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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.

Human breast cancer is usually caused by genetic alterations of somatic cells of the breast, but occasionally, susceptibility to the disease is inherited. Mapping the genes responsible for inherited breast cancer may also allow the identification of early lesions that are critical for the development of breast cancer in the general population. Chromosome 17q21 appears to be the locale of a gene for inherited susceptibility to breast cancer in families with early-onset disease. Genetic analysis yields a lod score (logarithm of the likelihood ratio for linkage) of 5.98 for linkage of breast cancer susceptibility to D17S74 in early-onset families and negative lod scores in families with late-onset disease. Likelihood ratios in favor of linkage heterogeneity among families ranged between 2000:1 and greater than 10(6):1 on the basis of multipoint analysis of four loci in the region.

Risk factors for the newly identified "intrinsic" breast cancer subtypes (luminal A, luminal B, basal-like and human epidermal growth factor receptor 2-positive/estrogen receptor-negative) were determined in the Carolina Breast Cancer Study, a population-based, case-control study of African-American and white women. Immunohistochemical markers were used to subtype 1,424 cases of invasive and in situ breast cancer, and case subtypes were compared to 2,022 controls. Luminal A, the most common subtype, exhibited risk factors typically reported for breast cancer in previous studies, including inverse associations for increased parity and younger age at first full-term pregnancy. Basal-like cases exhibited several associations that were opposite to those observed for luminal A, including increased risk for parity and younger age at first term full-term pregnancy. Longer duration breastfeeding, increasing number of children breastfed, and increasing number of months breastfeeding per child were each associated with reduced risk of basal-like breast cancer, but not luminal A. Women with multiple live births who did not breastfeed and women who used medications to suppress lactation were at increased risk of basal-like, but not luminal A, breast cancer. Elevated waist-hip ratio was associated with increased risk of luminal A in postmenopausal women, and increased risk of basal-like breast cancer in pre- and postmenopausal women. The prevalence of basal-like breast cancer was highest among premenopausal African-American women, who also showed the highest prevalence of basal-like risk factors. Among younger African-American women, we estimate that up to 68% of basal-like breast cancer could be prevented by promoting breastfeeding and reducing abdominal adiposity.

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Lymphedema is a public health issue deserving greater attention. More systematic surveillance for earlier detection and the potential benefits of physical activity to prevent lymphedema and mitigate symptoms warrant further clinical integration and research.

Risk factors were examined for subgroups of breast cancer characterized by estrogen receptor (ER) and progesterone receptor (PR) status. Data from the Carolina Breast Cancer Study, a population-based, North Carolina case-control study of 862 breast cancer cases aged 20-74 years diagnosed during 1993-1996 and 790 controls frequency matched on race and age, were obtained by personal interview. ER and PR status was retrieved from medical records (80%) or was determined in the authors' laboratory (11%) but was missing for 9% of cases. The receptor status distribution was as follows: 53% ER+PR+, 11% ER+PR-, 8% ER-PR+, and 28% ER-PR-. Several hormone-related factors were associated with stronger increased risks for ER+PR+ than for ER-PR- breast cancer: the elevated odds ratios were strongest for ER+PR+ breast cancer among postmenopausal women who had an early age at menarche (odds ratio (OR) = 1.6, 95% confidence interval (CI): 1.0, 2.4), nulliparity/late age at first full-term pregnancy (OR = 1.7, 95% CI: 0.9, 3.2 and OR = 1.6, 95% CI: 1.0, 2.7, respectively), or a high body mass index (OR = 1.6, 95% CI: 0.9, 3.0) and among pre-/perimenopausal women who had a high waist-hip ratio (OR = 1.9, 95% CI: 1.2, 3.1). In contrast, family history of breast or ovarian cancer and medical radiation exposure to the chest produced higher odds ratios for ER-PR- than for ER+PR+ breast cancer, especially among pre-/perimenopausal women.

Concordance for Type 2 (non-insulin-dependent) diabetes was determined in 250 monozygotic and 264 dizygotic white male twin pairs who participated in the National Heart, Lung, and Blood Institute Twin Study. These twins were born between 1917 and 1927 and were identified from military records without regard to disease status. We examined surviving members of the cohort twice--at mean ages of 47 and 57 years--and obtained 1-h post-load glucose tests and medication histories. Diagnostic criteria for Type 2 diabetes included a glucose value greater than or equal to 13.9 mmol/l or current use of antidiabetic medication; possible Type 1 (insulin-dependent) diabetic twins were excluded. A strong genetic predisposition to Type 2 diabetes was suggested by 3 lines of evidence from the second examination: (1) 58% of monozygotic co-twins of diabetic twins were themselves diabetic compared with an expected prevalence of 10%; (2) only 1 of 15 originally disease-discordant, monozygotic twin pairs remained discordant for diabetes; and (3) 65% of non-diabetic monozygotic co-twins of diabetic twins had elevated glucose values. Because concordance for diabetes was less than 100% for twins aged 52-65 years and because twins varied in age at onset of disease, non-genetic factors may also influence diabetes development. Among the 19 monozygotic twins pairs discordant for diabetes, diabetic twins did not differ from their non-diabetic co-twins in obesity, diet, alcohol consumption, or education. However, compared with unrelated non-diabetic twins of the same ages, non-diabetic co-twins of diabetic twins gained more weight as adults (p less than 0.02) and had higher glucose levels (p less than 0.03).