Article(id=1324070926857405337, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202507101, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1751904000000, receivedDateStr=2025-07-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793612709010, onlineDateStr=2026-11-02, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793612709010, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793612709010, creator=13701087609, updateTime=1793612709010, updator=13701087609, issue=Issue{id=1324070892967428793, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793612700931, creator='13701087609', updateTime=1793612772549, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324071193430602023, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324071193430602024, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4466, endPage=4472, ext={EN=ArticleExt(id=1324070927071314842, articleId=1324070926857405337, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Impact of occupational noise exposure, personality traits, and their interaction on depression symptoms, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the impact of occupational noise exposure, personality traits, and their interactions on the risk of depression among working populations, to identify potential high-risk groups for depression, and to provide scientific evidence for the early prevention and personalized intervention of depression among occupational populations.

Methods

In this study, individual occupational noise exposure levels were assessed using cumulative noise exposure (CNE) for employees in a transport rail enterprise and automobile manufacturing unit in Guangzhou City in 2024. Depression, personality traits, and other relevant information were collected through questionnaires and occupational health examinations. Associations of occupational noise exposure, personality traits, and depression symptoms were statistically analyzed using logistic regression models and restricted cubic spline analysis. Interactions between occupational noise exposure and personality traits were analyzed using additive models to identify subgroups that may be at different risk or benefit as a result of the interaction.

Results

1 046 employees from two units in Guangzhou City were included in the final study. The median age of the study subjects was 29.0 (8.0) years, with a median CNE exposure level of 90.9 dB-years. A total of 390 individuals were identified as having depressive symptoms. The results of the logistic regression model indicate that CNE (OR=1.013, 95% CI: 1.008 to 1.018) and neuroticism (OR=1.106, 95% CI: 1.087 to 1.126) are risk factors for positive depressive symptoms. Agreeableness (OR=0.906, 95% CI: 0.884 to 0.927), Conscientiousness (OR=0.929, 95% CI: 0.909 to 0.948), openness (OR=0.947, 95% CI: 0.927 to 0.966), and extraversion (OR=0.877, 95% CI: 0.855 to 0.898) were protective factors against positive depressive symptoms. Simultaneously, RCS results indicated that agreeableness and extraversion exhibited linear dose-response relationships with depressive symptoms (P for overall <0.05, P for nonlinear >0.05), while cumulative noise exposure, neuroticism, conscientiousness, and openness demonstrated non-linear dose-response relationships (P for overall <0.05, P for nonlinear <0.05). Moreover, high neuroticism, low agreeableness, and low extraversion each exhibited additive interactions with occupational noise exposure. The relative excess risk due to interaction (RERI) values were 3.332, 2.653, and 4.579; the synergy index (SI) values were 2.315, 1.852, and 2.979;and the attributable proportions of interaction (AP) were 0.485, 0.392, and 0.580, respectively.

Conclusion

Occupational noise exposure and personality traits are influencing factors in the development of depressive symptoms among employees, with occupational noise exposure exhibiting an additive interaction with high neuroticism, low agreeableness, and low extraversion. Consequently, organizations should strengthen noise control measures in the workplace and implement targeted psychological interventions for employees exhibiting specific personality characteristics within this environment.

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目的

探讨职业性噪声暴露和性格特征及其交互作用对职业人群抑郁患病风险的影响,识别潜在的抑郁高风险人群,为职业人群抑郁的早期预防与个性化干预提供科学依据。

方法

本研究以2024年广州市某交通轨道和汽车制造单位职工为研究对象,使用累积噪声暴露量(CNE)评估个体职业性噪声暴露水平。抑郁、性格特征、其他相关信息通过问卷调查和职业健康检查收集。采用逻辑回归模型和限制性立方样条法(RCS)对职业性噪声暴露、性格特征和抑郁症状的关联进行统计分析。使用相加交互模型分析职业性噪声暴露和性格特征的交互作用,以确定各亚群可能因两者交互作用而面临不同的风险或收益。

结果

来自广州市两家单位的1 046名男性职工被纳入最终的研究。研究对象中位年龄为29.0(8.0)岁,CNE的中位暴露水平为90.9 dB年,抑郁症状的检出人数为390人。逻辑回归模型的结果显示,CNE(OR=1.013,95% CI:1.008~1.018)和神经质(OR=1.106,95% CI:1.087~1.126)是抑郁症状阳性的危险因素。宜人性(OR=0.906,95% CI:0.884~0.927)、严谨性(OR=0.929,95% CI:0.909~0.948)、开放性(OR=0.947,95% CI:0.927~0.966)及外向性(OR=0.877,95% CI:0.855~0.898)是抑郁症状阳性的保护因素。同时RCS结果显示,宜人性、外向性与抑郁症状存在线性剂量-反应关系(P全<0.05,P非线性>0.05),累积噪声暴露量、神经质、严谨性、开放性与抑郁症状存在非线性剂量-反应关系(P全<0.05,P非线性<0.05)。此外,高神经质、低宜人性和低外向性与职业性噪声暴露均存在相加交互作用,超额相对危险度(RERI)分别为3.332、2.653、4.579,交互作用指数(SI)分别为2.315、1.852、2.979,交互作用归因百分比(AP)分别为0.485、0.392、0.580。

结论

职业性噪声和性格特征是职工抑郁症状发生的影响因素,并且职业性噪声暴露与高神经质、低宜人性和低外向性存在相加交互作用。因此,单位应加强作业场所噪声管控,并针对该环境中特定性格特征的职工实施定向心理干预。

