Developing Geographic Areas for Cancer Reporting Using Automated Zone Design.

The reporting and analysis of population-based cancer statistics in the United States has traditionally been done for counties. However, counties are not ideal for analysis of cancer rates, due to wide variation in population size, with larger counties having considerable sociodemographic variation within their borders and sparsely populated counties having less reliable estimates of cancer rates that are often suppressed due to confidentiality concerns. There is a need and an opportunity to utilize zone design procedures in the context of cancer surveillance to generate coherent, statistically stable geographic units that are more optimal for cancer reporting and analysis than counties. To achieve this goal, we sought to create areas within each US state that are: 1) similar in population size and large enough to minimize rate suppression; 2) sociodemographically homogeneous; 3) compact; and 4) custom crafted to represent areas that are meaningful to cancer registries and stakeholders. The resulting geographic units reveal the heterogeneity of rates that are hidden when reported at the county-level while substantially reducing the need to suppress data. We believe this effort will facilitate more meaningful comparative analysis of cancer rates for small geographic areas and will advance the understanding of cancer burden in the United States.

Survey of Surgical Oncology Fellowship Graduates 2005-2016: Insight into Initial Practice.

BACKGROUND: Despite burgeoning interest in Complex General Surgical Oncology (CGSO) fellowship training, little is reported about postgraduate employment. The goal of this study was to characterize CGSO graduates' first employment and to identify factors that influenced this decision. METHODS: The National Cancer Institute (NCI) and Society of Surgical Oncology developed and distributed an electronic survey to CGSO fellows who graduated from 2005 to 2016. RESULTS: The survey response rate was 47% (237/509). Fifty-seven percent of respondents were first employed as faculty surgeons at a university-based/affiliated hospital, with 15% returning to their residency institution. The distribution of respondents' current employment across the United States mirrored the locations of their hometowns. Eighty-five percent of respondents care for patients across at least three disease types, most commonly hepatopancreatobiliary (81%), esophagus/gastric (75%), and sarcoma (74%). Twenty-seven percent of respondents spend the majority of their time in one area of surgical oncology; melanoma, breast, and head/neck were the most common. Two-thirds of respondents (67%) reported that they performed either clinical or basic science research as part of their current position. Multiple factors influenced the decision of first faculty position. CONCLUSIONS: Most CGSO graduates are employed at academic medical centers across the country in proximity to NCI-designated centers, treat a variety of disease types, and spend a percentage of their time dedicated to clinical research.

Cumulative solar ultraviolet radiation exposure and basal cell carcinoma of the skin in a nationwide US cohort using satellite and ground-based measures.

BACKGROUND: Basal cell carcinoma of the skin (BCC) is the most common cancer in populations of European ancestry. Although consistently linked with basal cell carcinoma of the skin in case-control studies, few prospective cohort studies have evaluated the shape of the exposure-response of basal cell carcinoma associated with cumulative radiant solar ultraviolet exposure (UVR). METHODS: We followed 63,912 white cancer-free US radiologic technologists from entry (1983-1998) to exit (2003-2005) with known ultraviolet irradiance at up to 5 residential locations. Using generalized-additive and relative risk models we analyzed the exposure-response of basal cell carcinomas associated with ambient cumulative ultraviolet radiant exposure using ground-based National Solar Radiation database Average Daily Total Global data and satellite-based National Aeronautics and Space Administration Total Ozone Mapping Spectrometer data. RESULTS: There were 2151 technologists with an incident primary basal cell carcinoma. Risk of basal cell carcinoma rose with increasing cumulative ultraviolet radiation exposure using both measures, such that 1 MJ cm- 2 increased basal cell carcinoma risk by 8.48 (95% CI 5.22, 11.09, p < 0.001) and by 10.15 (95% CI 6.67, 13.10, p < 0.001) per 10,000 persons per year using the Average Daily Total Global and Total Ozone Mapping Spectrometer ultraviolet data, respectively; relative risk was likewise elevated. There was some evidence of upward curvature in the cumulative ultraviolet exposure response using both exposure measures with a greater increase in risk of basal cell carcinoma at higher levels of ultraviolet radiation exposure, but less evidence for curvature in relative risk. There are indications of substantial variation of relative risk with time after exposure and age at exposure, so that risk is highest for the period 10-14 years after ultraviolet radiation exposure and for those exposed under the age of 25. CONCLUSIONS: We observed increases in risk of basal cell carcinoma and a similar exposure-response for ground-based and satellite ultraviolet radiation measures. Our observations suggest that interventions should concentrate on persons with higher levels of ultraviolet radiation exposure.

