We sought to evaluate the association of urine calcium excretion (UCaE), which reflects systemic calcium absorption, with cardiovascular (CV) events and mortality in outpatients with prevalent coronary heart disease (CHD). Calcium supplementation is associated with vascular calcification and adverse CV outcomes in patients with end-stage renal disease. Recent studies have raised concern that this phenomenon may also extend to the general population. However, previous studies have assessed oral calcium intake, which correlates poorly with systemic calcium absorption. We measured UCaE from 24-hour urine collections provided by 903 outpatients who were recruited from 2000 to 2002. We used Cox proportional hazard models to evaluate the association of baseline UCaE with a primary end point of any CV event (myocardial infarction [MI], heart failure, stroke, or CV mortality). During a mean follow-up of 6 ± 3 years, 287 subjects (32%) had a CV event. After multivariate adjustment for demographics, traditional CV risk factors, and kidney function, there was no association between UCaE and the primary end point of any CV event (per 10-mg/day greater UCaE, hazard ratio 1.00, 95% confidence interval 0.98 to 1.02). Evaluation of individual CV outcomes revealed a lower rate of MI with higher UCaE (hazard ratio 0.97, 95% confidence interval 0.94 to 1.00). In conclusion, greater UCaE is not associated with higher overall CV event rates or mortality in outpatients with stable CHD. On the contrary, greater UCaE is associated with a modestly lower rate of MI. These findings suggest that greater systemic calcium absorption does not confer CV harm in outpatients with prevalent CHD.
Urine calcium excretion (UCaE) provides an estimate of the amount of calcium that is systemically absorbed and overcomes limitations of recall bias and differences in intestinal absorption. Therefore, in a well-characterized cohort of participants with known stable coronary disease, we sought to determine the association between UCaE and cardiovascular (CV) events.
Methods
The Heart and Soul Study is a prospective cohort study originally designed to investigate psychosocial factors and health outcomes in subjects with stable coronary heart disease (CHD). Details regarding recruitment methods and study design have been published previously. In brief, 1,024 outpatients with stable CHD were recruited from 2 Veterans Administration medical centers, 1 university medical center, and 9 public health clinics in the San Francisco Bay Area. Eligible participants met ≥1 of the following criteria: (1) history of myocardial infarction (MI), (2) evidence of ≥50% stenosis in ≥1 coronary vessel on cardiac catheterization, (3) evidence of exercise-induced ischemia by treadmill electrocardiogram or nuclear perfusion stress imaging, or (4) a history of coronary revascularization. Subjects were excluded if they had a history of MI in the previous 6 months, were unable to walk 1 block, or were planning to move out of the local area within 3 years. The study was approved by the institutional review board and all participants provided written informed consent.
From September 2000 through December 2002, all participants underwent a baseline study appointment that included a medical history, physical examination, and comprehensive health status questionnaire. Outpatient 24-hour timed urine collections and fasting (12-hour) morning venous blood samples were obtained. Of the 1,024 original study subjects, we excluded 121 subjects with missing covariate data. Participants were followed for CV events through April 12, 2012. The remaining 903 participants are the subjects of this analysis.
The protocol used for collection of the 24-hour timed urine specimens has been previously described in detail. In brief, participants were given detailed instructions regarding accurate timing of urine collection and appropriate refrigeration of specimens. Subjects were asked to void at the end of their study appointment and to begin the collection from that point forward. Research personnel retrieved the urine 24 hours after the collection was initiated to avoid over- or undercollection. If participants were unable to collect all urine for any reason or if collections were <1 or >3 L, the protocol was repeated. Urine volume was recorded. The 24-hour urine collections were originally collected at the time of baseline examination and stored for future analyses of associations between urine metabolites and CV events. Collections were stored frozen at 80°C until the time of analysis in 2009, when specimens were thawed and treated with hydrochloric acid 1 mol/L. Urine calcium was measured using a Cobas 6000 clinical analyzer (Roche Diagnostics, Indianapolis, Indiana; http://www.roche.com ). The lower limit of detection was 0.6 mg/dl, and coefficients of variation were <2.0%.