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李佳慧(1997—),女,硕士在读,研究方向:劳动卫生

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蔡春青和王致为共同通信作者。蔡春青,E-mail:;
王致,E-mail:
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Noise & Health, 2024, 26 (123): 523-534., articleTitle=Occupational noise, work-related stress, and teachers’ health in the French CONSTANCES study, refAbstract=null), Reference(id=1324070941554246649, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, doi=null, pmid=null, pmcid=null, year=2021, volume=48, issue=5, pageStart=502, pageEnd=509, url=null, language=null, rfNumber=[18], rfOrder=24, authorNames=王鹤霏, 白文琳, 陈茜, journalName=中国职业医学, refType=null, unstructuredReference=王鹤霏,白文琳,陈茜, 等. 间歇性与持续性噪声暴露致大鼠焦虑抑郁样行为改变机制 [J]. 中国职业医学, 2021, 48 (5): 502-509., articleTitle=间歇性与持续性噪声暴露致大鼠焦虑抑郁样行为改变机制, refAbstract=null), Reference(id=1324070941638132730, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, doi=null, pmid=null, pmcid=null, year=2021, volume=48, issue=5, pageStart=502, pageEnd=509, url=null, language=null, rfNumber=[18], rfOrder=25, authorNames=Wang HF, Bai WL, Chen Q, journalName=China Occupational Medicine, refType=null, unstructuredReference=Wang HF, Bai WL, Chen Q, et al. Mechanism of intermittent and persistent noise exposure-induced anxiety and depression-like behavior in rats [J]. China Occupational Medicine, 2021, 48 (5): 502-509. (In Chinese), articleTitle=Mechanism of intermittent and persistent noise exposure-induced anxiety and depression-like behavior in rats, refAbstract=null), Reference(id=1324070941738796027, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, doi=null, pmid=null, pmcid=null, year=2016, volume=11, issue=4, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[19], rfOrder=26, authorNames=Kim SE, Kim HN, Cho J, journalName=PLOS One, refType=null, unstructuredReference=Kim SE, Kim HN, Cho J, et al. Direct and indirect effects of five factor personality and gender on depressive symptoms mediated by perceived stress [J]. PLOS One, 2016, 11 (4): e0154140., articleTitle=Direct and indirect effects of five factor personality and gender on depressive symptoms mediated by perceived stress, refAbstract=null), Reference(id=1324070941831070716, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, doi=null, pmid=null, pmcid=null, year=2019, volume=105, issue=null, pageStart=86, pageEnd=97, url=null, language=null, rfNumber=[20], rfOrder=27, authorNames=Zänkert S, Bellingrath S, Wüst S, journalName=Psychoneuroendocrinology, refType=null, unstructuredReference=Zänkert S, Bellingrath S, Wüst S, et al. HPA axis responses to psychological challenge linking stress and disease: What do we know on sources of intra- and interindividual variability? [J]. Psychoneuroendocrinology, 2019, 105: 86-97., articleTitle=HPA axis responses to psychological challenge linking stress and disease: What do we know on sources of intra- and interindividual variability?, refAbstract=null)], funds=[Fund(id=1324070937309610971, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=202206010061, language=CN, fundingSource=广州市科学技术局重点研发计划项目(202206010061), fundOrder=null, country=null), Fund(id=1324070937389302748, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=2025—2027年, language=CN, fundingSource=广州市医学重点学科(2025—2027年), fundOrder=null, country=null), Fund(id=1324070937481577437, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=2023A03J0502, language=CN, fundingSource=广州市市校(院)企联合资助专题(广州市职业环境与健康重点实验室)(2023A03J0502), fundOrder=null, country=null), Fund(id=1324070937552880606, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=2025A031002, language=CN, fundingSource=广州市卫生健康科技重大项目(2025A031002), fundOrder=null, country=null), Fund(id=1324070937674515423, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=2023A03J0980, language=CN, fundingSource=广州市科技计划项目2023年度市校(院)企联合资助项目(2023A03J0980), fundOrder=null, country=null), Fund(id=1324070937754207200, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, awardId=2024A03J0505, language=CN, fundingSource=广州市科技计划项目2024年度市校(院)企联合资助项目(2024A03J0505), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324070928887448479, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, xref=1., ext=[AuthorCompanyExt(id=1324070928895837088, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, companyId=1324070928887448479, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, China), AuthorCompanyExt(id=1324070928908420001, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, companyId=1324070928887448479, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.南方医科大学公共卫生学院,广东 广州 510515)]), AuthorCompany(id=1324070930611307426, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, xref=2., ext=[AuthorCompanyExt(id=1324070930619696035, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, companyId=1324070930611307426, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广州市第十二人民医院职业环境与健康重点实验室)]), AuthorCompany(id=1324070930728747940, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, xref=3., ext=[AuthorCompanyExt(id=1324070930741330853, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, companyId=1324070930728747940, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.广州市职业病防治院)])], figs=[ArticleFig(id=1324070935564780497, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=EN, label=Fig.1, caption=Restricted cubic spline modelling of cumulative noise exposure, personality traits and depression symptoms, figureFileSmall=FY3QQ993KJ2iSJJlWA3cwg==, figureFileBig=K84m9yDVqxjPlH1tulT95Q==, tableContent=null), ArticleFig(id=1324070935900324818, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=CN, label=图1, caption=累积噪声暴露量、性格特征与抑郁症状的限制性立方样条图

注:图A为累积噪声暴露量与抑郁症状的剂量-反应关系;图B-F分别为性格特征中的神经质、宜人性、严谨性、开放性、外向性与抑郁症状的剂量-反应关系;所有模型均调整了年龄、教育水平、婚姻状况、收入、吸烟、饮酒等因素。

, figureFileSmall=FY3QQ993KJ2iSJJlWA3cwg==, figureFileBig=K84m9yDVqxjPlH1tulT95Q==, tableContent=null), ArticleFig(id=1324070936332338131, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=EN, label=Table 1, caption=

