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Uterine leiomyomas, also known as fibroids, are benign tumors of the uterus and the leading cause of hysterectomy in the United States, accounting for $1.2 billion in hospital expenditures annually.1–3 Approximately 1 in 4 women have uterine leiomyomas that come to clinical attention.4 Symptoms vary in severity and include pelvic pain, abnormal menstrual bleeding, and pregnancy complications.5
The etiology of uterine leiomyoma is poorly understood. Sex steroid hormones and growth factors have been hypothesized to play a role.6,7 Since endogenous hormones influence growth during childhood and are associated with excess weight and body shape, anthropometric characteristics may be an outward reflection of the internal hormonal milieu.
In 1998, Marshall et al8 reported on the association between body size and risk of incident uterine leiomyoma in the Nurses Health Study II over 4 years of follow-up. Here, we present a more detailed, extended analysis of this cohort including 12 years of follow up, with more than twice the number of incident cases of uterine leiomyoma previously reported and an evaluation of body size during childhood.
In 1989, 116,609 female registered nurses age 25 to 42 years and living in 1 of 14 US states responded to a baseline questionnaire about their medical histories and lifestyles. Women who reported cancer at enrollment (not including nonmelanoma skin cancer) were excluded. Follow-up questionnaires have been sent biennially to update information on risk factors and medical events. Follow-up for this cohort exceeds 95%. This study was approved by the institutional review boards of Brigham and Women’s Hospital and Harvard School of Public Health (Boston, MA).
Height, current weight, and weight at age 18 were self-reported at baseline (in 1989), and weight was self-reported in each follow-up questionnaire. In 1993, participants were provided with a tape measure and asked to report their waist and hip measurements within a quarter of an inch. The validity of self-reported height (r = 0.94) and weight at age 18 (r = 0.87) has previously been demonstrated in this cohort.9
Body shape throughout childhood and early adulthood (ages 5, 10, 20, 30, 40, and current) was assessed at baseline using a set of body shapes (Fig. 1) originally developed by Stunkard et al10 and shown to be correlated with measured body fatness in several studies (r = 0.36–0.83).11–13 Childhood body fatness was assessed by averaging the shapes reported for ages 5 and 10, and adolescent body fatness was assessed by averaging the shapes reported for ages 10 and 20.
Incidence of uterine leiomyoma was first assessed in 1993. Participants were asked if they had ever had uterine fibroids diagnosed by a physician and, if so, the date of first diagnosis and method of confirmation. A woman was considered a case only if she reported an ultrasound- or hysterectomy-confirmed uterine leiomyoma. Women who reported a fibroid that had not been confirmed by ultrasound or hysterectomy (ie, pelvic examination only) did not contribute person-time to that time period but were allowed to re-enter the analysis if the fibroid was later confirmed. Self-report of uterine leiomyomas was previously validated in a small subset of this cohort.14
Women were excluded if they had died (n = 1), had a uterine leiomyoma at baseline (n = 5284), the date of fibroid diagnosis was unknown (n = 900), had a hysterectomy (n = 4900), were postmenopausal (n = 482) or had history of cancer (n = 692). Each participant contributed follow-up time, measured in months, from the return of the 1989 questionnaire until the first of the following events: report of a uterine leiomyoma, death, hysterectomy, cancer diagnosis, menopause, the return of the 2001 questionnaire, or the last returned questionnaire (if lost to follow-up). Cutpoints for current body mass index (BMI) categories are based on World Health Organization guidelines identifying overweight (≥25.0 kg/m2) and obese (≥30.0 kg/m2) women.15
We used Cox proportional hazards regression models to estimate the association between anthropometric characteristics and uterine leiomyoma while controlling for known and suspected uterine leiomyoma risk factors. In addition, we performed stratified analyses to evaluate whether the association between anthropometric variables and uterine leiomyoma varied between subgroups. We stratified by race, recent breast or pelvic examination, fertility status, and parity. To test for interaction, we used a likelihood ratio test comparing a model with interaction terms and main effects to a model with only main effects. Analyses that included waist-to-hip ratio were restricted to follow-up between 1993 and 2001.
