Investigation of selection bias in the association of race with prevalent atrial fibrillation in a national cohort study: REasons for Geographic And Racial Differences in Stroke (REGARDS)

Depressive Symptoms and Risk of Stroke in a National Cohort of Black and White Participants From REGARDS

Objective

The purpose of this study was to examine depressive symptoms as a risk factor for incident stroke and determine whether depressive symptomatology was differentially predictive of stroke among Black and White participants.

Methods

The study comprised 9,529 Black and 14,516 White stroke-free participants, aged 45 and older, enrolled in the REasons for Geographic and Racial Differences in Stroke (2003-2007). Incident stroke was the first occurrence of stroke. Association between baseline depressive symptoms (assessed via the 4-item Center for Epidemiologic Studies Depression Scale [CES-D-4]: 0, 1-3, or ≥4) and incident stroke was analyzed with Cox proportional hazards models adjusted for demographics, stroke risk factors, and social factors.

Results

There were 1,262 strokes over an average follow-up of 9.21 (SD 4.0) years. Compared to participants with no depressive symptoms, after demographic adjustment, participants with CES-D-4 scores of 1-3 had 39% increased stroke risk (hazard ratio [HR] = 1.39, 95% confidence interval [CI] = 1.23-1.57), with slight attenuation after full adjustment (HR = 1.27, 95% CI = 1.11-1.43). Participants with CES-D-4 scores of ≥4 experienced 54% higher risk of stroke after demographic adjustment (HR = 1.54, 95% CI = 1.27-1.85), with risk attenuated in the full model similar to risk with 1-3 symptoms (HR = 1.25, 95% CI = 1.03-1.51). There was no evidence of a differential effect by race (p = 0.53).

Conclusions

The association of depressive symptoms with increased stroke risk was similar among a national sample of Black and White participants. These findings suggest that assessment of depressive symptoms should be considered in primary stroke prevention for both Black and White participants.

Matching participant address with public records database in a US national longitudinal cohort study

Background

Epidemiological studies utilize residential histories to assess environmental exposure risk. The validity from using commercially-sourced residential histories within national longitudinal studies remains unclear. Our study assessed predictors of non-agreement between baseline addresses from the commercially-sourced LexisNexis database and participants in the national longitudinal study, REasons for Geographic and Racial Differences in Stroke (REGARDS). Additionally, we assessed differences in stroke risk by neighborhood socioeconomic score (nSES) based on participant reported address compared to nSES from LexisNexis/REGARDS matched baseline address.

Methods

From January 2003–October 2007, REGARDS enrolled 30,239 black and white adults aged 45 and older within the continental United States and collected their baseline address. ArcGIS Desktop 10.5.1 with ESRI 2016 Business Analyst Data was used to geocode baseline addresses from LexisNexis and REGARDS. Logistic regression was used to estimate the likelihood that LexisNexis address matched REGARDS baseline address for each participant. Survival analysis was used to estimate association between nSES and incident stroke.

Results

Approximately 91% of REGARDS participants had a LexisNexis address. Of these geocoded addresses, 93% of REGARDS baseline addresses matched LexisNexis addresses. Odds of agreement between LexisNexis and REGARDS was higher for older-aged participants (OR = 1.02 per year, 95% CI: 1.01, 1.02), blacks compared to whites (OR = 1.16, 95% CI: 1.05, 1.29), females compared to males (OR = 1.15, 95% CI: 1.04, 1.26), participants with an income of $34k-74k compared to an income less than $20k (OR = 1.62, 95% CI: 1.39, 1.89). Odds of agreement were lower for residents in Midwest compared to residents in the south (OR = 0.82, 95% CI: 0.73, 0.94). No significant differences in nSES-stroke associations were observed between REGARDS only and LexisNexis/REGARDS matched addresses; however, differences in interactions were observed.

Conclusion

Agreement between LexisNexis and REGARDS addresses varied by sociodemographic groups, potentially introducing bias in studies reliant on LexisNexis alone for residential address data.

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Approximately 9% of REGARDS participants did not have a LexisNexis address history available.

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Of participants with both REGARDS and LexisNexis addresses available, 93% of these addresses matched.

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Agreement between REGARDS and LexisNexis address varied by socio-demographics—potentially biasing environmental exposures.

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Compared to LexisNexis, REGARDS addresses may be valuable in detecting interactions contributing to stroke disparities.

Comparison of Frequency of Atrial Fibrillation in Blacks Versus Whites and the Utilization of Race in a Novel Risk Score

Blacks have a lower prevalence of atrial fibrillation (AF) compared with Whites. We sought to confirm previously reported ethnic trends in AF in Blacks and Whites in a large database, and develop a prediction score for AF. Over 330 million hospital discharges between the years 2003 to 2013 from the National Inpatient Sample database were analyzed. All hospitalizations with a diagnosis of AF formed the study cohort. Traditional risk factors for the development of AF were compared between Blacks and Whites. Univariate and multiple logistic regression analyses were used to formulate a risk score to predict AF-CHADSAVES (Congestive heart failure, Hypertension, Age>65 years, Diabetes Mellitus, prior Stroke, Age>75 years, Vascular disease, White Ethnicity, and previous cardiothoracic Surgery). AF prevalence in Whites was 11.3% vs 4.6% in Blacks (p < 0.001). Blacks were younger (33.8% vs 14.4% patients <65 years, p < 0.01) and had less males (46.3% vs 49.4%, p < 0.01). Blacks had more hypertension (71.3% vs 64.1%, p < 0.01), congestive heart failure (24.8% vs 22.6%, p < 0.01), diabetes mellitus with (7.5% vs 4.7%, p < 0.01) or without complications (30.3% vs 23.1%, p < 0.01), renal failure (29.7% vs 17.1%, p < 0.01), and obesity (13.1% vs 8.7%, p < 0.01). CHADSAVES predicted AF in the study population (NIS 2003 to 2013) with an AUC of 0.82 and verified in a validation cohort (NIS 2014) with an AUC of 0.85. In conclusion, our data confirm a significant AF ethnicity paradox. Despite a higher prevalence of traditional risk factors for AF, Blacks had >2-fold lower prevalence of AF compared with Whites. CHADSAVES can be used effectively to predict AF in inpatients.