There have been articles on comparing methods for global clustering evaluation and cluster detection in disease surveillance, but power and sample size requirements have not been explored for spatially correlated data in this area. We are developing such requirements for tests of spatial clustering and cluster detection for regional cancer cases. We compared global clustering methods including Moran's I, Tango's and Besag-Newell's R statistics, and cluster detection methods including circular and elliptic spatial scan statistics (SaTScan), flexibly shaped spatial scan statistics (FSS), Turnbull's cluster evaluation permutation procedure (CEPP), local indicators of spatial association (LISA), and upper level set (ULS) scan statistics. We identified eight geographic patterns that are representative of patterns of mortality due to various types of cancer in the United States from 1998-2002. We then evaluated the selected spatial methods based on state-and county-level data simulated from these different spatial patterns in terms of geographic locations and relative risks, and varying sample sizes using the 2000 population in each county. The comparison provides insight into the performance of the spatial methods when applied to varying cancer count data in terms of power and precision of cluster detection.

Objective To provide cancer patients and clinicians with more accurate estimates of a patient’s life expectancy with respect to non-cancer mortality, we estimated comorbidity-adjusted life tables and health-adjusted age. Study Design and Setting Using data from the SEER-Medicare database, we estimated comorbidity scores that reflect the health status of people 66 years of age and older in the year prior to cancer diagnosis. Non-cancer survival by comorbidity score was estimated for each age, race and sex. Health-adjusted age was estimated by systematically comparing the non-cancer survival models with US life tables. Results Comorbidity, cancer status, sex and race are all important predictors of non-cancer survival; however, their relative impact on non-cancer survival decreases as age increases. Survival models by comorbidity better predicted non-cancer survival than the US life tables. The health-adjusted age and national life tables can be consulted to provide an approximate estimate of a person’s life expectancy, e.g., the health-adjusted age of a black man aged 75 with no comorbidities is 67, giving him a life expectancy of 13 years. Conclusions The health-adjusted age and the life tables adjusted by age, race, sex and comorbidity, can provide important information to facilitate decision-making about treatment for cancer and other conditions.

The Centers for Disease Control and Prevention's Youth Media Campaign designed VERB TM as an aspirational brand to increase physical activity among children aged 9-13 years. In the current study, we explore the influence of the VERB TM brand in the campaign using a brand equity framework. Brand equity responses were collected from 1,007 children from a national cross-sectional telephone survey. Findings indicated that high VERB brand equity was associated with increased positive attitudes toward physical activity and participation in free-time physical activity. The relationship between brand equity and free-time physical activity was partially mediated through attitudes. Brand personality and leadership=popularity constructs were found to be strong predictors in determining physical activity attitudes and behaviors, respectively. As the use of a branding strategy increases in public health, brand equity offers social marketers a framework for evaluating the effectiveness of their efforts. IntroductionThe Centers for Disease Control and Prevention (CDC) used a branding strategy for VERB TM , a campaign that used mass media, school and community promotions, and national partnerships to promote physical activity among children aged 9-13 years (tweens). As is typically done in commercial brand development, campaign planners for VERB conducted extensive formative research with tweens to discover how to create a brand for them that would connect physical activity to

The results of the two analyses appear to show a moderate effect of mammography usage on decreasing breast cancer mortality in the US, which seems to support the conclusions of randomized mammographic screening trials. While randomized controlled trials are certainly the gold standard in appraising the efficacy of new screening or treatment modalities, such trials are conducted under standardized conditions and do not always reflect the effect of these interventions at population level. This paper attempts to examine population level effects through ecologic analyses. Results, however, need to be interpreted cautiously owing to the limitations and biases inherent in such analyses.