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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Am J Cardiol. Author manuscript; available in PMC 2012 July 15.
Published in final edited form as:
PMCID: PMC3126875
NIHMSID: NIHMS294054

Relation of Low Body Mass Index to Low Urinary Creatinine Excretion Rate in Patients with Coronary Heart Disease

Nisha Bansal, MD MAS,a Chi-yuan Hsu, MD MSc,a Shoujun Zhao, PhD,b Mary A. Whooley, MD,a,b,c and Joachim H. Ix, MD MASd,e,f

Abstract

In patients with prevalent coronary heart disease (CHD), studies have found a paradoxical relationship in that patients with higher body mass index (BMI) have lower mortality. One possibility is that individuals with higher BMI have greater muscle mass; and higher BMI may be a marker of better overall health status. We evaluated whether the paradoxical association of BMI with mortality in CHD patients is attenuated when accounting for urinary creatinine excretion, a marker of muscle mass. The Heart and Soul Study is an observational study of outpatients with stable CHD designed to investigate the influence of psychosocial factors on the progression of CHD. Outpatient 24-hour timed urine collections were obtained. Participants were followed up for death for 5.9 (± 1.9) years. Cox proportional hazards models evaluate the association between sex-specific BMI quintiles and mortality. There were 886 participants in our study population. Participants in higher quintiles of BMI were younger, more likely to have diabetes mellitus and hypertension and had higher urinary creatinine excretion rate. Compared to the lowest BMI quintile, subjects in higher BMI quintiles were less likely to die during follow-up. Adjustment for major demographic variables, traditional cardiovascular risk factors and kidney function did not attenuate the relationship. Additional adjustment for urinary creatinine excretion rate did not materially change the association between BMI and all-cause mortality. In conclusion, low muscle mass and low BMI are each associated with greater all-cause mortality, however low muscle mass does not appear to explain why CHD patients with low BMI have worse survival.

Keywords: muscle, BMI, mortality, CHD

INTRODUCTION

Using urinary creatinine excretion rate as an indirect measure of muscle mass, we demonstrated in a prior study that lower urinary creatinine excretion rate was strongly associated with mortality independent of conventional measures of body composition, kidney function, and traditional cardiovascular risk factors among patients with coronary heart disease (CHD).1 Thus, both low creatinine excretion rate and low body mass index (BMI) are markers of greater risk of death in persons with CHD. What is unknown, however, is whether the association of low BMI with mortality in patients with CHD24 is explained by low muscle mass. To that end, we evaluate the association of BMI with mortality in outpatients with stable CHD to determine whether the association is attenuated when accounting for urinary creatinine excretion, a marker of muscle mass.

METHODS

The Heart and Soul Study is an observational study designed to investigate the influence of psychosocial factors on the progression of CHD. Methods have been described previously.5 Briefly, participants were recruited from outpatient clinics in the San Francisco Bay Area if they met one of the following inclusion criteria: history of myocardial infarction or coronary revascularization, angiographic evidence of > 50% stenosis in ≥ 1 coronary vessels, exercise-induced ischemia by treadmill or nuclear testing, or documented diagnosis of CHD. Participants were excluded if they were unable to walk 1 block, experienced myocardial infarction in the past 6 months, or were likely to move out of the area within 3 years. The study protocol was approved by the Institutional Review Boards of participating institutions, and all participants provided written informed consent. Between September 2000 and December 2002, 1024 participants enrolled and underwent a baseline study appointment that included a medical history, physical examination, and health status questionnaire. Outpatient 24-hour timed urine collections and fasting (12-hour) morning venous blood samples were obtained. Participants were followed through June 30, 2009. For the present analysis, we excluded participants with missing urine collections (N=57) or missing covariate data (N=81), providing a final analytic sample of 886 (87%) participants.

