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.

Theory, methods, and operational results of the Young Women's Health History Study: a study of young-onset breast cancer incidence in Black and White women.

PURPOSE: The etiology of young-onset breast cancer (BC) is poorly understood, despite its greater likelihood of being hormone receptor-negative with a worse prognosis and persistent racial and socioeconomic inequities. We conducted a population-based case-control study of BC among young Black and White women and here discuss the theory that informed our study, exposures collected, study methods, and operational results. METHODS: Cases were non-Hispanic Black (NHB) and White (NHW) women age 20-49 years with invasive BC in metropolitan Detroit and Los Angeles County SEER registries 2010-2015. Controls were identified through area-based sampling from the U.S. census and frequency matched to cases on study site, race, and age. An eco-social theory of health informed life-course exposures collected from in-person interviews, including socioeconomic, reproductive, and energy balance factors. Measured anthropometry, blood (or saliva), and among cases SEER tumor characteristics and tumor tissue (from a subset of cases) were also collected. RESULTS: Of 5,309 identified potentially eligible cases, 2,720 sampled participants were screened and 1,812 completed interviews (682 NHB, 1140 NHW; response rate (RR): 60%). Of 24,612 sampled control households 18,612 were rostered, 2,716 participants were sampled and screened, and 1,381 completed interviews (665 NHB, 716 NHW; RR: 53%). Ninety-nine% of participants completed the main interview, 82% provided blood or saliva (75% blood only), and SEER tumor characteristics (including ER, PR and HER2 status) were obtained from 96% of cases. CONCLUSIONS: Results from the successfully established YWHHS should expand our understanding of young-onset BC etiology overall and by tumor type and identify sources of racial and socioeconomic inequities in BC.

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.

Comparing multiple statistical software for multiple-indicator, multiple-cause modeling: an application of gender disparity in adult cognitive functioning using MIDUS II dataset.

BACKGROUND: The multiple-indicator, multiple-cause model (MIMIC) incorporates covariates of interest in the factor analysis. It is a special case of structural equation modeling (SEM), which is modeled under latent variable framework. The MIMIC model provides rigorous results and becomes broadly available in multiple statistical software. The current study introduces the MIMIC model and how it can be implemented using statistical software packages SAS CALIS procedure, R lavaan package, and Mplus version 8.0. METHODS: In this paper, we first discussed the formulation of the MIMIC model with regard to model specification and identification. We then demonstrated the empirical application of the MIMIC model with the Midlife in the United States II (MIDUS II) Study (N = 4109) using SAS CALIS procedure, R lavaan package and Mplus version 8.0 to examine gender disparities in cognitive functioning. The input, output, and diagram syntaxes of the three statistical software packages were also presented. RESULTS: In terms of data structure, all three statistical programs can be conducted using both raw data and empirical covariance matrix. SAS and R are comprehensive statistical analytic packages and encompass numerous data manipulation capacities. Mplus is designed primarily for latent variable modeling and has far more modeling flexibility compared to SAS and R, but limited in data manipulation. Differences in model results from the three statistical programs are trivial. Overall, the results show that while men show better performance in executive function than women, women demonstrate better episodic memory than men. CONCLUSIONS: Our study demonstrates the utility of the MIMIC model in its empirical application, fitted with three popular statistical software packages. Results from our models align with empirical findings from previous research. We provide coding procedures and examples with detailed explanations in the hopes of providing a concise tutorial for researchers and methodologists interested in incorporating latent constructs with multiple indicators and multiple covariates in their research projects. Future researchers are encouraged to adopt this flexible and rigorous modeling approach.

HIDDEN DISPARITIES: HOW COURSES AND CURRICULA SHAPE OPPORTUNITIES IN MATHEMATICS DURING HIGH SCHOOL.

Efforts to promote academic achievement by increasing access to courses, especially in mathematics, may mask educational disparities if variations in curriculum are not also monitored. A multi-dimensional description of students' mathematics curricula during high school was obtained from analyses of surveys, transcripts, and textbooks collected for a nationally representative study of adolescents during the mid-1990s. Few gaps in the number of years or credits in mathematics coursework were found. However, the quantity and cognitive challenge of instructional materials in textbooks adopted for those courses differed significantly both across and within mathematics tracks. Differences in the quality of curriculum accumulating during high school were also related to parents' education level. Reducing such gaps in learning opportunities would require teachers to supplement adopted instructional materials to ensure that all students receive a high quality mathematics curriculum.