BioCycle Study Research Articles

Menstrual Bleeding Patterns Among Regularly Menstruating Women

Menstrual bleeding patterns are considered relevant indicators of reproductive health, though few studies have evaluated patterns among regularly menstruating premenopausal women. The authors evaluated self-reported bleeding patterns, incidence of spotting, and associations with reproductive hormones among 201 women in the BioCycle Study (2005-2007) with 2 consecutive cycles. Bleeding patterns were assessed by using daily questionnaires and pictograms. Marginal structural models were used to evaluate associations between endogenous hormone concentrations and subsequent total reported blood loss and bleeding length by weighted linear mixed-effects models and weighted parametric survival analysis models. Women bled for a median of 5 days (standard deviation: 1.5) during menstruation, with heavier bleeding during the first 3 days. Only 4.8% of women experienced midcycle bleeding. Increased levels of follicle-stimulating hormone (β = 0.20, 95% confidence interval: 0.13, 0.27) and progesterone (β = 0.06, 95% confidence interval: 0.03, 0.09) throughout the cycle were associated with heavier menstrual bleeding, and higher follicle-stimulating hormone levels were associated with longer menses. Bleeding duration and volume were reduced after anovulatory compared with ovulatory cycles (geometric mean blood loss: 29.6 vs. 47.2 mL; P = 0.07). Study findings suggest that detailed characterizations of bleeding patterns may provide more insight than previously thought as noninvasive markers for endocrine status in a given cycle.

Adiposity and sex hormones across the menstrual cycle: the BioCycle Study

ObjectiveTo investigate the influence of adiposity on patterns of sex hormones across the menstrual cycle among regularly menstruating women.SubjectsThe BioCycle Study followed 239 healthy women for 1–2 menstrual cycles, with up to 8 visits per cycle timed using fertility monitors.MethodsSerum estradiol (E2), progesterone, luteinizing hormone (LH), follicle-stimulating hormone (FSH), and sex hormone binding globulin (SHBG) were measured at each visit. Adiposity was measured by anthropometry and by dual energy x-ray absorptiometry. Differences in hormonal patterns by adiposity measures were estimated using nonlinear mixed models, which allow for comparisons in overall mean levels, amplitude (i.e. lowest to highest level within each cycle), and shifts in timing of peaks while adjusting for age, race, energy intake, and physical activity.ResultsCompared to normal weight women (n=154), obese women (BMI≥30 kg/m2, n=25) averaged lower levels of progesterone (−15%, P=0.003), LH (−17%, P=0.01), FSH (−23%, P=0.001) and higher free E2 (+22%, p=0.001) across the cycle. To lesser magnitudes, overweight women (BMI: 25–30, n=60) also exhibited differences in the same directions for mean levels of free E2, FSH, and LH. Obese women experienced greater changes in amplitude of LH (9%, p=0.002), and FSH (8%, p=0.004), but no differences were observed among overweight women. Higher central adiposity by top compared to bottom tertile of trunk-to-leg fat ratio by DXA was associated with lower total E2 (−14%, p=0.005) and FSH (−15%, p=0.001). Peaks in FSH and LH occurred later (~0.5 day) in the cycle among women with greater central adiposity.ConclusionGreater total and central adiposity were associated with changes in mean hormone levels. The greater amplitudes observed among obese women suggest compensatory mechanisms at work to maintain hormonal homeostasis. Central adiposity may be more important in influencing timing of hormonal peaks than total adiposity.

Endogenous Reproductive Hormones and C-reactive Protein Across the Menstrual Cycle: The BioCycle Study

C-reactive protein (CRP) is one of the most commonly used markers of acute phase reaction in clinical settings and predictors of cardiovascular risk in healthy women; however, data on its physiologic regulation in premenopausal women are sparse. The objective of this study was to evaluate the association between endogenous reproductive hormones and CRP in the BioCycle Study (2005-2007). Women aged 18-44 years from western New York were followed prospectively for up to 2 menstrual cycles (n = 259). Serum levels of CRP, estradiol, progesterone, luteinizing hormone, and follicle-stimulating hormone were measured up to 8 times per cycle, timed by fertility monitors. CRP levels varied significantly across the cycle (P < 0.001). More women were classified as being at elevated risk of cardiovascular disease (CRP, >3 mg/L) during menses compared with other phases (12.3% vs. 7.4%; P < 0.001). A 10-fold increase in estradiol was associated with a 24.3% decrease in CRP (95% confidence interval: 19.3, 29.0). A 10-fold increase in luteal progesterone was associated with a 19.4% increase in CRP (95% confidence interval: 8.4, 31.5). These results support the hypothesis that endogenous estradiol might have antiinflammatory effects and highlight the need for standardization of CRP measurement to menstrual cycle phase in reproductive-aged women.

