歐奕含,張小玲,3*,張 瑩,康 平

西安BC、PM2.5與氣溫協(xié)同對(duì)心腦血管疾病死亡的影響

歐奕含1,2,張小玲1,2,3*,張 瑩1,2,康 平1,2

(1.成都信息工程大學(xué)大氣科學(xué)學(xué)院,四川 成都 610225；2.高原大氣與環(huán)境四川省重點(diǎn)實(shí)驗(yàn)室,四川 成都 610225；3.成都平原城市氣象與環(huán)境四川省野外科學(xué)觀測(cè)研究站,四川 成都 610225)

利用西安市2014～2015年BC、PM2.5和氣溫及心腦血管疾病每日死亡人數(shù)等資料,基于時(shí)間序列的廣義相加模型中的主效應(yīng)模型、非參數(shù)二元響應(yīng)模型和溫度分層模型對(duì)其進(jìn)行研究.結(jié)果表明,BC、PM2.5對(duì)心腦血管疾病死亡人數(shù)的影響存在滯后效應(yīng),最佳滯后時(shí)間下,BC、PM2.5濃度每增加1個(gè)IQR(BC:5.31μg/m3,PM2.5:40.30μg/m3),心腦血管疾病每日死亡人數(shù)ER(95%CI)分別為3.53%(95%CI:1.86,5.23)、2.01%(95%CI:1.06,2.97).氣溫與心腦血管疾病每日死亡人數(shù)的暴露反應(yīng)關(guān)系呈“V”型分布特征,最適溫度為26℃.低溫和高污染物濃度對(duì)心腦血管疾病的影響存在協(xié)同放大效應(yīng),當(dāng)氣溫低于26℃時(shí),BC對(duì)人群健康風(fēng)險(xiǎn)比PM2.5更大.對(duì)于心腦血管疾病而言,不同人群的易感程度不同,女性群體對(duì)BC、PM2.5暴露更為敏感.當(dāng)BC、PM2.5同時(shí)納入其它一種或幾種氣態(tài)污染物時(shí),對(duì)ER值無(wú)較大影響.BC僅占PM2.5濃度的一小部分,但健康影響不容忽視,BC可作為評(píng)估大氣污染物健康風(fēng)險(xiǎn)的重要空氣質(zhì)量指標(biāo).

黑碳；PM2.5；氣溫；協(xié)同效應(yīng)；心腦血管系統(tǒng)疾?。怀~死亡風(fēng)險(xiǎn)

西安市屬于西北地區(qū)的典型工業(yè)城市和商貿(mào)交通中心.隨著城市化進(jìn)程的加快,汽車尾氣、工業(yè)燃煤等污染物排放增加,以細(xì)顆粒物(PM2.5)為主要特征的區(qū)域持續(xù)性大氣復(fù)合污染頻發(fā),致使西安市大氣污染問(wèn)題越發(fā)嚴(yán)峻[1-4].空氣污染日益影響居民健康,已經(jīng)備受公眾關(guān)注[5].

現(xiàn)有的流行病和毒理學(xué)研究指出,顆粒物污染的人群不良健康效應(yīng)最為顯著,且粒徑越小引起的不良效應(yīng)越強(qiáng),相對(duì)于可吸入顆粒物(PM10),PM2.5粒徑小、比表面積大,易于富集空氣中的細(xì)菌、病毒、有機(jī)物等有毒有害物質(zhì),對(duì)健康產(chǎn)生的威脅大,更易誘發(fā)呼吸系統(tǒng)、心腦血管系統(tǒng)等疾病[6-12].

黑碳(BC)是PM2.5的重要組分,由生物質(zhì)或化石燃料不完全燃燒產(chǎn)生,它具有吸光性強(qiáng)易擴(kuò)散的特性,其空氣動(dòng)力學(xué)直徑主要分布在0.01～1.0μm的超細(xì)粒子區(qū),高濃度的BC氣溶膠會(huì)加重霧霾嚴(yán)重程度,增加空氣污染的復(fù)雜性[13].大氣中BC以鏈條狀、球體形態(tài)而聚合在一起,因其不規(guī)則的物理結(jié)構(gòu)會(huì)大大吸附空氣中其他致癌物質(zhì),從而影響人體健康狀況,國(guó)際癌癥機(jī)構(gòu)已經(jīng)將BC歸類為 2B 類致癌物質(zhì)[14].BC會(huì)嚴(yán)重地影響人體健康,引起病癥的病理機(jī)制與PM2.5相同,它直接進(jìn)入人體肺部的深處并進(jìn)入肺泡[15],伴隨血液循環(huán)到達(dá)人體全身,對(duì)人體心腦血管系統(tǒng)、神經(jīng)系統(tǒng)等人體系統(tǒng)產(chǎn)生不利影響.一項(xiàng)對(duì)BC與日死亡率的時(shí)間序列研究的Meta分析[16]表明,BC與心肺死亡率之間呈顯著的正相關(guān)關(guān)系,該結(jié)果在其他幾項(xiàng)研究中得到證實(shí)[17-18].

