Daily luteal serum and urinary hormone profiles in the menopause transition: Study of Women's Health Across the Nation.

OBJECTIVE: To further characterize the endocrinology of the menopause transition, we sought to determine: whether relationships between urine and serum hormones are maintained as women enter their sixth decade; whether a single luteal phase serum progesterone (P) is reflective of integrated-luteal urinary pregnanediol glucuronide (uPdg); and whether serum P, like luteal uPdg, declines as women approach their final menses (FMP). METHODS: The Study of Women's Health Across the Nation (SWAN) Daily Hormone Study's (DHS) is a community-based observational study. A subset of participants underwent a timed, luteal blood draw planned for cycle days 16 to 24 during the same month of DHS collection. Serum-luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol and P, and urine LH, FSH, estrone conjugates (E1c), and daily and integrated luteal uPdg were measured in 268 samples from 170 women. Serum/urine hormone associations were determined using Pearson's correlation and linear regression, adjusted for concurrent age, body mass index, smoking status, and race/ethnicity. RESULTS: Pearson's r ranged from 0.573 (for LH) to 0.843 (for FSH) for serum/urine correlations. Integrated luteal uPdg weakly correlated with serum P (Pearson's r = 0.26, P = 0.004) and explained 7% of the variability in serum P in adjusted linear regression (total R 0.09, P = 0.002). Serum P demonstrated a marginally significant decline with approaching FMP in adjusted analysis (P = 0.04). CONCLUSIONS: Urine and serum hormones maintain a close relationship in women into their sixth decade of life. Serum luteal P was weakly reflective of luteal Pdg excretion.

Bayesian Nonparametric Longitudinal Data Analysis.

Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.

The relation of acculturation to overweight, obesity, pre-diabetes and diabetes among U.S. Mexican-American women and men.

OBJECTIVE: To estimate and compare the prevalences of overweight, obesity, pre-diabetes and diabetes among a nationally representative sample of Mexican-American, non-Latino white and black adults, and by acculturation for Mexican-Americans. DESIGN, SETTINGS AND PARTICIPANTS: The NHANES 1999-2008 data sets were used. Binomial regression models were used to compute prevalence ratios and their respective 95% confidence intervals to assess the relationships of race/ethnicity and acculturation with obesity, overweight, pre-diabetes and diabetes. MAIN OUTCOME MEASURES: Overweight, obesity, pre-diabetes, and diabetes. RESULTS: Mexican Americans had a higher prevalence of overweight than white non-Latinos and Black non-Latinos. Obesity was significantly more prevalent among the most acculturated Mexican Americans but not the least acculturated. In contrast, the least acculturated Mexican Americans had the highest prevalence of overweight. The prevalence of pre-diabetes was higher among Mexican Americans than white non-Latinos and black non-Latinos. The most acculturated Mexican Americans had a higher prevalence of diabetes and the prevalence of pre-diabetes was elevated in less acculturated Mexican Americans. In both unadjusted and adjusted models, the less acculturated were significantly more likely to be overweight and significantly less likely to be obese, compared to more acculturated Mexican Americans, and acculturation was not associated with diabetes or prediabetes in adjusted models. CONCLUSION: Our results suggest that obesity was less prevalent among the least acculturated Mexican-Americans but overweight was more prevalent.