The crossroads of GIS and health information: a workshop on developing a research agenda to improve cancer control

Utilizing residential histories to assess environmental exposure and socioeconomic status over the life course among mesothelioma patients

Background

Exposure misclassification based solely on the address at cancer diagnosis has been widely recognized though not commonly assessed.

Methods

We linked 1,015 mesothelioma cases diagnosed during 2011-2015 from the New York State Cancer Registry to inpatient claims and LexisNexis administrative data and constructed residential histories. Percentile ranking of exposure to ambient air toxics and socioeconomic status (SES) were based on the National Air Toxic Assessment and United States Census data, respectively. To facilitate comparisons over time, relative exposures (REs) were calculated by dividing the percentile ranking at individual census tract by the state-level average and subtracting one. We used generalized linear regression models to compare the RE in the past with that at cancer diagnosis, adjusting for patient-level characteristics.

Results

Approximately 43.7% of patients had residential information available for up to 30 years, and 96.0% up to 5 years. The median number of unique places lived was 4 [interquartile range (IQR), 2-6]. The time-weighted-average RE from all addresses available had a median of -0.11 (IQR, -0.50 to 0.30) for air toxics and -0.28 (IQR, -0.65 to 0.25) for SES. RE associated with air toxics (but not SES) was significantly higher for earlier addresses than addresses at cancer diagnosis for the 5-year [annual increase =1.24%; 95% confidence interval (CI): 0.71-1.77%; n=974] and 30-year (annual increase =0.36%; 95% CI: 0.25-0.48%; n=444) look-back windows, respectively.

Conclusions

Environmental exposure to non-asbestos air toxics among mesothelioma patients may be underestimated if based solely on the address at diagnosis. With geospatial data becoming more readily available, incorporating cancer patients' residential history would lead to reduced exposure misclassification and accurate health risk estimates.

Utilizing Residential History to Examine Heterogeneous Exposure Trajectories: A Latent Class Mixed Modeling Approach Applied to Mesothelioma Patients

Background

Life-course exposure assessment, as opposed to a one-time snapshot assessment based on the address at cancer diagnosis, has become increasingly possible with available cancer patients' residential history data. To demonstrate a novel application of residential history data, we examined the heterogeneous trajectories of the nonasbestos air toxic exposures among mesothelioma patients, and compared the patients' residential locations with the spatiotemporal clusters estimated from the National Air Toxic Assessment (NATA) data.

Methods

Patients' residential histories were obtained by linking mesothelioma cases diagnosed during 2011-2015 in the New York State (NYS) Cancer Registry to LexisNexis administrative data and inpatient claims data. To compare cancer risks over time, yearly relative exposure (RE) was calculated by dividing the NATA cancer risk at individual census tracts by the NYS average and subtracting 1. We used a latent class mixed model to identify distinct exposure trajectories among patients with a 15-year residential history prior to cancer diagnosis (n = 909). We further examined patient characteristics by the latent trajectory groups using bivariate comparisons and a logistic regression model. The spatiotemporal clusters of RE were generated based on all NATA data (n = 72,079) across the contiguous United States and using the SaTScan software.

Results

The median number of addresses lived was 2 (IQR, 1-4), with a median residential duration of 8 years (IQR, 4.7-13.2 years). We identified 3 distinct exposure trajectories: persistent low exposure (27%), decreased low exposure (41%), and increased high exposure (32%). Patient characteristics did not differ across trajectory groups, except for race and Hispanic ethnicity (P < .0001) and residential duration (P = .03). Compared to their counterparts, non-Hispanic White patients had a significantly lower odds of belonging to the increased high exposure group (adjusted odds ratio, 0.14; 95% CI, 0.09-0.23) than the persistent low exposure and decreased low exposure groups. Patients in the increased high exposure group tended to reside in New York City (NYC), which was covered by one of the high-RE clusters. On the other hand, patients in the persistent low exposure group tended to reside outside of NYC within NYS, which was largely covered by 2 low-RE clusters.

Conclusion

Using mesothelioma as an example, we quantified the heterogeneous trajectories of nonasbestos air toxic exposure based on patients' residential histories. We found that patients' race and ethnicity differed across the latent groups, likely reflecting the differences in patients' residential mobility before their cancer diagnoses. Our method can be used to study cancer types that do not have a clear etiology and may have a higher attributable risk due to environmental exposures as well as socioeconomic conditions.

