Background: Prior studies have found weak inverse associations between breast cancer and caffeine and coffee intake, possibly mediated through their effects on sex hormones.

Methods: High-performance liquid chromatography/tandem mass spectrometry was used to quantify levels of 15 individual estrogens and estrogen metabolites (EM) among 587 premenopausal women in the Nurses' Health Study II with mid-luteal phase urine samples and caffeine, coffee, and/or tea intakes from self-reported food frequency questionnaires. Multivariate linear mixed models were used to estimate geometric means of individual EM, pathways, and ratios by intake categories, and P values for tests of linear trend.

Results: Compared with women in the lowest quartile of caffeine consumption, those in the top quartile had higher urinary concentrations of 16α-hydroxyestrone (28% difference; Ptrend = 0.01) and 16-epiestriol (13% difference; Ptrend = 0.04), and a decreased parent estrogens/2-, 4-, 16-pathway ratio (Ptrend = 0.03). Coffee intake was associated with higher 2-catechols, including 2-hydroxyestradiol (57% difference, ≥4 cups/day vs. ≤6 cups/week; Ptrend = 0.001) and 2-hydroxyestrone (52% difference; Ptrend = 0.001), and several ratio measures. Decaffeinated coffee was not associated with 2-pathway metabolism, but women in the highest (vs. lowest) category of intake (≥2 cups/day vs. ≤1–3 cups/month) had significantly lower levels of two 16-pathway metabolites, estriol (25% difference; Ptrend = 0.01) and 17-epiestriol (48% difference; Ptrend = 0.0004). Tea intake was positively associated with 17-epiestriol (52% difference; Ptrend = 0.01).

Conclusion: Caffeine and coffee intake were both associated with profiles of estrogen metabolism in premenopausal women.

Impact: Consumption of caffeine and coffee may alter patterns of premenopausal estrogen metabolism. Cancer Epidemiol Biomarkers Prev; 24(8); 1174–83. ©2015 AACR.

This article is featured in Highlights of This Issue, p. 1149

Despite investigation in many large-scale epidemiologic studies, the association between coffee and breast cancer risk remains unclear. Although some evidence suggests a small inverse association between coffee and breast cancer risk (1, 2), some large prospective studies have reported null associations (3–6). Two meta-analyses reported that a 2-cup/day increase in coffee intake was associated with a nonsignificant 2% lower breast cancer risk (7, 8). Isolating the mechanism through which coffee might affect cancer risk is complicated by the chemical complexity of coffee, which comprises many potentially bioactive compounds. Coffee contains polyphenol antioxidants, which have been hypothesized to reduce breast cancer risk (9, 10), and is a major dietary source of caffeine, which has been inversely associated with breast cancer risk in some (1, 2, 7), though not all (3–6), studies. Caffeine represents a particularly interesting biologic component of coffee with respect to breast cancer, given that enzymes involved in its metabolism also play a role in estrogen metabolism (11, 12).

Parent estrogens, estrone and estradiol, are irreversibly metabolized along three different pathways, depending on the initial hydroxylation at the 2-, 4-, or 16-position of the steroid ring. Estrogen metabolites (EM) formed in each pathway are believed to have varying degrees of carcinogenic potential (13). Catechol estrogens, which have two adjacent hydroxyl groups, are formed after the initial hydroxylation of the parent estrogens at the 2- or 4-positions and may be oxidized to produce reactive quinones or inactivated by methylation of one of the adjacent their hydroxyl groups. Quinones may damage DNA directly, and also may undergo redox cycling to produce mutagenic reactive oxygen species. Laboratory studies suggest that 4-pathway catechols have more potential to induce DNA damage than 2-pathway catechols because they form covalent, depurinating adducts, and 2-methoxyestradiol may have antiestrogenic properties, inhibiting proliferation of breast cancer cells. Animal and laboratory evidence have demonstrated that metabolites in the 16-pathway are not only genotoxic, causing the formation of depurinating DNA adducts, but also bind tightly to the estrogen receptor, upregulate it, and increase cell proliferation (14–16). Although there is limited epidemiologic data for premenopausal women, among premenopausal women in the Nurses' Health Study II (NHSII), urinary mid-luteal levels of one 16-pathway EM and a higher ratio of 16-pathway metabolites to parent estrogens were associated with increased risk of breast cancer, while metabolites in the 2- and 4-pathways appeared inversely associated with risk (17).

The initial hydroxylation of the parent estrogens is catalyzed primarily by cytochrome P450 enzymes, which play key roles in the metabolism of caffeine. Of particular interest is the CYP1A2 isoform, which catalyzes the hydroxylation of the parent estrogens (11), and the initial demethylation of caffeine in humans (12). In prior studies, polymorphisms in the CYP1A2 gene modified the association between coffee consumption and age at breast cancer diagnosis and estrogen receptor status in the general population (18), and modified the association between coffee intake and risk of breast cancer among BRCA1 mutation carriers (19). Previously, in premenopausal women in the NHSII, we observed an inverse association between coffee and caffeine intake and mid-luteal plasma levels of estradiol (20). In another study of premenopausal women, coffee intake was positively associated with plasma levels of 2-hydroxyestrone, and nonsignificantly inversely associated with 16α-hydroxyestrone (21). However, it is unclear whether these associations are attributable to caffeine, or other known or unknown bioactive elements of coffee.

We sought to further elucidate the relationship between coffee and caffeine intakes and patterns of estrogen metabolism. Using a liquid chromatography/tandem mass spectrometry (LC/MS-MS) method with high sensitivity, accuracy, and reproducibility, we examined the cross-sectional relationship between intake of caffeine, coffee, tea, and decaffeinated coffee and urinary levels of 15 individual estrogens and EM (all 15 referred to as EM), total EM, and estrogen metabolism pathway measures among premenopausal women in the NHSII.

Study population

The NHSII is an ongoing prospective cohort study, established in 1989, when 116,430 registered nurses ages 25 to 42 years were enrolled. At baseline and biennially since, participants have returned mailed questionnaires with updated information about disease and exposure status. In 1996–1999, participants who were cancer-free and ages 32 to 54 years were asked to provide blood and urine samples. Of 29,611 women who provided samples, 18,521 who were premenopausal and had not been pregnant, breastfed, or used oral contraceptives in the 6 months preceding collection provided samples timed within their menstrual cycle. Women collected follicular phase blood samples during days 3 to 5 of their menstrual cycle, and blood and urine samples during the mid-luteal phase, 7 to 9 days before the anticipated start of their next cycle. Urine samples were shipped with an ice pack to our laboratory via overnight courier; 93% of samples were received within 26 hours of collection. Upon arrival at the laboratory, urine samples were aliquoted into cryotubes without preservatives and stored in liquid nitrogen freezers.

The current study population includes 110 women selected for a biomarker reproducibility study (22), and 493 controls from a nested case–control study of breast cancer (17). Of these 603 women, 587 had exposure data.

Assessment of exposure

Semi-quantitative food frequency questionnaires (FFQ) were used to assess intake of specific foods every 4 years, beginning in 1991. Possible choices for intake of coffee, caffeinated tea, and decaffeinated coffee ranged from “never or less than once per month” to “6 or more times per day.” Caffeine intake was derived from self-reported intakes of coffee, soda, tea, and chocolate using their caffeine content per serving as estimated by the U.S. Department of Agriculture (USDA) food composition sources. The average amount of caffeine was estimated to be 137 mg per 8 oz serving of coffee, 47 mg per 8 oz serving of tea, 46 mg per 12 oz serving of soda, and 7 mg per 1 oz serving of chocolate.

Caffeine was adjusted for energy intake using the residual method (23), and modeled as quartiles of daily intake (mg), while intake of each specific beverage was modeled as servings per month, week, or day. Results for caffeine were unchanged when unadjusted intakes were used. We present analyses using the 1999 self-reported intakes for exposure; results using the mean of the 1995 and 1999 responses were not appreciably different.

Assessment of covariates

The questionnaire completed at urine collection included information about collection time, whether urine was first morning void, and the participant's present weight and tobacco use. To confirm menstrual cycle phase and calculate luteal day at specimen collection, 97% of participants recorded the date of their next menstrual period on a postcard returned by mail. Progesterone levels were measured in the blood sample drawn on the same day as urine collection (24, 25). We considered women with luteal progesterone levels ≥400 ng/dL to have donated samples in an ovulatory cycle, while participants with levels below this cutoff point were defined as having an anovulatory cycle.

Anthropometric, reproductive, and other lifestyle factors were assessed on biennial questionnaires. Information on menstrual cycle regularity and usual length was obtained in 1993. Body mass index (BMI) was calculated from weight at time of urine collection and height in 1989. Physical activity was queried every 4 years; we used the average of the 1997 and 2001 surveys to estimate physical activity in metabolic equivalent (MET) hours/week. Average alcohol intake was calculated from the 1995 and 1999 FFQs.

