Risk of uterine leiomyomata in relation to tobacco, alcohol and caffeine consumption in the Black Women's Health Study

Lauren A. Wise1,2,7, Julie R. Palmer2, Bernard L. Harlow1,3, Donna Spiegelman1,4, Elizabeth A. Stewart5, Lucile L. Adams-Campbell6 and Lynn Rosenberg2

Departments of 1 Epidemiology and 4 Biostatistics, Harvard School of Public Health, Boston, MA 02115, 2 Slone Epidemiology Center, Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, 3 Obstetrics and Gynecology Epidemiology Center and 5 Center for Uterine Fibroids, Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 and 6 Cancer Prevention, Control, and Population Sciences, Howard University Cancer Center, Washington, DC 20060, USA

7 To whom correspondence should be addressed at: Slone Epidemiology Center, Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, USA. Email: lwise{at}hsph.harvard.edu


    Abstract
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
BACKGROUND: Tobacco, alcohol and caffeine consumption may influence risk of uterine leiomyomata via changes in ovarian function or hormone metabolism. METHODS: We prospectively assessed the relation of these exposures to risk of self-reported uterine leiomyomata in the Black Women's Health Study. From 1997 to 2001, we followed 21 885 premenopausal women with intact uteri and no prior myoma diagnosis. Cox regression models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs). RESULTS: During 73 426 person-years of follow-up, 2177 incident cases of uterine leiomyomata confirmed by ultrasound (n=1920) or hysterectomy (n=257) were reported. Cigarette smoking was not associated with risk of uterine leiomyomata. Risk was positively associated with years of alcohol consumption and current consumption of alcohol, particularly beer. Relative to non-drinkers, multivariate IRRs for beer consumption of <1, 1–6 and 7+ drinks/week were 1.11 (95% CI 0.98–1.27), 1.18 (95% CI 1.00–1.40) and 1.57 (95% CI 1.17–2.11), respectively. Heavy coffee and caffeine consumption were not associated with risk overall, but IRRs were increased among women aged <35 years. CONCLUSIONS: In US black women, risk of uterine leiomyomata was positively associated with current consumption of alcohol, particularly beer. Cigarette smoking and caffeine consumption were unrelated to risk overall.

Key words: African–Americans/female/premenopausal/risk factors/uterine neoplasms


    Introduction
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
Uterine leiomyomata (fibroids) are the most common tumours of the female reproductive tract and the leading indication for hysterectomy among US women (Farquhar and Steiner, 2002Go). Black women are more likely than white women to be diagnosed with uterine leiomyomata (Brett et al., 1997Go; Marshall et al., 1997Go; Baird et al., 2003Go), develop them at earlier ages (Baird et al., 2003Go), and have more numerous and symptomatic tumours at the time of diagnosis (Kjerulff et al., 1996Go). The observation that uterine leiomyomatas develop during the reproductive years and regress after menopause suggests that ovarian hormones play a critical role in their aetiology.

Tobacco, alcohol and caffeine consumption are modifiable risk factors that may affect endogenous levels of hormones via changes in ovarian function or alterations in hormone metabolism. Smoking is associated with lower serum and urinary estrogen levels in some (MacMahon et al., 1982Go; Westhoff et al., 1996Go), but not all (Longcope and Johnston, 1988Go; Zumoff et al., 1990Go; Daniel et al., 1992Go), studies. Alcohol consumption is associated with higher endogenous levels of estradiol (E2) and estrone (Katsouyami et al., 1991Go; Reichman et al., 1993Go; Hankinson et al., 1995Go), but other studies show no such associations (Cauley et al., 1989Go; London et al., 1991Go; Dorgan et al., 1994Go; Newcomb et al., 1995Go). Coffee and caffeine consumption are associated with increased levels of early follicular phase E2, independent of alcohol or tobacco use (Lucero et al., 2001Go), and may enhance sex steroid production (Leonard et al., 1987Go).

Many epidemiological studies have shown an inverse relationship between current cigarette smoking and risk of uterine leiomyomata (Ross et al., 1986Go; Romieu et al., 1991Go; Lumbiganon et al., 1996Go; Parazzini et al., 1996Go; Faerstein et al., 2001Go), but no association was found in the Nurses' Health Study II (Marshall et al., 1998Go), a US prospective cohort study. The latter study found a positive association for current alcohol consumption (Marshall et al., 1997Go). A case–control study of Italian women (Chiaffarino et al., 1999Go) found no association with alcohol, tea or coffee consumption. Since previous study populations comprised mostly white women (Schwartz and Marshall, 2000Go), little is known about the impact of these factors in black women. With evidence that premenopausal black women have higher ovarian hormone levels than white women (Woods et al., 1996Go; Haiman et al., 2002Go), risk factors for uterine leiomyomata may differ by race. The present study prospectively examines the association of tobacco, alcohol and caffeine consumption with risk of uterine leiomyomata in a large cohort of premenopausal US black women. Results on reproductive and hormonal risk factors for uterine leiomyomata in this cohort have been published previously (Wise et al., 2004Go).