Identifying Area-Level Disparities in Human Papillomavirus Vaccination Coverage Using Geospatial Analysis

BACKGROUND

Human papillomavirus (HPV) is the most common sexually transmitted infection within the United States (US). Despite clinical agreement on the effectiveness and widespread availability of the prophylactic HPV vaccine, vaccination coverage in the US is suboptimal and varies by geographic region and area-level variables. The goals of this article were to model the variation in vaccination rates among boys and girls within ZIP Codes in Virginia, determine whether neighborhood sociodemographic variables explain variation in HPV vaccination, and identify areas with significantly depressed vaccination coverage.

METHODS

We used Bayesian hierarchical spatial regression models with statewide immunization registry data to consider the correlation in vaccination among boys and girls, as well as the spatial correlation in vaccination for each sex.

RESULTS

The results showed low vaccination coverage in our birth cohort (28.9% in girls and 23.8% in boys) relative to the national level (56.8% and 51.8%, respectively). Several area-level variables were significantly and positively associated with vaccination coverage, including population density, percentage of Hispanic population, and average number of vehicles. In addition, there were several areas of significantly lowered vaccination coverage, including predominantly rural ones, and overall large geographic disparities in HPV vaccination.

CONCLUSIONS

Determining the geospatial patterning and area-level factors associated with HPV vaccination within a prescribed geographic area helps to inform future planning efforts.

IMPACT

The results of this study will help inform future planning efforts for geographically targeted interventions and policies, as well as drive new research to implement clinical and community strategies to increase HPV vaccination.

A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

Objectives

Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran.

Data description

We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

Area-Level Variation and Human Papillomavirus Vaccination among Adolescents and Young Adults in the United States: A Systematic Review

Understanding how human papillomavirus (HPV) vaccination coverage varies by geography can help to identify areas of need for prevention and control efforts. A systematic review of the literature was conducted using a combination of keywords (HPV vaccination, geography, neighborhoods, and sociodemographic factors) on Medline and Embase databases. Studies had to provide information on HPV vaccination by area-level variables, be conducted in the United States, and be published in English (analyzing data from January 2006 to February 2020). Conference abstracts and opinion pieces were excluded. Of 733 records identified, 25 were included for systematic review. Across studies, the average initiation rate was 40.5% (range, 6.3%-78.0%). The average rate of completion was 23.4% (range, 1.7%-55.2%). Geographic regions and area-level factors were associated with HPV vaccination, including zip code tabulation area-level poverty, urbanicity/rurality, racial/ethnic composition, and health service region characteristics. Only three studies utilized geospatial approaches. None accounted for geospatial-temporal associations. Individual-level and area-level factors and their interactions are important for characterizing HPV vaccination. Results demonstrate the need to move beyond existing multilevel methods and toward the adoption of geospatial approaches that allow for the mapping and detection of geographic areas with low HPV vaccination coverage.

Geospatial analyses identify regional hot spots of diffuse gastric cancer in rural Central America

Background

Geospatial technology has facilitated the discovery of disease distributions and etiology and helped target prevention programs. Globally, gastric cancer is the leading infection-associated cancer, and third leading cause of cancer mortality worldwide, with marked geographic variation. Central and South America have a significant burden, particularly in the mountainous regions. In the context of an ongoing population-based case-control study in Central America, our aim was to examine the spatial epidemiology of gastric cancer subtypes and H. pylori virulence factors.

Methods

Patients diagnosed with gastric cancer from 2002 to 2013 in western Honduras were identified in the prospective gastric cancer registry at the principal district hospital. Diagnosis was based on endoscopy and confirmatory histopathology. Geospatial methods were applied using the ArcGIS v10.3.1 and SaTScan v9.4.2 platforms to examine regional distributions of the gastric cancer histologic subtypes (Lauren classification), and the H. pylori CagA virulence factor. Getis-Ord-Gi hot spot and Discrete Poisson SaTScan statistics, respectively, were used to explore spatial clustering at the village level (30–50 rural households), with standardization by each village’s population. H. pylori and CagA serologic status was determined using the novel H. pylori multiplex assay (DKFZ, Germany).

