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Article(id=1325520829886366257, tenantId=1146029695717560320, journalId=1256213402557890569, issueId=1325520723858568134, articleNumber=null, orderNo=null, doi=10.16835/j.cnki.1000-9817.2025186, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739462400000, receivedDateStr=2025-02-14, revisedDate=1748793600000, revisedDateStr=2025-06-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1793958392830, onlineDateStr=2026-11-06, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793958392830, onlineIssueDateStr=2026-11-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793958392830, creator=13701087609, updateTime=1793958392830, updator=13701087609, issue=Issue{id=1325520723858568134, tenantId=1146029695717560320, journalId=1256213402557890569, year='2025', volume='46', issue='6', pageStart='761', pageEnd='912', issueExtLink='null', onlineDate='null', pubDate='1750780800000', pubDateStr='2025-06-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793958367551, creator='13701087609', updateTime=1793958367551, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=847, endPage=851, ext={EN=ArticleExt(id=1325520830062527026, articleId=1325520829886366257, tenantId=1146029695717560320, journalId=1256213402557890569, language=EN, title=Association between physical activity and inflammatory markers in college students, columnId=1325500884406379444, journalTitle=Chinese Journal of School Health, columnName=Disease Control, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the association and dose-response relationship between physical activity and inflammatory markers in college students, so as to provide a reference for promoting cardiometabolic health in college students.

Methods

A cluster random sampling method was used to select 747 college students from two universities in Hefei, Anhui Province and Shangrao, Jiangxi Province from April to May 2019. Physical activity was assessed by using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and peripheral blood was collected to detect plasma inflammatory factor levels [including hypersensitive C-reactive protein (hsCRP), interleukin-10 (IL-10), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)]. The differences between the groups were compared by using the χ2 test and the Kruskal-Wallis rank sum test, and the association between physical activity and inflammatory markers was analyzed by using the Generalized Linear Model. The dose-response relationship between physical activity and inflammatory markers was analyzed using the Restricted Cubic Spline Model.

Results

The proportions of low physical activity, moderate physical activity, and high physical activity groups of college students were 15.9%, 53.7% and 30.4%, respectively. The levels of hsCRP, IL-10, IL-1β, IL-6 and TNF-α in the high physical activity group were 0.38(0.21, 1.10)mg/L, 70.74(47.90, 116.43)pg/mL, 1.75(1.21, 2.64)pg/mL, 4.33(2.93, 6.82)pg/mL, 5.27(3.89, 7.30)pg/mL, the levels in the low physical activity group were 0.80(0.31, 1.30)mg/L, 73.88(47.90, 124.24)pg/mL, 1.88(1.42, 2.81) pg/mL, 4.82 (3.64, 6.67) pg/mL, 5.63 (4.34, 7.62)pg/mL, the levels in the moderate physical activity group were 0.63(0.25, 1.30)mg/L, 89.78(58.21, 127.65)pg/mL, 2.21(1.59, 3.27)pg/mL, 5.15(3.72, 7.72)pg/mL, 5.87(4.63, 8.00)g/mL, and the differences were statistically significant (H=10.66, 11.38, 27.79, 14.13, 9.44, P < 0.05). After adjusting for variables such as gender, body mass index, smoking, alcohol consumption and health status, the results of Generalized Linear Model showed that compared with the high physical activity group, the low physical activity group (OR=2.20, 95%CI=1.46-3.31) and the moderate physical activity group (OR=1.65, 95%CI=1.22-2.25) were more likely to have high levels of hsCRP, and the moderate physical activity group was more likely to have high levels of IL-1β (OR=1.85, 95%CI=1.36-2.51), IL-6 (OR=1.44, 95%CI=1.06-1.96), and TNF-α (OR=1.43, 95%CI=1.05-1.94) (P < 0.05). The Restricted Cubic Spline Model showed that there was no linear dose-response relationship between the time of moderate-to-vigorous physical activity weekly and IL-10, IL-6, II-1β, and TNF-α (P < 0.05).

Conclusion

There is an association between physical activity and inflammation in college students, and moderate to high intensity per week could reduce inflammation levels to promote cardiometabolic health in college students.