Analysis of the basic characteristics of the research subjects

, figureFileSmall=null, figureFileBig=null, tableContent=
变量全体
(n=1 046)
非抑郁症状
(n=656)
抑郁症状
(n=390)
P值
CNE[dB·年, M(IQR)]90.9(28.9)88.3(96.2)96.5(11.8)<0.001
噪声暴露[n(%)]<0.001
未接触噪声259(24.7)202(30.8)57(14.6)
低噪声暴露394(37.7)271(41.3)123(31.5)
高噪声暴露393(37.6)183(27.9)210(53.9)
年龄[岁, M(IQR)]29.0(8.0)29.0(9.0)30.0(8.0)<0.001
BMI[kg·m2, M(IQR)]23.1(5.0)22.8(5.0)23.5(4.7)0.017
吸烟[n(%)]0.202
不吸烟676(64.6)434(66.2)242(62.1)
吸烟370(35.4)222(33.8)148(37.9)
饮酒[n(%)]0.018
不饮酒666(63.7)436(66.5)230(59.0)
饮酒380(36.3)220(33.5)160(41.0)
教育水平[n(%)]0.064
初中及以下52(5.0)40(6.1)12(3.1)
高中或中专144(13.8)94(14.3)50(12.8)
大专及以上850(81.2)522(79.6)328(84.1)
婚姻状况[n(%)]0.060
未婚534(51.1)348(53.0)186(47.7)
已婚/同居491(46.9)299(45.6)192(49.2)
其他21(2.0)9(1.4)12(3.1)
收入[元/月, n(%)]<0.001
2 500元以下30(2.9)12(1.8)18(4.6)
2 500~5 000元389(37.2)222(33.8)167(42.8)
5 001~7 500元492(47.0)337(51.4)155(39.8)
7 500元以上135(12.9)85(13.0)50(12.8)
工龄[年, M(IQR)]6.1(11.0)5.2(9.0)7.1(8.7)<0.001
神经质[分, M(IQR)]20.0(14.0)17.0(11.0)26.0(13.8)<0.001
宜人性[分, M(IQR)]33.0(8.0)35.0(7.0)31.0(8.0)<0.001
严谨性[分, M(IQR)]35.0(9.0)37.0(9.0)33.0(8.0)<0.001
开放性[分, M(IQR)]31.0(9.0)32.0(9.0)30.0(7.0)<0.001
外向性[分, M(IQR)]31.0(9.0)33.0(9.0)27.0(8.0)<0.001
), ArticleFig(id=1324070936433001428, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=CN, label=表1, caption=

研究对象的基本特征分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量全体
(n=1 046)
非抑郁症状
(n=656)
抑郁症状
(n=390)
P值
CNE[dB·年, M(IQR)]90.9(28.9)88.3(96.2)96.5(11.8)<0.001
噪声暴露[n(%)]<0.001
未接触噪声259(24.7)202(30.8)57(14.6)
低噪声暴露394(37.7)271(41.3)123(31.5)
高噪声暴露393(37.6)183(27.9)210(53.9)
年龄[岁, M(IQR)]29.0(8.0)29.0(9.0)30.0(8.0)<0.001
BMI[kg·m2, M(IQR)]23.1(5.0)22.8(5.0)23.5(4.7)0.017
吸烟[n(%)]0.202
不吸烟676(64.6)434(66.2)242(62.1)
吸烟370(35.4)222(33.8)148(37.9)
饮酒[n(%)]0.018
不饮酒666(63.7)436(66.5)230(59.0)
饮酒380(36.3)220(33.5)160(41.0)
教育水平[n(%)]0.064
初中及以下52(5.0)40(6.1)12(3.1)
高中或中专144(13.8)94(14.3)50(12.8)
大专及以上850(81.2)522(79.6)328(84.1)
婚姻状况[n(%)]0.060
未婚534(51.1)348(53.0)186(47.7)
已婚/同居491(46.9)299(45.6)192(49.2)
其他21(2.0)9(1.4)12(3.1)
收入[元/月, n(%)]<0.001
2 500元以下30(2.9)12(1.8)18(4.6)
2 500~5 000元389(37.2)222(33.8)167(42.8)
5 001~7 500元492(47.0)337(51.4)155(39.8)
7 500元以上135(12.9)85(13.0)50(12.8)
工龄[年, M(IQR)]6.1(11.0)5.2(9.0)7.1(8.7)<0.001
神经质[分, M(IQR)]20.0(14.0)17.0(11.0)26.0(13.8)<0.001
宜人性[分, M(IQR)]33.0(8.0)35.0(7.0)31.0(8.0)<0.001
严谨性[分, M(IQR)]35.0(9.0)37.0(9.0)33.0(8.0)<0.001
开放性[分, M(IQR)]31.0(9.0)32.0(9.0)30.0(7.0)<0.001
外向性[分, M(IQR)]31.0(9.0)33.0(9.0)27.0(8.0)<0.001
), ArticleFig(id=1324070936709825493, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=EN, label=Table 2, caption=

Logistic regression analysis of occupational noise exposure, personality traits, and depression symptoms in the working population

, figureFileSmall=null, figureFileBig=null, tableContent=
变量抑郁症状检出率[OR (95% CI)]
未调整模型调整模型
CNE1.012(1.008~1.016)1.013(1.008~1.018)
未接噪组1.000(ref)1.000(ref)
低噪声组1.608(1.122~2.325)1.648(1.029~2.676)
高噪声组4.067(2.866~5.836)3.989(2.474~6.539)
神经质1.105(1.087~1.124)1.106(1.087~1.126)
宜人性0.905(0.883~0.926)0.906(0.884~0.927)
严谨性0.931(0.912~0.949)0.929(0.909~0.948)
开放性0.944(0.925~0.962)0.947(0.927~0.966)
外向性0.878(0.858~0.898)0.877(0.855~0.898)
), ArticleFig(id=1324070936823071702, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=CN, label=表2, caption=

