绿地暴露和颗粒物暴露与缺血性脑卒中患者死亡关联的队列研究

刘成榕; 刘超; 张莹莹; 赵珂; 张珮瑶; 张丙银; 鹿子龙; 郭晓雷; 薛付忠; 贾贤杰

doi:10.16462/j.cnki.zhjbkz.2024.05.009

绿地暴露和颗粒物暴露与缺血性脑卒中患者死亡关联的队列研究

doi: 10.16462/j.cnki.zhjbkz.2024.05.009

刘成榕¹,
刘超¹,
张莹莹¹,
赵珂¹,
张珮瑶¹,
张丙银²,
鹿子龙²,
郭晓雷²,
薛付忠^{3, 4},
贾贤杰^{1, 3, 4, ,}

1.
蚌埠医科大学公共卫生学院流行病与卫生统计学教研室，蚌埠 233030
2.
山东省疾病预防控制中心慢性非传染性疾病防制所，济南 250014
3.
山东大学齐鲁医学院公共卫生学院生物统计学系，济南 250012
4.
国家健康医疗大数据研究院，济南 250003

基金项目:

蚌埠医学院512人才培育计划 by51201202

安徽省高校自然科学研究项目 2023AH040288

详细信息

通讯作者:
贾贤杰，E-mail: jiaxianjie@bbmc.edu.cn

中图分类号: R181
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- 被引次数: 0
出版历程
- 收稿日期: 2023-07-11
- 修回日期: 2023-10-23
- 网络出版日期: 2024-06-05
- 刊出日期: 2024-05-10

Association of greenness exposure and particulate matter exposure with ischemic stroke patients mortality in a cohort study

1.
Department of Epidemiology and Health Statistics, School of Public Health, Bengbu Medical University, Bengbu 233030, China
2.
Institute of Chronic Non-Communicable Disease Prevention and Control, Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, China
3.
Department of Biostatistics, School of Public Health, Qilu Medical College, Shandong University, Jinan 250012, China
4.
National Institute of Health Care Big Data, Jinan 250003, China

Funds:

Bengbu Medical College 512 Talent Cultivation Program by51201202

Natural Science Research Program for Colleges and Universities in Anhui Province 2023AH040288

More Information

Corresponding author: JIA Xianjie, E-mail: jiaxianjie@bbmc.edu.cn

摘要

摘要: 目的基于卫星遥感数据评估的绿地暴露和颗粒物暴露与缺血性脑卒中(ischemic stroke, IS)死亡的关联。方法在山东5个县(区)收集2013―2019年患IS的个案病例，构建IS患者队列。根据每个患者的居住地址匹配归一化植被指数(normalized differential vegetation index, NDVI)夏季暴露值和PM_2.5、PM₁₀的年均暴露浓度。采用Cox比例风险回归模型探讨长期绿地暴露与PM_2.5和PM₁₀的联合暴露及其交互作用与IS患者死亡的关联，并且按性别、年龄和居住地进行分层分析。采用限制性立方样条函数分别评估绿地暴露、PM_2.5和PM₁₀与IS患者死亡风险的暴露-反应关系。结果共纳入59 084人，因IS死亡4 726人(8.00%)。分析结果显示：在评估NDVI与PM_2.5和PM₁₀的联合暴露时发现NDVI与IS患者死亡风险呈负相关。交互作用结果表明：NDVI每增加0.1个单位，IS患者的死亡风险为0.74(95% CI：0.67~0.82)，PM_2.5每增加10 μg/m³的IS患者的死亡风险为0.94(0.88~1.00)，交互项为1.04 (1.02~1.07)。年龄、性别和居住地是影响NDVI与PM_2.5和PM₁₀的联合暴露及其交互作用与IS患者死亡关联的效应修饰因子。NDVI与IS患者死亡风险的暴露-反应关系曲线呈非线性趋势，PM2.5和PM10与IS患者死亡风险的暴露-反应关系曲线呈“U”型和“J”型。结论绿地暴露可能降低IS患者的死亡风险，同时进行良好的绿地规划以及降低PM_2.5和PM₁₀的暴露浓度可能进一步降低该病的死亡风险。
- 缺血性脑卒中 /
- 绿地暴露 /
- 细微颗粒物 /
- 吸入颗粒物 /
- 回顾性队列研究
Abstract: Objective The interaction between greenness exposure and mortality from ischemic stroke (IS) was assessed based on satellite remote sensing data (NDVI). Methods Individual cases suffering from IS from 2013-2019 were collected in five counties in Shandong to construct a cohort of IS patients. NDVI summer exposure values and annual average exposure concentrations of PM_2.5 and PM₁₀ were matched according to the residential address of each patient. Cox proportional risk models were used to explore the association between long-term greenfield exposure and combined exposure to PM_2.5 and PM₁₀ and their interactions with ischemic stroke death, and the analyses were stratified by sex, age, and residence. Restricted cubic spline functions were used to assess the dose-response relationship between greenfield exposure, PM_2.5 and PM₁₀ and the risk of death in IS patients, respectively. Results The cohort included 59 084 individuals and 4 726 (8.00%) deaths due to IS. The results of the model′s analysis showed that NDVI was negatively associated with the risk of death in patients with IS when assessing the combined exposure of NDVI with PM_2.5 and PM₁₀. The interaction results showed that the IS mortality hazard ratio (HR) for each 0.1-unit increase in NDVI was 0.74 (95% CI: 0.67-0.82), each 10 μg/m³ increase in PM_2.5 was 0.94 (95% CI: 0.88-1.00), and the interaction term was 1.04 (95% CI: 1.02-1.07). Age, sex, and residence were effect modifiers influencing the association of combined exposure to NDVI with PM_2.5 and PM₁₀ and its interaction with death in IS patients. NDVI was nonlinearly associated with IS death, and PM_2.5 and PM₁₀ were associated with IS death in a "U" and "J" pattern, respectively. Conclusions Greenness exposure may reduce the risk of death from IS, while the risk of death from the disease may be further reduced by practicing good greenness planning and by reducing exposure concentrations of PM_2.5 and PM₁₀.
- Ischemic stroke /
- Greenness exposure /
- Fine particulate matter /
- Inhaled particulate matter /
- Retrospective cohort study