Caffeinated beverage intake and reproductive hormones among premenopausal women in the BioCycle Study

Caffeinated beverages are widely consumed among women of reproductive age, but their association with reproductive hormones, and whether race modifies any such associations, is not well understood. We assessed the relation between caffeine and caffeinated beverage intake and reproductive hormones in healthy premenopausal women and evaluated the potential effect modification by race. Participants (n = 259) were followed for up to 2 menstrual cycles and provided fasting blood specimens for hormonal assessment at up to 8 visits per cycle and four 24-h dietary recalls per cycle. Weighted linear mixed models and nonlinear mixed models with harmonic terms were used to estimate associations between caffeine and hormone concentrations, adjusted for age, adiposity, physical activity, energy and alcohol intakes, and perceived stress. On the basis of a priori assumptions, an interaction between race and caffeine was tested, and stratified results are presented. Caffeine intake ≥200 mg/d was inversely associated with free estradiol concentrations among white women (β = -0.15; 95% CI: -0.26, -0.05) and positively associated among Asian women (β = 0.61; 95% CI: 0.31, 0.92). Caffeinated soda intake and green tea intake ≥1 cup/d (1 cup = 240 mL) were positively associated with free estradiol concentrations among all races: β = 0.14 (95% CI: 0.06, 0.22) and β = 0.26 (95% CI: 0.07, 0.45), respectively. Moderate consumption of caffeine was associated with reduced estradiol concentrations among white women, whereas caffeinated soda and green tea intakes were associated with increased estradiol concentrations among all races. Further research is warranted on the association between caffeine and caffeinated beverages and reproductive hormones and whether these relations differ by race.

Caffeinated beverage intake and reproductive hormones among premenopausal women in the BioCycle Study

Caffeinated beverage intake and reproductive hormones among premenopausal women in the BioCycle Study

A Bayesian order‐restricted model for hormonal dynamics during menstrual cycles of healthy women

We propose a Bayesian framework for analyzing multivariate linear mixed effect models with linear constraints on the fixed effect parameters. The procedure can incorporate both firm and soft restrictions on the parameters and Bayesian model selection for the random effects. The framework is used to analyze data from the BioCycle study. One of the main objectives of the BioCycle study is to investigate the association between markers of oxidative stress and hormone levels during menstrual cycles of healthy women. Contrary to the popular belief that ovarian hormones are negatively associated with level of F (2) -isoprostanes, a known marker for oxidative stress, our analysis finds a positive association between ovarian hormone levels and isoprostane levels. The positive association corroborates the findings from a previous analysis of the BioCycle data.

Outcome‐dependent sampling for longitudinal binary response data based on a time‐varying auxiliary variable

Outcome-dependent sampling (ODS) study designs are commonly implemented with rare diseases or when prospective studies are infeasible. In longitudinal data settings, when a repeatedly measured binary response is rare, an ODS design can be highly efficient for maximizing statistical information subject to resource limitations that prohibit covariate ascertainment of all observations. This manuscript details an ODS design where individual observations are sampled with probabilities determined by an inexpensive, time-varying auxiliary variable that is related but is not equal to the response. With the goal of validly estimating marginal model parameters based on the resulting biased sample, we propose a semi-parametric, sequential offsetted logistic regressions (SOLR) approach. The SOLR strategy first estimates the relationship between the auxiliary variable and the response and covariate data by using an offsetted logistic regression analysis where the offset is used to adjust for the biased design. Results from the auxiliary variable model are then combined with the known or estimated sampling probabilities to formulate a second offset that is used to correct for the biased design in the ultimate target model relating the longitudinal binary response to covariates. Because the target model offset is estimated with SOLR, we detail asymptotic standard error estimates that account for uncertainty associated with the auxiliary variable model. Motivated by an analysis of the BioCycle Study (Gaskins et al., Effect of daily fiber intake on reproductive function: the BioCycle Study. American Journal of Clinical Nutrition 2009; 90(4): 1061-1069) that aims to describe the relationship between reproductive health (determined by luteinizing hormone levels) and fiber consumption, we examine properties of SOLR estimators and compare them with other common approaches.

