Journal of the American Heart Association · 2026
Neighborhood-Level Racial and Ethnic Residential Segregation and Incidence of Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis.
СтатьяМногоцентровое исследованиеПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Essien Utibe R, Harrington Katharine, Alexandria Shaina J, Greenland Philip, Heckbert Susan R, Szklo Moyses, Mujahid Mahasin S, Carnethon Mercedes R, Watson Karol E, Tang Jasmyn J, Kershaw Kiarri N
Аннотация
BACKGROUND: Atrial 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.
METHODS: Data 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.
RESULTS: Our 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.
CONCLUSIONS: In 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.
METHODS: Data 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.
RESULTS: Our 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.
CONCLUSIONS: In 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.