Spatial Analysis and Geoclimatic Factors Associated With the Incidence of Acute Lymphoblastic Leukemia in Iran During 2006–2014: An Environmental Epidemiological Study Publisher Pubmed



Pordanjani SR^{1, 2} ; Kavousi A³ ; Mirbagheri B⁴ ; Shahsavani A^{5, 6} ; Etemad K⁷
Source: Environmental Research Published:2021

Abstract

Background and objectives: The present study aims to determine the cumulative incidence rate of acute lymphoblastic leukemia (ALL), the degree of spatial autocorrelation and clustering of ALL, the hotspot and coldspots of ALL and geoclimatic conditions affecting the incidence of ALL in Iran and to draw a comparison between global and local regression models. Materials and methods: In this ecological study, an exploratory-etiologic multiple-group method has been adopted to investigate all children under 15 years of age with ALL in Iran during 2006–2014. Data analysis was performed using Mann Whitney U, Pearson correlation coefficients (PCCs), Global Moran's I, Optimized hotspot analysis (OHSA), Global Poisson regression (GPR), Geographically Weighted Poisson Regression (GWPR) at a significant level of α = 0.05. Results: The cumulative incidence rate of ALL was estimated at 21,315 per 100,000 Iranian children under 15 years of age. The value of Global Moran's I index was estimated 0.338 and significant (<0.001 P-value). Coldspots were observed in north and northwest of Iran and hotspots were identified in south, southwest and mid-east of Iran. In the present study, Max Temperature of Warmest Month (MTWM) and Direct Normal Irradiation (DNI) were risk factors and Precipitation of the Coldest Quarter (PCQ) and Altitude (AL) were protective factors in the incidence of ALL, even though the non-stationarity of local coefficients and local t-values was clear. GWPR, by capturing and applying spatial heterogeneity and spatial autocorrelation, had a greater performance and goodness of fit than GPR. Discussion: ALL has created spatial clusters in Iran. The incidence of ALL is the result of synergistic interaction between environmental, infectious, geographical and genetic risk factors. It is recommended to use of local models in ecological studies. © 2021 Elsevier Inc.