Background Women attending mammography screening units (msus) and well women’s clinics (wwcs) represent a motivated cohort likely to engage in interventions aimed at primary breast cancer (bca) prevention. Methods We used a feasibility questionnaire distributed to women (40–49 or 50–74 years of age) attending msus and wwcs in Halifax, Nova Scotia, to examine ■ women’s views about bca primary prevention and sources of health care information, ■ prevalence of lifestyle-related bca risk factors, and ■ predictors of prior mammography encounters within provincial screening guidelines. Variables examined included personal profiling, comorbidities, prior mammography uptake, lifestyle behaviours, socioeconomic status, health information sources, and willingness to discuss or implement lifestyle modifications, or endocrine therapy, or both. A logistic regression analysis examined associations with prior mammography encounters. Results Of the 244 responses obtained during 1.5 months from women aged 40–49 years (n = 75) and 50–74 years (n = 169), 56% and 75% respectively sought or would prefer to receive health information from within, as opposed to outside, health care. Lifestyle-related bca risk factors were prevalent, and most women were willing to discuss or implement lifestyle modifications (93%) or endocrine therapy (67%). Of the two age groups, 49% and 93% respectively had previously undergone mammography within guidelines. Increasing age and marital status (single, separated, or divorced vs. married or partnered) were independent predictors of prior mammography encounters within guidelines for women 40–49 years of age; no independent predictors were observed in the older age group. Conclusions Women attending msus and wwcs seem to largely adhere to mammography guidelines and appear motivated to engage in bca primary prevention strategies, including lifestyle modifications and endocrine therapy. Women’s views as observed in this study provide a rationale for the potential incorporation of bca risk assessment within the “mammogram point of care” to engage motivated women in bca primary prevention strategies.

Background: Hispanic and black women with breast cancer have poorer survival and are more likely to be obese and sedentary than non-Hispanic whites. Regular physical activity, high intake of fruits and vegetables, and lean body mass may improve survival. We report the initial results of a randomized wait-list controlled pilot study to test the effects of 6 months of the community-based Curves® exercise and nutrition program on weight loss among minority BC survivors.Methods: Hispanic/black women with stage 0-IIIa breast cancer who were ≥6 months post-treatment, sedentary and had a BMI≥25kg/m2 were enrolled. Eligible participants were randomized to the Immediate Arm (IA): 6 months of the Curves® exercise and dietary change weight loss program, followed by 6 months of observation; or the Delayed Arm (DA): 6 months of a waitlist control period, followed by 6 months of the Curves® program. The intervention entailed recommending exercise 5 times/wk using the 30-minute Curves® circuit-based exercise program and attending a series of 6 weekly nutrition sessions that promoted a high-vegetable/low-fat diet. All study materials were available in Spanish and English. Participants underwent clinic visits at baseline, 3, 6, 9, and 12 months and were followed with monthly telephone calls during the intervention. Month 6 results are reported here.Results: Forty-two women enrolled in the study (IA, n=22; DA, n=20). Baseline characteristics: mean (±SD) age, 50.7 (±8.9) years; 78.6% Hispanic/21.4% black; breast cancer stage, stage 0 9.5%, stage I 42.9%, stage II 33.3%, stage III 14.2%; mean body mass index (BMI), 33.2 (±5.9) kg/m2; mean % body fat as measured by DEXA, 41.6 (±4.9) %; and mean VO2 max, 18.4 (±3.6). Six month data were collected from 39 women; 2 women were removed from the study due to medical conditions (1 recurrent disease, 1 previously undiagnosed cardiac condition) and 1 women dropped from the study due to being too busy. In the IA, the average number of exercise sessions attended over the 6 month period was 1.1(±0.8) per week (range: 0.04 to 2.9/wk), and all participants attended all 6 nutrition classes either in-person or via phone make-up sessions. After 6 months, women in the IA lost an average of 2.7 (±3.2) kg (range: loss of 9.9 kg to gain of 1.7 kg), had a decrease in percent body fat of 1.5 (±1.5)% (range: loss of 5.9% to gain of 0.2%), and a decrease in VO2max of 1.0 (±3.4) ml/kg/min (range: decrease of 8.6 ml/kg/min to increase of 2.5 ml/kg/min) (within-subject measures p<0.05 for change in weight and percent body fat; all between-arm measures p>0.05). Twelve month data collection will be completed in July 2009 and will be presented at the conference.Conclusions: This 6 month pilot physical activity and dietary change intervention resulted in decreased in body weight and percent body fat among Hispanic and black BC survivors, although this decline was not significantly different than the wait-list control group. Though adherence to the exercise intervention was less than the targeted 5 exercise sessions per week, those that did adhere lost up to 9.9 kg. Further research on barriers to participation, optimal dose, and duration are necessary for future intervention trials. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1038.