Generalized degrees of freedom and adaptive model selection in linear mixed-effects models

Linear mixed-effects models involve fixed effects, random effects and covariance structures, which require model selection to simplify a model and to enhance its interpretability and predictability. In this article, we develop, in the context of linear mixed-effects models, the generalized degrees of freedom and an adaptive model selection procedure defined by a data-driven model complexity penalty. Numerically, the procedure performs well against its competitors not only in selecting fixed effects but in selecting random effects and covariance structure as well. Theoretically, asymptotic optimality of the proposed methodology is established over a class of information criteria. The proposed methodology is applied to the BioCycle Study, to determine predictors of hormone levels among premenopausal women and to assess variation in hormone levels both between and within women across the menstrual cycle.

Realignment and multiple imputation of longitudinal data: an application to menstrual cycle data.

Reproductive hormone levels are highly variable among premenopausal women during the menstrual cycle. Accurate timing of hormone measurement is essential, especially when investigating day- or phase-specific effects. The BioCycle Study used daily urine home fertility monitors to help detect the luteinising hormone (LH) surge in order to schedule visits with biologically relevant windows of hormonal variability. However, as the LH surge is brief and cycles vary in length, relevant hormonal changes may not align with scheduled visits even when fertility monitors are used. Using monitor data, measurements were reclassified according to biological phase of the menstrual cycle to more accurate cycle phase categories. Longitudinal multiple imputation methods were applied after reclassification if no visit occurred during a given menstrual cycle phase. Reclassified cycles had more clearly defined hormonal profiles, with higher mean peak hormones (up to 141%) and reduced variability (up to 71%). We demonstrate the importance of realigning visits to biologically relevant windows when assessing phase- or day-specific effects and the feasibility of applying longitudinal multiple imputation methods. Our method has applications in settings where missing data may occur over time, where daily blood sampling for hormonal measurements is not feasible, and in other areas where timing is essential.

Regression analysis with covariates that have heteroscedastic measurement error

We consider the estimation of the regression of an outcome Y on a covariate X, where X is unobserved, but a variable W that measures X with error is observed. A calibration sample that measures pairs of values of X and W is also available; we consider calibration samples where Y is measured (internal calibration) and not measured (external calibration). One common approach for measurement error correction is Regression Calibration (RC), which substitutes the unknown values of X by predictions from the regression of X on W estimated from the calibration sample. An alternative approach is to multiply impute the missing values of X given Y and W based on an imputation model, and then use multiple imputation (MI) combining rules for inferences. Most of current work assumes that the measurement error of W has a constant variance, whereas in many situations, the variance varies as a function of X. We consider extensions of the RC and MI methods that allow for heteroscedastic measurement error, and compare them by simulation. The MI method is shown to provide better inferences in this setting. We also illustrate the proposed methods using a data set from the BioCycle study.

Cadmium, Lead, and Mercury in Relation to Reproductive Hormones and Anovulation in Premenopausal Women