To assess the influence of misclassification of the outcome, we used methods proposed by Duffy et al.16 Briefly, we determined the corrected log hazard ratio (HR) by dividing the log HR by the sum of the positive predictive value, the negative predictive value and negative one. We assumed self-reported uterine leiomyoma had a positive predictive value of 93% based on the validation study performed earlier in this population14 and a negative predictive value of 51% based on the sonographic screening of a randomly selected population with no reported uterine leiomyoma.17
During 999,728 person-years of follow-up, we observed 8446 incident cases of uterine leiomyoma confirmed by ultrasound or hysterectomy. Overall, we observed an increased incidence of uterine leiomyoma with increasing BMI (Table 1). This association was attenuated after adjusting for potential confounders, particularly age at menarche, age at first birth and time since last birth. When we corrected our estimates for misclassification of the outcome, we observed a stronger association between BMI and uterine leiomyoma. Compared with women who had a BMI <20, the corrected HRs for women with BMIs of 20–21.9, 22 to 23.9, 24–24.9, 25–26.9, 27–29.9, ≥30 were 0.83 [95% CI = 0.67–1.01], 1.07 (0.91–1.26), 1.34 (1.09–1.65), 1.35 (1.12–1.62), 1.77 (1.48–2.12), and 1.98 (1.69–2.33), respectively. HRs did not vary substantially from original estimates when uterine leiomyomas diagnosed by pelvic examination were included in the case definition. We observed an even greater risk of uterine leiomyoma for parous women with a BMI of 30 or more (covariate-adjusted HR = 1.41; 1.30–1.54), but a decreased risk for nulliparous women with a BMI of 30 or more (0.88; 0.78–1.01). After age-adjustment, the test for interaction was statistically significant (P value = 0.03); however, when parity-associated variables were added to the model (eg, age at first birth, time since last birth), the test for interaction was no longer significant (P value = 0.62).
Weight change since age 18 was associated with uterine leiomyoma incidence (Table 1). Additional adjustment for BMI at age 18 did not change the association (data not shown). Parity, age at first birth, and time since last birth had the greatest influence on multivariate estimates. We observed a trend in increasing uterine leiomyoma risk with increasing waist-to-hip ratio (P = 0.02) but no association between height and incidence of uterine leiomyoma. We observed no clear associations between BMI at age 18 and uterine leiomyoma risk, and the association remained null when we corrected for misclassification of the outcome; likewise, body fatness during development was not associated with uterine leiomyoma risk (Table 2).
We observed a stronger association for current BMI and weight change with uterine leiomyoma among white women than among African American women (Appendix Table A1, available with the online version of this paper). However, there was no significant interaction by race. Furthermore, we observed no material differences in associations when assessed by fertility status or recent gynecologic examination.
In further analyses, we restricted follow-up from 1993 to 2001, since uterine leiomyoma diagnosed between 1989 and 1993 had been recalled in 1993. We found no appreciable differences in the associations between anthropometric characteristics and incidence of uterine leiomyoma.
Overall, we observed that current BMI, change in weight since age 18, and waist-to-hip ratio were each associated with an increase in uterine leiomyoma risk. However, we observed no association with BMI at age 18, childhood or adolescent body size, or adult height. This pattern suggests that body mass and weight gain in adulthood increases uterine leiomyoma risk, while body mass up to age 18 does not.
