Article(id=1241319149817885035, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202503077, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741017600000, receivedDateStr=2025-03-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773883147911, onlineDateStr=2026-03-19, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773883147911, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773883147911, creator=13701087609, updateTime=1773883147911, updator=13701087609, issue=Issue{id=1241319148798669160, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='12', pageStart='2113', pageEnd='2304', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773883147667, creator=13701087609, updateTime=1773885555254, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241329247004971040, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241329247004971041, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2166, endPage=2171, ext={EN=ArticleExt(id=1241319150145040751, articleId=1241319149817885035, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between polycyclic aromatic hydrocarbon exposure and atherogenic index of plasma, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

This study aims to investigate the association between polycyclic aromatic hydrocarbons (PAHs) exposure and the atherogenic index of plasma (AIP) by analyzing data from the National Health and Nutrition Examination Survey (NHANES).

Methods

Participants aged ≥20 years were selected from NHANES 2009-2016. Due to the left-skewed distribution of urinary PAHs metabolites (OH-PAHs), logarithmic transformation (lg) was applied to approximate a normal distribution. Participants were categorized into four quartiles based on lgOH-PAHs levels. A multiple linear regression model was used to evaluate the association between PAHs and AIP. A smoothing curve fitting approach was employed to explore potential nonlinear relationships, and subgroup analyses were conducted.

Results

A total of 3 084 participants were included, including 1 560 females (50.6%) with an average age of (49.1±17.6) years.After adjusting for age, sex, race, education level, marital status, the ratio of family income to poverty, body mass index (BMI), smoking, alcohol consumption, hypertension, and high cholesterol, multiple linear regression analysis indicated a positive association between the highest quartile of PAHs exposure (Q4) (β=0.056, 95% CI: 0.021-0.091) and AIP compared to the lowest quartile (Q1). In sex-stratified subgroup analyses, higher PAHs exposure (Q4) (β=0.068, 95% CI: 0.010-0.126) was positively associated with AIP in the male population. A similar positive correlation was also found in the female population (β=0.047, 95% CI: 0.001-0.094). In BMI-stratified analyses, the association between PAHs exposure and AIP was significant in participants with BMI <25(β=0.096, 95% CI: 0.032-0.160). Smoothing curve fitting demonstrated an inverted U-shaped relationship between PAHs concentration and AIP.

Conclusion

This study found a strong association between PAHs exposure and AIP, suggesting that PAHs exposure may be an important risk factor for increased AIP.

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目的

通过分析美国国家健康和营养调查数据(National Health and Nutrition Examination Survey, NHANES)探讨多环芳烃(PAHs)暴露与血浆致动脉粥样硬化指数(AIP)的关联性。

方法

本研究选自NHANES 2009—2016年中≥20岁人群,由于尿液多环芳烃代谢物(OH-PAHs)的分布呈偏态(左偏),本研究应用对数变换(lg)使数据接近正态分布,根据lgOH-PAHs的四分位数水平将参与者分为四组。采用多元线性回归模型评估PAHs暴露与AIP的关联,使用平滑曲线拟合进一步探究PAHs暴露与AIP的非线性关系,并进行亚组分析。

结果

共纳入3 084例参与者,其中女性1560例(50.6%),平均年龄(49.1±17.6)岁。在校正年龄、性别、种族、教育水平、婚姻状况、家庭收入与贫困的比率、体重指数(BMI)、吸烟、饮酒、高血压、高胆固醇后,多元线性回归模型发现,与最低四分位数组(Q1)相比,最高四分位数组(Q4)(β=0.056,95% CI:0.021~0.091)与AIP呈正相关;在性别分层的亚组分析中,男性人群PAHs高暴露组(Q4)(β=0.068,95% CI:0.010~0.126)与AIP呈正相关,女性(β=0.047,95% CI:0.001~0.094)同上;在按BMI分层的亚组中,BMI<25的人群(β=0.096,95% CI:0.032~0.160)里,PAHs的水平与AIP的正相关显著。平滑曲线拟合结果显示,PAHs浓度与AIP呈倒U型关系。

结论

本研究发现PAHs暴露与AIP密切相关,提示PAHs暴露是AIP升高的重要危险因素。

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熊静远,E-mail:
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袁鑫(2003—),男,本科在读,研究方向:劳动卫生与环境卫生