Laboratory methods

Details of the assay have previously been described (26, 27). Briefly, frozen 500-μL aliquots of urine were shipped to the Laboratory of Proteomics and Analytical Technologies (Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD), where levels of 15 individual EM were quantified using stable isotope dilution LC/MS-MS. Because urinary EM are generally present as glucoronide and sulfate conjugates, an initial hydrolysis step was performed using B-glucuronidase/sulfatase from Helix pomatia. To correct for loss of EM throughout the assay procedure and allow accurate quantification, an internal standard solution of 5 deuterated EM (17β-estradiol-d4, estriol-d3, 2-hydroxy-17β-estradiol-d5, 2-methoxy-17β-estradiol-d5, 16-epiestriol-d3) was added to each thawed aliquot. Each batch of urine samples included masked replicate quality control samples, which were used to assess intra- and interbatch assay variability. For most metabolites, coefficients of variation were below 7%, though two low concentration EM, 4-methoxyestradiol and 4-methoxyestrone, had CVs of 15% and 17%, respectively. The lower limit of quantitation for all EM was approximately 150 fmol/mL urine.

Two batches of urinary creatinine were measured at the Endocrine Core Laboratory at Emory University (Atlanta, GA); a third was measured at the laboratory of Dr. Vincent Ricchiuti at Brigham and Women's Hospital (Boston, MA). CVs were ≤9.2%. Plasma progesterone was assayed by chemiluminescent immunoassay using the Immulite Auto-Analyzer (Diagnostic Products Corp.). Overall CVs were ≤17%, while within-batch CVs were ≤4%.

Statistical analysis

EM levels were standardized by creatinine level to account for differences in urine volume and concentration. EM were assessed individually and summed as total EM; we additionally examined a number of groups (i.e., catechols) and ratios of individual EM and pathways based on shared biochemical characteristics, known metabolic pathways, and etiologic hypotheses. To improve normality, all outcome measures were log-transformed. Statistical outliers for each measure were identified using the generalized extreme Studentized deviate many-outlier approach (28), and removed from analyses [N = 0–16 (2-methoxyestradiol)].

Multivariate linear mixed models were used to estimate geometric means of the log-transformed metabolites, pathways, and ratios by exposure category. Tests of linear trend were conducted by modeling the median of each beverage intake category and the quartile medians of caffeine intake as continuous variables. All models were adjusted for age at urine collection, BMI at collection, height, ovulatory cycle, first-morning urine, alcohol intake, total physical activity, current tobacco use, luteal day, usual menstrual cycle length, menstrual cycle regularity, and age at first birth and parity. Additional adjustment for creatinine did not significantly change our results, and this variable was not retained in final models.

In secondary analyses, we restricted to women with ovulatory cycles, nonsmokers, or women who provided samples between luteal days 4 and 10. We also examined potential effect modification by BMI (≤25 vs. >25). Wald tests were used to assess the significance of interaction terms between dichotomous BMI and the median of the exposure category that were included in models that included all women. All P values were two-sided and tests of significance were performed at the α = 0.05 level. All analyses were conducted using SAS v. 9.2 (SAS Institute).

The mean age of the study population was 42.8 years at urine collection, and the mean BMI was 25.1 (Table 1). On the basis of plasma progesterone level, 90% of cycles were ovulatory; 86% of samples were collected 4 to 10 days prior to next menstrual period. Compared with women with the lowest caffeine intake, those with highest intake were more likely to report being current smokers, had higher alcohol intake, and were less likely to have provided a first-morning urine sample. Women with highest caffeine intake were also slightly older than those with the lowest intake and had a higher BMI.

Table 1.

Characteristics of the premenopausal study population by quartiles of caffeine intake

<49 mg/d49–163 mg/d164–366 mg/d≥367 mg/d
144 144 144 145 
Age at urine collection, y 42.2 (4.0) 42.9 (3.9) 43.1 (3.9) 43.4 (3.4) 
Urinary creatinine, mg/L 1,146 (589) 1,209 (548) 1,077 (590) 1,094 (657) 
Ovulatory cycle, % 91 90 88 90 
First-morning urine sample, % 88 86 71 75 
Sample collected 4–10 days before next menstrual period, % 88 87 87 81 
BMI at time of urine collection, kg/m2 24.7 (4.9) 25.0 (5.1) 25.4 (5.3) 25.6 (6.0) 
Height, inches 65.1 (2.7) 65.2 (2.5) 65.1 (3.1) 65.0 (2.3) 
Caucasian, % 97 96 99 95 
Physical activity, MET-h/wk 20.9 (18.6) 21.3 (21.8) 22.8 (20.9) 20.7 (17.7) 
Alcohol intake, g/d 2.2 (5.5) 3.5 (5.1) 4.6 (6.2) 5.3 (7.0) 
Current smoker, % 12 
Parous, % 83 81 81 82 
Age at first birth, y 26.7 (4.3) 26.6 (4.6) 26.4 (4.8) 27.3 (4.9) 
Regular menstrual cycles, % 96 94 94 97 
Menstrual cycle length 26–31 days, % 71 66 67 63 
Coffee intake, cups/day 0 (0) 0.4 (0.4) 1.6 (0.9) 3.1 (1.1) 
Decaffeinated coffee intake, cups/day 0.4 (0.9) 0.3 (0.7) 0.4 (0.8) 0.2 (0.6) 
Tea intake, cups/day 0.1 (0.1) 0.5 (0.7) 0.5 (1.0) 0.4 (0.8) 
<49 mg/d49–163 mg/d164–366 mg/d≥367 mg/d
144 144 144 145 
Age at urine collection, y 42.2 (4.0) 42.9 (3.9) 43.1 (3.9) 43.4 (3.4) 
Urinary creatinine, mg/L 1,146 (589) 1,209 (548) 1,077 (590) 1,094 (657) 
Ovulatory cycle, % 91 90 88 90 
First-morning urine sample, % 88 86 71 75 
Sample collected 4–10 days before next menstrual period, % 88 87 87 81 
BMI at time of urine collection, kg/m2 24.7 (4.9) 25.0 (5.1) 25.4 (5.3) 25.6 (6.0) 
Height, inches 65.1 (2.7) 65.2 (2.5) 65.1 (3.1) 65.0 (2.3) 
Caucasian, % 97 96 99 95 
Physical activity, MET-h/wk 20.9 (18.6) 21.3 (21.8) 22.8 (20.9) 20.7 (17.7) 
Alcohol intake, g/d 2.2 (5.5) 3.5 (5.1) 4.6 (6.2) 5.3 (7.0) 
Current smoker, % 12 
Parous, % 83 81 81 82 
Age at first birth, y 26.7 (4.3) 26.6 (4.6) 26.4 (4.8) 27.3 (4.9) 
Regular menstrual cycles, % 96 94 94 97 
Menstrual cycle length 26–31 days, % 71 66 67 63 
Coffee intake, cups/day 0 (0) 0.4 (0.4) 1.6 (0.9) 3.1 (1.1) 
Decaffeinated coffee intake, cups/day 0.4 (0.9) 0.3 (0.7) 0.4 (0.8) 0.2 (0.6) 
Tea intake, cups/day 0.1 (0.1) 0.5 (0.7) 0.5 (1.0) 0.4 (0.8) 

NOTE: Values are means (SD) or percentages.

About half of women (49.9%) reported drinking ≤6 cups of coffee/week, and 40 (6.9%) reported drinking ≥4 cups/day. Median caffeine intake was 163.1 mg/day. Consumption of tea and decaffeinated coffee was notably lower than that of coffee; 415 women (71.4%) reported drinking <1 cup of tea/week, while 36 (6.2%) reported drinking ≥2 cups/day. A total of 369 (63.5%) participants drank decaffeinated coffee <3 times/month and 44 (7.6%) drank ≥2 cups/day. No significant correlations were observed between intakes of coffee, decaffeinated coffee, and tea (all r < 0.08).

In multivariate analyses, caffeine intake was associated with several individual EM and metabolic ratios (Table 2). Higher caffeine intake was associated with higher urinary levels of two 16-pathway metabolites, 16α-hydroxyestrone (28% higher among women in the highest quartile of caffeine intake compared with the lowest quartile, Ptrend = 0.01), and 16-epiestriol (13% higher, Ptrend = 0.04). Furthermore, suggestively, though not significantly, higher 16-ketoestradiol levels were observed at higher levels of caffeine intake (12% higher, Ptrend = 0.07). However, the combined 16-pathway was only nonsignificantly 5% higher at higher caffeine intake.

Table 2.

