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1Institute for Mind and Biology, 2Department of Medicine, and 3Department of Psychology, University of Chicago, Chicago, Illinois 60637
Submitted 9 March 2004 ; accepted in final form 10 May 2004
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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African American; blacks; male; norepinephrine; epinephrine; cortisol; creatinine
Currently, two primary strategies exist for collecting urine samples and calculating urinary hormone levels. The first is collecting a 24-h urine sample and determining hormone levels per urine volume (19). The second is collecting an overnight urine sample and calculating hormone values per amount of urinary creatinine (4, 18, 19). Each approach has advantages and disadvantages (see Table 1). A third approach, which accounts for urine flow, has been used when neither 24-h nor overnight sampling is practical (8).
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Unfortunately, this approach also presents problems. The first is that creatinine excretion is influenced by muscle mass, and muscle mass varies as a function of individual differences that are independent of hormone production. Gender differences are a case in point. In a study of 468 men and women aged 18–88 yr, Janssen et al. (11) found that men had significantly more skeletal muscle mass compared with women both in absolute terms (33 vs. 21 kg) and relative to body mass (38.4 vs 30.6%). Other studies have shown greater urinary creatinine among men compared with women over 24 h (10) and in spot samples (14). When urinary hormone concentration is divided by creatinine concentration, the larger values of creatinine concentration among men reduce the hormone-to-creatinine ratio. This effectively underestimates urinary hormone values among men. Using a nationally representative data set, Mattix et al. (14) demonstrated that using a single cutoff value (30 µg/mg) of urinary albumin-to-creatinine ratio led to a significant underestimation of microalbuminuria prevalence in men (6.0%) compared with women (9.2%). This was attributed to the significantly higher urinary creatinine excretion among men (152 mg/dl) compared with women (108 mg/dl). The authors concluded that gender-specific albumin-to-creatinine ratio cutoff values should be used to account for differences in creatinine excretion when screening for microalbuminuria.
A second problem with creatinine standardization is that creatinine excretion varies by ethnicity. James et al. (10) found that blacks excrete 5% more urinary creatinine per weight compared with whites. This difference was attributed to greater muscle mass among blacks compared with whites. A subsequent study found 30% higher urinary creatinine per weight among blacks compared with whites (7). Ethnic differences in muscle mass, muscle metabolism, and dietary protein were offered as possible explanations. Although gender differences in muscle mass are well established, ethnic differences in muscle mass are less clear. Gallagher et al. (5) found no black-white muscle mass difference among men but a 10% greater muscle mass among black women compared with white women (5). As for muscle metabolism, Ama et al. (1) found that the activity of muscle enzymes (creatinine kinase, hexokinase, and lactate dehydrogenase) was 30–40% greater among blacks compared with whites. Others have suggested that increased urinary creatinine among blacks may be related to higher levels of testosterone. Testosterone promotes the synthesis of creatine, a creatinine precursor (7).
The effects of creatinine standardization on test results can be seen by comparing studies that report 24-h urinary hormone levels with those that report creatinine-corrected hormone levels. Souza et al. (17) reported greater 24-h excretion of both epinephrine and norepinephrine among men compared with women. Gerlo et al. (6) also found higher 24-h urinary epinephrine, norepinephrine, and dopamine levels among men compared with women. In that study, correcting for urinary creatinine excretion reversed the gender effect and resulted in higher creatinine-corrected norepinephrine and dopamine among women compared with men. The creatinine-corrected epinephrine remained higher among men, but the gender difference was reduced. Correcting for creatinine excretion, Hansen et al. (9) found higher 24-h urinary epinephrine among men but no gender differences in urinary excretion of norepinephrine or cortisol. That study did not report raw hormone values. Another study noted higher creatinine-corrected overnight epinephrine among women compared with men and some evidence of lower epinephrine and norepinephrine among blacks compared with whites (15). These results suggest that creatinine correction leads to underestimation of urinary hormone values among men and may affect comparison of urinary hormones by ethnicity.
The first aim of the present study was to examine gender and ethnic differences in overnight urinary catecholamines, cortisol, and creatinine in a population-based sample of older adults in an urban setting. A related aim was to investigate whether inconsistencies in the prior literature might be due to the effects of gender and ethnic differences in creatinine excretion on creatinine-corrected hormone values. Finally, we tested a new method of analysis that permits calculation of urinary hormone concentrations while accounting for gender and ethnic differences in creatinine excretion due to muscle mass.