Background: Metals can interfere with hormonal functioning by binding at the receptor site and through indirect mechanisms; thus, they may be associated with hormonal changes in premenopausal women.Objectives: We examined the associations between cadmium, lead, and mercury, and anovulation and patterns of reproductive hormones [estradiol, progesterone, follicle-stimulating hormone (FSH), luteinizing hormone] among 252 premenopausal women 18–44 years of age who were enrolled in the BioCycle Study in Buffalo, New York.Methods: Women were followed for up to two menstrual cycles, with serum samples collected up to eight times per cycle. Metal concentrations were determined at baseline in whole blood by inductively coupled mass spectroscopy. Marginal structural models with stabilized inverse probability weights and nonlinear mixed models with harmonic terms were used to estimate the effects of cadmium, lead, and mercury on reproductive hormone levels during the menstrual cycle and anovulation.Results: Geometric mean (interquartile range) cadmium, lead, and mercury levels were 0.29 (0.19–0.43) μg/L, 0.93 (0.68–1.20) μg/dL, and 1.03 (0.58–2.10) μg/L, respectively. We observed decreases in mean FSH with increasing cadmium [second vs. first tertile: –10.0%; 95% confidence interval (CI), –17.3% to –2.5%; third vs. first tertile: –8.3%; 95% CI, –16.0% to 0.1%] and increases in mean progesterone with increasing lead level (second vs. first tertile: 7.5%; 95% CI, 0.1–15.4%; third vs. first tertile: 6.8%; 95% CI, –0.8% to 14.9%). Metals were not significantly associated with anovulation.Conclusions: Our findings support the hypothesis that environmentally relevant levels of metals are associated with modest changes in reproductive hormone levels in healthy, premenopausal women.

Energy Expenditure and Plasma F2-Isoprostanes across the Menstrual Cycle

Habitual energy expenditure seems to favorably alter oxidant/antioxidant balance. Sparse evidence suggests that hormones that fluctuate during the menstrual cycle, particularly estrogens, may influence concentrations of oxidative biomarkers and their relation to energy expenditure. We investigated the relation between energy expenditure and plasma free F2-isoprostane concentrations in 259 healthy, regularly menstruating 18- to 44-yr-old participants of the BioCycle Study. Habitual energy expenditure was measured using a baseline International Physical Activity Questionnaire and categorized as low, moderate, or high. Women were followed for one or two subsequent menstrual cycles. Past-week and past-day physical activity were measured during follow-up using questionnaires and diaries, respectively. F2-isoprostane concentrations were measured in blood samples collected at both menses (approximate cycle day 2; low serum estradiol concentration) and the late follicular phase (approximate cycle day 12; peak estradiol concentration). Generalized estimating equations were used to model the energy expenditure/isoprostane association, adjusting for confounders. Habitual energy expenditure was positively associated with F2-isoprostane concentration (adjusted difference in median F2-isoprostane, high versus low energy expenditure: 17.4%; 95% confidence interval (CI)=3.3%-31.4%). This association was not modified by cycle phase (interaction, P=0.61) or differences in peak estradiol concentration across women (interaction, P=0.20). Past-week and past-day physical activity measures were not associated with F2-isoprostane concentration (category trend, P=0.50 and P=0.18, respectively). These results suggest that higher habitual energy expenditure may be associated with higher concentration of F2-isoprostanes in healthy, reproductive-aged women. Estradiol concentration changes during the menstrual cycle do not seem to influence this relationship.

Age at Menarche and Metabolic Markers for Type 2 Diabetes in Premenopausal Women: The BioCycle Study

Early age at menarche has been linked to an elevated risk of type 2 diabetes. However, the underlying mechanism is unclear. Our objective was to examine associations between age at menarche and type 2 diabetes risk factors. The BioCycle Study followed 253 healthy premenopausal women from the general population (Buffalo, NY) for one to two menstrual cycles. Age at menarche was self-reported. Body mass index and waist circumference were measured by trained personnel. Total body and trunk fat were measured by dual-energy x-ray absorptiometry. Fasting glucose, insulin, highly sensitive C-reactive protein, and SHBG levels were measured up to eight times per cycle. Insulin resistance (IR) and β-cell function were evaluated using the homeostasis model assessment (HOMA)-IR and HOMA-β. The mean age at menarche was 12.5 ± 1.2 yr. After adjustment for age, race, education, and physical activity, early menarche (≤12 yr) was significantly associated with an increase of 1.35 kg/m(2) in body mass index (P = 0.01), 2.52% in percent total body fat (P = 0.004), 3.02% in percent trunk fat (P = 0.004), 0.15 μIU/ml in (log)insulin (P = 0.02), 0.15 U in (log)HOMA-IR (P = 0.03), and 0.16 U in (log)HOMA-β (P = 0.01) compared with average menarche (12-14 yr). No associations were found for SHBG or highly sensitive C-reactive protein. Early onset of menarche is associated with unfavorable metabolic phenotypes compared with average onset of menarche in healthy premenopausal women, including reduced insulin sensitivity and β-cell function and greater total and trunk fat.