Multivariate-adjusteda geometric means of estrogen metabolism measures by quartiles of caffeine intake

Geometric mean by caffeine intake
<49 mg/d49–163 mg/d164–366 mg/d≥367 mg/dPtrend
144 144 144 145  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 199.0 183.4 203.5 211.0 0.10 
Parent estrogens 40.8 39.4 40.5 41.3 0.67 
 Estrone 26.8 25.4 26.4 27.4 0.54 
 Estradiol 13.2 12.8 12.9 13.5 0.66 
Catechols 67.8 61.5 62.3 74.6 0.19 
 2-catechols 56.7 53.0 53.1 65.3 0.10 
  2-Hydroxyestrone 50.0 46.8 46.5 57.9 0.10 
  2-Hydroxyestradiol 5.8 5.4 5.6 6.5 0.14 
 4-catechols      
  4-Hydroxyestrone 7.6 5.7 5.9 6.2 0.28 
Methylated catechols 11.4 10.9 10.1 10.5 0.28 
 Methylated 2-catechols 11.1 10.6 9.7 10.1 0.25 
  2-Methoxyestrone 8.7 8.2 7.6 7.8 0.18 
  2-Methoxyestradiol 0.78 0.70 0.71 0.69 0.29 
  2-Hydroxyestrone-3-methyl ether 1.4 1.3 1.2 1.3 0.18 
 Methylated 4-catechols 0.25 0.23 0.22 0.25 0.91 
  4-Methoxyestrone 0.15 0.15 0.13 0.18 0.37 
  4-Methoxyestradiol 0.06 0.05 0.06 0.05 0.45 
2-Hydroxylation pathway 70.1 64.8 64.0 76.7 0.25 
4-Hydroxylation pathway 8.3 6.8 6.6 7.2 0.39 
16-Hydroxylation pathway 62.3 61.0 67.3 65.3 0.33 
16α-Hydroxyestrone 9.7 10.1 11.2 12.4 0.01 
 Estriol 27.5 26.4 30.6 26.2 1.00 
 17-Epiestriol 1.6 1.7 1.7 1.6 0.96 
 16-Ketoestradiol 12.2 12.6 14.2 13.7 0.07 
16-Epiestriol 5.3 5.4 5.9 6.0 0.04 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 5.0 4.6 4.0 4.5 0.29 
4-Pathway/2-pathway 0.11 0.10 0.10 0.09 0.01 
2-Pathway/16-pathway 1.1 1.0 0.9 1.2 0.69 
2,4-Pathway/16-pathway 0.13 0.11 0.09 0.11 0.15 
2-Catechols/methylated 2-catechols 5.0 4.9 5.4 6.3 0.0002 
4-Catechols/methylated 4-catechols 31.7 25.9 27.2 26.8 0.53 
Catechols/methylated catechols 5.8 5.5 6.1 7.0 0.001 
Parent estrogens/2-, 4-, 16-pathways 0.28 0.28 0.26 0.25 0.03 
2-Pathway/parent estrogens 1.7 1.6 1.5 1.8 0.23 
4-Pathway/parent estrogens 0.20 0.17 0.16 0.17 0.20 
16-Pathway/parent estrogens 1.5 1.6 1.7 1.6 0.50 
Geometric mean by caffeine intake
<49 mg/d49–163 mg/d164–366 mg/d≥367 mg/dPtrend
144 144 144 145  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 199.0 183.4 203.5 211.0 0.10 
Parent estrogens 40.8 39.4 40.5 41.3 0.67 
 Estrone 26.8 25.4 26.4 27.4 0.54 
 Estradiol 13.2 12.8 12.9 13.5 0.66 
Catechols 67.8 61.5 62.3 74.6 0.19 
 2-catechols 56.7 53.0 53.1 65.3 0.10 
  2-Hydroxyestrone 50.0 46.8 46.5 57.9 0.10 
  2-Hydroxyestradiol 5.8 5.4 5.6 6.5 0.14 
 4-catechols      
  4-Hydroxyestrone 7.6 5.7 5.9 6.2 0.28 
Methylated catechols 11.4 10.9 10.1 10.5 0.28 
 Methylated 2-catechols 11.1 10.6 9.7 10.1 0.25 
  2-Methoxyestrone 8.7 8.2 7.6 7.8 0.18 
  2-Methoxyestradiol 0.78 0.70 0.71 0.69 0.29 
  2-Hydroxyestrone-3-methyl ether 1.4 1.3 1.2 1.3 0.18 
 Methylated 4-catechols 0.25 0.23 0.22 0.25 0.91 
  4-Methoxyestrone 0.15 0.15 0.13 0.18 0.37 
  4-Methoxyestradiol 0.06 0.05 0.06 0.05 0.45 
2-Hydroxylation pathway 70.1 64.8 64.0 76.7 0.25 
4-Hydroxylation pathway 8.3 6.8 6.6 7.2 0.39 
16-Hydroxylation pathway 62.3 61.0 67.3 65.3 0.33 
16α-Hydroxyestrone 9.7 10.1 11.2 12.4 0.01 
 Estriol 27.5 26.4 30.6 26.2 1.00 
 17-Epiestriol 1.6 1.7 1.7 1.6 0.96 
 16-Ketoestradiol 12.2 12.6 14.2 13.7 0.07 
16-Epiestriol 5.3 5.4 5.9 6.0 0.04 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 5.0 4.6 4.0 4.5 0.29 
4-Pathway/2-pathway 0.11 0.10 0.10 0.09 0.01 
2-Pathway/16-pathway 1.1 1.0 0.9 1.2 0.69 
2,4-Pathway/16-pathway 0.13 0.11 0.09 0.11 0.15 
2-Catechols/methylated 2-catechols 5.0 4.9 5.4 6.3 0.0002 
4-Catechols/methylated 4-catechols 31.7 25.9 27.2 26.8 0.53 
Catechols/methylated catechols 5.8 5.5 6.1 7.0 0.001 
Parent estrogens/2-, 4-, 16-pathways 0.28 0.28 0.26 0.25 0.03 
2-Pathway/parent estrogens 1.7 1.6 1.5 1.8 0.23 
4-Pathway/parent estrogens 0.20 0.17 0.16 0.17 0.20 
16-Pathway/parent estrogens 1.5 1.6 1.7 1.6 0.50 

aAdjusted for age at urine collection (continuous), BMI at collection (kg/m2, continuous), height (continuous), ovulatory cycle (yes/no), first-morning urine (yes/no), quartiles of alcohol intake (nondrinker, ≤1.49, 1.50–4.85, >4.85 g/day), total physical activity (<3, 3–8.9, 9–17.9, 18–26.9, 27–41.9, ≥42 MET h/wk), current tobacco use (yes/no), luteal day (≤5, 6–7, 8–9, ≥10 days to next period), usual menstrual cycle length (<26, 26–31, ≥32 days), menstrual cycle regularity (extremely regular, very regular, regular, usually/always irregular), and age at first birth and parity (nulliparous, age at first birth <25 years/1–2 children, age at first birth 25–29 years/1–2 children, age at first birth ≥30 years/1–2 children, age at first birth <25 years/≥3 children, age at first birth ≥25 years/≥3 children). Numbers do not sum to 603 due to missing values for exposure. Significant Ptrend shown in bold.

There were suggestive positive association between caffeine consumption and the 2-catechols, though these associations did not appear linear and were not statistically significant. Compared with women in the lowest quartile of caffeine intake, those with the highest intake had 16% higher levels of 2-hydroxyestrone (Ptrend = 0.10) and 13% higher levels of 2-hydroxyestradiol (Ptrend = 0.14). These suggestive associations with 2-catechols appeared to drive the positive associations observed with the 2-catechols/methylated 2-catechols ratio (Ptrend = 0.0002), and the catechols/methylated catechols ratio (Ptrend = 0.001), and the inverse association with the 4-pathway/2-pathway ratio (Ptrend = 0.01). Finally, an inverse association between caffeine and the parent estrogens/2-, 4-, 16-pathway ratio was observed (Ptrend = 0.03), largely because total EM nonsignificantly increased with caffeine intake (Ptrend = 0.10).

Coffee consumption was positively associated with urinary levels of 2-catechols, but not with methylated 2- or 4-catechols (Table 3). Compared with women who reported drinking ≤6 cups/week, those who drank ≥4 cups/day had 52% higher 2-hydroxyestrone levels (Ptrend = 0.001) and 57% higher 2-hydroxyestradiol levels (Ptrend = 0.001). Overall, 2-catechols were 52% higher (Ptrend = 0.001), catechols were 45% higher (Ptrend = 0.002), and the 2-hydroxylation pathway was 41% higher (Ptrend = 0.01) among participants in the top category of intake compared with the lowest.

Table 3.