Previous studies of BMI and uterine leiomyoma are inconsistent.8,18,19 Some have reported an increased risk of uterine leiomyoma with increasing BMI20,21 while others have reported no association.19,22,23 Study design, method of case identification, or the ethnic makeup of the study population could explain these differences. Our results are generally consistent with those reported by Marshall et al.8 As expected, we were able to generate more precise estimates of these associations due to longer follow-up. Attenuation of the association in the multivariate model suggests the presence of confounding, and, given the small size of the effect, residual or unmeasured confounding could explain the association between BMI and uterine leiomyoma. Ultrasound examination is common during pregnancy and could lead to more frequent detection of subclinical uterine leiomyoma. Although we observed a stronger association among parous women, it was not statistically different from our observations among nulliparous women. Others have shown that high blood pressure is associated with an increased risk of uterine leiomyoma,24,25 which could explain the association between weight and uterine leiomyoma. However, in our analyses the association persisted after adjustment for hypertension and hypertension medications.
Hyperinsulinemia and insulin resistance that result from excess weight decrease hepatic production of the insulin growth factor (IGF) binding proteins; consequently, free IGF levels are elevated.26 Women with a high waist-to-hip ratio are more likely to have hyperinsulinemia and insulin resistance.27 We observed slightly increased uterine leiomyoma risk with increased waist-to-hip ratio, suggesting a role for hyperinsulinemia, insulin resistance, and IGF in uterine leiomyoma development. However, fibroids were not associated with height (which is associated with elevated IGF levels during growth and development28), BMI at age 18, or body size during development, suggesting that elevated IGF before adulthood does not influence uterine leiomyoma risk.
Pattern of association with body size across the lifecourse is a focus of investigation for several disease processes, including breast cancer29 and cardiovascular disease.30 A concentration of effect in adulthood suggests that uterine leiomyoma risk is neither initiated nor promoted as part of gynecologic development and the menarchal axis, but rather is driven by physiologic processes associated with adult body size and weight change.
Our study is limited by the fact that many uterine leiomyomas are asymptomatic. Approximately 50% of women age 35–49 years with no previous history of uterine leiomyoma will have a uterine leiomyoma detected by ultrasound.17 Consequently, spurious associations may be observed between exposures that are associated with medical surveillance and uterine leiomyoma, if increased surveillance leads to the detection of subclinical uterine leiomyoma. Since we observed no difference by fertility status or recent gynecologic examination (which are proxies for medical surveillance), detection bias is unlikely. Furthermore, correction for misclassification resulted in slightly stronger associations. Therefore, variables that appear to have no association with uterine leiomyoma may truly be associated.
With respect to public health significance, uterine leiomyoma that come to clinical attention are the most relevant to study, since these are a source of considerable morbidity. Undetected uterine leiomyomas are more likely to be asymptomatic31; therefore, identification of factors involved in the initiation of uterine leiomyoma development may not be as important. Since our population is predominantly white, we are limited in our ability to evaluate race-specific differences in uterine leiomyoma risk.
Strengths of our study include its large sample size, prospective design, evaluation of childhood body size relations, and updated exposure and covariate information. Our ability to update weight over time is particularly useful since weight at different life stages can have different associations with disease.
In conclusion, our data suggest that excess weight and central adiposity in adulthood are associated with a modest increase in the risk of uterine leiomyoma in premenopausal women. However, anthropometric measures influenced by early life exposures, including height, weight at age 18, and body size during childhood and adolescence, do not influence uterine leiomyoma risk.
We thank the participants of the Nurses’ Health Study II for their ongoing commitment to the study.
