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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Menopause. Author manuscript; available in PMC 2010 October 5.
Published in final edited form as:
PMCID: PMC2950016
NIHMSID: NIHMS84679

Relative Androgen Excess During the Menopausal Transition Predicts Incident Metabolic Syndrome in Mid-Life Women: SWAN

Abstract

Background

During the menopausal transition, total testosterone remains unchanged while estrogen decreases markedly creating a state of relative androgen excess. We hypothesized that change in the testosterone/estradiol (T/E) ratio during the menopausal transition would be associated with incident metabolic syndrome.

Methods and Results

The association between incident metabolic syndrome and total estradiol, total testosterone, sex hormone binding globulin, the free androgen index (FAI), baseline ratio of total testosterone over total estradiol and the change of this ratio over time was evaluated in a multiethnic cohort of 1,862 pre- and perimenopausal women without diabetes enrolled in the Study of Women’s Health Across the Nation (SWAN). New cases (n=257) of the metabolic syndrome were identified in the cohort during 6296 woman-years of follow-up. The age adjusted total T/E ratio increased 10.1% per year during the 5 years of follow-up. Neither baseline nor change in estradiol were associated with incident metabolic syndrome. Low sex hormone biding globulin, free androgen index and high total testosterone at baseline all increased the risk of metabolic syndrome but their change over time did not. Both baseline total T/E ratio (1.41; 95% CI=1.17-1.1.69; P 0.001) and its rate of change (1.24; 95% CI=1.01-1.52; P 0.04) were associated with increased incident metabolic syndrome independent of ethnicity.

Conclusions

The interaction between testosterone and estradiol during the menopausal transition, rather than the individual change of each over time, is a factor in determination of risk for developing the metabolic syndrome during the menopausal transition. This relationship was independent of ethnicity and other factors associated with prevalent metabolic syndrome prior to the onset of the menopausal transition.

Keywords: Menopause, Testosterone, Estrogen, Metabolic, Syndrome

Introduction

It has long been the belief that the estrogen deficiency during the menopausal transition was responsible for the increased risk of cardiovascular disease seen in postmenopausal women. However, prospective randomized clinical trails have not demonstrated cardiovascular disease protection from estrogen therapyi,ii,iii, calling this long standing hypothesis into question. Less attention has been paid to role of endogenous androgens on cardiovascular risk factors in women despite studies suggesting that androgens may play an important role. High testosterone levels predict insulin resistance and incident type 2 diabetes in postmenopausal womeniv. Increased testosterone and low sex hormone biding globulin (SHBG) levels have also been individually linked to the some of the components of the metabolic syndrome and diabetes in both pre and postmenopausal womenv,vi,vii,viii,ix,x,xi. Low SHBG has been demonstrated to be independently associated with MS in postmenopausal women, after adjustment for BMI, in a recent sample from the Women’s Health Studyxii.

During the menopausal transition testosterone levels remain unchanged while estradiol levels decrease. Thus, the testosterone to estradiol ratio at baseline increases over time creating a state of “relative androgen excess”xiii,xiv,xv. The “relative androgen excess” created during the menopausal transition, may help explain the increasing risk of cardiovascular disease in postmenopausal women.

The metabolic syndrome generates a greater sensitivity for the detection of cardiovascular disease than its individual constituentsxvi,xvii,xviii,xix. We hypothesized that the relative excess of androgens created during the menopausal transition would be associated with an increased risk of developing the metabolic syndrome. We used the prospective data for the first five years of follow-up of the 3,302 premenopausal and early perimenopausal women enrolled in the Study of Women’s Health Across the Nation (SWAN), a multicenter, multiethnic, community-based, longitudinal study of perimenopausal women, to test this hypothesis.

Methods

Study Population

The design, sampling strategy, cohort recruitment and enrollment of SWAN have been described in detail elsewherexx. In brief, participants were enrolled at seven clinical sites. Recruitment techniques were designed to generate a community-based sample of women at each of the seven sites. All seven sites enrolled Caucasian women, and each site also enrolled women belonging to one pre-specified minority ethnic group. African-American women were enrolled in Boston, Chicago, the Detroit area, and Pittsburgh. Japanese, Chinese, and Hispanic women were enrolled in Los Angeles, Oakland California, and Hudson County New Jersey, respectively. Eligibility criteria for entry into the SWAN longitudinal cohort were as follows: age between 42–52; the presence of a uterus and at least one ovary; no current use of estrogens or other medications known to affect ovarian function; at least one menstrual period in the 3 months before screening; and self-identification as a member of one of the five eligible ethnic groups. The Institutional Review Board at each SWAN center approved the study. All women provided written informed consent prior to participation in the study.