流行病學(xué)研究發(fā)現(xiàn),BC的健康影響可能與PM2.5有所不同,某些方面可能略強(qiáng)于PM2.5[19-23].世界衛(wèi)生組織評(píng)估黑碳的健康效應(yīng)報(bào)告中指出,BC濃度每增加1μg/m3引起的心腦血管疾病死亡率增加1.77%,PM2.5濃度每增加1μg/m3引起的心腦血管疾病死亡率增加0.19%.我國(guó)對(duì)BC與健康的影響研究起步較晚,研究較少,主要集中在北京[24-27]、上海[13-28],所以相關(guān)研究還需深入.

與污染物相比,不良?xì)庀髼l件也是影響人群健康的危險(xiǎn)因素.大量研究表明,氣溫是影響人體健康最重要的因素之一[29-32],氣溫過(guò)高或過(guò)低均易誘發(fā)相關(guān)疾病.氣溫和顆粒物都與疾病有關(guān),但以往研究對(duì)所謂的排除混雜因素的數(shù)學(xué)處理具有一定的片面性,當(dāng)探究氣溫對(duì)疾病的影響時(shí),往往把污染物作為混雜因子排除;而在研究污染物對(duì)疾病的影響時(shí),把氣溫作為混雜因素來(lái)考慮[33].

國(guó)外對(duì)污染物與氣溫的交互作用影響做了相關(guān)研究,發(fā)現(xiàn)溫度會(huì)改變顆粒物對(duì)死亡率的影響程度[34],例如高溫條件能使PM10帶來(lái)更多不利的健康影響[35].一項(xiàng)氣溫與O3對(duì)美國(guó)60個(gè)東部城市的死亡影響研究中也發(fā)現(xiàn)高溫能增加O3的死亡風(fēng)險(xiǎn)[36].國(guó)內(nèi)學(xué)者[37-38]研究發(fā)現(xiàn)高溫條件能增加顆粒物的心血管疾病、呼吸系統(tǒng)風(fēng)險(xiǎn),高濃度顆粒物在該種氣溫條件下會(huì)對(duì)人群健康的負(fù)面影響產(chǎn)生協(xié)同加強(qiáng)效應(yīng)[26,39].與國(guó)外相比,國(guó)內(nèi)在該方面的研究還比較少.

基于此,本研究采用近年來(lái)國(guó)際上通用的危險(xiǎn)度評(píng)價(jià)方法—基于時(shí)間序列的廣義相加模型(GAMs),以心腦血管疾病死亡數(shù)據(jù)為暴露效應(yīng)指標(biāo),選取人口密度大、顆粒物污染重的西安市作為代表城市,探討該市氣溫和BC、PM2.5濃度和氣溫對(duì)人群對(duì)心腦血管疾病死亡的影響,以及兩者協(xié)同作用的影響,為西安市大氣污染防治措施和政策制定提供科學(xué)參考.

1 資料與方法

1.1 資料來(lái)源

所用疾病資料:2014年1月1日～2015年12月31日心腦血管疾病死亡資料來(lái)自于中國(guó)疾病預(yù)防控制中心(CDC)全國(guó)疾病監(jiān)測(cè)死因監(jiān)測(cè)數(shù)據(jù)集.根據(jù)國(guó)際疾病分類標(biāo)準(zhǔn)第10版本(ICD-10)對(duì)死因進(jìn)行分類,整理得到的心腦血管疾病資料(ICD-10 編碼:I00-I99)共45544例,其中男性24497l例,女性21047例.

大氣環(huán)境監(jiān)測(cè)資料:本研究所用同期的日均污染數(shù)據(jù)包括BC、PM2.5、SO2、NO2共4種.除BC外其他3種污染物數(shù)據(jù)來(lái)源于全國(guó)城市空氣質(zhì)量實(shí)時(shí)發(fā)布平臺(tái)(http://113.108.142.147:20035/),按照《環(huán)境空氣質(zhì)量標(biāo)準(zhǔn)》(GB 3095—2012)[40]計(jì)算日平均濃度(去除清潔對(duì)照站),同時(shí)為了保證數(shù)據(jù)的可靠性,將由于不可抗(停電、儀器校準(zhǔn))因素出現(xiàn)的缺測(cè)情況剔除;BC數(shù)據(jù)來(lái)源于中國(guó)氣象局西安涇河觀測(cè)站點(diǎn)(108°58￠N,34°26￠E),該站為國(guó)家級(jí)大氣成分觀測(cè)站,觀測(cè)儀器為美國(guó)MAGEE公司的7波段Aethalometer黑碳儀器(AE31),利用黑碳對(duì)光的吸收特性進(jìn)行測(cè)量,數(shù)據(jù)采集頻率均為5min,選擇波長(zhǎng)為880nm的BC濃度,數(shù)據(jù)經(jīng)過(guò)質(zhì)量控制后處理成1h平均值和日平均值.

