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Clinical Chemistry 54: 1027-1037, 2008. First published April 10, 2008; 10.1373/clinchem.2007.098996
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Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors
(Clinical Chemistry. 2008;54:1027-1037.)
© 2008 American Association for Clinical Chemistry, Inc.

Lipids, Lipoproteins, and Cardiovascular Risk Factors

Ethnic Differences in C-Reactive Protein Concentrations

Alyson Kelley-Hedgepeth1, Donald M. Lloyd-Jones2, Alicia Colvin3, Karen A. Matthews4, Janet Johnston5, MaryFran R. Sowers6, Barbara Sternfeld7, Richard C. Pasternak8, Claudia U. Chae9,a for the SWAN Investigators

1 Molecular Cardiology Research Institute, Tufts Medical Center, Boston, MA; 2 Department of Preventive Medicine and Division of Cardiology, Northwestern University, Chicago, IL; 3 Epidemiology Data Center and Departments of 4 Psychiatry and 5 Epidemiology, University of Pittsburgh, Pittsburgh, PA; 6 Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI; 7 Department of Epidemiology and Biostatistics, Division of Research, Kaiser Permanente Medical Care Program, Oakland, CA; 8 Merck & Co., Inc., Rahway, NJ; 9 Cardiology Division, Massachusetts General Hospital, Boston, MA.

aAddress correspondence to this author at: Cardiology Division, YAW 5800, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114. Fax (617) 726-1209; e-mail cchae{at}partners.org.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Limited data exist regarding the ethnic differences in C-reactive protein (CRP) concentrations, an inflammatory marker associated with risk of cardiovascular disease (CVD). We hypothesized that known CVD risk factors, including anthropometric characteristics, would explain much of the observed ethnic variation in CRP.

Methods: We performed a cross-sectional analysis of 3154 women, without known CVD and not receiving hormone therapy, enrolled in the Study of Women’s Health Across the Nation (SWAN), a multiethnic prospective study of pre- and perimenopausal women.

Results: The study population was 47.4% white, 27.7% African-American, 8.5% Hispanic, 7.7% Chinese, and 8.6% Japanese; mean age was 46.2 years. African-American women had the highest median CRP concentrations (3.2 mg/L), followed by Hispanic (2.3 mg/L), white (1.5 mg/L), Chinese (0.7 mg/L), and Japanese (0.5 mg/L) women (all pairwise P < 0.001 compared with white women). Body mass index (BMI) markedly attenuated the association between ethnicity and CRP. After adjusting for age, socioeconomic status, BMI, and other risk factors, African-American ethnicity was associated with CRP concentrations >3 mg/L (odds ratio 1.37, 95% CI 1.07–1.75), whereas Chinese and Japanese ethnicities were inversely related (0.58, 0.35–0.95, and 0.43, 0.26–0.72, respectively).

Conclusions: Modifiable risk factors, particularly BMI, account for much but not all of the ethnic differences in CRP concentrations. Further study is needed of these ethnic differences and their implications for the use of CRP in CVD risk prediction.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Cardiovascular disease (CVD)1 has a significant impact on morbidity and mortality worldwide and is the leading cause of death in the United States in women, as in men(1). C-reactive protein (CRP), a marker of systemic inflammation, is independently associated with risk of myocardial infarction and cardiovascular death in prospective cohort studies(2)(3)(4). The American Heart Association (AHA) and the CDC have evaluated CRP as a risk assessment tool and suggested that cut points of <1 mg/L, 1–3 mg/L, and >3 mg/L be used to identify those at lower, average, and high relative risk, respectively, for CVD events(5). However, because these reference intervals were derived from largely white cohorts of European descent(2)(3)(4), the AHA/CDC panel also identified a major and urgent need for data to address the gaps in our knowledge regarding CRP and its utility in CVD risk prediction in other ethnic populations(5).

