Methods

The SCCS is an ongoing prospective cohort study that enrolled >85,000 adults aged 40 to 79 years residing in 12 states in the southeastern United States from 2002 to 2009. The SCCS design and methods have been described in detail previously. In this report, we focus on the black and white SCCS participants who were aged ≥65 years on or before December 31, 2008, and were recruited at participating community health centers (CHCs), institutions that provide primary health and preventive services in medically underserved populations. The restriction to those aged ≥65 years ensured that the black and white participants had generally similar coverage in Medicare, from which AF diagnoses were ascertained. The restriction to those enrolled in CHCs (representing most SCCS participants) ensured that the participants were of similar socioeconomic status and had generally equal access to health care regardless of race at cohort entry.

Upon entry into the SCCS, participants were administered a baseline computer-assisted personal interview at the CHC (available at http://www.southerncommunitystudy.org ), which ascertained information about demographic characteristics, personal and family medical histories, height, weight, tobacco and alcohol use history, and other factors. Many of the questions on the SCCS questionnaire were adapted from questionnaires used and validated in other settings, and a series of validation studies have also demonstrated the high reliability of the questionnaire within the SCCS population for variables such as tobacco use status, self-reported diseases, height, and weight. The questionnaire responses enabled us to characterize patients with AF with respect to various characteristics and assess how they differed from similar SCCS participants without AF.

Diagnoses of AF among cohort members were ascertained by linkage, using Social Security number, date of birth, and gender, of the cohort with national Centers for Medicare and Medicaid Services Research Identifiable Files from January 1, 1999, through December 31, 2008 (the latest date for which data were available). Patients with AF were defined as Medicare beneficiaries aged ≥65 years with ≥1 medical claim with an International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis code of 427.3 (AF and atrial flutter) within the Medicare institutional (Medicare Provider Analysis and Review), Part B carrier, or outpatient base claims files from 1999 through 2008. A comparison population of SCCS participants without AF was defined as Medicare beneficiaries aged ≥65 years with no AF medical claims but with ≥1 non-AF medical claim within the Medicare institutional (Medicare Provider Analysis and Review), Part B carrier, or outpatient base claims files during the same time period. Follow-up of the participants for mortality was accomplished by linkages with the Social Security Administration vital status service for epidemiologic researchers and the National Death Index. All study procedures were approved by the institutional review boards of Vanderbilt University Medical Center and Meharry Medical College.

Chi-square tests were used to compare crude percentage distributions of patients with versus without AF and between blacks and whites. Multivariate logistic regression analyses were used to estimate odds ratios (ORs) and corresponding 95% confidence intervals (CI) as measures of association between AF prevalence and participant characteristics. Analyses were performed separately for blacks and whites and for men and women, as well as for race and gender groups combined. ORs of AF were calculated in relation to the following demographic, lifestyle, anthropometric, and medical history variables reported at baseline: race (black or white); gender (male or female); age (years) at the end of follow-up (December 31, 2008, or the date of death if earlier); height (<68, 68–<72, or ≥72 inches for men and <63, 63–<66, or ≥66 inches for women); body mass index, classified as underweight (<18.5 kg/m ² ), normal (18.5–24.9 kg/m ² ), overweight (25–29.9 kg/m ² ), obese (30–39.9 kg/m ² ) or extremely obese (≥40 kg/m ² ); cigarette smoking status (ever or never); alcohol drinking, classified as none, moderate (≤3 drinks/day), or heavy (>3 drinks/day); self-reported history (yes or no) of diagnosed hypertension, diabetes, stroke, high cholesterol, and myocardial infarction (MI) or coronary artery bypass grafting (CABG). Population-attributable fraction was calculated to determine the race-specific impact of the clinical risk factors in the model (MI or CABG, hypertension, diabetes, and stroke) on AF occurrence using the following formula: population-attributable fraction = pd _i [(RR _i − 1)/RR _i ], where pd _i is the proportion of cases with ith exposure, and RR is the OR comparing ith exposure with unexposed group (i = 0). All analyses were conducted using SAS version 9.2 (SAS Institute, Inc., Cary, North Carolina).

To gain insight into the clinical features of AF in this study population and whether they differed between blacks and whites, we ascertained, for each participant with AF, the presence within his or her Medicare claims history of certain medical diagnoses associated with AF, including essential hypertension (International Classification of Diseases, Ninth Revision, Clinical Modification code 401), congestive heart failure (code 428.0), coronary atherosclerosis (code 414.0), diabetes mellitus (code 250), long-term use of anticoagulants (code V586.1), and mitral or aortic valve disease (codes 394–397 and 398.9). Finally, we conducted secondary analyses restricted to cases diagnosed with AF after entry into the SCCS.

Results

The 8,836 SCCS Medicare-eligible participants (5,810 blacks and 3,026 whites) experienced a total of 50,641 person-years of Medicare coverage from January 1, 1999, to December 31, 2008 (mean 5.8 years for blacks and 5.6 years for whites). We identified 1,062 patients (617 blacks and 445 whites) with ≥1 diagnosis of AF over this period, corresponding to a significantly (p <0.0001) lower overall (crude) prevalence of 11% among blacks compared to 15% among whites ( Table 1 ). The mean age of patients with AF at the end of follow-up (or death), regardless of race or gender, was approximately 73 years, compared to 71 years among those without AF. Those with versus without AF were more likely to be male (p <0.001), tall (p <0.001), and obese (p = 0.03), although with the exception of extreme obesity (body mass index ≥40 kg/m ² ), the association with obesity appeared to be restricted to whites. The frequency of smoking was slightly higher, while the frequency of heavy drinking was similar, among those with versus without AF. History of hypertension was very common in this elderly study population, reported by 83% of patients with AF overall, compared to 77% of those without AF (p <0.001), an excess seen among blacks and whites. Diabetes, stroke, and MI or CABG also were reported substantially more frequently by those with AF than without AF (p ≤0.001 for all comparisons, overall and separately for blacks and whites).