Multivariate-adjusteda geometric means of estrogen metabolism measures by category of coffee intake

Geometric mean by coffee intake
≤6 cups/wk1 cup/day2–3 cups/day4+ cups/dayPtrend
293 73 181 40  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 195.5 197.0 207.2 222.7 0.08 
Parent estrogens 40.5 41.8 41.2 44.4 0.37 
 Estrone 26.1 28.0 27.6 28.5 0.29 
 Estradiol 13.5 12.5 13.3 14.7 0.51 
Catechols 61.2 62.0 69.4 88.5 0.002 
2-catechols 51.9 54.4 59.7 79.0 0.001 
  2-Hydroxyestrone 45.7 48.4 52.6 69.6 0.001 
  2-Hydroxyestradiol 5.4 5.3 6.1 8.4 0.001 
 4-catechols 
  4-Hydroxyestrone 6.1 5.5 6.1 7.1 0.61 
Methylated catechols 11.2 10.2 10.4 10.7 0.49 
 Methylated 2-catechols 10.8 9.8 10.0 10.4 0.46 
  2-Methoxyestrone 8.3 7.6 7.8 7.9 0.45 
  2-Methoxyestradiol 0.71 0.71 0.69 0.73 0.94 
  2-Hydroxyestrone-3-methyl ether 1.4 1.2 1.3 1.3 0.37 
 Methylated 4-catechols 0.25 0.23 0.25 0.26 0.86 
  4-Methoxyestrone 0.16 0.14 0.16 0.18 0.47 
  4-Methoxyestradiol 0.06 0.06 0.05 0.05 0.51 
2-Hydroxylation pathway 64.3 64.8 70.7 90.5 0.01 
4-Hydroxylation pathway 7.0 6.1 7.1 7.8 0.59 
16-Hydroxylation pathway 65.8 65.7 65.8 61.6 0.79 
 16α-Hydroxyestrone 10.7 11.4 11.3 12.6 0.17 
 Estriol 29.4 27.9 28.3 24.6 0.30 
 17-Epiestriol 1.7 1.6 1.4 1.9 0.51 
 16-Ketoestradiol 13.1 14.0 13.7 13.6 0.45 
 16-Epiestriol 5.6 5.3 6.0 5.9 0.28 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.3 4.1 4.5 5.0 0.32 
4-Pathway/2-pathway 0.10 0.10 0.09 0.09 0.03 
2-Pathway/16-pathway 0.94 1.0 1.1 1.4 0.01 
2,4-Pathway/16-pathway 0.10 0.09 0.11 0.12 0.53 
2-Catechols/methylated 2-catechols 4.7 5.5 6.0 7.4 <0.0001 
4-Catechols/methylated 4-catechols 25.1 23.3 26.2 29.2 0.54 
Catechols/methylated catechols 5.4 6.0 6.7 8.1 <0.0001 
Parent estrogens/2-, 4-, 16-pathways 0.28 0.28 0.26 0.25 0.10 
2-Pathway/parent estrogens 1.5 1.6 1.7 2.0 0.003 
4-Pathway/parent estrogens 0.17 0.15 0.17 0.17 0.84 
16-Pathway/parent estrogens 1.6 1.6 1.6 1.5 0.35 
Geometric mean by coffee intake
≤6 cups/wk1 cup/day2–3 cups/day4+ cups/dayPtrend
293 73 181 40  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 195.5 197.0 207.2 222.7 0.08 
Parent estrogens 40.5 41.8 41.2 44.4 0.37 
 Estrone 26.1 28.0 27.6 28.5 0.29 
 Estradiol 13.5 12.5 13.3 14.7 0.51 
Catechols 61.2 62.0 69.4 88.5 0.002 
2-catechols 51.9 54.4 59.7 79.0 0.001 
  2-Hydroxyestrone 45.7 48.4 52.6 69.6 0.001 
  2-Hydroxyestradiol 5.4 5.3 6.1 8.4 0.001 
 4-catechols 
  4-Hydroxyestrone 6.1 5.5 6.1 7.1 0.61 
Methylated catechols 11.2 10.2 10.4 10.7 0.49 
 Methylated 2-catechols 10.8 9.8 10.0 10.4 0.46 
  2-Methoxyestrone 8.3 7.6 7.8 7.9 0.45 
  2-Methoxyestradiol 0.71 0.71 0.69 0.73 0.94 
  2-Hydroxyestrone-3-methyl ether 1.4 1.2 1.3 1.3 0.37 
 Methylated 4-catechols 0.25 0.23 0.25 0.26 0.86 
  4-Methoxyestrone 0.16 0.14 0.16 0.18 0.47 
  4-Methoxyestradiol 0.06 0.06 0.05 0.05 0.51 
2-Hydroxylation pathway 64.3 64.8 70.7 90.5 0.01 
4-Hydroxylation pathway 7.0 6.1 7.1 7.8 0.59 
16-Hydroxylation pathway 65.8 65.7 65.8 61.6 0.79 
 16α-Hydroxyestrone 10.7 11.4 11.3 12.6 0.17 
 Estriol 29.4 27.9 28.3 24.6 0.30 
 17-Epiestriol 1.7 1.6 1.4 1.9 0.51 
 16-Ketoestradiol 13.1 14.0 13.7 13.6 0.45 
 16-Epiestriol 5.6 5.3 6.0 5.9 0.28 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.3 4.1 4.5 5.0 0.32 
4-Pathway/2-pathway 0.10 0.10 0.09 0.09 0.03 
2-Pathway/16-pathway 0.94 1.0 1.1 1.4 0.01 
2,4-Pathway/16-pathway 0.10 0.09 0.11 0.12 0.53 
2-Catechols/methylated 2-catechols 4.7 5.5 6.0 7.4 <0.0001 
4-Catechols/methylated 4-catechols 25.1 23.3 26.2 29.2 0.54 
Catechols/methylated catechols 5.4 6.0 6.7 8.1 <0.0001 
Parent estrogens/2-, 4-, 16-pathways 0.28 0.28 0.26 0.25 0.10 
2-Pathway/parent estrogens 1.5 1.6 1.7 2.0 0.003 
4-Pathway/parent estrogens 0.17 0.15 0.17 0.17 0.84 
16-Pathway/parent estrogens 1.6 1.6 1.6 1.5 0.35 

aAdjusted for age at urine collection (continuous), BMI at collection (kg/m2, continuous), height (continuous), ovulatory cycle (yes/no), first-morning urine (yes/no), quartiles of alcohol intake (nondrinker, ≤1.49, 1.50–4.85, >4.85 g/day), total physical activity (<3, 3–8.9, 9–17.9, 18–26.9, 27–41.9, ≥42 MET h/week), current tobacco use (yes/no), luteal day (≤5, 6–7, 8–9, ≥10 days to next period), usual menstrual cycle length (<26, 26–31, ≥32 days), menstrual cycle regularity (extremely regular, very regular, regular, usually/always irregular), and age at first birth and parity (nulliparous, age at first birth <25 years/1–2 children, age at first birth 25–29 years/1–2 children, age at first birth ≥30 years/1–2 children, age at first birth <25 years/≥3 children, age at first birth ≥25 years/≥3 children). Numbers do not sum to 603 due to missing values for exposure. Significant Ptrend shown in bold.

A number of ratios comparing 2-catechol levels to other pathways were also associated with coffee consumption. Positive associations were observed for the following ratios where 2-catechols were included in the numerator: 2-pathway/16-pathway (Ptrend = 0.01), 2-catechols/methylated 2-catechols (Ptrend < 0.0001), catechols/methylated catechols (Ptrend < 0.0001), and 2-pathway/parent estrogens ratio (Ptrend = 0.003). Conversely, an inverse association with coffee intake was observed for the 4-pathway/2-pathway ratio (Ptrend = 0.03). As with caffeine, total EM nonsignificantly increased with coffee intake (Ptrend = 0.08).

Markedly fewer associations were observed between individual EM and decaffeinated coffee and tea intakes (Tables 4 and 5). Two individual 16-pathway metabolites were inversely associated with decaffeinated coffee intake (Table 4). Compared with those who reported drinking ≤3 cups/month, participants who drank ≥2 cups/day had 25% lower estriol levels (Ptrend = 0.01) and 48% lower 17-epiestriol levels (Ptrend = 0.0004). Decaffeinated coffee also was suggestively but nonsignificantly inversely associated with other 16-pathway metabolites, specifically 16-ketoestradiol (top vs. bottom intake: 14% lower) and 16-epiestriol (16% lower). Overall, levels of all 16-pathway metabolites combined were 16% lower among participants in the highest category, though the test for trend was not significant (Ptrend = 0.14).

Table 4.

Multivariate-adjusteda geometric means of estrogen metabolism measures by category of decaffeinated coffee intake

