Despite the overall improvement in health status, the timing and magnitude of changes in health outcomes (e.g. percentage of cancer late-stage diagnosis, adverse birth outcomes) display strong racial and geographical disparities. Quantifying the magnitude of these disparities at different scales and how they change with time are crucial metrics for understanding their origins and tracking progress towards their elimination. The proposed research will contribute to these important goals through: 1) the development of a geostatistical approach to identify and map nested scales of changes corresponding to individual ->neighborhood ->region, explore their relationships with covariates (e.g. other health outcomes or putative factors) through boundary overlap analysis and quantify the temporal stability of these spatial patterns, and 2) an in-depth boundary and multi-level analysis of the geographic and socioeconomic disparities in the incidence of breast cancer late-stage diagnosis and adverse birth outcomes (mortality and low birth weight), as well as their temporal changes, in Michigan. Specifically, this project will accomplish three aims: 1. Develop new methodologies for applying boundary analysis to raster data (e.g. imagery or disease risk maps) and within a multi-scale framework to account for the existence of boundaries at different spatial levels (e.g., counties, ZIP codes and census tracts), and implementing boundary analysis in a temporal framework to allow the study of temporal trends in the strength and location of geographic boundaries. 2. Explore the use of diffusion of innovation theory and simulated annealing-based spatial aggregation algorithms for the representation and exploratory data analysis of temporal trends in health outcomes and their relationship to putative factors in both space and time. 3. Apply the methodology to demonstrate the approach and its unique benefits for the investigation of geographical and racial disparities in temporal trends of several health outcomes (late-stage breast cancer, infant mortality and low birth weight), and the exploration of their relationships with potential factors, such as proximityto screening facilities (e.g. mammography clinics), socio-economic status, air pollution, and individual-level factors (e.g. smoking, health insurance, age). These technologic and scientific innovations will revolutionize our ability to visualize and interpret variation in cancer incidenceat multiple spatial scales and across time, which will help generating hypotheses for in depth individual studies of risk factors that are causal, or impact survival or morbidity, and establishig the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will also facilitate the long-term quantification of the benefits of current strategies and policies for reducing the observed geographic and racial disparities in cancer stage at diagnosis and incidence of infant mortality

Public Health Relevance

The substantial benefit of this research is its utility in documenting, analyzing and interpreting geographic and temporal variation in health outcomes and relating these boundaries to boundaries in potential environmental exposures, socio-demographic environment and access to health care. The methods developed in this project will help gain a better understanding of the mechanisms/pathways/causes by which regions and neighborhood influence health outcomes, and lead to a long-term quantification of the benefits of current strategies and policies for reducing the observed geographic disparities in cancer incidence and adverse birth outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21ES021570-02
Application #
8588323
Study Section
Special Emphasis Panel (ZRG1-PSE-C (90))
Program Officer
Dilworth, Caroline H
Project Start
2012-12-01
Project End
2014-11-30
Budget Start
2013-12-01
Budget End
2014-11-30
Support Year
2
Fiscal Year
2014
Total Cost
$182,523
Indirect Cost
$70,023
Name
Biomedware
Department
Type
DUNS #
947749388
City
Ann Arbor
State
MI
Country
United States
Zip Code
48103
Siska, Peter P; Goovaerts, Pierre; Hung, I-K (2016) Evaluating susceptibility of karst dolines (sinkholes) for collapse in Sango, Tennessee, USA. Prog Phys Geogr 40:579-597
Goovaerts, P; Albuquerque, Teresa; Antunes, Margarida (2016) A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration. Math Geosci 48:921-939
Kerry, Ruth; Goovaerts, Pierre; Vowles, Maureen et al. (2016) Spatial analysis of drug poisoning deaths in the American West, particularly Utah. Int J Drug Policy 33:44-55
Goovaerts, Pierre; Xiao, Hong; Adunlin, Georges et al. (2015) GEOGRAPHICALLY-WEIGHTED REGRESSION ANALYSIS OF PERCENTAGE OF LATE-STAGE PROSTATE CANCER DIAGNOSIS IN FLORIDA. Appl Geogr 62:191-200
Goovaerts, Pierre; Xiao, Hong; Gwede, Clement K et al. (2015) Impact of Age, Race and Socio-economic Status on Temporal Trends in Late-Stage Prostate Cancer Diagnosis in Florida. Spat Stat 14:321-337
Aidoo, Eric N; Mueller, Ute; Goovaerts, Pierre et al. (2015) Evaluation of geostatistical estimators and their applicability to characterise the spatial patterns of recreational fishing catch rates. Fish Res 168:20-32
Xiao, Hong; Tan, Fei; Goovaerts, Pierre et al. (2014) Multilevel Factors Associated With Overall Mortality for Men Diagnosed With Prostate Cancer in Florida. Am J Mens Health 8:316-26
Goovaerts, P (2014) Geostatistics: a common link between medical geography, mathematical geology, and medical geology. J South Afr Inst Min Metall 114:605-612
Xiao, Hong; Tan, Fei; Goovaerts, Pierre et al. (2013) Construction of a comorbidity index for prostate cancer patients linking state cancer registry with inpatient and outpatient data. J Registry Manag 40:159-64
Xiao, Hong; Tan, Fei; Goovaerts, Pierre et al. (2013) Use of treatment information from a state central cancer registry in prostate cancer research. J Registry Manag 40:127-30

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