职业性噪声暴露、性格特征与职业人群抑郁症状之间的逻辑回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量抑郁症状检出率[OR (95% CI)]
未调整模型调整模型
CNE1.012(1.008~1.016)1.013(1.008~1.018)
未接噪组1.000(ref)1.000(ref)
低噪声组1.608(1.122~2.325)1.648(1.029~2.676)
高噪声组4.067(2.866~5.836)3.989(2.474~6.539)
神经质1.105(1.087~1.124)1.106(1.087~1.126)
宜人性0.905(0.883~0.926)0.906(0.884~0.927)
严谨性0.931(0.912~0.949)0.929(0.909~0.948)
开放性0.944(0.925~0.962)0.947(0.927~0.966)
外向性0.878(0.858~0.898)0.877(0.855~0.898)
), ArticleFig(id=1324070936906957783, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=EN, label=Table 3, caption=

Qualitative analysis of the additive interaction of occupational noise exposure and personality traits on the risk of developing depression symptoms in the working population

, figureFileSmall=null, figureFileBig=null, tableContent=
噪声暴露性格特征类型未调整模型调整模型
OR (95% CI)P值OR (95% CI)P值
否低神经质1.000(ref)1.000(ref)
否高神经质2.489(1.335~4.642)0.0042.518(1.324~4.786)0.005
是低神经质2.323(1.345~4.010)0.0022.017(1.077~3.776)0.028
是高神经质7.714(4.511~13.194)<0.0016.867(3.713~12.698)<0.001
否高宜人性1.000(ref)1.000(ref)
否低宜人性2.965(1.612~5.868)<0.0012.861(1.528~5.375)0.001
是高宜人性2.538(1.528~4.216)<0.0012.252(1.237~4.099)0.008
是低宜人性7.988(4.821~13.236)<0.0016.766(3.746~12.223)<0.001
否高外向性1.000(ref)1.000(ref)
否低外向性2.591(1.398~4.802)0.0022.479(1.318~4.660)0.005
是高外向性2.047(1.198~3.498)0.0091.835(0.981~3.435)0.058
是低外向性8.810(5.206~14.909)<0.0017.893(4.258~14.629)<0.001
否高严谨性1.000(ref)1.000(ref)
否低严谨性5.854(2.961~11.575)<0.0015.683(2.824~11.439)<0.001
是高严谨性5.136(2.805~9.402)<0.0014.393(2.209~8.738)<0.001
是低严谨性10.517(5.736~19.286)<0.0018.810(4.466~17.382)<0.001
否高开放性1.000(ref)1.000(ref)
否低开放性1.717(0.950~3.104)0.0741.662(0.901~3.064)0.104
是高开放性2.363(1.498~3.726)<0.0012.169(1.260~3.735)0.005
是低开放性4.810(3.041~7.610)<0.0014.282(2.480~7.393)<0.001
), ArticleFig(id=1324070937007621080, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070926857405337, language=CN, label=表3, caption=

职业性噪声暴露和性格特征对职业人群抑郁症状患病风险相加交互作用的定性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
噪声暴露性格特征类型未调整模型调整模型
OR (95% CI)P值OR (95% CI)P值
否低神经质1.000(ref)1.000(ref)
否高神经质2.489(1.335~4.642)0.0042.518(1.324~4.786)0.005
是低神经质2.323(1.345~4.010)0.0022.017(1.077~3.776)0.028
是高神经质7.714(4.511~13.194)<0.0016.867(3.713~12.698)<0.001
否高宜人性1.000(ref)1.000(ref)
否低宜人性2.965(1.612~5.868)<0.0012.861(1.528~5.375)0.001
是高宜人性2.538(1.528~4.216)<0.0012.252(1.237~4.099)0.008
是低宜人性7.988(4.821~13.236)<0.0016.766(3.746~12.223)<0.001
否高外向性1.000(ref)1.000(ref)
否低外向性2.591(1.398~4.802)0.0022.479(1.318~4.660)0.005
是高外向性2.047(1.198~3.498)0.0091.835(0.981~3.435)0.058
是低外向性8.810(5.206~14.909)<0.0017.893(4.258~14.629)<0.001
否高严谨性1.000(ref)1.000(ref)
否低严谨性5.854(2.961~11.575)<0.0015.683(2.824~11.439)<0.001
是高严谨性5.136(2.805~9.402)<0.0014.393(2.209~8.738)<0.001
是低严谨性10.517(5.736~19.286)<0.0018.810(4.466~17.382)<0.001
否高开放性1.000(ref)1.000(ref)
否低开放性1.717(0.950~3.104)0.0741.662(0.901~3.064)0.104
是高开放性2.363(1.498~3.726)<0.0012.169(1.260~3.735)0.005
是低开放性4.810(3.041~7.610)<0.0014.282(2.480~7.393)<0.001
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Quantitative analysis of the additive interaction between occupational noise exposure and personality traits on the risk of depression symptoms prevalence in the working population

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变量RERI(95% CI)AP(95% CI)SI(95% CI)
未调整模型
噪声暴露+高神经质3.902(1.547~6.258)0.506(0.194~0.818)2.388(1.475~3.864)
噪声暴露+低宜人性3.485(1.101~5.868)0.436(0.108~0.765)1.995(1.268~3.139)
噪声暴露+低外向性5.172(2.263~8.081)0.587(0.323~0.851)2.960(1.616~5.423)
噪声暴露+低严谨性0.527(-2.726~3.780)0.050(-0.541~0.641)1.059(0.522~2.146)
噪声暴露+低开放性1.731(0.374~3.087)0.360(0.014~0.705)1.832(0.784~4.282)
调整模型
噪声暴露+高神经质3.332(0.762~5.904)0.485(0.145~0.826)2.315(1.370~3.912)
噪声暴露+低宜人性2.653(0.188~5.118)0.392(0.021~0.764)1.852(1.104~3.107)
噪声暴露+低外向性4.579(1.352~7.805)0.580(0.297~0.864)2.979(1.504~5.900)
噪声暴露+低严谨性-0.266(-3.624~3.091)-0.030(-0.693~0.632)0.967(0.424~2.208)
噪声暴露+低开放性1.451(0.020~2.883)0.339(-0.039~0.717)1.793(0.704~4.565)
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职业性噪声暴露和性格特征对职业人群抑郁症状患病风险相加交互作用的定量分析