1. Zhao SZ, Wong JM, Arguelles LM. Hospitalization costs associated with leiomyoma. Clin Ther
2. Wilcox LS, Koonin LM, Pokras R, et al. Hysterectomy in the United States, 1988–1990. Obstet Gynecol
3. Farquhar CM, Steiner CA. Hysterectomy rates in the United States 1990–1997. Obstet Gynecol
4. Buttram VC Jr, Reiter RC. Uterine leiomyomata: etiology, symptomatology, and management. Fertil Steril
5. Stewart EA. Uterine fibroids. Lancet
6. Rein MS, Barbieri RL, Friedman AJ. Progesterone: a critical role in the pathogenesis of uterine myomas. Am J Obstet Gynecol
7. Flake GP, Andersen J, Dixon D. Etiology and pathogenesis of uterine leiomyomas: a review. Environ Health Perspect
8. Marshall LM, Spiegelman D, Manson JE, et al. Risk of uterine leiomyomata among premenopausal women in relation to body size and cigarette smoking. Epidemiology
9. Troy LM, Hunter DJ, Manson JE, et al. The validity of recalled weight among younger women. Int J Obes Relat Metab Disord
10. Stunkard AJ, Sorensen T, Schulsinger F. Use of the Danish Adoption Register for the study of obesity and thinness. Res Publ Assoc Res Nerv Ment Dis
11. Must A, Willett WC, Dietz WH. Remote recall of childhood height, weight, and body build by elderly subjects. Am J Epidemiol
12. Munoz KA, Ballard-Barbash R, Graubard B, et al. Recall of body weight and body size estimation in women enrolled in the breast cancer detection and demonstration project (BCDDP). Int J Obes Relat Metab Disord
13. Koprowski C, Coates RJ, Bernstein L. Ability of young women to recall past body size and age at menarche. Obes Res
14. Marshall LM, Spiegelman D, Barbieri RL, et al. Variation in the incidence of uterine leiomyoma among premenopausal women by age and race. Obstet Gynecol
15. World Health Organiziation. Obesity. Preventing and managing the global epidemic. Report of a WHO consultation on obesity. Geneva, Switzerland: World Health Organization; 1998.
16. Duffy SW, Warwick J, Williams AR, et al. A simple model for potential use with a misclassified binary outcome in epidemiology. J Epidemiol Community Health
17. Baird DD, Dunson DB, Hill MC, et al. High cumulative incidence of uterine leiomyoma in black and white women: ultrasound evidence. Am J Obstet Gynecol
18. Ross RK, Pike MC, Vessey MP, et al. Risk factors for uterine fibroids: reduced risk associated with oral contraceptives. Br Med J (Clin Res Ed)
19. Lumbiganon P, Rugpao S, Phandhu-fung S, et al. Protective effect of depot-medroxyprogesterone acetate on surgically treated uterine leiomyomas: a multicentre case-control study. Br J Obstet Gynaecol
20. Parazzini F, La Vecchia C, Negri E, et al. Epidemiologic characteristics of women with uterine fibroids: a case-control study. Obstet Gynecol
21. Samadi AR, Lee NC, Flanders WD, et al. Risk factors for self-reported uterine fibroids: a case-control study. Am J Public Health
22. Parazzini F, Negri E, La Vecchia C, et al. Reproductive factors and risk of uterine fibroids. Epidemiology
23. Wise LA, Palmer JR, Spiegelman D, et al. Influence of body size and body fat distribution on risk of uterine leiomyomata in U.S. black women. Epidemiology
24. Boynton-Jarrett R, Rich-Edwards J, Malspeis S, et al. A prospective study of hypertension and risk of uterine leiomyomata. Am J Epidemiol
25. Faerstein E, Szklo M, Rosenshein NB. Risk factors for uterine leiomyoma: a practice-based case-control study II. Atherogenic risk factors and potential sources of uterine irritation.. Am J Epidemiol
26. Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer
27. Hollmann M, Runnebaum B, Gerhard I. Impact of waist-hip-ratio and body-mass-index on hormonal and metabolic parameters in young, obese women. Int J Obes Relat Metab Disord
28. Rogers I, Metcalfe C, Gunnell D, et al. Insulin-like growth factor-I and growth in height, leg length, and trunk length between ages 5 and 10 years. J Clin Endocrinol Metab
29. Baer HJ, Colditz GA, Rosner B, et al. Body fatness during childhood and adolescence and incidence of breast cancer in premenopausal women: a prospective cohort study. Breast Cancer Res
30. Smith GD, Hart C. Life-course socioeconomic and behavioral influences on cardiovascular disease mortality: the collaborative study. Am J Public Health
31. Schwartz SM, Marshall LM. Uterine leiomyomata. In: Goldman MB, Hatch MC, eds. Women and Health
. San Diego: Academic Press; 2000:240–252.