南喀拉拉邦甲状腺癌发病率的时空空间模式:基于人口的研究
Preethi Sara George1, Aleyamma Mathew2, S Sruthi3
1Additional Professor, Regional Cancer Centre, Thiruvananthapuram, Kerala, India.
Indian journal of public health
|July 17, 2023
概括
三重的甲状腺癌发病率显示了海岸附近的显著空间聚类. 这一发现有助于识别甲状腺癌 (TC) 的高风险区域,并改善癌症控制计划.
科学领域:
- 流行病学 流行病学
- 地理信息系统 (GIS) 是指地理信息系统.
- 公共卫生 公共卫生
背景情况:
- 甲状腺癌 (TC) 是全球最常见的内分泌恶性瘤,发病率不断增加.
- 喀拉拉邦的锡鲁万纳普勒报告说,印度的男性TC发病率最高,女性TC发病率第二高.
- 这一地区TC发病率上升的原因仍未确定.
研究的目的:
- 为了研究甲状腺癌发病率的时空模式在三.
- 确定该地区内TC的地理差异和潜在风险区域.
- 为目标癌症控制策略提供信息.
主要方法:
- 2012-2016年使用基于人口的癌症登记数据对1937例甲状腺癌病例的分析.
- 应用空间和时间统计方法,包括地理空间分析,莫兰索引,Getis-Ord-Gi*,近邻比,内核密度估计和SaTScan.
- 数据按地理区域 (沿海,中部,高地) 和人口因素 (年龄,性别,组织学) 分层.
主要成果:
- 甲状腺癌发病率显示出显著的空间聚类,主要在沿海地区 (56.9%的病例).
- 地理空间分析证实了沿海附近的集群模式,热点和高风险区域.
- 在SaTScan分析中,显著的TC集群的相对风险为1.60 (95% CI:1.03-1.84).
结论:
- 甲状腺癌发病率的显著空间变化存在于锡鲁瓦南塔普勒姆,在沿海地区附近的显著度.
- 该研究成功地确定了甲状腺癌高风险的地理区域.
- 调查结果为该地区开发更有效和更有针对性的癌症控制计划提供了关键数据.
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