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Cardiovascular Diabetology, 2024, 23(1): 255., articleTitle=Association of atherogenic index of plasma with cardiovascular disease mortality and all-cause mortality in the general US adult population:results from NHANES 2005-2018, refAbstract=null)], funds=[Fund(id=1241319159569642201, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, awardId=2025ZNSFSC0641, language=CN, fundingSource=四川省自然科学基金面上项目(2025ZNSFSC0641), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241319154112852411, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, xref=null, ext=[AuthorCompanyExt(id=1241319154121241020, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, companyId=1241319154112852411, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1241319154125435325, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, companyId=1241319154112852411, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=四川大学华西公共卫生学院/华西第四医院,四川 成都 610041)])], figs=[ArticleFig(id=1241319158198104693, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=EN, label=Fig.1, caption=Flow chart ofthe study population screening, figureFileSmall=OkqarXU2P3fxNXIlFVuR9g==, figureFileBig=ap/OQo3zYgIqiAX17uMPEA==, tableContent=null), ArticleFig(id=1241319158298768000, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=CN, label=图1, caption=研究人群筛选流程图, figureFileSmall=OkqarXU2P3fxNXIlFVuR9g==, figureFileBig=ap/OQo3zYgIqiAX17uMPEA==, tableContent=null), ArticleFig(id=1241319158537843346, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=EN, label=Fig.2, caption=Correlation between lgOH-PAHs and AIP, figureFileSmall=FYvDT3sdCY/zprlgGKQtOg==, figureFileBig=evjxi4anSYm+RXzDZdwz9A==, tableContent=null), ArticleFig(id=1241319158659478170, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=CN, label=图2, caption=lgOH-PAHs与AIP的相关性

注:A为lgOH-PAHs与AIP之间的散点分布图,黑色实线为基于广义加性模型拟合的平滑曲线,表明两者之间存在非线性关联;B为使用广义加性模型拟合的lgOH-PAHs与AIP之间的剂量-反应关系曲线,实线表示模型估计的AIP变化趋势,虚线为95%置信区间,底部的短竖线表示样本数据的分布密度。

, figureFileSmall=FYvDT3sdCY/zprlgGKQtOg==, figureFileBig=evjxi4anSYm+RXzDZdwz9A==, tableContent=null), ArticleFig(id=1241319158760141474, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=EN, label=Table 1, caption=

General characteristics of the study subject

, figureFileSmall=null, figureFileBig=null, tableContent=
项目lgOH-PAHs(ng/g 肌酐)χ2/FP
Q1
n=771)
Q2
n=771)
Q3
n=771)
Q4
n=771)
年龄(岁,50.45±18.3349.52±17.8647.83±17.4148.60±16.673.2000.022
性别[n(%)]56.028<0.001
男性469 (60.8)359 (46.6)334 (43.3)362 (47.0)
女性302 (39.2)412 (53.4)437 (56.7)409 (53.0)
种族[n(%)]87.114<0.001
墨西哥裔美国人92 (11.9)106 (13.7)160 (20.8)92 (11.9)
其他西班牙裔57 (7.4)115 (14.9)115 (14.9)80 (10.4)
非西班牙裔白人374 (48.5)310 (40.2)258 (33.5)353 (45.8)
非西班牙裔黑人134 (17.4)141 (18.3)138 (17.9)163 (21.1)
其他种族-包括多种族114 (14.8)99 (12.8)100 (13.0)83 (10.8)
教育水平[n(%)]102.760<0.001
高中以下132 (17.1)150 (19.5)217 (28.1)253 (32.8)
高中毕业或同等学历151 (19.6)159 (20.6)170 (22.0)200 (25.9)
大专及以上488 (63.3)462 (59.9)384 (49.8)318 (41.2)
婚姻状况[n(%)]15.1370.019
已婚/与伴侣同居471 (61.1)451 (58.5)483 (62.6)424 (55.0)
丧偶/离婚/分居153 (19.8)165 (21.4)145 (18.8)199 (25.8)
从未结婚147 (19.1)155 (20.1)143 (18.5)148 (19.2)
家庭收入与贫困的比率(2.74±1.662.63±1.672.34±1.591.95±1.4438.060<0.001
BMI[kg/m2n(%)]19.9780.003
<25265 (34.4)244 (31.6)222 (28.8)279 (36.2)
25~29.9282 (36.6)258 (33.5)258 (33.5)241 (31.3)
≥30224 (29.1)269 (34.9)291 (37.7)251 (32.6)
吸烟[n(%)]317.691<0.001
250 (32.4)260 (33.7)298 (38.7)550 (71.3)
521 (67.6)511 (66.3)473 (61.3)221 (28.7)
饮酒[n(%)]20.303<0.001
565 (73.3)568 (73.7)522 (67.7)600 (77.8)
206 (26.7)203 (26.3)249 (32.3)171 (22.2)
高血压[n(%)]2.7650.429
279 (36.2)272 (35.3)277 (35.9)301 (39.0)
492 (63.8)499 (64.7)494 (64.1)470 (61.0)
高胆固醇[n(%)]2.2890.515
272 (35.3)287 (37.2)259 (33.6)269 (34.9)
499 (64.7)484 (62.8)512 (66.4)502 (65.1)
总胆固醇(mg/dl,191.63±40.85190.94±41.51191.23±38.42190.54±40.720.1000.960
低密度脂蛋白(mg/dl,114.76±34.99113.08±36.32113.35±33.53112.87±36.240.4520.716
高密度脂蛋白(mg/dl,54.47±15.3455.48±15.4855.04±15.8353.19±17.442.9480.032
甘油三酯(mg/dl,112.01±63.23111.95±62.85114.24±64.55122.46±68.154.5630.003
血浆致动脉粥样硬化指数0.27±0.300.26±0.300.27±0.310.32±0.325.8360.001
), ArticleFig(id=1241319158898553520, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=CN, label=表1, caption=

