Rural/Nonrural Differences in Colorectal Cancer Incidence in the United States, 1998--2001

BACKGROUND. Few studies of colorectal cancer incidence by rural, suburban, and metropolitan residence have been published. METHODS. The authors examined colorectal cancer incidence among men and women in U.S. counties classified as rural, suburban, and metropolitan for the period 1998–2001. They examined rural/suburban/metropolitan differences in incidence by age, race, Hispanic ethnicity, stage at diagnosis, histology, and percentage of the total county population below the poverty level, using data from the CDC’s National Program of Cancer Registries, the NCI’s Surveillance, Epidemiology, and End Results Program, and the 2000 U.S. Census. RESULTS. A total of 495,770 newly diagnosed or incident cases of colorectal cancer were included in this analysis (249,919 among men and 245,851 among women). Over the period 1998–2001, the colorectal cancer incidence rates among men tended to be lower among those who resided in rural areas, for each of the subgroups examined, with the exception of Asians and Pacific Islanders and those living in more affluent counties. Among women aged 75 years and older, the colorectal cancer incidence rates tended to be lower among rural than metropolitan or suburban residents, though the differences were slight. In multivariate analysis, the incidence of colorectal cancer was higher in metropolitan, suburban, and rural areas for blacks than that for whites (incidence rate ratios [RR] = 1.12, 1.07, and 1.06, respectively, all P \u3c 0.015). CONCLUSIONS. This study suggests that black men who reside in metropolitan areas have a higher risk of colorectal cancer than black men who reside in rural areas. This finding suggests the need for diverse approaches for reducing colorectal cancer when targeting rural compared with metropolitan areas

Use of attribute association error probability estimates to evaluate quality of medical record geocodes

BACKGROUND: The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. METHODS: A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. RESULTS: We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. CONCLUSIONS: The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics

Use of attribute association error probability estimates to evaluate quality of medical record geocodes

BACKGROUND: The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. METHODS: A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. RESULTS: We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. CONCLUSIONS: The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics

Are Cancer Survivors Physically Active? A Comparison by US States

Cancer survivors who engage in physical activity (PA) have improved quality of life, reduced fatigue, and lower mortality rates. We compare the percentage of cancer survivors meeting PA recommendations for US states, stratified by age and gender, to identify the need for PA education and intervention among cancer survivors. Pooled data from the 1997-2010 National Health Interview Survey were used to determine and rank age-adjusted PA by state. American Cancer Society guidelines (≥150 min/wk of PA) were used to compare prevalence by state, stratified by age group (< 65 and ≥65) and gender. Thirty-three percent of cancer survivors met PA recommendations. The highest age-adjusted compliance to PA recommendations was in Vermont (59.9%, 95% confidence interval [CI], 40.8-76.3) and the lowest was in Louisiana (14.8%, 95% CI, 9.6-22.1) and Mississippi (15.5%, 95% CI, 10.4-22.3). The lowest percentages meeting recommendations were in Arkansas for males (8.6%, 95% CI, 7.0-10.6), Louisiana for females (12.5%, 95% CI, 6.8-21.9), Louisiana for survivors < 65 (15.6%, 95% CI, 10.5-22.6), and West Virginia for those ≥65 years (12.7%, 95% CI, 7.6-20.6). Meeting PA recommendations by cancer survivors varies markedly by state of residence. Future efforts should target states with low percentages, tailoring interventions to the special needs of this high-risk population. The importance of PA should be incorporated within cancer survivorship care plans

Fileset to accompany "The relationship between cancer incidence, stage, and poverty in the United States"

<p>This fileset contains 3 data sets referenced in the paper, "The relationship between cancer incidence, stage, and poverty in the United States", submitted as a preprint in September 2015 to the University at Albany preprint server.</p

Relative risk of cancer incidence by site, stage, and poverty level

<p>These are the data used to generate Figure 1 in the manuscript, "The relationship between cancer incidence, stage, and poverty in the United States". The relative risks are relative to the lowest poverty group (<5% poverty). Confidence intervals are 95% CIs. The poisson regression model used to generate these results modeled expected counts based on age, sex, race, poverty, and log-population.</p

Estimates of the influence of poverty on national cancer counts, by site and stage

<p>These are the data used to generate Figure 2 in the manuscript, "The relationship between cancer incidence, stage, and poverty in the United States". The variable 'count' represents the actual single year case counts in the areas included in the study (16 states+Los Angeles) projected to the entire US. The variable 'countnopov' represents the expected case counts were all persons to be in the lowest poverty category, all other things being equal.</p

Relative risk of cancer incidence by site, stage, and poverty level

<p>These are the data used to generate Figure 1 in the manuscript, "The relationship between cancer incidence, stage, and poverty in the United States". The relative risks are relative to the lowest poverty group (<5% poverty). Confidence intervals are 95% CIs. The poisson regression model used to generate these results modeled expected counts based on age, sex, race, poverty, and log-population.</p

Cancer counts and populations by site, stage, sex, poverty, race, and age

<p>This is a file containing cancer counts and populations stratified by site (21 most common stageable sites plus tobacco-related, HPV-related, and all stageable sites combined), stage (local, regional, distant, unknown), sex, census tract poverty category (<5%, 5-9.9%, 10-19.9% and 20+% of households in the census tract of residence at diagnosis below poverty level as measured by the 2005-2009 American Community Survey), race (white, black, Asian and Pacific Islander, American Indian and Alaska Native, Hispanic), and age (0, 1-4, 5-9, then 5 year groups through 80-84, 85+) for 16 US states plus Los Angelese. These data are being used in the manuscript in preparation, "The relationship between cancer incidence, stage, and poverty in the United States". The populations were customized for this project, but are consistent with the populations published here: http://seer.cancer.gov/popdata/</p

Associations of Census-Tract Poverty with Subsite-Specific Colorectal Cancer Incidence Rates and Stage of Disease at Diagnosis in the United States

Background. It remains unclear whether neighborhood poverty contributes to differences in subsite-specific colorectal cancer (CRC) incidence. We examined associations between census-tract poverty and CRC incidence and stage by anatomic subsite and race/ethnicity. Methods. CRC cases diagnosed between 2005 and 2009 from 15 states and Los Angeles County (N=278,097) were assigned to 1 of 4 groups based on census-tract poverty. Age-adjusted and stage-specific CRC incidence rates (IRs) and incidence rate ratios (IRRs) were calculated. Analyses were stratified by subsite (proximal, distal, and rectum), sex, race/ethnicity, and poverty. Results. Compared to the lowest poverty areas, CRC IRs were significantly higher in the most impoverished areas for men (IRR = 1.14 95% CI 1.12–1.17) and women (IRR = 1.06 95% CI 1.05–1.08). Rate differences between high and low poverty were strongest for distal colon (male IRR = 1.24 95% CI 1.20–1.28; female IRR = 1.14 95% CI 1.10–1.18) and weakest for proximal colon. These rate differences were significant for non-Hispanic whites and blacks and for Asian/Pacific Islander men. Inverse associations between poverty and IRs of all CRC and proximal colon were found for Hispanics. Late-to-early stage CRC IRRs increased monotonically with increasing poverty for all race/ethnicity groups. Conclusion. There are differences in subsite-specific CRC incidence by poverty, but associations were moderated by race/ethnicity