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Spatial and Temporal Analyses of Cervical Cancer Patients in Upper Northern Thailand

  • Thongsak, Natthapat (Department of Statistics, Faculty of Science, Faculty of Medicine, Chiang Mai University) ;
  • Chitapanarux, Imjai (Division of Therapeutic Radiology and Oncology, Faculty of Medicine, Chiang Mai University) ;
  • Suprasert, Prapaporn (Department of Obstetrics and Gynecology, Faculty of Medicine, Chiang Mai University) ;
  • Prasitwattanaseree, Sukon (Department of Statistics, Faculty of Science, Faculty of Medicine, Chiang Mai University) ;
  • Bunyatisai, Walaithip (Department of Statistics, Faculty of Science, Faculty of Medicine, Chiang Mai University) ;
  • Sripan, Patumrat (Division of Therapeutic Radiology and Oncology, Faculty of Medicine, Chiang Mai University) ;
  • Traisathit, Patrinee (Department of Statistics, Faculty of Science, Faculty of Medicine, Chiang Mai University)
  • Published : 2016.11.01

Abstract

Background: Cervical cancer is a major public health problem worldwide. There have been several studies indicating that risk is associated with geographic location and that the incidence of cervical cancer has changed over time. In Thailand, incidence rates have also been found to be different in each region. Methods: Participants were women living or having lived in upper Northern Thailand and subjected to cervical screening at Maharaj Nakorn Chiang Mai Hospital between January 2010 and December 2014. Generalized additive models with Loess smooth curve fitting were applied to estimate the risk of cervical cancer. For the spatial analysis, Google Maps were employed to find the geographical locations of the participants' addresses. The Quantum Geographic Information System was used to make a map of cervical cancer risk. Two univariate smooths: x equal to the residency duration was used in the temporal analysis of residency duration, and x equal to the calendar year that participants moved to upper Northern Thailand or birth year for participants already living there, were used in the temporal analysis of the earliest year. The spatial-temporal analysis was conducted in the same way as the spatial analysis except that the data were split into overlapping calendar years. Results: In the spatial analysis, the risk of cervical cancer was shown to be highest in the Eastern sector of upper Northern Thailand (p-value <0.001). In the temporal analysis of residency duration, the risk was shown to be steadily increasing (p-value =0.008), and in the temporal analysis of the earliest year, the risk was observed to be steadily decreasing (p-value=0.016). In the spatial-temporal analysis, the risk was stably higher in Chiang Rai and Nan provinces compared to Chiang Mai province. According to the display movement over time, the odds of developing cervical cancer declined in all provinces. Conclusions: The risk of cervical cancer has decreased over time but, in some areas, there is a higher risk than in the major province of Chiang Mai. Therefore, we should promote cervical cancer screening coverage in all areas, especially where access is difficult and/or to women of lower socioeconomic status.

Keywords

Spatial and temporal analyses;quantum geographic information system;cervical cancer;Thailand

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