Alteration of insulin sensitivity by sex hormones during the menstrual cycle.

It is well established that insulin resistance and impaired insulin secretion are two major prerequisites in the development of type 2 diabetes. Given the growing global epidemic of obesity, it is expected that the number of people with insulin resistance will expand exponentially. To maintain glucose homeostasis, insulin action, reflected by insulin sensitivity measured in vivo, is regulated by a well organized, but complicated, hierarchical mechanism. In this regard, many studies have shown that environmental factors might have a great influence on insulin sensitivity and these issues are further complicated when interaction between genes and the environment is taken into consideration1. Additionally, a number of studies have shown that the degree of insulin sensitivity is also influenced by many biological factors, in particular, hormone alterations, which might account for the diurnal changes of insulin sensitivity in normal and diabetic individuals or involve the occurrence of the dawn phenomenon. Extensive studies were carried out to determine how sex hormones harness insulin sensitivity or predispose humans to the development of diabetes2. In a recent article, obtained from The BioCycle Study, Yeung et al.3 reported that, in a group of relatively healthy premenopausal women, insulin resistance, expressed by homeostasis model assessment for insulin resistance (HOMA‐IR), changed slightly, but significantly, during the normal menstrual cycle. Specifically, HOMA‐IR rose from 1.35 in the midfollicular phase to 1.59 (with a magnitude of increase of 17.8%) during the early luteal phase and decreased to 1.55 (by 14.8%) in the late luteal phase. These changes were positively associated with levels of estradiol and progesterone, but negatively associated with follicle stimulating hormone (FSH) and sex hormone binding globin (SHBG). In addition to findings from previous studies showing the impact of menstrual cycle variability on insulin sensitivity, this BioCycle Study enrolled the greatest number of healthy women (n = 257) and had the most frequent visits (eight visits during a cycle period), designed to monitor women at peak fertility. Thus, the findings from this study, which has overcome the shortages of previous inconsistent reports, should be reliable. However, concerns were raised as to how accurate HOMA‐IR is in capturing the degree of insulin resistance4. It will be of great value, although difficult, to use more precise measures of insulin resistance, such as the glucose clamp study, in those studied participants. The physiological effects of circulating estradiol and progesterone levels on insulin resistance in premenopausal women might be distinct from pharmacological applications in postmenopausal women. The present author and others have shown that oral contraceptive pills might decrease insulin resistance and increase cardiovascular risk in young women, whereas transdermal use of estrogen might prevent these untoward effects5. It is postulated that estrogen‐induced increases in glucocorticoid activity might account for these unwanted effects. In addition, the influence of long‐term use of estrogen might be different from that of short‐term use, with the former preserving insulin secretion and maintaining glucose homeostasis. In this article, the finding that alterations of HOMA‐IR primarily reflected changes in fasting insulin levels and not fasting glucose levels3 is not unexpected, given the tight regulation of insulin secretion during alterations of insulin sensitivity in healthy individuals. One of the limitations of the study by Yeung et al.3 was the lack of measurement of testosterone, which was reported to be associated with insulin resistance, although the use of SHBG in this study might partially reflect the bioavailability and action of testosterone. In addition, the association between HOMA‐IR and SHBG became insignificant after adjustment of body mass index (BMI), showing that these associations might be mediated through adiposity in the studied population. Finally, although the alterations of insulin resistance during the menstrual cycle might be considered as minor, caution should be taken when recruiting premenopausal women to serve as study volunteers, especially when comparing changes of insulin resistance before and after certain interventional trials.

Effect of dietary fiber intake on lipoprotein cholesterol levels independent of estradiol in healthy premenopausal women.