, authors=Tangjun JIANG1, Tingting LI1, Shuman TAO1, 2, Liwei ZOU1, 2, Yajuan YANG1, 2, Fangbiao TAO1, 2, Xiaoyan WU*, 1, 2, authorsList=Tangjun JIANG, Tingting LI, Shuman TAO, Liwei ZOU, Yajuan YANG, Fangbiao TAO, Xiaoyan WU, authorCompany=null, correspAuthors=Xiaoyan WU, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Chinese Journal of School 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=1325520830645535285, articleId=1325520829886366257, tenantId=1146029695717560320, journalId=1256213402557890569, language=CN, title=大学生体力活动与炎症标志物的关联, columnId=1325500884628677558, journalTitle=中国学校卫生, columnName=疾病控制, runingTitle=null, highlight=null, articleAbstract=
目的

分析大学生体力活动与炎症标志物的关联及剂量反应关系，为促进大学生心血管健康提供参考依据。

方法

采用整群随机抽样方法，于2019年4—5月在安徽省合肥市和江西省上饶市2所高校抽取747名大学生，使用国际体力活动问卷—短卷(IPAQ-SF)评估大学生体力活动，同时采集外周血检测血浆炎症因子水平[超敏C反应蛋白(hsCRP)、白介素-10(IL-10)、白介素-1β(IL-1β)、白介素-6(IL-6)、肿瘤坏死因子α(TNF-α)]。使用χ2检验和双侧Kruskal-Wallis秩和检验比较组间差异，采用广义线性模型和限制性立方样条模型分别分析体力活动与炎症标志物的关联及其剂量反应关系。

结果

大学生低、中、高体力活动组的占比分别为15.9%，53.7%，30.4%。hsCRP、IL-10、II-1β、IL-6、TNF-α水平在高体力活动组分别为0.38(0.21，1.10)mg/L，70.74(47.90，116.43)pg/mL，1.75(1.21，2.64)pg/mL，4.33(2.93，6.82)pg/mL，5.27(3.89，7.30)pg/mL；低体力活动组分别为0.80(0.31，1.30)mg/L，73.88(47.90，124.24)pg/mL，1.88(1.42，2.81)pg/mL，4.82(3.64，6.67)pg/mL，5.63(4.34，7.62)pg/mL；中体力活动组分别为0.63(0.25，1.30)mg/L，89.78(58.21，127.65)pg/mL，2.21(1.59，3.27)pg/mL，5.15(3.72，7.72)pg/mL，5.87(4.63，8.00)pg/mL，差异均有统计学意义(H值分别为10.66，11.38，27.79，14.13，9.44，P值均 < 0.05)。广义线性模型结果显示，调整性别、体质量指数、吸烟、饮酒和健康状况等变量后，与高体力活动组相比，低体力活动(OR=2.20，95%CI=1.46~3.31)和中体力活动组(OR=1.65，95%CI=1.22~2.25)出现高水平hsCRP的可能性更高，中体力活动组出现高水平IL-1β(OR=1.85，95%CI=1.36~2.51)、IL-6(OR=1.44，95%CI=1.06~1.96)、TNF-α(OR=1.43，95%CI=1.05~1.94)的可能性更高(P值均 < 0.05)。限制性立方样条模型显示，每周中高强度体力活动时间与IL-10、IL-6、IL-1β和TNF-α之间存在非线性剂量反应关系(P值均 < 0.05)。

结论

大学生体力活动与炎症之间存在关联；中高强度体力活动有助于降低炎症水平，促进大学生心血管代谢健康。

, authors=江唐军1, 李婷婷1, 陶舒曼1, 2, 邹立巍1, 2, 杨娅娟1, 2, 陶芳标1, 2, 伍晓艳*, 1, 2, authorsList=江唐军, 李婷婷, 陶舒曼, 邹立巍, 杨娅娟, 陶芳标, 伍晓艳, authorCompany=null, correspAuthors=伍晓艳, authorNote=

江唐军(1999-)，男，安徽安庆人，在读硕士，主要研究方向为儿童青少年健康

, correspAuthorsNote=
伍晓艳，E-mail:
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江唐军(1999-)，男，安徽安庆人，在读硕士，主要研究方向为儿童青少年健康

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Obesity, insulin resistance, and type 2 diabetes: associations and therapeutic implications[J]. Diabetes Metab Syndr Obes, 2020, 13: 3611-3616., articleTitle=null, refAbstract=null)], funds=[Fund(id=1325520843857592950, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, awardId=null, language=CN, fundingSource=国家自然科学基金项目(82173542，82373592)；安徽医科大学科研水平提升计划资助项目(2022xkjT004), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1325520830872027702, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, xref=1, ext=[AuthorCompanyExt(id=1325520830884610615, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, companyId=1325520830872027702, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei (230032), Anhui Province, China), AuthorCompanyExt(id=1325520830892999224, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, companyId=1325520830872027702, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1安徽医科大学公共卫生学院儿少卫生与妇幼保健学系，合肥 230032)]), AuthorCompany(id=1325520830964302393, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, xref=2, ext=[AuthorCompanyExt(id=1325520830976885306, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, companyId=1325520830964302393, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2出生人口健康教育部重点实验室/安徽省环境与人口健康重点实验室)])], figs=[ArticleFig(id=1325520838753124971, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=EN, label=Fig.1, caption=Dose-response relationship between physical activity and inflammatory markers in college students, figureFileSmall=Dlue1QZK5b0PwjmQC6nf1Q==, figureFileBig=IIVVKdsZmZab3YntwCvA5A==, tableContent=null), ArticleFig(id=1325520838832816748, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=CN, label=图1, caption=大学生体力活动与炎症标志物的剂量反应关系, figureFileSmall=Dlue1QZK5b0PwjmQC6nf1Q==, figureFileBig=IIVVKdsZmZab3YntwCvA5A==, tableContent=null), ArticleFig(id=1325520839575208558, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=EN, label=Tab.1, caption=