研究对象的一般特征

, figureFileSmall=null, figureFileBig=null, tableContent=
项目lgOH-PAHs(ng/g 肌酐)χ2/FP
Q1
n=771)
Q2
n=771)
Q3
n=771)
Q4
n=771)
年龄(岁,50.45±18.3349.52±17.8647.83±17.4148.60±16.673.2000.022
性别[n(%)]56.028<0.001
男性469 (60.8)359 (46.6)334 (43.3)362 (47.0)
女性302 (39.2)412 (53.4)437 (56.7)409 (53.0)
种族[n(%)]87.114<0.001
墨西哥裔美国人92 (11.9)106 (13.7)160 (20.8)92 (11.9)
其他西班牙裔57 (7.4)115 (14.9)115 (14.9)80 (10.4)
非西班牙裔白人374 (48.5)310 (40.2)258 (33.5)353 (45.8)
非西班牙裔黑人134 (17.4)141 (18.3)138 (17.9)163 (21.1)
其他种族-包括多种族114 (14.8)99 (12.8)100 (13.0)83 (10.8)
教育水平[n(%)]102.760<0.001
高中以下132 (17.1)150 (19.5)217 (28.1)253 (32.8)
高中毕业或同等学历151 (19.6)159 (20.6)170 (22.0)200 (25.9)
大专及以上488 (63.3)462 (59.9)384 (49.8)318 (41.2)
婚姻状况[n(%)]15.1370.019
已婚/与伴侣同居471 (61.1)451 (58.5)483 (62.6)424 (55.0)
丧偶/离婚/分居153 (19.8)165 (21.4)145 (18.8)199 (25.8)
从未结婚147 (19.1)155 (20.1)143 (18.5)148 (19.2)
家庭收入与贫困的比率(2.74±1.662.63±1.672.34±1.591.95±1.4438.060<0.001
BMI[kg/m2n(%)]19.9780.003
<25265 (34.4)244 (31.6)222 (28.8)279 (36.2)
25~29.9282 (36.6)258 (33.5)258 (33.5)241 (31.3)
≥30224 (29.1)269 (34.9)291 (37.7)251 (32.6)
吸烟[n(%)]317.691<0.001
250 (32.4)260 (33.7)298 (38.7)550 (71.3)
521 (67.6)511 (66.3)473 (61.3)221 (28.7)
饮酒[n(%)]20.303<0.001
565 (73.3)568 (73.7)522 (67.7)600 (77.8)
206 (26.7)203 (26.3)249 (32.3)171 (22.2)
高血压[n(%)]2.7650.429
279 (36.2)272 (35.3)277 (35.9)301 (39.0)
492 (63.8)499 (64.7)494 (64.1)470 (61.0)
高胆固醇[n(%)]2.2890.515
272 (35.3)287 (37.2)259 (33.6)269 (34.9)
499 (64.7)484 (62.8)512 (66.4)502 (65.1)
总胆固醇(mg/dl,191.63±40.85190.94±41.51191.23±38.42190.54±40.720.1000.960
低密度脂蛋白(mg/dl,114.76±34.99113.08±36.32113.35±33.53112.87±36.240.4520.716
高密度脂蛋白(mg/dl,54.47±15.3455.48±15.4855.04±15.8353.19±17.442.9480.032
甘油三酯(mg/dl,112.01±63.23111.95±62.85114.24±64.55122.46±68.154.5630.003
血浆致动脉粥样硬化指数0.27±0.300.26±0.300.27±0.310.32±0.325.8360.001
), ArticleFig(id=1241319159020188343, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=EN, label=Table 2, caption=