A total of 3,302 women were enrolled. At baseline, the cohort consisted of 1550 Caucasians, 935 African-Americans, 281 Japanese, 250 Chinese, and 286 Hispanics at baseline. Women were followed yearly. The data reported here represent the analysis of the first 5 years of follow-up. From the full SWAN cohort a total of 1,862 women were used for these analyses and 1,440 women were excluded from the analysis for the presence of the following confounders: presence of the metabolic syndrome or diabetes at entry (N=844), abnormal TSH (0.1 – 9.99 uIU/ml; N=65) or abnormal testosterone (> 100 ng/ml; N=73) at any single visit, or use of hormone therapy or surgical menopause (N=239). Remaining exclusions were for missing or incomplete follow-up data (n=219).

Questionnaires and Physical Measurements

Demographic information, history of hypertension or diabetes, smoking status, perceived stress, physical activity, race/origin, and menopausal status were obtained using standardized questionnaires. Primary race/ethnicity was self-defined as one of the five groups noted above. Nutrient intake for total fat consumption, percent of total calories consumed from fat per day were assessed using the NCI (Block) food frequency questionnaire (FFQ), which was enhanced to accommodate the ethnic diversity in SWANxxi. Information on alcohol consumption was derived from the FFQ and categorized based on amount of alcohol consumptionxxii. Standardized protocols were used to measure height, weight, waist circumference, and blood pressure.

Biochemical Measurements and Calculation of Relative Androgen Excess

Biochemical analyses were done on the samples obtained at baseline and years 1, 3, 5 of follow-up. Blood was drawn on days 2-5 of the follicular phase after an 8 hour fast. Lipids and glucose were assayed at the Medical Research Laboratories, (Lexington, Kentucky, USA) which is certified by the National Heart Lung and Blood Institute, Centers for Disease Control Part III program. Lipid and lipoprotein fractions were analyzed on EDTA treated plasma. Total cholesterol and triglycerides were analyzed by enzymatic methods. HDL-C was isolated using heparin-2M manganese chloride. Serum insulin was measured using the RIA (DPC Coat-a-count, Los Angeles, CA) procedure and monitored monthly as part of the quality assurance program by the Diabetes Diagnostic Laboratory at the University of Missouri. Glucose was measured using a hexokinase-coupled reaction (Boehringer Mannheim Diagnostics, Indianapolis, IN).

Hormone assays were conducted at the University of Michigan SWAN Endocrine Laboratory using the ACS-180 automated analyzer (Bayer Diagnostics Corp, Norwood, MA). Sex hormone binding globulin (SHBG) was measured using a newly developed, two-site chemiluminescent assay with a lower limit of detection was 2 Nm; intra and interassay CV’s were 9.9% and 6.1%, respectively. The estradiol (E2) assay modifies the rabbit anti-E2-6 ACS-180 immunoassay to increase sensitivity, with a lower limit of detection (LLD) of 1.0 pg/mL; intra and interassay CV’s were 10.6% and 6.4%, respectively. The testosterone (T) assay modifies the rabbit polyclonal anti-T ACS-180 immunoassay, with a LLD of 2.19 ng/dL; intra and interassay CV’s were 10.5% and 8.5%, respectively.

Calculation of Free Androgen Index, T/E2 molar ratio and Relative Androgen Excess

The free androgen index (FAI) was used to estimate of the amount of free T, as it correlates well with the free T level as measured by equilibrium dialysis (FAI = 100*T(ng/ml)/28.84*SHBG(nM))xxiii. The Free Estrogen Index (FEI) was calculated as 100*E2(pg/ml)/272.11*SHBG(nM). To quantify the amount of T relative to E2, the molar ratio of log(FAI/FEI) was used. The log(FAI/FEI) is equivalent to the molar ratio of log(T/E2) as SHBG is represented in both the numerator and denominator and thus cancels out of the equation. Relative androgen excess is defined as the difference between the baseline T/E2 and each follow-up visit.

