Atlas of cancer mortality in the United Arab Emirates aided by application of geographic information system methods

The aim of this study was to determine cancer mortality rates for the United Arab Emirates (UAE) and to create an atlas of cancer mortality for the UAE. This atlas is the first of its kind in the Gulf country and the Middle East. Death certificates were reviewed for a period from January 1, 1990 to December 31, 1999 and cancer deaths were identified. Cancer mortality cases were verified by comparing with medical records. Age-adjusted cancer mortality rates were calculated by gender, emirate/medical district and nationality (UAE nationals and overall UAE population). Individual rates for each emirate were compared to the overall rate of the corresponding population for the same cancer site and gender. Age-adjusted rates were mapped using MapInfo software. High rates for liver, lung and stomach cancer were observed in Abu Dhabi, Dubai and the northern emirates, respectively. Rates for UAE nationals were greater compared to the overall UAE population. Several factors were suggested that may account for high rates of specific cancers observed in certain emirates. It is hoped that this atlas will provide leads that will guide further epidemiologic and public health activities aimed at preventing cancer. ^

Toxics Release Inventory facilities and childhood cancer: Geographic information systems based approach

Purpose. To examine the association between living in proximity to Toxics Release Inventory (TRI) facilities and the incidence of childhood cancer in the State of Texas. ^ Design. This is a secondary data analysis utilizing the publicly available Toxics release inventory (TRI), maintained by the U.S. Environmental protection agency that lists the facilities that release any of the 650 TRI chemicals. Total childhood cancer cases and childhood cancer rate (age 0-14 years) by county, for the years 1995-2003 were used from the Texas cancer registry, available at the Texas department of State Health Services website. Setting: This study was limited to the children population of the State of Texas. ^ Method. Analysis was done using Stata version 9 and SPSS version 15.0. Satscan was used for geographical spatial clustering of childhood cancer cases based on county centroids using the Poisson clustering algorithm which adjusts for population density. Pictorial maps were created using MapInfo professional version 8.0. ^ Results. One hundred and twenty five counties had no TRI facilities in their region, while 129 facilities had at least one TRI facility. An increasing trend for number of facilities and total disposal was observed except for the highest category based on cancer rate quartiles. Linear regression analysis using log transformation for number of facilities and total disposal in predicting cancer rates was computed, however both these variables were not found to be significant predictors. Seven significant geographical spatial clusters of counties for high childhood cancer rates (p<0.05) were indicated. Binomial logistic regression by categorizing the cancer rate in to two groups (<=150 and >150) indicated an odds ratio of 1.58 (CI 1.127, 2.222) for the natural log of number of facilities. ^ Conclusion. We have used a unique methodology by combining GIS and spatial clustering techniques with existing statistical approaches in examining the association between living in proximity to TRI facilities and the incidence of childhood cancer in the State of Texas. Although a concrete association was not indicated, further studies are required examining specific TRI chemicals. Use of this information can enable the researchers and public to identify potential concerns, gain a better understanding of potential risks, and work with industry and government to reduce toxic chemical use, disposal or other releases and the risks associated with them. TRI data, in conjunction with other information, can be used as a starting point in evaluating exposures and risks. ^

Geographic variation of the etiology of travelers' diarrhea

Introduction. Traveler's Diarrhea is an important public health program in travelers from industrialized nations to the developing world with a prevalence rate of between 13 and 60%. Although studies are found on the etiology of traveler's diarrhea, these studies have not described the etiology over different regions of the world. The objective of this study was to identify the frequency of specific etiology of traveler's diarrhea by geographic area of the world. In addition to this, it was also examined whether there are any regional differences in the isolation rate of ETEC and conventional pathogens and variation, if any, in frequency of these pathogens in different regions over time.^ Material and methods. This is a systematic review of the studies on the etiology of traveler's diarrhea by geographic regions. The search databases used were Medline Pubmed and Medline Ovid and key words used for the search were Etiology of traveler's diarrhea, travelers' diarrhea and acute diarrhea of travelers. The articles were selected according to the inclusion and exclusion criteria and relevant data was extracted which was statistically analyzed.^ Results. Out of 110 studies from 1970 to 2004, 52 studies were included and 58 were excluded from the review. All the 52 studies were grouped according to the geographic regions of interest. Latin America (25 studies), Asia (7 studies), Africa (9 studies), and others/Mixed (11 studies), were the 4 major groups of regions studied. The overall most common pathogen was ETEC (29.10%) in this study and other common pathogens were EAEC (14.42%), norovirus (10.95%), EPEC (6%) and rotavirus (5.23%). ETEC and Shigella show a decreasing trend in Latin America & Caribbean but increasing trend in Asia.^ Conclusion. ETEC is the single most common cause of travelers' diarrhea in the world. Potent vaccines against ETEC are required to prevent travelers' diarrhea and thus reduce the attack rate. Also, PCR based studies are required to identify the causes of pathogen negative diarrhea. ^