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图 1 NDVI、PM_2.5和PM₁₀与缺血脑卒中患者死亡风险的暴露-反应关系

NDVI: 归一化植被指数；PM_2.5: 细颗粒物；PM₁₀: 可吸入颗粒物。

Figure 1. Exposure-response relationships between NDVI, PM_2.5, and PM₁₀ and the risk of death in ischemic stroke patients

NDVI: normalized differential vegetation index; PM_2.5: fine particulate matter; PM₁₀: inhaled particulate matter.

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表 1 研究对象基本特征

Table 1. Basic characteristics of research subjects

变量Variable	缺血性脑卒中患者^① Ischemic stroke patients^①
队列信息The cohort information
随访人数Number of follow-ups	59 084(100.00)
人时数/人年Person-hours/person-years	159 586.68
死亡人数Number of deaths	4 726(8.00)
绿地暴露Grenness Expouse
归一化植被指数Normalized differential vegetation index	0.39±0.11
空气污染/(μg·m^-3) Air pollution/(μg·m^-3)
细颗粒物Fine particulate matter	64.06±9.02
可吸入颗粒物Inhaled particulate matter	115.19±14.48
协变量Covariate
性别Gender
男Male	33 022(55.89)
女Female	26 062(44.11)
年龄组/岁Age group/years
≤60	17 193(29.10)
＞60	41 890(70.90)
居住地区Residence
城市	35 812(60.73)
农村	23 202(39.27)
县级变量County variables
人均GDP /元GDP per capita/CNY	76 126.29(61 176.29, 107 625.21)
床位数/每千人Number of beds/per 1 000 population	4.78(1.39, 10.03)
医生数/每千人Number of doctors / per 1 000 population	5.54(4.30, 15.54)
吸烟率/% Smoking prevalence / %	20.68(12.10, 21.83)
饮酒率/% Drinking rate/%	24.67(17.29, 24.67)
村级变量Village variables
人口密度/ (人·km^-2) Population density/ (persons·km^-2)	988.60(553.59, 4 323.03)
道路密度/(km·km^-2) Road density/(km·km^-2)	6.66±9.29
注：①以人数(占比/%)、x±s和M(P₂₅, P₇₅)表示。 Note: ① Number of people(proportion/%), x±s, M(P₂₅, P₇₅).

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表 2 长期绿地暴露和颗粒物暴露(PM_2.5和PM₁₀)的独立效应和联合暴露与缺血性脑卒中患者死亡的关联

Table 2. Association of independent and joint effects of long-term greenness exposure and particulate matter exposure (PM_2.5 and PM₁₀) with ischemic stroke mortality