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变量RERI(95% CI)AP(95% CI)SI(95% CI)
未调整模型
噪声暴露+高神经质3.902(1.547~6.258)0.506(0.194~0.818)2.388(1.475~3.864)
噪声暴露+低宜人性3.485(1.101~5.868)0.436(0.108~0.765)1.995(1.268~3.139)
噪声暴露+低外向性5.172(2.263~8.081)0.587(0.323~0.851)2.960(1.616~5.423)
噪声暴露+低严谨性0.527(-2.726~3.780)0.050(-0.541~0.641)1.059(0.522~2.146)
噪声暴露+低开放性1.731(0.374~3.087)0.360(0.014~0.705)1.832(0.784~4.282)
调整模型
噪声暴露+高神经质3.332(0.762~5.904)0.485(0.145~0.826)2.315(1.370~3.912)
噪声暴露+低宜人性2.653(0.188~5.118)0.392(0.021~0.764)1.852(1.104~3.107)
噪声暴露+低外向性4.579(1.352~7.805)0.580(0.297~0.864)2.979(1.504~5.900)
噪声暴露+低严谨性-0.266(-3.624~3.091)-0.030(-0.693~0.632)0.967(0.424~2.208)
噪声暴露+低开放性1.451(0.020~2.883)0.339(-0.039~0.717)1.793(0.704~4.565)
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职业性噪声暴露和性格特征及其交互作用对抑郁症状的影响
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李佳慧 1, 2 , 段丹萍 2, 3 , 白卢皙 2, 3 , 李燕茹 2, 3 , 蔡春青 1 , 王致 2
现代预防医学 | 环境与职业卫生 2025,52(24): 4466-4472
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现代预防医学 |环境与职业卫生 2025 , 52 (24) : 4466 -4472
职业性噪声暴露和性格特征及其交互作用对抑郁症状的影响
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李佳慧1, 2, 段丹萍2, 3, 白卢皙2, 3, 李燕茹2, 3, 蔡春青1 , 王致2
作者信息
  • 1.南方医科大学公共卫生学院,广东 广州 510515
  • 2.广州市第十二人民医院职业环境与健康重点实验室
  • 3.广州市职业病防治院
通讯作者:
蔡春青和王致为共同通信作者。蔡春青,E-mail:;
王致,E-mail:
作者简介:

李佳慧(1997—),女,硕士在读,研究方向:劳动卫生

Impact of occupational noise exposure, personality traits, and their interaction on depression symptoms
Jia-hui LI1, 2, Dan-ping DUAN2, 3, Lu-xi BAI2, 3, Yan-ru LI2, 3, Chun-qing CAI1 , Zhi WANG2
Affiliations
  • School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, China
出版时间: 2025-12-25 doi: 10.20043/j.cnki.MPM.202507101
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目的

探讨职业性噪声暴露和性格特征及其交互作用对职业人群抑郁患病风险的影响,识别潜在的抑郁高风险人群,为职业人群抑郁的早期预防与个性化干预提供科学依据。

方法

本研究以2024年广州市某交通轨道和汽车制造单位职工为研究对象,使用累积噪声暴露量(CNE)评估个体职业性噪声暴露水平。抑郁、性格特征、其他相关信息通过问卷调查和职业健康检查收集。采用逻辑回归模型和限制性立方样条法(RCS)对职业性噪声暴露、性格特征和抑郁症状的关联进行统计分析。使用相加交互模型分析职业性噪声暴露和性格特征的交互作用,以确定各亚群可能因两者交互作用而面临不同的风险或收益。

结果

来自广州市两家单位的1 046名男性职工被纳入最终的研究。研究对象中位年龄为29.0(8.0)岁,CNE的中位暴露水平为90.9 dB年,抑郁症状的检出人数为390人。逻辑回归模型的结果显示,CNE(OR=1.013,95% CI:1.008~1.018)和神经质(OR=1.106,95% CI:1.087~1.126)是抑郁症状阳性的危险因素。宜人性(OR=0.906,95% CI:0.884~0.927)、严谨性(OR=0.929,95% CI:0.909~0.948)、开放性(OR=0.947,95% CI:0.927~0.966)及外向性(OR=0.877,95% CI:0.855~0.898)是抑郁症状阳性的保护因素。同时RCS结果显示,宜人性、外向性与抑郁症状存在线性剂量-反应关系(P全<0.05,P非线性>0.05),累积噪声暴露量、神经质、严谨性、开放性与抑郁症状存在非线性剂量-反应关系(P全<0.05,P非线性<0.05)。此外,高神经质、低宜人性和低外向性与职业性噪声暴露均存在相加交互作用,超额相对危险度(RERI)分别为3.332、2.653、4.579,交互作用指数(SI)分别为2.315、1.852、2.979,交互作用归因百分比(AP)分别为0.485、0.392、0.580。

结论

职业性噪声和性格特征是职工抑郁症状发生的影响因素,并且职业性噪声暴露与高神经质、低宜人性和低外向性存在相加交互作用。因此,单位应加强作业场所噪声管控,并针对该环境中特定性格特征的职工实施定向心理干预。

抑郁症  /  个体噪声暴露水平  /  性格特征  /  交互作用
Objective

To investigate the impact of occupational noise exposure, personality traits, and their interactions on the risk of depression among working populations, to identify potential high-risk groups for depression, and to provide scientific evidence for the early prevention and personalized intervention of depression among occupational populations.