Definition of the Metabolic Syndrome

Currently there is no uniform well-accepted definition for the metabolic syndrome. We used the American Heart Assocation/National Heart Blood and Lung Institutes definition for the metabolic syndrome because the ethnic diversity of our study population included Asians; a group at increased risk of diabetes hypertension and dyslipidemia at lower overall adiposityxxiv,xxv,xxvi,xxvii. Any subject with any 3 of the 5 criteria was considered to have the metabolic syndrome: a) waist circumference ≥ 88 ( ≥ 80 for Asians), b) triglycerides ≥ 150 md/dl, c) HDL < 50 mg/dl, d) elevated blood pressure ≥ 130 mmHg systolic or ≥ 85 mm Hg diastolic or on antihypertensive drug treatment, e) fasting blood glucose ≥ 100 mg/dl.

Statistical methods

Ethnic differences in baseline characteristics were tested using standard Chi-squared or one-way ANOVA’s. Where necessary, variables were log-transformed. In order to asses how hormones changed over time, the unadjusted means of T, E2, T/E2 and RAE were plotted against time. In addition, change over time was estimated using mixed models, with each hormone modeled as a simple function of time, adjusting for baseline age. MS incidence rates were calculated as the total number of cases divided by the total number of person-years of follow-up. A univariate complimentary log-log model was used to test for ethnic differences in MS incidence.

The association between incident MS and hormone levels was modeled using a discrete-time proportional hazards model, i.e., a complementary log-log modelxxviii,xxix. A discrete-time model instead of a Cox analysis has been used since our identification of incident MS cases occurs only at several discrete times (i.e. the 01, 03 and 05 visits), which is known as grouped or interval-censored data. In each model, incident MS was modeled as a function of baseline (log-transformed) hormone and average annual change in hormone levels between baseline and each follow-up visit (on a log scale). All models were adjusted for ethnicity, clinical site, age at baseline, a time interval indicator, and ‘phlebotomy in window’ (whether phlebotomy at each visit was in days 2-5 of the menstrual cycle).

The ‘residual BMI’, a term designed to capture departure from expected change in BMI, was added into the models to correct for difference in weight over time as waist circumference is included in the definition of the metabolic syndrome. This latter variable was calculated as the error term from a simple model of each follow-up BMI as a function of baseline BMI. All other covariates, including physical activity, level of education, alcohol consumption, smoking, total fat consumption, percent of total calories consumed from fat per day, income and perceived stress, were taken from the baseline visit and included in final models only where statistical significance was achieved. Analysis was carried out using SAS Version 8. Model fit was verified using the Hosmer and Lemeshow goodness-of-fit testxxx.

The primary reason for participant drop-out was the initiation of hormone therapy. The validity of all models was assessed by investigating the impact of hormone therapy users on model results.

Results

Baseline characteristics of the final analytic sample are shown in Table 1. The distributions of all variables differed very significantly across ethnic groups (p<0.01 to p<0.001) except for marginally significant between ethnic differences for SHBG (p=0.04) and FAI (p=0.06). The T/E2 molar ratio did not differ significantly by ethnic group. Overall, Hispanics were considerably more likely to be less well educated. Chinese and Japanese women were more likely to be pre-menopausal at baseline. Chinese women were also considerably less likely to smoke, drink alcohol and consumed lower % of KCAL from fat while Caucasians were more likely to be physically active. The components of the metabolic syndrome, E2, T differed across ethnic groups. No differences were seen in SHBG, FAI and T/E2 molar ratio across ethnic groups.

Table 1
Baseline characteristics of the study sample by ethnicity

During the follow-up period, the age-adjusted estradiol levels decreased by an estimated 12.0% each year (P<0.0001), while the average annual age-adjusted decrease in total testosterone was much less (3.1% per year, P<0.0001, Figure 1). At baseline, the unadjusted median T/E2 molar ratio ranged from 5.62 in Hispanics to 6.62 in Chinese women (table 1). The age adjusted T/E2 molar ratio increased 10.1% per year during the 5 years of follow-up (P<0.001) creating a state of androgen excess relative to the baseline T/E2 values (Figure 2).

Figure 1
The changing relationship of estradiol to testosterone as the menopausal transition progresses. Estradiol is shown in pmol/L and testosterone in pmol/L × 100 with units on the Y axis depicting hormone concentration. The X axis depicts time since ...
Figure 2
Change in the molar ratio of testosterone to estradiol as the menopausal transition progresses. The Yaxis shows the Ratio, and the X axis is identical to Figure 1. The shaded triangle indicates the increase in the testosterone to estradiol ratio, or the ...