主模型和亚组分析 Main model and subgroup analysis	模型1 Model 1 NDVI	模型2 Model 2 PM_2.5	模型3 Model 3 PM₁₀	模型4 Model 4		模型5 Model 5
主模型和亚组分析 Main model and subgroup analysis	模型1 Model 1 NDVI	模型2 Model 2 PM_2.5	模型3 Model 3 PM₁₀	NDVI	PM_2.5	NDVI	PM₁₀
主模型Main model	0.96(0.93~0.98)	1.11(1.09~1.13)	1.06 (1.04~1.08)	0.97(0.94~0.98)	1.06(1.04~1.07)	0.97(0.94~0.99)	1.11 (1.09~1.13)
亚组分析Subgroup analysis
性别Gender
男Male	0.95 (0.91~0.99)	1.01(1.08~1.13)	1.05 (1.03~1.07)	0.96(0.92~1.00)	1.10(1.07~1.13)	0.96(0.92~0.99)	1.05(1.03~1.07)
女Female	0.97 (0.93~1.01)	1.12(1.09~1.15)	1.07 (1.05~1.20)	0.98(0.94~1.03)	1.12(1.09~1.15)	0.98(0.94~1.03)	1.07(1.05~1.09)
年龄组/岁Age group /years
40~60	0.98(0.89~1.08)	1.11(1.05~1.18)	1.06 (1.01~1.12)	0.99(0.90~1.09)	1.12(1.06~1.19)	0.99(0.90~1.09)	1.06(1.01~1.12)
＞60~70	0.92 (0.86~0.98)	1.07(1.03~1.12)	1.04 (1.00~1.07)	0.92(0.86~0.99)	1.07(1.02~1.11)	0.92(0.86~0.98)	1.03(0.99~1.07)
＞70~80	0.97 (0.92~1.03)	1.12(1.08~1.15)	1.07 (1.04~1.20)	0.99(0.93~1.04)	1.12(1.08~1.15)	0.99(0.93~1.04)	1.07(1.04~1.09)
＞80~90	0.95(0.90~1.00)	1.12(1.08~1.15)	1.06 (1.03~1.09)	0.97(0.91~1.02)	1.12(1.08~1.15)	0.96(0.91~1.02)	1.06(1.03~1.09)
＞90	1.03(0.87~1.22)	1.17(1.81~1.28)	1.12(1.04~1.21)	1.05(0.90~1.24)	1.18(1.09~1.28)	1.56(0.90~1.24)	1.13(1.05~1.21)
居住地Residence
城市Urban	1.02(0.97~1.07)	1.07(1.04~1.10)	1.03 (1.01~1.05)	1.03(0.97~1.08)	1.07(1.04~1.10)	1.03(0.97~1.08)	1.03(1.01~1.05)
农村Rural	0.89(0.86~0.93)	1.15(0.12~1.18)	1.10 (1.07~1.12)	0.91(0.87~0.95)	1.14(1.12~1.72)	0.91(0.87~0.94)	1.09(1.07~1.12)
注：NDVI, 归一化植被指数；PM_2.5, 细颗粒物；PM₁₀, 可吸入颗粒物。所有模型都对年龄、性别、居住地、人口密度、床位数、受初等教育人数、人均GDP、道路密度、吸烟率和饮酒率进行了调整。模型1评估了NDVI每增加0.1个单位对缺血性脑卒中患者死亡的影响；模型2评估了PM_2.5每增加10 μg/m^-3对缺血性脑卒中患者死亡的影响；模型3评估了PM₁₀每增加10 μg/m^-3对缺血性脑卒中患者死亡的影响；模型4评估了NDVI每增加0.1个单位和PM_2.5每增加10 μg/m^-3对缺血性脑卒中患者死亡的影响；模型5评估了NDVI每增加0.1个单位和PM₁₀每增加10 μg/m^-3对缺血性脑卒中患者死亡的影响。 Note: NDVI, normalized differential vegetation index; PM_2.5, fine particulate matter; PM₁₀, inhaled particulate matter. All models were adjusted for age, sex, place of residence, population density, number of beds, number of people with primary education, GDP per capita, road density, smoking prevalence, and alcohol consumption. Model 1 assessed the effect of each 0.1-unit increase in NDVI on deaths in ischemic stroke patients; model 2 assessed the effect of each 10 μg/m^-3 increase in PM_2.5 on deaths in ischemic stroke patients; model 3 assessed the effect of each 10 μg/m^-3 increase in PM₁₀ on deaths in ischemic stroke patients; and model 4 assessed the effect of each 0.1-unit increase in NDVI and each 10 μg/m^-3 increase in PM_2.5 on deaths in ischemic stroke patients. per 10 μg/m^-3 increase in NDVI and PM_2.5 per 10 μg/m^-3 increase in PM_2.5 on death in patients with ischemic stroke; and Model 5 assessed the effect of each 0.1 unit increase in NDVI and each 10 μg/m^-3 increase in PM₁₀ on death in patients with ischemic stroke.

