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Vol. 183, No. 11 DOI: 10.1093/aje/kwv278 Advance Access publication: May 5, 2016
Original Contribution Measures of Body Size and Composition and Risk of Incident Atrial Fibrillation in Older People The Cardiovascular Health Study
Maria G. Karas, Laura M. Yee, Mary L. Biggs, Luc Djoussé, Kenneth J. Mukamal, Joachim H. Ix, Susan J. Zieman, David S. Siscovick, John S. Gottdiener, Michael A. Rosenberg, Richard A. Kronmal, Susan R. Heckbert, and Jorge R. Kizer* * Correspondence to Dr. Jorge R. Kizer, Cardiovascular Clinical Research Unit, Department of Medicine, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461 ( [email protected]).
Initially submitted June 1, 2015; accepted for publication October 5, 2015.
Various anthropometric measures, including height, have been associated with atrial fibrillation (AF). This raises questions about the appropriateness of using ratio measures such as body mass index (BMI), which contains height squared in its denominator, in the evaluation of AF risk. Among older adults, the optimal anthropometric approach to risk stratification of AF remains uncertain. Anthropometric and bioelectrical impedance measures were obtained from 4,276 participants (mean age = 72.4 years) free of cardiovascular disease in the Cardiovascular Health Study. During follow-up (1989–2008), 1,050 cases of AF occurred. BMI showed a U-shaped association, whereas height, weight, waist circumference, hip circumference, fat mass, and fat-free mass were linearly related to incident AF. The strongest adjusted association occurred for height (per each 1-standard-deviation increment, hazard ratio = 1.38, 95% confidence interval: 1.25, 1.51), which exceeded all other measures, including weight (hazard ratio = 1.21, 95% confidence interval: 1.13, 1.29). Combined assessment of log-transformed weight and height showed regression coefficients that departed from the 1 to −2 ratio inherent in BMI, indicating a loss of predictive information. Risk estimates for AF tended to be stronger for hip circumference than for waist circumference and for fat-free mass than for fat mass, which was explained largely by height. These findings highlight the prominent role of body size and the inadequacy of BMI as determinants of AF in older adults. aging; atrial fibrillation; body size; obesity
Abbreviations: AF, atrial fibrillation; BMI, body mass index; CHS, Cardiovascular Health Study; HC, hip circumference; WC, waist circumference; WHR, waist-to-hip ratio.
Atrial fibrillation (AF), the most common sustained cardiac dysrhythmia (1), is a growing public health concern among aging populations worldwide (2). In addition to being an independent risk factor for stroke (3), AF has been linked to higher risks of heart failure (4), cognitive decline (5), and death (6). Together with aging trends, the global prevalence of obesity has registered a marked increase (7). It has been shown in multiple prior studies that excess adiposity, as defined by elevated body mass index (BMI) (8–11) or waist circumference (WC) (12), increases the risk of AF. Although the mechanisms linking obesity to AF are not well defined, proposed mediators include
hypertension, diabetes, chronic inflammation, and obstructive sleep apnea, along with left ventricular diastolic dysfunction and left atrial enlargement (13–17). Given the intersection of aging, obesity, and AF, a key question is the extent to which body composition in older adults might determine the higher incidence of AF later in life. Because aging is associated with an increase in adipose mass and its central redistribution (18), along with a decrease in skeletal muscle mass (19), the same relationships between adiposity and AF that have been documented in younger individuals may not apply equally in older people. Moreover, beyond adiposity measures, taller heights 998
Am J Epidemiol. 2016;183(11):998–1007
Anthropometry and Atrial Fibrillation 999
(20–22) and larger hip circumferences (HCs) (21, 23) have been shown to be significantly associated with the risk of AF. These findings suggest that BMI, which includes height squared in its denominator, may not be the best anthropometric variable for assessing AF risk. They also raise questions about the suitability of waist-to-hip ratio (WHR) for capturing AF risk. In this regard, both fat mass and fat-free mass were recently associated with a higher risk of AF in a middle-aged cohort (21), but the corresponding associations of adipose and lean body mass in older adults have not been examined. We therefore investigated the relationships of various measures of body size and composition with incident AF in the Cardiovascular Health Study (CHS), a large cohort study of older adults with a high number of AF events. METHODS
sex (0 = women, 1 = men) (27). Fat mass was calculated as body weight minus fat-free mass. Definition of other covariates
Participants answered standard questionnaires regarding smoking, alcohol intake, and self-assessed health status. Recent smokers were defined as those who quit within the past 5 years. Physical activity level was determined using a validated questionnaire (28). Blood samples collected after a 12-hour overnight fast were processed for biochemical testing (29). Diabetes was defined as having a fasting glucose level of 126 mg/dL or higher or use of hypoglycemic therapy. Echocardiography performed at baseline on the original cohort, but not the supplementary cohort, included M-mode measurement of left atrial anteroposterior diameter (24).