An important observation in the Study of Women’s Health Across the Nation (SWAN) cohort is that CRP concentrations vary significantly between ethnic groups, with the highest concentrations seen in African-American participants, followed in order by Hispanic, white, Chinese, and Japanese participants(6). Ethnic differences in CRP concentrations have been found in several other cross-sectional studies, but the basis for these differences is unclear(7)(8)(9)(10)(11). In this analysis, we examined the factors associated with the observed ethnic differences in CRP concentrations in SWAN, including risk factors for CVD, detailed anthropometric measures, sex hormone concentrations, and markers of socioeconomic status (SES). We hypothesized that the ethnic variation in CRP concentrations observed in SWAN would be mediated by other known cardiovascular risk factors, including measures of adiposity, insulin resistance, hypertension, and lifestyle habits.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
study population
SWAN is a multicenter, community-based, longitudinal study of biological and psychosocial changes in 3302 pre- and perimenopausal women. Details of recruitment and data collection have been published(12). Eligibility criteria included age 42–52 years; intact uterus and at least 1 ovary; no current use of estrogens or other medications known to affect ovarian function; at least 1 menstrual period in the 3 months before screening; and self-identification as a member of 1 of the 5 eligible ethnic groups: white, African-American, Hispanic, Chinese, or Japanese. Each site recruited non-Hispanic whites as well as 1 prespecified minority group.

We excluded women who were missing CRP measurements and those with self-reported CVD, defined as a history of angina, myocardial infarction, or stroke, leaving 3154 women for this analysis. The institutional review committees of the study sites approved the study, and all participants provided informed consent. Blood samples and questionnaire data regarding demographic variables, lifestyle habits, prevalent medical conditions, and medications were obtained at the baseline visit as described(6).

blood samples
Blood samples, drawn into EDTA-containing tubes after a minimum 10-h fast, were timed to occur between days 2 and 5 of the follicular phase of the menstrual cycle. Samples were stored at 4 °C before processing, then centrifuged; the separated plasma was frozen at –80 °C and shipped on dry ice to Medical Research Laboratories (Highland Heights, KY), a facility certified by the National Heart, Lung, and Blood Institute and CDC Part III program(13), for analysis. High-sensitivity CRP was measured using ultrasensitive rate immunonephelometry on the Behring Nephelometer II, with a lower limit of detection of 0.01 mg/L(14). The limit of quantification of the assay is determined by the lower limit of the reference curve and depends on the CRP concentration of the standard. Thus it is possible to have a different limit of quantification for each reference curve. The CRP assay within-run CV was 3.3%, and the between-day imprecision was 4.0% at a concentration of 58.9 mg/L and 6.8% at a concentration of 10.2 mg/L.

Lipid and lipoprotein fractions were analyzed in EDTA-treated plasma. We used the Friedewald formula(15) to calculate LDL cholesterol unless special circumstances dictated the use of the DeLong formula(16). Given that a 12-h fast is optimal for the use of the Friedewald equation(17), and SWAN study protocol required only a minimum 10-h fast, we acknowledge that SWAN LDL cholesterol values may be underestimated. We analyzed total cholesterol and triglycerides by enzymatic methods. HDL cholesterol was isolated after addition of heparin and 2 mol/L MnCl2. Serum insulin was measured by RIA (DPC Coat-a-count) and monitored as part of the monthly quality assurance program by the Diabetes Diagnostic Laboratory at the University of Missouri. We measured glucose with a hexokinase-coupled reaction (Boehringer Mannheim Diagnostics). HOMA-IR (homeostasis model assessment of insulin resistance) was calculated as (fasting insulin x fasting glucose)/22.5(18).

Hormone assays were performed at the University of Michigan SWAN Endocrine Laboratory with an ACS-180 automated analyzer (Bayer Diagnostics Corp). Serum follicle-stimulating hormone (FSH) concentrations were measured with a 2-site chemiluminescent immunoassay, sex hormone–binding globulin (SHBG) with a competitive chemiluminescent assay, serum estradiol (E2) concentrations with a modified, offline ACS-180 (E2–6) immunoassay, and testosterone concentrations with the ACS-180 total testosterone assay modified to increase precision in the low ranges.

physical measurements and definitions of prevalent disease
Height, weight, waist and hip circumferences, and blood pressure were measured by trained SWAN technicians using standardized protocols. Height and weight were recorded without shoes while wearing light clothing. Waist circumference, defined as the narrowest part of the torso, was measured over undergarments or light clothing. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Waist-to-hip ratio (WHR) was calculated as waist circumference divided by hip circumference. Three blood pressure measurements were taken, using a mercury column manometer after a minimum of 5 min of rest with participants in the seated position, and the average of the latter 2 values was used. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of antihypertensive medications.