The protocol for timed urine collection has been described previously.6 In brief, participants received instructions on urine collection and specimen refrigeration. They were asked to void at the end of their study appointment and to begin the collection from that point forward. Research personnel arrived at the patient’s home 24 hours after the timed collection was initiated. If patients reported missing any urine or collections were < 1 or > 3 liters, collections were repeated. If participants were unable to collect all urine, no data were recorded. Urine volume was recorded (mL), and creatinine was measured by the rate Jaffe method. Urinary creatinine excretion was calculated in milligrams per day (urine volume [mL] times urine creatinine [mg/dL] divided by 100).

Between the baseline examination and May 1, 2009 annual telephone interviews were conducted with study participants (or their proxy) for vital status. For any reported event, medical records, death certificates, and coroner’s reports were retrieved. Date of death was recorded to provide time-to-event data from the baseline examination.

Patient demographics and co-morbid diseases were determined by questionnaire. Systolic and diastolic blood pressures were measured after 5 minutes of rest in subjects in the supine position by trained research personnel. Participants were instructed to take their blood pressure medications on the morning of the intake appointment and not to smoke or consume caffeine 5 hours before the visit. Weight and height were measured in participants wearing light clothing and no shoes. BMI was calculated as weight in kilograms divided by height in meters squared.

Serum cystatin C concentrations were measured with a particle-enhanced immunonephelometric assay7 (N Latex Cystatin-C, Dade Behring, Inc, Deerfield, Ill) and used to calculate estimated GFR (eGFRcys) with the following formula: eGFRcys=76.7× cystatin C−1.19. This formula, which has been validated with comparison with iothalamate-measured GFR in a pooled cohort of kidney disease studies, showed little bias and provided a non–creatinine based method to adjust for kidney function for this study.8 Total cholesterol and high-density lipoprotein (HDL) cholesterol were measured with standard clinical chemistry analyzers. High sensitivity C-reactive protein (CRP) was measured with the Roche (Indianapolis, Ind) and the Beckman Extended Range (Galway,Ireland) assays.9 Fasting glucose was measured by a standard clinical analyzer, and fasting insulin was measured by ELISA (Linco Research, St Charles, Mo). Participants provided rest transthoracic echocardiograms that were read by a single expert cardiologist blinded to all clinical data as described previously.10 Left ventricular mass was calculated with the truncated ellipsoid method11 and indexed to body surface area. Left ventricular ejection fraction was determined by biplane method of disks.12 Exercise treadmill test by the modified Bruce protocol was performed and the maximum number of metabolic equivalents (METs) and heart rate achieved were recorded.

We began by exploring the association of sex-specific BMI quintiles in men (24.0 kg/m2, 26.3 kg/m2, 28.7 kg/m2, 31.6 kg/m2) and women (24.6 kg/m2, 27.4 kg/m2, 30.0 kg/m2, 34.6 kg/m2) with mortality. We verified the linearity of the association between BMI and mortality to maximize statistical power. The distribution of demographic variables and standard CHD risk factors were compared across BMI quintiles using ANOVA tests for continuous variables and the chi square tests for categorical variables, as appropriate. We performed Cox proportional hazards regression to examine the association between BMI and all-cause mortality, using the lowest sex-specific BMI quintile as the referent category. Patient demographics, co-morbid diseases, physical measurements and laboratory values were added to the Cox proportional hazards regression models. Prior analyses have demonstrated a linear relationship of urine creatinine excretion rate with mortality in this cohort.1 Urinary creatinine excretion rate was included in the final model as a continuous covariate to evaluate whether it attenuated the association of BMI with all-cause mortality.

We performed a sensitivity analyses to investigate whether over- or under- urine collections may have introduced bias. We excluded participants whose measured 24-hour urinary creatinine clearance was > 30% different from their eGFRcys. This takes advantage of the fact that urinary creatinine excretion rate divided by serum creatinine equals creatinine clearance (in mL/min), an estimate of GFR. eGFRcys provided another estimate of GFR that was independent of the quality of timed urine collections and of creatinine kinetics. Because the eGFRcys estimate is given as GFR normalized to body surface area, to compare the two renal function estimates, measured creatinine clearance was divided by body surface area and multiplied by 1.73.