Using Gini coefficient to determining optimal cluster reporting sizes for spatial scan statistics.

BACKGROUND: Spatial and space-time scan statistics are widely used in disease surveillance to identify geographical areas of elevated disease risk and for the early detection of disease outbreaks. With a scan statistic, a scanning window of variable location and size moves across the map to evaluate thousands of overlapping windows as potential clusters, adjusting for the multiple testing. Almost always, the method will find many very similar overlapping clusters, and it is not useful to report all of them. This paper proposes to use the Gini coefficient to help select which of the many overlapping clusters to report. METHODS: The Gini coefficient provides a quick and intuitive way to evaluate the degree of the heterogeneity of the collection of clusters, which is useful to explain how well the cluster collection reveal the underlying true cluster patterns. Using simulation studies and real cancer mortality data, it is compared with the traditional approach for reporting non-overlapping clusters. RESULTS: The Gini coefficient can identify a more refined collection of non-overlapping clusters to report. For example, it is able to determine when it makes more sense to report a collection of smaller non-overlapping clusters versus a single large cluster containing all of them. It also fulfils a set of desirable theoretical properties, such as being invariant under a uniform multiplication of the population numbers by the same constant. CONCLUSIONS: The Gini coefficient can be used to determine which set of non-overlapping clusters to report. It has been implemented in the free SaTScan™ software version 9.3 ( www.satscan.org ).

Geographic disparities in late stage breast cancer incidence: results from eight states in the United States.

BACKGROUND: Late stage of cancer at diagnosis is an important predictor of cancer mortality. In many areas worldwide, cancer registry systems, available data and mapping technologies can provide information about late stage cancer by geographical regions, offering valuable opportunities to identify areas where further investigation and interventions are needed. The current study examined geographical variation in late stage breast cancer incidence across eight states in the United States with the objective to identify areas that might benefit from targeted interventions. METHODS: Data from the Surveillance Epidemiology and End Results Program on late stage breast cancer incidence was used as dependent variable in regression analysis and certain factors known to contribute to high rates of late stage cancer (socioeconomic characteristics, health insurance characteristics, and the availability and utilization of cancer screening) as covariates. Geographic information systems were used to map and highlight areas that have any combination of high late stage breast cancer incidence and significantly associated risk factors. RESULTS: The differences in mean rates of late stage breast cancer between eight states considered in this analysis are statistically significant. Factors that have statistically negative association with late stage breast cancer incidence across the eight states include: density of mammography facilities, percent population with Bachelor's degree and English literacy while percent black population has statistically significant positive association with late stage breast cancer incidence. CONCLUSIONS: This study describes geographic disparities in late stage breast cancer incidence and identifies areas that might benefit from targeted interventions. The results suggest that in the eight US states examined, higher rates of late stage breast cancer are more common in areas with predominantly black population, where English literacy, percentage of population with college degree and screening availability are low. The approach described in this work may be utilized both within and outside US, wherever cancer registry systems and technologies offer the same opportunity to identify places where further investigation and interventions for reducing cancer burden are needed.

Using a composite index of socioeconomic status to investigate health disparities while protecting the confidentiality of cancer registry data.

PURPOSE: The lack of individual socioeconomic status (SES) information in cancer registry data necessitates the use of area-based measures to investigate health disparities. Concerns about confidentiality, however, prohibit publishing patients' residential locations at the subcounty level. We developed a census tract-based composite SES index to be released in place of individual census tracts to minimize the risk of disclosure. METHODS: Two SES indices based on the measures identified in the literature were constructed using factor analysis. The analyses were repeated using the data from the 2000 decennial census and 2005-2009 American Community Survey to create the indices at two time points, which were linked to 2000-2009 Surveillance, Epidemiology, and End Results registry data to estimate incidence and survival rates. RESULTS: The two indices performed similarly in stratifying census tracts and detecting socioeconomic gradients in cancer incidence and survival. The gradient in the incidence is positive for breast and prostate, and negative for lung cancers, in all races, although the level varies. The positive gradient in survival is more salient for regional-staged breast, colorectal, and lung cancers. CONCLUSIONS: The census tract-based SES index provides a valuable tool for monitoring the disparities in cancer burdens while avoiding potential identity disclosure. This index, divided into tertiles and quintiles, is now available to the researchers on request.