    Patients and methods
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
Study population
The Black Women's Health Study (BWHS) is an ongoing prospective cohort study, established in 1995, when ~59 000 US black women aged 21–69 years were enrolled through questionnaires mailed mainly to subscribers of Essence magazine (Rosenberg et al., 1995Go). The baseline questionnaire elicited information on demographic and behavioural characteristics, reproductive history, health-care utilization, and medical conditions. The cohort is followed every 2 years by postal questionnaire and >80% of the original cohort completed a questionnaire in each follow-up cycle.

Follow-up for the present analysis began in 1997, the start of the second questionnaire cycle, because data on method of confirmation for uterine leiomyomata were first obtained in 1999. Of the 53 322 women who completed the 1997 questionnaire, we restricted the sample to premenopausal women with intact uteri (n=36 618) and excluded women who reported a diagnosis of leiomyomata before 1997 (n=10 455), women who did not complete any follow-up questionnaires in 1999 or 2001 (n=2193), ‘cases’ who provided no information about year of diagnosis (n=99) or confirmation type (n=208), and women with incomplete data on smoking, alcohol or caffeine (n=1015). After these exclusions, 21 885 women remained and were followed for incidence of leiomyomata in the subsequent 4 years.

Assessment of outcome
Because studies limited to histologically confirmed cases of uterine leiomyomata may spuriously identify risk factors associated with large tumour size, symptoms or treatment preference (Schwartz et al., 2000Go), our outcome definition included confirmation by ultrasound or hysterectomy. This is the same definition as employed by the Nurses' Health Study II, a prospective study with similar methodology to the BWHS (Marshall et al., 1997Go). Ultrasound has high sensitivity (99%) and specificity (91%) relative to histological evidence (Loutradis et al., 1990Go; Dueholm et al., 2002Go).

On the 1999 and 2001 follow-up questionnaires, women were asked if they had been diagnosed with ‘fibroids’ in the previous 2-year interval and, if ‘yes’, the calendar year in which they were first diagnosed and whether their diagnosis was confirmed by ‘pelvic exam’ and/or by ‘ultrasound/hysterectomy’. A diagnosis was considered ‘hysterectomy-confirmed’ if the woman reported hysterectomy on the same questionnaire.

Incident cases were defined as women who self-reported a first diagnosis of ‘fibroids’ confirmed by ultrasound or hysterectomy. Women with diagnoses confirmed only by pelvic exam (n=394) were treated as non-cases in primary analyses, because their diagnoses may have represented other pathology (Loutradis et al., 1990Go). Since their diagnosis may have influenced a change in lifestyle factors, their exposure information was not updated beyond the time of diagnosis.

We assessed the accuracy of self-reported uterine leiomyomata in a random sample of 248 ultrasound- or hysterectomy-confirmed cases. These women were mailed supplemental questionnaires regarding their method of confirmation, symptoms and treatment, and were asked for permission to review their medical records. We obtained medical records for 123 of the 128 women who gave us permission and confirmed the self-report in 118 (96%). The proportion of cases reporting on the supplemental questionnaire the presence of symptoms at the time of diagnosis (71%) was similar among those who did (n=128) and did not (n=50) release their medical record (73% versus 60%).

Assesment of exposures and covariates
Data on smoking history were first obtained in 1995 and were updated in 1997 and 1999. Ever-smokers were asked about the age at which they started to smoke regularly, the number of cigarettes they smoked and the cumulative number of years they had smoked. Former smokers were asked how many years ago they quit. Current exposure to environmental tobacco smoke was measured in 1997 and was defined as being ‘in the same room with a smoker for at least 1 h a day for 12 consecutive months or more, at home or in the workplace’.

Alcohol intake was derived mainly from the 1995 questionnaire, because this was the only questionnaire on which we asked about type of alcoholic beverage. Current drinkers were asked to report the average frequency of beer [12 oz (360 ml) can or bottle], wine [4 oz (120 ml) glass] and liquor [1 oz (30 ml) shot] consumption during the previous year. We computed the average daily intake of each beverage by multiplying the frequency of consumption by the alcoholic content in the specified portion size; per drink, beer contains 12.8 g of alcohol, wine 11.0 g and liquor 14.0 g (Department of Agriculture, 1982Go). Total alcohol intake was the sum of values for all three beverages. In 1997 and 1999, participants were asked about frequency of alcohol consumption.

