Int J Cancer Manag. 2017 July; 10(7):e5753. Published online 2017 July 31. doi: 10.5812/ijcm.5753. Research Article Cancer Incidence Rate in the Elderly Inhabitants of Tehran: Is there Really any Cluster? Marzieh Rohani-Rasaf, 1 Mohammad Reza Rohani-Rasaf, 2 Seyed Saeed Hashemi Nazari, 3 Abdollah Mohammadian-Hafshejani, 4 and Mohsen Asadi-Lari 5,* 1 Student Research Committee, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2 Geography and Urban Planning Department, Shahid Chamran University of Ahvaz, Ahvaz, IR Iran 3 Safety Promotion and Injury Prevention Research Center AND Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran 4 Department of Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 5 Associate Professor of Epidemiology, Oncopathology Research Centre, Iran University of Medical Sciences, Tehran, IR Iran * Corresponding author: Mohsen Asadi-Lari, Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, IR Iran. Tel: +98-9122115440, E-mail: mohsen.asadi@yahoo.com Received 2016 February 21; Revised 2016 October 10; Accepted 2017 July 08. Abstract Background: The number of new cancer cases in the elderly is growing because of the aging population. Methods: Cancer data of the elderly (65 years and older) were collected from Iran cancer registry in 2007. Local Moran’s I was used as a measure of spatial analysis to identify the cluster patterns. Results: The overall cancer incidence rates were 862.4 and 474.8 per 100,000 in men and women, respectively. Prostate cancer and breast cancer were the most common types of cancer in men and women, correspondingly. Using the Local Moran’s I tool, we identified more spatial clusters among men than women. Districts 1, 2, 3 and 6 in the north of Tehran were hot spots for prostate cancer and district 16 in the south of Tehran was the cool spot for this type of cancer, and districts 1 and 3 were the hot spots for breast cancer. Conclusions: More cancer hot spots were located in the north of Tehran where districts are more privileged, and more cool spots were located in the south of the city where districts are more underprivileged. Keywords: Cancer Incidence, Local Moran’s I, Elderly Inhabitants of Tehran 1. Background The majority of the older population live in develop- ing countries where the number of older people is pro- jected to grow by 250 and 71% in developing and devel- oped countries, respectively within the next 30 years glob- ally (1). The proportion of people aged over 65 is growing faster than any other age groups because of both longer life expectancy and the decline of fertility rates. As pre- dicted by WHO, Chile, China and the Islamic Republic of Iran will have a greater proportion of older people than the United States in 2050 (2). Non-communicable diseases are responsible for more than 87% of the burden of diseases and 60% of all cancers diagnosed in the elderly. This could be explained through the dose-duration effects of carcino- genic exposures and the vulnerability of the elderly to can- cer (3). The total cancer incidence rate for the elderly men is four times the rate of 45-64 year old men and twice that of women (4). The incidence of cancer in the 65- and- older population is 10 times higher compared to the younger population (5). The incidence of cancer is estimated to in- crease in the next decades particularly in the less devel- oped countries due to global aging. Over 50% of cancers occur at the age of 70 and above; however, this gradient reduces in the oldest age group (6, 7). A relationship was found between aging and cancer even with minimum en- vironmental carcinogens; and as a consequence, more hu- man and monetary resources are required to investigate the cancer etiology, prevention, control and quality of life in the elderly (8). Geographic Information System (GIS) and spatial anal- ysis have provided new opportunities for the policymak- ers to investigate the relationship between health and en- vironmental risk factors or the geographic characteristics (9-14). Spatial analysis allows us to identify the patterns, and classify data as regular, random, or clustered (15). Spa- tial autocorrelation is used to assess the rates, and Moran’s I is one of the best statistical measures that is similar to the Pearson’s correlation coefficient. The I statistic measures the covariation between the rates of adjacent regions (16, 17). The current study aimed to examine cancer incidence rates in those over 65 years of age living in Tehran, con- Copyright © 2017, International Journal of Cancer Management. 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