Study population
AF events
CHS is a prospective study of cardiovascular risk factors among community-dwelling people 65 years of age or older (24). Individuals were recruited from Medicare eligibility lists and examined at 4 field centers across the United States (24, 25). The original cohort consisted of 5,201 individuals who enrolled in 1989–1990, with a supplementary cohort of 687 black participants enrolled in 1992–1993. Health evaluations were conducted for all participants using standardized protocols (24, 25). In the present study, subjects with prevalent AF (n = 157) were excluded, as were those with prevalent cardiovascular disease (n = 1,410), because the latter can alter the usual relations of adiposity measures with adverse outcomes. Prevalent cardiovascular disease comprised coronary heart disease, stroke, transient ischemic attack, heart failure, and peripheral arterial disease. These conditions were ascertained through the use of questionnaires, review of medical records, or adjudication of prior events by specialized committees. After additional exclusion of participants with missing data on anthropometric variables (n = 45), there were 4,276 participants eligible for evaluation.
Annual study clinic visits were conducted for all CHS participants for 10 years, with interim telephone contacts every 6 months. Thereafter, telephone contacts were made every 6 months. In addition, information on all hospitalizations was collected. Incident cases of AF were diagnosed through June 2008 from 12-lead electrocardiograms taken at the annual study clinic visits (30) or from discharge diagnosis codes, except when these accompanied coronary artery bypass or valve replacement surgery (31). Prior work in CHS has shown that the positive predictive value of hospital discharge codes for diagnosing AF was 98.6% compared with direct review of medical records (31).
Baseline assessment of body size and composition
Anthropometric measurements were obtained by trained personnel using standardized methods (26). Height was measured in centimeters using a stadiometer. Weight was measured in pounds using a balance beam scale while participants were wearing examination gowns and no shoes. WC and HC were measured at the level of the umbilicus and the maximal protrusion of the gluteal muscles, respectively. BMI was calculated as weight in kilograms divided by height in meters squared. WHR was calculated as WC divided by HC. Participants also underwent bioelectrical impedance analysis. Resistance was measured at 50 kHz in the supine position using a TVI-10 Body Composition Analyzer (Danninger Medical, Columbus, Ohio) attached to 4 adhesive electrocardiographic electrodes placed in the standard distal positions on the dorsum of the right hand and foot. Fat-free mass was calculated as (6,710) × (ht 2/R) + (3.1 × S) + 3.9, where ht 2 was standing height in meters squared, R was resistance in ohms, and S was Am J Epidemiol. 2016;183(11):998–1007
Statistical analysis
Levels of baseline covariates were described across sexspecific quintiles of height. Spearman correlation coefficients among measures of body size and composition were computed. The functional forms of the associations of anthropometric and bioelectric impedance variables with AF were evaluated using penalized cubic splines (32). Cox models were used to estimate the relative risk of AF associated with BMI, weight, height, WC, HC, WHR, fat mass, and fat-free mass. On the basis of assessment of penalized cubic splines, BMI was modeled using a linear plus quadratic term, whereas all other measures were modeled using linear terms. For each measure of body size/composition, 3 models were evaluated: 1) a model adjusted for demographic characteristics, including age, sex, and race; 2) a model additionally adjusted for the confounders smoking status, physical activity level, alcohol consumption, estrogen therapy use, and serum creatinine level; and 3) a model further adjusted for mediators, such as hypertension and dysglycemia measures, lipid fractions, and C-reactive protein concentration. The additional impact of adjustment of individual anthropometric and bioelectric impedance parameters for other such parameters was subsequently examined in these models. Assessment for interactions of body size/composition measures by age, sex, or race involved inclusion of cross-product terms. In sensitivity analyses, we restricted evaluation to 1) never smokers and smokers who quit less than 5 years earlier;
Quintile of Height a
Covariate
b
1 (n = 918) Mean (SD)
Age, years
3c (n = 859)
2 (n = 833) No.
