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Article(id=1241023850490679747, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410259, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729180800000, receivedDateStr=2024-10-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812743064, onlineDateStr=2026-03-18, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812743064, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812743064, creator=13701087609, updateTime=1773812743064, updator=13701087609, issue=Issue{id=1241023847537897695, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812742361, creator=13701087609, updateTime=1773812823817, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024189247845056, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024189247845057, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=232, endPage=239, ext={EN=ArticleExt(id=1241023850754920902, articleId=1241023850490679747, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Research on the relationship between occupational physical activity and dyslipidemia in coal mine employees, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between occupational physical activity and dyslipidemia among coal mine employees, providing reference for improving the prevention and control of dyslipidemia among coal mine employees and formulating health strategies.

Methods

This study was conducted in 2023 at Xishan coal electricity corporation occupational disease prevention and control institute. It was a cross-sectional study, with a total of 9 864 coal mine employees included in the analysis. We collected physical activity data using the International Physical Activity Questionnaire, and diagnosed dyslipidemia using the "Chinese Guidelines for the Prevention and Treatment of Adult Blood Lipid Disorders". We analyzed the relationship between occupational physical activity and dyslipidemia among coal mine employees using a multiple factor logistic regression model.

Results

The proportion of low, medium, and high intensity occupational physical activities among coal mine employees were 38.42%, 35.75%, and 25.83%, respectively. There were intergroup differences (P<0.05) in the incidence of high TG and dyslipidemia among occupational physical activities of different intensities, but this difference was not observed in the incidence of high TC, low HDL, and high LDL (P>0.05). After adjusting for factors such as gender, age, and leisure time physical activity, the incidence of dyslipidemia was lower among coal miners engaged in moderate to high-intensity occupational physical activity compared to those engaged in low-intensity physical activity (OR=0.84, 95%CI:0.76-0.94; OR=0.77, 95%CI:0.69-0.87); The incidence of low HDL was also lower (OR=0.85, 95%CI:0.77-0.95; OR=0.83, 95%CI:0.73-0.93).

Conclusion

There is a negative correlation between occupational physical activity and dyslipidemia among coal mine employees. For coal mine workers engaged in low-intensity occupational physical activities, it is recommended to intervene in other modifiable behavioral risk factors related to dyslipidemia to maintain healthy blood lipid levels.

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目的

探索煤矿从业人员职业性体力活动与血脂异常的关系，为提高煤矿从业人员血脂异常防控水平，制定健康策略提供参考。

方法

采用横断面设计的研究方法，选取2023年于西山煤电（集团）有限责任公司职业病防治所职业体检的煤矿从业人员研究对象，共计9 864名煤矿从业人员被纳入分析。采用国际体力活动问卷收集体力活动数据，血脂异常采用《中国成人血脂异常防治指南》进行诊断。运用多因素logistic回归模型分析煤矿从业人员职业性体力活动和血脂异常之间的关系。

结果

煤矿从业人员职业性体力活动低、中、高强度人数占比分别为38.42%、35.75%、25.83%。不同强度职业性体力活动与高TG及血脂异常患病率存在组间差异（P<0.05），这种差异在高TC、低HDL、高LDL患病中未显现（P>0.05）。在调整了性别、年龄、闲暇时间体力活动等因素后，相较于低强度体力活动的煤矿从业人员，中及高强度职业性体力活动的煤矿从业人员血脂异常患病率更低（OR=0.84，95%CI:0.76~0.94；OR=0.77，95%CI:0.69~0.87）；低HDL患病率也更低（OR=0.85，95%CI:0.77~0.95；OR=0.83，95%CI:0.73~0.93）。

结论

煤矿从业人员职业性体力活动与血脂异常呈负相关关系。对于从事低强度职业性体力活动煤矿从业人员，建议针对血脂异常的其他可改变行为危险因素进行干预，以维持血脂的健康水平。

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陈青松与刘改生为共同通信作者；陈青松，E-mail：；
刘改生，E-mail：
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罗颖琪（1998—），女，硕士在读，研究方向：公共卫生

