Assessment of Interstate Residential Mobility of SEER Patients: SEER and LexisNexis Residential Address Linkage.

The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) program is continuously exploring opportunities to augment its already extensive collection of data, enhance the quality of reported cancer information, and contribute to more comprehensive analyses of cancer burden. This manuscript describes a recent linkage of the LexisNexis longitudinal residential history data with 11 SEER registries and provides estimates of the inter-state mobility of SEER cancer patients. To identify mobility from one state to another, we used state postal abbreviations to generate state-level residential histories. From this, we determined how often cancer patients moved from state-to-state. The results in this paper provide information on the linkage with LexisNexis data and useful information on state-to-state residential mobility patterns of a large portion of US cancer patients for the most recent 1-, 2-, 3-, 4-, and 5-year periods. We show that mobility patterns vary by geographic area, race/ethnicity and age, and cancer patients tend to move less than the general population.

Effects of Buffer Size and Shape on the Association of Neighborhood SES and Adult Fruit and Vegetable Consumption.

Introduction: Neighborhood environment factors are relevant for dietary behaviors, but associations between home neighborhood context and disease prevention behaviors vary depending on the definition of neighborhood. The present study uses a publicly available dataset to examine whether associations between neighborhood socioeconomic status (NSES) and fruit/vegetable (FV) consumption vary when NSES is defined by different neighborhood sizes and shapes. Methods: We analyzed data from 1,736 adults with data in GeoFLASHE, a geospatial extension of the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating Study (FLASHE). We examined correlations of NSES values across neighborhood buffer shapes (circular or street network) and sizes (ranging from 400 to 1,200 m) and ran weighted simple and multivariable regressions modeling frequency of FV consumption by NSES for each neighborhood definition. Regressions were also stratified by gender. Results: NSES measures were highly correlated across various neighborhood buffer definitions. In models adjusted for socio-demographics, circular buffers of all sizes and street buffers 750 m and larger were significantly associated with FV consumption frequency for women only. Conclusion: NSES may be particularly relevant for women's FV consumption, and further research can examine whether these associations are explained by access to food stores, food shopping behavior, and/or psychosocial variables. Although different NSES buffers are highly correlated, researchers should conceptually determine spatial areas a priori.

A national examination of neighborhood socio-economic disparities in built environment correlates of youth physical activity.

Adolescents in the U.S. do not meet current physical activity guidelines. Ecological models of physical activity posit that factors across multiple levels may support physical activity by promoting walkability, such as the neighborhood built environment and neighborhood socioeconomic status (nSES). We examined associations between neighborhood built environment factors and adolescent moderate-to-vigorous physical activity (MVPA), and whether nSES moderated associations. Data were drawn from a national sample of adolescents (12-17 years, N = 1295) surveyed in 2014. MVPA (minutes/week) were estimated from self-report validated by accelerometer data. Adolescents' home addresses were geocoded and linked to Census data from which a nSES Index and home neighborhood factors were derived using factor analysis (high density, older homes, short auto commutes). Multiple linear regression models examined associations between neighborhood factors and MVPA, and tested interactions between quintiles of nSES and each neighborhood factor, adjusting for socio-demographics. Living in higher density neighborhoods (B(SE): 9.22 (2.78), p = 0.001) and neighborhoods with more older homes (4.42 (1.85), p = 0.02) were positively associated with adolescent MVPA. Living in neighborhoods with shorter commute times was negatively associated with MVPA (-5.11 (2.34), p = 0.03). Positive associations were found between MVPA and the high density and older homes neighborhood factors, though associations were not consistent across quintiles. In conclusion, living in neighborhoods with walkable attributes was associated with greater adolescent MVPA, though the effects were not distributed equally across nSES. Adolescents living in lower SES neighborhoods may benefit more from physical activity interventions and environmental supports that provide opportunities to be active beyond neighborhood walkability.

The relationship between area poverty rate and site-specific cancer incidence in the United States.