%
74.2 (6.0)
Mean (SD)
No.
%
73.0 (5.7)
Mean (SD)
4d (n = 850) No.
%
72.2 (5.2)
Mean (SD)
5e (n = 816) No.
%
71.4 (4.8)
Mean (SD)
No.
%
70.9 (4.6)
Male sex
360 39.2
313 37.6
349 40.6
291 34.2
327 40.1
Black race
129 14.1
119 14.3
134 15.6
136 16.0
135 16.5
Systolic blood pressure, mm Hg
140 (22)
137 (21)
137 (21)
133 (21)
134 (21)
Diastolic blood pressure, mm Hg
71 (11)
71 (11)
71 (11)
71 (11)
73 (12)
Antihypertensive medication use
368 40.1
340 40.8
323 37.6
325 38.2
299 36.6
Impaired fasting glucose level
109 13.8
105 14.3
106 14.2
96 13.3
98 14.1
Diabetes
128 13.9
99 11.9
111 12.9
128 15.1
120 14.7
Never
481 52.4
416 49.9
411 47.8
378 44.5
366 44.9
Former
351 38.2
303 36.4
342 39.8
350 41.2
351 43.0
9.4
114 13.7
106 12.3
122 14.4
99 12.1
0
500 54.5
416 49.9
396 46.1
391 46.0
384 47.1
Vol. 183, No. 11 DOI: 10.1093/aje/kwv278 Advance Access publication: May 5, 2016
Original Contribution Measures of Body Size and Composition and Risk of Incident Atrial Fibrillation in Older People The Cardiovascular Health Study
Maria G. Karas, Laura M. Yee, Mary L. Biggs, Luc Djoussé, Kenneth J. Mukamal, Joachim H. Ix, Susan J. Zieman, David S. Siscovick, John S. Gottdiener, Michael A. Rosenberg, Richard A. Kronmal, Susan R. Heckbert, and Jorge R. Kizer* * Correspondence to Dr. Jorge R. Kizer, Cardiovascular Clinical Research Unit, Department of Medicine, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461 ( [email protected]).
Initially submitted June 1, 2015; accepted for publication October 5, 2015.
Various anthropometric measures, including height, have been associated with atrial fibrillation (AF). This raises questions about the appropriateness of using ratio measures such as body mass index (BMI), which contains height squared in its denominator, in the evaluation of AF risk. Among older adults, the optimal anthropometric approach to risk stratification of AF remains uncertain. Anthropometric and bioelectrical impedance measures were obtained from 4,276 participants (mean age = 72.4 years) free of cardiovascular disease in the Cardiovascular Health Study. During follow-up (1989–2008), 1,050 cases of AF occurred. BMI showed a U-shaped association, whereas height, weight, waist circumference, hip circumference, fat mass, and fat-free mass were linearly related to incident AF. The strongest adjusted association occurred for height (per each 1-standard-deviation increment, hazard ratio = 1.38, 95% confidence interval: 1.25, 1.51), which exceeded all other measures, including weight (hazard ratio = 1.21, 95% confidence interval: 1.13, 1.29). Combined assessment of log-transformed weight and height showed regression coefficients that departed from the 1 to −2 ratio inherent in BMI, indicating a loss of predictive information. Risk estimates for AF tended to be stronger for hip circumference than for waist circumference and for fat-free mass than for fat mass, which was explained largely by height. These findings highlight the prominent role of body size and the inadequacy of BMI as determinants of AF in older adults. aging; atrial fibrillation; body size; obesity
Abbreviations: AF, atrial fibrillation; BMI, body mass index; CHS, Cardiovascular Health Study; HC, hip circumference; WC, waist circumference; WHR, waist-to-hip ratio.
