Metabolic Syndrome and Risk of Ischemic Stroke in Atrial Fibrillation: Atherosclerosis Risk In Communities (ARIC) Study

Abstract

BACKGROUND AND PURPOSE:

Metabolic syndrome (MetS), a prothrombotic state, is associated with an increased risk of atrial fibrillation (AF) and stroke. The CHA₂DS₂-VASc score does not account for the MetS components of prehypertension, prediabetes, abdominal obesity, elevated triglycerides and low high- density lipoprotein (HDL). Data are limited on the association of MetS with stroke in AF, independent of CHA₂DS₂-VASc variables. Our aim was to identify MetS components associated with ischemic stroke in participants with AF in the Atherosclerosis Risk in Communities (ARIC) Study.

METHODS:

We included 1,172 participants with incident AF within 5 years of measurement of MetS components. MetS was defined by ATP criteria and International Diabetes Federation criteria. Incident ischemic stroke was physician adjudicated. Multivariable Cox proportional hazards regression was used to assess the association of MetS components with stroke.

RESULTS:

After a median follow-up of 14.8 years, there were 113 ischemic stroke cases. Of the individual MetS components, low HDL was borderline associated with increased stroke risk (HR, 1.48; 95% CI, 0.99–2.21) after adjustment for CHA2DS2-VASc variables while the remaining MetS variables were not associated with stroke risk. The presence of ≥3 components of MetS was not significantly associated with ischemic stroke after adjustment for CHA2DS2-VASc variables (HR, 1.38; 95% CI, 0.91–2.11). The risk of stroke increased by 13% for each additional component of MetS; however, this association was borderline significant (HR, 1.13 95% CI, 0.99–1.28).

CONCLUSION:

The presence of MetS was not significantly associated with ischemic stroke after adjustment for CHA₂DS₂-VASc variables. Consideration of MetS is unlikely to improve stroke prediction in AF.

Introduction

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the general population and it is associated with a 5-fold increased risk of ischemic stroke and a 2-fold increased risk of cardiac mortality.^1,2 Given the significant morbidity and mortality associated with stroke in AF, the CHADS₂ and CHA₂DS₂-VASc scores have been established as validated stroke risk stratification schemes in patients with AF.^3,4 The CHADS₂ score includes congestive heart failure, hypertension, age >75 years, diabetes mellitus and prior stroke or transient ischemic attack (TIA). Although simple to use, the CHADS₂ score has modest predictive ability and known limitations with classifying low and intermediate risk patients.⁵ The CHA₂DS₂-VASc score, which was developed to address the limitations of the CHADS₂ score, includes additional risk factors of vascular disease, age between 65 and 74 years, and female sex and allows for more comprehensive stroke risk assessment.

Metabolic syndrome is a constellation of cardiovascular risk factors and is defined as the presence of any three of the following five traits including abdominal obesity, elevated triglycerides, reduced high-density lipoprotein (HDL) cholesterol, prehypertension or hypertension and insulin resistance or diabetes. Metabolic syndrome is considered to be both a proinflammatory and prothrombotic state as adults with metabolic syndrome have been shown to have decreased serum concentrations of antioxidants and elevated C-reactive protein, fibrinogen and plasminogen activator inhibitor-1 concentrations.^6,7 Additionally, metabolic syndrome has been shown to be independently associated with an increased risk of new-onset AF and ischemic stroke.^8,9 The association between metabolic syndrome and thromboembolic risk in patients with AF was evaluated in a study based in Taiwan which found that every component of metabolic syndrome was associated with increased risk of thromboembolism, range of HR: 1.35 to 1.75 .¹⁰ Furthermore, considering components of the metabolic syndrome improved model discrimination of thromboembolic events over the CHADS₂ score alone (ROC area: 0.729 vs. 0.670, P = 0.034).¹⁰

While overlap exists between metabolic syndrome and CHA₂DS₂-VASc with regards to hypertension and diabetes, the CHA₂DS₂-VASc score does not include prehypertension, prediabetes, abdominal obesity, elevated triglycerides and low HDL. It remains unknown whether the components of metabolic syndrome would improve risk prediction of stroke, after accounting for the CHA₂DS₂-VASc score in the US population. The objective of this study was to assess the association between the metabolic syndrome and the risk of ischemic stroke in participants with AF in the Atherosclerosis Risk in Communities (ARIC) Study, a community-based prospective cohort study.