High-fiber diets are associated with improved lipid profiles. However, pre- and postmenopausal women respond differently to fiber intake, suggesting that endogenous estradiol mediates the effect. The authors' objective was to determine the direct effect of fiber intake on lipoprotein cholesterol levels independent of estradiol among premenopausal women. The BioCycle Study, a prospective cohort study conducted at the State University of New York at Buffalo from 2005 to 2007, followed 259 healthy women for up to 2 complete menstrual cycles. Serum lipoprotein and hormone levels were measured at 16 visits timed using fertility monitors. Fiber intake was assessed by 8 24-hour recalls. Marginal structural models with inverse probability weights for both lipoprotein and estradiol levels were used to estimate controlled direct effects of the highest category of fiber intake (≥22 g/day vs. <22 g/day) while accounting for age, body mass index, total energy, vitamin E intake, physical activity, luteinizing hormone, follicle-stimulating hormone, and progesterone. Reductions were observed in total and low density lipoprotein cholesterol in women with higher fiber intakes. Direct effects were greater than total effects. These analyses suggested that estradiol mediates at least part of the association between fiber and cholesterol among premenopausal women. More research is needed to elucidate the biologic mechanisms driving these associations.

Cholesterol, endocrine and metabolic disturbances in sporadic anovulatory women with regular menstruation

Sporadic anovulation among regularly menstruating women is not well understood. It is hypothesized that cholesterol abnormalities may lead to hormone imbalances and incident anovulation. The objective was to evaluate the association between lipoprotein cholesterol levels and endocrine and metabolic disturbances and incident anovulation among ovulatory and anovulatory women reporting regular menstruation. The BioCycle Study was a prospective cohort study conducted at the University at Buffalo from September 2005 to 2007, which followed 259 self-reported regularly menstruating women aged 18-44 years, for one or two complete menstrual cycles. Sporadic anovulation was assessed across two menstrual cycles. Mean total and low-density lipoprotein cholesterol and triglycerides levels across the menstrual cycles were higher during anovulatory cycles (mean difference: 4.6 (P = 0.01), 3.0 (P = 0.06) and 6.4 (P = 0.0002) mg/dl, respectively, adjusted for age and BMI). When multiple total cholesterol (TC) measures prior to expected ovulation were considered, we observed a slight increased risk of anovulation associated with increased levels of TC (odds ratio per 5 mg/dl increase, 1.07; 95% confidence interval, 0.99, 1.16). Sporadic anovulation was associated with an increased LH:FSH ratio (P = 0.002), current acne (P = 0.02) and decreased sex hormone-binding globulin levels (P = 0.005). These results do not support a strong association between lipoprotein cholesterol levels and sporadic anovulation. However, sporadic anovulation among regularly menstruating women is associated with endocrine disturbances which are typically observed in women with polycystic ovary syndrome.

Longitudinal Study of Insulin Resistance and Sex Hormones over the Menstrual Cycle: The BioCycle Study

Conflicting findings have been reported regarding the effect of menstrual cycle phase and sex hormones on insulin sensitivity. The aim was to determine the pattern of insulin resistance over the menstrual cycle and whether variations in sex hormones explain these patterns. The BioCycle study is a longitudinal study that measured hormones at different phases of the menstrual cycle. Participants had up to eight visits per cycle; each visit was timed using fertility monitors to capture sensitive windows of hormonal changes. The study was conducted in the general community of the University at Buffalo (Buffalo, NY). A total of 257 healthy, premenopausal women (age, 27±8 yr; body mass index, 24±4 kg/m2) participated in the study. We measured fasting insulin, glucose, and insulin resistance by the homeostasis model of insulin resistance (HOMA-IR). Significant changes in HOMA-IR were observed over the menstrual cycle; from a midfollicular phase level of 1.35, levels rose to 1.59 during the early luteal phase and decreased to 1.55 in the late-luteal phase. HOMA-IR levels primarily reflected changes in insulin and not glucose. After adjustment for age, race, cycle, and other sex hormones, HOMA-IR was positively associated with estradiol (β=0.082; P<0.001) and progesterone (β=0.025; P<0.001), and inversely associated with FSH (adjusted β=-0.040; P<0.001) and SHBG (β=-0.085; P<0.001). LH was not associated with HOMA-IR. Further adjustment for BMI weakened the association with SHBG (β=-0.057; P=0.06) but did not affect other associations. Insulin exhibited minor menstrual cycle variability. Estradiol and progesterone were positively associated with insulin resistance and should be considered in studies of insulin resistance among premenopausal women.

