The Evolution of Un Abrazo Para La Familia: Implications for Survivors of Cancer.

Un Abrazo Para La Familia™ (Abrazo) is a 3-h modular preventive intervention designed for low-income caregivers who are co-survivors of cancer. Here we (1) consider the benefit to survivors of cancer, that is, the care recipients who participate in Abrazo; (2) summarize the literature specific to research outreach to low-income, underserved populations when they are faced with cancer; and (3) describe current steps being taken in Southern Arizona to reach these populations via Abrazo. Specific to considering the benefit to care recipients, we analyzed care recipient data derived from three existing cohorts of Abrazo participants. Analyses of the combined cohorts of these data demonstrate that Abrazo is effective with care recipients given statistically significant higher cancer knowledge and self-efficacy scores, pre- vs. post-intervention. We can now report benefit to care recipients who participate in Abrazo. This allows us, with confidence, to expand research recruitment efforts to include care recipients as part of the Abrazo intervention in our efforts to serve low-income, underserved populations when faced with cancer.

Socioeconomic and food-related physical characteristics of the neighbourhood environment are associated with body mass index.

OBJECTIVE: To determine whether socioeconomic and food-related physical characteristics of the neighbourhood are associated with body mass index (BMI; kg/m(2)) independently of individual-level sociodemographic and behavioural characteristics. DESIGN AND METHODS: Observational study using (1) individual-level data previously gathered in five cross-sectional surveys conducted by the Stanford Heart Disease Prevention Program between 1979 and 1990 and (2) neighbourhood-level data from (a) the census to describe socioeconomic characteristics and (b) data obtained from government and commercial sources to describe exposure to different types of retail food stores as measured by store proximity, and count of stores per square mile. Data were analysed using multilevel modelling procedures. The setting was 82 neighbourhoods in agricultural regions of California. PARTICIPANTS: 7595 adults, aged 25-74 years. RESULTS: After adjusting for age, gender, ethnicity, individual-level socioeconomic status, smoking, physical activity and nutrition knowledge, it was found that (1) adults who lived in low socioeconomic neighbourhoods had a higher mean BMI than adults who lived in high socioeconomic neighbourhoods; (2) higher neighbourhood density of small grocery stores was associated with higher BMI among women; and (3) closer proximity to chain supermarkets was associated with higher BMI among women. CONCLUSION: Living in low socioeconomic neighbourhoods, and in environments where healthy food is not readily available, is found to be associated with increased obesity risk. Unlike other studies which examined populations in other parts of the US, a positive association between living close to supermarkets and reduced obesity risk was not found in this study. A better understanding of the mechanisms by which neighbourhood physical characteristics influence obesity risk is needed.

The neighborhood food environment: sources of historical data on retail food stores.

With the rapidly increasing prevalence of obesity in the United States, and the minimal success of education-based interventions, there is growing interest in understanding the role of the neighborhood food environment in determining dietary behavior. This study, as part of a larger study, identifies historical data on retail food stores, evaluates strengths and limitations of the data for research, and assesses the comparability of historical retail food store data from a government and a commercial source. Five government and commercial listings of retail food stores were identified. The California State Board of Equalization (SBOE) database was selected and then compared to telephone business directory listings. The Spearman's correlation coefficient was used to assess the congruency of food store counts per census tract between the SBOE and telephone business directory databases. The setting was four cities in Northern California, 1979-1990. The SBOE and telephone business directory databases listed 127 and 351 retail food stores, respectively. The SBOE listed 36 stores not listed by the telephone business directories, while the telephone business directories listed 260 stores not listed by the SBOE. Spearman's correlation coefficients between estimates of stores per census tract made from the SBOE listings and those made from the telephone business directory listings were approximately 0.5 (p < .0001) for the types of stores studied (chain supermarkets, small grocery stores, and chain convenience markets). We conclude that, depending on the specific aims of the study, caution and considerable effort must be exercised in using and applying historical data on retail food stores.