Methods

The data, analytic methods, and study materials will be made available to other researchers for purposes of reproducing the results or replicating the procedure in accordance with ARIC policies. Data are maintained by ARIC through the University of North Carolina Collaborative Studies Coordinating Center. Further information is available on the ARIC website.

Study Population and follow-up

The ARIC study is a community-based prospective cohort study of cardiovascular disease with participants sampled from 4 US communities: suburbs of Minneapolis, Minnesota; Washington County, Maryland; Forsyth County, North Carolina; and Jackson, Mississippi. The study included 15,792 men and women 45–64 years of age at enrollment (1987–1989) who underwent a baseline visit at the time of enrollment (visit 1) and then attended subsequent exams in 1990–1992, 1993–1995, 1996–1998 and 2011–2013, 2016–2017 (visits 2–6), with visit 7 ongoing. Study visits included a clinical exam, fasting laboratory measurements and an electrocardiogram (ECG) which was centrally read. Additional details on outcome ascertainment procedures, study design and population statistics have been previously described.¹¹ The ARIC study’s research protocol was approved by institutional review boards at each participating center, and all participants provided informed consent.

For our analysis, we considered 1,392 participants who developed AF within a 5 year time period after presentation for study clinic visits 1–5. We excluded those with missing covariates (n=21), on anticoagulation within 1 year after AF diagnosis (n=188) and race other than white or black, along with non-whites in the Minneapolis and Washington County field centers, due to small numbers (n=11), which would not contribute meaningfully to the analysis (Figure 1). The final analytic cohort included 1,172 participants.

Figure 1.

Flowchart of study participants.

Ascertainment of Atrial Fibrillation

Details of AF ascertainment in ARIC have previously been described.^12,13 Briefly, AF was ascertained from resting 12-lead ECGs obtained during the baseline and 4 follow-up visits as well as hospital discharge records using International Classification of Disease 9th revision, Clinical Modification [ICD-9-CM] 427.31 or 427.32 diagnosis codes. All study visit ECGs coded by ECG software as AF were visually confirmed by either a cardiologist or a trained coder.

Components of Metabolic Syndrome

Measurements of components of metabolic syndrome were obtained at visits 1–5. Metabolic syndrome was defined by current ATP III criteria.¹⁴ Abdominal obesity was defined as a waist circumference in men ≥102 cm (40 in) and in women ≥88 cm (35 in). Elevated triglycerides was defined as ≥1.7 mmol/L (150 mg/dL) or drug treatment for elevated triglycerides. Low high-density lipoprotein (HDL) cholesterol was defined as <1 mmol/L (40 mg/dL) in men and <1.3 mmol/L (50 mg/dL) in women or drug treatment for low HDL cholesterol. Elevated fasting plasma glucose was defined as fasting plasma glucose (FPG) ≥5.6 mmol/L or 100 mg/dL (also known as prediabetes), drug treatment for elevated blood glucose, or a diagnosis of diabetes. Diabetes was defined as FPG ≥7.0 mmol/L (126 mg/dL), non-fasting glucose ≥11.1 mmol/L (200 mg/dl) or drug treatment for diabetes. There was a small number of participants (n=36) who were not fasting and had a blood glucose of ≥5.6 mmol/L (100 mg/dL); however, all of these participants met criteria for inclusion in the elevated fasting plasma group based on either drug treatment for elevated blood glucose or a diagnosis of diabetes. Elevated blood pressure was defined as blood pressure ≥130/85 mmHg (also known as prehypertension) or drug treatment for elevated blood pressure. Hypertension was defined as systolic blood pressure >140 mmHg and/or diastolic blood pressure >90 mmHg or drug treatment for hypertension. Participants were considered to have metabolic syndrome if ≥3 components of metabolic syndrome were present.

An additional analysis defined metabolic syndrome by the International Diabetes Federation criteria: BMI >30 mg/m² is used to define central obesity rather than waist circumference. The definitions for elevated triglycerides, low HDL, elevated fasting plasma glucose and elevated blood pressure, as detailed above, are the same for both ATP and International Diabetes Federation criteria.

Ascertainment of Ischemic Stroke

ARIC participants were contacted annually by phone in order to identify deaths and hospitalizations within the previous year. Hospital records and death certificates were then obtained for physician review of all potential cases of stroke. Further classification of stroke was adjudicated by a panel of physicians with assistance of a computerized algorithm utilizing validated criteria from the National Survey of Stroke by the National Institute of Neurological Disorders. If the physician panel was unable to reach a consensus on a stroke diagnosis, further review and adjudication was determined by a neurologist or cardiologist.