A geographic analysis of liver cancer mortality and alcohol dependence or abuse in Texas and the U.S., 1980--2003

Background. Liver cancer mortality continues to be a significant factor in deaths worldwide and in the U.S., yet there remains a lack of studies on how mortality burden is impacted by racial groups or by heavy alcohol use. This study evaluated the geographic distribution of liver cancer mortality across population groups in Texas and the U.S. over a 24-year period, as well as determining whether alcohol dependence or abuse correlates with mortality rates. ^ Methods. The Spatial Scan Statistic was used to identify regions of excess liver cancer mortality in Texas counties and the U.S. from 1980 to 2003. The statistic was conducted with a spatial cluster size of 50% of the population at risk, and all analyses used publicly available data. Alcohol abuse data by state and ethnicity were extracted from SAMHSA datasets for the study period 2000–2004. ^ Results. The results of the geographic analysis of liver cancer mortality in both Texas and the U.S. indicate that there were four and seven regions, respectively, that were identified as having statistically significant excess mortality rates with elevated relative risks ranging from 1.38–2.07 and 1.05–1.623 (p = 0.001), respectively. ^ Conclusion. This study revealed seven regions of excess mortality of liver cancer mortality across the U.S. and four regions of excess mortality in Texas between 1980–2003, as well as demonstrated a correlation between elevated liver cancer mortality rates and reporting of alcohol dependence among Hispanics and Other populations. ^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

Geographic variation in the utilization and survival associated with oxaliplatin chemotherapy in patients with stage III colon cancer

Background: Overall objectives of this dissertation are to examine the geographic variation and socio-demographic disparities (by age, race and gender) in the utilization and survival of newly FDA-approved chemotherapy agents (Oxaliplatin-containing regimens) as well as to determine the cost-effectiveness of Oxaliplatin in a large nationwide and population-based cohort of Medicare patients with resected stage-III colon cancer. Methods: A retrospective cohort of 7,654 Medicare patients was identified from the Surveillance, Epidemiology and End Results – Medicare linked database. Multiple logistic regression was performed to examine the relationship between receipt of Oxaliplatin-containing chemotherapy and geographic regions while adjusting for other patient characteristics. Cox proportional hazard model was used to estimate the effect of Oxaliplatin-containing chemotherapy on the survival variation across regions using 2004-2005 data. Propensity score adjustments were also made to control for potential bias related to non-random allocation of the treatment group. We used Kaplan-Meier sample average estimator to calculate the cost of disease after cancer-specific surgery to death, loss-to follow-up or censorship. Results: Only 51% of the stage-III patients received adjuvant chemotherapy within three to six months of colon-cancer specific surgery. Patients in the rural regions were approximately 30% less likely to receive Oxaliplatin chemotherapy than those residing in a big metro region (OR=0.69, p=0.033). The hazard ratio for patients residing in metro region was comparable to those residing in big metro region (HR: 1.05, 95% CI: 0.49-2.28). Patients who received Oxalipaltin chemotherapy were 33% less likely to die than those received 5-FU only chemotherapy (adjusted HR=0.67, 95% CI: 0.41-1.11). KMSA-adjusted mean payments were almost 2.5 times higher in the Oxaliplatin-containing group compared to 5-FU only group ($45,378 versus $17,856). When compared to no chemotherapy group, ICER of 5-FU based regimen was $12,767 per LYG, and ICER of Oxaliplatin-chemotherapy was $60,863 per LYG. Oxaliplatin was found economically dominated by 5-FU only chemotherapy in this study population. Conclusion: Chemotherapy use varies across geographic regions. We also observed considerable survival differences across geographic regions; the difference remained even after adjusting for socio-demographic characteristics. The cost-effectiveness of Oxaliplatin in Medicare patients may be over-estimated in the clinical trials. Our study found 5-FU only chemotherapy cost-effective in adjuvant settings in patients with stage-III colon cancer.^