Atrial fibrillation (AF), the most common sustained cardiac dysrhythmia (1), is a growing public health concern among aging populations worldwide (2). In addition to being an independent risk factor for stroke (3), AF has been linked to higher risks of heart failure (4), cognitive decline (5), and death (6). Together with aging trends, the global prevalence of obesity has registered a marked increase (7). It has been shown in multiple prior studies that excess adiposity, as defined by elevated body mass index (BMI) (8–11) or waist circumference (WC) (12), increases the risk of AF. Although the mechanisms linking obesity to AF are not well defined, proposed mediators include
hypertension, diabetes, chronic inflammation, and obstructive sleep apnea, along with left ventricular diastolic dysfunction and left atrial enlargement (13–17). Given the intersection of aging, obesity, and AF, a key question is the extent to which body composition in older adults might determine the higher incidence of AF later in life. Because aging is associated with an increase in adipose mass and its central redistribution (18), along with a decrease in skeletal muscle mass (19), the same relationships between adiposity and AF that have been documented in younger individuals may not apply equally in older people. Moreover, beyond adiposity measures, taller heights 998
Am J Epidemiol. 2016;183(11):998–1007
Anthropometry and Atrial Fibrillation 999
(20–22) and larger hip circumferences (HCs) (21, 23) have been shown to be significantly associated with the risk of AF. These findings suggest that BMI, which includes height squared in its denominator, may not be the best anthropometric variable for assessing AF risk. They also raise questions about the suitability of waist-to-hip ratio (WHR) for capturing AF risk. In this regard, both fat mass and fat-free mass were recently associated with a higher risk of AF in a middle-aged cohort (21), but the corresponding associations of adipose and lean body mass in older adults have not been examined. We therefore investigated the relationships of various measures of body size and composition with incident AF in the Cardiovascular Health Study (CHS), a large cohort study of older adults with a high number of AF events. METHODS
sex (0 = women, 1 = men) (27). Fat mass was calculated as body weight minus fat-free mass. Definition of other covariates
Participants answered standard questionnaires regarding smoking, alcohol intake, and self-assessed health status. Recent smokers were defined as those who quit within the past 5 years. Physical activity level was determined using a validated questionnaire (28). Blood samples collected after a 12-hour overnight fast were processed for biochemical testing (29). Diabetes was defined as having a fasting glucose level of 126 mg/dL or higher or use of hypoglycemic therapy. Echocardiography performed at baseline on the original cohort, but not the supplementary cohort, included M-mode measurement of left atrial anteroposterior diameter (24).
Study population
AF events
CHS is a prospective study of cardiovascular risk factors among community-dwelling people 65 years of age or older (24). Individuals were recruited from Medicare eligibility lists and examined at 4 field centers across the United States (24, 25). The original cohort consisted of 5,201 individuals who enrolled in 1989–1990, with a supplementary cohort of 687 black participants enrolled in 1992–1993. Health evaluations were conducted for all participants using standardized protocols (24, 25). In the present study, subjects with prevalent AF (n = 157) were excluded, as were those with prevalent cardiovascular disease (n = 1,410), because the latter can alter the usual relations of adiposity measures with adverse outcomes. Prevalent cardiovascular disease comprised coronary heart disease, stroke, transient ischemic attack, heart failure, and peripheral arterial disease. These conditions were ascertained through the use of questionnaires, review of medical records, or adjudication of prior events by specialized committees. After additional exclusion of participants with missing data on anthropometric variables (n = 45), there were 4,276 participants eligible for evaluation.