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罗颖琪（1998—），女，硕士在读，研究方向：公共卫生

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High physical activity is associated with an improved lipid profile among male coal miners[J]. Chinese Journal of Disease Control & Prevention, 2017, 21(2): 123-127. (In Chinese), articleTitle=High physical activity is associated with an improved lipid profile among male coal miners, refAbstract=null), Reference(id=1241023864172499054, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, doi=null, pmid=null, pmcid=null, year=2022, volume=11, issue=12, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[26], rfOrder=31, authorNames=Stanton KM, Kienzle V, Dinnes DLM, journalName=Journal of the American Heart Association, refType=null, unstructuredReference=Stanton KM, Kienzle V, Dinnes DLM, et al. Moderate- and High-Intensity exercise improves lipoprotein profile and cholesterol efflux capacity in healthy young men[J]. Journal of the American Heart Association, 2022, 11(12): e023386., articleTitle=Moderate- and High-Intensity exercise improves lipoprotein profile and cholesterol efflux capacity in healthy young men, refAbstract=null)], funds=[Fund(id=1241023859059643131, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, awardId=2025A03J3722, language=CN, fundingSource=广州市科技计划基金项目(2025A03J3722), fundOrder=null, country=null), Fund(id=1241023859151917827, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, awardId=2022A1515011357, language=CN, fundingSource=广东省自然科学基金项目(2022A1515011357), fundOrder=null, country=null), Fund(id=1241023859260969743, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, awardId=2025A03J3722, language=CN, fundingSource=广州市科技计划基金项目(2025A03J3722), fundOrder=null, country=null), Fund(id=1241023859374215961, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, awardId=SL2022A04J00361, language=CN, fundingSource=广州市科技局基金项目(SL2022A04J00361), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023852063543767, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, xref=1．, ext=[AuthorCompanyExt(id=1241023852071932376, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, companyId=1241023852063543767, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510310, China), AuthorCompanyExt(id=1241023852076126682, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, companyId=1241023852063543767, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1．广东药科大学公共卫生学院，广东　广州　510310)]), AuthorCompany(id=1241023852164207068, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, xref=2．, ext=[AuthorCompanyExt(id=1241023852172595677, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, companyId=1241023852164207068, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2．西山煤电（集团）有限责任公司职业病防治所)])], figs=[ArticleFig(id=1241023856454980256, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=EN, label=Fig.1, caption=The prevalence of dyslipidemia among coal mine employees, figureFileSmall=nmHmtAMcOm7SKAwJsFaZww==, figureFileBig=goqFmD0CwrZmbbCx2EYX+w==, tableContent=null), ArticleFig(id=1241023856564032166, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=CN, label=图1, caption=煤矿从业人员血脂异常患病率, figureFileSmall=nmHmtAMcOm7SKAwJsFaZww==, figureFileBig=goqFmD0CwrZmbbCx2EYX+w==, tableContent=null), ArticleFig(id=1241023856773747382, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=EN, label=Table 1, caption=