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MATERIALS AND METHODS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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A population-based sample of 229 English-speaking blacks (44 women, 37 men), Hispanics (33 women, 33 men), and non-Hispanic whites (43 women, 39 men) from Cook County, Illinois, aged 50–67 yr, served as participants in the first year of the Chicago Health, Aging, and Social Relations Study, a longitudinal, population-based study. A multistage probability sampling design was used to select respondents. Additional information on the sampling and recruiting strategies is available from the authors on request. Informed consent was obtained, and participants were paid $126 for participating in the first year. Table 2 provides demographic information about the sample.
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Before their scheduled test day in the laboratory, participants were mailed instructions and a container (prefilled with 25 ml of 50% glacial acetic acid as a preservative) for an overnight urine sample. Participants were instructed to thoroughly void, but not into the container, before going to bed on the night before the laboratory tests. The provided container was used for any nighttime voiding and for the first morning void the next day. Participants were also instructed to mix the contents of the container.
Participants arrived at the laboratory at 
8:30 AM, whereupon the urine sample volume was measured and aliquots of urine were frozen at –80°C and batched for later testing. After providing informed consent, participants began a day of assessments that included demographic evaluation (age, education, occupation), self-report surveys, interviews, lunch, and a cardiovascular protocol that is not directly related to this study.
Measures
Urinary analyses. Analyses of urinary creatinine and urinary free hormones (epinephrine, norepinephrine, and cortisol) were conducted using high-performance liquid chromatography. The acidity of each urine sample was adjusted as necessary to achieve optimal extraction of constituents. Inter- and intra-assay variability (i.e., coefficient of variation) for these high-performance liquid chromatography analyses is 4–7% for epinephrine, 3–5% for norepinephrine, 6–10% for cortisol, and 2% for creatinine. Although 229 participants enrolled in the study, the number of participants who provided urinary samples for which hormone and creatinine levels could be determined varied from 198 to 221 depending on the constituent.
Weight, body mass index, and fat-free mass. Participants were weighed and measured on a standard medical scale (Detecto, Pro-Med Products, Atlanta, GA). Body mass index (BMI) was calculated as weight (kg)/height (m2). Body composition was measured by using bioelectrical impedance analysis (RJL Systems, Clinton Township, MI). Using this system, two pairs of electrodes are attached to specific anatomic landmarks on the ankle and wrist of the subject. An electrical current of 50 kHz is applied across the distal source electrodes, and resistance to the current is detected by the proximal detecting electrodes. As the current travels through the body, it experiences a slight delay due to living cells. This delay, compared with the reference signal, provides a reactance reading that reflects intracellular volume and permits the calculation of body cell mass and intracellular water. Relative to the reference signal, the nondelayed signal provides a magnitude (resistance) reading that permits the calculation of extracellular water and extracellular mass. Fat-free mass is calculated as the sum of body cell mass and extracellular mass.
Demographic Variables
Gender, ethnicity, age, education, and income were the demographic variables of interest. Gender and ethnicity were treated as categorical variables, whereas the other variables were treated as continuous. Education was obtained by using a 5-point scale, ranging from "1 = less than high school" to "5 = completed graduate school." Income was obtained by using a 11-point scale, ranging from "1 = less than $5,000" to "11 = over $200,000." See Table 2 for the distribution of education and income.
Data Reduction and Statistical Analysis
Three methods for calculating overnight urinary hormone levels were used. In the first and simplest, we controlled for volume by dividing total urinary hormone by the volume of urine produced. In the second, we controlled for urine concentration by dividing the hormone concentration by the urinary creatinine concentration.
Finally, we developed a new method of standardization for urine concentration that removes the variance in creatinine levels attributable to differences in muscle mass. The proposed method utilizes a partial regression approach. In essence, the first step involves calculating residualized scores for creatinine levels using fat-free mass as the predictor. That is, each individual has a residual score that represents the difference between his or her creatinine level (the "observed value") and the predicted value on the basis of the regression of urinary creatinine levels (the dependent variable) on fat-free mass (the predictor variable). These residual scores represent creatinine values that do not differ as a function of fat-free mass (see Fig. 1). By eliminating the effects of muscle mass on creatinine values, these residual creatinine scores can be used to adjust for urine concentration without biasing against those with larger muscle mass.
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RESULTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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The response rate among eligible persons was comparable to those of other well-conducted telephone surveys. Among all households called, we were unable to speak to someone (despite repeated attempts) or were unable to determine whether an eligible individual lived in the household in 23%. Among households with eligible individuals, the overall response rate was 45%.