Diabetes was defined as fasting glucose 126 mg/dL or the use of diabetic medications. Women were considered to have metabolic syndrome if they met at least 3 of the following 5 criteria: triglycerides ≥150 mg/dL2 ; HDL cholesterol <50 mg/dL; systolic blood pressure ≥130 mmHg, diastolic blood pressure ≥85 mmHg, or on antihypertensive medication; fasting glucose >10 mg/dL and/or diabetes; and waist circumference >80 cm for Chinese and Japanese women and ≥88 cm for white, Hispanic, and African-American women(19).

statistical analysis
We compared clinical characteristics by ethnic group using {chi}2 statistics for categorical variables and analysis of variance for continuous measurements. We calculated Spearman correlation coefficients to assess the relationships between CRP concentrations and continuous CVD risk factors and used multivariate linear regression models to evaluate the relationship between ethnicity and CRP concentrations. We assessed the linear-regression model fit by examining residual plots. Based on the distribution of the residuals, we log-transformed CRP and verified a normal probability plot of residuals. Linear regression analyses were stratified to investigate the impact of ethnicity. We followed a hierarchical model, with the addition of age and markers of SES, followed by the addition of anthropometric parameters, comorbidities, lifestyle factors, and serum lipid concentrations. We assessed multivariate model performance by comparing the model adjusted R2 (95% CI) and used colinearity diagnostic tests to examine the relationship between BMI and WHR; variance inflation factors ranged from 1.5 to 1.8, and both terms were therefore included in the multivariate models. Coefficients of these models are expressed as percent difference (95% CI) in CRP concentration.

In secondary analyses, we examined the joint effects of BMI and WHR on log-CRP concentrations, after adjustment for age and ethnicity in a linear regression model. For this analysis, participants were stratified by clinical categories of BMI (<25, 25–29.9, and ≥30 kg/m2) and by tertiles of WHR. We tested for statistical interaction between BMI and WHR by adding the multiplicative term to the full multivariate models. Finally, we examined multivariable logistic regression models to determine covariates associated with having a high relative risk of CRP >3 mg/L.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Clinical characteristics differed by ethnicity (Table 1 ). African-American women, followed by Hispanic women, had the highest prevalence of obesity, hypertension, and diabetes. Metabolic syndrome was most common in Hispanic women, who correspondingly had the highest triglyceride and LDL cholesterol concentrations and the lowest concentrations of HDL cholesterol. Hispanic women were the least physically active and the least likely to have a college education; African-American women were the most likely to be current smokers; and abstinence from alcohol was most common in Chinese women.


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  		Table 1. Clinical characteristics by ethnicity of 3154 pre- and perimenopausal women without known CVD in SWAN.


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  		Table 1A. Clinical characteristics by ethnicity of 3154 pre- and perimenopausal women without known CVD in SWAN. (Continued from page 1030)

Fig. 1 shows that median CRP concentrations were highest in the African-American participants [3.2 mg/L, interquartile range (IQR) 1.1–7.7], followed by Hispanic (2.3 mg/L, IQR 1.0–5.1), white (1.5 mg/L, IQR 0.6–4.1), Chinese (0.7 mg/L, IQR 0.4–1.6), and Japanese (0.5 mg/L, IQR 0.2–1.1) participants. Median CRP values varied significantly in all non-white ethnic groups compared with whites (all pairwise P < 0.001). We also noted variation in the range of CRP concentrations by ethnic group, with the largest range of values in white followed by African-American women.


Figure 1
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  		Figure 1. Median (IQR) CRP concentrations by ethnicity.

Compared with whites, all ethnic groups had significant differences in median CRP values (all pairwise ANCOVA P < 0.001).

Concentrations of CRP (Table 2 ) were strongly correlated with BMI in all ethnic groups, particularly in white, African-American, and Japanese women. Systolic blood pressure had a modest correlation with CRP concentrations; this was most evident in the Caucasian and Chinese women, although statistically significant across all ethnic groups. Concentrations of CRP were moderately correlated with WHR and triglyceride concentrations and were inversely correlated with HDL cholesterol; the magnitude of these correlations were modest and were weaker in Hispanics.


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  		Table 2. Correlations between CRP concentrations and continuous cardiovascular risk factors by ethnic group.