Comparison of distribution of physical activity levels among college students with different groups

, figureFileSmall=null, figureFileBig=null, tableContent=
人口统计学指标选项人数低体力活动中体力活动高体力活动χ2值P值
性别男24842(16.9)94(37.9)112(45.2)44.12＜0.01
女49977(15.4)307(61.5)115(23.0)
健康状况好44561(13.7)231(51.9)153(34.4)10.240.04
一般27854(19.4)155(55.8)69(24.8)
差244(16.7)15(62.5)5(20.8)
BMI/(kg·m-2)＜18.512317(13.8)84(68.3)22(17.9)20.33＜0.01
18.5~＜24.055594(16.9)272(49.0)189(34.1)
≥24.0698(11.6)45(65.2)16(23.2)
最近1个月吸烟天数/d0696109(15.7)388(55.7)199(28.6)19.39＜0.01
≥15110(19.6)13(25.5)28(54.9)
最近1个月饮酒天数/d058396(16.5)332(56.9)155(26.6)18.38＜0.01
≥116423(14.0)69(42.1)72(43.9)
家庭经济条件好399(23.1)18(46.2)12(30.8)5.620.23
一般54279(14.6)304(56.1)159(29.3)
差16631(18.7)79(47.6)56(33.7)
家庭居住地农村41568(16.4)218(52.5)129(31.1)1.350.85
城镇21533(15.3)115(53.5)67(31.2)
市区11718(15.4)68(58.1)31(26.5)
), ArticleFig(id=1325520840028193391, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=CN, label=表1, caption=

不同组别大学生体力活动水平分布比较

, figureFileSmall=null, figureFileBig=null, tableContent=
人口统计学指标选项人数低体力活动中体力活动高体力活动χ2值P值
性别男24842(16.9)94(37.9)112(45.2)44.12＜0.01
女49977(15.4)307(61.5)115(23.0)
健康状况好44561(13.7)231(51.9)153(34.4)10.240.04
一般27854(19.4)155(55.8)69(24.8)
差244(16.7)15(62.5)5(20.8)
BMI/(kg·m-2)＜18.512317(13.8)84(68.3)22(17.9)20.33＜0.01
18.5~＜24.055594(16.9)272(49.0)189(34.1)
≥24.0698(11.6)45(65.2)16(23.2)
最近1个月吸烟天数/d0696109(15.7)388(55.7)199(28.6)19.39＜0.01
≥15110(19.6)13(25.5)28(54.9)
最近1个月饮酒天数/d058396(16.5)332(56.9)155(26.6)18.38＜0.01
≥116423(14.0)69(42.1)72(43.9)
家庭经济条件好399(23.1)18(46.2)12(30.8)5.620.23
一般54279(14.6)304(56.1)159(29.3)
差16631(18.7)79(47.6)56(33.7)
家庭居住地农村41568(16.4)218(52.5)129(31.1)1.350.85
城镇21533(15.3)115(53.5)67(31.2)
市区11718(15.4)68(58.1)31(26.5)
), ArticleFig(id=1325520840426652272, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=EN, label=Tab.2, caption=

Comparison of inflammatory marker levels in groups stratified by physical activity levels of college students[M(P25, P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
体力活动人数hsCRP/(mg·L-1)IL-10/(pg·L-1)IL-1β/(pg·L-1)IL-6/(pg·L-1)TNF-α/(pg·L-1)
低1190.80(0.31，1.30)73.88(47.90，124.24)1.88(1.42，2.81)4.82(3.64，6.67)5.63(4.34，7.62)
中4010.63(0.25，1.30)89.78(58.21，127.65)2.21(1.59，3.27)5.15(3.72，7.72)5.87(4.63，8.00)
高2270.38(0.21，1.10)70.74(47.90，116.43)1.75(1.21，2.64)4.33(2.93，6.82)5.27(3.89，7.30)
H值10.6611.3827.7914.139.44
P值＜0.01＜0.01＜0.01＜0.01＜0.01
), ArticleFig(id=1325520840837694066, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=CN, label=表2, caption=