Correlation of tuberculosis and human immunodeficiency virus in Harris County, Texas from 2009 through 2010 using Geographic Information Systems

A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^

Inappropriate imaging utilization in Texas: Geographic variation and predictive factors

Objective::Describe and understand regional differences and associated multilevel factors (patient, provider and regional) to inappropriate utilization of advance imaging tests in the privately insured population of Texas. Methods: We analyzed Blue Cross Blue Shield of Texas claims dataset to study the advance imaging utilization during 2008-2010 in the PPO/PPO+ plans. We used three of CMS "Hospital Outpatient Quality Reporting" imaging efficiency measures. These included ordering MRI for low back pain without prior conservative management (OP-8) and utilization of combined with and without contrast abdominal CT (OP-10) and thorax CT (OP-11). Means and variation by hospital referral regions (HRR) in Texas were measured and a multilevel logistic regression for being a provider with high values for any the three OP measures was used in the analysis. We also analyzed OP-8 at the individual level. A multilevel logistic regression was used to identify predictive factors for having an inappropriate MRI for low back pain. Results: Mean OP-8 for Texas providers was 37.89%, OP-10 was 29.94% and OP-11 was 9.24%. Variation was higher for CT measure. And certain HRRs were consistently above the mean. Hospital providers had higher odds of high OP-8 values (OP-8: OR, 1.34; CI, 1.12-1.60) but had smaller odds of having high OP-10 and OP-11 values (OP-10: OR, 0.15; CI, 0.12-0.18; OP-11: OR, 0.43; CI, 0.34-0.53). Providers with the highest volume of imaging studies performed, were less likely to have high OP-8 measures (OP-8: OR, 0.58; CI, 0.48-0.70) but more likely to perform combined thoracic CT scans (OP-11: OR, 1.62; CI, 1.34-1.95). Males had higher odds of inappropriate MRI (OR, 1.21; CI, 1.16-1.26). Pattern of care in the six months prior to the MRI event was significantly associated with having an inappropriate MRI. Conclusion::We identified a significant variation in advance imaging utilization across Texas. Type of facility was associated with measure performance, but the associations differ according to the type of study. Last, certain individual characteristics such as gender, age and pattern of care were found to be predictors of inappropriate MRIs.^

A geographic information science (GIS) approach to conducting comparative area-level community assessments in the Texas CORD Study

This study assessed and compared sociodemographic and income characteristics along with food and physical activity assets (i.e. grocery stores, fast food restaurants, and park areas) in the Texas Childhood Obesity Research Demonstration (CORD) Study intervention and comparison catchment areas in Houston and Austin, Texas. The Texas CORD Study used a quasi-experimental study design, so it is necessary to establish the interval validity of the study characteristics by confirming that the intervention and comparison catchment areas are statistically comparable. In this ecological study, ArcGIS and Esri Business Analyst were used to spatially relate U.S. Census Bureau and other business listing data to the specific school attendance zones within the catchment areas. T-tests were used to compare percentages of sociodemographic and income characteristics and densities of food and physical activity assets between the intervention and comparison catchment areas.^ Only five variables were found to have significant differences between the intervention and comparison catchment areas: Age groups 0-4 and 35-64, the percentage of owner-occupied and renter-occupied households, and the percentage of Asian and Pacific Islander residents. All other variables showed no significant differences between the two groups. This study shows that the methodology used to select intervention and comparison catchment areas for the Texas CORD Study was effective and can be used in future studies. The results of this study can be used in future Texas CORD studies to confirm the comparability of the intervention and comparison catchment areas. In addition, this study demonstrates a methodology for describing detailed characteristics about a geographic area that practitioners, researchers, and educators can use.^