Adiposity throughout Adulthood and Risk of Young Onset Breast Cancer Tumor Subtypes in the Young Women's Health History Study.

BACKGROUND: The role of adult adiposity in young-onset breast cancer (YOBC) subtype risk is not well understood. METHODS: In this population-based case(n=1812)-control(n=1381) study of invasive YOBC (aged <50 years), cases were identified from the Los Angeles County and Metropolitan Detroit SEER registries, 2010-2015. Area-based, frequency-matched controls were sampled from the 2010 Census. General adiposity (body mass index (BMI)) and central adiposity (waist circumference (WC), waist-to-height ratio (WHtR)) across adulthood and covariates were collected from in-person interviews and measurements. Odds ratios (ORs) and 95% confidence intervals (CIs) for adiposity and YOBC tumor subtypes (i.e., luminal A, luminal B, HER2+, triple negative (TN)) were calculated, overall and by parity, using multivariable weighted logistic regression. RESULTS: Obese young adult BMI was inversely associated with luminal A YOBC (OR=0.35, 95% CI 0.16-0.79); other subtype associations were non-significant. Similarly, adult overweight and obese BMIs were inversely associated with luminal A (respectively OR=0.66, 95% CI 0.48-0.91 and OR=0.59, 95% CI 0.46-0.87), but not other subtypes. Conversely, larger WC was associated with higher odds of luminal B and TN YOBC (respectively OR=1.48, 95% CI 1.01-2.15 and OR=2.48, 95% CI 1.52-3.88), but not other subtypes (with similar results for WHtR); highest odds were among parous women. CONCLUSIONS: Findings show greater general adult adiposity is associated with reduced odds of luminal A YOBC, while greater central adiposity is associated with increased odds of luminal B and TN YOBC, particularly among parous women. IMPACT: Additional studies of central adiposity and YOBC subtype risk, especially incorporating pregnancy history, are warranted.

Lifetime alcohol consumption patterns and young-onset breast cancer by subtype among Non-Hispanic Black and White women in the Young Women's Health History Study.

PURPOSE: The role of alcohol in young-onset breast cancer (YOBC) is unclear. We examined associations between lifetime alcohol consumption and YOBC in the Young Women's Health History Study, a population-based case-control study of breast cancer among Non-Hispanic Black and White women < 50 years of age. METHODS: Breast cancer cases (n = 1,812) were diagnosed in the Metropolitan Detroit and Los Angeles County SEER registry areas, 2010-2015. Controls (n = 1,381) were identified through area-based sampling and were frequency-matched to cases by age, site, and race. Alcohol consumption and covariates were collected from in-person interviews. Weighted multivariable logistic regression was conducted to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for associations between alcohol consumption and YOBC overall and by subtype (Luminal A, Luminal B, HER2, or triple negative). RESULTS: Lifetime alcohol consumption was not associated with YOBC overall or with subtypes (all ptrend ≥ 0.13). Similarly, alcohol consumption in adolescence, young and middle adulthood was not associated with YOBC (all ptrend ≥ 0.09). An inverse association with triple-negative YOBC, however, was observed for younger age at alcohol use initiation (< 18 years vs. no consumption), aOR (95% CI) = 0.62 (0.42, 0.93). No evidence of statistical interaction by race or household poverty was observed. CONCLUSIONS: Our findings suggest alcohol consumption has a different association with YOBC than postmenopausal breast cancer-lifetime consumption was not linked to increased risk and younger age at alcohol use initiation was associated with a decreased risk of triple-negative YOBC. Future studies on alcohol consumption in YOBC subtypes are warranted.

Lifetime personal cigarette smoking and risk of young-onset breast cancer by subtype among non-Hispanic Black and White women in the Young Women's Health History Study.

PURPOSE: To evaluate the association between lifetime personal cigarette smoking and young-onset breast cancer (YOBC; diagnosed <50 years of age) risk overall and by breast cancer (BC) subtype, and whether risk varies by race or socioeconomic position (SEP). METHODS: Data are from the Young Women's Health History Study (YWHHS), a population-based case-control study of non-Hispanic Black (NHB) and White (NHW) women, ages 20-49 years (n = 1812 cases, n = 1381 controls) in the Los Angeles County and Metropolitan Detroit Surveillance, Epidemiology, and End Results (SEER) registry areas, 2010-2015. Lifetime personal cigarette smoking characteristics and YOBC risk by subtype were examined using sample-weighted, multivariable-adjusted polytomous logistic regression. RESULTS: YOBC risk associated with ever versus never smoking differed by subtype (Pheterogeneity = 0.01) with risk significantly increased for Luminal A (adjusted odds ratio [aOR] 1.34; 95% confidence interval [CI] 1.06-1.68) and HER2-type (aOR 1.97; 95% CI 1.23-3.16), and no association with Luminal B or Triple Negative subtypes. Additionally, ≥30 years since smoking initiation (versus never) was statistically significantly associated with an increased risk of Luminal A (aOR 1.55; 95% CI 1.07-2.26) and HER2-type YOBC (aOR 2.77; 95% CI 1.32-5.79), but not other subtypes. In addition, among parous women, smoking initiated before first full-term pregnancy (versus never) was significantly associated with an increased risk of Luminal A YOBC (aOR 1.45; 95% CI 1.11-1.89). We observed little evidence for interactions by race and SEP. CONCLUSION: Findings confirm prior reports of a positive association between cigarette smoking and Luminal A YOBC and identify a novel association between smoking and HER2-type YOBC.

The Decomposition of Between and Within Effects in Contextual Models.

In contextual studies, group compositions are often extracted from individual data in the sample, in order to estimate the group compositional effects [e.g., school socioeconomic status (SES) effect] controlling for interindividual differences in multilevel models. As the same variable is used at both group level and individual level, an appropriate decomposition of between and within effects is a key to providing a clearer picture of these organizational and individual processes. The current study developed a new approach with within-group finite population correction (fpc). Its performances were compared with the manifest and latent aggregation approaches in the decomposition of between and within effects. Under a moderate within-group sampling ratio, the between effect estimates from the new approach had a lesser degree of bias and higher observed coverage rates compared with those from the manifest and latent aggregation approaches. A real data application was also used to illustrate the three analysis approaches.