Temporal and spatial analyses of colorectal cancer incidence in Yogyakarta, Indonesia: a cross-sectional study

Geospat Health. 2023 May 25;18(1). doi: 10.4081/gh.2023.1186.

Abstract

We aimed to explore the district-level temporal dynamics and sub-district level geographical variations of colorectal cancer (CRC) incidence in the Special Region of Yogyakarta Province. We performed a cross-sectional study using data from the Yogyakarta population-based cancer registry (PBCR) comprised of 1,593 CRC cases diagnosed in 2008-2019. The age-standardized rates (ASRs) were determined using 2014 population data. The temporal trend and geographical distribution of cases were analysed using joinpoint regression and Moran's I statistics. During 2008-2019, CRC incidence increased by 13.44% annually. Joinpoints were identified in 2014 and 2017, which were also the periods when annual percentage change (APC) was the highest throughout the observation periods (18.84). Significant APC changes were observed in all districts, with the highest in Kota Yogyakarta (15.57). The ASR of CRC incidence per 100,000 person- years was 7.03 in Sleman, 9.20 in Kota Yogyakarta, and 7.07 in Bantul district. We found a regional variation of CRC ASR with a concentrated pattern of hotspots in the central sub-districts of the catchment areas and a significant positive spatial autocorrelation of CRC incidence rates in the province (I=0.581, p<0.001). The analysis identified four high-high clusters sub-districts in the central catchment areas. This is the first Indonesian study reported from PBCR data, showing an increased annual CRC incidence during an extensive observation period in the Yogyakarta region. A heterogeneous distribution map of CRC incidence is included. These findings may serve as basis for CRC screening implementation and healthcare services improvement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Colorectal Neoplasms* / epidemiology
  • Cross-Sectional Studies
  • Humans
  • Incidence
  • Indonesia / epidemiology
  • Spatial Analysis