Predicting county-level cancer incidence rates and counts in the USA.
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ABSTRACT:
SUBMITTER: Yu B
PROVIDER: S-EPMC5933533 | biostudies-literature | 2013 Sep
REPOSITORIES: biostudies-literature
Publications
Predicting county-level cancer incidence rates and counts in the USA.
Statistics in medicine 20130513 22
Many countries, including the USA, publish predicted numbers of cancer incidence and death in current and future years for the whole country. These predictions provide important information on the cancer burden for cancer control planners, policymakers and the general public. Based on evidence from several empirical studies, the joinpoint (segmented-line linear regression) model (JPM) has been adopted by the American Cancer Society to estimate the number of new cancer cases in the USA and in ind ...[more]
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Project description:BACKGROUND:Individual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains. METHODS:The EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status. RESULTS:Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality. CONCLUSION:We observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.
| S-EPMC6121813 | biostudies-literature
Project description:BACKGROUND:Debates over the importance of "lifestyle" versus "environment" contributions to cancer have been going on for over 40?years. While it is clear that cigarette smoking is the most significant cancer risk factor, the contributions of occupational and environmental carcinogens in air, water and food remain controversial. In practice, most cancer prevention messaging focuses on reducing cigarette smoking and changing other personal behaviors with little mention of environmental chemicals, despite widespread exposure to many known carcinogens. To inform decision-making on cancer prevention priorities, we evaluated the potential impact of smoking cessation on cancer rates. METHODS:Using cancer incidence data from 612 counties in the SEER database, and county-level smoking prevalences, we investigated the impact of smoking cessation on incidence for 12 smoking-related cancer types, 2006-2016. A multilevel mixed-effects regression model quantified the association between county-level smoking prevalence and cancer incidence, adjusting for age, gender and variability over time and among counties. We simulated complete smoking cessation and estimated the effects on county-level cancer rates. RESULTS:Regression models showed the expected strong association between smoking prevalence and cancer incidence. Simulating complete smoking cessation, the incidence of the 12 smoking-related cancer types fell by 39.8% (54.9% for airways cancers; 28.9% for non-airways cancers). And, while the actual rates of smoking-related cancers from 2006 to 2016 declined (annual percent change (APC)?=?-?0.8, 95% CI?=?-?1.0 to -?0.5%), under the scenario of smoking elimination, the trend in cancer incidence at these sites was not declining (APC?=?-?0.1, 95% CI?=?-?0.4 to +?0.1%). Not all counties were predicted to benefit equally from smoking elimination, and cancer rates would fall less than 10% in some counties. CONCLUSIONS:Smoking prevention has produced dramatic reductions in cancer in the US for 12 major types. However, we estimate that eliminating smoking completely would not affect about 60% of cancer cases of the 12 smoking-related types, leaving no improvement in the incidence trend from 2006 to 2016. We conclude that cancer prevention strategies should focus not only on lifestyle changes but also the likely contributions of the full range of risk factors, including environmental/occupational carcinogens.
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Project description:BackgroundMultiple studies have reported higher rates of glioma in areas with higher socioeconomic status (SES) but to the authors' knowledge have not stratified by other factors, including race/ethnicity or urban versus rural location.MethodsThe authors identified the average annual age-adjusted incidence rates and calculated hazard ratios for death for gliomas of various subtypes, stratified by a county-level index for SES, race/ethnicity, US region, and rural versus urban status.ResultsRates of glioma were highest in counties with higher SES (rate ratio, 1.18; 95% CI, 1.15-1.22 comparing the highest with the lowest quintiles [P < .001]). Stratified by race/ethnicity, higher rates in high SES counties persisted for white non-Hispanic individuals. Stratified by rural versus urban status, differences in incidence by SES were more pronounced among urban counties. Survival was higher for residents of high SES counties after adjustment for age and extent of surgical resection (hazard ratio, 0.82; 95% CI, 0.76-0.87 comparing the highest with the lowest quintile of SES [P < .001]). Survival was higher among white Hispanic, black, and Asian/Pacific Islander individuals compared with white non-Hispanic individuals, after adjustment for age, SES, and extent of surgical resection, and when restricted to those individuals with glioblastoma who received radiation and chemotherapy.ConclusionsThe incidence of glioma was higher in US counties of high compared with low SES. These differences were most pronounced among white non-Hispanic individuals and white Hispanic individuals residing in urban areas. Better survival was observed in high SES counties, even when adjusting for extent of surgical resection, and when restricted to those who received radiation and chemotherapy for glioblastoma. Differences in incidence and survival were associated with SES and race, rather than rural versus urban status.
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