Weighted multivariate linear regression model for the association of PAHs and AIP

, figureFileSmall=null, figureFileBig=null, tableContent=
因素Model1Model2Model3
β值(95% CIPβ值(95% CIPβ值(95% CIP
PAHs
Q1RefRefRef
Q2-0.006(-0.049~0.037)0.7850.012(-0.030~0.054)0.7090.002(-0.035~0.039)0.899
Q30.005(-0.034~0.043)0.8090.022(-0.018~0.062)0.3470.003(-0.031~0.037)0.846
Q40.067(0.031~0.104)<0.0010.067(0.031~0.104)<0.0010.056(0.021~0.091)0.003
P趋势<0.001<0.0010.006
), ArticleFig(id=1241319159125045951, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=CN, label=表2, caption=

多环芳烃与血浆致动脉粥样硬化指数关联的加权多元线性回归模型

, figureFileSmall=null, figureFileBig=null, tableContent=
因素Model1Model2Model3
β值(95% CIPβ值(95% CIPβ值(95% CIP
PAHs
Q1RefRefRef
Q2-0.006(-0.049~0.037)0.7850.012(-0.030~0.054)0.7090.002(-0.035~0.039)0.899
Q30.005(-0.034~0.043)0.8090.022(-0.018~0.062)0.3470.003(-0.031~0.037)0.846
Q40.067(0.031~0.104)<0.0010.067(0.031~0.104)<0.0010.056(0.021~0.091)0.003
P趋势<0.001<0.0010.006
), ArticleFig(id=1241319159204737733, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=EN, label=Table 3, caption=

Subgroup analysis of the association between PAHs and AIP

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因素Q1Q2Q3
β值(95% CIPβ值(95% CIP
性别
Ref-0.018(-0.071~0.034)0.480-0.009(-0.063~0.044)0.733
Ref0.016(-0.030~0.061)0.4870.010(-0.034~0.055)0.638
年龄(岁)
<60Ref-0.015(-0.061~0.031)0.519-0.005(-0.042~0.032)0.774
≥60Ref0.020(-0.044~0.084)0.534-0.004(-0.056~0.049)0.889
BMI(kg/m2
<25Ref0.008(-0.061~0.077)0.8100.002(-0.048~0.052)0.929
25~29.9Ref0.014(-0.039~0.067)0.592-0.013(-0.079~0.054)0.699
≥30Ref-0.016(-0.080~0.048)0.6220.013(-0.048~0.074)0.662
因素Q4P趋势P交互
β值(95% CIP
性别0.902
0.068(0.010~0.126)0.0220.010
0.047(0.001~0.094)0.047<0.001
年龄(岁)0.566
<600.043(-0.003~0.089)0.0650.002
≥600.055(-0.008~0.119)0.0860.235
BMI(kg/m20.412
<250.096(0.032~0.160)0.004<0.001
25~29.90.015(-0.045~0.075)0.6210.732
≥300.048(-0.023~0.119)0.1780.123
), ArticleFig(id=1241319159397675726, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319149817885035, language=CN, label=表3, caption=

多环芳烃与血浆致动脉粥样硬化指数关联的亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
因素Q1Q2Q3
β值(95% CIPβ值(95% CIP
性别
Ref-0.018(-0.071~0.034)0.480-0.009(-0.063~0.044)0.733
Ref0.016(-0.030~0.061)0.4870.010(-0.034~0.055)0.638
年龄(岁)
<60Ref-0.015(-0.061~0.031)0.519-0.005(-0.042~0.032)0.774
≥60Ref0.020(-0.044~0.084)0.534-0.004(-0.056~0.049)0.889
BMI(kg/m2
<25Ref0.008(-0.061~0.077)0.8100.002(-0.048~0.052)0.929
25~29.9Ref0.014(-0.039~0.067)0.592-0.013(-0.079~0.054)0.699
≥30Ref-0.016(-0.080~0.048)0.6220.013(-0.048~0.074)0.662
因素Q4P趋势P交互
β值(95% CIP
性别0.902
0.068(0.010~0.126)0.0220.010
0.047(0.001~0.094)0.047<0.001
年龄(岁)0.566
<600.043(-0.003~0.089)0.0650.002
≥600.055(-0.008~0.119)0.0860.235
BMI(kg/m20.412
<250.096(0.032~0.160)0.004<0.001
25~29.90.015(-0.045~0.075)0.6210.732
≥300.048(-0.023~0.119)0.1780.123
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多环芳烃暴露与血浆致动脉粥样硬化指数的关联性研究
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袁鑫 , 何莹粲 , 金明浩 , 王一淇 , 熊静远
现代预防医学 | 环境与职业卫生 2025,52(12): 2166-2171
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现代预防医学 | 环境与职业卫生 2025, 52(12): 2166-2171
多环芳烃暴露与血浆致动脉粥样硬化指数的关联性研究
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袁鑫, 何莹粲, 金明浩, 王一淇, 熊静远
作者信息
  • 四川大学华西公共卫生学院/华西第四医院,四川 成都 610041
  • 袁鑫(2003—),男,本科在读,研究方向:劳动卫生与环境卫生

