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2021, 38(1):17-22.doi:10.13213/j.cnki.jeom.2021.20384

Effect of short-term atmospheric PM2.5 exposure on cardiovascular mortality in China: A meta-analysis


School of Public Health, Inner Mongolia Medical University, Hohhot, Inner Mongolia 010110, China

Received: 2020-08-09;  Accepted:2020-12-03;  Published: 2021-02-04

Corresponding Author: FANG Xin, Email: 18686066179@163.com  

Not required  Obtained

Competng interests  None declared

[Background] Fine particulate matter (PM2.5), the main pollution component of atmospheric particulate matters, is closely related to the occurrence and development of cardiovascular disease.

[Objective] This study is designed to investigate the short-term effect of atmospheric PM2.5 concentration on cardiovascular mortality in China.

[Methods] The databases of Wanfang, VIP, China National Knowledge Infrastructure, and PubMed were searched for the literature reporting a relationship between PM2.5 concentration and cardiovascular disease mortality in China since January 1, 2000-April 22, 2020 using fine particulate matter, ambient particulate matters, cardiovascular disease, and mortality as key words in either Chinese or English. The percentage of cardiovascular disease mortality (ER) with each increase of 10 μg·m-3 PM2.5 was used as the effect index. A short-term effect was defined as < 7 d continuous exposure to any index pollutant. Stata 15.0 software was used for meta-analysIs.

[Results] A total of 581 articles were retrieved, and 18 articles were finally included according to inclusion and exclusion criteria. The random effect model showed that for every 10 μg·m-3 increase in PM2.5, the mortality rate of cardiovascular disease increased by 0.51% (95% CI:0.37%-0.65%), I2=80.2%. After subgrouping PM2.5 annual average concentrations, the heterogeneity of the concentration ≥ 75 μg·m-3 group decreased significantly, and the heterogeneity results of the subgroups of different methods and lag effects and the sensitivity test results were found no significantly change. Egger's test results indicated publication bias (P < 0.05).

[Conclusion] Higher PM2.5 concentrations may increase the mortality of cardiovascular disease.

Key Words: PM2.5 cardiovascular disease;  mortality;  short-term exposure;  meta-analysis 

图 1

文献筛选流程表

Figure 1

Flow chart of literature screening

表 1

纳入文献基本特征

Table 1

Basic characteristics of included literature

图 2

我国PM2.5对心血管系统疾病死亡影响的meta分析森林图(随机效应模型)

Figure 2

Meta-analysis forest map of PM2.5 associated with cardiovascular disease mortality in China (random effects model)

表 2

亚组分析结果

Table 2

Subgroup analysis results

图 3

我国PM2.5对心血管系统疾病死亡率影响meta分析漏斗图

Figure 3

Meta-analysis funnel chart of PM2.5 associated with cardiovascular disease mortality in China

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我国各级医疗机构对儿童用基本药物剂型和规格的需求调查

PM2.5是指空气动力学直径≤ 2.5 μm的颗粒物,又称为细颗粒物,主要来自燃料燃烧、机动车尾气排放、工业生产活动和扬尘等。PM2.5中的可溶性成分及超细颗粒物可穿过肺间质进入血液循环,从而对全身健康产生影响[1]。大量研究显示,长期或短期暴露于不同浓度的PM2.5,可增加心血管事件的发生和死亡风险,且没有安全阈值[2]。2013—2017年我国PM2.5年平均浓度总体呈下降趋势,但2017年全国范围内PM2.5年平均浓度仍超过环境空气质量标准(35 μg·m-3[3]。据估计,2016年有1 790万人死于心血管疾病,占全球死亡人数的31%[4]。近年来,我国心血管疾病患病率持续上升,心血管疾病患者超过2.9亿[5]。2017年我国因大气污染导致心血管疾病过早死亡人数为77万(95% CI:52万~101万),占全国心血管疾病死亡人数的19.4%,其中PM2.5对全国心血管病过早死亡人数的平均贡献率为11.7%[9万(95% CI:6万~11万)] [6]。本研究收集国内大气PM2.5暴露与心血管疾病死亡关系的文献进行meta分析,为大气PM2.5对居民健康影响的危险度评估提供循证依据。

