scholarly journals Early-life exposures and age at thelarche in the Sister Study cohort

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Mandy Goldberg ◽  
Aimee A. D’Aloisio ◽  
Katie M. O’Brien ◽  
Shanshan Zhao ◽  
Dale P. Sandler

Abstract Background Early age at breast development (thelarche) has been associated with increased breast cancer risk. Average age at thelarche has declined over time, but there are few established risk factors for early thelarche. We examined associations between pre- and postnatal exposures and age at thelarche in a US cohort of women born between 1928 and 1974. Methods Breast cancer-free women ages 35–74 years who had a sister diagnosed with breast cancer were enrolled in the Sister Study from 2003 to 2009 (N = 50,884). At enrollment, participants reported information on early-life exposures and age at thelarche, which we categorized as early (≤ 10 years), average (11–13 years), and late (≥ 14 years). For each exposure, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) for early and late thelarche using polytomous logistic regression, adjusted for birth cohort, race/ethnicity and family income level in childhood. Results Early thelarche was associated with multiple prenatal exposures: gestational hypertensive disorder (OR = 1.25, 95% CI 1.09–1.43), diethylstilbestrol use (OR = 1.23, 95% CI 1.04–1.45), smoking during pregnancy (OR = 1.20, 95% CI 1.13–1.27), young maternal age (OR 1.30, 95% CI 1.16–1.47 for < 20 vs. 25–29 years), and being firstborn (OR = 1.25, 95% CI 1.17–1.33). Birthweight < 2500 g and soy formula use in infancy were positively associated with both early and late thelarche. Conclusions Associations between pre- and postnatal exposures and age at thelarche suggest that the early-life environment influences breast development and therefore may also affect breast cancer risk by altering the timing of pubertal breast development.

2005 ◽  
Vol 23 (7) ◽  
pp. 609-624 ◽  
Author(s):  
Michele R. Forman ◽  
Marie M. Cantwell ◽  
Cécile Ronckers ◽  
Yawei Zhang

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Lauren C. Houghton ◽  
Seungyoun Jung ◽  
Rebecca Troisi ◽  
Erin S. LeBlanc ◽  
Linda G. Snetselaar ◽  
...  

Abstract Background Earlier age at onset of pubertal events and longer intervals between them (tempo) have been associated with increased breast cancer risk. It is unknown whether the timing and tempo of puberty are associated with adult breast density, which could mediate the increased risk. Methods From 1988 to 1997, girls participating in the Dietary Intervention Study in Children (DISC) were clinically assessed annually between ages 8 and 17 years for Tanner stages of breast development (thelarche) and pubic hair (pubarche), and onset of menses (menarche) was self-reported. In 2006–2008, 182 participants then aged 25–29 years had their percent dense breast volume (%DBV) measured by magnetic resonance imaging. Multivariable, linear mixed-effects regression models adjusted for reproductive factors, demographics, and body size were used to evaluate associations of age and tempo of puberty events with %DBV. Results The mean (standard deviation) and range of %DBV were 27.6 (20.5) and 0.2–86.1. Age at thelarche was negatively associated with %DBV (p trend = 0.04), while pubertal tempo between thelarche and menarche was positively associated with %DBV (p trend = 0.007). %DBV was 40% higher in women whose thelarche-to-menarche tempo was 2.9 years or longer (geometric mean (95%CI) = 21.8% (18.2–26.2%)) compared to women whose thelarche-to-menarche tempo was less than 1.6 years (geometric mean (95%CI) = 15.6% (13.9–17.5%)). Conclusions Our results suggest that a slower pubertal tempo, i.e., greater number of months between thelarche and menarche, is associated with higher percent breast density in young women. Future research should examine whether breast density mediates the association between slower tempo and increased breast cancer risk.


2007 ◽  
Vol 122 (3) ◽  
pp. 481-485 ◽  
Author(s):  
Dimitrios Trichopoulos ◽  
Hans-Olov Adami ◽  
Anders Ekbom ◽  
Chung-Cheng Hsieh ◽  
Pagona Lagiou

2008 ◽  
Vol 17 (11) ◽  
pp. 3150-3160 ◽  
Author(s):  
Louise A. Brinton ◽  
Douglas Richesson ◽  
Michael F. Leitzmann ◽  
Gretchen L. Gierach ◽  
Arthur Schatzkin ◽  
...  

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Zhoufeng Ye ◽  
Gillian Dite ◽  
John Hopper

Abstract Background Our previous work on body mass index (BMI) and breast cancer risk found that the association depended on menopausal status but not on familial risk (Hopper, JL., et al, 2018). We now consider whether weight is a more informative risk factor for breast cancer than BMI. Methods We used data from the Prospective Family Study Cohort, a consortium of international prospective cohorts that are enriched for familial risk of breast cancer and include 16,035 unaffected women from 6701 families. Participants were followed for up to 20 years (mean 10.5 years) and there were 896 incident breast cancers with a mean age at diagnosis of 55.7 years. Cox regression was used to model risk associations as a function of age, menopausal status and underlying familial risk. We calculated robust confidence intervals by clustering by family. Model comparisons were made using the Bayesian Information Criterion (BIC). Results In repeating the best-fitting model from our original analyses, but using weight instead of BMI, we found that the log likelihood for the model using weight was 1.92 units greater than for the model using BMI (difference in BIC = 3.84). Therefore, the data are almost 50 times more likely under the model using weight. Conclusions The study found positive evidence that weight gives more information on risk than does BMI. Key messages Analysing breast cancer risk in terms of weight, rather than only BMI, might give greater insight and results that are easier to convey to the public.


2013 ◽  
Vol 24 (12) ◽  
pp. 2231-2243 ◽  
Author(s):  
Elisa V. Bandera ◽  
Urmila Chandran ◽  
Gary Zirpoli ◽  
Gregory Ciupak ◽  
Dana H. Bovbjerg ◽  
...  

2021 ◽  
pp. canprevres.CAPR-21-0164-A.2021
Author(s):  
Zhoufeng Ye ◽  
Shuai Li ◽  
Gillian S Dite ◽  
Tuong L. Nguyen ◽  
Robert J MacInnis ◽  
...  

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