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University of Michigan (J.F.R., M.S., I.B.), Ann Arbor, Michigan 48109-0276; University of California, Davis (E.B.G.), Davis, California 95616; University of California, Los Angeles (G.A.G.), Los Angeles, California 90095; and University of Pittsburgh (J.T.B., S.E.B., K.A.M.), Pittsburgh, Pennsylvania 15260
Address all correspondence and requests for reprints to: John F. Randolph, Jr., M.D., L4228 Women’s Hospital, University of Michigan Health System, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109-0276. E-mail: jfrandol{at}med.umich.edu.
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Abstract |
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Objective: The purpose of this report was to relate longitudinal serum concentrations of the reproductive hormones estradiol (E2), FSH, testosterone (T), dehydroepiandrosterone sulfate (DHEAS), and SHBG and the free hormone indices free E2 index (FEI) and free T index (FTI) with the occurrence of VMS in women traversing the menopausal transition.
Design and Setting: The Study of Women’s Health Across the Nation is a multisite, longitudinal, cohort study of the menopausal transition being conducted in community-based groups of women.
Participants and Main Outcome Measures: At baseline, 3302 menstruating women who belonged to one of five ethnic/racial groups were recruited and followed up with annual visits. Frequencies of symptoms (hot flashes, night sweats) for the prior 2 wk and measures of other covariates as well as potentially confounding variables were self-reported in the annual interview. Serum was obtained annually, on d 2–5 of a spontaneous cycle in cycling women or within 90 d of the anniversary of the baseline study visit in noncycling women and assayed for FSH, E2, T, SHBG, and DHEAS. FTI and FEI were calculated. This analysis incorporated available longitudinal data from 3293 women, excluding information collected at or after first report of hormone therapy use or hysterectomy. Data were analyzed using longitudinal marginal logistic regression models and a partial proportional odds model.
Results: After adjusting for age, body mass index, and other related covariates, VMS prevalence increased with higher logFSH concentrations, and the increase was greater when blood was drawn more than 5 d after menses began. FSH concentrations were positively associated with the frequency of either hot flashes or night sweats, and higher FSH concentrations were associated with greater odds of reporting more frequent symptoms. Vasomotor symptom prevalence decreased with higher logE2, sqrtSHBG, and logFEI but only when these hormone values were modeled independently of logFSH values and the specimens were obtained outside the d 2–5 window. When modeled simultaneously with logFSH, logE2, sqrtSHBG, and logFEI were no longer significantly associated with symptom prevalence. Cubic rootT and sqrtDHEAS concentrations and logFTI were not associated with the prevalence of VMS.
Conclusions: Annual serum FSH concentrations, but not E2, T, DHEAS, FTI, or FEI when collectively modeled longitudinally, are associated with both the prevalence and frequency of VMS in women at midlife.
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Introduction |
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VMS are reported by 65–76% of women traversing the menopausal transition and are a primary reason for medical intervention during this life stage (5, 6, 7). They are characterized as an episodic alteration in the central thermoregulatory mechanism in the hypothalamus resulting in a decrease in core body temperature of 0.2 C (8, 9). VMS in midlife women have been associated with a decrease in serum estradiol (E2) and inhibin levels and an increase in FSH concentrations (10), putatively mediated through 
-adrenergic receptors within the central noradrenergic system (11).
The exact trigger of a vasomotor episode is unclear, but increases in serum LH, adrenocorticotropic hormone, GH, and cortisol have all been acutely associated with symptoms (9, 12, 13). Immediate changes in serum E2 and estrone levels have not been associated with VMS (12), although longitudinal annual studies have suggested a greater prevalence of symptoms in women with a lower or falling E2 (14, 15) and higher or rising FSH (15) concentrations. Higher serum androgen levels have also been associated with a decreasing incidence of VMS (15) in postmenopausal women. However, an exclusive causal relationship between reproductive hormones and the occurrence and severity of VMS seems unlikely because not all women report symptoms despite the universal experience of menopause, and most women who report symptoms note their eventual cessation despite persistent changes in hormone levels (16).