We determined which risk factors and potential confounders influenced the association between ethnicity and CRP concentrations in a series of linear regression models (Table 3 ). We examined the strength of the associations between CRP and anthropometric measures including BMI, waist circumference, and WHR and between different measures of glucose intolerance including diabetes, HOMA-IR, and metabolic syndrome. We found that BMI and WHR, but not waist circumference, had the greatest effect on the log-CRP β-coefficient (data not shown), and therefore chose to use these 2 anthropometric terms in our regression modeling. Likewise, glucose intolerance (categorized as normal, impaired fasting glucose, or diabetes) was more informative than HOMA-IR and metabolic syndrome (data not shown).


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  		Table 3. Percent difference in CRP concentration by ethnicity after covariate adjustment in SWAN.

After adjustment for age (model 1), African-American or Hispanic ethnicity was associated with having higher CRP concentrations, whereas Chinese or Japanese ethnicity was inversely associated with CRP concentrations (all P < 0.001). In model 2, after the addition of markers of SES, the association between ethnicity and CRP in Hispanic women was no longer statistically significant; we found modest effects in African-American women and only marginal effects of SES in Chinese and Japanese women. Although remaining statistically significant, the strength of the association between ethnicity and CRP concentrations was substantially attenuated after controlling for BMI (model 3), especially in the African-American, Chinese, and Japanese women. When WHR was added to the model (model 4), these associations were further attenuated in the Hispanic and African-American women, whereas the inverse associations in the Chinese and Japanese women became somewhat stronger. Additional adjustment for other cardiovascular risk factors and medication use (model 5), as well as hormone concentrations (model 6), had relatively modest impact on the associations between ethnicity and CRP in African-American, Chinese, and Japanese women. The association between ethnicity and CRP concentrations remained nonsignificant in Hispanic women in the fully adjusted multivariate models (model 5), with SES and physical activity, followed by hypertension and HDL cholesterol concentrations, identified as the major confounders. Model fit was substantially improved with the addition of BMI (age-, SES-, and BMI-adjusted R2 = 0.39, compared with 0.15 in the model adjusting for age and SES, suggesting that BMI accounted for 24% of the variance in CRP concentrations); adjusting for additional covariates resulted in only modest incremental improvement in model fit (adjusted R2 improved from 0.39–0.40 to 0.43 in models 4–6).

As demonstrated in the above models, BMI and WHR were important confounders of the association between ethnicity and CRP. After adjustment for age and ethnicity, within each tertile of BMI, CRP concentrations increased with increasing WHR (Fig. 2 ). Similarly, within each WHR tertile, higher CRP concentrations were found as BMI increased (all P < 0.001 vs those with BMI <25 and in the lowest WHR tertile). The test for interaction between BMI and WHR was significant P = 0.03), with BMI (especially BMI above 30 kg/m2) having a stronger influence on CRP concentrations than WHR. Given the lack of overlap between ethnicities at the extremes of BMI, with 50.5% of African-American and 35.2% of Hispanic women having BMI 30 kg/m2 and most Chinese (76.7%) and Japanese (78.8%) women having BMI <25 kg/m2, we performed a sensitivity analysis by repeating our multivariate models restricted to the middle 75% of the population distribution of BMI. We found similar results, in that increases in BMI and WHR had an additive influence on CRP concentrations.


Figure 2
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  		Figure 2. Age- and ethnicity-adjusted mean CRP concentrations, by strata of BMI and WHR.

Compared to those with both BMI <25 kg/m2 and WHR in the first tertile, all P < 0.0001. In these models, mean log-CRP concentrations were back-transformed to provide the geometric means depicted in the y axis.

After multivariate adjustment, compared with whites, African-American ethnicity was independently associated with having CRP concentrations >3 mg/L [odds ratio (OR) 1.37, 95% CI 1.07–1.75] (Table 4 ). Chinese (OR 0.58, 95% CI 0.35–0.95) and Japanese (0.43, 0.26–0.72) ethnicities were inversely associated, and Hispanic ethnicity was not associated (0.82, 0.54–1.23), with having CRP >3 mg/L. Obesity, defined as BMI ≥30 kg/m2, was associated with a 6-fold increased risk of having CRP >3 mg/L. Other components of the metabolic syndrome, including glucose intolerance/diabetes, systolic blood pressure, and triglyceride and HDL cholesterol concentrations, were also significant predictors of CRP concentrations >3 mg/L in these women. After multivariate adjustment, WHR was no longer statistically significant (P = 0.64). High school education or less, a marker of SES, was also an independent predictor of increased CRP concentrations in the multivariate model. There was a trend toward higher physical activity scores and moderate alcohol intake being associated with lower CRP concentrations.


