Article(id=1321169575077593368, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, articleNumber=null, orderNo=null, doi=10.11847/zgggws1147417, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742140800000, receivedDateStr=2025-03-17, revisedDate=1752422400000, revisedDateStr=2025-07-14, acceptedDate=1757865600000, acceptedDateStr=2025-09-15, onlineDate=1792920972841, onlineDateStr=2026-10-25, pubDate=1762704000000, pubDateStr=2025-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792920972841, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792920972841, creator=13701087609, updateTime=1792920972841, updator=13701087609, issue=Issue{id=1321169495406785472, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='11', pageStart='1281', pageEnd='1408', issueExtLink='null', onlineDate='null', pubDate='1762704000000', pubDateStr='2025-11-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792920953847, creator='13701087609', updateTime=1793011176900, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321547918390178721, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321547918390178722, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1293, endPage=1300, ext={EN=ArticleExt(id=1321169575304085785, articleId=1321169575077593368, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Prevalence and influencing factors of occupational stress among ride-hailing drivers in a megacity: a cross-sectional study, columnId=1321169498275689409, journalTitle=Chinese Journal of Public Health, columnName=Special Report—Advancing Mental Health and Building Mental Health Care Systems, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the prevalence of occupational stress among ride-hailing drivers in a megacity and analyze its influencing factors.

Methods

From June 2024 to November 2024, a cross-sectional study and convenience sampling were conducted to investigate the occupational stress of ride-hailing drivers in a megacity. A total of 2 687 self-administered questionnaires were ultimately included in the statistical analysis. Binary logistic regression was adopted to analyze the factors influencing occupational stress.

Results

The overall prevalence of occupational stress remained at 53.96% in the megacity, being higher in males (54.38%) than in females (44.04%) (χ2 = 4.51, P = 0.034). The comparison between different age groups showed that the prevalence of occupational stress in the group of 35–44 years old was the highest (59.09%). The factors associated with an increased risk of occupational stress among male participants included age of 35–44 years old (OR = 1.42, 95%CI: 1.06–1.90, P = 0.001), inadequate rest (OR = 1.52, 95%CI: 1.28–1.81, P < 0.001), not consuming fresh vegetables daily (OR=1.38, 95%CI: 1.09–1.75, P = 0.007), daily consumption of sugar-sweetened beverages (OR = 1.22, 95%CI: 1.03–1.45, P = 0.021), and daily consumption of milk or yogurt (OR = 1.31, 95%CI: 1.10–1.56, P = 0.002). The factor associated with a decreased risk of occupational stress among males was consuming ≥ 3 meals per day (OR = 0.61, 95%CI: 0.39–0.95, P = 0.002). The factors associated with an increased risk of occupational stress among female participants were daily tea consumption (OR = 2.29, 95%CI: 1.002–5.23, P = 0.049) and not consuming fresh vegetables daily (OR = 4.56, 95%CI: 1.41–14.72, P = 0.011).

Conclusions

The prevalence of occupational stress among ride-hailing drivers is high, and its influencing factor are age of 35–44 years, inadequate rest, and dietary habits. Preventive measures targeting occupational stress in this population should be implemented.

, authors=Yuqian LI1, Yan DONG1, Jie GAO1, Yun SUN1, Juntong LIU1, Zizi LI2, Yan LIU1, authorsList=Yuqian LI, Yan DONG, Jie GAO, Yun SUN, Juntong LIU, Zizi LI, Yan LIU, authorCompany=null, correspAuthors=Yan LIU, authorNote=null, correspAuthorsNote=
LIU Yan, E-mail:
, copyrightStatement=Copyright © 2025 Chinese Journal of Public Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321169577887777056, articleId=1321169575077593368, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=某超大城市网约车驾驶员职业紧张流行状况及影响因素:一项横断面研究, columnId=1321169498439267267, journalTitle=中国公共卫生, columnName=专题报道——关注心理健康,加强精神卫生服务体系建设, runingTitle=null, highlight=null, articleAbstract=
目的

调查分析某超大城市网约车驾驶员职业紧张流行状况及其影响因素。

方法

于2024年6—11月,采用横断面研究和方便抽样方法,对某超大城市2 687名网约车驾驶员进行自填式问卷调查。采用二元logistic回归方法分析职业紧张的影响因素。

结果

某超大城市网约车驾驶员职业紧张总体检出率为53.96%,其中,男性为54.38%,女性为44.04%;男性检出率高于女性,差异有统计学意义(χ2=4.51,P=0.034)。不同年龄组比较,35~44岁职业紧张检出率最高,为59.09%。年龄35~44岁(OR=1.42,95%CI=1.06~1.90,P=0.001)、休息不充分(OR=1.52,95%CI=1.28~1.81,P<0.001)、不是每天吃新鲜蔬菜(OR=1.38,95%CI=1.09~1.75,P=0.007)、每天喝含糖饮料(OR=1.22,95%CI=1.03~1.45,P=0.021)、每天喝牛奶、酸奶(OR=1.31,95%CI=1.10~1.56,P=0.002)与男性网约车驾驶员职业紧张风险呈正相关联;每日的餐次数≥3顿(OR=0.61,95%CI=0.39~0.95,P=0.002)与男性网约车驾驶员职业紧张风险呈负相关联。每天喝茶(OR=2.29,95%CI=1.002~5.23,P=0.049)、不是每天吃新鲜蔬菜(OR=4.56,95%CI=1.41~14.72,P=0.011)与女性网约车驾驶员职业紧张风险呈正相关联。