Urban sprawl, obesity, and cancer mortality in the United States: cross-sectional analysis and methodological challenges.

BACKGROUND: Urban sprawl has the potential to influence cancer mortality via direct and indirect effects on obesity, access to health services, physical activity, transportation choices and other correlates of sprawl and urbanization. METHODS: This paper presents a cross-sectional analysis of associations between urban sprawl and cancer mortality in urban and suburban counties of the United States. This ecological analysis was designed to examine whether urban sprawl is associated with total and obesity-related cancer mortality and to what extent these associations differed in different regions of the US. A major focus of our analyses was to adequately account for spatial heterogeneity in mortality. Therefore, we fit a series of regression models, stratified by gender, successively testing for the presence of spatial heterogeneity. Our resulting models included county level variables related to race, smoking, obesity, access to health services, insurance status, socioeconomic position, and broad geographic region as well as a measure of urban sprawl and several interactions. Our most complex models also included random effects to account for any county-level spatial autocorrelation that remained unexplained by these variables. RESULTS: Total cancer mortality rates were higher in less sprawling areas and contrary to our initial hypothesis; this was also true of obesity related cancers in six of seven U.S. regions (census divisions) where there were statistically significant associations between the sprawl index and mortality. We also found significant interactions (p < 0.05) between region and urban sprawl for total and obesity related cancer mortality in both sexes. Thus, the association between urban sprawl and cancer mortality differs in different regions of the US. CONCLUSIONS: Despite higher levels of obesity in more sprawling counties in the US, mortality from obesity related cancer was not greater in such counties. Identification of disparities in cancer mortality within and between geographic regions is an ongoing public health challenge and an opportunity for further analytical work identifying potential causes of these disparities. Future analyses of urban sprawl and health outcomes should consider exploring regional and international variation in associations between sprawl and health.

A National Map of NCI-Designated Cancer Center Catchment Areas on the 50th Anniversary of the Cancer Centers Program.

BACKGROUND: In 1971, the National Cancer Act created a process to recognize the leadership, facilities, and research efforts at cancer centers throughout the United States. Toward this goal, each NCI-designated cancer center defines and describes a catchment area to which they tailor specific scientific and community engagement activities. METHODS: The geographically defined catchment areas of 63 NCI-designated comprehensive and clinical cancer centers are collated and presented visually. In addition, the NCI-designated cancer center catchment areas are geographically linked with publicly available data sources to aggregate sociodemographic and epidemiologic characteristics across the NCI Cancer Centers Program. RESULTS: The national map portrays the size, shape, and locations for 63 catchment areas of the 71 NCI-designated cancer centers. The findings illustrate the geographic extent of the NCI Cancer Centers Program during the 50th anniversary of the National Cancer Act. CONCLUSIONS: NCI-designated cancer centers occupy a prominent role in the cancer control ecosystem and continue to perform research to address the burden of cancer among their local communities. The strength of the NCI Cancer Centers Program is partly defined by the scope, quality, and impact of community outreach and engagement activities in the catchment areas. IMPACT: The collation and geographic presentation of the distinct, but complementary, NCI-designated cancer center catchment areas are intended to support future research and community outreach activities among NCI-designated cancer centers. See related commentary by Vadaparampil and Tiro, p. 952.

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.

Association between cutaneous melanoma incidence rates among white US residents and county-level estimates of solar ultraviolet exposure.