The 1995 questionnaire included a 68-item Block NCI food frequency questionnaire to assess the consumption of specified foods during the previous year, including caffeinated items (coffee, decaffeinated coffee, tea, soft drinks and chocolate candy), with frequencies ranging from ‘never or <1 per month’ to ‘6+ per day’, and portion sizes of ‘small’, ‘medium’ [8 oz (250 ml) for coffee or tea, 12 oz (360 ml) for soft drinks and 1 oz (31 ml) for chocolate candy] or ‘large’ (Block et al., 1986Go). This questionnaire was validated in 408 cohort members against three non-consecutive 24-h recalls and a 3-day food diary (Kumanyika et al., 2003Go). We calculated a summary caffeine score for each subject based on estimates that there are 137 mg per cup of coffee, 47 mg per cup of tea, 46 mg per 12 oz soft drink, 7 mg per serving of chocolate candy and 5 mg per cup of decaffeinated coffee (Willett et al., 1987Go). These quantities were then multiplied by portion size.

Age at menarche and education were ascertained on the baseline survey. Data on parity, age at each birth, oral contraceptive (OC) use and body mass index (BMI) were obtained on the baseline and follow-up surveys, and were treated as time-dependent variables in the analysis, as was smoking.

Data analysis
Each participant contributed person-time from March 1997 until the diagnosis of uterine leiomyomata, menopause, death, loss to follow-up or end of follow-up (March 2001), whichever came first. Analyses were carried out using SAS statistical software (SAS Institute, 2002Go). We used multivariate Cox regression to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for tobacco, alcohol and caffeine consumption (Cox and Oakes, 1984Go). To control for age, calendar time and any two-way interactions between these two time scales, we stratified our analyses jointly by age in 1-year intervals at the start of follow-up and calendar year of the questionnaire cycle (Hertzmark and Spiegelman, 2001Go). The Anderson–Gill data structure was used to update time-varying covariates (Therneau, 1997Go) and exact methods were used to handle tied event times (Kalbfleisch and Prentice, 1980Go).

A covariate was included in multivariate analyses if the literature supported its role as a risk factor or if adding it to a model containing all other predictors of uterine leiomyomata changed the IRR by 10% or more (Greenland, 1989Go). Based on these criteria, we adjusted for age at menarche, parity, age at first birth, years since last birth, OC use, education and BMI, and mutually adjusted for smoking, alcohol and caffeine.

Departures from the proportional hazards assumption (i.e. effect modification by age and time) were tested by the likelihood ratio test comparing models with and without cross-product terms for exposures (in their categorical form) with age (<35 versus 35 + years) and time period (1997–1999 versus 1999–2001). In addition, we conducted stratified analyses and computed likelihood ratio tests to evaluate effect modification by education, BMI, parity and OC use, risk factors by which BWHS participants may differ from the general population of black women. Finally, we used Robins' methods of ‘inverse probability of censoring weighting’ (Robins et al., 2000Go) to evaluate the impact of differential loss to follow-up. This method constructs a regression model that weights women who were not lost to follow-up more heavily to account for those who were, given the same exposure and covariate history.


    Results
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
At the start of follow-up, the prevalence of current and former smoking in the cohort was 14% and 13%, respectively (Table I). Relative to never smokers, current smokers consumed more alcohol and caffeine, and were older, less educated and less likely to report a recent Pap smear. Current alcohol drinkers (25%) were older than never drinkers, and were more likely to smoke, consume caffeine and have greater energy intake. Median caffeine consumption was 64 mg/day, equivalent to half a cup of caffeinated coffee (data not shown). Heavy consumers of caffeine [500 + mg/day (5%)] were older than light consumers, and were more likely to smoke, consume alcohol, be less educated, and have higher BMI and energy intake.


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Table I. Characteristics of 21 885 women according to tobacco, alcohol and caffeine consumption at the start of follow-up: the Black Women's Health Study, 1997a

 
During 73 426 person-years of follow-up, 2177 new cases of uterine leiomyomata confirmed by ultrasound (n=1920) or hysterectomy (n=257) were reported. There was little evidence of an association between smoking and uterine leiomyomata (Table II). The IRR was slightly reduced for current smokers, but there was no trend across pack-years of smoking, number of cigarettes smoked per day, years of smoking or age first smoked. None of the IRRs varied appreciably by age or by exposure to environmental tobacco smoke (data not shown). To assess differences according to method of confirmation, we repeated our analyses among hysterectomy-confirmed cases only. In this case group, the IRR was 0.65 (95% CI 0.46–0.94) for former smoking and 0.92 (95% CI 0.66–1.29) for current smoking. Results for all other smoking variables were similar to those presented in Table II (data not shown).