氣象資料:本研究所用到的氣象資料來(lái)源于中國(guó)氣象局西安涇河站,該站為基本氣象站,是西安市的氣象代表站,由國(guó)家氣象信息中心提供,包括日均氣溫、相對(duì)濕度、風(fēng)速、氣壓.所有獲取的數(shù)據(jù)均經(jīng)過(guò)國(guó)家氣象信息中心嚴(yán)格的質(zhì)量控制和檢查.

1.2 研究方法

1.2.1 半?yún)?shù)廣義相加模型的建立 采用SPSS19.0軟件進(jìn)行統(tǒng)計(jì)描述,采用R4.3.2統(tǒng)計(jì)分析方法軟件中的“mgcv”包和“dlnm”程序包進(jìn)行半?yún)?shù)廣義相加模型(GAM)及分布滯后非線性模型(DLNM)建模定量分析.GAM模型可處理因變量和眾多解釋變量間過(guò)度復(fù)雜非線性的關(guān)系,可用以調(diào)整死亡的長(zhǎng)期和季節(jié)趨勢(shì)、氣象因素等潛在的混雜因素,近年來(lái)被廣泛引入定量評(píng)價(jià)大氣污染健康效應(yīng)的時(shí)間序列研究中.DLNM模型可以通過(guò)建立交叉基函數(shù)描述因變量在自變量維度與滯后維度的分布,同時(shí)還可以以暴露—滯后—反應(yīng)關(guān)系三維空間分布圖給出暴露因素的滯后效應(yīng)和非線性效應(yīng)[41].相對(duì)于西安市總?cè)藬?shù)來(lái)說(shuō),因變量心腦血管疾病日門(mén)診量相對(duì)較少,其分布近似于服從Possion分布,因此本研究將回歸模型(Possion)引入GAM中,擬合疾病死亡人數(shù)與各影響因素之間的暴露-響應(yīng)關(guān)系.

首先建立單污染物模型,選取心腦血管疾病實(shí)際死亡人數(shù)作為響應(yīng)變量,再利用非參數(shù)平滑樣條函數(shù)擬合非線性自變量,包括時(shí)間(time, time= 1...,731)、氣溫、相對(duì)濕度,用來(lái)控制氣象因素對(duì)污染物與疾病死亡人數(shù)的混雜影響.選擇赤池信息準(zhǔn)則(AIC)最小原則,確定非參數(shù)樣條平滑函數(shù)的自由度取值,選擇使得AIC見(jiàn)效的氣象要素引入模型,同時(shí)需引入周日亞元變量(DOW, DOW=1～7),假日指示變量.最終時(shí)間平滑函數(shù)的自由度采用11,溫度、相對(duì)濕度、風(fēng)速、氣壓的自由度分別為6,5,5,5.核心模型建立后,再將污染物日均濃度作為線性變量引入模型,同心腦血管疾病每日死亡人數(shù)建立泊松廣義相加模型.考慮到大氣顆粒物對(duì)心腦血管疾病每日死亡人數(shù)有滯后和累積效應(yīng),將污染物當(dāng)日(Lag0)、1～6d(Lag1～ Lag6)和01～07d(Lag01～Lag07)前濃度引入模型,同樣采用AIC準(zhǔn)則對(duì)模型進(jìn)行檢驗(yàn).在確定最佳滯后天數(shù)后,選擇最優(yōu)模型進(jìn)行暴露反應(yīng)分析,并按照性別進(jìn)行分層建模.具體模型如下:

log[(Y)](time,)+(Z,)+basis.Z+×X+

as.factor(DOW)+as.factor(Holiday)+(1)

式中:Y是指第日的西安市心腦血管疾病實(shí)際死亡人數(shù);E(Y)是指第日的疾病死亡人數(shù)的期望值;為非參數(shù)樣條平滑函數(shù),排除長(zhǎng)期趨勢(shì)、季節(jié)性、日歷效應(yīng)、氣象等混雜因素;time為日歷時(shí)間;為自由度;Z為第日的氣象要素;Z表示由DLNM模型構(gòu)建的“交叉基”;為回歸系數(shù),即暴露—反應(yīng)關(guān)系系數(shù);X為第日的污染物濃度;DOW是指處理“星期幾效應(yīng)”的虛擬函數(shù);Holiday是指控制假日的變量;為截距[42].

多污染物模型的建立:在確定最優(yōu)單污染物模型后,在該基礎(chǔ)上引入多種污染物,建立多污染物模型,并把兩者對(duì)比分析,目的是檢驗(yàn)單污染物模型敏感性的同時(shí),分析多種污染物協(xié)同作用下大氣污染物對(duì)居民健康造成的影響,由此確定出研究期間影響心腦血管疾病每日死亡人數(shù)的主要危險(xiǎn)因子.

1.2.2 平均氣溫與污染物協(xié)同作用的研究方法 因平均氣溫與污染物的共同作用引發(fā)相關(guān)疾病,所以選擇非參數(shù)二元響應(yīng)模型[43]擬合兩者共同作用對(duì)相關(guān)疾病人數(shù)影響三維空間圖,通過(guò)描述平均氣溫與污染物對(duì)疾病作用的空間分布特征,直觀展示兩者共同作用對(duì)疾病的影響.模型如下:

log[E(Y/X)](temperature,PM)COVs (2)

式中:(temperature,PM)為平均氣溫與污染物PM對(duì)心腦血管疾病的協(xié)同作用項(xiàng);PM表示BC或PM2.5中的一種,COVs代表所有混雜因素.