BACKGROUND: Recent US studies have raised questions as to whether geographic differences in cutaneous melanoma incidence rates are associated with differences in solar ultraviolet (UV) exposure. OBJECTIVES: We sought to assess the association of solar UV exposure with melanoma incidence rates among US non-Hispanic whites. METHODS: We assessed the association between county-level estimates of average annual solar UV exposure for 1961 to 1990 and county-level melanoma incidence rates during 2004 to 2006. We used Poisson multilevel mixed models to calculate incidence density ratios by cancer stage at diagnosis while controlling for individuals' age and sex and for county-level estimates of solar UV exposure, socioeconomic status, and physician density. RESULTS: Age-adjusted rates of early- and late-stage melanoma were both significantly higher in high solar UV counties than in low solar UV counties. Rates of late-stage melanoma incidence were generally higher among men, but younger women had a higher rate of early-stage melanoma than their male counterparts. Adjusted rates of early-stage melanoma were significantly higher in high solar UV exposure counties among men aged 35 years or older and women aged 65 years or older. LIMITATIONS: The relationship between individual-level UV exposure and risk for melanoma was not evaluated. CONCLUSIONS: County-level solar UV exposure was associated with the incidence of early-stage melanoma among older US adults but not among younger US adults. Additional studies are needed to determine whether exposure to artificial sources of UV exposure or other factors might be mitigating the relationship between solar UV exposure and risk for melanoma.

Triple-negative breast cancer incidence in the United States: ecological correlations with area-level sociodemographics, healthcare, and health behaviors.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer, more commonly diagnosed among black women than other subgroups. TNBC varies geographically, but little is known about area-level characteristics associated with elevated incidence. METHODS: We generated 2011-2013 age-adjusted TNBC incidence rates for state economic areas (SEAs) in 43 states using data from North American Association of Central Cancer Registries. For cases missing data on molecular markers, we imputed TNBC status using cross-marginal proportions. We linked these data to SEA covariates from national sources. Using linear ecological regression, we examined correlates of TNBC incidence rates for the overall population and for age (< 50 years or 50 + years)- or race (white or black)-specific subgroups. RESULTS: The mean annual incidence of TNBC across SEAs was 13.7 per 100,000 women (range = 4.5-26.3), with especially high and variable rates among African American women (mean = 20.5, range 0.0-155.1). TNBC incidence was highest in South Atlantic and East South Central Census Divisions and lowest in Mountain Division. Overall TNBC incidence was associated with SEA sociodemographics (e.g., percent of females age 45 + who are non-Hispanic black: coefficient estimate [est.] = 1.62), healthcare characteristics (e.g., percent of population without health insurance: est. = - 0.52), and health behaviors (e.g., prevalence of obesity among women: est. = 0.72) (all p < 0.05). Other variables related to TNBC incidence included density of obstetrician/gynecologists and prevalence of smoking. CONCLUSION: TNBC incidence varied across SEAs in the U.S., particularly for African American women. Identifying areas with elevated TNBC incidence can facilitate research and interventions on area- and individual-level correlates of TNBC.

Trends in Mortality From Drug Poisonings, Suicide, and Alcohol-Induced Deaths in the United States From 2000 to 2017.

Importance: Life expectancy has decreased in the US, driven largely by increases in drug poisoning, suicide, and alcohol-induced deaths. Assessing whether patterns of these causes differ is required to inform public health interventions. Objective: To compare patterns and trends in drug poisoning, suicide, and alcohol-induced death rates by geography and demographic characteristics. Design, Setting, and Participants: This serial cross-sectional study used national vital statistics data from the entire US population from January 1, 2000, to December 31, 2017, among US residents aged 20 to 64 years. Data were analyzed from January through August 2019. Exposures: Age, sex, race/ethnicity, county-level percentage of unemployment, rurality, and geography. Main Outcomes and Measures: Deaths were categorized as due to drug poisoning, suicide, or alcohol-induced causes based on underlying cause of death. Age-standardized incidence rates and annual percentage changes (APCs) in rates were estimated. Clusters of high-rate counties were identified with hot spot analysis. Excess deaths during 2001 to 2017 were estimated for each cause as the difference between the number of deaths observed and expected if rates had remained stable starting in 2000. Results: During 2000 to 2017, 1 446 177 drug poisoning, suicide, and alcohol-induced premature deaths occurred in the US, including 563 765 drug poisoning deaths (age-standardized rate: 17.6 per 100 000 person-years [PYs]), 517 679 suicides (age-standardized rate: 15.8 per 100 000 PYs), and 364 733 alcohol-induced deaths (age-standardized rate: 10.5 per 100 000 PYs), totaling 451 596 more deaths than expected based on 2000 rates. High drug poisoning death rates were clustered in the Northeast through Appalachia, yet rates of suicide and alcohol-induced deaths were highest in the West. Only suicide death rates were highest in rural areas. Drug poisoning death rates were highest among people aged 35 to 49 years (age-standardized rate: 23.7 per 100 000 PYs), whereas suicide and alcohol-induced death rates peaked among people aged 50 to 64 years (suicide age-standardized rate: 19.6 per 100 000 PYs; alcohol-induced age-standardized death rate: 26.8 per 100 000 PYs). Increases occurred over time across racial/ethnic groups, although trajectories and inflection years varied. Drug poisoning (2013-2017 APC, 15.0% [95% CI, 11-8%-18.3%] per year) and alcohol-induced death rates (2012-2017 APC, 4.1% [95% CI, 3.3%-4.9%] per year) have accelerated recently, while increases in suicide death rates have largely increased at a constant trajectory (2000-2017 APC, 1.8% [95% CI, 1.7%-1.9%] per year). Conclusions and Relevance: This cross-sectional study found that demographic characteristics and geographic patterns varied by cause of death, suggesting that increasing death rates from these causes were not concentrated in 1 group or region. Specialized interventions tailored for the underlying drivers of each cause of death are urgently needed.