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Table II. Risk of ultrasound- or hysterectomy-confirmed uterine leiomyomata in relation to cigarette smoking: the Black Women's Health Study, 1997–2001

 
There was a small positive association between current alcohol consumption and uterine leiomyomata (Table III). Among ever drinkers, risk was positively associated with years of alcohol consumption. In models that controlled for other sources of alcohol, the IRR increased monotonically with increasing current consumption of beer, but not wine or liquor. The elevated risk among beer drinkers remained when the alcohol variables were assessed in their continuous form: for each additional beer consumed per week, holding other sources of alcohol constant, the multivariate IRR was 1.02 (95% CI 1.01–1.04). The association for beer differed significantly from liquor (P=0.02), but not wine (P=0.10) (data not shown). Additional control for variables that distinguished beer drinkers from other drinkers—e.g. occupation and marital status—did not alter these findings. Results were not notably different when we stratified by age, when we repeated analyses among hysterectomy-confirmed cases only, when we updated status or frequency of consumption in 1997 and 1999, or when we used a cumulative average measure for alcohol consumption (data not shown).


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Table III. Risk of ultrasound- or hysterectomy-confirmed uterine leiomyomata in relation to alcohol consumption in 1995: the Black Women's Health Study, 1997–2001

 
No association was detected for coffee or caffeine consumption overall (Table IV). Since the caffeine data indicated a departure from the proportional hazards assumption, we presented these data within strata of age. The IRRs were significantly elevated in the highest category of coffee and caffeine consumption among women <35 years of age, but there was no evidence of a monotonic dose–response relation for either of these measures. When analyses were confined to hysterectomy-confirmed cases only, findings remained similar overall; small numbers of cases precluded us from assessing differences according to age.


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Table IV. Risk of ultrasound- or hysterectomy-confirmed uterine leiomyomata in relation to caffeine consumption in 1995, according to age at start of questionnaire cycle: the Black Women's Health Study, 1997–2001

 
Effect modification was not observed by BMI, education, parity or OC use on any of the associations of interest, nor was there any evidence that smoking modified the IRRs for alcohol or caffeine consumption. Because current smokers, alcohol drinkers and heavy consumers of caffeine were less likely to report a recent Pap smear (Table I), a marker of pelvic exam, we restricted analyses to the 90% of women who reported this practice in the prior 2 years. None of the results changed materially. Results were also unchanged when cases confirmed by pelvic examination only (n=394) were included as part of the outcome definition, censored at the time of diagnosis or excluded from the analysis.


    Discussion
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
The BWHS is the first prospective cohort study to examine risk factors for uterine leiomyomata in a large population of US black women. Although uterine leiomyomata represent a major public health problem among black women of reproductive age, most epidemiological studies have been conducted in white women. In the BWHS, risk was positively associated with current consumption of alcohol, particularly beer. Cigarette smoking and caffeine consumption were unrelated to risk overall.

While some studies show an association between smoking and lower endogenous estrogen levels (MacMahon et al., 1982Go; Westhoff et al., 1996Go), others show no such association (Longcope and Johnston, 1988Go; Zumoff et al., 1990Go; Daniel et al., 1992Go). Tobacco components may inhibit aromatase, an enzyme that synthesizes estrogen in granulosa cells (Barbieri et al., 1986Go), or shift E2 metabolism toward 2-hydroxylation pathways, thereby decreasing estrogen bioavailability (Michnovicz et al., 1986Go; Bradlow, 1994Go).

In the epidemiological studies that show an inverse association between current smoking and uterine leiomyomata, decreases in risk range from 20% to 50% (Ross et al., 1986Go; Romieu et al., 1991Go; Lumbiganon et al., 1996Go; Parazzini et al., 1996Go; Faerstein et al., 2001Go). The null association for cigarette smoking in the BWHS is consistent with the Nurses' Health Study II (Marshall et al., 1998Go). The counteracting effects of tobacco smoke components could explain the lack of association. While smoking may have an anti-estrogen effect on the endogenous hormonal milieu (MacMahon et al., 1982Go; Westhoff et al., 1996Go), components of cigarette smoke (e.g. dioxin) may also exert estrogen-related effects on the uterus that could promote cell proliferation (Ohtake et al., 2003Go).

High levels of estrogens, prolactin and insulin-like growth factor (IGF) may promote growth of uterine leiomyomata (Mora et al., 1995Go; Andersen, 1996Go). Several studies have shown associations between alcohol intake and high levels of plasma or urinary E2 (Katsouyami et al., 1991Go; Reichman et al., 1993Go; Hankinson et al., 1995Go), estrone, androstenedione, IGF-I and prolactin (Soyka et al., 1991Go; Singletary and Gapstur, 2001Go), as well as lower levels of FSH (Singletary and Gapstur, 2001Go), while others have shown no such associations (Cauley et al., 1989Go; London et al., 1991Go; Dorgan et al., 1994Go; Newcomb et al., 1995Go).

