• Journal of Environmental Health Sciences
• /
• v.37 no.1
• /
• pp.1-11
• /
• 2011

Recent advances in Geographic Information Systems and spatial statistical and analytical methods, along with the availability of spatially referenced health and environmental data, have created unique opportunities to investigate spatial associations between environment exposures and health outcomes at multiple spatial scales and resolutions. However, the increased use of spatial data also faces challenges, one of which is to ensure certainty and accuracy of locational data that meets the needs of a study. This article critically reviews the use of spatially referenced data in epidemiologic studies, focusing on the issue of locational uncertainty generated from the process of geocoding health and environmental data. Primarily, major issues involving the use of spatially referenced data are addressed, including completeness and positional accuracy, potential source of bias and exposure misclassification, and implications for epidemiologic studies. The need for critical assessment and caution in designing and conducting spatial epidemiology studies is briefly discussed.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.8
• /
• pp.3579-3586
• /
• 2015

Geographic information system (GIS) technology has useful applications for epidemiology, enabling the detection of spatial patterns of disease dispersion and locating geographic areas at increased risk. In this study, we applied GIS technology to characterize the spatial pattern of mortality due to liver cancer in the autonomous region of Guangxi Zhuang in southwest China. A database with liver cancer mortality data for 1971-1973, 1990-1992, and 2004-2005, including geographic locations and climate conditions, was constructed, and the appropriate associations were investigated. It was found that the regions with the highest mortality rates were central Guangxi with Guigang City at the center, and southwest Guangxi centered in Fusui County. Regions with the lowest mortality rates were eastern Guangxi with Pingnan County at the center, and northern Guangxi centered in Sanjiang and Rongshui counties. Regarding climate conditions, in the 1990s the mortality rate of liver cancer positively correlated with average temperature and average minimum temperature, and negatively correlated with average precipitation. In 2004 through 2005, mortality due to liver cancer positively correlated with the average minimum temperature. Regions of high mortality had lower average humidity and higher average barometric pressure than did regions of low mortality. Our results provide information to benefit development of a regional liver cancer prevention program in Guangxi, and provide important information and a reference for exploring causes of liver cancer.

• Journal of the Korean Geographical Society
• /
• v.47 no.5
• /
• pp.677-699
• /
• 2012

Climate changes may cause substantial changes in spatial patterns and distribution of vector-borne diseases (VBD's), which will result in a significant threat to humans and emerge as an important public health problem that the international society needs to solve. As global warming becomes widespread and the Korean peninsula characterizes subtropical climate, the potentials of climate-driven disease outbreaks and spread rapidly increase with changes in land use, population distributions, and ecological environments. Vector-borne diseases are typically infected by insects such as mosquitoes and ticks, and infected hosts and vectors increased dramatically as the habitat ranges of the VBD agents have been expanded for the past 20 years. Medical geography integrates and processes a wide range of public health data and indicators at both local and regional levels, and ultimately helps researchers identify spatiotemporal mechanism of the diseases determining interactions and relationships between spatial and non-spatial data. Spatial epidemiology is a new and emerging area of medical geography integrating geospatial sciences, environmental sciences, and epidemiology to further uncover human health-environment relationships. An introduction of GIS-based disease monitoring system to the public health surveillance system is among the important future research agenda that medical geography can significantly contribute to. Particularly, real-time monitoring methods, early-warning systems, and spatial forecasting of VBD factors will be key research fields to understand the dynamics of VBD's.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.9
• /
• pp.4025-4029
• /
• 2015

Background: Gastrointestinal tract cancers are among the most common cancers in Iran and comprise approximately 38% of all the reported cases of cancer. This study aimed to describe the epidemiology and to investigate spatial clustering of common cancers of the gastrointestinal tract across the counties of Iran using full Bayesian smoothing and Moran I Index statistics. Materials and Methods: The data of the national registry cancer were used in this study. Besides, indirect standardized rates were calculated for 371 counties of Iranand smoothed using Winbug 1.4 software with a full Bayesian method. Global Moran I and local Moran I were also used to investigate clustering. Results: According to the results, 75,644 new cases of cancer were nationally registered in Iran among which 18,019 cases (23.8%) were esophagus, gastric, colorectal, and liver cancers. The results of Global Moran's I test were 0.60 (P=0.001), 0.47 (P=0.001), 0.29 (P=0.001), and 0.40 (P=0.001) for esophagus, gastric, colorectal, and liver cancers, respectively. This shows clustering of the four studied cancers in Iran at the national level. Conclusions: High level clustering of the cases was seen in northern, northwestern, western, and northeastern areas for esophagus, gastric, and colorectal cancers. Considering liver cancer, high clustering was observed in some counties in central, northeastern, and southern areas.