Associations between Urban Sprawl and Life Expectancy in the United States.

In recent years, the United States has had a relatively poor performance with respect to life expectancy compared to the other developed nations. Urban sprawl is one of the potential causes of the high rate of mortality in the United States. This study investigated cross-sectional associations between sprawl and life expectancy for metropolitan counties in the United States in 2010. In this study, the measure of life expectancy in 2010 came from a recently released dataset of life expectancies by county. This study modeled average life expectancy with a structural equation model that included five mediators: annual vehicle miles traveled (VMT) per household, average body mass index, crime rate, and air quality index as mediators of sprawl, as well as percentage of smokers as a mediator of socioeconomic status. After controlling for sociodemographic characteristics, this study found that life expectancy was significantly higher in compact counties than in sprawling counties. Compactness affects mortality directly, but the causal mechanism is unclear. For example, it may be that sprawling areas have higher traffic speeds and longer emergency response times, lower quality and less accessible health care facilities, or less availability of healthy foods. Compactness affects mortality indirectly through vehicle miles traveled, which is a contributor to traffic fatalities, and through body mass index, which is a contributor to many chronic diseases. This study identified significant direct and indirect associations between urban sprawl and life expectancy. These findings support further research and practice aimed at identifying and implementing changes to urban planning designed to support health and healthy behaviors.

Improving Assessment of Lifetime Solar Ultraviolet Radiation Exposure in Epidemiologic Studies: Comparison of Ultraviolet Exposure Assessment Methods in a Nationwide U.S. Occupational Cohort.

Solar ultraviolet radiation is the primary risk factor for skin cancers and sun-related eye disorders. Estimates of individual ambient ultraviolet irradiance derived from ground-based solar measurements and from satellite measurements have rarely been compared. Using self-reported residential history from 67 189 persons in a nationwide occupational US radiologic technologists' cohort, we estimated ambient solar irradiance using data from ground-based meters and noontime satellite measurements. The mean distance moved from city of longest residence in childhood increased from 137.6 km at ages 13-19 to 870.3 km at ages ≥65, with corresponding increases in absolute latitude difference moved. At ages 20/40/60/80, the Pearson/Spearman correlation coefficients of ground-based and satellite-derived potential solar ultraviolet exposure, using irradiance and cumulative radiant exposure metrics, were high (=0.87-0.92). There was also moderate correlation (Pearson/Spearman correlation coefficients = 0.51-0.60) between irradiance at birth and at last-known address, for ground-based and satellite data. Satellite-based lifetime estimates of ultraviolet radiation were generally 14-15% lower than ground-based estimates, albeit with substantial uncertainties, possibly because ground-based estimates incorporate fluctuations in cloud and ozone, which are incompletely incorporated in the single noontime satellite-overpass ultraviolet value. If confirmed elsewhere, the findings suggest that ground-based estimates may improve exposure assessment accuracy and potentially provide new insights into ultraviolet radiation-disease relationships in epidemiologic studies.

The association between contextual socioeconomic factors and prevalent asthma in a cohort of Southern California school children.