Geometric mean by decaffeinated coffee intake
≤1–3 cups/month1–6 cups/week1 cup/day2+ cups/dayPtrend
369 132 36 44  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 208.1 212.0 175.8 205.2 0.60 
Parent estrogens 42.5 45.2 33.5 39.6 0.28 
 Estrone 28.1 28.7 21.5 26.8 0.42 
 Estradiol 13.8 14.8 10.8 12.2 0.07 
Catechols 65.9 74.8 63.6 76.6 0.33 
 2-catechols 56.7 64.3 54.8 65.2 0.35 
  2-Hydroxyestrone 50.0 56.8 48.7 57.2 0.39 
  2-Hydroxyestradiol 5.8 6.4 5.3 7.0 0.19 
 4-catechols 
  4-Hydroxyestrone 6.4 6.8 4.3 6.8 0.73 
Methylated catechols 10.9 11.9 8.7 11.1 0.86 
 Methylated 2-catechols 10.5 11.5 8.4 10.7 0.93 
  2-Methoxyestrone 8.2 9.0 6.3 8.4 0.86 
  2-Methoxyestradiol 0.71 0.73 0.61 0.72 0.69 
  2-Hydroxyestrone-3-methyl ether 1.3 1.4 1.2 1.5 0.27 
 Methylated 4-catechols 0.26 0.26 0.20 0.27 0.96 
  4-Methoxyestrone 0.17 0.16 0.14 0.16 0.64 
  4-Methoxyestradiol 0.06 0.06 0.05 0.07 0.38 
2-Hydroxylation pathway 68.6 77.2 65.8 76.5 0.46 
4-Hydroxylation pathway 7.3 7.5 5.4 7.8 0.84 
16-Hydroxylation pathway 67.9 65.6 61.2 57.3 0.14 
 16α-Hydroxyestrone 11.3 11.3 11.4 10.7 0.99 
Estriol 29.7 30.3 23.5 22.3 0.01 
17-Epiestriol 1.8 1.5 1.7 0.92 0.0004 
 16-Ketoestradiol 14.0 13.1 13.0 12.0 0.31 
 16-Epiestriol 6.0 5.7 5.0 5.1 0.11 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.3 4.8 4.1 5.3 0.42 
4-Pathway/2-pathway 0.10 0.10 0.09 0.09 0.56 
2-Pathway/16-pathway 1.02 1.15 1.0 1.2 0.28 
2,4-Pathway/16-pathway 0.10 0.11 0.10 0.13 0.31 
2-Catechols/methylated 2-catechols 5.4 5.6 5.7 6.1 0.27 
4-Catechols/methylated 4-catechols 25.2 27.7 24.1 27.7 0.91 
Catechols/methylated catechols 6.1 6.3 6.3 6.9 0.25 
Parent estrogens/2-, 4-, 16-pathways 0.27 0.28 0.22 0.28 0.84 
2-Pathway/parent estrogens 1.6 1.7 1.8 1.8 0.22 
4-Pathway/parent estrogens 0.17 0.17 0.18 0.19 0.39 
16-Pathway/parent estrogens 1.6 1.5 1.9 1.4 0.62 
Geometric mean by decaffeinated coffee intake
≤1–3 cups/month1–6 cups/week1 cup/day2+ cups/dayPtrend
369 132 36 44  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 208.1 212.0 175.8 205.2 0.60 
Parent estrogens 42.5 45.2 33.5 39.6 0.28 
 Estrone 28.1 28.7 21.5 26.8 0.42 
 Estradiol 13.8 14.8 10.8 12.2 0.07 
Catechols 65.9 74.8 63.6 76.6 0.33 
 2-catechols 56.7 64.3 54.8 65.2 0.35 
  2-Hydroxyestrone 50.0 56.8 48.7 57.2 0.39 
  2-Hydroxyestradiol 5.8 6.4 5.3 7.0 0.19 
 4-catechols 
  4-Hydroxyestrone 6.4 6.8 4.3 6.8 0.73 
Methylated catechols 10.9 11.9 8.7 11.1 0.86 
 Methylated 2-catechols 10.5 11.5 8.4 10.7 0.93 
  2-Methoxyestrone 8.2 9.0 6.3 8.4 0.86 
  2-Methoxyestradiol 0.71 0.73 0.61 0.72 0.69 
  2-Hydroxyestrone-3-methyl ether 1.3 1.4 1.2 1.5 0.27 
 Methylated 4-catechols 0.26 0.26 0.20 0.27 0.96 
  4-Methoxyestrone 0.17 0.16 0.14 0.16 0.64 
  4-Methoxyestradiol 0.06 0.06 0.05 0.07 0.38 
2-Hydroxylation pathway 68.6 77.2 65.8 76.5 0.46 
4-Hydroxylation pathway 7.3 7.5 5.4 7.8 0.84 
16-Hydroxylation pathway 67.9 65.6 61.2 57.3 0.14 
 16α-Hydroxyestrone 11.3 11.3 11.4 10.7 0.99 
Estriol 29.7 30.3 23.5 22.3 0.01 
17-Epiestriol 1.8 1.5 1.7 0.92 0.0004 
 16-Ketoestradiol 14.0 13.1 13.0 12.0 0.31 
 16-Epiestriol 6.0 5.7 5.0 5.1 0.11 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.3 4.8 4.1 5.3 0.42 
4-Pathway/2-pathway 0.10 0.10 0.09 0.09 0.56 
2-Pathway/16-pathway 1.02 1.15 1.0 1.2 0.28 
2,4-Pathway/16-pathway 0.10 0.11 0.10 0.13 0.31 
2-Catechols/methylated 2-catechols 5.4 5.6 5.7 6.1 0.27 
4-Catechols/methylated 4-catechols 25.2 27.7 24.1 27.7 0.91 
Catechols/methylated catechols 6.1 6.3 6.3 6.9 0.25 
Parent estrogens/2-, 4-, 16-pathways 0.27 0.28 0.22 0.28 0.84 
2-Pathway/parent estrogens 1.6 1.7 1.8 1.8 0.22 
4-Pathway/parent estrogens 0.17 0.17 0.18 0.19 0.39 
16-Pathway/parent estrogens 1.6 1.5 1.9 1.4 0.62 

aAdjusted for age at urine collection (continuous), BMI at collection (kg/m2, continuous), height (continuous), ovulatory cycle (yes/no), first-morning urine (yes/no), quartiles of alcohol intake (nondrinker, ≤1.49, 1.50–4.85, >4.85 g/day), total physical activity (<3, 3–8.9, 9–17.9, 18–26.9, 27–41.9, ≥42 MET h/week), current tobacco use (yes/no), luteal day (≤5, 6–7, 8–9, ≥10 days to next period), usual menstrual cycle length (<26, 26–31, ≥32 days), menstrual cycle regularity (extremely regular, very regular, regular, usually/always irregular), and age at first birth and parity (nulliparous, age at first birth <25 years/1–2 children, age at first birth 25–29 years/1–2 children, age at first birth ≥30 years/1–2 children, age at first birth <25 years/ ≥3 children, age at first birth ≥25 years/≥3 children). Numbers do not sum to 603 due to missing values for exposure. Significant Ptrend shown in bold.

Table 5.

Multivariate-adjusteda geometric means of estrogen metabolism measures by category of tea intake

Geometric mean by tea intake
≤1–3 cups/month1–6 cups/week1 cup/day2+ cups/dayPtrend
415 80 50 36  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 210.7 194.2 189.6 215.5 0.76 
Parent estrogens 42.3 40.3 39.4 44.5 0.79 
 Estrone 27.9 26.6 25.5 27.7 0.66 
 Estradiol 13.6 13.2 13.2 15.4 0.17 
Catechols 69.7 70.0 62.6 61.5 0.35 
 2-catechols 59.9 60.7 54.0 52.5 0.38 
  2-Hydroxyestrone 52.8 53.8 47.9 45.9 0.39 
  2-Hydroxyestradiol 6.1 6.0 5.6 5.5 0.29 
 4-catechols      
  4-Hydroxyestrone 6.4 6.6 5.7 6.4 0.79 
Methylated catechols 10.9 10.7 11.7 12.2 0.34 
 Methylated 2-catechols 10.5 10.4 11.3 11.8 0.32 
  2-Methoxyestrone 8.1 8.2 8.8 8.7 0.63 
  2-Methoxyestradiol 0.72 0.72 0.66 0.75 0.80 
  2-Hydroxyestrone-3-methyl ether 1.4 1.2 1.4 1.4 0.80 
 Methylated 4-catechols 0.26 0.23 0.24 0.27 0.76 
  4-Methoxyestrone 0.17 0.16 0.15 0.18 0.82 
  4-Methoxyestradiol 0.06 0.05 0.06 0.05 0.66 
2-Hydroxylation pathway 71.9 72.6 66.4 66.4 0.59 
4-Hydroxylation pathway 7.4 7.0 6.8 7.3 0.88 
16-Hydroxylation pathway 67.4 58.6 60.2 74.0 0.29 
 16α-Hydroxyestrone 11.6 9.4 10.2 10.7 0.83 
 Estriol 28.9 26.7 25.5 34.7 0.13 
17-Epiestriol 1.6 1.7 1.6 2.4 0.01 
 16-Ketoestradiol 14.0 12.4 11.5 15.5 0.48 
 16-Epiestriol 5.9 5.2 5.5 6.3 0.44 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.4 5.6 4.9 4.1 0.76 
4-Pathway/2-pathway 0.10 0.10 0.09 0.10 0.62 
2-Pathway/16-pathway 1.05 1.1 1.1 0.86 0.20 
2,4-Pathway/16-pathway 0.10 0.12 0.12 0.08 0.26 
2-Catechols/methylated 2-catechols 5.7 5.5 4.8 4.4 0.02 
4-Catechols/methylated 4-catechols 26.4 26.8 24.8 21.4 0.32 
Catechols/methylated catechols 6.3 6.2 5.4 5.0 0.02 
Parent estrogens/2-, 4-, 16-pathways 0.27 0.27 0.28 0.28 0.85 
2-Pathway/parent estrogens 1.7 1.7 1.7 1.5 0.34 
4-Pathway/parent estrogens 0.17 0.17 0.17 0.15 0.36 
16-Pathway/parent estrogens 1.6 1.5 1.5 1.7 0.39 
Geometric mean by tea intake
≤1–3 cups/month1–6 cups/week1 cup/day2+ cups/dayPtrend
415 80 50 36  
Individual and grouped EM (pmol/mg creatinine) 
Total EM 210.7 194.2 189.6 215.5 0.76 
Parent estrogens 42.3 40.3 39.4 44.5 0.79 
 Estrone 27.9 26.6 25.5 27.7 0.66 
 Estradiol 13.6 13.2 13.2 15.4 0.17 
Catechols 69.7 70.0 62.6 61.5 0.35 
 2-catechols 59.9 60.7 54.0 52.5 0.38 
  2-Hydroxyestrone 52.8 53.8 47.9 45.9 0.39 
  2-Hydroxyestradiol 6.1 6.0 5.6 5.5 0.29 
 4-catechols      
  4-Hydroxyestrone 6.4 6.6 5.7 6.4 0.79 
Methylated catechols 10.9 10.7 11.7 12.2 0.34 
 Methylated 2-catechols 10.5 10.4 11.3 11.8 0.32 
  2-Methoxyestrone 8.1 8.2 8.8 8.7 0.63 
  2-Methoxyestradiol 0.72 0.72 0.66 0.75 0.80 
  2-Hydroxyestrone-3-methyl ether 1.4 1.2 1.4 1.4 0.80 
 Methylated 4-catechols 0.26 0.23 0.24 0.27 0.76 
  4-Methoxyestrone 0.17 0.16 0.15 0.18 0.82 
  4-Methoxyestradiol 0.06 0.05 0.06 0.05 0.66 
2-Hydroxylation pathway 71.9 72.6 66.4 66.4 0.59 
4-Hydroxylation pathway 7.4 7.0 6.8 7.3 0.88 
16-Hydroxylation pathway 67.4 58.6 60.2 74.0 0.29 
 16α-Hydroxyestrone 11.6 9.4 10.2 10.7 0.83 
 Estriol 28.9 26.7 25.5 34.7 0.13 
17-Epiestriol 1.6 1.7 1.6 2.4 0.01 
 16-Ketoestradiol 14.0 12.4 11.5 15.5 0.48 
 16-Epiestriol 5.9 5.2 5.5 6.3 0.44 
Ratios (pmol/pmol) 
2-Hydroxyestrone/16α-hydroxyestrone 4.4 5.6 4.9 4.1 0.76 
4-Pathway/2-pathway 0.10 0.10 0.09 0.10 0.62 
2-Pathway/16-pathway 1.05 1.1 1.1 0.86 0.20 
2,4-Pathway/16-pathway 0.10 0.12 0.12 0.08 0.26 
2-Catechols/methylated 2-catechols 5.7 5.5 4.8 4.4 0.02 
4-Catechols/methylated 4-catechols 26.4 26.8 24.8 21.4 0.32 
Catechols/methylated catechols 6.3 6.2 5.4 5.0 0.02 
Parent estrogens/2-, 4-, 16-pathways 0.27 0.27 0.28 0.28 0.85 
2-Pathway/parent estrogens 1.7 1.7 1.7 1.5 0.34 
4-Pathway/parent estrogens 0.17 0.17 0.17 0.15 0.36 
16-Pathway/parent estrogens 1.6 1.5 1.5 1.7 0.39 