There were 257 new cases of the metabolic syndrome during 6296 person-years of follow-up. Hispanic had a greater incidence rate than Caucasians (8.81 vs. 4.12 per 100 person years) while Chinese women had lower rates than Caucasians (2.34 vs. 4.12 per 100 person years) (Table 2).

Table 2
Incident metabolic syndrome reported as number of cases per 100 person years

Individual models were created to asses the association of E2 (model 1), T (model 2), SHBG (model 3), FAI (model 4) and the T/E2 molar ratio, RAE (model 5) with the incidence of the metabolic syndrome (Table 3). Neither the baseline E2 or its rate of change were associated with incidence (model 1). Although higher baseline T, FAI, and lower SHBG levels were associated with higher incidence, the models for rates of change over time were not statistically significantly (models 2-4). Unlike FAI and SHBG, both a higher baseline T/E2 molar ratio and change over time in the RAE were associated with increased risk of developing MS (model 5).

Table 3
Results from multivariate models. Each row represents a separate multivariable model.

The associations between risk of MS and either baseline T/E2 molar ratio and RAE did not vary significantly by ethnicity, with coefficients similar in magnitude and direction across all ethnic groups. Interaction terms between ethnicity and baseline hormone levels, ethnicity and change in hormone levels, and baseline hormone and change in hormone were not found to be significant.

To estimate for potential changes in risk associated with hormone therapy use, each model was rerun including hormone therapy users and adjusted for hormone therapy use via an indicator variable. The model coefficients for each hormone and its change were unchanged in direction and significance level when the indicator variable was placed in the model. The indicator variable for hormone therapy use was not significant, suggesting that hormone therapy use was not associated with risk of MS.

Discussion

Higher baseline testosterone/estradiol ratio and change over time in the relative androgen excess were associated with increased risk of developing the metabolic syndrome during the menopausal transition. Neither baseline estradiol nor its decline over time was associated with increased overall risk. While the baseline testosterone, FAI, and SHBG all appeared to be associated with an increased risk of developing metabolic syndrome, their change over time was not. These findings suggest that there is a complex interaction between testosterone and estradiol, rather than simply changes in testosterone, free androgen index and SHBG, determines a woman’s risk for developing the metabolic syndrome during the menopausal transition.

Our results highlight that estrogen deficiency by itself is not as important as the relationship between testosterone and estradiol during the menopausal transition. This finding is supported by primary and secondary prevention randomized, clinical trials of postmenopausal women that do not demonstrate a benefit of exogenous estradiol1-3. Observational cohort studies have demonstrated that increased endogenous estradiol in the postmenopause is not associated with reduced cardiovascular events4.

Endogenous and exogenous testosterone influence a woman’s cardiovascular risk factors. Unbound circulating testosterone best reflects a woman’s overall androgen statusxxxi. High free androgen index levels have been associated with a more atherogenic lipid profile independent of metabolic factors and health behaviors5. High free androgen index has been associated with the metabolic syndrome in postmenopausal women6. Administration of testosterone to normal females and female transsexuals leads to insulin resistance as measured by an insulin clampxxxii,xxxiii. Such doses are typically supraphysiological for women, and at lower doses of testosterone, carbohydrate metabolism has been reported to be unaffected in two short term studies of over 1,000 women, although specific measures were not shown and long term data are not available.xxxiv,xxxv We have previously demonstrated that high free androgen index and low SHBG were strongly and consistently related to adverse cardiovascular risk factors during cross sectional analysis of the SWAN cohort. Even after adjusting for body mass index, free androgen index was most strongly associated with PAI-1, tPA, triglycerides and glucose while SHBG was most strongly associated with PAI-1, triglycerides and HDLxxxvi,xxxvii. The present findings extend the logic of examining androgens in women in a longitudinal fashion, as they appear to be strongly associated with adverse intermediate outcomes such as metabolic syndrome.

The Prospective Cardiovascular Munster Program was used to estimate the risk of an acute coronary events in the Melbourne Women’s Midlife Health Project, a cohort of 438 Australian midline women were followed through the menopausal transitionxxxviii. In this study, lower than average estradiol levels, estradiol levels that decreased, and high free testosterone levels were associated with increased risk of a coronary event. While our study supports the increased risk seen with free androgen index, neither our study nor other previous studies support their findings as it pertains to decreasing estrogen levels4-6.

