In one paragraphArticle in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
11 authors.
Utibe R EssienDivision of General Internal Medicine and Health Services David Geffen School of Medicine at the University of California Los Angeles Los Angeles CA USA.ORCID 0000-0002-4494-5028 Katharine HarringtonDepartment of Preventive Medicine Feinberg School of Medicine at Northwestern University Chicago IL USA.ORCID 0000-0002-2829-5133 Shaina J AlexandriaDepartment of Preventive Medicine Feinberg School of Medicine at Northwestern University Chicago IL USA.ORCID 0000-0002-3069-4299 Philip GreenlandDepartment of Preventive Medicine Feinberg School of Medicine at Northwestern University Chicago IL USA.ORCID 0000-0002-6327-2439 Susan R HeckbertDepartment of Epidemiology School of Public Health at the University of Washington Seattle WA USA.ORCID 0000-0002-7100-512X Moyses SzkloDivision of Cardiovascular and Clinical Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD USA.ORCID 0000-0001-9433-6266 Mahasin S MujahidDivision of Epidemiology School of Public Health at the University of California Berkeley Berkeley CA USA.ORCID 0000-0001-9795-9338 Mercedes R CarnethonDepartment of Preventive Medicine Feinberg School of Medicine at Northwestern University Chicago IL USA.ORCID 0000-0001-7035-0848 Karol E WatsonDivision of Cardiology David Geffen School of Medicine at University of California Los Angeles Los Angeles CA USA.ORCID 0000-0003-3658-6165 Jasmyn J TangDivision of General Internal Medicine and Health Services David Geffen School of Medicine at the University of California Los Angeles Los Angeles CA USA.ORCID 0009-0001-8737-0447 Kiarri N KershawDepartment of Preventive Medicine Feinberg School of Medicine at Northwestern University Chicago IL USA.ORCID 0000-0002-0063-6397 Funding
Task Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 to 2025
$5.1MTO EXERCISE OPTION PERIOD ONE (1) FOR TASK AREA A - MESA CORE OPERATIONS, FIELD CENTER.75N92020D00004 · NHLBI · NORTHWESTERN UNIVERSITY · PI SIEGEL, JONATHAN H · 2020 to 2025
$4.5MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00006 · NHLBI · UNIVERSITY OF MINNESOTA · PI PANKOW, JAMES S · 2020 to 2025
$4.4MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00003 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI POST, WENDY S · 2020 to 2025
$3.8MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00007 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BERTONI, ALAIN GERALD · 2020 to 2025
$3.5MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00002 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEA, STEVEN J · 2020 to 2025
$3.4MNHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003I
6 · The paper itselfAbstract
backgroundAtrial fibrillation (AF) is the most common arrhythmia, affecting up to 6 million in the United States, and is associated with significant morbidity and mortality. Despite higher rates of AF clinical and social risk factors, underrepresented racial and ethnic group individuals have lower AF incidence. Structural factors, such as neighborhood-level racial and ethnic residential segregation, have been associated with incident cardiometabolic disease, particularly among underrepresented individuals. However, as data on segregation and incident AF are sparse our objective was to examine the association of segregation on AF.
methodsData from MESA (Multi-Ethnic Study of Atherosclerosis; baseline 2000-2002) were used to identify those with a diagnosis of AF during follow-up. Own-group racial and ethnic segregation was defined by local Gi* statistic, which compares the percentage of each racial and ethnic group in a current census tract to the surrounding area. Racial- and ethnic-stratified Cox proportional hazard models were used to estimate hazard ratios comparing across segregation levels. Models were adjusted for demographic, participant, and neighborhood level socioeconomic, and clinical factors.
resultsOur cohort comprised 5375 participants (31% Black, 25% Hispanic/Latino, 44% White). During a median follow-up of 16.6 years, 1035 participants (19.3%) were diagnosed with AF. Black and Hispanic/Latino participants had the highest prevalence of AF risk factors at baseline and were more likely to reside in segregated neighborhoods than White participants. After adjusting for demographic, socioeconomic, and clinical factors, neighborhood segregation was not found to be associated with AF across racial and ethnic groups.
conclusionsIn this longitudinal analysis we did not observe an association between residential segregation and AF incidence for Black, Hispanic/Latino, or White participants in fully adjusted models. Further research is needed to understand how individual factors may intersect with clinical, health care, and structural factors to drive previously described differential risk of AF.
Indexed as
AtherosclerosisAtrial FibrillationEthnicityNeighborhood CharacteristicsResidence CharacteristicsResidential SegregationAgedAged, 80 and overBlack or African AmericanFemaleHealth Status DisparitiesHispanic or LatinoHumansIncidenceMaleMiddle Agedatrial fibrillationdisparitiesepidemiologyhealth equitysegregation
Identifiers
PMID42333700
PMCPMC13477282
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