不同体力活动水平分组大学生炎症标志物水平比较[M(P25, P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
体力活动人数hsCRP/(mg·L-1)IL-10/(pg·L-1)IL-1β/(pg·L-1)IL-6/(pg·L-1)TNF-α/(pg·L-1)
低1190.80(0.31，1.30)73.88(47.90，124.24)1.88(1.42，2.81)4.82(3.64，6.67)5.63(4.34，7.62)
中4010.63(0.25，1.30)89.78(58.21，127.65)2.21(1.59，3.27)5.15(3.72，7.72)5.87(4.63，8.00)
高2270.38(0.21，1.10)70.74(47.90，116.43)1.75(1.21，2.64)4.33(2.93，6.82)5.27(3.89，7.30)
H值10.6611.3827.7914.139.44
P值＜0.01＜0.01＜0.01＜0.01＜0.01
), ArticleFig(id=1325520840908997235, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=EN, label=Tab.3, caption=

Associations between physical activity level and inflammatory markers in college students[OR(95%CI), n=747]

, figureFileSmall=null, figureFileBig=null, tableContent=
调整前后自变量hsCRPIL-10IL-1βIL-6TNF-α
调整前低体力活动2.03(1.36~3.03)**1.14(0.77~1.70)1.37(0.92~2.04)1.39(0.93~2.07)1.29(0.87~1.93)
中体力活动1.58(1.18~2.12)**1.58(1.18~2.12)**2.21(1.64~2.98)**1.69(1.26~2.27)**1.56(1.16~2.09)**
调整后低体力活动2.20(1.46~3.31)**0.99(0.66~1.49)1.20(0.80~1.80)1.28(0.85~1.92)1.21(0.81~1.81)
中体力活动1.65(1.22~2.25)**1.34(0.99~1.82)1.85(1.36~2.51)**1.44(1.06~1.96)*1.43(1.05~1.94)*
), ArticleFig(id=1325520842582524533, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325520829886366257, language=CN, label=表3, caption=

大学生体力活动水平与炎症标志物的关联[OR值(95%CI)，n=747]

, figureFileSmall=null, figureFileBig=null, tableContent=
调整前后自变量hsCRPIL-10IL-1βIL-6TNF-α
调整前低体力活动2.03(1.36~3.03)**1.14(0.77~1.70)1.37(0.92~2.04)1.39(0.93~2.07)1.29(0.87~1.93)
中体力活动1.58(1.18~2.12)**1.58(1.18~2.12)**2.21(1.64~2.98)**1.69(1.26~2.27)**1.56(1.16~2.09)**
调整后低体力活动2.20(1.46~3.31)**0.99(0.66~1.49)1.20(0.80~1.80)1.28(0.85~1.92)1.21(0.81~1.81)
中体力活动1.65(1.22~2.25)**1.34(0.99~1.82)1.85(1.36~2.51)**1.44(1.06~1.96)*1.43(1.05~1.94)*
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大学生体力活动与炎症标志物的关联
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江唐军 1 , 李婷婷 1 , 陶舒曼 1, 2 , 邹立巍 1, 2 , 杨娅娟 1, 2 , 陶芳标 1, 2 , 伍晓艳 *, 1, 2
中国学校卫生 | 疾病控制 2025,46(6): 847-851
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中国学校卫生 |疾病控制 2025 , 46 (6) : 847 -851
大学生体力活动与炎症标志物的关联
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江唐军1, 李婷婷1, 陶舒曼1, 2, 邹立巍1, 2, 杨娅娟1, 2, 陶芳标1, 2, 伍晓艳*, 1, 2
作者信息
  • 1安徽医科大学公共卫生学院儿少卫生与妇幼保健学系，合肥 230032
  • 2出生人口健康教育部重点实验室/安徽省环境与人口健康重点实验室
通讯作者:
伍晓艳，E-mail:
作者简介:

江唐军(1999-)，男，安徽安庆人，在读硕士，主要研究方向为儿童青少年健康

Association between physical activity and inflammatory markers in college students
Tangjun JIANG1, Tingting LI1, Shuman TAO1, 2, Liwei ZOU1, 2, Yajuan YANG1, 2, Fangbiao TAO1, 2, Xiaoyan WU*, 1, 2
Affiliations
  • 1Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei (230032), Anhui Province, China
出版时间: 2025-06-25 doi: 10.16835/j.cnki.1000-9817.2025186
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摘要
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目的

分析大学生体力活动与炎症标志物的关联及剂量反应关系，为促进大学生心血管健康提供参考依据。

方法

采用整群随机抽样方法，于2019年4—5月在安徽省合肥市和江西省上饶市2所高校抽取747名大学生，使用国际体力活动问卷—短卷(IPAQ-SF)评估大学生体力活动，同时采集外周血检测血浆炎症因子水平[超敏C反应蛋白(hsCRP)、白介素-10(IL-10)、白介素-1β(IL-1β)、白介素-6(IL-6)、肿瘤坏死因子α(TNF-α)]。使用χ2检验和双侧Kruskal-Wallis秩和检验比较组间差异，采用广义线性模型和限制性立方样条模型分别分析体力活动与炎症标志物的关联及其剂量反应关系。

