The main aim of this study was to explore the spatio-temporal patterns of breast and prostate cancer incidence and to the best of our knowledge, this is the first study in the province of Kerman to assess spatial variations in the pattern of breast and prostate cancers. The study revealed a high incidence rate of both breast and prostate cancers in the Northwest of the province while it was low in the Southeast part of the Kerman province. The number of people with breast and prostate cancer increased considerably after 25 and 45 years of age, respectively.. Further investigations are needed to assess the drivers in the high-risk areas identified in northwest Kerman. They might be associated with environmental factors and lifestyles (12), poor access to cancer-specific services (27), hereditary reasons (10), and/or socio-economic inequalities (28, 29).
Environmental risk factors such as air pollution (30–32) and heavy metals (33, 34) could be linked to the geographic outcome disparities in breast and\or prostate cancer incidence. We found high-risk areas of breast and prostate cancer in the Northwest of the province during 2014–2017. Kerman is located in the Southeast of the Iranian volcano-plutonic copper belt (35) and arsenic contamination is one of the most significant environmental concerns in the Northwest of this province (36). The Sarcheshmeh copper industrial plant, the biggest copper mine of Iran, is located in the Kerman's Northwest and this area could be contaminated by heavy metals such as arsenic. Field studies report widely distributed travertine rocks in the North of the Sarcheshmeh copper mine and indicated that highly concentrated range of arsenic exists in the travertine rocks (36). This arsenic could move into the water system and contaminate the drinking water in nearby urban and rural communities (36, 37). In these areas, the arsenic concentration is higher than the World Health Organisation (WHO) drinking water recommended values (36, 38, 39). Indeed, arsenic-enriched water is one of the critical challenges in Kerman (36). Arsenic has been categorised as a Group 1 carcinogen factor by the International Agency for Research on Cancer (IARC) (40) and some studies associate arsenic and breast cancer (41–44); its presence in the study area is thus a potential explanation for the increased incidence of breast cancer found. However, other studies did not show any significant association with arsenic (45, 46). The power of this association can change due to local and individual diversities (43). Furthermore, several studies indicate also a significant association between arsenic-enriched water and prostate cancer incidence (44, 47, 48). Thus, high incidence of both breast and prostate cancers in the North-west of Kerman may be associated with arsenic contamination and this should be investigated in future studies.
Increased levels of copper may play a significant role in the initiation of prostate cancer (33). Copper smelting and toxic discharges have led to soil pollution, especially in the region of the smelting plant in Sarcheshmeh Copper Complex. Studies indicated that most contaminated areas are located in the wind directions (49), Which is particularly disturbing is that the polluted areas are also used as grazing land so the toxic elements of soil enter the food chain. These elements include various heavy metals in addition to copper and arsenic, such as lead, molybdenum and cadmium (49). Therefore, soil, water and nutrition of Rafsanjan and the adjacent townships, located the North-West of the province, are subject to the potential negative effects of these heavy metals. Indeed, previous studies have found associations between heavy metals and breast and prostate cancers (50–52). The current study strongly recommends to examine the hypothesis which exposure to heavy metals, especially arsenic and copper, may associate with high incidence of gender-specific cancers in the northwest of Kerman Province.
Air pollution measures, such as particulate matter, have been shown to be associated with risk of breast cancer (31, 32). Further studies to confirm the effects of airborne pollution, especially particulate matter, on the risk of breast cancer is suggested. Fazzo et al. (2016) used a spatial approach to estimate the industrial air pollution impact on 17 selected neoplasms in Priolo, Sicily Italy. The territory around the industrial Sicilian area of Priolo, Italy, was defined as a contaminated site of national priority for remediation because of diffuse environmental contamination caused by large industrial settlements. The study found a higher incidence of breast cancer in the contaminated area compared to the rest of the province (53).
Previous studies highlighted that poor access to health care services lead to poor health outcomes (54, 55) such as increased incidence of cancer (27, 56). The high incidence of gender-specific cancers in some regions of the study area may be due to their considerable distance from the provincial capital with limited cancer screening programmes. On the other hand, parts of the study area in the South had the lowest incidence of both breast and prostate cancers, although they were located even further away from the provincial capital. However, proximity to health care services does not directly translate into access because of potential factors such as poor socio-economic status and low level of education that could be associated with poor access (54). GIS enable researchers to assess the revealed access to cancer services through combing spatial and non-spatial factors (55, 57, 58) and the results suggest measuring access to cancer prevention programmes in the study area as the first step of examining this hypothesis. Previous studies have highlighted the impact of the socio-economic status on the differences in breast and prostate cancers incidence (59–61). Assessing the impact of socio-economic status on the geographic disparities of the gender-specific cancers incidence in the study area can be done by analysing the overall spatial structure or identifying high-risk areas. This also warrants further studies.
Hereditary cancer syndromes, a type of inherited disorder in which there is a higher-than-normal risk of certain types of cancer, are caused by mutations in certain genes passed from parents to children (62–66). Indeed, certain patterns of cancer may be seen within families, e.g., hereditary breast (65) and lynch syndrome (63). Hereditary cancer screening programmes (67–69) have made it possible to detect many of the approximately 5–10% of breast cancers caused by a genetic predisposition (70, 71) and ultimately to prevent them before they occur. Also, there are studies that assessed risk of prostate cancer associated with hereditary cancer syndromes. This highlights the risk of prostate cancer in people with a family history of cancer that strongly associates with early-onset disease (66). We strongly recommend researchers and policymakers to perform hereditary cancer screening and genetic testing in high-risk areas of the province and assess the association of the results with the high incidence rate of both breast and prostate cancers in these areas.
Spatio-temporal cluster analysis plays a significant role in visualising and quantifying geographical variation in patterns of disease incidence. This study used Local Moran’s I to identify the high and low clusters as well as spatial outliers of breast and prostate cancer. Global Moran’s I and Getis-Ord General G statistic are the Global clustering methods which investigate the level of spatial autocorrelation in disease patterns. While Local Moran’s I and Getis-Ord Gi* are the local cluster analyses which can indicate the locations of the clusters. Although Getis-Ord Gi* statistic is used for identifying hot and cold spots, Local Moran's I method is also effective for assessing statistically significant spatial outliers (72). Thus, it was applied over other local methods (26, 73) and successfully assessed disease hotspots (74, 75). If a study wants to use these methods to analyse the spatial pattern of incident data, it should consider aggregating the incident data into polygons. The main question here is the geographical scale that should be used for aggregation because it could affect the results. In this study, we conducted the analyses in both in county and district level.