The purpose of this report was to relate serum concentrations of the reproductive hormones E2, FSH, testosterone (T), and dehydroepiandrosterone sulfate (DHEAS) and the calculated free steroid indices free estradiol index (FEI) and free testosterone index (FTI) with the occurrence of VMS in women as they traversed the menopausal transition. We assessed these relationships in a cohort of participants in The Study of Women’s Health Across the Nation (SWAN), a community-based longitudinal, multiethnic, multidisciplinary study of the natural history of the menopausal transition (17). We addressed two major questions: 1) are reproductive hormone concentrations and their change over time associated with the prevalence of VMS and 2) are reproductive hormone concentrations and their change over time associated with the frequency of VMS?
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Subjects and Methods |
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SWAN is a multisite, longitudinal cohort study being conducted in community-based groups of women. At baseline, 3302 women who belonged to one of five ethnic/racial groups were recruited: Caucasian (n = 1550), African-American (n = 935), Japanese (n = 281), Chinese (n = 250), and Hispanic (n = 286). Eligibility criteria for entry into the SWAN longitudinal cohort were: age 42–52 yr; intact 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. Cohort recruitment and enrollment have been described in detail (17). In brief, participants were enrolled at seven clinical sites in the following geographic areas: Boston, MA; Chicago, IL; the Detroit area (Michigan); Los Angeles, CA; Hudson County, NJ; Oakland, CA; and Pittsburgh, PA. Recruitment techniques were designed to generate a community-based sample of women at each of the sites. Each site enrolled Caucasian women as well as women who self-identified as belonging to one prespecified race/ethnic group. African-American women were enrolled in Boston, Chicago, the Detroit area, and Pittsburgh, and Japanese, Chinese, and Hispanic women were enrolled in Los Angeles, Oakland, and Hudson County, NJ, respectively. Institutional review board approval was obtained at each study site.
This analysis includes data from 3293 women with at least one serum hormone value and available VMS data from at least one longitudinal visit: baseline, first, second, third, and/or fourth annual follow-up. Data from participants with reported hysterectomy, pregnancy, or cancer were censored from analysis. Although, based on study eligibility requirements, women at baseline were not using exogenous hormones, by follow-up 4, 18.7% of the cohort population (n = 617) had reported hormone use at least once, and their data were then censored in analyses at that point.
Measures
All sites used a single common assessment protocol for the study. Height (centimeters) and weight (kilograms) were measured using a stadiometer and calibrated scales. Body mass index (BMI) was calculated as weight (kilograms)/height (meters)2. Women self-reported that paying for basics (food, housing, and heat) was not difficult, somewhat difficult, or very difficult. Smoking history was based on seven smoking questions adapted from the American Thoracic Society standards (18), and women were categorized as never, former, or current smokers. Menopausal status was based on self-report of bleeding patterns. Bleeding in the 3 months before examination and no decrease in the predictability of menses in the year before examination were considered premenopausal, bleeding in the past 3 months and a decrease in predictability in the past year were considered early perimenopausal, no menses for 3–11 months was classified as late perimenopausal, and no menses for 12 or more months was categorized as postmenopausal (19).
Frequencies of symptoms (hot flashes, night sweats) for the prior 2 wk were self-reported in the interview (19, 20, 21, 22) as a categorical 5-level variable for the number of days in the previous 2 wk that each symptom occurred: none, one to five, six to eight, nine to 13, or every day.
Women were scheduled for venipuncture before 1000 h on d 2–5 of a spontaneous menstrual cycle occurring within 60 d of recruitment at the baseline visit and annually thereafter. Two attempts were made to obtain the d 2–5 sample. If a timed sample could not be obtained, a random fasting sample was taken within a 90-d window of the anniversary of the baseline visit. Blood was refrigerated 1–2 h after phlebotomy, and then, after centrifugation, the serum was aliquoted, frozen, and batched for shipment to the central laboratory.