结果

大学生低、中、高体力活动组的占比分别为15.9%，53.7%，30.4%。hsCRP、IL-10、II-1β、IL-6、TNF-α水平在高体力活动组分别为0.38(0.21，1.10)mg/L，70.74(47.90，116.43)pg/mL，1.75(1.21，2.64)pg/mL，4.33(2.93，6.82)pg/mL，5.27(3.89，7.30)pg/mL；低体力活动组分别为0.80(0.31，1.30)mg/L，73.88(47.90，124.24)pg/mL，1.88(1.42，2.81)pg/mL，4.82(3.64，6.67)pg/mL，5.63(4.34，7.62)pg/mL；中体力活动组分别为0.63(0.25，1.30)mg/L，89.78(58.21，127.65)pg/mL，2.21(1.59，3.27)pg/mL，5.15(3.72，7.72)pg/mL，5.87(4.63，8.00)pg/mL，差异均有统计学意义(H值分别为10.66，11.38，27.79，14.13，9.44，P值均 < 0.05)。广义线性模型结果显示，调整性别、体质量指数、吸烟、饮酒和健康状况等变量后，与高体力活动组相比，低体力活动(OR=2.20，95%CI=1.46~3.31)和中体力活动组(OR=1.65，95%CI=1.22~2.25)出现高水平hsCRP的可能性更高，中体力活动组出现高水平IL-1β(OR=1.85，95%CI=1.36~2.51)、IL-6(OR=1.44，95%CI=1.06~1.96)、TNF-α(OR=1.43，95%CI=1.05~1.94)的可能性更高(P值均 < 0.05)。限制性立方样条模型显示，每周中高强度体力活动时间与IL-10、IL-6、IL-1β和TNF-α之间存在非线性剂量反应关系(P值均 < 0.05)。

结论

大学生体力活动与炎症之间存在关联；中高强度体力活动有助于降低炎症水平，促进大学生心血管代谢健康。

运动活动  /  细胞因子类  /  剂量-反应关联  /  学生
Objective

To analyze the association and dose-response relationship between physical activity and inflammatory markers in college students, so as to provide a reference for promoting cardiometabolic health in college students.

Methods

A cluster random sampling method was used to select 747 college students from two universities in Hefei, Anhui Province and Shangrao, Jiangxi Province from April to May 2019. Physical activity was assessed by using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and peripheral blood was collected to detect plasma inflammatory factor levels [including hypersensitive C-reactive protein (hsCRP), interleukin-10 (IL-10), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)]. The differences between the groups were compared by using the χ2 test and the Kruskal-Wallis rank sum test, and the association between physical activity and inflammatory markers was analyzed by using the Generalized Linear Model. The dose-response relationship between physical activity and inflammatory markers was analyzed using the Restricted Cubic Spline Model.

Results

The proportions of low physical activity, moderate physical activity, and high physical activity groups of college students were 15.9%, 53.7% and 30.4%, respectively. The levels of hsCRP, IL-10, IL-1β, IL-6 and TNF-α in the high physical activity group were 0.38(0.21, 1.10)mg/L, 70.74(47.90, 116.43)pg/mL, 1.75(1.21, 2.64)pg/mL, 4.33(2.93, 6.82)pg/mL, 5.27(3.89, 7.30)pg/mL, the levels in the low physical activity group were 0.80(0.31, 1.30)mg/L, 73.88(47.90, 124.24)pg/mL, 1.88(1.42, 2.81) pg/mL, 4.82 (3.64, 6.67) pg/mL, 5.63 (4.34, 7.62)pg/mL, the levels in the moderate physical activity group were 0.63(0.25, 1.30)mg/L, 89.78(58.21, 127.65)pg/mL, 2.21(1.59, 3.27)pg/mL, 5.15(3.72, 7.72)pg/mL, 5.87(4.63, 8.00)g/mL, and the differences were statistically significant (H=10.66, 11.38, 27.79, 14.13, 9.44, P < 0.05). After adjusting for variables such as gender, body mass index, smoking, alcohol consumption and health status, the results of Generalized Linear Model showed that compared with the high physical activity group, the low physical activity group (OR=2.20, 95%CI=1.46-3.31) and the moderate physical activity group (OR=1.65, 95%CI=1.22-2.25) were more likely to have high levels of hsCRP, and the moderate physical activity group was more likely to have high levels of IL-1β (OR=1.85, 95%CI=1.36-2.51), IL-6 (OR=1.44, 95%CI=1.06-1.96), and TNF-α (OR=1.43, 95%CI=1.05-1.94) (P < 0.05). The Restricted Cubic Spline Model showed that there was no linear dose-response relationship between the time of moderate-to-vigorous physical activity weekly and IL-10, IL-6, II-1β, and TNF-α (P < 0.05).