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表 3 长期绿地暴露和颗粒物暴露(PM_2.5和PM₁₀)之间的交互作用与缺血性脑卒中患者死亡的关联

Table 3. Association between long-term greenness exposure and particulate matter exposure (PM_2.5, PM₁₀) and ischemic stroke mortality

主模型和亚组分析 Main model and subgroup analysis	模型1 Model 1				模型2 Model 2
主模型和亚组分析 Main model and subgroup analysis	NDVI	PM_2.5	交互项 Interaction	P_交互值 P_interaction value	NDVI	PM₁₀	交互项 Interaction	P_交互值 P_interaction value
主模型Main model	0.74(0.67~0.82)	0.94(0.88~1.00)	1.04(1.02~1.07)	＜0.001	0.75(0.66~0.82)	0.97(0.93~1.01)	1.03(1.01~1.04)	＜0.001
亚组分析Subgroup analysis
性别Gender
男Male	0.74(0.67~0.81)	0.93(0.88~1.00)	1.06(1.03~1.08)	0.001	0.72(0.60~0.85)	0.95(0.89~1.01)	1.03(1.01~1.05)	0.001
女Female	0.78(0.68~0.91)	0.97(0.88~1.06)	1.03(1.00~1.06)	0.001	0.80(0.67~0.96)	1.00(0.93~1.07)	1.02(0.99~1.04)	0.114
年龄组/岁Age group/years
40~60	0.82(0.59~1.15)	0.99(0.81~1.22)	1.00(0.94~1.07)	0.146	0.82(0.55~1.24)	0.99(0.86~1.15)	1.00(0.95~1.05)	0.352
＞60~70	0.80(0.56~1.11)	0.86(0.73~1.01)	1.05(1.00~1.11)	0.005	0.71(0.52~0.97)	0.94(0.84~1.05)	1.01(0.98~1.06)	0.437
＞70~80	0.83(0.69~0.99)	1.00(0.90~1.12)	1.04(1.00~1.08)	0.044	0.83(0.67~1.03)	1.00(0.93~1.09)	1.02(0.99~1.05)	0.112
＞80~90	0.66(0.57~0.81)	0.88(0.80~0.98)	1.07(1.04~1.10)	0.001	0.64(0.52~0.79)	0.92(0.85~0.99)	1.05(1.01~1.10)	0.001
>90	1.37(0.84~2.25)	1.39(1.03~1.80)	0.96(0.88~1.05)	0.256	1.49(0.82~2.70)	1.27(1.03~1.57)	0.97(0.90~1.04)	0.232
居住地Residence
城市Urban	0.98(0.84~1.14)	1.04(0.97~1.13)	1.02(0.99~1.05)	0.190	1.13(0.93~1.38)	1.06(1.00~1.12)	1.00(0.97~1.02)	0.639
农村Rural	0.53(0.45~0.63)	0.77(0.68~0.88)	1.07(1.02~1.12)	0.003	0.43(0.34~0.54)	0.79(0.71~0.88)	1.06(1.02~1.10)	0.002
注：1. NDVI, 归一化植被指数；PM_2.5, 细颗粒物；PM₁₀, 可吸入颗粒物。 2. 所有模型都对年龄、性别、居住地、人口密度、床位数、受初等教育人数、人均GDP、道路密度、吸烟率和饮酒率进行了调整。模型1评估了NDVI每增加0.1个单位、PM_2.5每增加10 μg/m^-3、NDVI(每增加0.1个单位)与PM_2.5(每增加10 μg/m^-3)的乘积项对缺血性脑卒中患者死亡所产生的交互作用；模型2评估了NDVI每增加0.1个单位、PM₁₀每增加10 μg/m^-3、NDVI(每增加0.1个单位)与PM₁₀(每增加10 μg/m^-3)的乘积项对缺血性脑卒中患者死亡的所产生的交互作用。 Note: 1. NDVI, normalized differential vegetation index; PM_2.5, fine particulate matter; PM₁₀, inhaled particulate matter. 2. All models were adjusted for age, sex, place of residence, population density, number of beds, number of people with primary education, GDP per capita, road density, smoking prevalence and alcohol consumption. Model 1 assessed the interaction effect of each 0.1 unit increase in NDVI, each 10 μg/m^-3 increase in PM_2.5, and the product term of NDVI (for each 0.1 unit increase) and PM_2.5 (for each 10 μg/m^-3 increase) on deaths of patients with ischemic stroke; and Model 2 assessed the interaction effect of each 0.1 unit increase in NDVI, each 10 μg/m^-3 increase in PM₁₀, Model 2 assessed the interaction between the product of NDVI (per 0.1 unit increase) and PM₁₀ (per 10 μg/m^-3 increase) on death in ischemic stroke patients.

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