BACKGROUND: The relationship between socioeconomic status and cancer incidence in the United States has not traditionally been a focus of population-based cancer surveillance systems. METHODS: Nearly 3 million tumors diagnosed between 2005 and 2009 from 16 states plus Los Angeles were assigned into 1 of 4 groupings based on the poverty rate of the residential census tract at time of diagnosis. The sex-specific risk ratio of the highest-to-lowest poverty category was measured using Poisson regression, adjusting for age and race, for 39 cancer sites. RESULTS: For all sites combined, there was a negligible association between cancer incidence and poverty; however, 32 of 39 cancer sites showed a significant association with poverty (14 positively associated and 18 negatively associated). Nineteen of these sites had monotonic increases or decreases in risk across all 4 poverty categories. The sites most strongly associated with higher poverty were Kaposi sarcoma, larynx, cervix, penis, and liver; those most strongly associated with lower poverty were melanoma, thyroid, other nonepithelial skin, and testis. Sites associated with higher poverty had lower incidence and higher mortality than those associated with lower poverty. CONCLUSIONS: These findings demonstrate the importance and relevance of including a measure of socioeconomic status in national cancer surveillance. Cancer 2014;120:2191-2198. © 2014 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

Confidence intervals for ranks of age-adjusted rates across states or counties.

Health indices provide information to the general public on the health condition of the community. They can also be used to inform the government's policy making, to evaluate the effect of a current policy or healthcare program, or for program planning and priority setting. It is a common practice that the health indices across different geographic units are ranked and the ranks are reported as fixed values. We argue that the ranks should be viewed as random and hence should be accompanied by an indication of precision (i.e., the confidence intervals). A technical difficulty in doing so is how to account for the dependence among the ranks in the construction of confidence intervals. In this paper, we propose a novel Monte Carlo method for constructing the individual and simultaneous confidence intervals of ranks for age-adjusted rates. The proposed method uses as input age-specific counts (of cases of disease or deaths) and their associated populations. We have further extended it to the case in which only the age-adjusted rates and confidence intervals are available. Finally, we demonstrate the proposed method to analyze US age-adjusted cancer incidence rates and mortality rates for cancer and other diseases by states and counties within a state using a website that will be publicly available. The results show that for rare or relatively rare disease (especially at the county level), ranks are essentially meaningless because of their large variability, while for more common disease in larger geographic units, ranks can be effectively utilized.

Multilevel predictors of colorectal cancer screening use in California.

BACKGROUND: Screening can detect colorectal cancer (CRC) early, yet its uptake needs to be improved. Social determinants of health (SDOH) may be linked to CRC screening use but are not well understood. OBJECTIVES: To examine geographic variation in CRC screening and the extent to which multilevel SDOH explain its use in California, the most populous and racially/ethnically diverse state in the United States. STUDY DESIGN: Analysis of individual and neighborhood data on 20,626 adult respondents aged >50 years from the 2005 California Health Interview Survey. METHODS: We used multilevel logistic regression models to estimate the effects of individual characteristics and area-level segregation, socioeconomic status (SES), and healthcare resources at 2 different geographic levels on CRC screening use. RESULTS: We confirmed that individual-level factors (eg, race/ethnicity, income, insurance) were strong predictors and found that area-level healthcare resources were associated with CRC screening. Primary care shortage in the Medical Service Study Area was associated with CRC screening for any modality (odds ratio [OR] = 0.89; 95% confidence interval [CI], 0.80-1.00). County-level HMO penetration (OR = 1.85; 95% CI, 1.47-2.33) and primary care shortage (OR = 0.73; 95% CI, 0.53-0.99) were associated with CRC screening with flexible sigmoidoscopy. CONCLUSIONS: Contextual factors including locality, primary care resources, and HMO membership are important determinants of CRC screening uptake; SES and segregation did not explain variation in screening behavior. More studies of contextual factors and varying geographic scales are needed to further elucidate their impact on CRC screening uptake.

Identifying clusters of active transportation using spatial scan statistics.

BACKGROUND: There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation. METHODS: Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008. RESULTS: Geographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC. CONCLUSIONS: The use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.