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Farivar D, Peterman NJ, Nilssen PK, Illingworth KD, Nuckols TK, Skaggs DL. Geographic Access to Pediatric Orthopedic Surgeons in the United States: An Analysis of Sociodemographic Factors. Orthopedics 2024; 47:e204-e210. [PMID: 38690849 DOI: 10.3928/01477447-20240424-03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
BACKGROUND It is unclear how pediatric orthopedic surgeons are geographically distributed relative to their patients. The purpose of this study was to evaluate the geographic distribution of pediatric orthopedic surgeons in the United States. MATERIALS AND METHODS County-level data of actively practicing pediatric orthopedic surgeons were identified by matching several registries and membership logs. Data were used to calculate the distance between counties and nearest surgeon. Counties were categorized as "surgeon clusters" or "surgeon deserts" if the distance to the nearest surgeon was less than or greater than the national average and the average of all neighboring counties, respectively. Cohorts were then compared for differences in population characteristics using data obtained from the 2020 American Community Survey. RESULTS A total of 1197 unique pediatric orthopedic surgeons were identified. The mean distance to the nearest pediatric orthopedic surgeon for a patient residing in a surgeon desert or a surgeon cluster was 141.9±53.8 miles and 30.9±16.0 miles, respectively. Surgeon deserts were found to have lower median household incomes (P<.001) and greater rates of children without health insurance (P<.001). Multivariate analyses showed that higher Rural-Urban Continuum codes (P<.001), Area Deprivation Index scores (P<.001), and percentage of patients without health insurance (P<.001) all independently required significantly greater travel distances to see a pediatric orthopedic surgeon. CONCLUSION Pediatric orthopedic surgeons are not equally distributed in the United States, and many counties are not optimally served. Additional studies are needed to identify the relationship between travel distances and patient outcomes and how geographic inequalities can be minimized. [Orthopedics. 2024;47(4):e204-e210.].
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Benoit JL, Hogan AN, Connelly KM, McMullan JT. Intra-arrest blood-based biomarkers for out-of-hospital cardiac arrest: A scoping review. J Am Coll Emerg Physicians Open 2024; 5:e13131. [PMID: 38500598 PMCID: PMC10945310 DOI: 10.1002/emp2.13131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/29/2024] [Accepted: 02/02/2024] [Indexed: 03/20/2024] Open
Abstract
Objective Blood-based biomarkers play a central role in the diagnosis and treatment of critically ill patients, yet none are routinely measured during the intra-arrest phase of out-of-hospital cardiac arrest (OHCA). Our objective was to describe methodological aspects, sources of evidence, and gaps in research surrounding intra-arrest blood-based biomarkers for OHCA. Methods We used scoping review methodology to summarize existing literature. The protocol was designed a priori following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews. Inclusion criteria were peer-reviewed scientific studies on OHCA patients with at least one blood draw intra-arrest. We excluded in-hospital cardiac arrest and animal studies. There were no language, date, or study design exclusions. We conducted an electronic literature search using PubMed and Embase and hand-searched secondary literature. Data charting/synthesis were performed in duplicate using standardized data extraction templates. Results The search strategy identified 11,834 records, with 118 studies evaluating 105 blood-based biomarkers included. Only eight studies (7%) had complete reporting. The median number of studies per biomarker was 2 (interquartile range 1-4). Most studies were conducted in Asia (63 studies, 53%). Only 22 studies (19%) had blood samples collected in the prehospital setting, and only six studies (5%) had samples collected by paramedics. Pediatric patients were included in only three studies (3%). Out of eight predefined biomarker categories of use, only two were routinely assessed: prognostic (97/105, 92%) and diagnostic (61/105, 58%). Conclusions Despite a large body of literature on intra-arrest blood-based biomarkers for OHCA, gaps in methodology and knowledge are widespread.