1.2.3 危險(xiǎn)度評(píng)估 根據(jù)GAM模型估算得到的暴露—反應(yīng)關(guān)系系數(shù),去定量評(píng)價(jià)污染物的健康效應(yīng).當(dāng)污染物濃度每變化單位Δc濃度時(shí),每日死亡人數(shù)相對(duì)危險(xiǎn)度(RR):

RR=exp(Δ×) (3)

根據(jù)RR計(jì)算當(dāng)污染物增加Δ時(shí),對(duì)疾病日死亡人數(shù)造成的超額死亡風(fēng)險(xiǎn)(ER)及其95%置信區(qū)間(CI):

ER%=(RR-1)×100% (4)

ER%(95%CI)=[exp(Δ×(±1.95SE)-1)×100% (5)

式中:為模型中污染物的回歸系數(shù);SE為污染物的標(biāo)準(zhǔn)誤差;Δ為濃度的變化范圍.

2 結(jié)果分析

2.1 統(tǒng)計(jì)分析

表1為西安市區(qū)2014～2015年主要?dú)庀笠蜃印?種大氣污染物日均濃度和心腦血管疾病每日死亡人數(shù)的描述性統(tǒng)計(jì)結(jié)果,由表1可以看出,心腦血管疾病平均每天死亡人數(shù)為62.39例,25、50、75分別為50,61,72例/d,男性和女性分別為33.56和28.83例/d.西安市年均溫度為15.27℃,日均溫度幅度為-3～33.8℃,年平均相對(duì)濕度為61.48%,日均相對(duì)濕度幅度為19%～97%.BC和PM2.5年平均濃度分別為6.98和66.97μg/m3,PM2.5年均濃度已經(jīng)明顯超過(guò)國(guó)家GB0395-2012標(biāo)準(zhǔn)[40]中規(guī)定的二級(jí)空氣質(zhì)量標(biāo)準(zhǔn)(35μg/m3),研究時(shí)段內(nèi)(730d)PM2.5超標(biāo)天數(shù)為564d(77%),PM2.5為西安市的主要污染物.目前國(guó)家空氣質(zhì)量監(jiān)測(cè)標(biāo)準(zhǔn)無(wú)BC污染物,但我國(guó)BC年均濃度相比北美、南美和中東等地區(qū)偏高[44-45].

2.2 大氣污染物與氣象要素之間Spearman相關(guān)分析

Spearman相關(guān)性分析結(jié)果見(jiàn)表2,BC和PM2.5均存在顯著的正相關(guān),且具有統(tǒng)計(jì)學(xué)意義.氣溫、風(fēng)速與污染物之間存在明顯負(fù)相關(guān)關(guān)系,相對(duì)濕度與污染物呈現(xiàn)負(fù)相關(guān)關(guān)系,氣壓與污染物呈明顯正相關(guān)關(guān)系.大氣污染物與氣象要素間較強(qiáng)的關(guān)聯(lián),表明二者之間存在固有的理化特征,且對(duì)人體健康的影響并不是單因素的,提示氣象要素是研究大氣污染物對(duì)人群健康影響的重要混雜因素或效應(yīng)修飾因素.

2.3 大氣污染物對(duì)心腦血管疾病超額死亡風(fēng)險(xiǎn)的影響

2.3.1 單污染物模型 控制氣象因素、季節(jié)性和長(zhǎng)期趨勢(shì)、星期幾效應(yīng)等混雜因素后,利用單污染物模型分別探討不同滯后時(shí)間條件下BC和PM2.5對(duì)心腦血管疾病日死亡人數(shù)的超額危險(xiǎn)度(ER)(圖1).可以看出BC、PM2.5對(duì)心腦血管疾病的影響均存在滯后效應(yīng)和累積效應(yīng),隨著滯后天數(shù)的增加,兩種污染物對(duì)疾病的影響減弱,這種滯后效應(yīng)在其他研究中也有表現(xiàn)[46-50].

表1 心腦血管疾病每日死亡人數(shù)、氣象要素及污染物的描述性分析

表2 心腦血管疾病每日死亡人數(shù)與氣象要素和大氣污染物的相關(guān)關(guān)系

注:**<0.01,*<0.05.

