proportion of clinical trials published within 24 months of study completion ranged from 10.8% (4/37) to 40.3% (31/77) across academic medical centers, whereas results reporting on ClinicalTrials.gov ranged from 1.6% (2/122) to 40.7% (72/177). Conclusions: Despite the ethical mandate and expressed values and mission of academic institutions, there is poor performance and noticeable variation in the dissemination of clinical trial results across leading academic medical centers

Summary of Methodology Documentation.

<p>Summary of Methodology Documentation.</p

PRISMA Flow Diagram.

<p>PRISMA Flow Diagram.</p

Study Characteristics.

<p>Study Characteristics.</p

Variable Definitions.

<p>Variable Definitions.</p