Methods

In this study, individual occupational noise exposure levels were assessed using cumulative noise exposure (CNE) for employees in a transport rail enterprise and automobile manufacturing unit in Guangzhou City in 2024. Depression, personality traits, and other relevant information were collected through questionnaires and occupational health examinations. Associations of occupational noise exposure, personality traits, and depression symptoms were statistically analyzed using logistic regression models and restricted cubic spline analysis. Interactions between occupational noise exposure and personality traits were analyzed using additive models to identify subgroups that may be at different risk or benefit as a result of the interaction.

Results

1 046 employees from two units in Guangzhou City were included in the final study. The median age of the study subjects was 29.0 (8.0) years, with a median CNE exposure level of 90.9 dB-years. A total of 390 individuals were identified as having depressive symptoms. The results of the logistic regression model indicate that CNE (OR=1.013, 95% CI: 1.008 to 1.018) and neuroticism (OR=1.106, 95% CI: 1.087 to 1.126) are risk factors for positive depressive symptoms. Agreeableness (OR=0.906, 95% CI: 0.884 to 0.927), Conscientiousness (OR=0.929, 95% CI: 0.909 to 0.948), openness (OR=0.947, 95% CI: 0.927 to 0.966), and extraversion (OR=0.877, 95% CI: 0.855 to 0.898) were protective factors against positive depressive symptoms. Simultaneously, RCS results indicated that agreeableness and extraversion exhibited linear dose-response relationships with depressive symptoms (P for overall <0.05, P for nonlinear >0.05), while cumulative noise exposure, neuroticism, conscientiousness, and openness demonstrated non-linear dose-response relationships (P for overall <0.05, P for nonlinear <0.05). Moreover, high neuroticism, low agreeableness, and low extraversion each exhibited additive interactions with occupational noise exposure. The relative excess risk due to interaction (RERI) values were 3.332, 2.653, and 4.579; the synergy index (SI) values were 2.315, 1.852, and 2.979;and the attributable proportions of interaction (AP) were 0.485, 0.392, and 0.580, respectively.

Conclusion

Occupational noise exposure and personality traits are influencing factors in the development of depressive symptoms among employees, with occupational noise exposure exhibiting an additive interaction with high neuroticism, low agreeableness, and low extraversion. Consequently, organizations should strengthen noise control measures in the workplace and implement targeted psychological interventions for employees exhibiting specific personality characteristics within this environment.