Strokes were classified as definite or probable thrombotic stroke, definite or probable cardioembolic stroke, definite or probable subarachnoid hemorrhage, definite or probable brain hemorrhage, and possible stroke of undetermined type or cryptogenic stroke. All definite thrombotic strokes were further sub-typed as definite thrombotic lacunar and definite thrombotic non-lacunar strokes. The primary endpoint in our study was definite ischemic stroke, which included all definite thrombotic strokes and all definite cardioembolic strokes. Further details on stroke identification and specific classification criteria in the ARIC study have been previously described.^15,16

Statistical Analyses

Metabolic syndrome components were assessed at each of the 5 study visits, and the measurements from the visit preceding development of AF were used for this analysis. The components of metabolic syndrome were modeled as dichotomous variables, with an additional analysis modeling HDL as a continuous variable. In order to estimate the association between metabolic syndrome components with incident ischemic stroke, we calculated hazard ratios (HRs) and 95% confidence intervals (CIs) using multivariable Cox proportional hazard models. The first multivariable model was adjusted for age, sex, race/study center. The second model additionally adjusted for CHA₂DS₂-VASc variables of heart failure, hypertension, diabetes, coronary artery disease, previous myocardial infarction, peripheral artery disease and history of stroke or transient ischemic attack and also adjusted for use of anticoagulation. A third model additionally adjusted for the CHADS₂ variables of heart failure, hypertension, diabetes and history of stroke or transient ischemic attack as well as for use of anticoagulation.

The reference group for comparison of participants with elevated blood pressure comprised participants without hypertension or prehypertension. The reference group for comparison of participants with elevated fasting plasma glucose comprised participants without diabetes or prediabetes. The CHA₂DS₂-VASc and CHADS₂ scores, which are the basis for adjustments used in models 2 and 3 respectively, overlap with the definition of metabolic syndrome with regards to hypertension and diabetes. As a result of these overlapping definitions, we did not include hypertension in the adjustments for the second and third models when assessing for the association of elevated BP with stroke. Similarly, we did not include diabetes in the second and third models when assessing for the association of elevated fasting plasma glucose and stroke.

In addition to assessing the association of individual metabolic syndrome components with incident ischemic stroke, we also performed analysis evaluating the risk of stroke associated with meeting the criteria for the diagnosis of metabolic syndrome, based on both ATP criteria and International Diabetes Federation criteria. For this analysis, the second and third models did not include hypertension or diabetes given the aforementioned overlap of those within the CHA₂DS₂-VASc score and the definition of metabolic syndrome. We also performed analysis evaluating the association between the number of components of metabolic syndrome and stroke and also assessed the risk of stroke for one additional component of metabolic syndrome, modeled as a discrete continuous variable. Furthermore, we conducted an additional analysis to evaluate the association of metabolic syndrome components with embolic stroke. Lastly, we performed a sensitivity analysis by fitting the Fine-Gray model, a proportional hazards model for the subdistribution of competing risks.¹⁷

Results

Baseline Characteristics

Baseline characteristics of the 1,172 study participants, all of whom had AF, stratified by metabolic syndrome are summarized in Table 1. There were 514 (44%) female participants and 194 (17%) were black. Compared with participants without metabolic syndrome, those with metabolic syndrome were older, had a higher CHA₂DS₂-VASc score, and had higher prevalence of MI, stroke/TIA, and heart failure.

Table 1.

Clinical Characteristics at Time of Atrial Fibrillation Diagnosis, Atherosclerosis Risk in Communities (ARIC) Study

	All	No MetS	MetS
Characteristic	N=1172	N=340	N=832	P-value
Age (Years)	71 +/− 9	68.6 +/− 8	71.6 +/−9	<0.0001
Female sex	514 (44)	143 (42)	371 (45)	0.43
Previous MI	254 (22)	49 (14)	205 (25)	<0.0001
Heart failure	374 (32)	87 (26)	287 (35)	0.003
PAD	125 (11)	32 (9)	93 (11)	0.37
Past stroke/TIA	163 (14)	35 (10)	133 (16)	0.02
CHA2DS2VASc	3.4 +/− 1.8	2.5 +/− 1.6	3.7 +/− 1.7	<0.0001
Black race	194 (17)	48 (14)	146 (18)	0.15
Metabolic syndrome variables
High waist circumference	780 (67)	121 (36)	659 (79)	<0.0001
High triglycerides	624 (53)	26 (8)	598 (72)	<0.0001
Low HDL	704 (60)	52 (15)	652 (78)	<0.0001
Elevated fasting plasma glucose	795 (68)	113 (33)	682 (82)	<0.0001
Diabetes	351 (30)	23 (7)	338 (39)	<0.0001
Elevated blood pressure	955 (81)	190 (56)	765 (92)	<0.0001
Hypertension	819 (70)	156 (46)	663 (80)	<0.0001

