Spatial epidemiology of skin cancer in Iran: separating sun-exposed and non-sun-exposed parts of the body

Abstract

Background Skin cancer is among the most common cancer types with an increasing global trend of incidence rate. This study explores the spatial distribution of skin cancer, considering body sites exposed and not exposed to sunshine separately. Methods We used 4302 skin cancer cases recorded by Fars Cancer Registry in south-western Iran for over 6 years (2011–2017). The variables included in the study were patients’ residence address, gender, age, report date, and final topographical code. The patients’ addresses were geocoded to the counties of the study area. Skin cancer sites were categorized based on sun exposure in male and female cases. We used the empirical Bayesian smoothing approach to smooth the skin cancer incidence rate at the county level to remove any potential population size bias. Finally, Anselin’s Local Moran’s Index and Getis Ord G* were used to identify the clustered and high-risk skin cancer geographical areas. Results The incidence rates had an increasing trend from 14.28 per 100,000 people in 2011 to 17.87 per 100,000 people in 2016, however, it was decreased to 13.05 per 100,000 people in 2017. Out of 4302 patients with skin cancer, 2602 cases (60%) were male. The cancer cumulative incidence rate in males and females who were not exposed to sunshine was 7.80 and 14.18 per 100,000, respectively. The rates increased to 86.22 and 48.20 in males and females who were exposed to the sun. There were some high-risk spatial clusters of skin cancer in the study area. Further investigations are required to identify the underlying cause of the formation of these clusters. Conclusions Patients exposed to sunshine, especially among the male group, experienced much higher rates of cancer occurrence as compared to unexposed individuals. With a heterogeneous spatial pattern, hotspots were identified in non-sun-exposed and sun-exposed categories in the study area. Researchers and policymakers can significantly benefit from the spatial analyses of skin cancer incidence. These analyses can provide useful and timely prevention policies as well as tailored monitoring techniques in high-risk regions.

Incidence Rates and Time Trends of Skin Cancer in Golestan Province, Northeastern Iran, 2005-2018

“…Overall, the trend analysis during the 14-year period shows a relative increase in the incidence of NMSC. Most studies conducted in different parts of Iran have also shown the increasing trend of NMSC in recent years 7,11,13,23,31 and the higher overall incidence rate in men. 7,32 Despite the increasing trend of NMSC in most parts of Iran, a study based on the cancer registration statistics of Iran reported a decreasing trend for skin cancer during 2000-2016, making skin cancer the second most common cancer in Iran.…”

“…In this study, both forms of skin cancer were more common in men (60.1%), and the men: women ratio was 1.56, which is in line with the reports of the IARC 26 and previous studies. 6,7,9,13,21,23,25,27 Apart from the issue of hijab in women which hinders sunlight exposure, the higher incidence of skin cancer in men could be related to the higher rate of outdoor occupations in men and the subsequent exposure to sunlight and other carcinogenic factors. 3,27 In our study, the highest and lowest ASR of skin cancer was observed in people aged ≥ 85 years for non-melanoma and melanoma, 0-4 years for non-melanoma, and 5-14 years for melanoma.…”

Cancer patterns in Iran: a gender-specific spatial modelling of cancer incidence during 2014–2017

“…Based on our results, non-melanoma skin cancer was the second common cancer among both men and women. Studies indicated that this type of cancer was more common in men than in women and was more commonly observed in older age groups and increasing incidence rates reported in Iran [ 46 , 47 ]. Skin cancer is primarily caused by exposure to ultraviolet radiation [ 48 ].…”

Geospatial Patterns of Non-Melanoma Skin Cancer in Relation to Climate Changes in Iran

“…A higher R 2 value implies a better fit of the model to the data, suggesting that the model captures a larger portion of the variation in the dependent variable based on the independent variables [29]. R 2 can be calculated using equation (11). (11) [ ] [ ]…”

“…Additionally, evidence suggests that outdoor activities, increased exposure to UV radiation, and total sunshine hours can also contribute to the incidence of skin cancer [10]. In this regard, various types of skin cancer are significantly linked to environmental conditions and the level of ultraviolet (UV) radiation exposure [11]. The…”