基于PCA-GAM的中国空气污染与肺癌疾病负担关联分析及预测

马倩倩; 陈保站; 谭中科; 王振博

doi:10.16462/j.cnki.zhjbkz.2024.09.008

基于PCA-GAM的中国空气污染与肺癌疾病负担关联分析及预测

doi: 10.16462/j.cnki.zhjbkz.2024.09.008

马倩倩^{1, 2, ,},
陈保站^{1, 2},
谭中科¹,
王振博^{1, 2}

1.
郑州大学第一附属医院互联网医疗系统与应用国家工程实验室，郑州 450052
2.
郑州大学第一附属医院远程医学中心，郑州 450052

基金项目:

国家资助博士后研究人员计划 GZC20232414

河南省医学科技攻关项目 LHGJ20210323

详细信息

通讯作者:
马倩倩，E-mail: qian_ma91green@163.com

中图分类号: R734; R122.7
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- 被引次数: 0
出版历程
- 收稿日期: 2024-02-01
- 修回日期: 2024-06-17
- 网络出版日期: 2024-10-24
- 刊出日期: 2024-09-10

Association analysis between air pollution and lung cancer burden and prediction of disease burden based on PCA-GAM in China

MA Qianqian^{1, 2
, ,},
CHEN Baozhan^{1, 2},
TAN Zhongke¹,
WANG Zhenbo^{1, 2}

1.
National Engineering Laboratory for Internet Medical Systems and Applications, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
2.
Telemedicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China

Funds:

National Support Programme for Postdoctrol Researchers of China GZC20232414

Jonit Construction Project of the Henan Province Medical Science and Technology LHGJ20210323

More Information

Corresponding author: MA Qianqian, E-mail: qian_ma91green@163.com

摘要

摘要: 目的探索中国肺癌疾病负担与空气污染时间序列特征，进行关联性分析及肺癌疾病负担预测，为肺癌防控工作提供参考依据。方法收集1990―2019年中国肺癌发病与死亡疾病负担数据，以及1970―2015年空气污染数据。通过灰色关联度分析与广义加性模型研究空气污染与肺癌疾病负担的关联，预测2020―2022年肺癌疾病负担。结果 1990―2019年，中国肺癌发病率年均复合增长率为3.48%，死亡率年均复合增长率为3.15%。细颗粒物(fine particulate matter, PM_2.5)、可吸入颗粒物(inhalable particulate matter, PM₁₀)、黑碳(black carbon, BC)、有机碳(organic carbon, OC)、二氧化硫(sulfur dioxide, SO₂)、氨气(ammonia, NH₃)、氮氧化物(nitrogen oxide, NOx)、一氧化碳(carbon monoxide, CO)、非甲烷挥发性有机化合物(non-methane volatile organic compounds, NMVOC) 与肺癌发病率序列关联最大的序列间距分别为19年、19年、19年、19年、13年、20年、10年、19年、4年，与肺癌死亡率序列关联最大的序列间距分别为19年、19年、19年、19年、12年、12年、10年、19年、4年。非参数效应分析显示，PM_2.5等污染物与肺癌疾病负担存在曲线关联。预测2020―2022年我国肺癌发病率依次为59.547/10万、59.838/10万、58.026/10万，肺癌死亡率依次为53.465/10万、54.106/10万、53.458/10万。结论空气污染致肺癌发病与死亡存在滞后效应，与肺癌疾病负担呈曲线正相关。2020―2022年中国肺癌疾病负担将呈波动变化趋势。
- 肺癌 /
- 疾病负担 /
- 空气污染 /
- 灰色关联度 /
- 广义相加模型 /
- 主成分分析
Abstract: Objective To explore the time series characteristics of the disease burden of lung cancer and air pollution in China, and to analyze their correlation and predict the disease burden of lung cancer, and provide a reference for lung cancer prevention and control. Methods The data of disease burden such as the incidence and death of lung cancer in China from 1990 to 2019, and air pollution data from 1970 to 2015 were collected. Grey correlation analysis and generalized additive model were used to study the association between air pollution and lung cancer disease burden, and to predict the lung cancer disease burden from 2020 to 2022. Results From 1990 to 2019, the compound annual growth rate of the incidence of lung cancer in China was 3.48%, and the compound annual growth rate of the mortality rate was 3.15%. The lag times of PM_2.5, PM₁₀, BC, OC, SO₂, NH₃, NOx, CO, and NMVOC sequences most correlated with the incidence of lung cancer were 19 years, 19 years, 19 years, 19 years, 13 years, 20 years, 10 years, 19 years, 4 years. While the lag times of the sequences with the greatest correlation between the above air pollutants and lung cancer mortality were 19 years, 19 years, 19 years, 19 years, 12 years, 12 years, 10 years, 19 years, and 4 years, respectively. Nonparametric effect analysis showed a curvilinear correlation between pollutants such as PM_2.5 and the disease burden of lung cancer. It is predicted that the incidence rate of lung cancer in China from 2020 to 2022 will be 59.547/100 000, 59.838/100 000 and 58.026/100 000 respectively; The mortality rates of lung cancer will be 53.465/100 000, 54.106/100 000, and 53.458/100 000, respectively. Conclusions There is a hysteresis effect on the incidence and death of lung cancer caused by air pollution, and they are curvilinearly positively correlated. The disease burden of lung cancer in China has shown a fluctuated trend from 2020 to 2022.
- Lung cancer /
- Disease burden /
- Air pollution /
- Grey relation analysis /
- Generalized additive model /
- Principal component analysis