如圖1所示,BC和PM2.5在心腦血管疾病模擬部分的Lag0-Lag3,Lag01-Lag04具有統(tǒng)計(jì)學(xué)意義(<0.01),各自的滯后結(jié)構(gòu)表現(xiàn)出較強(qiáng)的一致性.BC在累積滯后3d(Lag03),PM2.5在滯后2d(Lag2)與心腦血管疾病每日死亡人數(shù)關(guān)聯(lián)的ER最大.最佳滯后時(shí)間下,BC、PM2.5每增加一個(gè)IQR單位濃度(BC為5.31μg/m3,PM2.5為40.30μg/m3)對(duì)應(yīng)的心腦血管疾病日死亡人數(shù)ER值為3.53% (95%CI:1.86,5.23)、2.01% (1.06,2.97),其ER值均通過(guò)=0.001顯著性檢驗(yàn),均具有統(tǒng)計(jì)學(xué)意義.最佳滯后時(shí)間下,BC、PM2.5每增加一個(gè)1μg/m3對(duì)應(yīng)的心腦血管疾病日死亡人數(shù)ER為0.66% (95%CI:0.35,0.97)、0.05% (95%CI:0.02,0.08),其ER值均通過(guò)=0.001顯著性檢驗(yàn),均具有統(tǒng)計(jì)學(xué)意義.

考慮到男女性別的差異,以性別建立模型探討B(tài)C、PM2.5濃度變化對(duì)不同人群下的健康影響.表3是污染物濃度升高對(duì)不同性別人群心腦血管疾病日死亡人數(shù)變化的影響,在最佳滯后時(shí)間下,BC、PM2.5每升高一個(gè)IQR,男性群體的心腦血管疾病的超額死亡率為2.83% (95%CI:0.76,4.95), 1.36% (95%CI:0.07,2.67),女性群體的心腦血管疾病的超額死亡率為4.30% (95%CI:1.84,6.82),2.74% (95%CI: 1.34,4.15),說(shuō)明女性群體對(duì)BC、PM2.5暴露更為敏感.

圖1 不同時(shí)間滯后條件下BC、PM2.5濃度變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

表3 性別分層下BC、PM2.5濃度變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

注:***<0.001,**<0.01,*<0.05.

2.3.2 多污染物模型 低溫與高濃度BC、PM2.5的協(xié)同作用對(duì)心腦血管疾病死亡均有顯著影響.在多污染物模型中,同時(shí)引入PM2.5、SO2、NO2、BC中的2種、3種或4種污染物,多種污染物共同作用對(duì)西安市心腦血管疾病每日死亡人數(shù)的影響見(jiàn)表4.對(duì)于BC來(lái)說(shuō),分別加入SO2、NO2或同時(shí)加入這兩種污染物后,ER值與BC單污染物模型擬合值相比略有上升,表明SO2、NO2可能存在協(xié)同作用,雙污染物模型得出BC的健康影響強(qiáng)于BC的單污染物模型,Janssen等[51]在探究BC氣溶膠在空氣質(zhì)量管理評(píng)估中的作用時(shí)也持同樣觀點(diǎn);而對(duì)于PM2.5來(lái)說(shuō),分別加入SO2、NO2或同時(shí)加入兩種污染物后對(duì)其ER值影響不大.總體而言,對(duì)于心腦血管疾病,當(dāng)BC、PM2.5同時(shí)納入其它一種或幾種污染物時(shí),對(duì)ER值無(wú)較大影響.

表4 多污染物模型下BC、PM2.5濃度變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

注:***<0.001.

表5 不同時(shí)間自由度下BC、PM2.5濃度變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

注:***<0.001.

2.3.3 敏感性分析 選取單污染物模型結(jié)果確定的BC、PM2.5最佳滯后天數(shù)對(duì)應(yīng)的濃度,采用變更時(shí)間自由度的方式,對(duì)BC、PM2.5和心腦血管疾病死亡的關(guān)系進(jìn)行分析,結(jié)果見(jiàn)表5,改變自由度后(df=10、11、12、13),其ER值及對(duì)應(yīng)的95%CI可信度變化不大,說(shuō)明模型較穩(wěn)定.

2.4 氣溫變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

各氣象要素中,氣溫對(duì)心腦血管疾病影響最大,相關(guān)系數(shù)為-0.66,呈負(fù)相關(guān),說(shuō)明心腦血管疾病每日死亡人數(shù)隨著溫度的降低而升高.為研究溫度范圍對(duì)心腦血管疾病每日死亡人數(shù)的影響,利用模型(1)擬合氣溫與心腦血管疾病每日死亡人數(shù)的暴露反應(yīng)關(guān)系,平均氣溫與疾病每日死亡人數(shù)呈近似“V”型分布特征(圖2),即氣溫效應(yīng)大致分為3個(gè)部分:當(dāng)氣溫由低到高增加時(shí),死亡風(fēng)險(xiǎn)逐漸減小,超過(guò)一定閾值后再次增加,且增幅較大,在氣溫較適宜階段25～27℃對(duì)心腦血管疾病死亡影響非常小,該階段為死亡風(fēng)險(xiǎn)最小的最適溫度范圍(氣溫閾值范圍).各氣溫段均具有一定的滯后作用,且滯后性的變化趨勢(shì)各有不同,最大危險(xiǎn)度對(duì)應(yīng)的滯后日也有一定區(qū)別.