FSH assays were conducted in singlicate and E2 assays in duplicate using an ACS-180 automated analyzer (Bayer Diagnostics Corp., Norwood, MA). E2 concentrations were measured with a modified, off-line ACS-180 (E2–6) immunoassay. Inter- and intraassay coefficients of variation averaged 10.6 and 6.4%, respectively, over the assay range, and the lower limit of detection was 1 pg/ml. Serum FSH concentrations were measured with a two-site chemiluminometric immunoassay. Inter- and intraassay coefficients of variation were 12.0 and 6.0%, respectively, and the lower limit of detection was 1.1 IU/liter. The absolute concentrations of FSH are somewhat higher in this assay, compared with values from many clinical laboratories, based on differences in the standards selected. Serum T concentrations were determined by competitive binding of a DMAE-labeled T derivative to a rabbit polyclonal anti testosterone antibody premixed with monoclonal antirabbit IgG antibody immobilized on the solid-phase paramagnetic particles. Inter- and intraassay coefficients of variation were 10.5 and 8.5%, respectively, and the lower limit of detection was 2 ng/dl. The de novo two-site chemiluminescent assays for serum SHBG and DHEAS concentrations involved competitive binding of DMAE-labeled SHBG or DHEAS to a commercially available rabbit anti-SHBG or anti-DHEAS antibody and a solid phase of goat antirabbit IgG conjugated to paramagnetic particles. Inter- and intraassay coefficients of variation for SHBG were 9.9 and 6.1%, respectively, and the lower limit of detection was 2 nM. Inter- and intraassay coefficients of variation for DHEAS were 11.3 and 7.6%, respectively, and the lower limit of detection was 2 µg/dl. Total T was indexed to SHBG to calculate the FTI (FTI = 100 x T (nanograms per deciliter)/28.84 x SHBG (nanomoles). Likewise, total E2 was indexed to SHBG to calculate the FEI (FEI = 100 x E2 (picograms per milliliter)/272.11 x SHBG (nanomoles) (23).
Data analysis
Serum hormone concentrations were transformed to reduce skewness and centered at the study population average. Age was centered at 49 yr, and BMI was centered at 26 kg/m2 (24). Time of phlebotomy was categorized as a three-level variable including d 2–5 of the menstrual cycle, not on d 2–5 of the menstrual cycle but menses within the last 3 months and no menses for the last 3+ months. All models included ethnicity, site, smoking behavior, and degree of difficulty in paying for basics as an indicator of socioeconomic status.
The odds of reporting each VMS as a function of the concurrent level of serum hormones was estimated by fitting marginal logistic models and using generalized estimating equation theory (25), appropriate for repeated-measures data, adjusting for all other variables in the model. Time of phlebotomy was included in the model as a covariate and an interaction term, whenever it was applicable. Patterns of association between serum hormones and the odds of reporting either night sweats or hot flashes were very similar. The only explanatory variable that was shown to have a different effect on night sweats and hot flashes was age, with a weaker effect on night sweats.
To estimate the association of concurrent hormone measures with the odds of reporting any VMS, a binary variable (yes/no) for a report of either VMS in the last 2 wk was created, consolidating information from the self-reported experience of hot flashes and night sweats. Marginal logistic models were fit for this combined outcome. To test whether the results differed by menopausal status, after incorporating day of phlebotomy into the model, we used a stratified analysis and found that the association between hormone levels and the prevalence of VMS followed a very similar pattern for each menopausal status category.
To evaluate the effect of change in hormone levels on the prevalence of VMS, we decomposed concurrent hormone values into baseline and change from baseline. Data were modeled as first-order Markov chains to study associations between concurrent hormone levels and VMS, conditioned on the report of symptoms at the previous visit (25).
The differential effect of hormone concentrations on frequency of hot flashes was examined to explore the ordinal nature of hot flash frequency. As indicated by stratified analysis and the Wald test, the assumption of proportionality of hormone related cumulative odds was relaxed to build a partial proportional odds model (26), formulated in terms of a threshold of change (27), assuring that slopes for loghormone concentrations corresponding to the different thresholds did not intersect and violate the assumption of the natural order of the thresholds (28). Night sweats were analyzed in the same framework. Both marginal and mixed-effects (results not shown) models were built. SAS software (version 8.0, SAS Institute, Cary, NC) and Mixor (version 2) (29) were used for statistical analyses.