We also explored whether measures of subclinical cardiovascular disease might attenuate the associations of BMI with mortality in our population. We stratified the outcome of mortality into early (< 3 years from enrollment) versus late mortality (≥ 3 years from enrollment). This cut-point was chosen as the half-way point of the median follow-up in our study (6 years). Additional analyses evaluated whether adjustment for self-reported overall health (on a 5-point Likert scale), total METS achieved on the modified Bruce protocol treadmill test, and left ventricular mass index, attenuated the association of BMI with mortality in Cox models.

All analyses were conducted using SAS (version 9.2, SAS Institute Inc., Cary, NC, USA). P-values < 0.05 were considered statistically significant.

RESULTS

The mean age of the 886 participant study population was 66.8 (± 10.9) years. 82% were male, reflecting heavy sampling from a VA medical center. The mean BMI was 28.4 (± 5.3) kg/m2. Mean follow-up time was 5.9 (± 1.9) years, during which time 273 participants died, 22 of whom were women. Baseline characteristics of the study population by sex-specific BMI quintiles are shown in Table 1.

Table 1
Characteristics of the study cohort (N=886)

BMI and urinary creatinine excretion rate were directly correlated (Pearson correlation coefficient 0.35, P<.0001). Compared to the lowest BMI quintile, those in higher BMI quintiles were less likely to die during follow-up (Table 2). This association was fairly monotonic with increasing BMI quintiles. When BMI was evaluated as a continuous risk factor, each 5kg/m2 greater BMI was associated with a 21% lower risk of death (hazard ratio [HR] 0.79; 95% confidence interval [CI] 0.68–0.91). Adjustment for major demographic variables, cardiovascular risk factors and kidney function did not attenuate the relationship (HR per 5kg/m2 greater 0.80; 95% CI 0.68–0.94). Additional adjustment for urinary creatinine excretion rate did not change the association between BMI and all-cause mortality (HR 0.82; 95% CI 0.69–0.96; Figure 1).

Figure 1
Hazard Ratio for Mortality by Sex-Specific Body Mass Index (BMI) Quintiles
Table 2
Association of body mass index with all-cause mortality in outpatients with stable coronary heart disease (N= 886)

We performed a sensitivity analysis where we excluded participants whose measured 24-hour urinary creatinine clearance was > 30% different from their eGFRcys to evaluate potential bias introduced by potentially inaccurately collected urine specimens. A total of 258 (29%) participants were excluded for disparate collections by this criteria for this analysis. Within the remaining individuals, the results did not differ significantly from that observed in all participants (Table 3).

Table 3
Association of body mass index and all-cause mortality in outpatients with stable coronary heart disease, sensitivity analysis testing validity of urine collection (N=628)

We also evaluated whether the association of BMI with mortality was similar among individuals who died within< 3 years from enrollment versus later. In this analysis, the inverse association between BMI and all-cause mortality appeared stronger among individuals who died early compared with later (Table 4). Adjustment for creatinine excretion rate in addition to traditional cardiovascular risk factors did little to change the nature of the association of BMI with mortality (results not shown).

Table 4
Hazard ratios between body mass index and all-cause mortality in patients with stable coronary heart disease, stratified by early versus late death*

As low BMI in persons with CHD may reflect poorer global health status or poorer physical fitness, we performed additional analyses evaluating variables that could attenuate the association between BMI and mortality, including self-reported overall health, METS achieved on the modified Bruce treadmill test and left ventricular mass index. Adjusting for these variables either individually or jointly did not materially alter the hazard ratio between BMI and mortality (Table 5).