通讯作者:

熊静远,E-mail:
Association between polycyclic aromatic hydrocarbon exposure and atherogenic index of plasma
Xin YUAN, Ying-can HE, Ming-hao JIN, Yi-qi WANG, Jing-yuan XIONG
Affiliations
  • West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-06-25 doi: 10.20043/j.cnki.MPM.202503077
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目的

通过分析美国国家健康和营养调查数据(National Health and Nutrition Examination Survey, NHANES)探讨多环芳烃(PAHs)暴露与血浆致动脉粥样硬化指数(AIP)的关联性。

方法

本研究选自NHANES 2009—2016年中≥20岁人群,由于尿液多环芳烃代谢物(OH-PAHs)的分布呈偏态(左偏),本研究应用对数变换(lg)使数据接近正态分布,根据lgOH-PAHs的四分位数水平将参与者分为四组。采用多元线性回归模型评估PAHs暴露与AIP的关联,使用平滑曲线拟合进一步探究PAHs暴露与AIP的非线性关系,并进行亚组分析。

结果

共纳入3 084例参与者,其中女性1560例(50.6%),平均年龄(49.1±17.6)岁。在校正年龄、性别、种族、教育水平、婚姻状况、家庭收入与贫困的比率、体重指数(BMI)、吸烟、饮酒、高血压、高胆固醇后,多元线性回归模型发现,与最低四分位数组(Q1)相比,最高四分位数组(Q4)(β=0.056,95% CI:0.021~0.091)与AIP呈正相关;在性别分层的亚组分析中,男性人群PAHs高暴露组(Q4)(β=0.068,95% CI:0.010~0.126)与AIP呈正相关,女性(β=0.047,95% CI:0.001~0.094)同上;在按BMI分层的亚组中,BMI<25的人群(β=0.096,95% CI:0.032~0.160)里,PAHs的水平与AIP的正相关显著。平滑曲线拟合结果显示,PAHs浓度与AIP呈倒U型关系。

结论

本研究发现PAHs暴露与AIP密切相关,提示PAHs暴露是AIP升高的重要危险因素。

多环芳烃  /  血浆致动脉粥样硬化指数  /  心血管疾病  /  NHANES
Objective

This study aims to investigate the association between polycyclic aromatic hydrocarbons (PAHs) exposure and the atherogenic index of plasma (AIP) by analyzing data from the National Health and Nutrition Examination Survey (NHANES).

Methods

Participants aged ≥20 years were selected from NHANES 2009-2016. Due to the left-skewed distribution of urinary PAHs metabolites (OH-PAHs), logarithmic transformation (lg) was applied to approximate a normal distribution. Participants were categorized into four quartiles based on lgOH-PAHs levels. A multiple linear regression model was used to evaluate the association between PAHs and AIP. A smoothing curve fitting approach was employed to explore potential nonlinear relationships, and subgroup analyses were conducted.

Results

A total of 3 084 participants were included, including 1 560 females (50.6%) with an average age of (49.1±17.6) years.After adjusting for age, sex, race, education level, marital status, the ratio of family income to poverty, body mass index (BMI), smoking, alcohol consumption, hypertension, and high cholesterol, multiple linear regression analysis indicated a positive association between the highest quartile of PAHs exposure (Q4) (β=0.056, 95% CI: 0.021-0.091) and AIP compared to the lowest quartile (Q1). In sex-stratified subgroup analyses, higher PAHs exposure (Q4) (β=0.068, 95% CI: 0.010-0.126) was positively associated with AIP in the male population. A similar positive correlation was also found in the female population (β=0.047, 95% CI: 0.001-0.094). In BMI-stratified analyses, the association between PAHs exposure and AIP was significant in participants with BMI <25(β=0.096, 95% CI: 0.032-0.160). Smoothing curve fitting demonstrated an inverted U-shaped relationship between PAHs concentration and AIP.

Conclusion

This study found a strong association between PAHs exposure and AIP, suggesting that PAHs exposure may be an important risk factor for increased AIP.