In the present study, risk of uterine leiomyomata was positively associated with years of alcohol consumption and current consumption of alcohol, particularly beer. The BWHS is the first study to examine risk in relation to type of alcoholic beverage. The Nurses' Health Study II also found a positive association for current alcohol consumption, but did not report effect estimates (Marshall et al., 1997Go), while an Italian case–control study found no association (Chiaffarino et al., 1999Go). In the latter study, subjects were interviewed after the diagnosis of uterine leiomyomata, and no data on portion size were elicited.

In the BWHS, there appeared to be a stronger association for beer consumption than for wine or liquor consumption. This finding requires confirmation by future studies. It is possible that beer exerts a different effect than other types of alcohol on hormone-dependent neoplasms. In the Italian case–control study, wine accounted for >90% of the alcohol consumed (Chiaffarino et al., 1999Go), which could explain the lack of association between alcohol and uterine leiomyomata in that study. A meta-analysis of cohort studies showed that beer drinkers have the largest relative risk of breast cancer, although the beverage-specific risks were not significantly different (Smith-Warner et al., 1998Go). Moreover, a recent study showed that the phytoestrogen in beer, 8-prenylnarigenin, stimulates the growth of MCF-7/6 breast cancer cell lines in vitro, and may mimic the effects of 17{beta}-E2 (Rong et al., 2001Go).

Few studies have examined the effect of caffeine on ovarian hormones. In a cross-sectional study, coffee and total caffeine consumption were associated with increased levels of early follicular phase E2, independent of alcohol or tobacco use (Lucero et al., 2001Go). By inhibiting phosphodiesterase, caffeine may decrease clearance of cAMP and enhance steroid production (Leonard et al., 1987Go). Moreover, in high doses, caffeine can induce stress-like effects in the pituitary–adrenal axis (Spiller, 1998Go), which could raise risk of uterine leiomyomata via increased secretion of prolactin (Reichlin, 1988Go; Mora et al., 1995Go; Andersen, 1996Go).

The one previous study to examine caffeine consumption as a risk factor for uterine leiomyomata was a case–control study, and no association was found (Chiaffarino et al., 1999Go). In the BWHS, no overall association was observed for coffee or caffeine consumption, but an increased risk was found for heavy consumption in younger women. This latter finding should be interpreted with caution, because there is no evidence that caffeine metabolism differs by age in humans (Arnaud, 1993Go). It is also possible that unmeasured factors related both to heavy consumption of caffeine and risk of leiomyomata confounded the results, or that reverse causality played a role (e.g. subclinical cases could have experienced anemia and fatigue, leading to heavy caffeine consumption). There was no evidence that differential screening by age and caffeine consumption accounted for the observed effect modification. Pap smear screening levels were similar for both younger (88%) and older (85%) heavy caffeine consumers, and within age groups, the heavy consumers were consistently less likely than the light consumers to report a recent Pap smear.

BWHS participants were not systematically screened for uterine leiomyomata. Owing to the high cumulative incidence of these tumours and their tendency to be asymptomatic (Baird et al., 2003Go), true cases may have been misclassified as non-cases. If misclassification was unrelated to tobacco, alcohol or caffeine consumption, the IRRs would have been biased towards the null, unless there was perfect specificity, in which case the IRR would be unbiased (Greenland, 1998Go). Since we were able to confirm 96% of self-reported cases in the BWHS validation study, specificity of outcome classification was high. In contrast, if exposure status influenced the likelihood of detection, over- or underestimation of the IRR could have occurred. Since restriction of the analytic sample to women with a recent Pap smear yielded similar results, detection bias is unlikely to account for our findings. Moreover, 71% of validation study cases had symptoms prior to their initial diagnosis, suggesting that the proportion of incidentally detected cases was low.

One strength of the present study is that exposure data were collected before the diagnosis and confirmation of uterine leiomyomata, thereby avoiding recall bias. In addition, low loss to follow-up in the BWHS reduced the potential for selection bias. While mean length of follow-up was similar for current and never smokers, current and never alcohol drinkers, and heavy and light caffeine consumers, significant differences existed for educational attainment (40 versus 43 months of follow-up for <13 versus 17 + years of education; P<0.001). As education was inversely associated with smoking and alcohol consumption, and positively associated with risk of uterine leiomyomata, differential loss to follow-up may have produced a downward bias of the IRRs. However, use of Robins' methods (Robins et al., 2000Go) did not change the results appreciably.

Prevalence estimates for smoking and drinking in the BWHS were slightly lower than those documented in nationwide representative studies of black women (US Department of Health and Human Services, 2001Go; Centers for Disease Control, 2002Go). Because we did not find effect modification by any factor, with the exception of age, BWHS findings should be generalizable to other black women.