Basic information description of coal mine employees in different occupational physical activity intensity groups[n(%),M(P25,P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
因素总体职业体力活动强度H/χ2P
低强度中强度高强度
年龄（岁）40.00(35.00,49.00)40.00(35.00,49.00)41.00(35.00,50.00)40.00(35.00,49.00)18.327<0.001
性别517.562<0.001
男9 247(93.74)3 291(35.59)3 420(36.98)2 536(27.43)
女617(6.26)499(80.88)106(17.18)12(1.94)
学历369.213<0.001
初中及以下1 657(16.80)481(29.03)698(42.12)478(28.85)
高中3 424(34.71)1 033(30.17)1 275(37.24)1 116(32.59)
大专本科及以上4 783(48.49)2 276(47.59)1 553(32.47)954(19.95)
家庭月人均收入（元）43.653<0.001
≤2 0001 965(19.92)687(34.96)741(37.71)537(27.33)
2 001~3 0002 233(22.64)802(35.92)779(34.89)652(29.20)
3 001~5 0002 447(24.81)1 029(42.05)846(34.57)572(23.38)
5 001~10 0002 657(26.94)1 047(39.41)950(35.75)660(24.84)
>10 000562(5.70)225(40.04)210(37.37)127(22.60)
BMI（kg/m2）6.9760.323
低体重116(1.18)42(36.21)43(37.07)31(26.72)
正常体重3 099(31.42)1 200(38.72)1 075(34.69)824(26.59)
超重4 260(43.19)1 602(37.61)1 541(36.17)1 117(26.22)
肥胖2 389(24.22)946(39.60)867(36.29)576(24.11)
婚姻状况9.9940.041
未婚510(5.17)184(36.08)181(35.49)145(28.43)
已婚8 988(91.12)3 445(38.33)3 213(35.75)2 330(25.92)
其他366(3.71)161(43.99)132(36.07)73(19.95)
生活行为习惯
吸烟59.098<0.001
否4 231(42.89)1 807(42.71)1 427(33.73)997(23.56)
是5 094(51.64)1 798(35.30)1 900(37.30)1 396(27.40)
已戒烟539(5.46)185(34.32)199(36.92)155(28.76)
饮酒18.8380.001
否4 135(41.92)1 679(40.60)1 457(35.24)999(24.16)
是5 271(53.44)1 955(37.09)1 893(35.91)1 423(27.00)
已戒酒458(4.64)156(34.06)176(38.43)126(27.51)
饮茶习惯17.584<0.001
否6 395(64.83)2 395(37.45)2 263(35.39)1 737(27.16)
是3 469(35.17)1 395(40.21)1 263(36.41)811(23.38)
闲暇时间体力活动35.377<0.001
否7 939(80.48)3 058(38.52)2 743(34.55)2 138(26.93)
是1 925(19.52)732(38.03)783(40.68)410(21.30)
职业情况35.577<0.001
目前岗位工龄13.00(7.00, 18.50)12.00(6.00,18.00)13.00(7.00,19.50)13.00(8.13,18.50)
工种1 492.583<0.001
井下一线1 807(18.32)333(18.43)596(32.98)878(48.59)
井下辅助4 513(45.75)1 355(30.02)1 811(40.13)1 347(29.85)
地面3 544(35.93)2 102(59.31)1 119(31.57)323(9.11)
噪声暴露780.866<0.001
否3 728(37.79)2 055(55.12)1 132(30.36)541(14.51)
是6 136(62.21)1 735(28.28)2 394(39.02)2 007(32.71)
粉尘暴露1 167.865<0.001
否3 524(35.72)2 112(59.93)1 000(28.38)412(11.69)
是6 340(64.27)1 678(26.47)2 526(39.84)2 136(33.69)
有毒有害气体暴露732.864<0.001
否6 431(65.20)2 991(46.51)2 270(35.30)1 170(18.19)
是3 433(34.80)799(23.27)1 256(36.59)1 378(40.14)
夜班情况22.148<0.001
否5 544(56.20)2 235(40.31)1 954(35.25)1 355(24.44)
是4 320(43.80)1 555(36.00)1 572(36.39)1 193(27.62)
既往史
糖尿病25.328<0.001
否9 066(91.91)3 445(38.00)3 220(35.52)2 401(26.48)
是798(8.09)345(43.23)306(38.35)147(18.42)
高血压10.5560.005
否7 679(77.85)2 915(37.96)2 722(35.45)2 042(26.59)
是2 185(22.15)875(40.05)804(36.80)506(23.16)
高尿酸血症26.864<0.001
否7 157(72.57)2 680(37.45)2 529(35.34)1 948(27.22)
是2 705(27.43)1 108(40.96)997(36.86)600(22.18)
膳食因素
精制糖的使用量（g/d）26.279<0.001
≤257 609(77.14)3 011(39.57)2 691(35.37)1 907(25.06)
26~301 498(15.19)517(34.51)556(37.12)425(28.37)
31~35436(4.42)158(36.24)168(38.53)110(25.23)
≥36321(3.25)104(32.40)111(34.58)106(33.02)
红肉摄入频率8.5500.382
很少1 518(15.39)562(37.02)541(35.64)415(27.34)
有时1 719(17.43)668(38.86)599(34.85)452(26.29)
偶尔1 955(19.82)761(38.93)724(37.03)470(24.04)
经常1 028(10.42)415(40.37)348(33.85)265(25.78)
总是3 644(36.94)1 384(37.98)1 314(36.06)946(25.96)
食用油的使用量（勺）5.3370.254
≤12 322(23.54)904(38.93)840(36.18)578(24.89)
2~33 821(38.74)1 458(38.16)1 330(34.81)1 033(27.03)
≥43 721(37.72)1 428(38.38)1 356(36.44)937(25.18)
), ArticleFig(id=1241023856882799295, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=CN, label=表1, caption=