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Results |
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). Hot flashes were slightly less prevalent at baseline (26.7%) than night sweats (29.3%) but more prevalent at follow-up 4 (43.1% vs. 35.8%). The frequency of reporting any symptom (hot flashes or night sweats) increased from 39.1% at baseline to 52.3% at follow-up 4. This increase is consistent with the change in menopausal status. Based on study eligibility criteria, at baseline all women were either premenopausal or early perimenopausal. However, by follow-up 4, 21% of women were postmenopausal, 12% were late perimenopausal, 58% were early perimenopausal, and only 9% were premenopausal. The percentage of women having phlebotomy within the d 2–5 window also changed, consistent with the shift in status. At baseline, 78.5% of subjects were sampled within the window, whereas at the fourth follow-up, 32.1% had not had a bleeding episode for at least 3 months and only 47.8% were sampled within d 2–5 of a menstrual bleed.
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. The mean serum FSH concentrations were relatively stable over time in those samples drawn in the d 2–5 early follicular window or from women without menses for at least 3 months. However, FSH concentrations were nearly 4-fold higher in those women for whom 3 months had passed without menstrual bleeding than in women with d 2–5 samples. Serum E2 levels were minimally lower at the fourth follow-up than at baseline in samples from within the d 2–5 window. In contrast, E2 levels were lower and a greater decline was observed in those samples from women without menses for at least 3 months.
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and Fig. 1A, and this increase in prevalence was greater when specimens came from women studied outside the d 2–5 window. For each unit increase in serum logFSH, the odds of reporting any VMS increased 29% in women with samples outside the d 2–5 window and increased 58% in women without menses for at least 3 months. FSH was the only hormone that was significantly associated with the prevalence of VMS when specimens came from d 2–5.
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and Fig. 1B, but only in women with samples outside the d 2–5 window. When modeled independently from FSH, the odds of reporting symptoms per unit increase in serum logE2 decreased 20% with samples outside the d 2–5 window and decreased 16% in women without menses for at least 3 months. The effect of logFEI on VMS prevalence was very similar to logE2.
Cubic root(T), logFTI, sqrt(SHBG), and sqrt(DHEAS) concentrations were not associated with the prevalence of VMS, as seen in Table 3.
In longitudinal analyses, women reporting VMS at the previous visit had a 6-fold greater likelihood of symptoms at the subsequent visit than women who did not report symptoms at the previous visit, and both logFSH and logE2 remained predictive of vasomotor prevalence [odds ratio (OR) (95% confidence interval) 6.06 (5.28, 6.96) and 5.75 (5.04, 6.57), respectively]. The concurrent hormone value had the same effect on VMS risk as an estimate of the change in hormone value from the previous visit (data not shown).
When logFSH and logE2 were in the same model as predictors of VMS, logE2 was no longer significantly associated with symptom prevalence, as shown in Table 4. Estimates for logFSH remained positively associated and very similar to the independent estimates graphed in Fig. 1A.
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Greater FSH concentrations were positively associated with the reported frequency of both hot flashes and night sweats, as shown in Fig. 2 for hot flashes. Based on evaluating thresholds for the probability of moving from one hot flash frequency category to another (27), we defined two thresholds in separate models, one for having any hot flashes and the second for having hot flashes on 9+ d in the prior 2-wk period. Women who were no longer cycling had a 30% probability of having hot flashes at an FSH concentration of 20 IU/liter after adjusting for all significant covariates. An increase in FSH to 60 IU/liter changed the probability of having any hot flashes to 41% (the upper set of curves in Fig. 2). At an FSH concentration of 20 IU/liter, the probability of having hot flashes 9+ d of the prior 14 d was 4.1% for women who were no longer cycling. An increase in FSH to 60 IU/liter more than doubled the probability to 9% (the lower set of curves). The estimated effect of higher FSH levels on the frequency of night sweats followed a similar trend (data not shown). The E2 effect also varied by the frequency of hot flashes but only for noncycling women and only when modeled independently from FSH (data not shown).
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Discussion |
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An annual serum FSH measure was a better independent predictor of VMS prevalence than an annual serum E2 level. FSH was positively associated with VMS prevalence, even in regularly cycling women whose blood sampling occurred within the d 2–5 early follicular phase window when E2 was not independently predictive. FSH was the only hormonal predictor of VMS prevalence or frequency in a model including both hormones. Whereas both hormones have been temporally associated with VMS (10, 14, 15), the primacy of FSH as a predictor raises the possibility that E2 may not exert a direct effect on VMS and may be working primarily through feedback regulation of FSH. This is consistent with other studies that have not directly related estrogen concentrations with VMS (30, 31, 32). However, the association of an annual serum FSH level and VMS explains only part of the variation in prevalence and still lacks sufficient predictive value to be a clinically useful measure (1, 2).