1   材料与方法

1.1   检索策略

中文文献检索:以“(SU=PM2.5 OR SU=大气颗粒物)AND SU=心血管系统疾病AND SU=死亡”为检索式,检索中国知网、万方、维普数据库。英文文献检索:以“fine particulate matter[Mesh] or ambient particulate matters[Mesh] and cardiovascular disease[Mesh] and mortality[Mesh] ”为检索词,检索时间为2000年1月1日—2020年4月22日,检索PubMed数据库。此外通过追溯相关文献的参考文献,收集近年来关于大气PM2.5暴露对心血管疾病影响的流行病学研究文献。

1.2   文献及数据筛选

1.2.1   纳入标准

(1)研究内容为我国大气PM2.5对心血管疾病死亡的影响;(2)研究PM2.5的短期效应,即持续时间不超过7 d所产生的效应[7];(3)研究PM2.5浓度,而非PM2.5中的某种成分;(4)心血管疾病死因归类参照《国际疾病分类》第十版中的I00~I99;(5)研究对象为全人群;(6)研究方法为时间序列研究或病例交叉研究;(7)文献中包含PM2.5对人群心血管疾病死亡风险的RRORER及95% CI;(8)同一研究期间、地点和人口中有两篇及以上的文章具有相同的污染物、健康结果和数据来源,选择最近发表的文章。

1.2.2   排除标准

(1)动物研究、体外毒理学研究、综述及评论文章;(2)研究持续时间不到一年;(3)原文无原始数据;(4)研究结局为心血管系统单一疾病死亡;(5)PM2.5长期暴露对人群心血管疾病产生的慢性死亡效应的文献;(6)缺乏研究年份的文章。

1.2.3   滞后天数选择

空气污染对健康影响的短期效应是暴露后不同滞后时间(以d为单位)的健康影响,不同文献报告的滞后天数不同,本研究采取以下方法来选择滞后天数纳入分析。若文章只报告一个滞后结果,将该结果纳入数据分析中。若文章包含两个及以上滞后结果,选择有统计学意义、效应估计值最大的滞后结果[8]。当单一城市研究与多城市研究的时间和地点重复时,剔除单一城市研究。

1.3   效应指标

以大气PM2.5质量浓度每增加10 μg·m-3时人群心血管疾病死亡率增加的百分比(ER值)为效应指标。若文献中得到的是βRR,可通过公式RR=exp(β)和ER=(RR-1)×100%转换为ER[9]

1.4   统计学分析

文献收集及管理使用EndNote X7,文献数据提取后采用Excel 2016建立数据库。使用Stata 15.0软件进行meta分析,若异质性结果I2 ≥ 50%,则认为多个独立研究异质性较大,采用随机效应模型,否则采用固定效应模型计算合并统计量。若存在异质性,则进行亚组分析及敏感性分析。采用漏斗图及Egger’s检测发表偏倚。异质性分析以α=0.1为检验水准,其余检验水准α=0.05。

2   结果

2.1   纳入文献基本情况

根据上述文献检索方式共检索到581篇文献,依据纳入排除及数据筛选标准共纳入18篇文献(见图 1),中文9篇,英文9篇,包含20个研究城市。纳入文献显示PM2.5对心血管疾病过早死亡有一定影响(ER>0),但有1篇文献过早死亡风险无统计学意义,其ER的95%CI包含0(见表 1)。

图 1

文献筛选流程表

Figure1.

Flow chart of literature screening

表1

纳入文献基本特征

Table1.

Basic characteristics of included literature

2.2   异质性检验

异质性检验显示本研究纳入的文献间存在较高的异质性(Q=95.96,P < 0.1,I2=80.2%),故采用随机效应模型合并,合并后RR(95% CI)=1.005 1(1.003 7~ 1.006 5),即大气PM2.5质量浓度每增加10 μg·m-3,人群心血管疾病死亡率增加0.51%(见图 2)。

图 2

我国PM2.5对心血管系统疾病死亡影响的meta分析森林图(随机效应模型)

Figure2.

Meta-analysis forest map of PM2.5 associated with cardiovascular disease mortality in China (random effects model)

2.3   亚组分析

将纳入研究文献依据《环境空气质量标准》以PM2.5年平均质量浓度以75 μg·m-3为分割点进行亚组分析,结果显示PM2.5质量浓度≥ 75 μg·m-3组的异质性降低,而PM2.5质量浓度 < 75 μg·m-3组的异质性依旧较高;将纳入文献按照效应类型、研究方法进行亚组分析,异质性I2未见明显降低(见表 2)。

表2

亚组分析结果

Table2.