• Journal of Environmental Health Sciences
• /
• v.38 no.5
• /
• pp.369-379
• /
• 2012

Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.sup3
• /
• pp.59-64
• /
• 2016

Breast cancer (BC) is the most common cancer in females (27% of the total) and the main cause of death (16%) due to cancer in women in developed and developing countries. Variations in its incidence rate among geographical areas are due to various contributing factors. Since there have been a lack of studies on this topic in our country, the present spatial analysis of breast cancer incidence in Iran in 2009 was conducted using data from the national cancer registry system. The reported incidences of the disease were standardized according to the World Health Organization population and the direct method. Then data was inserted into the GIS software and finally, using the Hot Spot Analysis (Geties-Ord Gi), high-risk areas were drawn. Provinces with incidences 1.96 SD higher or lower than the national average were considered as hot spots or cold spots, at the significance level of 0.05%. In 2009, a total of 7,582 cases of BC occurred in Iran. The annual incidence was 33.2 per hundred thousand people. Our study showed that the highest incidence of BC in women occurred in the central provinces of the country, Tehran, Isfahan, Yazd, Markazi and Fars. The results of hot spots analysis showed that the distribution of high-risk BC was focused in central parts of Iran, especially Isfahan province (p <0.01). The other provinces were not significantly different from the national average. The higher incidence in central provinces may be due to greater exposure to carcinogens in urban areas, a Western lifestyle and high prevalence of other risk factors. Further epidemiological studies about the etiology and early detection of BC are essential.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.sup3
• /
• pp.27-32
• /
• 2016

Stomach cancer, the fourth most common cancer and the second leading cause of cancer-related death through the world, is very common in parts of Iran. Geographic variation in the incidence of stomach cancer is due to many different factors. The aim of this study was to assess the geographical and spatial distribution of stomach cancer in Iran using data from the cancer registry program in Iran for the year 2009. The reported incidences of stomach cancer for different provinces were standardized to the world population structure. ArcGIS software was used to analyse the data. Hot spots and high risk areas were determined using spatial analysis (Getis-Ord Gi). Hot and cold spots were determined as more than or less than 2 standard deviations from the national average, respectively. A significance level of 0.10 was used for statistical judgment. In 2009, a total of 6,886 cases of stomach cancers were reported of which 4,891 were in men and 1,995 in women (standardized incidence rates of 19.2 and 10.0, respectively, per 100,000 population). The results showed that stomach cancer was concentrated mainly in northwest of the country in both men and women. In women, northwest provinces such as Ardebil, East Azerbaijan, West Azerbaijan, Gilan, and Qazvin were identified as hot spots (p<0.1). In men, all northwest provinces, Ardabil, East Azerbaijan, Gilan, Qazvin, Zanjan and Kurdistan, the incidences were higher than the national average and these were identified as hot spots (P<0.01). As stomach cancer is clustered in the northwest of the country, further epidemiological studies are needed to identify factors contributing to this concentration.

• Journal of Preventive Medicine and Public Health
• /
• v.51 no.1
• /
• pp.33-40
• /
• 2018

Objectives: The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods: This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The $Besag-York-Molli{\acute{e}}$ (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results: The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Conclusions: Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in at-risk areas.

• Spatial Information Research
• /
• v.20 no.1
• /
• pp.81-90
• /
• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.4
• /
• pp.1557-1561
• /
• 2014

Background: Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at the area-level is helpful for health policy makers. However, traditional methods of estimation which do not take spatial heterogeneity into account suffer from drawbacks and their results may be misleading, as the estimated maps of incidence vary dramatically in neighboring areas. Spatial methods have been proposed to overcome drawbacks of traditional methods by including spatial sources of variation in the model to produce smoother maps. Materials and Methods: In this study we analyzed the breast cancer data in Iran during 2004-2008. We used a method proposed to cover spatial and temporal effects simultaneously and their interactions to study trends of breast cancer incidence in Iran. Results: The results agree with previous studies but provide new information about two main issues regarding the trend of breast cancer in provinces of Iran. First, this model discovered provinces with high relative risks of breast cancer during the 5 years of the study. Second, new information was provided with respect to overall trend trends o. East-Azerbaijan, Golestan, North-Khorasan, and Khorasan-Razavi had the highest increases in rates of breast cancer incidence whilst Tehran, Isfahan, and Yazd had the highest incidence rates during 2004-2008. Conclusions: Using spatial methods can provide more accurate and detailed information about the incidence or prevalence of a disease. These models can specify provinces with different health priorities in terms of needs for therapy and drugs or demands for efficient education, screening, and preventive policy into action.