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Affiliation(s)
- Justin L. Benoit
- Department of Emergency MedicineUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
| | - Andrew N. Hogan
- Department of Emergency MedicineUT Southwestern Medical CenterDallasTexasUSA
| | | | - Jason T. McMullan
- Department of Emergency MedicineUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
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Farivar D, Peterman NJ, Narendran N, Illingworth KD, Nuckols TK, Bonda D, Skaggs DL. Geographic access to pediatric neurosurgeons in the USA: an analysis of sociodemographic factors. Childs Nerv Syst 2024; 40:905-912. [PMID: 37794171 PMCID: PMC10891277 DOI: 10.1007/s00381-023-06172-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/28/2023] [Indexed: 10/06/2023]
Abstract
PURPOSE Geographic access to physicians has been shown to be unevenly distributed in the USA, with those in closer proximity having superior outcomes. The purpose of this study was to describe how geographic access to pediatric neurosurgeons varies across socioeconomic and demographic factors. METHODS Actively practicing neurosurgeons were identified by matching several registries and membership logs. This data was used to find their primary practice locations and the distance the average person in a county must travel to visit a surgeon. Counties were categorized into "surgeon deserts" and "surgeon clusters," which were counties where providers were significantly further or closer to its residents, respectively, compared to the national average. These groups were also compared for differences in population characteristics using data obtained from the 2020 American Community Survey. RESULTS A total of 439 pediatric neurosurgeons were identified. The average person in a surgeon desert and cluster was found to be 189.2 ± 78.1 miles and 39.7 ± 19.6 miles away from the nearest pediatric neurosurgeon, respectively. Multivariate analyses showed that higher Rural-Urban Continuum (RUC) codes (p < 0.001), and higher percentages of American Indian (p < 0.001) and Hispanic (p < 0.001) residents were independently associated with counties where the average person traveled significantly further to surgeons. CONCLUSION Patients residing in counties with greater RUC codes and higher percentages of American Indian and Hispanic residents on average need to travel significantly greater distances to access pediatric neurosurgeons.
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Affiliation(s)
- Daniel Farivar
- Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Nicholas J Peterman
- Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Nakul Narendran
- Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Kenneth D Illingworth
- Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Teryl K Nuckols
- Division of General Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - David Bonda
- Department of Neurological Surgery, University of Washington Medical Center, Seattle, WA, USA
| | - David L Skaggs
- Department of Orthopaedic Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 175] [Impact Index Per Article: 175.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Guan A, Pruitt SL, Henry KA, Lin K, Meltzer D, Canchola AJ, Rathod AB, Hughes AE, Kroenke CH, Gomez SL, Hiatt RA, Stroup AM, Pinheiro PS, Boscoe FP, Zhu H, Shariff-Marco S. Asian American Enclaves and Healthcare Accessibility: An Ecologic Study Across Five States. Am J Prev Med 2023; 65:1015-1025. [PMID: 37429388 PMCID: PMC10921977 DOI: 10.1016/j.amepre.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/03/2023] [Accepted: 07/05/2023] [Indexed: 07/12/2023]
Abstract
INTRODUCTION Access to primary care has been a long-standing priority for improving population health. Asian Americans, who often settle in ethnic enclaves, have been found to underutilize health care. Understanding geographic primary care accessibility within Asian American enclaves can help to ensure the long-term health of this fast-growing population. METHODS U.S. Census data from five states (California, Florida, New Jersey, New York, and Texas) were used to develop and describe census-tract level measures of Asian American enclaves and social and built environment characteristics for years 2000 and 2010. The 2-step floating catchment area method was applied to National Provider Identifier data to develop a tract-level measure of geographic primary care accessibility. Analyses were conducted in 2022-2023, and associations between enclaves (versus nonenclaves) and geographic primary care accessibility were evaluated using multivariable Poisson regression with robust variance estimation, adjusting for potential area-level confounders. RESULTS Of 24,482 census tracts, 26.1% were classified as Asian American enclaves. Asian American enclaves were more likely to be metropolitan and have less poverty, lower crime, and lower proportions of uninsured individuals than nonenclaves. Asian American enclaves had higher primary care accessibility than nonenclaves (adjusted prevalence ratio=1.23, 95% CI=1.17, 1.29). CONCLUSIONS Asian American enclaves in five of the most diverse and populous states in the U.S. had fewer markers of disadvantage and greater geographic primary care accessibility. This study contributes to the growing body of research elucidating the constellation of social and built environment features within Asian American enclaves and provides evidence of health-promoting characteristics of these neighborhoods.