Results

Three hundred seventy-eight incident cases met the inclusion criteria (mean age 63.7, male 66.3%). Areas of higher gastric cancer incidence were identified. Significant spatial clustering of diffuse histology adenocarcinoma was revealed both by the Getis-Ord-GI* hot spot analysis (P-value < 0.0015; range 0.00003–0.0014; 99%CI), and by the SaTScan statistic (P-value < 0.006; range 0.0026–0.0054). The intestinal subtype was randomly distributed. H. pylori CagA had significant spatial clustering only in association with the diffuse histology cancer hot spot (Getis-Ord-Gi* P value ≤0.001; range 0.0001–0.0010; SaTScan statistic P value 0.0085). In the diffuse gastric cancer hot spot, the lowest age quartile range was 21–46 years, significantly lower than the intestinal cancers (P = 0.024).

Conclusions

Geospatial methods have identified a significant cluster of incident diffuse type adenocarcinoma cases in rural Central America, suggest of a germline genetic association. Further genomic and geospatial analyses to identify potential spatial patterns of genetic, bacterial, and environmental risk factors may be informative.

Geographic distribution of cancer cases in isfahan province/2006-2010

BACKGROUND

To facilitate analysis, interpreting and sharing cancer data and investigation spatial and geographical aspect of cancers in Isfahan province, cancer cases distribution was displayed using geographic information systems (GIS).

METHODS

About 118,000 cancer data, which were confirmed in national cancer registration unit were extracted. Age-specific incidence rate and age standardized rate (ASR) of cancer cases from 2006 to 2010 was calculated for Isfahan province and its different districts. Distribution of ASR was determined according to sex and age groups. Spatial maps were drawn with the help of Arc GIS version 10 (ESRI, Redland, CA, USA) software in choropleth based maps. The data are classified in GIS environment by means of quantile method. Data were described with the help of maps spatially.

RESULTS

Age standardized rate of cancers was higher in men than in women (134.58 vs. 115.4). The highest ASR was reported in the Isfahan (ASR: 133) and lowest in the Chadegan counties (ASR: 28). Different geographical distribution patterns of cancers were seen in district level. Cancer incidence was higher in the Isfahan, Lenjan, Fereidon Shahr and Falavarjan districts (134.3, 117.2, 113.5 and 111.1 respectively) among men and in Isfahan, Shahin Shahr, Lenjan and Najafabad districts (122.8, 102.3, 94 and 93 respectively) among women. The incidence rates of most cancers were lowest in the North East region of the province compared to the rest of the region.

CONCLUSIONS

Using GIS for visual displaying of cancers facilitated communication with the policymakers and community. This study provided hypotheses about differences in the incidence of cancer in Isfahan districts. Higher age-specific incidence rate in the Isfahan city is probably a reflection of problems in addressing the patients in cancer registration. Complementary studies are needed to evaluate lower ASR in the North East regions of the province.

Using geographic methods to inform cancer screening interventions for South Asians in Ontario, Canada

Background

Literature suggests that South Asians in Ontario, Canada are under-screened for breast, cervical and colorectal cancer. Accordingly, we are involved in a community-engaged multi-phase study aimed at increasing cancer screening for this vulnerable group. In the work described in this manuscript, we aimed to use visual displays of spatial analyses to identify the most appropriate small geographic areas in which to pilot targeted cancer screening interventions for Ontario’s South Asian community.

Methods

We used Geographic Information Systems (GIS), including Local Indicators of Spatial Association (LISA) using GeoDa software, and population-level administrative data to create multi-layered maps of: i) rates of appropriate cancer screening, ii) the percentage of residents of South Asian ethnicity, and iii) the locations of primary care practices and community health centres by census tract in the Peel Region of Ontario (population: 1.2 million). The maps were shared with partner health service and community service organizations at an intervention development workgroup meeting to examine face validity.

Results

The lowest rates of appropriate cancer screening for census tracts across the region were 51.1% for cervical cancer, 48.5% for breast cancer, and 42.5% for colorectal cancer. We found marked variation both in screening rates and in the proportion of South Asians residents by census tract but lower screening rates in the region were consistently associated with larger South Asian populations. The LISA analysis identified a high-risk area consisting of multiple neighbouring census tracts with relatively low screening rates for all three cancer types and with a relatively large South Asian population. Partner organizations recognized and validated the geographic location highlighted by the LISA analysis. Many primary care practices are located in this high-risk area, with one community health centre located very nearby.