Polycyclic aromatic hydrocarbons  /  Atherogenic index of plasma  /  Cardiovascular disease  /  NHANES
袁鑫, 何莹粲, 金明浩, 王一淇, 熊静远. 多环芳烃暴露与血浆致动脉粥样硬化指数的关联性研究. 现代预防医学, 2025 , 52 (12) : 2166 -2171 . DOI: 10.20043/j.cnki.MPM.202503077
Xin YUAN, Ying-can HE, Ming-hao JIN, Yi-qi WANG, Jing-yuan XIONG. Association between polycyclic aromatic hydrocarbon exposure and atherogenic index of plasma[J]. Modern Preventive Medicine, 2025 , 52 (12) : 2166 -2171 . DOI: 10.20043/j.cnki.MPM.202503077
在全球范围内,心血管疾病是全球死亡的主要原因[1]。血浆致动脉粥样硬化指数(AIP)用于表达甘油三酯(TG)与高密度脂蛋白胆固醇(HDL-C)的比值关系,即 AIP=lg(TG/HDL-C),是预测心血管结局的关键指标[2]。大量研究表明,AIP是预测心血管疾病的关键生物标志物[3-6],其与冠状动脉粥样硬化疾病的风险和严重程度呈正相关[7]。AIP作为动态敏感指标,可更早反映脂代谢紊乱及动脉硬化风险和严重程度,具有临床预警价值,为预防CVD提供更多依据。
多环芳烃(PAHs)是一类有机污染物,几乎在所有不完全燃烧过程中形成,存在于环境空气、土壤、水和食物中[8],严重危害人类健康,可累及多个系统和器官,增加患肺癌和心血管疾病的风险。由于当前环境污染问题十分严峻,PAHs对健康人群的健康危害效应值得引起重视。现有研究表明多环芳烃类化合物暴露同氧化应激和动脉粥样硬化之间存在联系,并可能会增加癌症以及心血管系统疾病(CVD)的发病风险,包括动脉粥样硬化、冠状动脉损伤、高血压、心肌梗死等[9-10]。本研究通过分析美国国家健康与营养调查数据(National Health and Nutrition Examination Survey, NHANES),首次基于大样本人群,系统探究PAHs暴露与AIP之间的潜在关联,以AIP作为结局,能够更全面的表现各种心血管疾病的风险,受主观因素影响小,可靠性高,为心血管疾病的预防和控制提供新的科学依据和理论支持。
本研究使用的所有数据均来源于NHANES数据库,选取其中2009—2016年所有研究对象(n=40 439)。排除:(1)年龄<20岁的人群(n=17 173);(2)缺失尿液多环芳烃代谢物(OH-PAHs)和肌酐数据的人群(n=16 198);(3)缺失血脂数据的人群(n=3 984)。最终共有3 084例受试者纳入分析,详见图1
本研究选择OH-PAHs包括5个尿液低分子量PAH代谢物(1-羟基萘、2-羟基萘、2-羟基芴、3-羟基芴、1-羟基菲)和1个尿液高分子量代谢物(1-羟基芘)作为代表PAHs暴露程度的生物标志物[11]。采用同位素稀释高效液相色谱-串联质谱法对尿液样本进行检测[12]。低于检测限的值被替换为检测限除以作为浓度值[13]。将6种OH-PAHs的浓度相加并使用肌酐进行校正,得到总暴露水平(ng/g肌酐)。肌酐:1 mg/dl=0.0884 mmol/l。即:
由于OH-PAHs的分布呈偏态(左偏),本研究在分析前应用对数变换(lg)使数据接近正态分布。根据lgOH-PAHs的四分位数水平将参与者分为四组:Q1(lgOH-PAHs<-0.37)、Q2(-0.37≤ lgOH-PAHs<-0.12)、Q3(-0.12≤ lgOH-PAHs <0.20)、Q4(lgOH-PAHs ≥0.20)。
根据NHANES质量保证和质量控制协议采集空腹静脉血标本。采用贝克曼5800全自动生化分析仪检测总胆固醇(TC, mg/dl)、甘油三酯(TG, mg/dl)、低密度脂蛋白胆固醇(LDL-C, mg/dl)、高密度脂蛋白胆固醇(HDL-C, mg/dl)[14],TC/LDL-C/HDL-C:1 mg/dl=0.025 86 mmol/l;TG:1 mg/dl=0.011 29 mmol/l。AIP计算公式为:
