Jisheng Cui

The aims of this study were to describe, in relation to date of final menses, the average androgen levels of women in the years before and after this date, and to determine the extent to which these average levels were dependent on age and body mass index (BMI) and the degree of tracking in residual androgen levels, or the extent to which individuals above (below) the mean for their age or time relative to final menstrual period (FMP) and BMI remain above (below) the mean as time progresses. Serial levels of serum sex hormone-binding globulin (SHBG), testosterone (T), and dehydroepiandrosterone sulfate (DHEAS) were measured annually in 172 women from the Melbourne Women's Midlife Health Project who experienced a natural menopause during 7 yr of follow-up. Fasting blood samples were drawn between days 4-8 if women were still menstruating or after 3 months of amenorrhea. The free androgen index (FAI) was calculated as the ratio ofT to SHBG x 100. Means of the log-transformed androgen levels were analyzed as a double logistic function of time relative to FMP as well as age and BMI, and correlations between repeated androgen levels were measured. Mean SHBG levels decreased by 43% from 4 yr before to 2 yr after the FMP. The time of most change was 2 yr before FMP [95% confidence interval (CI), 0.8-3.2]. SHBG levels were, on the average, 5% lower for each halving of estradiol (E2) levels and 4% lower for each kilogram per m2 of BMI (P < 0.0001). About one third of the decline in SHBG was explained by E2 and BMI. After adjusting for all variables, SHBG showed strong tracking. Mean T levels did not vary with time relative to FMP and were independent of age and BMI. Residual values of T showed weak tracking. The FAI increased by 80% from 4 yr before FMP to 2 yr after FMP, and changed maximally 2.2 yr before FMP (95% CI, 1.2-3.2). The FAI was not related to age or E2, but was, on the average, 4% higher for each kilogram per m2 of BMI (P < 0.0001). Residual values of FAI showed moderate tracking. Mean DHEAS levels were not related to the FMP, but were 1.5% lower for each year of age (P < 0.01) and 3.8% lower for each kilogram per m2 of BMI (P < 0.0001). Residual values of DHEAS showed strong tracking. It is concluded that SHBG and FAI levels change at the time of the menopause, at least partially due to the decline in E2. DHEAS decreases as a function of age, not time relative to FMP, and T remains unchanged during the menopausal years. SHBG and DHEAS show a high degree of stability within an individual over time.

The linkage and association between inherent blood pressure and underlying genotype is potentially confounded by antihypertensive treatment. We estimated blood pressure variance components (genetic, shared environmental, individual-specific) in 767 adult volunteer families by using a variety of approaches to adjusting blood pressure of the 244 subjects (8.2%) receiving antihypertensive medications. The additive genetic component of variance for systolic pressure was 73.9 mm Hg(2) (SE, 8.8) when measured pressures (adjusted for age by gender within each generation) were used but fell to 61.4 mm Hg(2) (SE, 8.0) when treated subjects were excluded. When the relevant 95th percentile values were substituted for treated systolic pressures, the additive genetic component was 81.9 mm Hg(2) (SE, 9.5), but individual adjustments in systolic pressure ranged from -53.5 mm Hg to +64.5 mm Hg (mean, +17.2 mm Hg). Instead, when 10 mm Hg was added to treated systolic pressure, the additive genetic component rose to 86.6 mm Hg(2) (SE, 10.1). Similar changes were seen in the shared environment component of variance for systolic pressure and for the combined genetic and shared environmental (ie, familial) components of diastolic pressure. There was little change in the individual-specific variance component across any of the methods. Therefore, treated subjects contribute important information to the familial components of blood pressure variance. This information is lost if treated subjects are excluded and obscured by treatment effects if unadjusted measured pressures are used. Adding back an appropriate increment of pressure restores familial components, more closely reflects the pretreatment values, and should increase the power of genomic linkage and linkage disequilibrium analyses.

This paper proposes a nonparametric method for estimating a delay distribution based on left-censored and right-truncated data. A variance-covariance estimator is provided. The method is applied to the Australian AIDS data in which some data are left censored and some data are not left censored. This situation arises with AIDS case-reporting data in Australia because reporting delays were recorded only from November 1990 rather than from the beginning of the epidemic there. It is shown that inclusion of the left-censored data, as opposed to analyzing only the uncensored data, improves the precision of the estimate.