Demographic Differences in Education and Age
Ethnic groups did not differ significantly in household income, but they did differ in highest level of education attained [
2(8) = 25.505, P < 0.01]. This difference was attributable to graduate school being completed by a greater proportion of whites than blacks or Hispanics. In addition, the Hispanic group was slightly younger than the white and black groups [F(2,228) = 8.09, P < 0.001].
Demographic Differences in Weight, BMI, Fat-Free Mass, and Creatinine Production
Although there was no significant gender difference in BMI, weight and fat-free mass were significantly higher among men compared with women (see Table 3). Compared with whites and Hispanics, blacks had higher weight and BMI. In contrast, the ethnic differences in fat-free mass were not statistically significant. To examine whether urine creatinine concentration differed across gender and ethnicity, a two (gender: men vs. women) x three (ethnicity: white, black, Hispanic) analysis of variance was conducted. The analysis yielded a significant main effect for gender [F(1,218) = 39.20, P < 0.001], indicating that men have higher levels of urinary creatinine than women. Additionally, there was a main effect for ethnicity [F(2,218) = 4.22, P =0.016], indicating that blacks excrete more creatinine than whites. Creatinine excretion was correlated with fat-free mass [r(195) = 0.32, P < 0.001] but not weight [r(228) = 0.121, P > 0.05] or BMI [r(222) = –0.03, P > 0.6]. The slope of the relationship between creatinine and FFM did not differ by ethnicity or the presence of diabetes. In addition, there was no difference in the ratio of creatinine to fat-free mass by gender or ethnicity.
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Attention then turned to examining whether there were demographic differences in urinary catecholamine and glucocorticoid excretion. A two (gender) x three (ethnicity) analysis of variance was conducted for each of the hormones examined by using three types of standardization (volume, creatinine, and residualized change; see Table 3). Regarding volume-standardized hormone levels, the analysis yielded significant main effects for gender, such that men excreted more overnight epinephrine [F(1,192) = 12.98, P < 0.001], norepinephrine [F(1,208) = 9.53, P = 0.002], and cortisol [F(1, 19) = 8.45, P = 0.004]. Additionally, there was also a main effect for ethnicity, such that blacks excreted more epinephrine and more norepinephrine than whites [F(2,19) = 12.98, P = 0.021; F(2,208) = 3.86, P = 0.023, respectively]. There was no significant ethnic difference in cortisol excretion.
Regarding creatinine-standardized hormone levels, the results revealed significant main effects for gender, with women excreting higher levels of overnight norepinephrine [F(1,213) = 11.40, P = 0.001]. No gender difference in epinephrine production was noted. These results are contrary to the volume-standardized hormones results. Analyses of ethnicity also revealed different results after standardizing by creatinine levels, namely that ethnicity was not significantly associated with variation in excretion of any of the hormones.
For the residualized hormone levels, consistent with the volume-standardized (but contrary to the creatinine-standardized) analysis, there were significant main effects for gender, with men excreting higher levels of overnight epinephrine and norepinephrine [F(1,163) = 5.72, P = 0.018; F(1,182) = 4.60, P = 0.033, respectively]. The higher level of cortisol among men compared with women approached statistical significance [F(1,166) = 3.63, P = 0.058]. Although ethnicity was not significantly associated with variation in excretion of any of the hormones, the mean levels were consistent with those obtained in the volume-standardized analysis. Analysis of variance testing for interaction effects revealed the gender differences in epinephrine and norepinephrine did not vary by ethnicity. In addition, no gender-ethnicity interaction effect was noted in cortisol production.
To examine whether there were age, education, or income-related differences, the urinary hormones were regressed on age, education, and income with gender and ethnicity entered as controls (see Table 4). For volume-standardized hormones, controlling for gender and ethnicity, age was significantly associated with epinephrine excretion. As age increases, there is decreased epinephrine excretion (B = –4.89, SE = 2.15, P = 0.024) and decreased cortisol excretion (B = –25.66, SE = 12.72, P = 0.045). Education and income were not significantly associated with variations in urinary hormone excretion.
For the creatinine-standardized hormones (controlling for gender and ethnicity), contrary to the volume-standardized analyses, age was not significantly associated with variations in excretion for any of the hormones. Level of income was inversely associated with catecholamine excretion. As income increased, epinephrine and norepinephrine excretion decreased (B = –0.07, SE = 0.04, P = 0.060, B = –1.21, SE = 0.48, P = 0.012, respectively).