BackgroundThe growing availability of (non-)commercial historical datasets opens a new avenue of research on how long-term exposure to the neighbourhood environment affects health. However, traditional tools for longitudinal analysis (e.g. mixed models) are limited in their ability to operationalise long-term exposure. This study aims to summarise longitudinal exposure to the neighbourhood using latent class growth analysis (LCGA). Using the National Establishment Time-Series (NETS) 1990–2010, we analysed the trajectory of change in New York City (NYC) in the number of unhealthy food businesses – a potential indicator of an obesogenic environment.MethodsThe NETS is a commercial dataset providing retail business information in the United States. NYC data were acquired for the period 1990–2010. Businesses were grouped into researcher-defined categories based on Standard Industrial Classification codes and other fields such as business name. All businesses were re-geocoded to ensure accurate localisation. We defined access to BMI-unhealthy businesses (characterised as selling calorie-dense foods such as pizza and pastries) as the total number of BMI-unhealthy businesses present in each NYC census tract (n=2,167) in January of each year. We conducted LCGA in Mplus to identify census tracts with similar trajectories of BMI-unhealthy businesses. We used model fit statistics and interpretability to determine the number of classes. Using the final models, we assigned census tracts to latent classes. We predicted class membership with socio-demographic variables from the Census (population size, income, and ethnic composition) using multinomial logistic regressions and reported predicted probabilities with 95% CI. Sensitivity analyses were undertaken.ResultsThe final models include 5 and 10 latent classes, respectively. The 5-class solution indicates an overall increase in the number of BMI-unhealthy businesses over time and shows a pattern of fanning out: the higher the value in 1990, the greater the increase over time. Classes are associated with 1990 population size, income, proportion of Black residents (all p<0.001), proportion of Hispanic residents (p=0.033), and 1990–2010 change in population size and income (p<0.001). The 10-class solution identifies two pairs of classes with similar 1990 values, but different trajectories. Differences in those trajectories are associated with population size and ethnic composition (p<0.001).ConclusionThis study illustrates how LCGA contributes to the understanding of long-term exposure to the obesogenic environment. The technique can easily be applied to other aspects of the neighbourhood and to other geographies. When linked with health data, identified latent classes can be used to assess how longitudinal exposure to changing neighbourhoods affects health.

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Background: Weight gain after breast cancer diagnosis increases the risk of mortality. African American/Black breast cancer survivors are more likely to have excess body weight than their White counterparts, which may contribute to their higher mortality rate. Emerging evidence suggests that post-diagnosis weight gain may result from multilevel determinants. However, no study has investigated the multilevel characteristics among Black breast cancer survivors. Objective: To evaluate associations between individual-level factors and neighborhood social and built environment factors with weight change after breast cancer diagnosis among Black women. Methods: We evaluated associations of interest among 785 women enrolled in the Women's Circle of Health Follow-Up Study (WCHFS), a longitudinal study of Black breast cancer survivors in New Jersey. Weight change was primarily based on measurements at baseline and follow-up visits (Median: 10.3 and 23.2 mo. since diagnosis, respectively). Participants were grouped into categories of stable weight (52.4%), ≥3% weight loss (20.0%), and ≥3% weight gain (27.6%). Using multivariate- adjusted multinomial logistic regression and multilevel multinomial logistic regression, we evaluated relative risk ratios (RRRs) for associations between multilevel factors and post-diagnosis weight change category. Results: Black breast cancer survivors who were older at diagnosis, had higher household income, post-menopausal status, and higher baseline BMI were less likely to gain weight compared to women with stable weight. Former smoking, higher tumor stage, and chemotherapy were associated with increased relative risk of weight gain (e.g. RRR-chemo: 1.45, 95% CI: 1.01, 2.08). Black women residing in neighborhoods in the highest tertile for density of walkable destinations had a decreased relative risk of post- diagnosis weight gain (e.g. RRR-T3 highest density vs. T1 lowest: 0.39, 95% CI: 0.20, 0.75), while those residing in neighborhoods with higher density of fast food restaurants had increased relative risk of weight gain (RRR-T3 highest density vs. T1 lowest: 1.94, 95% CI: 1.23, 3.05). Conclusion: Both individual and neighborhood factors may influence the risk of weight gain among Black women after breast cancer diagnosis.