Jane A. McElroy

Socioeconomic risk factors for breast cancer: distinguishing individual- and community-level effects.

Background: Women are at higher risk of breast cancer if they have higher socioeconomic status (SES) or live in higher SES or urban communities. We examined whether women living in such communities remained at greater risk of breast cancer after controlling for individual education and other known individual-level risk factors. Methods: Data were from a population-based, breast cancer case-control study conducted in Wisconsin from 1988 to 1995 (n = 14,667). Data on community SES and urbanicity come from the 1990 census, measured at the census tract and zip code levels. We evaluated relationships between individual- and community-level variables and breast cancer risk using multilevel logistic regression models with random community intercepts. Results: After controlling for individual education and other individual-level risk factors (age, mammography use, family history of breast cancer, parity, age at first birth, alcohol intake, body mass index, hormone replacement use, oral contraceptive use, and menopausal status), women living in the highest SES communities had greater odds of having breast cancer than women living in the lowest SES communities (1.20; 95% confidence interval = 1.05–1.37). Similarly, the odds were greater for women in urban versus rural communities (1.17; 1.06–1.28). Conclusions: Community SES and urbanicity are apparently not simply proxies for individual SES. Future research should examine why living in such communities itself is associated with greater risk of breast cancer.

Geocoding addresses from a large population-based study: lessons learned.

Background Geographic information systems (GIS) and spatial statistics are useful for exploring the relation between geographic location and health. The ultimate usefulness of GIS depends on both completeness and accuracy of geocoding (the process of assigning study participants’ residences latitude/longitude coordinates that closely approximate their true locations, also known as address matching). The goal of this project was to develop an iterative geocoding process that would achieve a high match rate in a large population-based health study. Methods Data were from a study conducted in Wisconsin using mailing addresses of participants who were interviewed by telephone from 1988 to 1995. We standardized the addresses according to US Postal Service guidelines, used desktop GIS geocoding software and two versions of the Topologically Integrated Geographic Encoding and Referencing street maps, accessed Internet mapping engines for problematic addresses, and recontacted a small number of study participants’ households. We also tabulated the project’s cost, time commitment, software requirements, and brief notes for each step and their alternatives. Results Of the 14,804 participants, 97% were ultimately assigned latitude/longitude coordinates corresponding to their respective residences. The remaining 3% were geocoded to their zip code centroid. Conclusion The multiple methods described in this work provide practical information for investigators who are considering the use of GIS in their population health research.

Duration of sleep and breast cancer risk in a large population-based case : control study

One important function of sleep may be its contribution to the maintenance of the immune system and regulation of the circadian rhythms by melatonin. Researchers have speculated that disruption of immune functions involving cortisol levels and natural killer cell activity may increase breast cancer risk whereas increased melatonin exposure may protect against breast cancer. We conducted a multistate population‐based case–control study of 4033 women with invasive breast cancer and 5314 community women without breast cancer in which we inquired about womens sleep habits in the recent past and during adult lifetime. Relative to women who slept 7.0–7.9 h/night, the multivariate odds ratio for developing breast cancer among women who slept an average of 9 h or more per night approximately 2 years prior to interview was 1.13 (95% CI 0.93–1.37). The multivariate‐adjusted odds ratio for the continuous term was 1.06 (95% CI 1.01–1.11), suggesting a 6% increase in risk for every additional hour of sleep. Similar patterns were observed for average lifetime adult sleep duration. We found little evidence that sleeping few hours per night was associated with breast cancer risk. The results of this study suggest that increasing sleep duration is modestly associated with an increased breast cancer risk. In contrast, short duration of sleep (<7 h/night) is not substantially associated with increased risk. Further research in this area is warranted.

Urinary Cadmium Levels and Tobacco Smoke Exposure in Women Age 20–69 Years in the United States

Cadmium is a toxic, bioaccumulated heavy metal with a half-life of one to four decades in humans (CDC, 2005). Primary exposure sources include food and tobacco smoke. In our population-based study, a risk-factor interview was conducted as part of a breast cancer study for 251 randomly selected women living in Wisconsin (USA), aged 20–69 yr, and spot-urine specimens were also obtained. Urine collection kits were carefully designed to minimize trace element contamination during specimen collection and handling in each participants home. Urine cadmium concentrations were quantified using inductively coupled plasma–mass spectrometry, and creatinine levels and specific gravity were also determined. Statistically significant increasing creatinine-adjusted urinary cadmium mean levels relative to smoking status (never, former, and current respectively) were observed. A difference in mean cadmium levels for nonsmokers who reported environmental tobacco smoke exposure during childhood or the recent past (approximately 2 yr prior to the interview) for exposure at home, at work, or in social settings compared to those who reported no exposure was not found.

Electric blanket or mattress cover use and breast cancer incidence in women 50-79 years of age

Previous research has demonstrated inconsistent associations between electromagnetic radiation, especially from electric blanket use, and breast cancer. Breast cancer risk according to electric blanket or mattress cover use was examined as part of a multicenter population-based case-control study. Breast cancer patients 50–79 years of age (N = 1949) were identified from statewide tumor registries in Massachusetts, New Hampshire, and Wisconsin from the period June 1994 to July 1995. Women of similar age were randomly selected from population lists as controls. Information regarding electric blanket and mattress cover use and breast cancer risk factors was obtained through telephone interviews. After adjustment for age, body mass index, and other breast cancer risk factors, the risk of breast cancer was similar among ever-users (relative risk = 0.93; 95% confidence interval = 0.82–1.06) and lower among current users than among never-users (relative risk = 0.79; 95% confidence interval = 0.66–0.95). There was no evidence of a dose-response relation with increasing number of months that electric blankets had been used. This study provides evidence against a positive association between electric blanket or mattress cover use and breast cancer.

Predictors of Willingness to Participate in Window-of-Opportunity Breast Trials

Objective We conducted a pilot survey to evaluate breast cancer patients’ willingness to participate in a preoperative chemoprevention (ie, window-of-opportunity) study. Design A 27-question written survey was developed and administered to participants. Setting A breast cancer specialty clinic at the University of Wisconsin Hospital and Clinics. Participants 30 adult patients with newly diagnosed operable breast cancer participated after signing informed consent. Methods A convenience sample of 30 participants was recruited from July 2005 through January 2006. Participants were administered the survey in clinic. Univariate ordinal logistic regression models were used to identify predictors of willingness to participate in window-of-opportunity trials. Results Overall, 26.7% of respondents were willing to participate in a research trial between the time of breast cancer diagnosis and surgery. Univariate ordinal logistic regression models identified that women with a prior history of breast cancer (P=0.060), prior research participation (P=0.006), more education (P=0.034), and self-reported breast cancer knowledge (P=0.043) were more willing to participate. On average, women preferred to have surgery 7 days (range 1–14) after their diagnosis, but the actual average wait time between diagnostic biopsy and surgery was 37.5 days (standard deviation = 23.4 days). Conclusion There is ample time before breast surgery to conduct preoperative window-of-opportunity trials. Interventions aimed at expanding patients’ breast cancer knowledge may improve accrual to window-of-opportunity studies.