aAdjusted for age at urine collection (continuous), BMI at collection (kg/m2, continuous), height (continuous), ovulatory cycle (yes/no), first-morning urine (yes/no), quartiles of alcohol intake (nondrinker, ≤1.49, 1.50–4.85, >4.85 g/day), total physical activity (<3, 3–8.9, 9–17.9, 18–26.9, 27–41.9, ≥42 MET h/week), current tobacco use (yes/no), luteal day (≤5, 6–7, 8–9, ≥10 days to next period), usual menstrual cycle length (<26, 26–31, ≥32 days), menstrual cycle regularity (extremely regular, very regular, regular, usually/always irregular), and age at first birth and parity (nulliparous, age at first birth <25 years/1–2 children, age at first birth 25–29 years/1–2 children, age at first birth ≥30 years/1–2 children, age at first birth <25 years/≥3 children, age at first birth ≥25 years/≥3 children). Numbers do not sum to 603 due to missing values for exposure. Significant Ptrend shown in bold.

Caffeinated tea intake was positively associated with 17-epiestriol (Ptrend = 0.01), which was 52% higher among those consuming ≥2 cups/day compared with those who drank ≤3 cups/month (Table 5). Tea intake was also inversely associated with the 2-catechols/methylated 2-catechols (Ptrend = 0.02) and the catechols/methylated catechols ratios (Ptrend = 0.02).

Results from sensitivity analyses among nonsmokers (n = 560), samples 4 to 10 days before next menstrual period (n = 516), and ovulatory cycles (n = 537) did not differ appreciably from the results of main analyses. We observed some evidence of modification by BMI of the association between coffee and estrogen metabolism, with several associations appearing stronger in overweight women (BMI > 25) than in normal weight women (BMI ≤ 25). Positive associations between coffee and 2-hydroxyestrone (P-interaction = 0.02), 2-hydroxyestradiol (P-interaction = 0.06), and 4-hydroxyestrone (P-interaction = 0.11) were observed only among overweight women. Positive associations between coffee intake and 2-catechols (Pinteraction = 0.02), catechols (Pinteraction = 0.02), 2-hydroxylation pathway (Pinteraction = 0.04), 4-hydroxylation pathway (Pinteraction = 0.13), and total EM (Pinteraction = 0.05) were limited to, or stronger among, overweight women. Consequently, the 2-catechols/methylated 2 catechols ratio (Pinteraction = 0.01), and catechols/methylated catechols ratio (Pinteraction = 0.01) were also limited to, or stronger among, overweight women. For other exposures, results stratified by BMI generally appeared similar.

When we summed regular and decaffeinated coffee, we observed associations that were similar to those seen for each exposure individually, though the magnitude of the associations appeared somewhat attenuated (data not shown). Positive associations were observed between total coffee intake and 2-hydroxyestrone (33% higher, ≥4 cups/day vs. ≤6 cups/week; Ptrend = 0.001) and 2-hydroxyestradiol (35% higher; Ptrend = 0.0001), and inverse associations were seen for estriol (17% lower; Ptrend = 0.03) and 17-epiestriol (33% lower; Ptrend = 0.02). Adjustment for caffeine did not materially change these results, though associations with 16-pathway metabolites appeared somewhat stronger (i.e., 17-epiestriol: 47% lower; Ptrend = 0.0003). Similarly, results for tea were generally unchanged when adjusted for caffeine.

In this population of premenopausal women, we observed several associations between coffee and caffeine intakes and luteal urinary levels of individual EM, metabolic pathways, and ratio measures. Interestingly, there were relatively few individual EM that were associated with more than one exposure. Coffee intake was positively associated with levels of both 2-catechol EM, 2-hydroxyestrone and 2-hydroxyestradiol, and several ratio and group measures involving these metabolites. In contrast, caffeine, caffeinated tea, and decaffeinated coffee were each associated with individual 16-pathway EM.

Prior to the development of the high-throughput LC/MS-MS method, measuring multiple EM was largely infeasible and inaccurate (26). Consequently, prior epidemiologic studies of caffeine, coffee, and EM focused largely on 2-hydroxyestrone and 16α-hydroxyestrone. Early evidence suggested that among premenopausal women not using oral contraceptives, daily coffee consumption was positively associated with plasma levels of 2-hydroxyestrone and 2-hydroxyestrone/16α-hydroxyestrone ratio, and nonsignificantly inversely associated with 16α-hydroxyestrone level (21). Bradlow and colleagues (29) also reported that coffee intake was positively associated with premenopausal 2-hydroxyestrone/16α-hydroxyestrone ratio in plasma, but not urine. However, in a large, multiethnic group of premenopausal women, coffee intake was not related to urinary 2-hydroxyestrone levels, though a positive association was observed between this metabolite and caffeine from non-coffee sources (30).

In addition to supporting previous findings of a positive association between coffee intake and 2-hydroxyestrone, our study provides evidence that coffee may be associated with 2-hydroxyestradiol, another 2-catechol. The strong association between coffee and 2-catechols in our study contributed to several associations with ratio measures, indicating that coffee intake may increase metabolism in the 2-pathway, relative to the 4- and 16-pathways. Coffee has many constituents that may influence estrogen metabolism, including caffeine. Metabolism of caffeine is catalyzed primarily by CYP1A2 enzymes, and laboratory and human studies have suggested that caffeine is as an inducer of CYP1A2 activity (12). This hepatic enzyme also plays a key role in 2-, 4-, and 16-hydroxylation of parent estrogens, though it is believed to be more active in hydroxylation at the C-2 position of the parent estrogens than at the C-4 or C-16α positions (11). Interestingly, we observed no significant association between caffeine and urinary levels of either 2-catechol EM, though some evidence of a nonlinear positive association was observed with 2-hydroxyestrone and 2-hydroxyestradiol. Independent of caffeine, coffee may also act as an inducer of CYP1A2 (31, 32), potentially by polycyclic aromatic hydrocarbons (PAH) produced by high-temperature brewing (33). Laboratory evidence also suggests that caffeic acid and chlorogenic acid, two polyphenols found in coffee, inhibit 2-catechol and 4-catechol methylation (34), which may explain the finding of a positive association between coffee and 2-catechols, though no associations with 4-catechols were observed. The associations between total (regular plus decaffeinated) coffee and 2-catechols persisted after adjustment for caffeine, and inverse associations with 16-pathway EM appeared stronger, suggesting that non-caffeine elements of coffee may be important in estrogen metabolism. However, given that coffee accounted for 72% of caffeine consumption among NHSII participants in 1999, it is difficult to disentangle the roles of caffeine versus other bioactive components of coffee in our population.