At present, few modifiable risk factors for uterine leiomyomata have been identified. Observations from the present study regarding smoking and alcohol consumption are consistent with another large US prospective study (Marshall et al., 1998Go). Future studies are needed to evaluate whether the BWHS findings for beer, coffee and caffeine consumption can be replicated. As the associations are modest, and the prevalence of these risk factors low, they are unlikely to explain a large fraction of the disease burden among US black women.


    Acknowledgements
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
The authors gratefully acknowledge the study participants and staff of the Black Women's Health Study. This work was supported by National Cancer Institute grant CA56420.


    References
 Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Acknowledgements
 References
 
Andersen J (1996) Growth factors and cytokines in uterine leiomyomas. Semin Reprod Endocrinol 14, 269–282.[Medline]

Arnaud MJ (1993) Metabolism of caffeine and other components of coffee. In Garattini S (ed.) Caffeine, Coffee and Health. Raven Press, New York, NY, USA, pp. 43–95.

Baird DD, Dunson DB, Hill MC, Cousins D and Schectman JM (2003) High cumulative incidence of uterine leiomyoma in black and white women: ultrasound evidence. Am J Obstet Gynecol 188, 100–107.[CrossRef][Medline]

Barbieri RL, McShane PM and Ryan KJ (1986) Constituents of cigarette smoke inhibit human granulosa cell aromatase. Fertil Steril 46, 232–236.[Medline]

Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J and Gardner L (1986) A data-based approach to diet questionnaire design and testing. Am J Epidemiol 124, 453–469.[Abstract]

Bradlow L (1994) Variations in estrogen metabolism. In Snow R and Hall P (eds) Steroid Contraceptives and Women's Response. Plenum Press, New York, NY, USA, pp. 171–178.

Brett KM, Marsh JV and Madans JH (1997) Epidemiology of hysterectomy in the United States: demographic and reproductive factors in a nationally representative sample. J Womens Health 6, 309–316.[Medline]

Cauley JA, Gutai JP, Kuller LH, LeDonne D and Powell JG (1989) The epidemiology of serum sex hormones in postmenopausal women. Am J Epidemiol 129, 1120–1131.[Abstract]

Centers for Disease Control (2002) Alcohol use among women of childbearing age—United States 1991–1999. MMWR Morb Mortal Wkly Rep 51, 273–276.[Medline]

Chiaffarino F, Parazzini F, La Vecchia C, Chatenoud L, Di Cintio E and Marsico S (1999) Diet and uterine myomas. Obstet Gynecol 94, 395–398.[Abstract/Free Full Text]

Cox DR and Oakes D (1984) Analysis of Survival Data. Chapman Hall, London, UK.

Daniel M, Martin AD and Faiman C (1992) Sex hormones and adipose tissue distribution in premenopausal cigarette smokers. Int J Obes Relat Metab Disord 16, 245–254.[Medline]

Department of Agriculture (1982) Provisional Table on the Nutrient Content of Beverages. In Human Nutrition Information Service. Washington, DC, USA.

Dorgan JF, Reichman ME, Judd JT, Brown C, Longcope C, Schatzkin A, Campbell WS, Franz C, Kahle L and Taylor PR (1994) The relation of reported alcohol ingestion to plasma levels of estrogens and androgens in premenopausal women (Maryland United States). Cancer Causes Control 5, 53–60.[Medline]

Dueholm M, Lundorf E, Hansen ES, Ledertoug S and Olesen F (2002) Accuracy of magnetic resonance imaging and transvaginal ultrasonography in the diagnosis, mapping, and measurement of uterine myomas. Am J Obstet Gynecol 186, 409–415.[CrossRef][Medline]

Faerstein E, Szklo M and Rosenshein N (2001) Risk factors for uterine leiomyoma: a practice-based case-control study. I. African–American heritage, reproductive history, body size, and smoking. Am J Epidemiol 153, 1–10.[Abstract/Free Full Text]

Farquhar CM and Steiner CA (2002) Hysterectomy rates in the United States 1990–1997. Obstet Gynecol 99, 229–234.[Abstract/Free Full Text]

Greenland S (1989) Modeling and variable selection in epidemiologic analysis. Am J Public Health 79, 340–349.[Abstract]

Greenland S (1998) Basic methods for sensitivity analysis and external adjustment. In Rothman K and Greenland S (eds) Modern Epidemiology. Lippincott-Raven, Philadelphia, PA, USA, pp. 350–352.