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  		Table 4. Multivariate ORs (95% CIs) of predictors of having a high-risk CRP concentration (>3 mg/L)


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this population of pre- and perimenopausal women without known CVD, CRP concentrations varied significantly among ethnic groups, with the highest concentrations among African-American women, followed by Hispanic, white, Chinese, and Japanese women. Known cardiovascular risk factors, especially BMI, accounted for much, but not all, of these ethnic differences. After substantial multivariate adjustment for known and suspected confounders, significant residual ethnic variation remained. Compared with whites, African-American ethnicity was associated with a 37% increased risk of having a CRP level >3 mg/L, whereas Chinese and Japanese ethnicities were 42% and 57% less likely to have CRP concentrations >3 mg/L. There was no association between Hispanic ethnicity and CRP level.

Our data add to a growing body of literature documenting ethnic differences in CRP concentrations(6)(7)(8)(9)(10)(11). Our findings are similar to those from the Women’s Health Study (WHS)(8), which documented that ethnic differences in CRP concentrations were substantially attenuated after controlling for BMI. Similarly, in a Canadian population, CRP concentrations were highest among men and women of Aboriginal ancestry, followed by those of South Asian, European, and Chinese ancestry(9). As in SWAN, the ethnic differences in CRP concentrations diminished after adjusting for BMI and waist circumference, although significant differences remained between Aboriginals and South Asians compared with whites.

Importantly, our study provides information regarding CRP concentrations in Chinese and Japanese women, in whom limited data exist. Both Japanese and Chinese women had lower CRP concentrations compared with other ethnicities. Controlling for BMI did lessen the impact of ethnicity on CRP concentrations in both these ethnic groups.

Based on our findings and those of others, substantial ethnic differences therefore appear to exist in the distribution of CRP and persist even after multivariate adjustment for known and suspected confounders. Genetic variation may account for this, as recent studies have shown that polymorphisms in the CRP gene are associated with circulating CRP concentrations, with frequency differences observed between ethnic groups(20)(21)(22)(23). Interestingly, a growing number of studies in non-white Asian populations have found that CRP concentrations in the upper quartile for that population are significantly associated with risk of diabetes/metabolic syndrome(24)(25)(26)(27)(28), despite being lower than the concentrations associated with the same diseases in white(29)(30) and Aboriginal(28) populations. Given these findings, it seems plausible that ethnic-specific ranges of CRP concentrations may be needed to ensure proper risk stratification in cardiovascular disease as well.

Sex discrepancies may also need to be accounted for when evaluating the cardiovascular risk associated with CRP concentrations. This could not be directly addressed in the SWAN analysis; however, differences in CRP concentrations by sex have been consistently observed(9)(10). The MESA (MultiEthnic Study of Atherosclerosis) cohort recently examined the impact of sex and ethnicity on CRP concentrations(31) and found women to have consistently higher CRP concentrations compared with ethnicity-matched men. These differences persisted after controlling for anthropometric and lifestyle factors.

Despite the persistent influence of ethnicity on CRP concentrations, it should be emphasized that much of the observed ethnic difference was accounted for by anthropometric measures and other risk factors. We found a strong joint association between BMI and WHR with CRP concentrations independent of age, SES, and ethnicity. The associations between ethnicity and CRP concentrations in SWAN appear to be influenced by the higher prevalence of obesity in African-American study participants and the relatively low BMI in Chinese and Japanese women(32)(33). The association between modifiable risk factors and circulating CRP concentrations is an attractive target for clinical intervention. Obesity, glucose intolerance/diabetes, and lower SES (high school education or less) were all significant predictors of increased CRP, whereas moderate alcohol use and physical activity tended to be associated with lower CRP concentrations. Therefore, regardless of the absolute CRP scale used for risk stratification, these results provide additional justification for clinicians to advocate for lifestyle modification to reduce risk.