Conclusions

In this populous region of Ontario, South Asians are more likely to reside in areas with lower rates of appropriate breast, cervical and colorectal cancer screening. We have identified a high-risk area appropriate for both patient- and provider-focused interventions. Geographic Information Systems, in particular LISA analyses, can be invaluable when working with health service and community organizations to define areas with the greatest need for interventions to reduce health inequities.

Combining area-based and individual-level data in the geostatistical mapping of late-stage cancer incidence

This paper presents a geostatistical approach to incorporate individual-level data (e.g. patient residences) and area-based data (e.g. rates recorded at census tract level) into the mapping of late-stage cancer incidence, with an application to breast cancer in three Michigan counties. Spatial trends in cancer incidence are first estimated from census data using area-to-point binomial kriging. This prior model is then updated using indicator kriging and individual-level data. Simulation studies demonstrate the benefits of this two-step approach over methods (kernel density estimation and indicator kriging) that process only residence data.

SAS macro programs for geographically weighted generalized linear modeling with spatial point data: applications to health research

An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above.

Spatio-temporal epidemiology: principles and opportunities

Space-time analysis of disease data has historically involved the search for patterns in aggregated data to identify how regions of high and low risk change through time. Space-time analysis of aggregated data has great value, but represents only a subset of space-time epidemiologic applications. Technological advances for tracking and mapping individuals (e.g., global positioning systems) have introduced mobile populations as an important element in space-time epidemiology. We review five domains critical to the developing field of spatio-temporal epidemiology: (1) spatio-temporal epidemiologic theory, (2) selection of appropriate spatial scale of analysis, (3) choice of spatial/spatio-temporal method for pattern identification, (4) individual-level exposure assessment in epidemiologic studies, and (5) assessment and consideration of locational and attribute uncertainty. This review provides an introduction to principles of space-time epidemiology and highlights future research opportunities.

An eight-year snapshot of geospatial cancer research (2002-2009): clinico-epidemiological and methodological findings and trends

Geographic information systems (GIS) offer a very rich toolbox of methods and technologies, and powerful research tools that extend far beyond the mere production of maps, making it possible to cross-link and study the complex interaction of disease data and factors originating from a wide range of disparate sources. Despite their potential indispensable role in cancer prevention and control programmes, GIS are underrepresented in specialised oncology literature. The latter has provided an impetus for the current review. The review provides an eight-year snapshot of geospatial cancer research in peer-reviewed literature (2002-2009), presenting the clinico-epidemiological and methodological findings and trends in the covered corpus (93 papers). The authors concluded that understanding the relationship between location and cancer/cancer care services can play a crucial role in disease control and prevention, and in better service planning, and appropriate resource utilisation. Nevertheless, there are still barriers that hinder the wide-scale adoption of GIS and related technologies in everyday oncology practice.

Application of geographic information systems and asset mapping to facilitate identification of colorectal cancer screening resources

OBJECTIVE

We sought to identify and map the geographic distribution of available colorectal cancer screening resources; following identification of this priority within a needs assessment of a local community-academic collaborative to reduce cancer health disparities in medically underserved communities.

METHODS

We used geographic information systems (GIS) and asset mapping tools to visually depict resources in the context of geography and a population of interest. We illustrate two examples, offer step-by-step directions for mapping, and discuss the challenges, lessons learned, and future directions for research and practice.

RESULTS

Our positive asset driven, community-based approach illustrated the distribution of existing colonoscopy screening facilities and locations of populations and organizations who might use these resources. A need for additional affordable and accessible colonoscopy resources was identified.

CONCLUSION

These transdisciplinary community mapping efforts highlight the benefit of innovative community-academic partnerships for addressing cancer health disparities by bolstering infrastructure and community capacity-building for increased access to colonoscopies.

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Work group II: Using Geographic Information Systems for enhancing research relevant to policy on diet, physical activity, and weight

Geographic Information Systems (GIS) was a theme for one of the four workgroups convened for the Measures of the Food and Built Environment meeting held in Bethesda, Maryland in November 2007. This summary of group discussions frames several critical conceptual, methodologic, and data challenges regarding the use of GIS to enhance research relevant to policy on diet, physical activity, and weight. Broad recommendations are offered in five areas: (1) theoretical and conceptual development in framing place effects on health; (2) contextualizing people and spatial behavior in built environments and improving empirical representations of place; (3) geospatial data availability, quality, and standards; (4) privacy and confidentiality; and, (5) building capacity in GIS personnel and infrastructure. These topics are inter-related. Although our discussion focuses on issues relevant to the role of the built environment in diet and physical activity outcomes, our recommendations also are salient to health and environment research generally.