协变量包括年龄、性别、婚姻状况、种族、教育水平、吸烟和饮酒状况、体重指数(BMI)、家庭收入与贫困的比率、是否高血压、是否高胆固醇。由经过培训的医务人员进行体格检查、实验室检查和问卷调查。教育水平根据受教育年限分为高中以下、高中毕业或同等学历和大专及以上。BMI的计算方式为体重/身高的二次方(kg/m2),BMI<25为正常,25~29.9为超重,≥30为肥胖。吸烟状况根据一生中是否至少抽100支香烟定义为“是”或“否”。饮酒状况根据一年中是否至少喝12杯酒精饮料定义为“是”或“否”。高血压和高胆固醇情况是根据受访者是否曾被医生或其他健康专业人员告知患有高血压/高胆固醇而获得的。使用R语言的Mice包对缺失数据进行多重插补,以最大限度的提高统计能力,并减少缺失数据可能导致的偏倚。
所有统计分析均使用R 4.4.2和EmpowerStats 6.0进行。由于NHANES使用复杂的多阶段概率抽样,所以需要对样本进行加权以确保分析结果能够准确反应美国人口的实际情况。本研究根据NHANES推荐的样本权重计算方法,使用参与人数最少的测量数据的权重(即尿液多环芳烃代谢物的样本权重),合并2009—2016年8年的数据,8年的样本权重等于2年样本权重的1/4。正态分布计量资料采用均数±标准差()表示,使用单因素方差分析比较。计数资料采用频数和频率[n(%)]表示, 使用卡方检验进行组间比较。采用加权多元线性回归模型来研究OH-PAHs和AIP的关联。此外,进行亚组分析,根据年龄、性别、BMI观察在不同亚组中OH-PAHs与AIP的关联以及是否存在交互作用。为了进一步探究两者的非线性关系,采用加权广义加性模型进行平滑曲线进行拟合,使用样条函数,并自动进行平滑优化。检验水准α=0.05。
本研究共纳入研究对象共3 084人,平均年龄为49.1岁, 其中女性1 560人(50.6%),男性1 524人(49.4%),不同lgOH-PAHs水平四分位组的年龄、性别、种族、教育水平、婚姻状况、家庭收入与贫困的比率、BMI、吸烟状态、饮酒状态、高密度脂蛋白胆固醇、甘油三酯与AIP均有统计学意义(P<0.05)。PAHs暴露较高的参与者受教育程度和收入水平较低,吸烟率较高。见表1
本研究按四分位数将lgOH-PAHs划分为Q1、Q2、Q3、Q4四组,使用加权多元线性回归模型评估lgOH-PAHs与AIP之间的关系。在模型1中,未调整混杂因素,发现较高的lgOH-PAHs与AIP呈正相关,即lgOH-PAHs的Q4组与Q1组相比,lgOH-PAHs水平每增加一个单位,AIP升高0.067。在对模型2与模型3中的协变量进行调整后,这种正相关依然显著。见表2
采用加权广义加性模型进行平滑曲线拟合进一步探究lgOH-PAHs与AIP的非线性关系。图2A表示个体lgOH-PAHs水平与AIP之间的分布情况,结合广义加性模型所拟合的平滑曲线,提示PAHs暴露与AIP之间可能存在非线性关系。图2B进一步通过模型估计剂量-反应关系曲线,结果表明AIP在中低暴露范围内随lgOH-PAHs水平升高而上升,而在较高暴露水平时出现下降趋势,呈现倒U型关系。此外,剂量-反应曲线的95%置信区间显示该关联在中低暴露水平段较为稳健,提示PAHs暴露与AIP之间可能存在剂量阈值效应,低剂量暴露对AIP的不良影响更为显著。
在按性别分层的亚组中发现,男性较高的lgOH-PAHs与AIP有显著正相关[β=0.068, 95% CI(0.010,0.126), P<0.05],女性同上[β=0.047,95% CI(0.001,0.094), P<0.05],且趋势性检验均有统计学意义(P趋势<0.05)。在按BMI分层的亚组分析中,lgOH-PAHs的Q4亚组与AIP的正相关在BMI<25时显著[β=0.096,95% CI(0.032,0.160),P<0.05],且趋势性检验有统计学意义(P趋势<0.05)。在按年龄的亚组分析中,lgOH-PAHs与AIP无统计学意义。交互检验表明,性别、年龄和BMI与多环芳烃暴露无交互作用(交互检验的P值均>0.05),见表3