^*Data are presented as n (%) or mean +/− standard deviation

^§Abbreviations: Myocardial Infarction (MI), Peripheral Arterial Disease (PAD), Transient

Ischemic Attack (TIA), High-density lipoprotein (HDL).

Elevated blood glucose - Fasting plasma glucose (FPG) ≥100 mg/dL (5.6 mmol/L) or drug treatment for elevated blood glucose and includes participants with diabetes

Elevated blood pressure - Blood pressure ≥130/85 mmHg or drug treatment for elevated blood pressure and includes participants with hypertension

Association of Metabolic Syndrome Components with Ischemic Stroke in AF

There were 113 incident ischemic stroke events occurring among 1,172 participants with AF after a median follow-up of 14.8 years. Of the 113 ischemic stroke events, 59 were classified as embolic and 21 were classified as thrombotic. Of the 21 thrombotic stroke events, 12 were non-lacunar and only 9 were lacunar. Table 2 lists the results of our Cox proportional hazards models for ischemic stroke. Of all the components of the metabolic syndrome, low HDL was the only component that was associated with an increased risk of stroke in AF after adjustment for age, sex, race/study center (model 1, Table 2), HR (95% CI), 1.58 (1.07–2.34). However, after adjustment for CHA₂DS₂-VASc and CHADS₂ variables (models 2 and 3), the association between low HDL and ischemic stroke was attenuated, HR (95% CI), 1.48 (0.99–2.21), P value=0.05 and HR (95% CI) 1.47 (0.99–2.22) P value=0.06 (models 2 and 3 respectively, Table 2). Supplemental Table I lists the results of our Cox proportional hazards models for subgroup analysis of embolic stroke. Low HDL was borderline associated with embolic stroke, HR (95% CI), 1.67 (0.97–2.87), HR (95% CI), 1.60 (0.92–2.78) HR (95% CI), 1.61 (0.93–2.81) (models 1, 2 and 3 respectively, Supplemental Table I in supplemental material) while the other components of the metabolic syndrome were not associated with increased risk of embolic stroke. Supplemental Table II lists the results of our proportional hazards models for the subdistribution of competing risks for models 2 and 3, which did not materially change the aforementioned results in Table 2 (Supplemental Table II in supplemental material). When HDL was modeled as a continuous variable, hazard ratios per standard deviation increment in HDL did not reach statistical significance for models 1–3 (Supplemental Table III in supplemental material).

Table 2.

Association of Metabolic Syndrome Components with Ischemic Stroke in Participants with Atrial Fibrillation, Atherosclerosis Risk in Communities (ARIC) Study

Individual variables	Absent	HR (95% CI), Model 1	P-value	HR (95% CI), Model 2	P-Value	HR (95% CI), Model 3	P-Value
High Waist Circumference	1 (Ref)	0.95 (0.64–1.42)	0.81	0.84 (0.56–1.27)	0.41	0.81 (0.55–1.25)	0.37
High Triglycerides	1 (Ref)	1.33 (0.92–1.94)	0.13	1.22 (0.83–1.80)	0.31	1.20 (0.82–1.77)	0.36
Low HDL	1 (Ref)	1.58 (1.07–2.34)	0.02	1.48 (0.99–2.21)	0.06	1.47 (0.99–2.20)	0.06
Elevated blood pressure	1 (Ref)	1.35 (0.83–2.20)	0.23	1.28 (0.77–2.12)*	0.34	1.24 (0.75–2.05)*	0.40
Elevated fasting plasma glucose	1 (Ref)	1.18 (0.79–1.77)	0.42	1.13 (0.75–1.71)**	0.55	1.12 (0.75–1.69)**	0.58

Model 1: Cox proportional hazards model adjusted for age, sex, race/center

Model 2: Cox proportional hazards model adjusted for age, sex, race/center and the remaining CHA₂DS₂-VASc

variables of stroke/transient ischemic attack, heart failure, hypertension, diabetes,

myocardial infarction, peripheral artery disease and also anticoagulation use.