Depression  /  Individual noise exposure level  /  Personality traits  /  Interaction
李佳慧, 段丹萍, 白卢皙, 李燕茹, 蔡春青, 王致. 职业性噪声暴露和性格特征及其交互作用对抑郁症状的影响. 现代预防医学, 2025 , 52 (24) : 4466 -4472 . DOI: 10.20043/j.cnki.MPM.202507101
Jia-hui LI, Dan-ping DUAN, Lu-xi BAI, Yan-ru LI, Chun-qing CAI, Zhi WANG. Impact of occupational noise exposure, personality traits, and their interaction on depression symptoms[J]. Modern Preventive Medicine, 2025 , 52 (24) : 4466 -4472 . DOI: 10.20043/j.cnki.MPM.202507101
职业性噪声是工作环境中最普遍的职业危害因素之一[1]。研究发现,职业性噪声暴露是抑郁的重要危险因素[2-3],其潜在机制可能涉及噪声通过激活下丘脑-垂体-肾上腺轴,导致海马体结构和功能受损,从而损害认知功能和情绪调节能力[4-5]。此外,在个体层面,性格特征也被证实是抑郁发生的重要影响因素。相关研究表明,神经质、外向性和宜人性等是抑郁发生的重要预测因子,并且个体性格特性显著影响个体在面对压力事件时的应对方式和情绪反应[6-7]。而噪声本质上是一种环境压力源[8],所以性格特征在职业性噪声导致抑郁的过程中可能起交互作用。然而,既往研究多聚焦于职业性噪声或性格对抑郁的独立效应,较少关注二者可能存在的交互作用。深入分析职业性噪声暴露与性格的交互效应,对于理解职业性噪声暴露条件下个体抑郁风险差异也具有重要意义。因此,本研究旨在探讨个体职业性噪声暴露、性格特征与抑郁之间的关系,并进一步分析性格特征与职业性噪声的交互作用,以期更精准地识别高风险人群,助力职业人群抑郁的早期预防及制定个性化干预策略提供科学依据。
研究于2024年9月至12月进行,选取广州市某交通轨道单位与某汽车制造单位的员工作为研究对象进行问卷调查。研究对象从事机械检修员、接触网检修员、工建检修员等岗位。研究对象纳入标准:①研究单位在岗职工;②获得知情同意。排除标准:①缺少暴露或结局资料及问卷填写不合格者;②患严重神经系统疾病、其他精神疾病及严重躯体疾病(肝肾功能衰竭、恶性肿瘤晚期等);③有耳毒性药物使用史、非噪声性耳聋。由于研究对象中接触职业性噪声暴露女性仅占1%,出于样本代表性考虑,排除女性职工。本研究经广州市第十二人民医院伦理审查委员会审核批准(审批编号:2023066),且所有研究对象均签署知情同意书。
依据国家标准GBZ/T 189.8—2007《工作场所物理因素测量第8部分:噪声》要求,由职业卫生专业人员实施现场调查和测量,在充分掌握工作场所噪声暴露的分布规律与特征下,确定适宜的测量方法。本研究采用定点采样和个体采样两种方法进行测量,噪声强度呈现规律性变化的岗位,选用定点采样法进行测定。少数噪声波动无规律的岗位,则采用个体采样法测量。考虑到劳动者接触噪声强度与接触时间的综合效应,本研究采用累积噪声暴露量(Cumulative Noise Exposure,CNE)作为个体噪声接触水平的量化指标。其计算方法为[9]:CNE=10log [∑(10dB(A)/10×T)]。式中,dB(A)代表A计权噪声测量值,T代表以年计的暴露时间。同时,将研究对象分为三组:未接触职业性噪声组、职业性噪声低暴露组及高暴露组。其中,噪声暴露组依据其CNE值的中位数进行划分,即低暴露组(CNE<中位数)和高暴露组(CNE≥中位数)[10]。
采用PHQ-9(Patient Health Questionnaire)抑郁症筛查量表评估被调查者抑郁情况。量表共有9个条目,每个条目计为0~3分,总分为0~27分。量表总分≥5分定义为抑郁症状[11]。本研究量表Cronbach α为0.871,表明其内部一致性信度良好。
采用王孟成学者[12]编制的中国大五人格问卷简式版(Chinese Big Five Personality Inventory brief version, CBF–PI–B)评估被调查者性格特征。该问卷共包含外向性、宜人性、严谨性、神经质、开放性5个性格维度。各维度有8个条目,问卷共40个条目。各维度得分范围8~48分,高分代表相应特质水平更高。神经质反映情绪稳定性差异。宜人性表征人际合作倾向。严谨性体现目标管理能力。开放性指对新事物的接纳度。外向性则衡量个体社交主动性。本研究中以各维度中位数为界,≥中位数定义为高分组,反之为低分组。所用量表的Cronbach α系数为0.847,具有良好的内部一致性信度。
年龄、体质指数(BMI)、工作年数、岗位来自职业健康检查数据。吸烟状况、饮酒状况、月收入、教育程度、婚姻状况通过自填式问卷进行收集。吸烟定义为每日吸烟≥1支且持续≥6个月。饮酒定义为每周饮酒≥1次且持续≥1年。教育水平分为初中及以下、高中或中专和大专及以上。婚姻状况分为未婚、已婚/同居和其他。月收入分为2 500元以下、2 500~5 000元、5 001~7 500元、7 500元以上。
研究中连续变量经正态分布检验(Q-Q图和Shapiro-Wilk检验),结果提示数据均为非正态分布。统计描述时,非正态分布的连续变量采用中位数M(IQR)表示,分类变量采用频数n(%)表示。组间比较时,非正态分布的连续变量采用Mann-Whitney U检验,分类变量采用卡方检验。逻辑回归模型以比值比(odds ratio, OR)和95%置信区间(confidence interval, CI)表示CNE、职业性噪声暴露和性格特征与抑郁之间的关系,并根据以往的研究[13-14]筛选协变量,拟合未调整模型和调整模型。采用限制性立方样条法(restricted cubic spline, RCS; K=4)来评估职业性噪声、性格特征与抑郁之间剂量-反应关系。此外,通过delta法检验性格特征中神经质(低神经质vs高神经质)、宜人性(低宜人性vs高宜人性)、严谨性(低严谨性vs高严谨性)、开放性(低开放性vs高开放性)和外向性(低外向性vs高外向性)与噪声暴露的交互作用。职业性噪声暴露和性格特征转换为二分类变量进行分析,便于解释各亚群可能因两者交互作用而存在的风险差异。统计分析使用R(4.4.0版本),检验水准为双侧α=0.05。
本研究共纳入1 046名男性职工进行数据分析。研究对象中位年龄为29.0(8.0)岁。抑郁症状检出人数为390人,检出率为37.3%。抑郁症状组的CNE、年龄、工龄、BMI、神经质水平高于非抑郁症状组(P<0.05),宜人性、严谨性、开放性、外向性水平低于非抑郁症状组(P<0.05)。此外,是否饮酒、不同收入在两组间也存在差异(P<0.05)。见表1。
由表2逻辑回归分析结果显示:CNE与抑郁症状相关(OR=1.013,95% CI:1.008~1.018)。在分类模型中,相比于未接触噪声组,低噪声暴露组(OR=1.648,95% CI:1.029~2.676)和高噪声暴露组(OR=3.989,95% CI:2.474~6.539)抑郁症状阳性风险更大。神经质、宜人性、严谨性、开放性及外向性也与抑郁症状显著相关。此外RCS分析显示宜人性、外向性与抑郁症状存在线性剂量-反应关系(P全<0.05,P非线性>0.05),累积噪声暴露量、神经质、严谨性、开放性与抑郁症状存在非线性剂量-反应关系(P全<0.05,P非线性<0.05)。见图1。