Annual study clinic visits were conducted for all CHS participants for 10 years, with interim telephone contacts every 6 months. Thereafter, telephone contacts were made every 6 months. In addition, information on all hospitalizations was collected. Incident cases of AF were diagnosed through June 2008 from 12-lead electrocardiograms taken at the annual study clinic visits (30) or from discharge diagnosis codes, except when these accompanied coronary artery bypass or valve replacement surgery (31). Prior work in CHS has shown that the positive predictive value of hospital discharge codes for diagnosing AF was 98.6% compared with direct review of medical records (31).
Baseline assessment of body size and composition
Anthropometric measurements were obtained by trained personnel using standardized methods (26). Height was measured in centimeters using a stadiometer. Weight was measured in pounds using a balance beam scale while participants were wearing examination gowns and no shoes. WC and HC were measured at the level of the umbilicus and the maximal protrusion of the gluteal muscles, respectively. BMI was calculated as weight in kilograms divided by height in meters squared. WHR was calculated as WC divided by HC. Participants also underwent bioelectrical impedance analysis. Resistance was measured at 50 kHz in the supine position using a TVI-10 Body Composition Analyzer (Danninger Medical, Columbus, Ohio) attached to 4 adhesive electrocardiographic electrodes placed in the standard distal positions on the dorsum of the right hand and foot. Fat-free mass was calculated as (6,710) × (ht 2/R) + (3.1 × S) + 3.9, where ht 2 was standing height in meters squared, R was resistance in ohms, and S was Am J Epidemiol. 2016;183(11):998–1007
Statistical analysis
Levels of baseline covariates were described across sexspecific quintiles of height. Spearman correlation coefficients among measures of body size and composition were computed. The functional forms of the associations of anthropometric and bioelectric impedance variables with AF were evaluated using penalized cubic splines (32). Cox models were used to estimate the relative risk of AF associated with BMI, weight, height, WC, HC, WHR, fat mass, and fat-free mass. On the basis of assessment of penalized cubic splines, BMI was modeled using a linear plus quadratic term, whereas all other measures were modeled using linear terms. For each measure of body size/composition, 3 models were evaluated: 1) a model adjusted for demographic characteristics, including age, sex, and race; 2) a model additionally adjusted for the confounders smoking status, physical activity level, alcohol consumption, estrogen therapy use, and serum creatinine level; and 3) a model further adjusted for mediators, such as hypertension and dysglycemia measures, lipid fractions, and C-reactive protein concentration. The additional impact of adjustment of individual anthropometric and bioelectric impedance parameters for other such parameters was subsequently examined in these models. Assessment for interactions of body size/composition measures by age, sex, or race involved inclusion of cross-product terms. In sensitivity analyses, we restricted evaluation to 1) never smokers and smokers who quit less than 5 years earlier;
Quintile of Height a
Covariate
b
1 (n = 918) Mean (SD)
Age, years
3c (n = 859)
2 (n = 833) No.
%
74.2 (6.0)
Mean (SD)
No.
%
73.0 (5.7)
Mean (SD)
4d (n = 850) No.
%
72.2 (5.2)
Mean (SD)
5e (n = 816) No.
%
71.4 (4.8)
Mean (SD)
No.
%
70.9 (4.6)
Male sex
360 39.2
313 37.6
349 40.6
291 34.2
327 40.1
Black race
129 14.1
119 14.3
134 15.6
136 16.0
135 16.5
Systolic blood pressure, mm Hg
140 (22)
137 (21)
137 (21)
133 (21)
134 (21)
Diastolic blood pressure, mm Hg
71 (11)
71 (11)
71 (11)
71 (11)
73 (12)
Antihypertensive medication use
368 40.1
340 40.8
323 37.6
325 38.2
299 36.6
Impaired fasting glucose level
109 13.8
105 14.3
106 14.2
96 13.3
98 14.1
Diabetes
128 13.9
99 11.9
111 12.9
128 15.1
120 14.7
Never
481 52.4
416 49.9
411 47.8
378 44.5
366 44.9
Former
351 38.2
303 36.4
342 39.8
350 41.2
351 43.0
9.4
114 13.7
106 12.3
122 14.4
99 12.1
0
500 54.5
416 49.9
396 46.1
391 46.0
384 47.1