Conclusion

There is an association between physical activity and inflammation in college students, and moderate to high intensity per week could reduce inflammation levels to promote cardiometabolic health in college students.

Motor activity  /  Cytokines  /  Dose-response relationship  /  Students
江唐军, 李婷婷, 陶舒曼, 邹立巍, 杨娅娟, 陶芳标, 伍晓艳. 大学生体力活动与炎症标志物的关联. 中国学校卫生, 2025 , 46 (6) : 847 -851 . DOI: 10.16835/j.cnki.1000-9817.2025186
Tangjun JIANG, Tingting LI, Shuman TAO, Liwei ZOU, Yajuan YANG, Fangbiao TAO, Xiaoyan WU. Association between physical activity and inflammatory markers in college students[J]. Chinese Journal of School Health, 2025 , 46 (6) : 847 -851 . DOI: 10.16835/j.cnki.1000-9817.2025186
正文
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全身慢性低度炎症(简称慢性炎症)是指临床上无明显的炎症反应，但是炎症标志物，如超敏C反应蛋白(hypersensitive C-reactive protein，hsCRP)、白介素-1(interleukin-1，IL-1)、白介素-10(interleukin-10，IL-10)、白介素-6(interleukin-6，IL-6)、肿瘤坏死因子α(tumor necrosis factor-α，TNF-α)等，处于正常值范围内的较高状态[1]。慢性炎症不仅与动脉粥样硬化和心肌梗死等心血管疾病的发生发展有直接关系，还与糖尿病、高血脂和肥胖等心血管危险因素密切相关[2]。长时间的运动训练可以产生持续的抗炎作用[3]，而体力活动通过其抗炎过程对心脏提供了保护作用[4-5]。流行病学研究证据也表明，体力活动与全身炎症标志物之间呈负相关[6]。世界卫生组织(World Health Organizaiton, WHO)建议成年人每周应进行至少150 min的中高强度体力活动(moderate-to-vigorous physical activity，MVPA)[7]；然而大学生体力活动不足普遍流行，西方国家有23%~60%的大学生未达到此推荐量，中国有超过40%的大学生未达到此推荐量[8]。研究表明，长时间缺乏运动会导致脂肪组织堆积，过多的脂肪组织会伴随着免疫细胞的浸润、脂肪因子释放的增加和全身低度炎症的发展[9]。肌肉收缩运动期间，IL-6水平会迅速升高，其生理浓度刺激抗炎细胞因子白介素-1α(interleukin-1α，IL-1α)和IL-10增加，并抑制促炎细胞因子TNF-α和白介素-1β(interleukin-1β，IL-1β)的产生；此外，IL-6能刺激脂肪氧化分解以阻止脂肪组织的积累，还可以通过改善血脂水平促进心血管健康，从而限制动脉粥样硬化的产生[10]。因此，本研究分析大学生体力活动与炎症标志物的关联，并探索两者间的剂量反应关系，为改善大学生炎症水平、保护心血管代谢健康提供科学依据。
1　对象与方法
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1.1　对象
2019年4—5月，采用整群随机抽样方法，从安徽省合肥市和江西省上饶市采用直接抽选法抽取2所高校，从每所高校采用直接抽选法分别抽取2个专业，每个专业所有学生作为整体纳入。最后共1 179名大学生参与问卷调查，排除无效问卷后收回有效问卷1 135份，有效率为96.3%。其中有771名大学生进行了血浆炎症标志物的检测。将体力活动的数据与炎症标志物的数据进行匹配，最终纳入747名研究对象，其中男生248名，女生499名；平均年龄(18.82±1.17)岁。本研究遵循“知情同意、隐私保护”的基本原则，并通过安徽医科大学伦理学委员会审查(编号：20170291)。
1.2　方法
1.2.1　问卷调查
使用自编大学生健康相关行为及心理健康问卷进行现场调研，研究对象使用软件扫描二维码填写电子问卷。调查内容包括人口统计学资料(性别、年龄、身高、体重、家庭居住地、自评家庭经济条件等)、自评健康状况、体力活动情况、最近1个月吸烟和饮酒情况等。其中使用自填的身高、体重计算体质量指数(body mass index，BMI)，BMI=体重(kg)/[身高(m)]2；根据中国18岁及以上成人BMI评判标准[11]，BMI＜18.5 kg/m2为体重过低，18.5~＜24.0 kg/m2为正常体重，24.0~＜28.0 kg/m2为超重，BMI≥28.0 kg/m2为肥胖，将超重和肥胖合并为一组。