结论

某超大城市中网约车驾驶员职业紧张检出率较高,其影响因素为年龄35~44岁、休息是否充分和膳食习惯,应采取措施积极进行干预。

, authors=李裕倩1, 董艳1, 高洁1, 孙赟1, 刘峻通1, 李孜孜2, 刘艳1, *, *, authorsList=李裕倩, 董艳, 高洁, 孙赟, 刘峻通, 李孜孜, 刘艳, authorCompany=null, correspAuthors=刘艳, authorNote=

李裕倩(1988—),助理研究员,博士,研究方向:职业危害

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刘艳,E-mail:
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李裕倩(1988—),助理研究员,博士,研究方向:职业危害

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Public Health Nutrition, 2019, 22(14): 2553-2560., articleTitle=null, refAbstract=null), Reference(id=1321169587970883957, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=28, rfOrder=27, authorNames=null, journalName=null, refType=null, unstructuredReference=王司宇, 顾叶青, 孟革, 等. 乳及乳制品与抑郁症关联的研究进展[J]. 营养学报, 2022, 44(3): 301-307., articleTitle=null, refAbstract=null), Reference(id=1321169588054770038, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=29, rfOrder=28, authorNames=null, journalName=null, refType=null, unstructuredReference=Saghafian F, Hajishafiee M, Rouhani P, et al. Dietary fiber intake, depression, and anxiety: a systematic review and meta-analysis of epidemiologic studies[J]. Nutritional Neuroscience, 2023, 26(2): 108-126., articleTitle=null, refAbstract=null), Reference(id=1321169588155433335, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=30, rfOrder=29, authorNames=null, journalName=null, refType=null, unstructuredReference=Swann O G, Kilpatrick M, Breslin M, et al. Dietary fiber and its associations with depression and inflammation[J]. Nutrition Reviews, 2020, 78(5): 394-411., articleTitle=null, refAbstract=null), Reference(id=1321169588247708024, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=31, rfOrder=30, authorNames=null, journalName=null, refType=null, unstructuredReference=Lai K F, Liu X L, Chan W K V. The benefits of willingness-to-pay-based incentive-driven rider repositioning in ride-hailing systems[C]//Proceedings of the 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Singapore: IEEE, 2023: 632-639., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1321169578126852385, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, xref=1, ext=[AuthorCompanyExt(id=1321169578135240994, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, companyId=1321169578126852385, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology, Beijing 100054, China), AuthorCompanyExt(id=1321169578147823907, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, companyId=1321169578126852385, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1北京市科学技术研究院城市安全与环境科学研究所,北京 100054)]), AuthorCompany(id=1321169578248487204, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, xref=2, ext=[AuthorCompanyExt(id=1321169578261070117, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, companyId=1321169578248487204, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China), AuthorCompanyExt(id=1321169578269458726, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, companyId=1321169578248487204, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2中国疾病预防控制中心营养与健康所,北京 100050)])], figs=[ArticleFig(id=1321169582673477970, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=EN, label=Tab.1, caption=

Workload of participants

, figureFileSmall=null, figureFileBig=null, tableContent=
变量合计(n=2 687)男性(n=2 578)女性(n=109)Z值P值
MP25~P75MP25~P75MP25~P75
年龄/岁45.039.0~50.044.039.0~50.045.041.0~49.01.000.315
BMI/(kg/m2)25.9523.94~28.3425.9524.06~28.3724.2422.27~27.34–4.09<0.001
本工作工龄/年6.03.0~8.06.03.0~8.05.03.0~6.0–4.37<0.001
每日工作时长/h12.011.0~14.012.011.0~14.012.010.0~14.0–2.630.009
每日接单量/单15.010.0~18.015.010.0~18.015.010.0~16.0–1.230.217
每日工间休息次数2.01.0~3.02.01.0~3.02.01.0~3.0–0.390.700
工间休息时长/min20.020.0~30.020.020.0~30.020.020.0~30.00.770.441
每周工时/d6.06.0~7.06.06.0~7.06.05.0~6.0–5.23<0.001
), ArticleFig(id=1321169582757364051, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=CN, label=表1, caption=

调查对象工作量等调查结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量合计(n=2 687)男性(n=2 578)女性(n=109)Z值P值
MP25~P75MP25~P75MP25~P75
年龄/岁45.039.0~50.044.039.0~50.045.041.0~49.01.000.315
BMI/(kg/m2)25.9523.94~28.3425.9524.06~28.3724.2422.27~27.34–4.09<0.001
本工作工龄/年6.03.0~8.06.03.0~8.05.03.0~6.0–4.37<0.001
每日工作时长/h12.011.0~14.012.011.0~14.012.010.0~14.0–2.630.009
每日接单量/单15.010.0~18.015.010.0~18.015.010.0~16.0–1.230.217
每日工间休息次数2.01.0~3.02.01.0~3.02.01.0~3.0–0.390.700
工间休息时长/min20.020.0~30.020.020.0~30.020.020.0~30.00.770.441
每周工时/d6.06.0~7.06.06.0~7.06.05.0~6.0–5.23<0.001
), ArticleFig(id=1321169582853833044, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=EN, label=Tab.2, caption=

