تعداد نشریات | 20 |
تعداد شمارهها | 1,149 |
تعداد مقالات | 10,518 |
تعداد مشاهده مقاله | 45,416,357 |
تعداد دریافت فایل اصل مقاله | 11,292,311 |
Clustering of Breast Cancer Cases among Women from Kurdistan Province, Iran: A Population-based Cross-sectional Study | ||
Middle East Journal of Cancer | ||
مقاله 8، دوره 9، شماره 1، فروردین 2018، صفحه 49-55 اصل مقاله (932.35 K) | ||
نوع مقاله: Original Article(s) | ||
شناسه دیجیتال (DOI): 10.30476/mejc.2018.42104 | ||
نویسندگان | ||
Seyed Mehdi Hosseini1؛ Masoud Parvin2؛ Payam Shokri3؛ Milad Fadaie4؛ Bahman Ghaytasi5؛ Manoochehr Khondabi1؛ Meysam Olfatifar* 3، 1؛ Ebrahim Chavoshi6 | ||
1Student Research Committee, Department of Epidemiology, Hamadan University of Medical Sciences, Hamadan, Iran | ||
2Student Research Committee, Department of Dentistry, Hamadan University of Medical Sciences, Hamadan, Iran | ||
3Social Determinants of Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran | ||
4Department of Biotechnology, Hamadan University of Medical Sciences, Hamadan, Iran | ||
5Department of Public Health and Disease Prevention and Control Center, Health Deputy, Kurdistan University of Medical Sciences, Sanandaj, Iran | ||
6Faculty of Agriculture, Bu Ali Sina University, Hamadan, Iran | ||
چکیده | ||
Background: Spatial analysis is one of the required tools of epidemiology and public health sciences. This study intends to detect significant clusters of breast cancer cases in Kurdistan Province, Iran.Methods: We obtained data that pertained to breast cancer cases during 2005-2014 from the Health Deputy at Kurdistan University of Medical Sciences. After application of spatial scan statistics to detect the purely spatial (aggregation of cases in particular locations of space) and space-time (diseases clusters in space that depend on the time period) clusters, we calculated the population attribution risk (%) values to better distinguish the detected clusters.Results: We observed that the second secondary purely spatial cluster (P=0.0051) had the highest population attribution risk (%) of 3.8 and the primary space-time unadjusted cluster (P=0.0019) had the lowest population attribution risk (%) of 0.67 of all the detected clusters. Before we applied the adjustment, both the space-time and purely spatial clusters had similar locations. However, after adjustment for age, the space-time clusters location shifted and population attribution risk (%) values changed (between 0.02 and 0.4).Conclusion: Population attribution risk (%) value differences and clusters’ temporal and spatial variations before and after adjustments can represent disease interventions impact. Additional studies should be conducted to strengthen the registering and reporting system to determine other influencing factors. | ||
آمار تعداد مشاهده مقاله: 3,676 تعداد دریافت فایل اصل مقاله: 1,205 |