Spatial cluster analysis of early stage breast cancer: a method for public health practice using cancer registry data

OBJECTIVES

Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice-research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data.

METHODS

Spatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms.

RESULTS

Analyses relying on point data identified spatial clusters not detected using data aggregated into census block groups, census tracts, or legislative districts. Further, using point data, Cuzick-Edwards' nearest neighbor test identified clusters not detected by the SaTScan spatial scan statistic. Regression and simulation analyses lent credibility to these findings.

CONCLUSIONS

In these cluster analyses of early stage breast cancer in Michigan, spatial analyses of point data are more sensitive than analyses relying on data aggregated into polygons, and the Cuzick-Edwards' test is more sensitive than the SaTScan spatial scan statistic, with acceptable Type I error. Cuzick-Edwards' test also enables presentation of results in a manner easily communicated to public health practitioners. The approach outlined here should help cancer registries conduct and communicate results of geographic analyses.

The perceived impact of location privacy: a web-based survey of public health perspectives and requirements in the UK and Canada

BACKGROUND

The "place-consciousness" of public health professionals is on the rise as spatial analyses and Geographic Information Systems (GIS) are rapidly becoming key components of their toolbox. However, "place" is most useful at its most precise, granular scale - which increases identification risks, thereby clashing with privacy issues. This paper describes the views and requirements of public health professionals in Canada and the UK on privacy issues and spatial data, as collected through a web-based survey.

METHODS

Perceptions on the impact of privacy were collected through a web-based survey administered between November 2006 and January 2007. The survey targeted government, non-government and academic GIS labs and research groups involved in public health, as well as public health units (Canada), ministries, and observatories (UK). Potential participants were invited to participate through personally addressed, standardised emails.

RESULTS

Of 112 invitees in Canada and 75 in the UK, 66 and 28 participated in the survey, respectively. The completion proportion for Canada was 91%, and 86% for the UK. No response differences were observed between the two countries. Ninety three percent of participants indicated a requirement for personally identifiable data (PID) in their public health activities, including geographic information. Privacy was identified as an obstacle to public health practice by 71% of respondents. The overall self-rated median score for knowledge of privacy legislation and policies was 7 out of 10. Those who rated their knowledge of privacy as high (at the median or above) also rated it significantly more severe as an obstacle to research (P < 0.001). The most critical cause cited by participants in both countries was bureaucracy.

CONCLUSION

The clash between PID requirements - including granular geography - and limitations imposed by privacy and its associated bureaucracy require immediate attention and solutions, particularly given the increasing utilisation of GIS in public health. Solutions include harmonization of privacy legislation with public health requirements, bureaucratic simplification, increased multidisciplinary discourse, education, and development of toolsets, algorithms and guidelines for using and reporting on disaggregate data.

An unsupervised classification method for inferring original case locations from low-resolution disease maps

Background

Widespread availability of geographic information systems software has facilitated the use of disease mapping in academia, government and private sector. Maps that display the address of affected patients are often exchanged in public forums, and published in peer-reviewed journal articles. As previously reported, a search of figure legends in five major medical journals found 19 articles from 1994–2004 that identify over 19,000 patient addresses. In this report, a method is presented to evaluate whether patient privacy is being breached in the publication of low-resolution disease maps.

Results

To demonstrate the effect, a hypothetical low-resolution map of geocoded patient addresses was created and the accuracy with which patient addresses can be resolved is described. Through georeferencing and unsupervised classification of the original image, the method precisely re-identified 26% (144/550) of the patient addresses from a presentation quality map and 79% (432/550) from a publication quality map. For the presentation quality map, 99.8% of the addresses were within 70 meters (approximately one city block length) of the predicted patient location, 51.6% of addresses were identified within five buildings, 70.7% within ten buildings and 93% within twenty buildings. For the publication quality map, all addresses were within 14 meters and 11 buildings of the predicted patient location.

Conclusion

This study demonstrates that lowering the resolution of a map displaying geocoded patient addresses does not sufficiently protect patient addresses from re-identification. Guidelines to protect patient privacy, including those of medical journals, should reflect policies that ensure privacy protection when spatial data are displayed or published.