Distribution of participants with different characteristics

, figureFileSmall=null, figureFileBig=null, tableContent=
特征合计(n=2 687)男性(n=2 578)女性(n=109)χ2值P值
调查人数占比/%调查人数占比/%调查人数占比/%
年龄/岁4.690.096
 <352459.122409.3154.59
 35~441 09540.751 05540.924036.70
 >451 34750.131 28349.776458.71
婚姻状况0.980.612
 已婚2 41589.882 31989.959688.07
 未婚1094.061054.0743.67
 离异/丧偶1636.071545.9798.26
家庭人均可支配月收入/元8.870.012
 ≤5 5001 68062.521 62362.965752.29
 5 501~13 00077728.9274228.783532.11
 ≥13 0012308.562138.261715.60
文化程度3.050.384
 初中及以下76628.5173628.553027.52
 高中(含中专)1 19644.511 15244.694440.37
 大专54320.2151419.942926.61
 本科及以上1826.771766.8365.50
吸烟状况133.30<0.001
 从不吸烟1 04638.9394636.7010091.74
 吸烟//既往吸烟1 64161.071 63263.3098.26
饮酒状况109.16<0.001
 从不饮酒76528.4768626.617972.48
 饮酒1 65561.591 62663.072926.61
 已戒酒2679.9426610.3210.92
下班后是否锻炼3.440.179
 从不锻炼1 03538.5298438.175146.79
 1~2次/周1 31849.051 27349.384541.28
 ≥3次/周33412.4332112.451311.93
每天吃新鲜蔬菜0.080.774
 是2 24183.402 14983.369284.40
 否44616.6042916.641715.60
每天吃新鲜水果6.560.010
 是1 92871.751 83871.309082.57
 否75928.2574028.701917.43
每天吃禽肉、畜肉0.700.402
 是2 10778.412 01878.288981.65
 否58021.5956021.722018.35
每天喝含糖饮料0.010.917
 是97436.2593536.273935.78
 否1 71363.751 64363.737064.22
每天喝茶1.300.254
 是1 62660.511 58361.406155.96
 否1 06139.4999538.604844.04
每周吃鱼虾1.020.313
 是1 64461.181 55560.327165.14
 否1 04338.821 02339.683834.86
每天吃蛋类2.270.132
 是1 92471.601 83971.338577.98
 否76328.4073928.672422.02
每天喝牛奶/酸奶16.00<0.001
 是1 08340.311 01939.536458.72
 否1 60459.691 55960.474541.28
每天餐次/顿1.660.436
 <21104.091034.0076.42
 21 07439.971 03039.954440.37
 ≥31 50355.941 44556.055853.21
外出就餐情况2.950.229
 不外出就餐或少于一半餐次在外就餐76828.5872928.283935.78
 包括或超过一半餐次在外就餐99036.8495537.043532.11
 全部在外就餐92934.5789434.683532.11
每天是否规律进餐1.110.291
 是1 34650.091 28649.886055.05
 否1 34149.911 29250.124944.95
每周>8 h工作日数18.09<0.001
 几乎每天2 25683.962 18084.567669.72
 每周2~3日33012.2830311.752724.77
 偶尔1次/从不1013.76953.6965.50
休息是否充分5.090.024
 是1 59459.321 51858.887669.72
 否1 09340.681 06041.123330.28
), ArticleFig(id=1321169583000633685, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=CN, label=表2, caption=

不同调查对象分布情况

, figureFileSmall=null, figureFileBig=null, tableContent=
特征合计(n=2 687)男性(n=2 578)女性(n=109)χ2值P值
调查人数占比/%调查人数占比/%调查人数占比/%
年龄/岁4.690.096
 <352459.122409.3154.59
 35~441 09540.751 05540.924036.70
 >451 34750.131 28349.776458.71
婚姻状况0.980.612
 已婚2 41589.882 31989.959688.07
 未婚1094.061054.0743.67
 离异/丧偶1636.071545.9798.26
家庭人均可支配月收入/元8.870.012
 ≤5 5001 68062.521 62362.965752.29
 5 501~13 00077728.9274228.783532.11
 ≥13 0012308.562138.261715.60
文化程度3.050.384
 初中及以下76628.5173628.553027.52
 高中(含中专)1 19644.511 15244.694440.37
 大专54320.2151419.942926.61
 本科及以上1826.771766.8365.50
吸烟状况133.30<0.001
 从不吸烟1 04638.9394636.7010091.74
 吸烟//既往吸烟1 64161.071 63263.3098.26
饮酒状况109.16<0.001
 从不饮酒76528.4768626.617972.48
 饮酒1 65561.591 62663.072926.61
 已戒酒2679.9426610.3210.92
下班后是否锻炼3.440.179
 从不锻炼1 03538.5298438.175146.79
 1~2次/周1 31849.051 27349.384541.28
 ≥3次/周33412.4332112.451311.93
每天吃新鲜蔬菜0.080.774
 是2 24183.402 14983.369284.40
 否44616.6042916.641715.60
每天吃新鲜水果6.560.010
 是1 92871.751 83871.309082.57
 否75928.2574028.701917.43
每天吃禽肉、畜肉0.700.402
 是2 10778.412 01878.288981.65
 否58021.5956021.722018.35
每天喝含糖饮料0.010.917
 是97436.2593536.273935.78
 否1 71363.751 64363.737064.22
每天喝茶1.300.254
 是1 62660.511 58361.406155.96
 否1 06139.4999538.604844.04
每周吃鱼虾1.020.313
 是1 64461.181 55560.327165.14
 否1 04338.821 02339.683834.86
每天吃蛋类2.270.132
 是1 92471.601 83971.338577.98
 否76328.4073928.672422.02
每天喝牛奶/酸奶16.00<0.001
 是1 08340.311 01939.536458.72
 否1 60459.691 55960.474541.28
每天餐次/顿1.660.436
 <21104.091034.0076.42
 21 07439.971 03039.954440.37
 ≥31 50355.941 44556.055853.21
外出就餐情况2.950.229
 不外出就餐或少于一半餐次在外就餐76828.5872928.283935.78
 包括或超过一半餐次在外就餐99036.8495537.043532.11
 全部在外就餐92934.5789434.683532.11
每天是否规律进餐1.110.291
 是1 34650.091 28649.886055.05
 否1 34149.911 29250.124944.95
每周>8 h工作日数18.09<0.001
 几乎每天2 25683.962 18084.567669.72
 每周2~3日33012.2830311.752724.77
 偶尔1次/从不1013.76953.6965.50
休息是否充分5.090.024
 是1 59459.321 51858.887669.72
 否1 09340.681 06041.123330.28
), ArticleFig(id=1321169583134851414, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=EN, label=Tab.3, caption=