Table 2 lists ORs and 95% CIs for the association between baseline characteristics and AF for the study population overall, as well as separately by race and by gender. After taking into account all the factors listed in Table 2 , blacks continued to have a substantially and significantly reduced OR for AF compared to whites (OR 0.64, 95% CI 0.55 to 0.73). Table 2 also indicates that men were at significantly higher risk for AF compared to women, and being taller than average height was significantly associated with AF, while being shorter was nonsignificantly inversely associated, a pattern that held among men and women. A U-shaped association was apparent between body mass index and AF, with increased ORs among those who were underweight and those who were obese or extremely obese, but only the latter was statistically significant (OR 1.59, 95% CI 1.20 to 2.12). Compared to no alcohol use, heavy but not moderate alcohol use was nonsignificantly positively associated with AF. Aside from age, the strongest risk factor for AF in this population was a history of MI or CABG, which was associated with a 2.4-fold increased risk for AF. Hypertension, diabetes, and stroke were also significantly associated, although less strongly, with increased risk for AF, with ORs of 1.29, 1.33, and 1.55, respectively.

Table 2

Logistic regression–derived odds ratios and 95% confidence intervals for the association between baseline characteristics and atrial fibrillation in the Southern Community Cohort Study, overall and by race and gender

	All	Blacks	Whites	Men	Women
Age (years)
65–69 (reference)
70–74	2.10 (1.54–2.87)	2.12 (1.42–3.18)	2.12 (1.29–3.46)	1.62 (1.00–2.63	2.59 (1.72–3.91)
75–85	3.93 (2.54–6.08)	3.73 (2.13–6.54)	4.40 (2.19–8.87)	2.57 (1.30–5.09)	5.50 (3.10–9.77)
Gender
Female (reference)				—	—
Male	1.43 (1.22–1.66)	1.53 (1.25–1.87)	1.27 (1.00–1.61)	—	—
Race
White (reference)		—	—
Black	0.64 (0.55–0.73)	—	—	0.72 (0.57–0.90)	0.58 (0.48–0.69)
Height ⁎
Short	0.86 (0.71–1.05)	0.94 (0.75–1.18)	0.76 (0.58–0.99)	0.90 (0.68–1.18)	0.83 (0.67–1.04)
Average (reference)
Tall	1.43 (1.22–1.68)	1.36 (1.10–1.67)	1.56 (1.21–2.01)	1.52 (1.18–1.97)	1.38 (1.13–1.69)
Body mass index (kg/m 2 )
<18.5	1.80 (1.04–3.12)	1.53 (0.71–3.27)	2.18 (0.97–4.87)	2.47 (1.14–5.38)	1.27 (0.56–2.87)
18.5–24.9 (reference)
25–29.9	0.86 (0.71–1.05)	0.79 (0.61–1.03)	0.97 (0.71–1.31)	0.86 (0.64–1.15)	0.90 (0.69–1.18)
30–39.9	1.10 (0.90–1.33)	0.90 (0.69–1.16)	1.49 (1.11–2.01)	1.27 (0.94–1.72)	1.06 (0.82–1.38)
≥40	1.59 (1.20–2.12)	1.48 (1.04–2.12)	1.73 (1.06–2.81)	1.07 (0.54–2.11)	1.72 (1.23–2.41)
Smoker
Never (reference)
Ever	1.09 (0.94–1.26)	1.13 (0.93–1.36)	1.04 (0.83–1.31)	0.99 (0.76–1.27)	1.15 (0.96–1.37)
Alcohol drinker
None (reference)
Moderate	0.79 (0.66–0.93)	0.67 (0.53–0.85)	0.95 (0.74–1.22)	0.83 (0.65–1.06)	0.74 (0.58–0.94)
Heavy	1.19 (0.80–1.77)	0.98 (0.60–1.61)	1.52 (0.77–3.03)	0.94 (0.60–1.48)	2.72 (1.18–6.26)
MI or CABG	2.38 (2.01–2.81)	2.46 (1.97–3.07)	2.34 (1.82–3.02)	2.35 (1.82–3.03)	2.44 (1.95–3.06)
Hypertension	1.29 (1.07–1.55)	1.37 (1.05–1.80)	1.19 (0.92–1.54)	1.18 (0.90–1.55)	1.38 (1.07–1.78)
Diabetes	1.33 (1.14–1.54)	1.38 (1.15–1.66)	1.25 (0.98–1.59)	0.99 (0.77–1.28)	1.56 (1.30–1.88)
Stroke	1.55 (1.29–1.87)	1.61 (1.26–2.05)	1.47 (1.11–1.97)	1.35 (1.01–1.82)	1.72 (1.36–2.18)
High cholesterol	0.94 (0.81–1.08)	0.96 (0.80–1.15)	0.92 (0.73–1.16)	0.93 (0.73–1.18)	0.97 (0.81–1.16)

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related

Related posts:

1. Improving the Positive Predictive Value of Exercise Testing in Women for Coronary Artery Disease
2. Capecitabine -Induced Chest Pain Relieved by Diltiazem
3. Application of the Seattle Heart Failure Model in Patients >80 Years of Age Enrolled in a Tertiary Care Heart Failure Clinic
4. Usefulness of Hemoglobin Level to Predict Long-Term Mortality in Patients With Asymptomatic Carotid Narrowing by Ultrasonography

Stay updated, free articles. Join our Telegram channel

Join