由表3和表4结果可知,职业性噪声暴露与高神经质、低宜人性及低外向性存在相加交互作用。职业性噪声暴露和高神经质两者同时存在时,其致抑郁症状的风险高于两者独立效应之和(RERI=3.332,95% CI:0.762~5.904),协同作用为两者独立效应之和的2.315倍(SI=2.315,95% CI:1.370~3.912),48.5%的抑郁症状阳性风险归因于两者的协同作用(AP=0.485,95% CI:0.145~0.826)。职业性噪声暴露和低宜人性两者同时存在时,其致抑郁症状的风险高于两者独立效应之和(RERI=2.653,95% CI:0.188~5.118),协同作用为两者独立效应之和的1.852倍(SI=1.852,95% CI:1.104~3.107),39.2%的抑郁症状阳性风险归因于两者的协同作用(AP=0.392,95% CI:0.021~0.764)。职业性噪声暴露和低外向性两者同时存在时,其致抑郁症状的风险高于两者独立效应之和(RERI=4.579,95% CI:1.352~7.805),协同作用为两者独立效应之和的2.979倍(SI=2.979,95% CI:1.504~5.900),58.0%的抑郁症状阳性风险归因于两者的协同作用(AP=0.580,95% CI:0.297~0.864)。低严谨性、低开放性与职业性噪声暴露均不存在相加交互作用。
本研究人群抑郁症状检出率为37.3%,高于河北某钢铁工人抑郁检出率27.15%[13],但低于广州某电子制造企业工人抑郁症状检出率63.2%[15]和广州某制造厂抑郁患病率47.1%[16]。这些差异可能源于研究领域和对象不同,但均凸显职业人群抑郁的高发风险。研究也通过量化个体的噪声暴露水平和性格特征,更精确地揭示噪声和性格对抑郁的影响。研究结果显示,抑郁症状阳性风险的显著增加与CNE和性格有关。同时,研究考虑到个体性格与职业性噪声的交互作用对职工心理影响,发现高神经质、低宜人性和低外向性与职业性噪声暴露存在正向相加交互作用,两者同时存在显著增加职业人群抑郁症状阳性风险。
Yang S[2]和Temam S[17]等学者的研究均发现职业性噪声暴露与抑郁之间呈正向关联。然而,这些研究中工作噪声暴露是通过问卷进行自我感知定义,不能准确反映研究对象的真实噪声暴露水平。陈小方[3]等学者研究表明CNE与负性情绪(压力感、焦虑感和抑郁感)呈正相关,相关系数分别为0.19、0.21和0.13,但该研究未纳入未接触噪声对照组及模型未调整协变量,导致结果可能受到多种混杂影响。在一项动物实验研究中,对大鼠施加间歇性及持续性噪声暴露,并通过糖水偏爱实验和强迫游泳实验评价抑郁行为,结果表明噪声暴露可以可导致大鼠出现焦虑抑郁样行为改变,且持续性噪声暴露作用更强[18]。与上述实验研究结果一致,本研究调整协变量后,结果仍显示职业噪声暴露与抑郁之间存在显著关联。
研究结果也显示性格特征是抑郁症状发生的重要影响因素,神经质、宜人性、严谨性、开放性、外向性与职业人群抑郁存在显著关联。同样国外Kim S E[19]的研究也发现神经质、外向性和严谨性等性格特征对抑郁症状有影响,并且人格因素与抑郁症状之间的联系是由压力介导的。
职业性噪声和性格特征可能通过交互作用对抑郁产生更复杂的影响,目前其机制尚未完全清晰。有研究发现,噪声作为一种应激源,可激活下丘脑-垂体-肾上腺(HPA)轴,导致促肾上腺皮质激素释放激素(CRH)和皮质醇等应激激素分泌增加。高水平皮质醇与大脑(尤其是海马区)的低亲和力糖皮质激素受体结合,可抑制海马神经元活性及其可塑性,从而损害情绪调控功能[4-5]。另一方面,个体性格特征可能与皮质醇过度激活有关,如高神经质等特质与HPA轴基础活性增高和应激反应增强密切相关[20]。这种生理易感性可能放大噪声诱导的神经内分泌反应,导致更显著或持续的皮质醇暴露,从而引起突触功能受损、神经发生抑制等神经元变化,最终协同增加抑郁风险。这不仅为噪声与性格的独立效应提供了机制解释,更从HPA轴调节层面,为二者的交互作用提供了生物学合理性,强调在抑郁防治中需重视“环境-个体”互作模式。但本研究并未发现严谨性、开放性等性格特征的交互作用,未来可以考虑更充足样本量进行分析。
本研究具有一些优势。研究探讨了职业性噪声暴露和个体性格特征及其交互作用对抑郁的影响,识别出潜在高危人群,提示未来的职业心理健康保护策略需从单纯控制环境危害,转向环境管理与个体易感性筛查相结合的精准预防模式。同时,本研究也存在一些不足,一是横断面设计难以确定职业性噪声暴露和性格与抑郁之间的因果关系。二是本研究对象均为男性且来自两个单位,可能在一定程度上限制了结果的推广性。但已通过严格的工作性质匹配及环境暴露验证,最大程度减少混杂偏倚。未来的研究需要进一步探讨这种交互作用的潜在机制,并考虑在不同人群中的适用性。
综上所述,噪声暴露和神经质是职业人群抑郁的危险因素。尤其值得注意的是,高神经质、低宜人性及低外向性人格特质与职业性噪声暴露会产生相加交互作用,这显著增加了职业人群抑郁症状阳性风险。因此,建议采取工程控制措施从源头上降低噪声强度,或加强个人防护以有效减少职工的噪声暴露水平。同时,应积极主动干预在职业噪声暴露环境下具有高神经质、低宜人性和低外向性特征的员工所承受的心理压力。
  • 广州市科学技术局重点研发计划项目(202206010061)
  • 广州市医学重点学科(2025—2027年)
  • 广州市市校(院)企联合资助专题(广州市职业环境与健康重点实验室)(2023A03J0502)
  • 广州市卫生健康科技重大项目(2025A031002)
  • 广州市科技计划项目2023年度市校(院)企联合资助项目(2023A03J0980)
  • 广州市科技计划项目2024年度市校(院)企联合资助项目(2024A03J0505)
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2025年第52卷第24期
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doi: 10.20043/j.cnki.MPM.202507101
  • 接收时间:2025-07-08
  • 首发时间:2026-11-02
  • 出版时间:2025-12-25
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  • 收稿日期:2025-07-08
基金
广州市科学技术局重点研发计划项目(202206010061)
广州市医学重点学科(2025—2027年)
广州市市校(院)企联合资助专题(广州市职业环境与健康重点实验室)(2023A03J0502)
广州市卫生健康科技重大项目(2025A031002)
广州市科技计划项目2023年度市校(院)企联合资助项目(2023A03J0980)
广州市科技计划项目2024年度市校(院)企联合资助项目(2024A03J0505)
作者信息
    1.南方医科大学公共卫生学院,广东 广州 510515
    2.广州市第十二人民医院职业环境与健康重点实验室
    3.广州市职业病防治院

通讯作者:

蔡春青和王致为共同通信作者。蔡春青,E-mail:;
王致,E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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