Ethnic differences in CRP concentrations also persisted in our analysis despite controlling for SES. A comprehensive review of >30 studies(34) found SES to be independently and inversely related to CRP concentrations. We confirmed this finding within the SWAN cohort, where we found educational level to be the most informative SES predictor of CRP concentrations. The impact of ethnicity and SES on CRP concentrations was also examined in the MESA cohort(35), where educational level was found to be a strong predictor of CRP. Yet in MESA, further examination in multivariate models found that the relationship between CRP and SES persisted only in whites, with substantial confounding by metabolic factors, adiposity, and behaviors. Given the overlap between mediating factors and the cross-sectional nature of this analysis, it is difficult to assess causality. The influence of ethnicity on CRP concentrations remains blurred given the confounding and high degree of association between many of these factors.

Our study’s strengths include its composition as a multiethnic cohort, from whom detailed, standardized clinical assessments, anthropometric measures, and laboratory data were obtained. However, our results should be applied only to pre- and perimenopausal women. Because of the study’s cross-sectional nature, our results do not imply causality. Ethnic status was based on self-identification, which may result in heterogeneity, particularly within African-American and Hispanic groups. Finally, we did not adjust for the possible influence of concomitant acute or chronic inflammatory conditions in this healthy population. We had only 1 measurement of CRP available at baseline, so a high CRP concentration could not be confirmed by a repeat test, as is typically done in clinical practice. Nevertheless, SWAN represents a valuable resource in which to examine cardiovascular risk factors in understudied ethnic groups and in women.

In conclusion, C-reactive protein concentrations differ with ethnicity. In this cohort of pre- and perimenopausal women, the highest concentrations were found in African-American women, followed in order by Hispanic, white, Chinese, and Japanese women. Modifiable risk factors, particularly BMI, account for much but not all of the differences in CRP concentrations between ethnic groups. Further study of these ethnic differences and their implications for how to use CRP in CVD risk stratification is needed.

swan
Clinical Centers.
University of Michigan, Ann Arbor (MaryFran Sowers, PI); Massachusetts General Hospital, Boston, MA (Robert Neer, PI, 1994–1999; Joel Finkelstein, PI, 1999–present); Rush University, Rush University Medical Center, Chicago, IL (Lynda Powell, PI); University of California, Davis/Kaiser (Ellen Gold, PI); University of California, Los Angeles (Gail Greendale, PI); University of Medicine and Dentistry, New Jersey Medical School, Newark (Gerson Weiss, PI, 1994–2004; Nanette Santoro, PI, 2004–present); and the University of Pittsburgh, Pittsburgh, PA (Karen Matthews, PI).

NIH Program Office.
National Institute on Aging, Bethesda, MD (Marcia Ory 1994–2001; Sherry Sherman 1994–present); National Institute of Nursing Research, Bethesda, MD (program officers).

Central Laboratory.
University of Michigan, Ann Arbor (Daniel McConnell, Central Ligand Assay Satellite Services).

Coordinating Center.
New England Research Institutes, Watertown, MA (Sonja McKinlay, PI, 1995–2001); University of Pittsburgh, Pittsburgh, PA (Kim Sutton-Tyrrell, PI, 2001–present).

Steering Committee.
Chris Gallagher, Chair; Susan Johnson, Chair.


   Acknowledgments
 
Grant/Funding Support: SWAN has grant support from the National Institutes of Health, Department of Health and Human Services, through the National Institute on Aging, the National Institute of Nursing Research, and the NIH Office of Research on Women’s Health (grants NR004061, AG012505, AG012535, AG012531, AG012539, AG012546, AG012553, AG012554, AG012495). The funding sources for this study played no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript before publication.

Financial Disclosures: We attest that our authors have no conflicts of interest, with the exception of the following items: MaryFran R. Sowers, research funding, grant no. 5U01NR004061-13, >$10 000; Karen A. Matthews, research funding, grant no. 5U01AG012546-14, >$10 000; Richard C. Pasternak, employment at Merck and Co., Inc., since 2005.

Acknowledgments: We thank the study staff at each site and all the women who participated in SWAN.


   Footnotes
 
1 Nonstandard abbreviations: CVD, cardiovascular disease; CRP, C-reactive protein; SWAN, Study of Women’s Health Across the Nation; SES, socioeconomic status; BMI, body mass index; WHR, waist-to-hip ratio; IQR, interquartile range.

2 Although this journal has a policy of using SI nomenclature and expressing concentrations per liter, the concentration units provided by the authors were retained here to allow comparison with other publications from SWAN.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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