Spatial variation in childhood asthma and a recent increase in prevalence indicate that environmental factors play a significant role in the etiology of this important disease. Socioeconomic position (SEP) has been associated inversely and positively with childhood asthma. These contradictory results indicate a need for systematic research about SEP and asthma. Pathways have been suggested for effects of SEP on asthma at both the individual and community level. We examined the relationship of prevalent asthma to community-level indicators of SEP among 5762 children in 12 Southern California communities, using a multilevel random effects model. Estimates of community-level SEP were derived by summarizing census block group-level data using a novel method of weighting by the proportion of the block groups included in a community-specific bounding rectangle that contained 95% of local study subjects. Community characteristics included measures of male unemployment, household income, low education (i.e., no high school diploma) and poverty. There was a consistent inverse association between male unemployment and asthma across the inter-quartile range of community unemployment rates, indicating that asthma rates increase as community SEP increases. The results were robust to individual-level confounding, methods for summarizing census block group data to the community level, scale of analysis (i.e., community-level vs. neighborhood-level) and the modeling algorithm. The positive association between SEP and prevalent childhood asthma might be explained by differential access to medical care that remains unmeasured, by the hygiene hypothesis (e.g., lower SES may associate with higher protective exposures to endotoxin in early life), or by SEP acting as a proxy for unmeasured neighborhood characteristics.

A geo-view into historical patterns of smoke-free policy coverage in the USA.

INTRODUCTION: Ample evidence shows that implementation of smoke-free policies can significantly reduce tobacco use. The indoor smoke-free policy coverage in the U.S. increased over the past 25 years. This study synthesized the available historical smoke-free policy data and achieved two complementary goals: 1) reconstructed historical patterns of indoor smoke-free policy coverage in the U.S., and 2) developed a web-based interactive tool for visualization and download of the U.S. historical smoke-free policy data for research. METHODS: Historical information on local and regional smoke-free policy was downloaded from the American Nonsmokers Rights Foundation (ANRF). Subsequent methodological processes included: geo-referencing of smoke-free policy data, spatial-temporal data linkage, spatial pattern analysis, data visualization, and the development of an interactive tool. RESULTS: The percentage of population covered by the smoke-free policies varies across the different geographic locations, scales, and over time. On average, the percentage of people covered by the smoke-free laws in the U.S. increased substantially in the recent decade. The Tobacco-Policy-Viewer reveals geographic patterns of increase in smoke-free policy adoption by cities, counties, and States over time. CONCLUSION: The utility of visualizing the historical patterns of smoke-free policy coverage in the U.S. is to understand where and for how long smoke-free policies were in place for indoor facilities and to inform planning for education and interventions in the areas of need. The benefit of data provided for download, via the Tobacco-Policy-Viewer, is to catalyze future research on the impacts of historical smoke-free policy coverage on reduction in secondhand-smoke exposures, tobacco use, and tobacco related diseases.

Geospatial Approaches to Cancer Control and Population Sciences.

Cancer incidence and mortality display strong geographic patterns worldwide and in the United States (1, 2). The environment where individuals live, work, and play is increasingly being recognized as important across the cancer control continuum, including the risk of cancer development, detection, diagnosis, treatment, mortality, and survivorship (3-5). At the same time, emergent technological capacity in geographic information systems (GIS) and mapping, along with increasing sophistication in applied spatial methods, has resulted in a growing research community developing and applying geospatial approaches in health research (5). Through collaborative, transdisciplinary efforts, and continued data collection efforts, there is great potential to apply these emerging geospatial approaches to various aspects of cancer prevention and control to inform etiology and target interventions and implementation of efficacious risk-reducing strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 472-5. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Competing definitions of contextual environments.