The primary outcome was any CV event, which was defined as a composite of hospitalization for MI, stroke, heart failure, or CV death. From the baseline examination to April 12, 2012, we conducted annual follow-up interviews with participants or their proxy to inquire about the interval death or hospitalization for “heart trouble.” For any reported event, we retrieved medical records, which 2 independent and blinded physician adjudicators reviewed. If the adjudicators agreed on the outcome classification, their classification was binding. In the event of a disagreement, a third blinded adjudicator was consulted.
All-cause mortality was determined by review of death certificates. MI was defined using American Heart Association diagnostic criteria. A heart disease–related death was defined as a death occurring during the same hospitalization in which an acute MI, congestive heart failure, severe cardiac dysrhythmia, or coronary artery bypass surgery was documented, or a death occurring within 1 hour of the onset of terminal symptoms not explained by other causes. Stroke was defined as a new neurologic deficit not known to be secondary to brain trauma, tumor, infection, or other cause. Heart failure was defined as hospitalization for a clinical syndrome based on Framingham congestive heart failure criteria, which require validation of 2 major criteria or 1 major criterion plus 2 minor criteria (major criteria: paroxysmal nocturnal dyspnea, orthopnea, increased jugular venous pressure, pulmonary rales, third heart sound, cardiomegaly on chest x-ray, pulmonary edema on chest x-ray, weight loss ≥4.5 kg in 5 days in response to heart failure therapy; minor criteria: peripheral edema, night cough, dyspnea on exertion, hepatomegaly, pleural effusion, heart rate >120/min).
Age, gender, race, medical history, and smoking status were determined by self-report questionnaire. Alcohol use was measured by the Alcohol Use Disorders Identification Test-Hepatitis C questionnaire, with a score of ≥4 used to define regular alcohol use. Weight and height were measured, and body mass index was calculated as weight (kilograms) divided by height (meters) squared. Systolic and diastolic blood pressures were measured in the supine position after 5 minutes of rest.
Serum cystatin C concentrations were measured with a particle-enhanced immunonephelometric assay (N Latex Cystatin-C, Dade Behring, Inc., Deerfield, Illinois) and used to calculate estimated glomerular filtration rate (eGFR cys ) with the following formula: eGFR cys = 76.7 × cystatin C −1.19 . This formula has been validated by comparison with Iothalamate-measured GFR in a pooled cohort of kidney disease studies. Total cholesterol and high-density lipoprotein cholesterol were measured from fasting (12-hour overnight) blood samples drawn at the baseline study appointment and low-density lipoprotein cholesterol was calculated using the Friedewald equation. High-sensitivity C-reactive protein was measured with Roche Diagnostics or Beckman Extended Range (Galway, Ireland) assays. Parathyroid hormone was measured using the Roche Diagnostics parathyroid hormone immunoassay on an Elecsys E170 automated analyzer (Indianapolis, Indiana). Echocardiograms at rest were obtained in all participants using a standardized protocol by 1 of 2 trained and experienced technicians. One experienced reader blinded to clinical information interpreted all studies as described previously.
In the absence of clear-cut points and after confirming linearity of the measurement, we analyzed UCaE levels by tertiles. Differences in participant characteristics by tertiles of baseline UCaE were compared using chi-square tests for dichotomous variables and 1-way analysis of variance for continuous variables. To determine the unadjusted association of UCaE with CV events, we measured cumulative event-free survival by the Kaplan–Meier method and compared unadjusted differences using log-rank test. Next, we used Cox proportional hazards models to evaluate the association of UCaE with the composite outcome in multivariable models by tertiles. The lowest tertile served as the reference category. We also evaluated UCaE as a continuous predictor (per 10 mg/day higher) in companion analyses.