Model 3: Cox proportional hazards model adjusted for age, sex, race/center and the remaining CHADS₂

variables of stroke/transient ischemic attack, heart failure, hypertension, diabetes and also anticoagulation use.

Ref indicates reference and HDL, High-density lipoprotein.

Ref for prehypertension includes participants without prehypertension or HTN

Ref for prediabetes includes participants without prediabetes or diabetes

^*Not adjusted for hypertension

^**Not adjusted for diabetes

When comparing participants without metabolic syndrome to those meeting diagnostic criteria with three or more of any of the components, metabolic syndrome was not found to be associated with ischemic stroke after adjustment for age, sex, race/study center (model 1), HR (95% CI), 1.36 (0.90–2.07) (Table 3). Utilizing BMI to define central obesity (based on International Diabetes Federation criteria) also did not demonstrate a significant association between the diagnosis of metabolic syndrome and stroke (Table 4).

Table 3.

Association of Metabolic Syndrome (ATP Criteria) with Ischemic Stroke in Participants with Atrial Fibrillation, Atherosclerosis Risk in Communities (ARIC) Study

	No metabolic syndrome	Metabolic syndrome (≥3 components)
N	340	832
# incident stroke	31	82
HR (95% CI), Model 1	1(ref)	1.36 (0.90–2.07)
HR (95% CI), Model 2	1(ref)	1.38 (0.91–2.11)

Model 1: Cox proportional hazards model adjusted for age, sex, race/center

Model 2: Cox proportional hazards model adjusted for age, sex, race/center and the remaining CHA₂DS₂-VASc

variables of stroke/transient ischemic attack, heart failure, myocardial infarction, peripheral artery disease and also anticoagulation use.

Ref indicates reference

Table 4.

Association of Metabolic Syndrome (IDF Criteria) with Ischemic Stroke in Participants with Atrial Fibrillation, Atherosclerosis Risk in Communities (ARIC) Study^*

	No metabolic syndrome	Metabolic syndrome (≥3 components)
N	421	751
# incident stroke	40	73
HR (95% CI), Model 1	1(ref)	1.29 (0.88–1.90)
HR (95% CI), Model 2	1(ref)	1.29 (0.87–1.91)

^*Using BMI to define central obesity (per International Diabetes Federation criteria)

Model 1: Cox proportional hazards model adjusted for age, sex, race/center

Model 2: Cox proportional hazards model adjusted for age, sex, race/center and the remaining CHA₂DS₂-VASc

variables of stroke/transient ischemic attack, heart failure, myocardial infarction and peripheral artery disease

Ref indicates reference

Next, we considered whether having more components of the metabolic syndrome was associated with a higher risk of ischemic stroke. We did not observe a significant association between increasing number of metabolic syndrome components with higher risk of stroke after adjustment for CHA₂DS₂-VASc variables (Table 5). When modeled as a discrete continuous variable, we observed that the risk of stroke increased by 13% for each additional component of metabolic syndrome; this association, however, was borderline significant. (Table 5).

Table 5.

Association of Number of Metabolic Syndrome Components with Ischemic Stroke in Participants with Atrial Fibrillation, Atherosclerosis Risk in Communities (ARIC) Study

Number of components	0–1	2	3	4	5	Per 1 additional component
N	145	195	269	266	297
# incident stroke	11	20	28	24	30
HR (95% CI), Model 1	1(ref)	1.29 (0.62–2.70)	1.50 (0.74–3.02)	1.42 (0.69–2.91)	1.91 (0.95–3.82)	1.12 (0.99–1.27)
HR (95% CI), Model 2	1(ref)	1.26 (0.60–2.64)	1.51 (0.75–3.06)	1.40 (0.68–2.88)	1.93 (0.96–3.90)	1.13 (0.99–1.28)

Model 1: Cox proportional hazards model adjusted for age, sex, race/center

Model 2: Cox proportional hazards model adjusted for age, sex, race/center and the remaining CHA₂DS₂-VASc

variables of stroke/transient ischemic attack, heart failure, myocardial infarction, peripheral artery disease and also anticoagulation use.