BACKGROUND: The growing interest in the effects of contextual environments on health outcomes has focused attention on the strengths and weaknesses of alternate contextual unit definitions for use in multilevel analysis. The present research examined three methods to define contextual units for a sample of children already enrolled in a respiratory health study. The Inclusive Equal Weights Method (M1) and Inclusive Sample Weighted Method (M2) defined communities using the boundaries of the census blocks that incorporated the residences of the CHS participants, except that the former estimated socio-demographic variables by averaging the census block data within each community, while the latter used weighted proportion of CHS participants per block. The Minimum Bounding Rectangle Method (M3) generated minimum bounding rectangles that included 95% of the CHS participants and produced estimates of census variables using the weighted proportion of each block within these rectangles. GIS was used to map the locations of study participants, define the boundaries of the communities where study participants reside, and compute estimates of socio-demographic variables. The sensitivity of census variable estimates to the choice of community boundaries and weights was assessed using standard tests of significance. RESULTS: The estimates of contextual variables vary significantly depending on the choice of neighborhood boundaries and weights. The choice of boundaries therefore shapes the community profile and the relationships between its components (variables). CONCLUSION: Multilevel analysis concerned with the effects of contextual environments on health requires careful consideration of what constitutes a contextual unit for a given study sample, because the alternate definitions may have differential impact on the results. The three alternative methods used in this research all carry some subjectivity, which is embedded in the decision as to what constitutes the boundaries of the communities. The Minimum Bounding Rectangle was preferred because it focused attention on the most frequently used spaces and it controlled potential aggregation problems. There is a need to further examine the validity of different methods proposed here. Given that no method is likely to capture the full complexity of human-environment interactions, we would need baseline data describing people's daily activity patterns along with expert knowledge of the area to evaluate our neighborhood units.

The objective assessment of lifetime cumulative ultraviolet exposure for determining melanoma risk.

Exposure to ultraviolet radiation has commonly been recognized as the most important environmental risk factor for melanoma. The measurement of UV exposure in humans, however, has proved challenging. Despite the general appreciation that an objective metric for individual UV exposure is needed to properly assess melanoma risk, little attention has been given to the issue of accuracy of UV exposure measurement. The present research utilized a GIS based historical UV exposure model (for which the accuracy of exposure estimates is known) and examined, in the case-control setting, the relative importance of UV exposure compared to self-reported time spent outdoors, in melanoma risk. UV estimates were coupled with residential histories of 820 representative melanoma cases among non-Hispanic white residents under 65 years of age from Los Angeles County and for 877 controls matched to cases by age, sex, race, and neighborhood of residence, to calculate the cumulative lifetime UV exposure and average annual UV exposure. For historical measures, when the participants resided outside the US, we also calculated UV estimates. While there was no increased risk of melanoma associated with self-reported time spent outdoors, the association between annual average UV exposure based on residential history and melanoma risk was substantial, as was the association between cumulative UV exposure based on residential history and melanoma. The time spent in outdoor activities appeared to have no significant effect on melanoma risk in any age strata, however, when adjusted for UV exposure based on residential history, time spent outdoors during young age significantly increased risk for melanoma. While there was some attenuation of risk when we excluded data from people resident overseas (as all other studies we are aware of have done), this did not significantly impact subsequent risk estimates of UV exposure on melanoma.

Prioritizing US Cervical Cancer Prevention With Results From a Geospatial Model.

PURPOSE: To determine if differences in screening and vaccination patterns across the population may accentuate ethnic and geographic variation in future burden of disease. METHODS: Using Cancer in North America data provided by the North American Association of Central Cancer Registries, county cervical cancer incidence trends from 1995 to 2009 were modeled for the entire United States using ecologic covariates. Rates for health service areas were also modeled by ethnicity. State-level incidence was mapped together with Papanicolaou (Pap) screening, past 3 years (women ≥ 18 years old), and three-dose human papillomavirus (HPV) vaccine coverage (girls 13 to 17 years old) to identify potential priority areas for preventive services. RESULTS: US cervical cancer incidence decreased more during the periods 1995 to 1999 and 2000 to 2004 than during the period 2005 to 2009. During these 15 years, the most affected areas became increasingly confined to Appalachia, the lower Mississippi Valley, the Deep South, Texas, and Florida. Hispanic and black women experienced a higher incidence of cervical cancer than both white and Asian and Pacific Islander women during each period. Women in 10 of 17 states/districts with a high incidence (≥ 8.14/100,000) reported low Pap testing (< 78.5%), HPV vaccine coverage (< 33.9%), or both prevention technologies. CONCLUSION: The decline in cervical cancer incidence has slowed in recent years. Access to HPV vaccination, targeted screening, and treatment in affected populations is needed to reduce cervical cancer disparities in the future.