Haiman CA, Pike MC, Bernstein L, Jaque SV, Stanczyk FZ, Afghani A, Peters RK, Wan P and Shames L (2002) Ethnic differences in ovulatory function in nulliparous women. Br J Cancer 86, 367–371.[CrossRef][Medline]

Hankinson SE, Willett WC, Manson JE, Hunter DJ, Colditz GA, Stampfer MJ, Longcope C and Speizer FE (1995) Alcohol, height, and adiposity in relation to estrogen and prolactin levels in postmenopausal women. J Natl Cancer Inst 87, 1297–1302.[Abstract]

Hertzmark E and Spiegelman D (2001) The SAS MPHREG Macro. Channing Laboratory, Boston, MA, USA.

Kalbfleisch JD and Prentice RL (1980) The Statistical Analysis of Failure Time Data. John Wiley & Sons, Inc., New York, NY, USA.

Katsouyami K, Boyle P and Trichopoulos D (1991) Diet and urine estrogens among postmenopausal women. Oncology 48, 490–494.[Medline]

Kjerulff KH, Langenberg P, Seidman JD, Stolley PD and Guzinski GM (1996) Uterine leiomyomas: racial differences in severity, symptoms, and age at diagnosis. J Reprod Med 41, 483–490.[Medline]

Kumanyika SK, Mauger D, Mitchell DC, Phillips B, Smiciklas-Wright H and Palmer JR (2003) Relative validity of food frequency questionnaire nutrient estimates in the Black Women's Health Study. Ann Epidemiol 13, 111–118.[CrossRef][Medline]

Leonard TK, Watson RR and Mohs ME (1987) The effects of caffeine on various systems: a review. J Am Diet Assoc 87, 1048–1053.[Medline]

London S, Willett W, Longcope C and McKinlay S (1991) Alcohol and other dietary factors in relation to serum hormone concentrations in women at climacteric. Am J Clin Nutrition 53, 166–171.[Abstract]

Longcope C and Johnston CC (1988) Androgen and estrogen dynamics in pre- and postmenopausal women: a comparison between smokers and nonsmokers. J Clin Endocrinol Metab 67, 379–383.[Abstract]

Loutradis D, Antsaklis A, Creatsas G, Hatzakis A, Kanakas N, Gougoulakis A, Michalas S and Aravantinos D (1990) The validity of gynecological ultrasonography. Gynecol Obstet Invest 29, 47–50.[Medline]

Lucero J, Harlow BL, Barbieri RL, Sluss P and Cramer DW (2001) Early follicular phase hormone levels in relation to patterns of alcohol, tobacco, and coffee use. Fertil Steril 76, 723–729.[CrossRef][Medline]

Lumbiganon P, Rugpao S, Phandhu-fung S, Laopaiboon M, Vudhikamraksa N and Werawatakul Y (1996) Protective effect of depot-medroxyprogesterone acetate on surgically treated uterine leiomyomas: a multicentre case–control study. Br J Obstet Gynaecol 103, 909–914.[Medline]

MacMahon B, Trichopoulos D, Cole P and Brown J (1982) Cigarette smoking and urinary estrogens. N Engl J Med 307, 1062–1065.[Medline]

Marshall LM, Spiegelman D, Barbieri RL, Goldman MB, Manson JE, Colditz GA, Willett WC and Hunter DJ (1997) Variation in the incidence of uterine leiomyoma among premenopausal women by age and race. Obstet Gynecol 90, 967–973.[Abstract/Free Full Text]

Marshall LM, Spiegelman D, Manson JE, Goldman MB, Barbieri RL, Stampfer MJ, Willett WC and Hunter DJ (1998) Risk of uterine leiomyomata among premenopausal women in relation to body size and cigarette smoking. Epidemiology 9, 511–517.[Medline]

Michnovicz JJ, Hershcopf RJ, Nagunuma H, Bradlow HL and Fishman J (1986) Increased 2-hydroxylation of estradiol as a possible mechanism for the anti-estrogenic effect of cigarette smoking. N Engl J Med 315, 1305–1309.[Abstract]

Mora S, Diehl T and Stewart EA (1995) Prolactin is an autocrine growth regulator for human myometrial and leiomyoma cells. J Soc Gynecol Invest 2, 396.

Newcomb PA, Klein R, Klein BE, Haffner S, Mares-Perlman J, Cruickshanks KJ and Marcus PM (1995) Association of dietary and life-style factors with sex hormones in postmenopausal women. Epidemiology 6, 318–321.[Medline]

Ohtake F, Takeyama K, Matsumoto T, Kitagawa H, Yamamoto Y, Nohara K, Tohyama C, Krust A, Mimura J, Chambon P et al. (2003) Modulation of oestrogen receptor signalling by association with the activated dioxin receptor. Nature 423, 545–550.[CrossRef][Medline]

Parazzini F, Negri E, La Vecchia C, Rabaiotti M, Luchini L, Villa A and Fedele L (1996) Uterine myomas and smoking. Results from an Italian study. J Reprod Med 41, 316–320.[Medline]

Reichlin S (1988) Prolactin and growth hormone secretion in stress. Adv Exp Med Biol 245, 353–376.[Medline]

Reichman ME, Judd JT, Longcope C, Schatzkin A, Clevidence BA, Nair PP, Campbell WS and Taylor PR (1993) Effects of alcohol consumption on plasma and urinary hormone concentrations in premenopausal women. J Natl Cancer Inst 85, 722–727.[Abstract]

Robins JM, Hernan MA and Brumback B (2000) Marginal structural models and causal inference in epidemiology. Epidemiology 11, 550–560.[CrossRef][Medline]

Romieu I, Walker AM and Jick S (1991) Determinants of uterine fibroids. Post Mark Surveill 5, 119–133.