圖2 日均氣溫與心腦血管疾病每日死亡人數(shù)的暴露反應(yīng)關(guān)系

圖3(a～c)是平均氣溫對(duì)不同性別心血腦疾病死亡的滯后效應(yīng)等值線圖,結(jié)合典型滯后日的剖面圖(圖3(d～g))可以看到,在滯后當(dāng)天(Lag0)時(shí)高溫和低溫兩側(cè)死亡風(fēng)險(xiǎn)較高(RR>1),表現(xiàn)為低溫效應(yīng)、高溫效應(yīng)同時(shí)存在的即時(shí)效應(yīng).不同水平氣溫的滯后效應(yīng)變化差異較大,平均氣溫對(duì)心腦血管疾病死亡的影響表現(xiàn)為低溫滯后效應(yīng)為主,25～27℃范圍內(nèi)的整體效應(yīng)較弱.Lag=1時(shí),高溫效應(yīng)維持,低溫效應(yīng)逐漸消失.Lag=4時(shí),高溫效應(yīng)逐漸消失,低溫效應(yīng)開(kāi)始凸顯,且隨著滯后時(shí)間的增加,對(duì)心腦血管疾病死亡有顯著影響的低溫效應(yīng)持續(xù)增高,約在Lag=5時(shí)達(dá)到最強(qiáng)后低溫效應(yīng)逐漸消失,低溫效應(yīng)在14d后再次增加,考慮到較長(zhǎng)滯后期內(nèi)會(huì)出現(xiàn)天氣疊加效應(yīng)、人為因素等其他影響因素,加之模型可能出現(xiàn)的過(guò)擬合現(xiàn)象,不作為主要結(jié)果.另外可以看出,死亡當(dāng)天女性對(duì)低溫的敏感性高于男性,而對(duì)高溫的敏感性低于男性,滯后效應(yīng)對(duì)兩類人群的影響與總心腦血管疾病的變化相似.

建立非參數(shù)二元響應(yīng)模型,用以擬合平均氣溫與不同污染物(BC、PM2.5)協(xié)同作用對(duì)心腦血管疾病有顯著協(xié)同作用的三維立體圖(圖4).BC與低溫對(duì)心腦血管疾病死亡可能存在交互影響,低溫、高濃度BC條件下,形成了心腦血管疾病每日死亡人數(shù)的峰值,其原因應(yīng)該是冬半年氣溫低且污染物濃度高,二者的協(xié)同效應(yīng)對(duì)心腦血管疾病死亡的影響增強(qiáng),PM2.5對(duì)心腦血管疾病的協(xié)同作用與BC基本一致.

為定量分析污染物與氣溫共同作用對(duì)疾病每日死亡人數(shù)的影響,采用溫度分層模型研究氣溫與BC(PM2.5)交互作用對(duì)心腦血管疾病每日死亡人數(shù)的影響.本研究選取26℃(圖2)為溫度臨界值,通過(guò)溫度閾值將氣溫分為相對(duì)高溫段(>26℃)、相對(duì)低溫段(<26℃)兩部分來(lái)分析不同溫度閾值條件下兩種污染物濃度變化對(duì)心腦血管疾病死亡的影響效應(yīng).不同溫度水平下BC、PM2.5的最佳滯后時(shí)間與溫度未分層模型結(jié)果一致,分別為L(zhǎng)ag03、Lag2.表6結(jié)果表明,對(duì)于BC、PM2.5而言,低溫效應(yīng)具有統(tǒng)計(jì)學(xué)意義,高溫?zé)o統(tǒng)計(jì)學(xué)意義,表明低溫可加劇污染物對(duì)人群健康的不利影響.總體來(lái)看,低溫條件下BC對(duì)人群的健康危害大于PM2.5.

圖4 日均氣溫與BC和PM2.5交互作用對(duì)心腦血管疾病每日死亡人數(shù)影響的平滑曲面

表6 不同溫度水平下BC和PM2.5濃度變化對(duì)心腦血管疾病每日死亡人數(shù)的影響

注:***<0.001.

3 討論

3.1 氣溫、污染物單效應(yīng)討論

本文對(duì)西安市BC和PM2.5與心腦血管疾病死亡的關(guān)聯(lián)進(jìn)行研究,發(fā)現(xiàn)BC、PM2.5對(duì)心腦血管疾病人群存在顯著的健康效應(yīng),當(dāng)兩種污染物增加相同質(zhì)量單位濃度時(shí),BC的超額死亡風(fēng)險(xiǎn)遠(yuǎn)大于PM2.5,這與世界衛(wèi)生組織的Meta分析結(jié)果較為一致[52].但是,一般情況下大氣中的 BC濃度比PM2.5濃度大約小1個(gè)量級(jí),所以應(yīng)選擇更接近實(shí)際情況的IQR計(jì)量為變化單位,計(jì)算超額死亡風(fēng)險(xiǎn).目前有限的科學(xué)證據(jù)表明,兩種顆粒物每增加一個(gè)IQR得到的健康效應(yīng)相似[53],這種結(jié)果尤其在心腦血管疾病研究方面較為明顯,Zanobetti等[54]在波士頓研究發(fā)現(xiàn)BC、PM2.5每增加一個(gè)IQR單位濃度,對(duì)應(yīng)的急性緊急梗塞發(fā)病人數(shù)的ER值為8.6%、8.3%,Wang等[55]在上海開(kāi)展的顆粒物健康效應(yīng)研究發(fā)現(xiàn),BC、PM2.5每增加一個(gè)IQR單位濃度,心腦血管疾病每日死亡人數(shù)的ER值為3.2%、3.3%.本文研究得出的西安市BC、PM2.5濃度每升高一個(gè)IQR,心腦血管疾病每日死亡人數(shù)分別增加3.53%、1.81%,但BC、PM2.5年均濃度分別為7.0,67.0μg/m3,BC僅占PM2.5濃度的一小部分,可見(jiàn)BC與心腦血管疾病每日死亡率的相關(guān)性比PM2.5更強(qiáng),表明BC是評(píng)估環(huán)境顆粒物健康風(fēng)險(xiǎn)的一個(gè)額外有價(jià)值的空氣質(zhì)量指標(biāo),這種現(xiàn)象可能是由于BC粒徑小,比表面積大,可以通過(guò)粘附更多的有毒物質(zhì)[56]表現(xiàn)出比PM2.5更強(qiáng)的毒性,引起內(nèi)皮細(xì)胞反應(yīng)增加,誘導(dǎo)疾病產(chǎn)生.