In contrast to regular coffee, decaffeinated coffee was not associated with 2-pathway EM, but rather, lower levels of two 16-pathway metabolites, estriol and 17-epiestriol. Decaffeinated and regular coffee differs in their caffeine content, and potentially in their antioxidant composition. Chemical analyses have detected lower levels of polyphenols in decaffeinated compared with regular coffee, possibly because of the decaffeination process (35, 36). In addition, it is possible that the relatively low range of decaffeinated coffee consumption in our study limited our ability to detect significant associations.

Laboratory evidence suggests that compared with 4- and 16-pathway EM, metabolites in the 2-pathway are hypothesized to have less genotoxic and estrogenic potential (13, 14, 37–39). Thus, our findings that coffee appears associated with higher 2-pathway activity may suggest a potential biologic mechanism through which coffee may reduce breast cancer risk, by shifting metabolism toward a profile in which 2-pathway metabolism is enhanced. However, associations between coffee and 2-pathway EM were limited to the 2-catechols, not the methylated 2-catechols that have been shown to inhibit growth of breast cancer cells in vitro (40). In addition, the associations between comprehensive profiles of estrogen metabolism and breast cancer risk have not been well studied, with the exception of our previous investigation in the NHSII (17). In that analysis, we did observed only suggestive, though not significant, associations between urinary levels of 2-and 4-pathway EM and risk. We also observed a positive association with a single 16-pathway EM, 17-epiestriol, as well as inverse associations with both parent estrogens. Thus, further work is needed to clarify relationships between EM profiles and breast cancer in humans. Finally, the relevance of urinary EM to breast cancer risk is as yet unclear, because these measures quantify excreted EM, which may be less indicative of estrogenic activity in breast tissue than plasma measurements.

The strengths of our study include well-timed luteal urine samples and precise and accurate quantification of 15 individual EM using a high-throughput approach. However, the cross-sectional nature of our study limits our ability to conclusively establish temporality. Furthermore, we only collected a single, luteal phase urine sample. Though luteal phase urinary EM have relatively high reproducibility over a 3-year period (22), we cannot extrapolate the associations with coffee, caffeine, and tea intake over other phases of the menstrual cycle. Although unmeasured confounding is always a possibility in an observational study, we carefully controlled for several factors associated with caffeine intake and urinary EM. For example, smoking was associated with caffeine intake in our population, and has been shown to be associated with patterns of estrogen metabolism (41); however, we adjusted for smoking, and results were unchanged when restricted to nonsmokers. Our assessment of exposure relied on self-reported data. However, results of a recent study in premenopausal women suggest that measurements of caffeine from FFQ and 24-hour recall are highly correlated (r = 0.73; P < 0.01), though FFQ measurements tend to be higher (42). Though we were not able to distinguish between specific types of coffees and teas, which may vary in caffeine content and chemical composition, associations between coffee and caffeine intakes derived from FFQ data and other outcomes in the Nurses' Health Studies suggest that self-reported intake is relatively well measured (43, 44). Finally, the large number of multiple comparisons performed could lead to the finding of statistically significant associations by chance. Because of correlations between metabolites, a Bonferroni-correction may be overly conservative. Nonetheless, at a corrected P-value of 0.003 (0.05/15 individual EM), some results remained statistically significant, including associations of 2-hydroxyestrone and 2-hydroxyestradiol with coffee.

In conclusion, our results suggest a relation of coffee and caffeine consumption with patterns of estrogen metabolism in premenopausal women. Our results support previous findings of a relationship between coffee and 2-hydroxyestrone, and possibly with the other 2-catechol, 2-hydroxyestradiol. In addition, we found associations between caffeine and 16-pathway metabolites, and suggestive associations with methylated 2-catechols. Further studies are needed to confirm our results.

No potential conflicts of interest were disclosed.

Conception and design: R. Ziegler, A.H. Eliassen

Development of methodology: R. Ziegler

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S.E. Hankinson, X. Xu, R. Ziegler, A.H. Eliassen

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.S. Sisti, S.E. Hankinson, R.M. Tamimi, B. Rosner, R. Ziegler

Writing, review, and/or revision of the manuscript: J.S. Sisti, S.E. Hankinson, N.E. Caporaso, F. Gu, R.M. Tamimi, X. Xu, R. Ziegler, A.H. Eliassen

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A.H. Eliassen

Study supervision: A.H. Eliassen

This study was supported by Infrastructure Grant UM1 CA176726 and Research Grants CA67262 (to S.E. Hankinson) and CA50385 from the National Cancer Institute and the Intramural Research Program of the Division of Cancer Epidemiology and Genetics of the National Cancer Institute, and with federal funds of the National Cancer Institute awarded under Contract HHSN261200800001E to SAIC-Frederick. J.S. Sisti was funded by R25 CA098566 and T32 CA900137.