During our prospective analysis, both the free androgen index and SHBG at baseline were associated with an increased risk for developing the metabolic syndrome, but their change over time was not. This suggests that the baseline values in free androgen index and SHBG predict a woman’s overall risk independent of the change over time in these variables. This is in agreement with previously published data from SWAN, in which baseline characteristics of the women were associated with the presence of the metabolic syndrome. In this study, SHBG and FAI remained independently associated with metabolic syndrome at baseline after adjusting for other factors such as age and waist circumference. Thus, although circulating free androgens and SHBG may predict a womans’s risk before she enters the menopausal transition, the change in these two factors over time does not explain why a woman’s risk of developing the metabolic syndrome increases during the menopausal transition. In our cohort, the testosterone/estradiol molar ratio increased over time creating a state of relative androgen excess during the menopausal transition (Figure 2). Both the baseline testosterone/estradiol molar ratio and the change over time in the relative androgen excess were associated with increased risk of developing the metabolic syndrome after correcting for multiple confounding variables. The associated risk seen with relative androgen excess was independent of ethnicity notwithstanding the ethnic differences in the baseline values of E, T and incidence of MS across the ethnic groups suggesting that ethnicity may predict an individual woman’s overall riskxxxix, but not the manner in which her risk changes during the transition.

Thus, not only does the baseline testosterone/estradiol molar ratio and its change over time suggests that the complex interplay between both of testosterone and estradiol during the menopausal transition may be responsible for increasing the risk of MS. Physiological interplay between androgens and estrogens in various endocrine targets is well established typically having opposing actions38. Androgen and estrogen responses occur at the promoter regions of selected genes independently through distinct response elements. This androgen estrogen interplay may reflect the combined effects of sex steroid specific regulated gene expression, each hormone may affect the expression of the other’s receptor, or each receptor may interact with each other39-42.

A potential mechanism that could explain our findings are the effects of androgens on inulin resistance. Exogenous administration of androgens to women has been demonstrated to increase insulin resistance31,32. As SHBG levels are suppressed by hyperinsulinemia, the relative androgen excess during the menopausal transition could lead to an insulin resistant state that subsequently further suppresses levels of SHBG causing higher levels of free testosterone. As low SHBG levels have been previously associated with an increased risk of a variety of cardiovascular risk factors and incident cardiovascular disease in post-menopausal women independent of insulin, obesity and dyslipidemia, further study is needed to assess if this proposed mechanism is valid43,44.

Our study has limitations. A small number of women in our cohort may have developed polycystic ovarian syndrome (PCOS) during follow-up. However, in the SWAN cohort, women with PCOS were largely excluded at entry as 87% of SWAN participants reported an intermenstrual interval of 21-35 days at baseline and the eligibility requirement of at least one menstrual period within the past 3 months. We also excluded from the analyses women with the metabolic syndrome and diabetes at entry, further decreasing the presence of women who may have had PCOS in this analysis. It must also be kept in mind that our blood sampling is restricted to the early follicular phase of the cycle. During the early stages of the menopausal transition, estradiol and, to a lesser extent, testosterone, are secreted in varying quantities over the menstrual cycle and thus this single assessment may not be reflective of the entire hormone exposure.

Our results imply that the complex interplay between testosterone and estradiol has been a relatively overlooked factor as a cause of morbidity in women at mid-life. The current lack of evidence that exogenous estrogen decreases cardiovascular morbidity and mortality in postmenopausal women argues that there is not a simple, single hormone that influences cardiovascular disease risk in peri and postmenopausal women. An understanding of how changes in the testosterone over estradiol molar ratio influence the ontogeny of the metabolic syndrome and insulin resistance may be important for the development of new cardiovascular disease prevention strategies. Moreover, the recent enthusiasm for the use of testosterone as a form of hormonal replacement for postmenopausal women30,45 will need to take into account the possible introduction of an adverse metabolic profile in at least some women, prior to its widespread initiation.

Acknowledgments

The Study of Women’s Health Across the Nation (SWAN) has grant support from the National Institutes of Health, DHHS, through the National Institute on Aging, the National Institute of Nursing Research and the NIH Office of Research on Women’s Health (Grants NR004061, AG017104, AG012505, AG012535, AG012531, AG012539, AG012546, AG012553, AG012554, AG012495).

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.

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

J.I.T. was supported by Grant HD-01457 as a BIRCWH Scholar, NS was supported by HD041978.

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