從性別分層來(lái)看,心腦血管疾病的女性人群健康風(fēng)險(xiǎn)均高于男性,并均具有統(tǒng)計(jì)學(xué)意義.這種性別差異引起的污染物健康效應(yīng)結(jié)果不同在出血性中風(fēng)、冠心病死亡和呼吸系統(tǒng)發(fā)病等研究中有所體現(xiàn)[11,57].所以女性對(duì)這些污染物是易感人群,會(huì)受到更多的污染物潛在危險(xiǎn)的影響.有研究表明男女群體對(duì)污染物的敏感程度不相同,這種差異可能與兩性的不同生理學(xué)結(jié)構(gòu)、暴露模式有關(guān),與肺功能、皮膚吸收等生理特征指標(biāo)相關(guān),兩性在職業(yè)、戶外活動(dòng)時(shí)間等方面也存在一定差異[58-59].

氣溫對(duì)人群健康的影響呈現(xiàn)非線性關(guān)系,國(guó)內(nèi)外學(xué)者們發(fā)現(xiàn)氣溫和人群死亡或發(fā)病的關(guān)系大多呈現(xiàn)“J”、“U”或“V”型,可以說(shuō)明氣溫對(duì)相關(guān)疾病死亡存在一個(gè)溫度閾值[60-61],該閾值下的疾病死亡風(fēng)險(xiǎn)最小,若超過(guò)該閾值,相關(guān)疾病死亡人數(shù)將會(huì)顯著增加.本研究中,相關(guān)心腦血管死亡人數(shù)與氣溫顯著相關(guān)性說(shuō)明氣溫是影響相關(guān)疾病最主要的氣象要素,從氣溫對(duì)西安市心腦血管疾病的影響和滯后性來(lái)看,日平均氣溫與心腦血管疾病每日死亡人數(shù)呈現(xiàn)近似“V”型分布的非線性關(guān)系,最適溫度為26℃,表現(xiàn)為高低溫即時(shí)效應(yīng)和低溫滯后效應(yīng),氣溫對(duì)心腦血管疾病的最大滯后時(shí)間為8d.

3.2 氣溫與污染物協(xié)同效應(yīng)討論

污染物對(duì)人群的健康影響往往存在于特定氣象條件下發(fā)生,并不是孤立存在的,已有證據(jù)指出氣象要素和大氣污染通過(guò)協(xié)同作用對(duì)人群的健康效應(yīng)產(chǎn)生不良影響[62-63],本文開(kāi)展了西安市2014～2015年氣溫、污染物(BC、PM2.5)及其二者交互作用對(duì)心腦血管疾病每日死亡人數(shù)的影響研究.結(jié)果發(fā)現(xiàn):在低溫、高濃度污染物條件下,心腦血管疾病的死亡風(fēng)險(xiǎn)最高,表明低溫與BC、PM2.5對(duì)人群健康效應(yīng)存在協(xié)同放大效應(yīng).值得注意的是,本研究中,低溫段BC對(duì)人群健康的影響比PM2.5更為顯著,這在以往的研究結(jié)果中尚未涉及.

3.3 局限性說(shuō)明

西安作為我國(guó)人口密度高、工業(yè)發(fā)達(dá)的典型城市,以細(xì)顆粒為主的大氣污染問(wèn)題嚴(yán)重,研究該市BC和PM2.5與氣溫交互作用對(duì)心腦血管疾病死亡的健康效應(yīng)影響具有典型代表性,可為其他城市提供參考.但存在一定的局限性,首先與發(fā)達(dá)國(guó)家相比,由于我國(guó)醫(yī)療數(shù)據(jù)獲取的難度較大,收集資料受限,沒(méi)有對(duì)年齡段和其他類別疾病進(jìn)行更為深入細(xì)致地研究,也無(wú)法排除個(gè)體的混雜因素如抽煙、體重等對(duì)于大氣污染健康效應(yīng)影響研究結(jié)果的干擾;其次,該資料采用的污染物暴露濃度為該市平均濃度和代表站濃度,對(duì)于個(gè)體暴露水平可能會(huì)造成一定偏差;另外,BC與PM2.5之間的高度相關(guān)性限制了分離單個(gè)污染物獨(dú)立效應(yīng)的能力,這可能導(dǎo)致模擬結(jié)果存在一定的偏差,目前該問(wèn)題尚未得到有效解決,需要進(jìn)一步深究.