1.
Ganmaa
D
,
Willett
WC
,
Li
TY
,
Feskanich
D
,
van Dam
RM
,
Lopez-Garcia
E
, et al
Coffee, tea, caffeine and risk of breast cancer: a 22-year follow-up
.
Int J Cancer
2008
;
122
:
2071
6
.
2.
Li
J
,
Seibold
P
,
Chang-Claude
J
,
Flesch-Janys
D
,
Liu
J
,
Czene
K
, et al
Coffee consumption modifies risk of estrogen-receptor negative breast cancer
.
Breast Cancer Res
2011
;
13
:
R49
.
3.
Boggs
DA
,
Palmer
JR
,
Stampfer
MJ
,
Spiegelman
D
,
Adams-Campbell
LL
,
Rosenberg
L
. 
Tea and coffee intake in relation to risk of breast cancer in the Black Women's Health Study
.
Cancer Causes Control
2010
;
21
:
1941
8
.
4.
Gierach
GL
,
Freedman
ND
,
Andaya
A
,
Hollenbeck
AR
,
Park
Y
,
Schatzkin
A
, et al
Coffee intake and breast cancer risk in the NIH-AARP diet and health study cohort
.
Int J Cancer
2012
;
131
:
452
60
.
5.
Ishitani
K
,
Lin
J
,
Manson
JE
,
Buring
JE
,
Zhang
SM
. 
Caffeine consumption and the risk of breast cancer in a large prospective cohort of women
.
Arch Intern Med
2008
;
168
:
2022
31
.
6.
Larsson
SC
,
Bergkvist
L
,
Wolk
A
. 
Coffee and black tea consumption and risk of breast cancer by estrogen and progesterone receptor status in a Swedish cohort
.
Cancer Causes Control
2009
;
20
:
2039
44
.
7.
Tang
N
,
Zhou
B
,
Wang
B
,
Yu
R
. 
Coffee consumption and risk of breast cancer: a metaanalysis
.
Am J Obstet Gynecol
2009
;
200
:
290
.
e1–9
.
8.
Jiang
W
,
Wu
Y
,
Jiang
X
. 
Coffee and caffeine intake and breast cancer risk: an updated dose-response meta-analysis of 37 published studies
.
Gynecol Oncol
2013
;
129
:
620
9
.
9.
Buck
K
,
Zaineddin
AK
,
Vrieling
A
,
Linseisen
J
,
Chang-Claude
J
. 
Meta-analyses of lignans and enterolignans in relation to breast cancer risk
.
Am J Clin Nutr
2010
;
92
:
141
53
.
10.
Mense
SM
,
Hei
TK
,
Ganju
RK
,
Bhat
HK
. 
Phytoestrogens and breast cancer prevention: possible mechanisms of action
.
Environ Health Perspect
2008
;
116
:
426
33
.
11.
Lee
AJ
,
Cai
MX
,
Thomas
PE
,
Conney
AH
,
Zhu
BT
. 
Characterization of the oxidative metabolites of 17beta-estradiol and estrone formed by 15 selectively expressed human cytochrome p450 isoforms
.
Endocrinology
2003
;
144
:
3382
98
.
12.
Butler
MA
,
Iwasaki
M
,
Guengerich
FP
,
Kadlubar
FF
. 
Human cytochrome P-450PA (P-450IA2), the phenacetin O-deethylase, is primarily responsible for the hepatic 3-demethylation of caffeine and N-oxidation of carcinogenic arylamines
.
Proc Natl Acad Sci U S A
1989
;
86
:
7696
700
.
13.
Yue
W
,
Yager
JD
,
Wang
J-P
,
Jupe
ER
,
Santen
RJ
. 
Estrogen receptor-dependent and independent mechanisms of breast cancer carcinogenesis
.
Steroids
2013
;
78
:
161
70
.
14.
Cavalieri
E
,
Frenkel
K
,
Liehr
JG
,
Rogan
E
,
Roy
D
. 
Estrogens as endogenous genotoxic agents–DNA adducts and mutations
.
J Natl Cancer Inst Monographs
2000
:
75
93
.
15.
Lippert
C
,
Seeger
H
,
Mueck
AO
. 
The effect of endogenous estradiol metabolites on the proliferation of human breast cancer cells
.
Life Sci
2003
;
72
:
877
83
.
16.
Telang
NT
,
Suto
A
,
Wong
GY
,
Osborne
MP
,
Bradlow
HL
. 
Induction by estrogen metabolite 16 alpha-hydroxyestrone of genotoxic damage and aberrant proliferation in mouse mammary epithelial cells
.
J Natl Cancer Inst
1992
;
84
:
634
8
.
17.
Eliassen
AH
,
Spiegelman
D
,
Xu
X
,
Keefer
LK
,
Veenstra
TD
,
Barbieri
RL
, et al
Urinary estrogens and estrogen metabolites and subsequent risk of breast cancer among premenopausal women
.
Cancer Res
2012
;
72
:
696
706
.
18.
Bågeman
E
,
Ingvar
C
,
Rose
C
,
Jernström
H
. 
Coffee consumption and CYP1A2*1F genotype modify age at breast cancer diagnosis and estrogen receptor status
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
895
901
.
19.
Kotsopoulos
J
,
Ghadirian
P
,
El-Sohemy
A
,
Lynch
HT
,
Snyder
C
,
Daly
M
, et al
The CYP1A2 genotype modifies the association between coffee consumption and breast cancer risk among BRCA1 mutation carriers
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
912
6
.
20.
Kotsopoulos
J
,
Eliassen
AH
,
Missmer
SA
,
Hankinson
SE
,
Tworoger
SS
. 
Relationship between caffeine intake and plasma sex hormone concentrations in premenopausal and postmenopausal women
.
Cancer
2009
;
115
:
2765
74
.
21.
Jernström
H
,
Klug
TL
,
Sepkovic
DW
,
Bradlow
HL
,
Narod
SA
. 
Predictors of the plasma ratio of 2-hydroxyestrone to 16alpha-hydroxyestrone among pre-menopausal, nulliparous women from four ethnic groups
.
Carcinogenesis
2003
;
24
:
991
1005
.
22.
Eliassen
AH
,
Ziegler
RG
,
Rosner
B
,
Veenstra
TD
,
Roman
JM
,
Xu
X
, et al
Reproducibility of fifteen urinary estrogens and estrogen metabolites over a 2- to 3-year period in premenopausal women
.
Cancer Epidemiol Biomarkers Prev
2009
;
18
:
2860
8
.
23.
Willett
WC
. 
Nutritional epidemiology
.
New York
:
Oxford University Press
; 
1998
.
24.
Missmer
SA
,
Spiegelman
D
,
Bertone-Johnson
ER
,
Barbieri
RL
,
Pollak
MN
,
Hankinson
SE
. 
Reproducibility of plasma steroid hormones, prolactin, and insulin-like growth factor levels among premenopausal women over a 2- to 3-year period
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
972
8
.
25.
Fortner
RT
,
Eliassen
AH
,
Spiegelman
D
,
Willett
WC
,
Barbieri
RL
,
Hankinson
SE
. 
Premenopausal endogenous steroid hormones and breast cancer risk: results from the Nurses' Health Study II
.
Breast Cancer Res
2013
;
15
:
R19
.
26.
Xu
X
,
Veenstra
TD
,
Fox
SD
,
Roman
JM
,
Issaq
HJ
,
Falk
R
, et al
Measuring fifteen endogenous estrogens simultaneously in human urine by high-performance liquid chromatography-mass spectrometry
.
Anal Chem
2005
;
77
:
6646
54
.
27.
Falk
RT
,
Xu
X
,
Keefer
L
,
Veenstra
TD
,
Ziegler
RG
. 
A liquid chromatography-mass spectrometry method for the simultaneous measurement of 15 urinary estrogens and estrogen metabolites: assay reproducibility and interindividual variability
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
3411
8
.
28.
Rosner
B
. 
Percentage points for a generalized ESD many-outlier procedure
.
Technometrics
1983
;
25
:
165
72
.
29.
Bradlow
HL
,
Jernström
H
,
Sepkovic
DW
,
Klug
TL
,
Narod
SA
. 
Comparison of plasma and urinary levels of 2-hydroxyestrogen and 16 alpha-hydroxyestrogen metabolites
.
Mol Genet Metab
2006
;
87
:
135
46
.
30.
Sowers
MR
,
Crawford
S
,
McConnell
DS
,
Randolph
JF
 Jr
,
Gold
EB
,
Wilkin
MK
, et al
Selected diet and lifestyle factors are associated with estrogen metabolites in a multiracial/ethnic population of women
.
J Nutr
2006
;
136
:
1588
95
.
31.
Tantcheva-Poór
I
,
Zaigler
M
,
Rietbrock
S
,
Fuhr
U
. 
Estimation of cytochrome P-450 CYP1A2 activity in 863 healthy Caucasians using a saliva-based caffeine test
.
Pharmacogenetics
1999
;
9
:
131
44
.
32.
Djordjevic
N
,
Ghotbi
R
,
Bertilsson
L
,
Jankovic
S
,
Aklillu
E
. 
Induction of CYP1A2 by heavy coffee consumption in Serbs and Swedes
.
Eur J Clin Pharmacol
2008
;
64
:
381
5
.
33.
Vakharia
DD
,
Liu
N
,
Pause
R
,
Fasco
M
,
Bessette
E
,
Zhang
QY
, et al
Effect of metals on polycyclic aromatic hydrocarbon induction of CYP1A1 and CYP1A2 in human hepatocyte cultures
.
Toxicol Appl Pharmacol
2001
;
170
:
93
103
.
34.
Zhu
BT
,
Wang
P
,
Nagai
M
,
Wen
Y
,
Bai
H-W
. 
Inhibition of human catechol-O-methyltransferase (COMT)-mediated O-methylation of catechol estrogens by major polyphenolic components present in coffee
.
J Steroid Biochem Mol Biol
2009
;
113
:
65
74
.
35.
Alves
RC
,
Costa
ASG
,
Jerez
M
,
Casal
S
,
Sineiro
J
,
Núñez
MJ
, et al
Antiradical activity, phenolics profile, and hydroxymethylfurfural in espresso coffee: influence of technological factors
.
J Agric Food Chem
2010
;
58
:
12221
9
.
36.
Farah
A
,
de Paulis
T
,
Moreira
DP
,
Trugo
LC
,
Martin
PR
. 
Chlorogenic acids and lactones in regular and water-decaffeinated arabica coffees
.
J Agric Food Chem
2006
;
54
:
374
81
.
37.
Seeger
H
,
Wallwiener
D
,
Kraemer
E
,
Mueck
AO
. 
Comparison of possible carcinogenic estradiol metabolites: effects on proliferation, apoptosis and metastasis of human breast cancer cells
.
Maturitas
2006
;
54
:
72
7
.
38.
Bradlow
HL
,
Hershcopf
RJ
,
Martucci
CP
,
Fishman
J
. 
Estradiol 16 alpha-hydroxylation in the mouse correlates with mammary tumor incidence and presence of murine mammary tumor virus: a possible model for the hormonal etiology of breast cancer in humans
.
Proc Natl Acad Sci U S A
1985
;
82
:
6295
9
.
39.
Zhu
BT
,
Conney
AH
. 
Functional role of estrogen metabolism in target cells: review and perspectives
.
Carcinogenesis
1998
;
19
:
1
27
.
40.
Liu
Z-J
,
Zhu
BT
. 
Concentration-dependent mitogenic and antiproliferative actions of 2-methoxyestradiol in estrogen receptor-positive human breast cancer cells
.
J Steroid Biochem Mol Biol
2004
;
88
:
265
75
.
41.
Gu
F
,
Caporaso
NE
,
Schairer
C
,
Fortner
RT
,
Xu
X
,
Hankinson
SE
, et al
Urinary concentrations of estrogens and estrogen metabolites and smoking in caucasian women
.
Cancer Epidemiol Biomarkers Prev
2013
;
22
:
58
68
.
42.
Schliep
KC
,
Schisterman
EF
,
Mumford
SL
,
Perkins
NJ
,
Ye
A
,
Pollack
AZ
, et al
Validation of different instruments for caffeine measurement among premenopausal women in the BioCycle study
.
Am J Epidemiol
2013
;
177
:
690
9
.
43.
Bhupathiraju
SN
,
Pan
A
,
Malik
VS
,
Manson
JE
,
Willett
WC
,
van Dam
RM
, et al
Caffeinated and caffeine-free beverages and risk of type 2 diabetes
.
Am J Clin Nutr
2013
;
97
:
155
66
.
44.
Ascherio
A
,
Zhang
SM
,
Hernán
MA
,
Kawachi
I
,
Colditz
GA
,
Speizer
FE
, et al
Prospective study of caffeine consumption and risk of Parkinson's disease in men and women
.
Ann Neurol
2001
;
50
:
56
63
.