HTML全文

图 1 1990―2019年中国肺癌疾病负担趋势图

Figure 1. Trends in the disease burden of lung cancer in China from 1990 to 2019

下载: 全尺寸图片幻灯片

图 2 基于主成分的GAM肺癌疾病负担预测模型拟合图

A，发病率预测图；B，死亡率预测图；GAM, 广义相加模型。

Figure 2. Fitting the disease burden of lung cancer using GAM model based on principal component

A, morbidity prediction chart; B, mortality prediction chart; GAM, generalized additive model.

下载: 全尺寸图片幻灯片

表 1 空气污染物与肺癌发病与死亡的GAM分析

Table 1. GAM models of air pollutants and lung cancer incidence and mortality

变量Variable	肺癌发病模型Lung cancer incidence model			肺癌死亡模型Lung cancer mortality model
变量Variable	v	F值value	P值value	v	F值value	P值value
s(PM_2.5)	2.186	23.569	＜0.001	2.220	27.697	＜0.001
s(PM₁₀)	2.243	38.044	＜0.001	2.293	43.978	＜0.001
s(BC)	5.194	82.522	＜0.001	5.281	89.422	＜0.001
s(OC)	3.362	1.001	0.049	3.333	1.133	0.031
s(SO₂)	2.346	25.931	＜0.001	2.642	27.050	＜0.001
s(NOx)	4.489	200.083	＜0.001	4.413	220.362	＜0.001
s(CO)	2.454	114.651	＜0.001	2.682	123.086	＜0.001
s(NMVOC)	7.637	229.773	＜0.001	7.593	202.483	＜0.001
s(NH₃)	5.693	222.013	＜0.001	1.753	41.441	＜0.001
注：PM_2.5，细颗粒物；PM₁₀，可吸入颗粒物；SO₂，二氧化硫；NH₃，氨气；OC，有机碳；BC，黑碳；CO，一氧化碳；NOx，氮氧化物；NMVOC，非甲烷挥发性有机化合物；GAM, 广义相加模型。 Note: PM2.5, fine particulate matter; PM₁₀, inhalable particulate matter; SO₂, sulfur dioxide; NH₃, ammonia; OC, organic carbon; BC, black carbon; CO, carbon monoxide; NOx, nitrogen oxide; NMVOC, non-methane volatile organic compounds; GAM, generalized additive model.

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