Andrew J. Bersch

Physical Activity and Survival after Diagnosis of Invasive Breast Cancer

Previous studies suggest that increased physical activity may lower the risk of breast cancer incidence, but less is known about whether levels of physical activity after breast cancer diagnosis can influence survival. We prospectively examined the relation between postdiagnosis recreational physical activity and risk of breast cancer death in women who had a previous invasive breast cancer diagnosed between 1988 and 2001 (at ages 20-79 years). All women completed a questionnaire on recent postdiagnosis physical activity and other lifestyle factors. Among 4,482 women without history of recurrence at the time of completing the questionnaire, 109 died from breast cancer within 6 years of enrollment. Physical activity was expressed as metabolic equivalent task-hours per week (MET-h/wk); hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated using Cox proportional hazards regression. After adjusting for age at diagnosis, stage of disease, state of residence, interval between diagnosis and physical activity assessment, body mass index, menopausal status, hormone therapy use, energy intake, education, family history of breast cancer, and treatment modality compared with women expending <2.8 MET-h/wk in physical activity, women who engaged in greater levels of activity had a significantly lower risk of dying from breast cancer (HR, 0.65; 95% CI, 0.39-1.08 for 2.8-7.9 MET-h/wk; HR, 0.59; 95% CI, 0.35-1.01 for 8.0-20.9 MET-h/wk; and HR, 0.51; 95% CI, 0.29-0.89 for ≥21.0 MET-h/wk; P for trend = 0.05). Results were similar for overall survival (HR, 0.44; 95% CI, 0.32-0.60 for ≥21.0 versus <2.8 MET-h/wk; P for trend <0.001) and were similar regardless of a woman’s age, stage of disease, and body mass index. This study provides support for reduced overall mortality and mortality from breast cancer among women who engage in physical activity after breast cancer diagnosis. (Cancer Epidemiol Biomarkers Prev 2008;17(2):379–86)

Body mass index before and after breast cancer diagnosis: Associations with all-cause, breast cancer, and cardiovascular disease mortality

Background: Factors related to improving outcomes in breast cancer survivors are of increasing public health significance. We examined postdiagnosis weight change in relation to mortality risk in a cohort of breast cancer survivors. Methods: We analyzed data from a cohort of 3,993 women with ages 20 to 79 years living in New Hampshire, Massachusetts, or Wisconsin with invasive nonmetastatic breast cancers diagnosed in 1988 to 1999 identified through state registries. Participants completed a structured telephone interview 1 to 2 years after diagnosis and returned a mailed follow-up questionnaire in 1998 to 2001 that addressed postdiagnosis weight and other factors. Vital status information was obtained from the National Death Index through December 2005. Hazard ratios and 95% confidence intervals were estimated from Cox proportional hazards models and adjusted for prediagnosis weight, age, stage, smoking, physical activity, and other important covariates. Results: During an average 6.3 years of follow-up from the postdiagnosis questionnaire, we identified 421 total deaths, including 121 deaths from breast cancer and 95 deaths from cardiovascular disease. Increasing postdiagnosis weight gain and weight loss were each associated with greater all-cause mortality. Among women who gained weight after breast cancer diagnosis, each 5-kg gain was associated with a 12% increase in all-cause mortality (P = 0.004), a 13% increase in breast cancer–specific mortality (P = 0.01), and a 19% increase in cardiovascular disease mortality (P = 0.04). Associations with breast cancer mortality were not modified by prediagnosis menopausal status, cigarette smoking, or body mass index. Conclusion: These findings suggest that efforts to minimize weight gain after a breast cancer diagnosis may improve survival. (Cancer Epidemiol Biomarkers Prev 2009;18(5):1403–9)

EFFECTS OF STRESS AND PHENOTYPIC VARIATION ON INBREEDING DEPRESSION IN BRASSICA RAPA

Abstract Stressful environments are often said to increase the expression of inbreeding depression. Alternatively, Crows “opportunity for selection” (the squared phenotypic coefficient of variation) sets a limit to how much selection can occur, constraining the magnitude of inbreeding depression. To test these hypotheses, we planted self- and cross-fertilized seeds of Brassica rapa into a factorial experiment that varied plant density and saline watering stresses. We then repeated the experiment, reducing the salt concentration. We observed considerable inbreeding depression, particularly for survival in the first experiment and growth in the second. Both stresses independently depressed plant performance. Families differed in their amounts of inbreeding depression and reaction norms across environments. Outcrossed progeny were sometimes more variable. Stresses had small and inconsistent effects on inbreeding depression and, when significant, tended to diminish it. Levels of phenotypic variability often predicted whether inbreeding depression would increase or decrease across environments and were particularly effective in predicting which traits display the most inbreeding depression. Thus, we find little support for the stress hypothesis and mixed support for the phenotypic variability hypothesis. Variable levels of phenotypic variation provide a parsimonious explanation for shifts in inbreeding depression that should be tested before invoking more complex hypotheses.

The Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research: rationale and methods

BackgroundEvidence-based public health requires the existence of reliable information systems for priority setting and evaluation of interventions. Existing data systems in the United States are either too crude (e.g., vital statistics), rely on administrative data (e.g., Medicare) or, because of their national scope (e.g., NHANES), lack the discriminatory power to assess specific needs and to evaluate community health activities at the state and local level. This manuscript describes the rationale and methods of the Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research.Methods/DesignThe program consists of a series of independent annual surveys gathering health-related data on representative samples of state residents and communities. Two-stage cluster sampling is used to select households and recruit approximately 800-1,000 adult participants (21-74 years old) each year. Recruitment and initial interviews are done at the household; additional interviews and physical exams are conducted at permanent or mobile examination centers. Individual survey data include physical, mental, and oral health history, health literacy, demographics, behavioral, lifestyle, occupational, and household characteristics as well as health care access and utilization. The physical exam includes blood pressure, anthropometry, bioimpedance, spirometry, urine collection and blood draws. Serum, plasma, and buffy coats (for DNA extraction) are stored in a biorepository for future studies. Every household is geocoded for linkage with existing contextual data including community level measures of the social and physical environment; local neighborhood characteristics are also recorded using an audit tool. Participants are re-contacted bi-annually by phone for health history updates.DiscussionSHOW generates data to assess health disparities across state communities as well as trends on prevalence of health outcomes and determinants. SHOW also serves as a platform for ancillary epidemiologic studies and for studies to evaluate the effect of community-specific interventions. It addresses key gaps in our current data resources and increases capacity for etiologic, applied and translational population health research. It is hoped that this program will serve as a model to better support evidence-based public health, facilitate intervention evaluation research, and ultimately help improve health throughout the state and nation.

Predictors of discordance between perceived and objective neighborhood data

PURPOSE Pathways by which the social and built environments affect health can be influenced by differences between perception and reality. This discordance is important for understanding health impacts of the built environment. This study examines associations between perceived and objective measures of 12 nonresidential destinations, as well as previously unexplored sociodemographic, lifestyle, neighborhood, and urbanicity predictors of discordance. METHODS Perceived neighborhood data were collected from participants of the Survey of the Health of Wisconsin, using a self-administered questionnaire. Objective data were collected using the Wisconsin Assessment of the Social and Built Environment, an audit-based instrument assessing built environment features around each participants residence. RESULTS Overall, there was relatively high agreement, ranging from 50% for proximity to parks to more than 90% for golf courses. Higher education, positive neighborhood perceptions, and rurality were negatively associated with discordance. Associations between discordance and depression, disease status, and lifestyle factors appeared to be modified by urbanicity level. CONCLUSIONS These data show perceived and objective neighborhood environment data are not interchangeable and the level of discordance is associated with or modified by individual and neighborhood factors, including the level of urbanicity. These results suggest that consideration should be given to including both types of measures in future studies.

The Wisconsin Assessment of the Social and Built Environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health

BackgroundGrowing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed. The Wisconsin Assessment of the Social and Built Environment (WASABE) is an objective audit tool designed as an addition to a statewide household-based health examination survey, the Survey of the Health of Wisconsin (SHOW), to objectively measure participant’s neighborhoods.MethodsThis paper describes the development and implementation of the WASABE and examines the instrument’s ability to capture a range of social and built environment features in urban and rural communities. A systematic literature review and formative research were used to create the tool. Inter-rater reliability parameters across items were calculated. Prevalence and density of features were estimated for strata formed according to several sociodemographic and urbanicity factors.ResultsThe tool is highly reliable with over 81% of 115 derived items having percent agreement above 95%. It captured variance in neighborhood features in for a diverse sample of SHOW participants. Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level. Walking and biking trails were present in 29% (19-39%) of participant buffer in urban areas compared to only 7% (2-12%) in rural communities. Significant environmental differences were also observed for white versus non-white, high versus low income, and college graduates versus individuals with lower level of education.ConclusionsThe WASABE has strong inter-rater reliability and validity properties. It builds on previous work to provide a rigorous and standardized method for systematically gathering objective built and social environmental data in a number of geographic settings. Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.

Fertility Drug Use and Mammographic Breast Density in a Mammography Screening Cohort of Premenopausal Women

The widespread use of ovulation-inducing drugs to enhance fertility has raised concerns about its potential effects on breast cancer risk, as ovarian stimulation is associated with increases in estrogen and progesterone levels. We investigated the short-term relation between fertility drug use and mammographic breast density, a strong marker of breast cancer risk, among participants in the Group Health Breast Cancer Screening Program. Data linkage with Group Health automated pharmacy records identified 104 premenopausal women <50 years old who obtained a mammogram during 1996-2006, within 2 years after a fertility drug dispensing. Premenopausal nonusers of fertility drugs were matched to users by age, body mass index, age at first birth, family history of breast cancer, past use of birth control hormones, race, and education (n = 1005). All mammograms were categorized for density according to the Breast Imaging Reporting Data System as entirely fat, scattered fibroglandular, heterogeneously dense, or extremely dense. Density in fertility drug users was equally likely as in nonusers to be rated entirely fat [odds ratio (OR), 0.83; 95% confidence interval (95% CI), 0.18-3.71], heterogeneously dense (OR, 1.09; 95% CI, 0.64-1.85), or extremely dense (OR, 0.93; 95% CI, 0.48-1.78) compared with scattered fibroglandular. In analyses restricted to fertility drug users, each additional month after the date of dispensing was associated with a 13% (95% CI for the OR, 1.01-1.27) increased odds of being categorized as heterogeneously/extremely dense compared with entirely fat/scattered fibroglandular (P = 0.04). Our results indicate no overall association between fertility drug use and mammographic density, but provide evidence that density may be lower in women more recently dispensed a fertility drug. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3128–33)