Abstract P2050: Neighborhood-Level Racial and Ethnic Residential Segregation and Incidence of Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis (MESA)

Introduction: Atrial fibrillation (AF) is the most common arrhythmia, affecting up to 6 million in the US, and is associated with significant morbidity and mortality. Despite higher rates of AF clinical and social risk factors, underrepresented racial and ethnic group (UREG) individuals have lower AF incidence. Structural factors, such as neighborhood-level racial/ethnic residential segregation, have been associated with incident cardiometabolic disease, particularly among UREG individuals. However, data on segregation and incident AF is sparse. Hypothesis: We hypothesized that adults living in more segregated neighborhoods would have a higher incidence of AF. Goals/Aims: We examined whether AF incidence differed across segregation categories among racial and ethnic groups. Methods: Administrative and clinical data from the Multi-Ethnic Study of Atherosclerosis (MESA; baseline 2000-2002) were used to identify those with a diagnosis of AF during follow-up. Own-group racial/ethnic segregation was defined by local GI* statistic, which compares the percent of each racial/ethnic group in a current census tract to the surrounding area. Racial/ethnic-stratified Cox proportional hazard models were created to estimate hazard ratios comparing across segregation levels. Models were adjusted for demographic factors, individual and neighborhood level socioeconomic factors, and clinical factors. Results: Our final cohort comprised 6,100 participants (27% Black, 12% Chinese, 22% Hispanic, 39% White). During a median follow-up of 14.2 years, 1,203 participants (19.7%) were diagnosed with AF. Black and Hispanic participants had the highest prevalence of AF risk factors at baseline. Black, Hispanic, and Chinese participants were more likely to reside in segregated neighborhoods (Table). After adjusting for demographic, socioeconomic and clinical factors, among all racial groups, neighborhood segregation was not associated with incident AF ( Table ). Conclusions: In this longitudinal analysis we did not observe a statistically significant association between residential segregation and AF incidence for any racial and ethnic groups in adjusted models. Further research is needed to understand how individual factors may intersect with clinical, healthcare, and structural factors to drive previously described differential incidence of AF.

Authors

Institutions

Publication Details

Journal
Circulation
Published
2025-03-11
DOI
https://doi.org/10.1161/cir.151.suppl_1.p2050
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract P2050: Neighborhood-Level Racial and Ethnic Residential Segregation and Incidence of Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis (MESA)

Philip Greenland, Susan R. Heckbert, Kiarri N. Kershaw, Utibe R. Essien et al.
Circulation
Cardiovascular Health and Risk Factors
article

Abstract P2050: Neighborhood-Level Racial and Ethnic Residential Segregation and Incidence of Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis (MESA)

Philip Greenland, Susan R. Heckbert, Kiarri N. Kershaw, Utibe R. Essien, Mandy Wong, Moysés Szklo, Karol E. Watson, Mercedes R. Carnethon, Mahasin S. Mujahid, Jingjing Tang
article en

Abstract

Introduction: Atrial fibrillation (AF) is the most common arrhythmia, affecting up to 6 million in the US, and is associated with significant morbidity and mortality. Despite higher rates of AF clinical and social risk factors, underrepresented racial and ethnic group (UREG) individuals have lower AF incidence. Structural factors, such as neighborhood-level racial/ethnic residential segregation, have been associated with incident cardiometabolic disease, particularly among UREG individuals. However, data on segregation and incident AF is sparse. Hypothesis: We hypothesized that adults living in more segregated neighborhoods would have a higher incidence of AF. Goals/Aims: We examined whether AF incidence differed across segregation categories among racial and ethnic groups. Methods: Administrative and clinical data from the Multi-Ethnic Study of Atherosclerosis (MESA; baseline 2000-2002) were used to identify those with a diagnosis of AF during follow-up. Own-group racial/ethnic segregation was defined by local GI* statistic, which compares the percent of each racial/ethnic group in a current census tract to the surrounding area. Racial/ethnic-stratified Cox proportional hazard models were created to estimate hazard ratios comparing across segregation levels. Models were adjusted for demographic factors, individual and neighborhood level socioeconomic factors, and clinical factors. Results: Our final cohort comprised 6,100 participants (27% Black, 12% Chinese, 22% Hispanic, 39% White). During a median follow-up of 14.2 years, 1,203 participants (19.7%) were diagnosed with AF. Black and Hispanic participants had the highest prevalence of AF risk factors at baseline. Black, Hispanic, and Chinese participants were more likely to reside in segregated neighborhoods (Table). After adjusting for demographic, socioeconomic and clinical factors, among all racial groups, neighborhood segregation was not associated with incident AF ( Table ). Conclusions: In this longitudinal analysis we did not observe a statistically significant association between residential segregation and AF incidence for any racial and ethnic groups in adjusted models. Further research is needed to understand how individual factors may intersect with clinical, healthcare, and structural factors to drive previously described differential incidence of AF.

CirculationVol. 151(Suppl_1)
Northwestern University (US), Berkeley College (US), Johns Hopkins University (US), University of Washington (US), UCLA Health (US), University of California, Berkeley (US)
Openalex Percentile: Top 87%
Cardiovascular Health and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.