Subgroup analysis results

2.4   敏感性分析

对meta分析中可能导致结果不稳定的因素采用留一交叉法进行验证,剔除初始研究中的其中任意一个研究,根据再次合并后的效应值与原效应值的差距考察其对整体结果的影响。使用敏感性检验发现,剔除任何一篇文献后所有剩余文献数据变化幅度均在可信区间内,未发现对一致性影响明显的文献。

2.5   发表偏倚检验

以lgRR为横坐标,以其标准误为纵坐标绘制漏斗图(图 3),发现分布明显不对称,故纳入文献存在发表偏倚,与Egger’s检验结果一致(P=0.002 < 0.05)。

图 3

我国PM2.5对心血管系统疾病死亡率影响meta分析漏斗图

Figure3.

Meta-analysis funnel chart of PM2.5 associated with cardiovascular disease mortality in China

3   讨论

大气颗粒物污染严重危害人群健康,PM2.5对居民心血管疾病的影响已成为人们关注焦点[28]。2019年Liu等[29]对全球24个国家672个城市PM2.5暴露对心血管疾病影响进行评估,发现大气PM2.5质量浓度每增加10μg·m-3,人群心血管疾病死亡率增加0.55%(95% CI:0.45%~0.66%),本研究结果与其暴露反应评估结果较为相近,但文献的异质性较大,可能是由于浓度水平、地域范围、人群结构不同,导致关于大气PM2.5暴露与心血管疾病死亡率的影响存在较大差异。

3.1   PM2.5浓度差异

从亚组分析的结果可以看出PM2.5浓度是造成暴露反应关系的异质性来源之一,PM2.5的浓度不同,健康反应有所不同。

3.2   地域范围差异

陈晨等[30]利用meta分析将中国40个县的数据合并得到PM2.5质量浓度每增加10 μg·m-3,人群心血管疾病死亡率增加0.53%(95% CI:0.15%~0.90%),本研究得到PM2.5每增加10 μg·m-3,人群心血管疾病死亡率增加0.51%(95% CI:0.37%~0.65%),两者结果相近。Lin等[31]的meta分析研究地区多为珠江三角洲及经济发达地区,其结果为PM2.5质量浓度每增加10 μg·m-3人群心血管疾病死亡率增加1.79%(95% CI:1.22%~2.36%),与本文结果相差较大,可能是由于纳入分析的研究地区差异较大。夏钟等[32]研究发现在评估地区性的PM2.5污染对人体健康的损害时,全国范围研究的异质性明显大于区域性研究,同时其发现珠江三角洲的暴露反应响应值最高。Lin等[31]的meta分析纳入珠江三角洲区域内的研究较多,而本项研究所包含的研究地点在全国范围内分布较为广泛。

3.3   人群结构差异

PM2.5质量浓度每增加10 μg·m-3,意大利人群心血管疾病死亡率增加1.25%(95% CI:0.17%~2.34%)[33],美国人群心血管疾病死亡率增加1.12%(95%CI:1.10%~ 1.15%)[34],加拿大人群心血管疾病死亡率增加1.25%(95%CI:1.19%~1.31%)[35],其结果均高于本研究结果。西班牙[36]、泰国[37]、韩国[38]等PM2.5暴露与心血管疾病死亡率的暴露反应关系也与本研究存在差异,主要与人种、生活习惯等方面的差异造成人体暴露大气污染物剂量不同有关。Ostro等[39]研究显示65岁以上人群属于潜在易感人群。现阶段欧美国家人口老龄化更为严重,因此易感人群所占比例较大。随着我国人口老龄化加剧,潜在易感人群增多,暴露反应关系系数有可能升高。

本研究存在一定的局限性,在进行meta分析时发现文献间异质性较大,可能是由于不同研究地点的地理和季节不同导致温度和湿度差异较大,研究表明环境的温度、湿度等会对PM2.5与心血管疾病的暴露反应关系产生影响[32],这可能是文章异质性的主要来源,本研究亚组分析及敏感性分析并未发现影响异质性的原因,后续可从气象因素进行深入研究。同时大气中其他污染物如总悬浮颗粒物、NO2、SO2等也会对PM2.5与心血管疾病的暴露反应关系产生交互作用[40],各研究地点的大气污染状况不同导致文献间的异质性较大。

本研究利用meta分析方法综合分析PM2.5浓度与心血管疾病死亡率的暴露反应关系,发现我国大气PM2.5浓度升高可能增加心血管疾病的死亡率。

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