1.2.2　体力活动判定
使用《国际体力活动问卷—短卷》(International Physical Activity Questionnaire-Short Form，IPAQ-SF)评估大学生过去1周的体力活动情况[12]，收集过去7 d内低强度体力活动(即步行)、中等强度体力活动(即快走、以平常速度骑自行车)和高强度体力活动(即提重物、挖掘、有氧运动或是快速骑车)的频率和持续时间。问卷将个体体力活动水平划分为低、中、高3组，其代谢当量(metabolic equivalent，MET)赋值分别为3.3，4.0和8.0[13]。某种强度体力活动水平=该体力活动对应的MET赋值×每周频率×每天时间，3种强度体力活动水平相加即为总体力活动水平[13]。将中等强度体力活动水平和高强度体力活动水平的每周时间(min)相加，计算参与者的MVPA时间[14]。使用累计每周MET-min将参与者分为3类，高体力活动的划分标准为各类高强度体力活动合计≥3 d且每周总体力活动水平≥1 500 MET-min，或3种强度体力活动合计≥7 d且每周总体力活动水平≥3 000 MET-min；中体力活动的划分标准为满足每天至少20 min的各类高强度体力活动合计≥3 d，或每天至少30 min的各类中等强度和/或步行类活动合计≥5 d，或3种强度体力活动合计≥5 d且每周总体力活动水平≥600 MET-min；低体力活动的划分标准为没有报告任何活动，或报告了一些活动，但是不满足上述中、高分组标准[15]。本研究中该量表的Cronbach α系数为0.89。
1.2.3　测试指标及方法
于问卷调查同时进行清晨(6:00—8:00)空腹采血，由医护人员采集并做好编号登记，受试者空腹采集静脉血5 mL，运送至实验室，静置2 h后，以3 000 r/min离心10 min，离心半径25 cm，提取血清，分装至500 μL冻存管，并储存于-80 ℃冰箱备用。实验前，调查人员准备基质、磁珠、质控、标准品及洗涤液，并采用液相蛋白悬浮芯片检测血浆炎症因子水平。所有分析物的批内变异系数＜5%，批间变异系数＜20%，低于检测限浓度值用最低检测限(limit of detection，LOD)代替。
1.3　质量控制
实施调查前统一对工作人员进行培训。调查时工作人员说明调查目的和填写注意事项，并告知所有填写内容都将严格保密。工作人员现场指导答疑并同时监控问卷系统后台，要求大学生在课堂环境中20~30 min内完成电子问卷。
1.4　统计学分析
采用SPSS 23.0和R 4.3.1软件进行数据处理。计数资料用频数或百分率描述，计量资料不符合正态分布，用M(P25，P75)描述。采用χ2检验比较大学生不同体力活动水平在人口统计学指标组间的分布，使用Kruskal-Wallis秩和检验比较炎症标志物在不同体力活动组间的差异。采用广义线性模型，以体力活动作为自变量(以高体力活动组作为参照)，炎症标志物作为因变量(炎症标志物为偏态分布，按照四分位数转换为分类变量)，调整协变量性别、BMI、健康状况、吸烟和饮酒后，分析体力活动和炎症标志物的关联。采用限制性立方样条模型分析MVPA时间与炎症标志物的剂量反应关系。检验水准α=0.05。
2　结果
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2.1　不同组别大学生各水平体力活动分布
大学生低体力活动、中体力活动和高体力活动组的占比分别为15.9%(119名)，53.7%(401名)和30.4%(227名)。不同性别、BMI、健康状况、吸烟和饮酒天数的大学生体力活动水平分布差异均有统计学意义(P值均＜0.05)。见表1。
2.2　不同体力活动水平分组大学生炎症标志物水平
与高体力活动组相比，低、中体力活动组的炎症标志物的中位数更高，差异均有统计学意义(P值均＜0.05)。见表2。
2.3　大学生体力活动水平与炎症标志物的关联
广义线性模型分析结果显示，在未调整模型中，与高体力活动组相比，低体力活动组出现高水平hsCRP(OR=2.03)的可能性更高，中体力活动组出现高水平的hsCRP(OR=1.58)、IL-10(OR=1.58)、IL-1β(OR=2.21)、IL-6(OR=1.69)、TNF-α(OR=1.56)的可能性更高(P值均＜0.05)。调整性别、BMI、吸烟、饮酒和健康状况等变量后，与高体力活动组相比，低体力活动组出现高水平hsCRP(OR=2.20)的可能性更高，中体力活动组出现高水平hsCRP(OR=1.65)、IL-1β(OR=1.85)、IL-6(OR=1.44)、TNF-α(OR=1.43)的可能性更高(P值均＜0.05)。见表3。
2.4　大学生MVPA时间与炎症标志物的剂量反应关系
限制性立方样条模型结果显示，大学生每周MVPA时间与IL-10、IL-6、IL-1β和TNF-α之间存在非线性剂量反应关系(P值均＜0.05)，阈值分别为153.77，162.81，144.72，153.77 min，但每周MVPA时间与hsCRP不存在非线性关系(P>0.05)。见图1。