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Affiliation(s)
- Alice Guan
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California
| | - Sandi L Pruitt
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Kevin A Henry
- Department of Geography and Urban Studies, College of Liberal Arts, Temple University, Philadelphia, Pennsylvania; Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Katherine Lin
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California
| | - Dan Meltzer
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California
| | - Alison J Canchola
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California
| | - Aniruddha B Rathod
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Amy E Hughes
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Candyce H Kroenke
- Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Scarlett L Gomez
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California; Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California
| | - Robert A Hiatt
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California; Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California
| | | | - Paulo S Pinheiro
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, Florida; Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida
| | | | - Hong Zhu
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, Virginia
| | - Salma Shariff-Marco
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California; Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California; Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
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Cerni J, Hosseinzadeh H, Mullan J, Westley-Wise V, Chantrill L, Barclay G, Rhee J. Does Geography Play a Role in the Receipt of End-of-Life Care for Advanced Cancer Patients? Evidence from an Australian Local Health District Population-Based Study. J Palliat Med 2023; 26:1453-1465. [PMID: 37252775 PMCID: PMC10658736 DOI: 10.1089/jpm.2022.0555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2023] [Indexed: 05/31/2023] Open
Abstract
Objectives: To assess the influence of geographic remoteness on health care utilization at end of life (EOL) by people with advanced cancer in a geographically diverse Australian local health district, using two objective measures of rurality and travel-time estimations to health care facilities. Methods: This retrospective cohort study examined the association between rurality (using the Modified Monash Model) and travel-time estimation, and demographic and clinical factors, with the receipt of >1 inpatient and outpatient health service in the last year of life in multivariate models. The study cohort comprised of 3546 patients with cancer, aged ≥18 years, who died in a public hospital between 2015 and 2019. Results: Compared with decedents from metropolitan areas, decedents from some rural areas had higher rates of emergency department visits (small rural towns: aRR 1.29, 95% CI: 1.07-1.57) and ICU admissions (large rural towns: aRR 1.32, 95% CI: 1.03-1.69), but lower rates of acute hospital admissions (large rural towns: aRR 0.83, 95% CI: 0.76-0.90), inpatient palliative care (PC) (regional centers: aRR 0.85, 95% CI: 0.75-0.97), and inpatient radiotherapy (lowest in small rural towns: aRR 0.07, 95% CI: 0.03-0.18). Decedents from rural and regional centers had lower rates of outpatient chemotherapy and radiotherapy use, yet higher rates of outpatient cancer service utilization (p < 0.05). Shorter travel times (10-<30 minutes) were associated with higher rates of inpatient specialist PC (aRR 1.48, 95% CI: 1.09-1.98). Conclusions: Reporting on a series of inpatient and outpatient services used in the last year of life, measures of rurality and travel-time estimates can be useful tools to estimate geographic variation in EOL cancer care provision, with significant gaps uncovered in inpatient PC and outpatient service utilization in rural areas. Policies aimed at redistributing EOL resources in rural and regional communities to reduce travel times to health care facilities could help to reduce regional disparities and ensure equitable access to EOL care services.
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Affiliation(s)
- Jessica Cerni
- Faculty of Arts, Social Sciences, and Humanities, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
| | - Hassan Hosseinzadeh
- Faculty of Arts, Social Sciences, and Humanities, School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
| | - Judy Mullan
- Centre for Health Research Illawarra Shoalhaven Population (CHRISP), Graduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia
| | - Victoria Westley-Wise
- Centre for Health Research Illawarra Shoalhaven Population (CHRISP), Illawarra Shoalhaven Local Health District (ISLHD), University of Wollongong, Wollongong, New South Wales, Australia
| | - Lorraine Chantrill
- Department of Medical Oncology and Illawarra Shoalhaven Local Health District, Wollongong, New South Wales, Australia
| | - Greg Barclay
- Department of Palliative Care, Illawarra Shoalhaven Local Health District, Wollongong, New South Wales, Australia
| | - Joel Rhee
- School of Population Health, University of New South Wales, Sydney, New South Wales, Australia
- Graduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1399] [Impact Index Per Article: 1399.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2562] [Impact Index Per Article: 1281.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Hirsch JA, Moore KA, Cahill J, Quinn J, Zhao Y, Bayer FJ, Rundle A, Lovasi GS. Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology. J Urban Health 2021; 98:271-284. [PMID: 33005987 PMCID: PMC8079597 DOI: 10.1007/s11524-020-00482-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/04/2020] [Indexed: 12/31/2022]
Abstract
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.
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Affiliation(s)
- Jana A. Hirsch
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA Philadelphia, USA
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Kari A. Moore
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Jesse Cahill
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - James Quinn
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - Yuzhe Zhao
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Felicia J. Bayer
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
| | - Andrew Rundle
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY USA
| | - Gina S. Lovasi
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA Philadelphia, USA
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA USA
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Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Cheng S, Delling FN, Elkind MSV, Evenson KR, Ferguson JF, Gupta DK, Khan SS, Kissela BM, Knutson KL, Lee CD, Lewis TT, Liu J, Loop MS, Lutsey PL, Ma J, Mackey J, Martin SS, Matchar DB, Mussolino ME, Navaneethan SD, Perak AM, Roth GA, Samad Z, Satou GM, Schroeder EB, Shah SH, Shay CM, Stokes A, VanWagner LB, Wang NY, Tsao CW. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation 2021; 143:e254-e743. [PMID: 33501848 DOI: 10.1161/cir.0000000000000950] [Citation(s) in RCA: 3159] [Impact Index Per Article: 1053.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease. RESULTS Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Brown JR, Hirsch JA, Judd SE, Hurvitz PM, Howard VJ, Safford M, Moore J, Lovasi GS. The Association of Neighborhood Medical Facilities with Aging in Place and Risk of Incident Myocardial Infarction. J Aging Health 2020; 33:227-236. [PMID: 33251918 PMCID: PMC8592305 DOI: 10.1177/0898264320975228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Objectives: Aging in place (residential stability) is a desirable means of aging where adults remain in their homes, even when facing challenges that impair their capacity for self-care. Residential stability, especially following acute health challenges, depends on individual and community factors, possibly including proximity to medical facilities. Methods: We explored the association between the density of medical facilities around homes with risk of incident myocardial infarction (MI) and with aging in place following incident MI. Results: Densities of neighborhood pharmacies were not associated with aging in place or time to MI. High densities of neighborhood clinical care facilities were significantly associated with decreased residential stability. Discussion: The lack of significant associations between medical facility exposures and MI-related outcomes, coupled with prior findings, casts doubt on their salience and may indicate that other neighborhood features are more strongly associated with these outcomes.