4 結(jié)論

4.1 BC、PM2.5對(duì)西安市心腦血管疾病每日死亡人數(shù)的影響存在滯后效應(yīng),在最佳滯后時(shí)間下,BC、PM2.5每增加1個(gè)IQR(BC為5.31μg/m3,PM2.5為40.30μg/m3),對(duì)應(yīng)的超額死亡風(fēng)險(xiǎn)值(ER)分別為3.55% (95%CI:1.86,5.23),2.01% (95%CI:1.06,2.97).

4.2 在性別屬性分類下,相對(duì)于男性群體,女性群體對(duì)BC、PM2.5暴露更為敏感;在季節(jié)分類下,冬半年BC、PM2.5暴露對(duì)于人群健康影響作用高于夏半年.

4.3 多污染物模型研究表明,對(duì)心腦血管疾病而言,當(dāng)BC、PM2.5同時(shí)納入其他一種或幾種污染物時(shí),對(duì)ER值無(wú)明顯影響.

4.4 在各氣象要素中,氣溫對(duì)心腦血管疾病影響最敏感.日平均氣溫與心腦血管疾病每日死亡人數(shù)呈現(xiàn)近似“V”型分布的非線性關(guān)系,最適溫度范圍是為25～27℃,高溫對(duì)心腦血管系統(tǒng)疾病死亡以即時(shí)效應(yīng)為主,低溫主要表現(xiàn)為滯后效應(yīng).

4.5 低溫與高濃度BC、PM2.5對(duì)心腦血管疾病死亡的健康效應(yīng)均有協(xié)同放大效應(yīng),低溫段BC對(duì)人群健康的影響比PM2.5更為顯著.

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感謝中國(guó)疾病預(yù)防控制中心鄭燦軍老師對(duì)疾病數(shù)據(jù)和本文研究工作提供的幫助！

Influence of BC, PM2.5, temperature and their synergy on mortality of cardiovascular diseases in Xi'an.

OU Yi-han1,2, ZHANG Xiao-ling1,2,3*, ZHANG Ying1, KANG ping1

(1.School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China；2.Key Laboratory of Plateau Atmosphere and Environment of Sichuan Province, Chengdu 610225, China；3.Chengdu Plain Urban Meteorology and Environment Scientific Observation and Research Station of Sichuan Province, Chengdu 610225, China)., 2021,41(9)：4415～4425

Daily death data of cardiovascular diseases during 2014～2015, daily average of BC(black carbon) and PM2.5and meteorological data during the same period in Xi’an were collected. Three semi-parametric Generalized Additive Models (GAMs) based on the time series, including an independent model, a non-parametric bivariate response surface model, and a temperature stratification model, were adopted to this study. The results showed that BC and PM2.5had a lag effect on the daily mortality of cardiovascular diseases in Xi 'an. With the optimal lag period, when concentrations of BC and PM2.5increased by interquartile range (IQR), the excess risk of cardiovascular diseases increased by 3.53%(95%CI: 1.86, 5.23) and 2.01% (95%CI: 1.06, 2.97), respectively. The exposure-response relationship between ambient temperature and mortality of cardiovascular diseases both exhibited "V" type and the most comfortable temperature was 26℃. Low temperature and high pollutant concentration had a synergistic strengthening effect on cardiovascular diseases. When the temperature lower 26℃, the modulating effects of temperature on BC-mortality relationship became more pronounced than that on PM2.5-mortality relationships with temperature cutoff increasing. For cardiovascular diseases, different susceptibility showed in different subgroups, and female groups was more sensitive to the health risks of BC and PM2.5. When BC and PM2.5were included in one or more other gaseous pollutants at the same time, the excess risk had no major impact. The adverse effect of BC on human health should not be neglected in the future. BC may be used as an important air quality indicator to assess the health risks of air pollutants.

black carbon；PM2.5；temperature；synergistic effect；cardiovascular diseases；risk of excessive death

X503.1

A

1000-6923(2021)09-4415-11

歐奕含(1996-),女,四川成都人,成都信息工程大學(xué)碩士研究生,主要從事大氣環(huán)境與健康研究.

2021-01-28

國(guó)家重點(diǎn)研發(fā)計(jì)劃課題(2016YFA0602004);國(guó)家自然科學(xué)基金資助項(xiàng)目(42005136);國(guó)家重點(diǎn)研發(fā)計(jì)劃課題(2018YFC0214002);成都市科技局技術(shù)創(chuàng)新研發(fā)項(xiàng)目(2018-YF05-00219-SN)

* 責(zé)任作者, 教授, xlzhang@ium.cn