Prevalence of occupational stress among participants with different characteristics

, figureFileSmall=null, figureFileBig=null, tableContent=
特征合计(n=2 687)男性(n=2 578)女性(n=109)
检出人数检出率/%检出人数检出率/%检出人数检出率(%)
年龄/岁
 <3512952.6512752.92240.00
 35~4464759.0962959.621845.00
 >4567450.0464650.352843.75
  χ2值20.1020.28
  P值<0.000 1<0.000 11.00f
餐次/(顿/天)
 <27467.276966.99571.43
 263158.7561459.611738.64
 ≥374549.5771949.762644.83
  χ2值29.4530.412.67
  P值<0.000 1<0.000 10.26
休息是否充分
 是77648.6874348.953343.42
 否67461.6765962.171545.45
  χ2值43.9944.000.04
  P值<0.000 1<0.000 10.84
是否每天吃新鲜蔬菜
 是1 16151.811 12552.353639.13
 否28964.8027764.571270.59
  χ2值25.2721.525.76
  P值<0.000 1<0.000 10.02
每天喝含糖饮料
 是56457.9154658.401846.15
 否88651.7285652.103042.86
  χ2值9.569.520.11
  P值<0.01<0.010.74
是否每天喝茶
 是88253.6585153.763150.82
 否56854.4655155.381735.42
  χ2值0.170.642.59
  P值0.680.420.11
是否每天喝牛奶、酸奶

 是58754.2056155.052640.63
 否86353.8084153.942248.89
  χ2值0.040.310.73
  P值0.840.580.39
合计1 45053.961 40254.384844.04
), ArticleFig(id=1321169583239709015, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=CN, label=表3, caption=

不同特征调查对象职业紧张检出情况

, figureFileSmall=null, figureFileBig=null, tableContent=
特征合计(n=2 687)男性(n=2 578)女性(n=109)
检出人数检出率/%检出人数检出率/%检出人数检出率(%)
年龄/岁
 <3512952.6512752.92240.00
 35~4464759.0962959.621845.00
 >4567450.0464650.352843.75
  χ2值20.1020.28
  P值<0.000 1<0.000 11.00f
餐次/(顿/天)
 <27467.276966.99571.43
 263158.7561459.611738.64
 ≥374549.5771949.762644.83
  χ2值29.4530.412.67
  P值<0.000 1<0.000 10.26
休息是否充分
 是77648.6874348.953343.42
 否67461.6765962.171545.45
  χ2值43.9944.000.04
  P值<0.000 1<0.000 10.84
是否每天吃新鲜蔬菜
 是1 16151.811 12552.353639.13
 否28964.8027764.571270.59
  χ2值25.2721.525.76
  P值<0.000 1<0.000 10.02
每天喝含糖饮料
 是56457.9154658.401846.15
 否88651.7285652.103042.86
  χ2值9.569.520.11
  P值<0.01<0.010.74
是否每天喝茶
 是88253.6585153.763150.82
 否56854.4655155.381735.42
  χ2值0.170.642.59
  P值0.680.420.11
是否每天喝牛奶、酸奶

 是58754.2056155.052640.63
 否86353.8084153.942248.89
  χ2值0.040.310.73
  P值0.840.580.39
合计1 45053.961 40254.384844.04
), ArticleFig(id=1321169583336178008, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=EN, label=Tab.4, caption=

Multivariate logistics regression results of occupational stress among participants with different characteristics

, figureFileSmall=null, figureFileBig=null, tableContent=
变量对照组参照组β $ S_{\overline{x}} $Wald χ2值P值OR值95%CI
男性
 年龄/岁35~44<350.210.0610.440.0011.421.06~1.90
>45–0.060.061.030.3101.080.81~1.44
 餐次/(顿/天)2<20.040.080.230.6290.830.54~1.29
≥3–0.270.099.310.0020.610.39~0.95
 休息是否充分否是0.210.0422.77<0.000 11.521.28~1.81
 是否每天吃新鲜蔬菜否是0.160.067.230.0071.381.09~1.75
 每天喝含糖饮料是否0.100.045.360.0211.221.03~1.45
 每天喝牛奶、酸奶是否0.140.049.340.0021.311.10~1.56
女性
 是否每天吃新鲜蔬菜否是0.760.306.450.0114.561.41~14.72
 是否每天喝茶是否0.410.213.860.0492.291.002~5.23
), ArticleFig(id=1321169583428452697, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169575077593368, language=CN, label=表4, caption=