We developed sequential models. Model 1 was adjusted for demographics (age, gender, and race); model 2 was adjusted for model 1 variables plus traditional CV risk factors (body mass index, MI, stroke, hypertension, and systolic blood pressure), medications (angiotensin receptor antagonists, loop diuretics, and thiazide diuretics) and C-reactive protein. C-reactive protein was log-transformed to normalize the distribution. Model 3 was adjusted for model 2 variables plus eGFR cys . We assessed proportional hazards assumptions by visual inspection of Schoenfeld residuals, log-minus-log plots, and use of time-varying covariates to assess for heterogeneity of effects across follow-ups and found no evidence of violation.
To determine whether any association between UCaE and CV events could have been caused by incomplete urine collections in subjects with low UCaE, we performed a sensitivity analysis excluding participants whose measured creatinine clearance on 24-hour urine collections was discrepant from eGFR cys by >30%, as previously described by Ix et al, because diuretics influence urine calcium excretion; we also performed a subgroup analysis restricted to subjects not receiving diuretics.
We then tested for an interaction to determine whether the association between UCaE and the primary end point differed by gender, race, presence of moderate chronic kidney disease (defined as eGFR >60 ml/min/1.73 m 2 ), or use of calcium supplements, with a p value <0.10 considered statistically significant for interaction terms and a p value <0.05 considered significant for all other analyses. All analyses were conducted using STATA 11.0 (STATA Corp., College Station, Texas).
Results
Mean age of the 903 study participants was 67 ± 11 years; 82% were men, reflecting heavy recruitment from Veterans Administration medical centers; and 30% had moderate chronic kidney disease. Median UCaE was 72.5 mg/day (intertertile range 50 to 109). Compared to participants who had UCaE in the lowest tertile, those in the highest tertile were younger, more likely to be of Caucasian race, and had higher body mass indexes. Participants in the lowest tertile had a greater prevalence of MI, stroke, and hypertension. They were more likely to be taking cardiac medications, had higher systolic blood pressures, lower eGFRs, higher C-reactive protein levels, and higher parathyroid hormone levels ( Table 1 ).
| Variable | UCaE (mg/day) | p Value | ||
|---|---|---|---|---|
| I (≤50) | II (50–109) | III (109–490) | ||
| Age (years) | 70 ± 11 | 67 ± 11 | 63 ± 10 | <0.001 |
| Men | 81% | 83% | 83% | 0.83 |
| Race | ||||
| White | 55% | 63% | 64% | <0.001 |
| Black | 23% | 14% | 10% | |
| Other | 22% | 24% | 26% | |
| Current smoker | 20% | 17% | 22% | 0.24 |
| Regular alcohol use | 26% | 27% | 32% | 0.24 |
| Body mass index (kg/m 2 ) | 28 ± 6 | 28 ± 5 | 29 ± 5 | 0.008 |
| Ejection fraction (%) | 61 ± 10 | 62 ± 10 | 62 ± 9 | 0.40 |
| Myocardial infarction | 61% | 52% | 50% | 0.01 |
| Stroke/transient ischemic attack | 18% | 13% | 11% | 0.05 |
| Heart failure | 21% | 15% | 16% | 0.08 |
| Diabetes | 30% | 24% | 24% | 0.13 |
| Hypertension | 80% | 65% | 68% | <0.001 |
