IntroductionHow much of the disease burden in a population could be eliminated if the effects of certain causal factors were eliminated from the population? To address this question, epidemiologists calculate the population attributable fraction. As noted in a recent editorial in the Journal, population attributable fraction estimates can help guide policymakers in planning public health interventions.' Despite numerous articles on population attributable fraction estimation, 2-7 errors in computation and interpretation persist. In addition, in certain settings, the value of a population attributable fraction estimate may be questionable. This commentary considers computational and conceptual issues relevant to population attributable fraction estimation that are infrequently discussed elsewhere, with illustrations from the breast cancer literature.

The Gail et al. model 2 fit well in this sample in terms of predicting numbers of breast cancer cases in specific risk factor strata but had modest discriminatory accuracy at the individual level. This finding has implications for use of the model in clinical counseling of individual women.

These results contribute to the body of evidence suggesting that higher levels of adult physical activity afford modest protection against breast cancer.

Survival-time studies sometimes do not yield distinct failure times. Several methods have been proposed to handle the resulting ties. The goal of this paper is to compare these methods. Simulations were conducted, in which failure times were generated for a two-sample problem with an exponential hazard, a constant hazard ratio, and no censoring. Failure times were grouped to produce heavy, moderate, and light ties, corresponding to a mean of 10.0, 5.0, and 2.5 failures per interval. Cox proportional hazards models were fit using each of three approximations for handling ties with each interval size for sample sizes of n = 25, 50, 250, and 500 in each group. The Breslow (1974, Biometrics 30, 89-99) approximation tends to underestimate the true beta, while the Kalbfleisch-Prentice (1973, Biometrika 60, 267-279) approximation tends to overestimate beta. As the ties become heavier, the bias of these approximations increases. The Efron (1977, Journal of the American Statistical Association 72, 557-565) approximation performs far better than the other two, particularly with moderate or heavy ties; even with n = 25 in each group, the bias is under 2%, and for sample sizes larger than 50 per group, it is less than 1%. Except for the heaviest ties in the smallest sample, confidence interval coverage for all three estimators fell in the range of 94-96%. However, the tail probabilities were asymmetric with the Breslow and Kalbfleisch-Prentice formulas; using the Efron approximation, they were closer to the nominal 2.5%. Although the Breslow approximation is the default in many standard software packages, the Efron method for handling ties is to be preferred, particularly when the sample size is small either from the outset or due to heavy censoring.

Established breast cancer risk factors, in addition to being relatively unmodifiable, are highly prevalent among US women. Previous reports of population attributable fraction for the established risk factors have used definitions that resulted in 75-100% of women in the source population labeled exposed. The practical value of such estimates has not been discussed; further, the estimates have frequently been misinterpreted. In the context of examining the interpretation and public health value of such estimates, the authors demonstrate the sensitivity of the population attributable fraction to changes in exposure cutpoints. They use data from the Carolina Breast Cancer Study, a case-control study of breast cancer conducted in North Carolina between 1993 and 1996. For the four established risk factors (menarche before age 14 years, first birth at age 20 years or later/nulliparity, family history of breast cancer, and history of benign breast biopsy), the estimated population attributable fraction was 0.25 (95% confidence interval 0.06-0.48). Over 98% of the source population was exposed to at least one of these risk factors. The population attributable fraction estimate was reduced to 0.15 when more restrictive definitions of early menarche (less than age 12 years) and late age at first full-term pregnancy (30 years or more) were used (proportion exposed, 0.62). Population attributable fractions for established breast cancer risk factors probably have little public health value because of both the high proportions exposed and the relative unmodifiability of the risk factor distributions.

The construct validity of the WHIIRS was supported because it was successfully used to detect self-reported sleep disturbance differences in women taking HT versus those taking a placebo as well as in groups known to differ in severity of their vasomotor symptoms.

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Background: Increased physical activity has been hypothesized to be a means of breast cancer prevention. We examined the associations between physical activity at two different times in life and breast cancer risk. Methods: We analyzed data from the Nurses' Health Study II, a prospective study of women aged 25-42 years in 1989. On the baseline survey, women were asked, ''While in high school and between the ages 18 and 22 years, how often did you participate in strenuous physical activity at least twice a week?'' We averaged answers to these two questions to develop a measure of late adolescent activity. Women were also asked at baseline to report the number of hours per week they currently spent in different nonoccupational activities. During 6 years of follow-up, we identified 372 cases of invasive breast cancer. Data were analyzed by use of multivariate pooled logistic regression to produce relative risk (RR) and confidence intervals (CIs) of being diagnosed with the disease. Results: Women who were more active in late adolescence were not at reduced risk of breast cancer compared with less active women. For those women who reported engaging in strenuous activity at least twice per week for 10-12 months per year in late adolescence, the RR of cancer, compared with those who never engaged in such activity, was 1.1 (95% CI = 0.8-1.6). Similarly, higher levels of recent