The association of FSH concentrations with VMS frequency, but not E2 concentrations when modeled together with FSH, has not been previously reported and suggests that nonsteroidal feedback systems may be more directly related to severity than estrogen feedback although estrogen therapy remains the most effective treatment for troubling VMS. Rising levels of FSH have been associated with a decrease in ovarian follicles and resultant decline in follicular phase serum inhibin B, a primary negative feedback regulator of FSH secreted by antral follicles (33, 34). The greater relative impact of a change in FSH concentration at higher frequencies suggests that FSH levels may be predictive of frequency in women experiencing VMS and that neuroendocrine or gonadal peptide-based approaches to therapy may be logical adjuncts or alternatives to estrogen-based therapies.
Serum T and DHEAS concentrations and calculated FTI were not associated with either VMS prevalence or frequency, which is in contrast to a recent report (15). Because levels of these hormones are less variable than E2 throughout the menstrual cycle (35) and through the transition (36), single annual samples are more reliable estimates of hormone exposure than E2 or FSH over time. The absence of an association with a relatively reliable hormone estimate suggests that the androgen axis is not a major determinant of VMS in the perimenopause and that androgen therapy for these symptoms should be used cautiously in carefully selected patients.
A striking finding is the 39% of participants who reported any VMS at baseline, when all were premenopausal or early perimenopausal by the bleeding criteria of the recruitment design. This is remarkably higher than the 10% of premenopausal women reporting VMS at baseline noted by McKinlay et al. (37) in 1178 women aged 45–55 yr, an older population using the same bleeding criteria for menopausal stage. Whereas only 21% of the participants reported here had been classified as postmenopausal by the fourth follow-up visit, the 67% cumulative rate of reporting any VMS suggests that a significant segment of the cohort will not report symptoms, consistent with prior longitudinal studies (8). Thus, neither hormone levels nor bleeding changes are sufficient to entirely explain either VMS prevalence or frequency. The positive association of VMS with both smoking behavior and psychosocial stress is consistent with previous reports (38).
Because women have less predictable bleeding during the transition, it becomes increasingly difficult to anchor a serum sample to a menstrual period, and the timing of the phlebotomy can be considered a surrogate for transition stage. Samples obtained in the d 2–5 window were primarily from premenopausal and early perimenopausal women, and samples obtained more than 3 months from the last bleeding episode are all from late perimenopausal or postmenopausal women by the definitions of transition stage used in SWAN. Ultimately, in the combined model incorporating all hormones, only FSH was predictive of VMS, and the FSH effect was modified by the timing of the serum sample, suggesting that progression through the transition amplifies the effect. When transition stage was included in the model with both day of phlebotomy and FSH concentration, it overcompensated for the effect of transition, so it was not included in the final model. Whereas timing of phlebotomy categories are not recognized bleeding-defined measures of menopausal status, they are a reproducible and clinically applicable variable for interpreting the effect of FSH on VMS prevalence and frequency.
In summary, we have shown that annual serum concentrations of most reproductive hormones are not directly related to reported VMS in a multiethnic cohort of midlife women. Whereas FSH and E2 levels and the calculated FEI, when measured longitudinally over the menopausal transition, are independently associated with the presence of reported VMS, when these hormones are modeled together, only FSH remains associated with the prevalence of VMS. Additionally, serum FSH concentrations and change in serum FSH concentrations over time are positively associated with the frequency of reported hot flashes, with a greater effect at higher hot flash frequencies. T, DHEAS, and SHBG levels and the calculated FTI are not associated with the presence of reported VMS.
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Acknowledgments |
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Footnotes |
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First Published Online September 6, 2005
Abbreviations: BMI, Body mass index; DHEAS, dehydroepiandrosterone sulfate; E2, estradiol; FEI, free estradiol index; FTI, free testosterone index; SWAN, Study of Women’s Health Across the Nation; T, testosterone; VMS, vasomotor symptom(s).
Received June 20, 2005.
Accepted August 26, 2005.
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