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Affiliation(s)
- Janene R Brown
- Urban Health Collaborative, 6527Drexel University, PA, USA
| | - Jana A Hirsch
- Urban Health Collaborative, 6527Drexel University, PA, USA
| | | | | | | | - Monika Safford
- Weill Cornell Medical College, Cornell University, NY, USA
| | - Jeffrey Moore
- Urban Health Collaborative, 6527Drexel University, PA, USA
| | - Gina S Lovasi
- Urban Health Collaborative, 6527Drexel University, PA, USA
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Tsui J, Hirsch JA, Bayer FJ, Quinn JW, Cahill J, Siscovick D, Lovasi GS. Patterns in Geographic Access to Health Care Facilities Across Neighborhoods in the United States Based on Data From the National Establishment Time-Series Between 2000 and 2014. JAMA Netw Open 2020; 3:e205105. [PMID: 32412637 PMCID: PMC7229525 DOI: 10.1001/jamanetworkopen.2020.5105] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
IMPORTANCE The association between proximity to health care facilities and improved disease management and population health has been documented, but little is known about small-area health care environments and how the presence of health care facilities has changed over time during recent health system and policy change. OBJECTIVE To examine geographic access to health care facilities across neighborhoods in the United States over a 15-year period. DESIGN, SETTING, AND PARTICIPANTS Using longitudinal business data from the National Establishment Time-Series, this cross-sectional study examined the presence of and change in ambulatory care facilities and pharmacies and drugstores in census tracts (CTs) throughout the continental United States between 2000 and 2014. Between January and April 2019, multinomial logistic regression was used to estimate associations between health care facility presence and neighborhood sociodemographic characteristics over time. MAIN OUTCOMES AND MEASURES Change in health care facility presence was measured as never present, lost, gained, or always present between 2000 and 2014. Neighborhood sociodemographic characteristics (ie, CTs) and their change over time were measured from US Census reports (2000 and 2010) and the American Community Survey (2008-2012). RESULTS Among 72 246 included CTs, the percentage of non-US-born residents, residents 75 years or older, poverty status, and population density increased, and 8.1% of CTs showed a change in the racial/ethnic composition of an area from predominantly non-Hispanic (NH) white to other racial/ethnic composition categories between 2000 and 2010. The presence of ambulatory care facilities increased from a mean (SD) of 7.7 (15.9) per CT in 2000 to 13.0 (22.9) per CT in 2014, and the presence of pharmacies and drugstores increased from a mean (SD) of 0.6 (1.0) per CT in 2000 to 0.9 (1.4) per CT in 2014. Census tracts with predominantly NH black individuals (adjusted odds ratio [aOR], 2.37; 95% CI, 2.03-2.77), Hispanic/Latino individuals (aOR 1.30; 95% CI, 1.00-1.69), and racially/ethnically mixed individuals (aOR, 1.53; 95% CI, 1.33-1.77) in 2000 had higher odds of losing health care facilities between 2000 and 2014 compared with CTs with predominantly NH white individuals, after controlling for other neighborhood characteristics. Census tracts of geographic areas with higher levels of poverty in 2000 also had higher odds of losing health care facilities between 2000 and 2014 (aOR, 1.12; 95% CI, 1.05-1.19). CONCLUSIONS AND RELEVANCE Differential change was found in the presence of health care facilities across neighborhoods over time, indicating the need to monitor and address the spatial distribution of health care resources within the context of population health disparities.
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Affiliation(s)
- Jennifer Tsui
- Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick
- Department of Health Behavior, Society, and Policy, Rutgers School of Public Health, Rutgers, The State University of New Jersey, New Brunswick
- Rutgers Center for State Health Policy, Rutgers, The State University of New Jersey, New Brunswick
| | - Jana A. Hirsch
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
| | - Felicia J. Bayer
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
| | - James W. Quinn
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Jesse Cahill
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - David Siscovick
- Research, Evaluation & Policy, New York Academy of Medicine, New York, New York
| | - Gina S. Lovasi
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania
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Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation 2020; 141:e139-e596. [PMID: 31992061 DOI: 10.1161/cir.0000000000000757] [Citation(s) in RCA: 4899] [Impact Index Per Article: 1224.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals. RESULTS Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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