调查对象职业紧张多因素logistic回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量对照组参照组β $ S_{\overline{x}} $Wald χ2值P值OR值95%CI
男性
 年龄/岁35~44<350.210.0610.440.0011.421.06~1.90
>45–0.060.061.030.3101.080.81~1.44
 餐次/(顿/天)2<20.040.080.230.6290.830.54~1.29
≥3–0.270.099.310.0020.610.39~0.95
 休息是否充分否是0.210.0422.77<0.000 11.521.28~1.81
 是否每天吃新鲜蔬菜否是0.160.067.230.0071.381.09~1.75
 每天喝含糖饮料是否0.100.045.360.0211.221.03~1.45
 每天喝牛奶、酸奶是否0.140.049.340.0021.311.10~1.56
女性
 是否每天吃新鲜蔬菜否是0.760.306.450.0114.561.41~14.72
 是否每天喝茶是否0.410.213.860.0492.291.002~5.23
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某超大城市网约车驾驶员职业紧张流行状况及影响因素:一项横断面研究
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李裕倩 1 , 董艳 1 , 高洁 1 , 孙赟 1 , 刘峻通 1 , 李孜孜 2 , 刘艳 1, *, *
中国公共卫生 | 专题报道——关注心理健康,加强精神卫生服务体系建设 2025,41(11): 1293-1300
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中国公共卫生 |专题报道——关注心理健康,加强精神卫生服务体系建设 2025 , 41 (11) : 1293 -1300
某超大城市网约车驾驶员职业紧张流行状况及影响因素:一项横断面研究
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李裕倩1, 董艳1, 高洁1, 孙赟1, 刘峻通1, 李孜孜2, 刘艳1, *, *
作者信息
  • 1北京市科学技术研究院城市安全与环境科学研究所,北京 100054
  • 2中国疾病预防控制中心营养与健康所,北京 100050
通讯作者:
刘艳,E-mail:
作者简介:

李裕倩(1988—),助理研究员,博士,研究方向:职业危害

Prevalence and influencing factors of occupational stress among ride-hailing drivers in a megacity: a cross-sectional study
Yuqian LI1, Yan DONG1, Jie GAO1, Yun SUN1, Juntong LIU1, Zizi LI2, Yan LIU1
Affiliations
  • 1Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology, Beijing 100054, China
  • 2National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
  • Corresponding Author:
    LIU Yan, E-mail:
出版时间: 2025-11-10 doi: 10.11847/zgggws1147417
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目的

调查分析某超大城市网约车驾驶员职业紧张流行状况及其影响因素。

方法

于2024年6—11月,采用横断面研究和方便抽样方法,对某超大城市2 687名网约车驾驶员进行自填式问卷调查。采用二元logistic回归方法分析职业紧张的影响因素。

结果

某超大城市网约车驾驶员职业紧张总体检出率为53.96%,其中,男性为54.38%,女性为44.04%;男性检出率高于女性,差异有统计学意义(χ2=4.51,P=0.034)。不同年龄组比较,35~44岁职业紧张检出率最高,为59.09%。年龄35~44岁(OR=1.42,95%CI=1.06~1.90,P=0.001)、休息不充分(OR=1.52,95%CI=1.28~1.81,P<0.001)、不是每天吃新鲜蔬菜(OR=1.38,95%CI=1.09~1.75,P=0.007)、每天喝含糖饮料(OR=1.22,95%CI=1.03~1.45,P=0.021)、每天喝牛奶、酸奶(OR=1.31,95%CI=1.10~1.56,P=0.002)与男性网约车驾驶员职业紧张风险呈正相关联;每日的餐次数≥3顿(OR=0.61,95%CI=0.39~0.95,P=0.002)与男性网约车驾驶员职业紧张风险呈负相关联。每天喝茶(OR=2.29,95%CI=1.002~5.23,P=0.049)、不是每天吃新鲜蔬菜(OR=4.56,95%CI=1.41~14.72,P=0.011)与女性网约车驾驶员职业紧张风险呈正相关联。

结论

某超大城市中网约车驾驶员职业紧张检出率较高,其影响因素为年龄35~44岁、休息是否充分和膳食习惯,应采取措施积极进行干预。

职业紧张  /  网约车驾驶员  /  超大城市  /  影响因素
Objective

To investigate the prevalence of occupational stress among ride-hailing drivers in a megacity and analyze its influencing factors.

Methods

From June 2024 to November 2024, a cross-sectional study and convenience sampling were conducted to investigate the occupational stress of ride-hailing drivers in a megacity. A total of 2 687 self-administered questionnaires were ultimately included in the statistical analysis. Binary logistic regression was adopted to analyze the factors influencing occupational stress.

Results

The overall prevalence of occupational stress remained at 53.96% in the megacity, being higher in males (54.38%) than in females (44.04%) (χ2 = 4.51, P = 0.034). The comparison between different age groups showed that the prevalence of occupational stress in the group of 35–44 years old was the highest (59.09%). The factors associated with an increased risk of occupational stress among male participants included age of 35–44 years old (OR = 1.42, 95%CI: 1.06–1.90, P = 0.001), inadequate rest (OR = 1.52, 95%CI: 1.28–1.81, P < 0.001), not consuming fresh vegetables daily (OR=1.38, 95%CI: 1.09–1.75, P = 0.007), daily consumption of sugar-sweetened beverages (OR = 1.22, 95%CI: 1.03–1.45, P = 0.021), and daily consumption of milk or yogurt (OR = 1.31, 95%CI: 1.10–1.56, P = 0.002). The factor associated with a decreased risk of occupational stress among males was consuming ≥ 3 meals per day (OR = 0.61, 95%CI: 0.39–0.95, P = 0.002). The factors associated with an increased risk of occupational stress among female participants were daily tea consumption (OR = 2.29, 95%CI: 1.002–5.23, P = 0.049) and not consuming fresh vegetables daily (OR = 4.56, 95%CI: 1.41–14.72, P = 0.011).