Regarding the residualized hormones (controlling for gender and ethnicity), consistent with the volume-standardized analyses, education was not significantly associated with variations in urinary hormone excretion. As age increased, epinephrine excretion decreased, although not significantly (B = –3.52, SE = 1.90, P = 0.066). Similarly, as income increased, epinephrine and norepinephrine excretion decreased (B = –7.07, SE = 3.99, P = 0.079, B = –98.85, B = 53.88, P = 0.068, respectively), although not significantly.
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DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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The results presented here are consistent with prior literature that shows greater creatinine production among men and blacks (7, 10, 14). Men had higher fat-free mass compared with women, but there were no significant gender or ethnic differences in the ratio of creatinine to fat-free mass. This suggests muscle mass largely accounts for differences in creatinine production.
The volume-standardized results from our overnight urine collection are consistent with previous reports showing higher 24-h levels of urinary epinephrine and norepinephrine among men compared with women (6, 17), higher cortisol production among men compared with women (3, 13, 16), and similar cortisol production among whites compared with blacks. However, volume standardization alone is not appropriate for overnight urine samples because it does not correct for urine concentration.
Consistent with previous reports, we found the relationships between gender and urinary stress hormones were significantly affected by creatinine correction (6). Specifically, creatinine standardization resulted in no gender differences in epinephrine or cortisol and higher levels of norepinephrine among women compared with men. We also found no ethnic differences in epinephrine, norepinephrine, or cortisol among blacks compared with whites. The differences between volume-corrected and creatinine-corrected hormone levels appear to be due to the placement of creatinine concentration in the denominator during creatinine standardization. This produces an underestimation of values among those with higher muscle mass.
To account for gender and ethnic differences in creatinine production while at the same time correcting for urine concentration, we calculated residual scores for creatinine and then regressed the urinary hormone levels on these residual creatinine scores. As would be expected, gender and ethnic differences in creatinine levels were substantially reduced in residual creatinine scores.
Analyses of the residual scores for hormones revealed a different pattern of results from that found when using the standard creatinine correction. Importantly, the pattern of results found for the residual scores for hormones was more consistent with values obtained through volume standardization and with previous 24-h urine studies (6, 17). We found the residualized epinephrine, norepinephrine, and cortisol were all higher among men compared with women. Also, although ethnic differences in urinary catecholamine levels were not statistically significant, our results suggest a larger sample size may identify higher epinephrine and norepinephrine among blacks compared with whites. Inferences regarding the relationship between cardiovascular disease and gender-ethnic differences in urinary free hormones should be made with caution, however, because urinary free hormones do not necessarily reflect the activity of plasma glucocorticoid and catecholamine metabolites. Second, we did not assess for variation in length of collection time or nighttime physical activity. Our findings therefore may reflect unmeasured group differences in these variables.
A limitation is the requirement of a measure of fat free mass if the correction procedure developed here is to be implemented. Indexes such as weight and BMI are economical to obtain, but we found weight and BMI to be unsuitable as substitutes for fat-free mass. Although our measure of fat-free mass confirmed that men were characterized by greater muscle mass than women, the BMI scores did not differ between these groups. Moreover, weight and BMI levels were found to be weakly correlated with our measure of fat-free mass and uncorrelated with creatinine levels. Thus, despite the simplicity and economy of weight and BMI measurement, substituting these measures for muscle mass is in effect equivalent to making no correction for the influence of muscle mass on creatinine levels.
Overnight urine samples offer an excellent opportunity for a time-integrated assessment of the stress response system. To date, inconsistencies have been noted between studies that report 24-h and overnight hormone levels (6, 15, 17). We believe these inconsistencies are related to the practice of standardizing urine concentration by dividing by creatinine concentration. Because of gender and ethnic differences in creatinine production, this practice underestimates hormone values among men and blacks. Utilization of residual creatinine scores permits the correction of overnight hormone levels for urine concentration while also eliminating muscle mass differences in creatinine production. Consequently, the correction procedure developed here in a population-based sample that varied across age, gender, and ethnicity should improve the measurement properties of overnight urinary hormone levels and thereby lead to further clarification of the role of the stress response system in gender and ethnic differences in disease. Moreover, given individual differences in muscle mass within gender and ethnicity, this procedure may increase the measurement properties of any urinary hormone assay, whether collected overnight or over a 24-h period, that are to be corrected using creatinine levels.
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GRANTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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REFERENCES |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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-hydroxycortisol to cortisol ratios: intraindividual variability and correlation under basal conditions and conditions of CYP 3A4 induction. J Clin Pharmacol 39: 487–494, 1999.[Abstract]
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