Rong H, Boterberg T, Maubach J, Stove C, Depypere H, Van Slambrouck S, Serreyn R, De Keukeleire D, Mareel M and Bracke M (2001) 8-Prenylnaringenin, the phytoestrogen in hops and beer, upregulates the function of E-cadherin/catenin complex in human mammary carcinoma cells. Eur J Cell Biol 80, 580–585.[Medline]

Rosenberg L, Adams-Campbell LL and Palmer JR (1995) The Black Women's Health Study: a follow-up study for causes and preventions of illness. J Am Med Womens Assoc 50, 56–58.[Medline]

Ross RK, Pike MC, Vessey MP, Bull D, Yeates D and Casagrande JT (1986) Risk factors for uterine fibroids: reduced risk associated with oral contraceptives. Br Med J Clin Res Ed 293, 359–362.[Medline]

SAS Institute (2002) SAS/STAT User's Guide, version 8.02. SAS Institute, Cary, NC, USA.

Schwartz SM and Marshall LM (2000) Uterine leiomyomata. In Goldman MB and Hatch MC (eds) Women and Health. Academic Press, San Diego, CA, USA, pp. 240–252.

Schwartz SM, Marshall LM and Baird DD (2000) Epidemiologic contributions to understanding the etiology of uterine leiomyomata. Environ Health Perspect 108, 821–827.[Medline]

Singletary KW and Gapstur SM (2001) Alcohol and breast cancer: review of epidemiologic and experimental evidence and potential mechanisms. JAMA 286, 2143–2151.[Abstract/Free Full Text]

Smith-Warner SA, Spiegelman D, Yaun SS, van den Brant PA, Folsom AR, Goldbohm RA, Graham S, Holmberg L, Howe GR, Marshall JR et al. (1998) Alcohol and breast cancer in women: a pooled analysis of cohort studies. JAMA 279, 535–540.[Abstract/Free Full Text]

Soyka M, Gorig E and Naber D (1991) Serum prolactin increase induced by ethanol: a dose-dependent effect not related to stress. Psychoneuroendocrinology 16, 441–446.[CrossRef][Medline]

Spiller GA (1998) Basic metabolism and physiological effects of the methylxanthines. In Spiller GA (ed.) Caffeine. CRC Press, Boca Raton, FL, USA, pp. 225–231.

Therneau TM (1997) Extending the Cox model. In Lin DY and Fleming TR (eds) Proceedings of the First Seattle Symposium in Biostatistics: Survival Analysis. Springer Verlag, New York, pp 51–84.

US Department of Health and Human Services (2001) Women and Smoking: A Report of the Surgeon General, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. US Department of Health and Human Services, Rockville MD.

Westhoff C, Gentile G, Lee J, Zacur H and Helbig D (1996) Predictors of ovarian steroid secretion in reproductive-aged women. Am J Epidemiol 144, 381–388.[Abstract]

Willett W, Reynolds RD, Cottrell-Hoehner S, Sampson L and Browne ML (1987) Validation of a semi-quantitative food frequency questionnaire: comparison with a 1-year diet record. J Am Diet Assoc 87, 43–47.[Medline]

Wise LA, Palmer JR, Harlow BL, Spiegelman D, Stewart EA, Adams-Campbell LL and Rosenberg L (2004) Reproductive factors, hormonal contraception and risk of uterine leiomyomata in African–American women: a prospective study. Am J Epidemiol 159, 113–123.[Abstract/Free Full Text]

Woods MN, Barnett JB, Spiegelman D, Trail N, Hertzmark E, Longcope C and Gorbach SL (1996) Hormone levels during dietary changes in premenopausal African–American women. J Natl Cancer Inst 88, 1369–1374.[Abstract/Free Full Text]

Zumoff B, Miller L, Levitt CD, Miller EH, Kalin M, Denman H, Jandorek R and Rosenfeld RS (1990) The effect of smoking on serum progesterone, estradiol, and luteinizing hormone levels over a menstrual cycle in normal women. Steroids 55, 507–511.[CrossRef][Medline]

Submitted on December 22, 2003; accepted on April 16, 2004.





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