Conclusions

The prevalence of occupational stress among ride-hailing drivers is high, and its influencing factor are age of 35–44 years, inadequate rest, and dietary habits. Preventive measures targeting occupational stress in this population should be implemented.

occupational stress  /  ride-hailing drivers  /  megacity  /  influencing factor
李裕倩, 董艳, 高洁, 孙赟, 刘峻通, 李孜孜, 刘艳. 某超大城市网约车驾驶员职业紧张流行状况及影响因素:一项横断面研究. 中国公共卫生, 2025 , 41 (11) : 1293 -1300 . DOI: 10.11847/zgggws1147417
Yuqian LI, Yan DONG, Jie GAO, Yun SUN, Juntong LIU, Zizi LI, Yan LIU. Prevalence and influencing factors of occupational stress among ride-hailing drivers in a megacity: a cross-sectional study[J]. Chinese Journal of Public Health, 2025 , 41 (11) : 1293 -1300 . DOI: 10.11847/zgggws1147417
网约车驾驶员是指通过网络预约平台提供运输服务的驾驶员,是新就业形态劳动者的一种。该职业是伴随着互联网技术应用和数字经济发展而出现的工作模式,因其工作时间弹性大等优势,吸纳了大量劳动者就业。据交通运输部统计,截至2024年10月31日,我国各地共发放网约车驾驶员证748.3万本[1]。在带动就业、改善居民出行体验的同时,网约车驾驶员的健康问题也逐渐显现。据某网约车平台2023年发布的《网约车司机职业健康调研报告》显示,网约车驾驶员面临工作时间长、长期疲劳驾驶、饮食不规律、多种慢性病共存等问题[2–3],网约车驾驶员的身心健康状况逐渐引起社会的关注。职业紧张又称职业应激、工作压力,是指个体所在工作岗位的要求与个人能力、资源或需求不匹配时出现的生理和心理反应[4]。既往研究表明,职业紧张与焦虑、抑郁等心理疾病及高血压、冠状动脉病变、血脂异常等心血管系统疾病有较强的相关性[5]。研究显示,出租车驾驶员群体已经出现不同程度的职业紧张问题,且其职业紧张的流行在我国普遍存在[6–7]。在Marín-Berges M等[8]纳入11项研究的系统综述显示,19%~55%的网约车驾驶员存在职业紧张,其影响因素包括遭受歧视、吸烟、语言能力弱、睡眠障碍等。驾驶员的职业紧张状态不仅影响其自身的健康状况,同时也会因为“溢出效应”影响驾驶安全,并可能导致交通事故的发生[9]。本研究旨在分析某超大城市网约车驾驶员职业紧张现状及影响因素,为提出针对性的干预措施,保护和促进网约车驾驶员的身心健康提供科学依据。
于2024年6—11月,采用方便抽样方法,将问卷星调查问卷推送给某超大城市的网约车平台公司,由网约车平台公司管理人员将问卷推送给公司的驾驶人员。纳入标准:网约车驾驶员工龄>1年。排除标准:已被专业的医疗机构诊断为抑郁症等其他心理疾患。参考已有的研究中,出租车司机的职业紧张检出率为19%~55%[8]。根据横断面研究样本量公式:
$ n=\dfrac{\text{z}_{\alpha /2}^{2}}{{\varepsilon}^{2}P} \times (1-P)$
取相对误差ε=10%,置信水平1–α=95%,z0.05/2=1.96,分别带入P=19%和P=55%到公式中进行计算。本研究的样本量为315~1 537人。回收问卷3 723份,去除含无效数据以及不符合纳入标准的问卷,最终纳入统计分析的问卷2 687份,有效问卷回收率为72.1%,样本量能够满足分析要求。本研究获得北京市科学技术研究院城市安全与环境科学研究所伦理委员会审查批准(2024–0421JJ)。所有调查对象均知情同意。
结合王瑾等[10]编制的《中国职业人群职业紧张测量核心量表》及自编基本信息调查问卷,编制本研究使用的网约车驾驶员职业紧张问卷。调查问卷采用电子问卷的形式,利用互联网调查研究工具“问卷星”制作。将问卷星调查问卷推送给某超大城市的网约车平台公司,由网约车平台公司管理人员将问卷推送给公司注册的驾驶人员。问卷主要内容包括:一般情况、职业紧张问卷、职业特征3部分。一般情况包括年龄、身高、体重、自报是否患有心脏病、高血压、糖尿病,自报是否吸烟、饮酒,以及下班后体育锻炼情况、饮食习惯等。职业紧张问卷采用王瑾等[10]编制“中国职业人群职业紧张测量核心量表”(Core Occupational Stress Scale, COSS)。该量表用于评估调查对象的职业紧张状况,包括社会支持(5个条目)、组织与回报(6个条目)、要求与付出(4个条目)、自主性(2个条目)共4个维度17个条目,每个条目为5级评价,1、2、3、4和5分分别代表完全不同意、不同意、基本同意、同意和完全同意。其中,组织与回报(6个条目)与要求与付出(4个条目)采取正向记分,各级选项的得分分别记为1、2、3、4、5分;社会支持和自主性2个维度条目的题目反向记分,各级选项的得分分别记为5、4、3、2、1分。