Table 5
Association between body mass index (per 1kg/m2 increase) and all-cause mortality adjusted for select patient variables

DISCUSSION

The purpose of our study was to evaluate whether low urinary creatinine excretion rate, a marker of low muscle mass, may explain the paradoxical relationship between low BMI and mortality observed among CHD patients. We found that while low creatinine excretion and low BMI were associated with greater mortality, controlling for creatinine excretion did not explain why patients with low BMI have worse survival.

Low BMI and low lean mass have been associated with higher mortality in other populations, including those with chronic obstructive pulmonary disease,1315 end-stage liver disease 16,17 and end-stage renal disease (ESRD).1820 However, it remains unclear whether low muscle mass accounts for the paradoxical association between BMI and mortality in these populations. A study of hemodialysis patients also used urinary creatinine excretion rate to estimate muscle mass and found that the protective effect of higher BMI was limited to patients with normal or high muscle mass.21 Our study took a similar approach in persons with stable CHD. Unlike findings in ESRD patients, our results demonstrate that the inverse association between BMI and mortality was not explained by muscle mass in persons with CHD. This suggests that varying mechanisms may account for the BMI-mortality paradox in different patient populations.

The inverse association between BMI and mortality was stronger in individuals who died < 3 years from enrollment. This suggests the possibility of reverse causality; individuals with a greater burden of subclinical diseases may have been prone to weight loss and early mortality. Other studies have examined the association between BMI and early mortality in the general population and found similar results. In a study of the general U.S. population, risk of mortality among those with lower BMI was substantially reduced when the first five years of follow-up were excluded.22 Among 99,000 male physicians, the relative risk for death was lower in men with BMI < 20 kg/m2 after excluding those who died within the first two years of follow-up.23 In a large study of 1.46 million White adults, the increased hazard ratio for death with low BMI was no longer seen after ≥ 15 years of follow-up.24 To our knowledge, our study is the first to extend these observations to those with preexisting CHD. If confirmed with other larger longitudinal studies, loss of body mass may be a useful indicator of greater death risk, where closer surveillance and investigation of subclinical diseases may ultimately prove useful for delaying death if appropriate corrective measures can be identified.

We also explored other potential mechanisms to explain the paradoxical relationship between BMI and mortality, such as self-reported overall health, METS achieved on a treadmill test and left ventricular mass index. Adjustment for these additional variables did not attenuate the relationship between BMI and mortality. Self-reported overall health,25,26 METS achieved on the modified Bruce protocol treadmill test27 and elevated left ventricular mass index have been found to be associated with worse outcomes.28,29 Thus, while the mechanisms responsible for the BMI-mortality paradox remain unclear, these data suggest that measurement of muscle mass, self-reported health status, evaluation of physical fitness and left ventricular mass may not be useful to identify CHD patients with low BMI at greatest risk of death.

Our study had several strengths. It evaluated a large, well-characterized CHD cohort with a median 5.9 years of follow-up for mortality. Our study is one of a few that contains data on 24-hour urine creatinine excretion, providing a standardized method to estimate muscle mass. All participants provided physical performance measurements on Bruce treadmill protocol and transthoracic echocardiograms. Our study also had some limitations. Subjects were older, mostly male, and had stable CHD. Results may differ in other populations. Other measures of muscle mass, such as dual energy x-ray absorptiometry, were not available. Larger sample sizes may have allowed detection of subtle differences in the association of BMI with mortality when adjusted for creatinine excretion rate. However, the very modest or altogether absent effect of adjustment observed in this study suggests that any such an effect would likely be modest.

ACKNOWLEGEMENTS

This study was supported by grants from the : American Kidney Fund (Bansal), National Heart Lung and Blood Institute (NHLBI-1R01HL096851) (Ix), and an American Heart Association Fellow-to-Faculty Transition Award (Ix). The Heart and Soul Study was funded by the Department of Veterans Affairs, American Federation of Aging Research, Robert Wood Johnson Foundation, Nancy Kirwan Heart Research Fund, Ischemic Research and Education Foundation, and the NHLBI (R01 HL079235).

Footnotes

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