| Revascularization | 64% | 57% | 58% | 0.12 |
| Aspirin | 76% | 76% | 80% | 0.37 |
| β Blocker | 63% | 55% | 55% | 0.07 |
| Angiotensin inhibitor | 57% | 51% | 47% | 0.05 |
| Thiazide diuretic | 23% | 13% | 8% | <0.001 |
| Loop diuretic | 20% | 15% | 12% | 0.03 |
| Statin | 65% | 63% | 65% | 0.86 |
| Calcium supplements | 12% | 17% | 13% | 0.21 |
| Systolic blood pressure (mm Hg) | 136 ± 22 | 131 ± 21 | 132 ± 19 | 0.002 |
| Cholesterol (mg/dl) | ||||
| Total | 176 ± 41 | 178 ± 43 | 178 ± 43 | 0.82 |
| High-density lipoprotein | 45 ± 15 | 46 ± 13 | 45 ± 14 | 0.58 |
| Low-density lipoprotein | 104 ± 33 | 106 ± 35 | 103 ± 31 | 0.61 |
| Estimated glomerular filtration rate by cystatin (ml/min/1.73 m 2 ) | 61 ± 23 | 72 ± 22 | 81 ± 18 | <0.001 |
| Log-transformed C-reactive protein (mg/L) | 0.9 ± 1.3 | 0.8 ± 1.3 | 0.5 ± 1.4 | 0.002 |
| Log-transformed parathyroid hormone (mg/L) | 4.1 ± 0.5 | 4.0 ± 0.4 | 3.9 ± 0.4 | <0.001 |
During 6.2 years (mean) of follow-up, there were 287 CV events. Greater UCaE was associated with a lower rate of the primary end point of any CV event in unadjusted analysis. After multivariate adjustment for demographics, CV risk factors, cardiac medications, and eGFR, the association was no longer present. In fully adjusted models evaluating UCaE as a continuous variable (per 10 mg/day greater), confidence intervals around the point estimate were narrow ( Table 2 ). Examination of individual CV outcomes revealed no significant associations between UCaE and heart failure, stroke, CV mortality, or all-cause mortality. Higher UCaE was associated with a modestly lower rate of MI, which remained statistically significant in the fully adjusted model ( Table 3 ). We found no effect modification by gender, race, presence of moderate chronic kidney disease, or use of calcium supplements (p for interaction >0.10 for all comparisons).
| HR (95% CI) | HR (95% CI) as Continuous Variable | ||||
|---|---|---|---|---|---|
| Tertile I (≤50 mg/day) | Tertile II (50–109 mg/day) | Tertile III (≥109 mg/day) | Per 10-mg/day Greater UCaE | p Value | |
| Proportion with events | 40% (121/301) | 30% (89/301) | 26% (77/301) | ||
| Model 1 | 1.00 | 0.70 (0.53–0.93) | 0.67 (0.50–0.91) | 0.98 (0.96–1.00) | 0.02 |
| Model 2 | 1.00 | 0.74 (0.56–0.99) | 0.75 (0.55–1.03) | 0.98 (0.97–1.00) | 0.07 |
| Model 3 | 1.00 | 0.86 (0.64–1.15) | 1.00 (0.71–1.40) | 1.00 (0.98–1.02) | 0.96 |
⁎ Any cardiovascular event was defined as myocardial infarction, heart failure, stroke/transient ischemic attack, or cardiovascular death.
| HR (95% CI) per 10-mg/day Greater UCaE | ||||||
|---|---|---|---|---|---|---|
| MI | HF | Stroke/TIA | Any CV Event ⁎ | CV Mortality | All-Cause Mortality | |
| (n = 117) | (n = 155) | (n = 41) | (n = 287) | (n = 113) | (n = 341) | |
| Model 1 | 0.95 (0.92–0.98) | 0.99 (0.97–1.01) | 0.97 (0.93–1.02) | 0.98 (0.96–1.00) | 0.97 (0.94–1.00) | 0.97 (0.96–0.99) |
| Model 2 | 0.96 (0.93–0.99) | 0.99 (0.97–1.02) | 0.99 (0.94–1.03) | 0.98 (0.97–1.00) | 0.97 (0.95–1.00) | 0.98 (0.96–0.99) |
| Model 3 | 0.97 (0.94–1.00) | 1.01 (0.99–1.04) | 0.99 (0.95–1.04) | 1.00 (0.98–1.02) | 0.98 (0.95–1.01) | 0.99 (0.97–1.00) |
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