量表总分为17~85分,总分越高表明职业紧张程度越严重。COSS总体及各维度分量表Cronbach′s α系数为0.772~0.896,显示该量表具有较好的信度。COSS经过结构效度、校标效度、聚合效度检验,显示量表具有较好的效度。本研究中,调查对象职业紧张量表评分≥50分判断为职业紧张检出[11]。经计算,本次调查问卷信效度指标Cronbach′s α系数为0.702 2。职业特征包括:本岗位工龄、每日工作时长、每日订单数、从事本工作年限(工龄)、每日工作时长(h)、每日接单量、每日工间休息次数、工间休息时长(min)、每周工时(d),以及调查对象自报的下班后疲惫状况、休息是否充分等。某特征人群的职业紧张检出率=某特征人群中职业紧张的检出人数/该特征人群的总人数×100%。体质量指数(body mass index, BMI)=体重(kg)/[身高(m)]2。
本研究使用“问卷星”创建、发放和回收问卷。问卷中备注说明填写要点与注意事项,电子版调查问卷有完整性检查功能,未填写完整的问卷不能提交。问卷在发放前向所有调查对象说明了调查人员的联系方式,以便调查对象有疑问时能够进行解答。在问卷填写完成后,项目工作组对问卷进行逻辑性检查,排除内容不符合逻辑及不符合纳入标准的问卷。
电子问卷导出数据库,采用SAS 9.4软件进行分析。计量资料经正态性检验,若符合正态分布,以$ \overline{x}\pm s $描述;若不符合正态分布,以四分位间距即M(P25~P75)描述。非正态分布的连续变量2组间差异比较采用秩和检验。计数资料以频数(构成比)描述,率的比较采用χ2检验;若某一特征的调查对象人数<5人,则采用fisher精确检验法计算P值。以调查对象是否检出职业紧张为应变量,进行多因素二元logistic回归分析。分析前对各自变量进行多重共线性诊断,采用Proc Reg程序步,计算方差膨胀因子和条件指数。检验水准为α=0.05。本研究进行logistic回归分析前对各相关自变量进行多重共线性诊断。结果显示,各自变量方差膨胀因子均<2,各变量条件指数均<4,各变量间的多重共线性程度不高[12],可以应用logistic回归对各自变量进行分析。
网约车驾驶员年龄为45.0(39.0~50.0)岁,BMI为25.95(23.94~28.34)kg/m2,本工作工龄为6.0(3.0~8.0)年,每日工作时长12.0(11.0~14.0)h,每日接单量15.0 (10.0~18.0)单,每日工间休息2.0(1.0~3.0)次,工间休息时长20.0(20.0~30.0)min,每周工时6.0(6.0~7.0)d。男性与女性网约车驾驶员在BMI、本工作工龄、每日工作时长、每周工时方面差异均有统计学意义(均P<0.05)。
调查对象男性2 578人,占95.94%;女性109人,占4.06%。男性与女性调查对象在家庭人均可支配月收入、吸烟、饮酒、每日的水果消费、每日的酸奶/牛奶消费、1周>8 h工作日数、休息是否充分方面差异均有统计学意义(均P<0.05)。
调查对象职业紧张检出人数1 450人,检出率为53.96%,其中男性1 402人,检出率为54.38%;女性48人,检出率为44.04%,男性检出率高于女性,差异有统计学意义(χ2=4.51, P=0.034)。不同年龄组比较,35~44岁的调查对象职业紧张检出率最高,为59.09%。进一步分析可见,自报休息充足的调查对象职业紧张检出率为48.68%,低于自报休息不充分的调查对象(χ2=43.99, P<0.001);每天吃新鲜蔬菜的调查对象职业紧张的检出率为51.81%,低于不每天吃新鲜蔬菜的调查对象(χ2=25.27, P<0.001);每天喝含糖饮料的调查对象职业紧张的检出率为57.91%,高于不每天喝含糖饮料的调查对象(χ2=9.56, P=0.002)。
男性调查对象职业紧张风险上升相关因素包括,年龄35~44岁(OR=1.42,95%CI=1.06~1.90,P=0.001),休息不充分(OR=1.52,95%CI=1.28~1.81,P<0.000 1),不是每天吃新鲜蔬菜(OR=1.38,95%CI=1.09~1.75,P=0.007),每天喝含糖饮料(OR=1.22,95%CI=1.03~1.45,P=0.021)、每天喝牛奶、酸奶(OR=1.31,95%CI=1.10~1.56,P=0.002)。男性职业紧张风险下降相关因素为每日餐次数≥3顿(OR=0.61,95%CI=0.39~0.95,P=0.002)。女性调查对象职业紧张风险上升相关因素包括每天喝茶(OR=2.29,95%CI=1.002~5.23,P=0.049),不是每天吃新鲜蔬菜(OR=4.56,95%CI=1.41~14.72,P=0.011)。
本研究中某超大城市网约车驾驶员的职业紧张检出率为53.96%,与王瑾等[10]编制《中国职业人群职业紧张测量核心量表》且判别标准相同的其他研究比较,本研究中某超大城市网约车驾驶员的职业紧张流行状况高于其他职业[13–18]。在刘啸文等[13]的研究中,江苏省公路交通驾驶员职业紧张检出率为23.97%;刘丹等[18]的研究中,北京市中小学教师的职业紧张检出率为16.66%;李晓艺等[19]的研究中,广东省制造业员工的职业紧张检出率为31.90%。由此可见,某超大城市网约车驾驶员的职业紧张检出率处于较高水平。在国外开展的关于出租车驾驶员的职业紧张相关研究结果显示,美国纽约的出租车驾驶员职业紧张检出率较高,为55%,澳大利亚墨尔本的出租车驾驶员职业紧张检出率较低,为19%[8]。本研究推测,不同城市出租车驾驶员职业紧张检出率的差异或与城市交通状况的复杂情况以及更高的工作要求相关,即城市的交通状况越复杂、乘客对出租车驾驶员的工作要求越高,出租车驾驶员的职业紧张情况越严重,这也可以部分解释本研究中超大城市网约车驾驶员较高的职业紧张检出情况。苏禹等[20]的研究结果显示,职业紧张与抑郁症状、焦虑症状、低生活满意度、失眠症状、疲劳蓄积程度与肌肉骨骼疾患的检出风险增加相关,网约车驾驶员的职业紧张问题应该引起重视。