Ref indicates reference

Discussion

In this prospective community-based cohort study, metabolic syndrome was not shown to be associated with ischemic stroke in participants with AF. Using a demographically adjusted model, low HDL was the only metabolic syndrome component that was shown to be associated with increased risk of ischemic stroke; the association, however, was borderline significant after adjustment for the CHA₂DS₂-VASc variables. This finding is consistent with a previously established association between low HDL and higher stroke risk in chronic AF.¹⁸ The results of our study are further supported by our competing risk analysis, which found a borderline significant association between low HDL and ischemic stroke. Additional analysis assessing for risk of embolic stroke, which is a mechanism that is more commonly responsible for stroke in AF, also did not significantly change our results.¹⁹

Despite the association of low HDL and increased stroke risk, our findings indicate that a constellation of 3 or more of any components of metabolic syndrome did not confer an increased risk of stroke. Hence, consideration of metabolic syndrome is unlikely to provide additional information on stroke risk assessment beyond the CHA₂DS₂-VASc score. Additionally, our study found that components of metabolic syndrome which overlap with the CHA₂DS₂-VASc score, namely elevated blood pressure and elevated fasting plasma glucose, were not shown to be associated with an increased risk of ischemic stroke. One possible explanation for this finding is that there are subgroups within risk profiles that may confer a higher risk of stroke. For instance, Patti et al. found that patients with AF and diabetes on insulin therapy had a significantly higher risk of thromboembolic events than diabetic patients who were not being treated with insulin.²⁰ Given the inclusion of a broad spectrum of disease from prediabetes to advanced diabetes requiring insulin, patients fitting the metabolic syndrome criteria for elevated fasting plasma glucose likely have varying degrees of stroke risk.

Our results are also in contrast to the findings of a study including 721 Taiwanese patients with AF, which found metabolic syndrome components to be associated with greater thromboembolic risk.¹⁰ This study by Tsai and colleagues demonstrated a graded association between increasing number of components of metabolic syndrome and higher risk of thromboembolic events and found that the proposed CHADS₂ –Metabolic syndrome score was superior to the CHADS₂ score in predicting thromboembolic risk.¹⁰ In our study, we observed that the risk of ischemic stroke increased by 12% for one additional component of the metabolic syndrome, but the association was borderline significant.

There are several differences between our study and the study conducted by Tsai and colleagues which provide potential explanations for these discrepant findings. One possible explanation is the different racial compositions of both studies: ARIC is comprised of black and white participants and patients in the study by Tsai and colleagues are Han Chinese. Racial differences may be important in regards to the prognostic significance of metabolic syndrome and its components. For example, Tsai et al. found BMI >30 to be associated with increased risk of thromboembolic events HR (95% CI), 1.44 (1.15–1.80).¹⁰ Previous studies indicate that metabolic responses to central obesity—with regards to cardiovascular risk factors such as hypertension, hyperglycemia and dyslipidemia—may be greater in South and East Asians than in Caucasians at given BMIs.²¹ The difference in metabolic risk at a fixed level of obesity, which is felt to be related in part to a higher percentage of body fat accumulation in Asians than Caucasians, may explain why our study did not find an association between BMI >30, or increased waist circumference, and stroke.²¹

Another potential explanation for conflicting results can be attributed to different primary endpoints. Our study looked strictly at ischemic stroke as a primary endpoint while the other study assessed for thromboembolic events, including ischemic stroke as well as peripheral embolic events and acute coronary syndrome. Lastly, our study excluded participants on anticoagulation, a potential confounding variable, while 56.9% and 13.5% in the other study’s participants were on aspirin and warfarin, respectively.

The strengths of our study include a community-based sample with extensive and rigorous measurement of covariates and long follow-up. Our study has several limitations. First, with a relatively small sample size of 1,172 participants with 113 total stroke events occurring over a nearly 15 year follow up period, it is possible that the study was underpowered to detect an association between metabolic syndrome and stroke. Secondly, incident AF was identified mostly from hospitalization discharges and we could have missed asymptomatic AF or AF managed exclusively in an outpatient setting. However, we and others have previously shown that the validity of AF ascertainment using hospitalizations is acceptable^13,22 and that incidence rates of AF in ARIC are consistent with other population-based studies.^13,22

Conclusion

In conclusion, our report—from a community based-cohort study with close to 15 years of follow-up—suggests that the metabolic syndrome is not significantly associated with ischemic stroke in AF after adjustment for CHA₂DS₂-VASc variables. Given the contrasting findings between our study and that of Tsai and colleagues, future studies could be pursued with larger sample sizes including individuals of different races and greater numbers of stroke events. In additional, further research is warranted to identify novel risk factors for stroke-related AF.