Influence of Endogenous Reproductive Hormones on F2-Isoprostane Levels in Premenopausal Women: The BioCycle Study

Endogenous reproductive hormones and oxidative stress have been independently linked to risk of chronic disease but mostly in postmenopausal women. The interplay between endogenous reproductive hormones and oxidative stress among premenopausal women, however, has yet to be clearly elucidated. The objective of this study was to investigate the association between endogenous reproductive hormones and F(2)-isoprostanes in the BioCycle Study. Women aged 18-44 years from western New York State were followed prospectively for up to 2 menstrual cycles (n = 259) during 2005-2007. Estradiol, progesterone, luteinizing hormone, follicle-stimulating hormone, sex hormone-binding globulin, F(2)-isoprostanes, and thiobarbituric acid-reactive substances were measured up to 8 times per cycle at clinic visits timed by using fertility monitors. F(2)-Isoprostane levels had an independent positive association with estradiol (beta = 0.02, 95% confidence interval: 0.01, 0.03) and inverse associations with sex hormone-binding globulin and follicle-stimulating hormone (beta = -0.04, 95% confidence interval: -0.07, -0.003; beta = -0.02, 95% confidence interval: -0.03, -0.002, respectively) after adjustment for age, race, age at menarche, gamma-tocopherol, beta-carotene, total cholesterol, and homocysteine by inverse probability weighting. Thiobarbituric acid-reactive substances, a less specific marker of oxidative stress, had similar associations. If F(2)-isoprostanes are specific markers of oxidative stress, these results call into question the commonly held hypothesis that endogenous estradiol reduces oxidative stress.

Racial Differences in the Association Between Sex Hormone–Binding Globulin and Adiposity in Premenopausal Women

OBJECTIVETo assess the associations between measures of adiposity and sex hormone– binding globulin (SHBG) and to evaluate whether such associations differ by race.RESEARCH DESIGN AND METHODSAdiposity was measured by anthropometry and dual-energy X-ray absorptiometry among women (146 white, 50 black, and 25 Asian) aged 18–44 years in the BioCycle study. SHBG was repeatedly measured over one to two menstrual cycles. The ratio of trunkal to leg fat (T/L) was used to assess upper to lower body adiposity.RESULTSAmong whites, all adiposity measures were significantly and inversely associated with SHBG. Among blacks, BMI (β = −0.032), waist circumference (β = −0.016), and T/L (β = −0.033) were significantly associated with SHBG, whereas total and trunkal fat were not (P interaction with race <0.04). Among Asians, measures of central and upper body fat were significantly associated with SHBG (e.g., T/L, β = −0.84) but not BMI.CONCLUSIONSAssociations between SHBG and adiposity differ by race among premenopausal women.

A Longitudinal Study of Serum Lipoproteins in Relation to Endogenous Reproductive Hormones during the Menstrual Cycle: Findings from the BioCycle Study

Exogenous estrogens have been shown to affect the lipid profile, leading to the hypothesis that endogenous estrogens may have similar effects. The objective of the study was to evaluate the association between endogenous estrogen and serum lipoproteins across the menstrual cycle. This was a prospective cohort study. The study was conducted at the University at Buffalo, 2005-2007. Participants included 259 healthy, regularly menstruating women aged 18-44 yr. Serum levels of total, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and triglycerides measured up to eight times per cycle for up to two cycles were measured. Total and LDL cholesterol were lower during the luteal phase as compared with the follicular phase (P < 0.001), and HDL levels were highest around ovulation (P < 0.001). More women were classified above the desirable range (LDL > or =130 mg/dl or total cholesterol > or =200 mg/dl) when measured during the follicular phase. Estradiol was positively associated with HDL in acute effects models [beta = 0.019, 95% confidence interval (CI) 0.015, 0.022] and inversely associated with total (beta = -0.017, 95% CI -0.020, -0.014) and LDL cholesterol (beta = -0.023, 95% CI -0.027, -0.018) and triglycerides (beta = -0.041, 95% CI -0.054, -0.029) in persistent effects models. Endogenous estrogen, like exogenous estrogen, appears to have beneficial effects on the lipid profile. Because lipoprotein cholesterol levels vary across the menstrual cycle, cyclic variations in lipoprotein levels may need to be considered in the design and interpretation of studies in reproductive-age women and in the clinical management of women's cholesterol.