3　讨论
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本研究结果显示，大学生低体力活动的检出率为15.9%。García等[16]对大学生的体力活动水平研究发现，低体力活动的检出率为13.9%。李奕等[17]研究发现，16.4%的武汉高校大学生的日常体力活动处于低水平。有研究表明大学生学习任务重、周围环境因素的影响以及大学生对手机的依赖，使大学生的体力活动显著减少[18]。
广义线性回归分析提示，与高体力活动组相比，hsCRP、IL-6、IL-1β、TNF-α水平与中体力活动组有较强的关联性，但在低体力活动组中仅有hsCRP被发现存在关联。高体力活动组相较中体力活动组可以降低炎症水平，但是在低体力活动组中关联无统计学意义，且风险水平低于中体力活动组，表明IL-10、IL-6、IL-1β、TNF-α水平可能与体力活动水平呈非线性关系；IL-10、IL-6、IL-1β、TNF-α在体力活动水平分组中的四分位数分布也呈现同样的结果。本研究结果显示，炎症标志物的水平随着MVPA时间的增加呈先上升后降低的非线性趋势，其阈值约为每周150 min MVPA，与WHO体力活动推荐量一致。先前研究表明，全身低度炎症与肥胖有关，包括脂肪因子、IL-6和TNF-α，可能导致心血管疾病的发生，运动干预可在一定程度上抵抗炎症状态和氧化状态，可能是由于运动增强了抗氧化能力和减少了活性氧的产生[19]。
体力活动与炎症存在明显关联，不同的体力活动强度和持续时间会引起不同的炎症反应[20]。在一项干预性研究中，高强度体力活动与老年男性IL-6水平下降有关[21]。Jahromi等[22]研究发现，成年男性经过8周耐力训练后，TNF-α水平降低。在2型糖尿病患者中也观察到体力活动与炎症标志物之间的类似关联[23]。以上研究结果均与本研究一致。
久坐行为和缺乏身体活动被认为是胰岛素抵抗(insulin resistance，IR)和2型糖尿病发展的重要致病因素[24-26]。有证据表明，即使是短期减少身体活动并增加久坐行为也会导致多器官胰岛素敏感性和肌肉胰岛素敏感性指数降低，并随之增加中枢和肝脏脂肪以及低密度脂蛋白胆固醇[27]。慢性低度全身炎症与IR的病理生理学密切相关，由于能量消耗低，不活跃的生活方式会引起腹部重要器官以及肝脏和肌肉细胞内过多的脂质积累[28]。脂肪组织是一种内分泌器官，可调节葡萄糖和脂质代谢，并分泌多种称为脂肪因子的生物活性循环介质，此外还有细胞因子和趋化因子[29]。这些蛋白与免疫系统的成分存在复杂的相互作用，内脏/皮下脂肪组织的积累会导致免疫系统活性和炎性细胞因子循环水平的增加，从而改变胰岛素信号传导并促进IR[24]。IR在许多心血管危险因素的发病机制中发挥着重要作用[29-30]。因此，每天进行2 h的MVPA可以降低大学生心血管代谢风险。
本研究存在一定局限性：第一，研究采用的是横断面设计，限制了研究确定因果关系的能力。第二，研究采用自我报告的方式收集大学生体力活动情况，因此可能无法避免回忆偏倚和报告偏倚。第三，调查过程中，未提前排除近期感冒或者炎症的人群，可能导致hsCRP等炎症指标会有影响。研究揭示了大学生体力活动与炎症标志物可能存在的非线性剂量反应关系，每周进行150 min的MVPA能有效降低炎症水平。提示未来可通过高强度的体力活动干预来降低炎症水平，改善大学生心血管代谢健康。
基金
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  • 国家自然科学基金项目(82173542，82373592)；安徽医科大学科研水平提升计划资助项目(2022xkjT004)
文献
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2025年第46卷第6期
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doi: 10.16835/j.cnki.1000-9817.2025186
  • 接收时间：2025-02-14
  • 首发时间：2026-11-06
  • 出版时间：2025-06-25
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  • 收稿日期：2025-02-14
  • 修回日期：2025-06-02
基金
国家自然科学基金项目(82173542，82373592)；安徽医科大学科研水平提升计划资助项目(2022xkjT004)
作者信息
    1安徽医科大学公共卫生学院儿少卫生与妇幼保健学系，合肥 230032
    2出生人口健康教育部重点实验室/安徽省环境与人口健康重点实验室

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伍晓艳，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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