Abstract B102: Multigenerational socioeconomic status and breast tissue composition in mothers and their adolescent daughters: Findings from a multiethnic cohort in New York City
Bibliographic record
Abstract
Abstract Social environment may influence breast tissue composition and breast cancer risk through shaping risk factors operating in early life, adolescence, and adulthood. Socioeconomic status (SES) has been positively associated with breast cancer risk, and mammography studies in women in middle to late adulthood suggest the association might be mediated by the positive relationship between higher SES and higher breast density. Yet, the impact of SES on breast tissue composition earlier in the lifecourse has not been examined, thus limiting the ability to elucidate lifecourse social influences and pathways in the development of breast cancer. In this study, we examined if SES is associated with breast tissue composition in a New York City cohort of 216 Black and Hispanic adolescent girls (aged 11-20 years) and their mothers (aged 29-55 years). We used optical spectroscopy to measure breast tissue chromophores including water content, lipid content, and collagen content, as well as a combined optical index measure. Previous studies have shown that these measures positively (water, collagen, optical index) or negatively (lipid) correlate with mammographic breast density. Questionnaires captured SES indicators at different timepoints across generations: grandparents’ highest level of education; mother’s highest level of education at daughter’s birth; mother’s highest level of education at breast measurement; household income at daughter’s birth; and public assistance at daughter’s birth. We evaluated associations using multivariable linear regression models adjusted for age at breast measurement, percent body fat at breast measurement, race/ethnicity, and mother’s birth country. We tested for additive effect modification by age at breast measurement. In daughters, higher mother’s education at birth was associated with lower lipid content (≥ bachelor’s degree vs. < high school degree, β: -6.96, 95% CI: -13.64, -0.27), and higher grandmother’s education was associated with higher water content (≥ some college vs. < elementary school, β: 3.77, 95% CI: 0.58, 6.97). In mothers, higher household income was associated with lower lipid content ($20,000-80,000 vs. < $10,000, β: -4.26, 95% CI: -7.93, -0.59) and higher optical index (β: 0.30, 95% CI: 0.01, 0.58), while not being on public assistance was associated with higher collagen content (β: 2.54, 95% CI: 0.74, 4.34). Mothers with some college education vs. high school degree or lower at daughter’s birth had higher water content (β: 3.81, 95% CI: 1.07, 6.54), but no association was found comparing mothers with bachelor’s degree or higher vs. high school degree or lower. Associations were not modified by age at breast measurement. This study provides novel data linking intergenerational and early life SES to breast tissue composition in adolescent girls independent of body fat and provides evidence consistent with previous mammography studies of a positive relationship between SES and breast density in adult women. Further studies are needed to explore the downstream factors mediating these relationships. Citation Format: Rebecca D. Kehm, Parisa Tehranifar, E. Jane Walter, Melissa L. White, Sabine Oskar, Julie B. Herbstman, Frederica Perera, Lothar Lilge, Rachel L. Miller, Mary Beth Terry. Multigenerational socioeconomic status and breast tissue composition in mothers and their adolescent daughters: Findings from a multiethnic cohort in New York City [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr B102.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".