Skin cancer incidence in the study area had an increasing trend during the study period (mid-March 2011 to mid-March 2017). Of 4302 patients with skin cancer, 2602 cases (60%) were male. Figure 2 illustrates the age-standardized distribution in all patients with skin cancer. According to this chart, the rate of reported skin cancer cases in the 80-89 age group (in both male and female genders) was higher compared to other age groups. The distribution of rates was further analyzed in the spatial findings section.
The overall average cancer incidence rate was 71.66 (per 100,000). The incidence EBS rate average in the male group (85.40 per 100,000) was higher than the female group (60.02 per 100,000). In terms of total incidence rates, males with a value of 109.89 (per 100,000) had a higher cancer incidence rate than females (81.25 per 100,000). The cancer average incidence rate in patients who were not exposed to sunshine was 7.14 (per 100,000). This rate increased to 64.96 in patients who were exposed to the sun. The rate in patients not exposed to the sun was 3.6 (per 100,000) in the male group and 10.94 (per 100,000) in the female group. However, the incidence rates in the sunshine-exposed group increased to 81.57 (per 100,000) in the male group and 49.42 81.57 (per 100,000) in the female group.
Figure 3 shows the maps of skin cancer EBS incidence rates by gender and category (SE: Sunshine-Exposed or NSE: Non-Sunshine-Exposed). According to these maps, in an NSE status, the incidence rates in the whole study area were below ten (per 100,000) (Figure 3a) and represented a homogeneous geographical distribution pattern. As Figure 3c and Figure 3e illustrate, this homogeneous geographical pattern of low rates is repeated in male and female groups. The difference is that women's rate (10.94 per 100,000) was higher than men's (3.60 per 100000). But when patients were exposed to sunshine, a different pattern was observed.
Some counties experienced very high rates (more than 70 per 100,000) (Figure 3b) (including Mamasani, Abadeh, Kavar, Neyriz, and Shiraz). In the male group (Figure 3d), nearly 80% of counties experienced these high rates. In the female group (Figure 3f), high rates are also seen in all counties, although only one county (Mamasani) had the highest rate (74.82 per 100,000).
The result highlights a significant difference in the geographical distribution of EBS rates between the two categories, and in the male group, all counties experienced higher EBS incidence rates.
To measure the spatial autocorrelation of incidence rates, ALMI was used. This approach shows the pattern of the geographical distribution of EBS rates on maps. The ALMI related maps are depicted in Figure 4. As established, based on total incidence EBS rates in NSE cases (Figure 4a), only two LH outliers were recognized, which included northwest counties. That is, the rates in these regions were lower compared to their neighbors. Again, in the same NSE category and the male group, a cluster (LL) in the northern region and an outlier (LH) in the southern area of the study area were formed (Figure 4c); the LL cluster highlights that the county itself had a very low rate and the neighbors also had low rates. In the female group (Figure 4e), in the NSE category, an outlier (LH) in the north, a cold spot (LL), and two hot spots (HH) were formed in the center of the study area. HH clusters show that both counties (Sarvestan and Kharameh) had higher rates, and the neighbors also had high rates.
In the SE category, in terms of total EBS rates (Figure 4b), three HH clusters in the north, one LH outlier in the northeast, one HL outlier in the center, and LL clusters in the south were formed. The pattern of the male group (Figure 4d) almost follows the total EBS rates clustering pattern. The difference is that the number of LH outliers has increased in the northern regions. In the female group (Figure 4f), only one HH cluster and one LH outlier were formed in the northwest.
In summary, there is a diversity of spatial clusters and outliers in total EBS rates maps. The clustering pattern of the male group followed the pattern of total clustering. But in the female group, this clustering was significantly different and strongly random.
Hot spot analysis
Since the Z-score values obtained in the skin cancer EBS rates were higher than 1.96 in some areas, we used the Getis-Ord Gi* statistic to identify hot spots. Figure 5 shows the results of Getis-Ord Gi* statistic for cancer EBS rates in two categories (NSE and SE) for the study population (Total, male, and female). Figure 5a illustrates the total skin cancer incidenceEBS hotspot map in the NSE category. According to this map, only one county in the northwest (Mamasani) was identified as a hotspot with higher Z-scores, lower p-values, and with 90% confidence. In this category and male group (Figure 5c), three hotspots were identified in the northwest (Mamasani and Kazerun) and southwest (Mohr) with 90% confidence. In the female group (Figure 5e), two hotspots were formed in the study area's central part with 95% confidence (Sarvestan and Kharameh).
Figure 5b depicts the total skin cancer incidence EBS hotspot map in the SE category. Unlike the NSE group, in this category, three different counties (Shiraz, Kazerun, and Sepidan) were identified as hotspots with 90-95% confidence, which were all concentrated in the north-western area. In other words, the pattern of hotspots was different in the two categories. In the SE category and the male group (Figure 5d), two hotspots, Shiraz in the west and Kharameh in th center were formed with 90% and 95% confidence respectively. According to Figure 5f, the pattern of hotspots in the female group was different. In this group, two hotspots (Rostam in the northwest and Kazerun in the west) were formed in the study area with 90% and 95% confidence, respectively.
As a result, hotspots were formed mostly in the west and northwest. Also, the pattern of hotspots in the female group was different from the male group. Some counties (Mamasani) in the NSE category and some others (Shiraz) in the SE category were the most frequent hotspots.