本研究利用NHANES数据探讨了多环芳烃暴露与血浆致动脉粥样硬化指数之间的关系。研究发现多环芳烃暴露较高组(Q4)与AIP呈显著的正相关关系,多环芳烃暴露较高的参与者的AIP更高,可能会增加动脉粥样硬化的风险。这一发现与相关研究一致,PAHs可能通过氧化应激、炎症反应、内皮细胞损伤和脂质代谢紊乱促进动脉粥样硬化[15-17]。PAHs 可通过芳香烃受体(AhR)诱导基因表达变化,导致活性氧(ROS)和反应性电亲和代谢物的形成。ROS直接损伤血管内皮,降低一氧化氮(NO)的生物利用度,从而损害血管舒张功能。过量的ROS还可氧化低密度脂蛋白(oxLDL),促进泡沫细胞的形成,加速动脉粥样硬化的进展。PAHs暴露也可激活AhR,并通过NF-κB等信号通路促进IL-1β、IL-6 和TNF-α等促炎细胞因子的释放,增强血管通透性,促进单核细胞进入动脉壁,并加剧粥样斑块的发展。此外PAHs可增加细胞间粘附分子(ICAM-1)和血管细胞粘附分子(VCAM-1)的表达,使单核细胞更容易粘附到血管壁。PAHs还可以干扰细胞内钙离子([Ca2+]i)信号,影响内皮细胞的功能,甚至导致内皮细胞凋亡。PAHs 在代谢过程中可形成环氧化物等亲电子代谢物,并与DNA结合形成DNA加合物,诱发突变。动脉粥样硬化斑块中可检测到PAH-DNA加合物,提示PAHs暴露可能导致血管平滑肌细胞的异常增殖,加速斑块的形成。我们的研究结果与既往研究[18-20]是一致的,多环芳烃暴露与各种心血管疾病之间存在正相关。本研究以AIP作为结局,较既往研究能够更全面的表现各种心血管疾病的风险,受主观因素影响小,可靠性高,而既往研究普遍使用自我报告的问卷数据作为心血管系统疾病结局指标,只纳入了充血性心力衰竭/冠心病/心绞痛/心脏病发作/中风五种疾病,可能存在疾病描述不清、不全面,回忆偏倚大等问题。并且既往研究大多分别对单个OH-PAH与结局的关系进行分析,而本研究将多种OH-PAH相加,探讨混合OH-PAHs共同作用对AIP的影响,更加符合体内的实际生理情况。性别和年龄是心血管疾病的重要影响因素,不同性别和年龄人群的代谢特征、生理状态可能不同,并且性别和年龄作为基础分类,可以保证每个亚组的样本量足够支撑有效分析。因此选择其作为分层因素具有实际意义。亚组分析结果显示,无论男性还是女性,PAHs高暴露均与AIP呈正相关,且在BMI<25的正常体重组中,这种相关性更为显著(P<0.05),而在超重和肥胖组(BMI≥25)中则不显著(P>0.05)。这可能是因为超重和肥胖个体本身已存在较高的代谢紊乱和炎症水平,PAHs暴露对其AIP的影响被掩盖或减弱。
平滑曲线拟合结果显示,PAHs暴露与AIP之间呈倒U型关系,提示多环芳烃可能会通过影响脂质代谢进而导致心血管疾病风险增加,并可能存在阈值效应。这一发现为进一步研究PAHs暴露的健康效应提供了新的视角,也为制定环境污染物暴露的健康干预策略提供了科学依据。
AIP是一种用于评估动脉粥样硬化风险的新型生物标志物,与TC、TG、LDL-C、HDL-C等传统脂质标志物相比,AIP能更有效的反映血脂代谢异常,可用于评估心血管疾病的风险[21]。但本研究为横断面设计,无法确定PAHs暴露与AIP之间的因果关系,只能解释两者的相关性。此外,研究只调整了部分混杂因素,未直接调整空气污染和膳食的残余混杂风险,也不能排除一些其他潜在因素。由于NHANES主要针对美国人群,因此其结果在全球其他国家或地区可能不具备相同的外部效应。不同国家和文化背景下的生活方式和健康状况可能会大不相同,NHANES中的许多健康和生活方式数据,例如饮食习惯、运动量、吸烟和饮酒等依赖于受访者的自我报告,这可能会引入回忆偏倚或社会期望偏倚。未来需要进一步开展大样本的前瞻性研究探讨PAHs与AIP的关系与机制,或结合影像学指标及纵向设计验证。
综上所述,本研究发现PAHs暴露与AIP密切相关,提示PAHs暴露是AIP升高的重要危险因素,为心血管疾病的预防提供科学依据。
  • 四川省自然科学基金面上项目(2025ZNSFSC0641)
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doi: 10.20043/j.cnki.MPM.202503077
  • 接收时间:2025-03-04
  • 首发时间:2026-03-19
  • 出版时间:2025-06-25
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  • 收稿日期:2025-03-04
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四川省自然科学基金面上项目(2025ZNSFSC0641)
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    四川大学华西公共卫生学院/华西第四医院,四川 成都 610041

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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