本研究结果显示,职业紧张风险上升相关因素包括年龄35~44岁、休息不充分及膳食习惯因素。一项纳入2 010名网约车驾驶员现状调查研究显示,北京市46.57%的网约车驾驶员表示每天工作时间>8 h;超过一半的网约车驾驶员表示每个月休息时间≤5 d;22.59%的网约车驾驶员表示每个月休息<4 d,周末只休息一天都难以保证[21]。8%的网约车驾驶员每天出车时间<8 h,出车>12 h的人群比例超过总体的1/3[22]。这些数据反映了超时工作是网约车驾驶员的工作常态,而这与网约车驾驶员的提成制“收入模式”密不可分,他们倾向于接受高强度的工作换取更高的收入[23]。对此,网约车平台推出了防范疲劳驾驶工作方案。例如,司机服务时长达到4 h以后,平台会强制休息20 min;当天计费时长达到10 h,平台会强制司机休息6 h。然而实际情况是1名司机往往同时注册几个平台,这样就可以利用某个平台强制休息的“空窗期”,在别的平台继续接单[24]。这种现象可能解释在本研究中40.68%的调查对象感觉休息并不充足。关于年龄对职业紧张的影响,或用“中年危机”这个概念解释更为合理,即人在40岁会经历身体、心理、家庭、职业发展上的瓶颈期,这些都会影响网约车驾驶员的心理状态[25]。
本研究显示,网约车驾驶员的食物消费与职业紧张之间存在关联。如每天喝含糖饮料、每天喝牛奶/酸奶、每天喝茶、不是每天吃新鲜蔬菜与职业紧张风险的上升呈正相关。目前,关于职业紧张与食物消费的相关性研究并不多见,但是由于本研究采用的量表与抑郁症状呈正相关[10],抑郁与食物消费的研究或可解释职业紧张与食物消费之间的关系。在Meyer B J[26] 的研究中显示,摄入蔬菜较多的调查对象与患抑郁症的风险降低相关,而较多摄入奶及奶制品、非酒精性饮料的调查对象患抑郁症的风险升高,与本研究结果相似。Zhang X Y[27]的研究认为,含糖饮料和焦虑、抑郁之间的联系可能与含糖饮料造成内皮功能障碍或更高水平的炎症有关。但乳制品消费与抑郁症的关系仍较为模糊,存在一定争议[28]。这可能是因为乳制品的种类多,如按照脂肪含量的不同,乳制品可以分为全脂、低脂或者脱脂;按照糖添加可分为含糖、无糖、代糖。若在调查研究中没有进行区分,这可能会成为乳制品消费与抑郁相关关系探索的混杂因素。Saghafian F[29]在纳入18篇研究的荟萃分析中显示,膳食纤维摄入是成年人抑郁的保护因素,并且总膳食纤维摄入量每增加5 g,抑郁症发病风险降低5%(OR=0.95,95%CI=0.94~0.97),其中的机制可能是高纤维饮食改变肠道的pH值、渗透性从而降低炎症,而炎症化合物的减少改变神经递质的浓度,从而减轻了抑郁症的症状[30]。
综上所述,年龄35~44岁、休息不充分、不是每天吃新鲜蔬菜、每天喝含糖饮料、每天喝牛奶/酸奶以及每天喝茶是超大城市网约车驾驶员职业紧张风险上升的相关因素。建议网约车平台和交通运输管理部门重视网约车驾驶员的职业紧张状况,对网约车驾驶员开展有针对性的职业健康教育和心理辅导。除此之外,建议网约车平台优化平台算法,合理分配工作任务与劳动报酬,确保消费者、劳动者、平台三方利益的共赢[31]。当然,网约车驾驶员要树立“健康第一责任人”信念,规划健康生活,主动寻求帮助。
本研究仍存在局限性:(1)本研究对调查对象食物消费的调查未采用食物频率法,这对食物消费与调查对象职业紧张之间的量效关系无法判断。(2)由于网约车驾驶员职业的流动性特点,只能通过网络调查工具“问卷星”问卷收集匿名问卷,无法进行重复测量的信效度检验。

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2025年第41卷第11期
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doi: 10.11847/zgggws1147417
  • 接收时间:2025-03-17
  • 首发时间:2026-10-25
  • 出版时间:2025-11-10
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  • 收稿日期:2025-03-17
  • 修回日期:2025-07-14
  • 录用日期:2025-09-15
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    1北京市科学技术研究院城市安全与环境科学研究所,北京 100054
    2中国疾病预防控制中心营养与健康所,北京 100050

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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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