不同职业性体力活动强度组煤矿从业人员基本情况描述[n(%),M(P25,P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
因素总体职业体力活动强度H/χ2P
低强度中强度高强度
年龄（岁）40.00(35.00,49.00)40.00(35.00,49.00)41.00(35.00,50.00)40.00(35.00,49.00)18.327<0.001
性别517.562<0.001
男9 247(93.74)3 291(35.59)3 420(36.98)2 536(27.43)
女617(6.26)499(80.88)106(17.18)12(1.94)
学历369.213<0.001
初中及以下1 657(16.80)481(29.03)698(42.12)478(28.85)
高中3 424(34.71)1 033(30.17)1 275(37.24)1 116(32.59)
大专本科及以上4 783(48.49)2 276(47.59)1 553(32.47)954(19.95)
家庭月人均收入（元）43.653<0.001
≤2 0001 965(19.92)687(34.96)741(37.71)537(27.33)
2 001~3 0002 233(22.64)802(35.92)779(34.89)652(29.20)
3 001~5 0002 447(24.81)1 029(42.05)846(34.57)572(23.38)
5 001~10 0002 657(26.94)1 047(39.41)950(35.75)660(24.84)
>10 000562(5.70)225(40.04)210(37.37)127(22.60)
BMI（kg/m2）6.9760.323
低体重116(1.18)42(36.21)43(37.07)31(26.72)
正常体重3 099(31.42)1 200(38.72)1 075(34.69)824(26.59)
超重4 260(43.19)1 602(37.61)1 541(36.17)1 117(26.22)
肥胖2 389(24.22)946(39.60)867(36.29)576(24.11)
婚姻状况9.9940.041
未婚510(5.17)184(36.08)181(35.49)145(28.43)
已婚8 988(91.12)3 445(38.33)3 213(35.75)2 330(25.92)
其他366(3.71)161(43.99)132(36.07)73(19.95)
生活行为习惯
吸烟59.098<0.001
否4 231(42.89)1 807(42.71)1 427(33.73)997(23.56)
是5 094(51.64)1 798(35.30)1 900(37.30)1 396(27.40)
已戒烟539(5.46)185(34.32)199(36.92)155(28.76)
饮酒18.8380.001
否4 135(41.92)1 679(40.60)1 457(35.24)999(24.16)
是5 271(53.44)1 955(37.09)1 893(35.91)1 423(27.00)
已戒酒458(4.64)156(34.06)176(38.43)126(27.51)
饮茶习惯17.584<0.001
否6 395(64.83)2 395(37.45)2 263(35.39)1 737(27.16)
是3 469(35.17)1 395(40.21)1 263(36.41)811(23.38)
闲暇时间体力活动35.377<0.001
否7 939(80.48)3 058(38.52)2 743(34.55)2 138(26.93)
是1 925(19.52)732(38.03)783(40.68)410(21.30)
职业情况35.577<0.001
目前岗位工龄13.00(7.00, 18.50)12.00(6.00,18.00)13.00(7.00,19.50)13.00(8.13,18.50)
工种1 492.583<0.001
井下一线1 807(18.32)333(18.43)596(32.98)878(48.59)
井下辅助4 513(45.75)1 355(30.02)1 811(40.13)1 347(29.85)
地面3 544(35.93)2 102(59.31)1 119(31.57)323(9.11)
噪声暴露780.866<0.001
否3 728(37.79)2 055(55.12)1 132(30.36)541(14.51)
是6 136(62.21)1 735(28.28)2 394(39.02)2 007(32.71)
粉尘暴露1 167.865<0.001
否3 524(35.72)2 112(59.93)1 000(28.38)412(11.69)
是6 340(64.27)1 678(26.47)2 526(39.84)2 136(33.69)
有毒有害气体暴露732.864<0.001
否6 431(65.20)2 991(46.51)2 270(35.30)1 170(18.19)
是3 433(34.80)799(23.27)1 256(36.59)1 378(40.14)
夜班情况22.148<0.001
否5 544(56.20)2 235(40.31)1 954(35.25)1 355(24.44)
是4 320(43.80)1 555(36.00)1 572(36.39)1 193(27.62)
既往史
糖尿病25.328<0.001
否9 066(91.91)3 445(38.00)3 220(35.52)2 401(26.48)
是798(8.09)345(43.23)306(38.35)147(18.42)
高血压10.5560.005
否7 679(77.85)2 915(37.96)2 722(35.45)2 042(26.59)
是2 185(22.15)875(40.05)804(36.80)506(23.16)
高尿酸血症26.864<0.001
否7 157(72.57)2 680(37.45)2 529(35.34)1 948(27.22)
是2 705(27.43)1 108(40.96)997(36.86)600(22.18)
膳食因素
精制糖的使用量（g/d）26.279<0.001
≤257 609(77.14)3 011(39.57)2 691(35.37)1 907(25.06)
26~301 498(15.19)517(34.51)556(37.12)425(28.37)
31~35436(4.42)158(36.24)168(38.53)110(25.23)
≥36321(3.25)104(32.40)111(34.58)106(33.02)
红肉摄入频率8.5500.382
很少1 518(15.39)562(37.02)541(35.64)415(27.34)
有时1 719(17.43)668(38.86)599(34.85)452(26.29)
偶尔1 955(19.82)761(38.93)724(37.03)470(24.04)
经常1 028(10.42)415(40.37)348(33.85)265(25.78)
总是3 644(36.94)1 384(37.98)1 314(36.06)946(25.96)
食用油的使用量（勺）5.3370.254
≤12 322(23.54)904(38.93)840(36.18)578(24.89)
2~33 821(38.74)1 458(38.16)1 330(34.81)1 033(27.03)
≥43 721(37.72)1 428(38.38)1 356(36.44)937(25.18)
), ArticleFig(id=1241023856983462597, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=EN, label=Table 2, caption=

Lipid levels of coal mine employees in different occupational physical activity intensity groups[M(P25，P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
因素(mmol/L)总体职业体力活动强度HP
低强度中强度高强度
TC4.45(3.89,5.05)4.54(3.98,5.15)4.45(3.89,5.04)4.31(3.79,4.91)94.419<0.001
TG1.48(0.99,2.29)1.57(1.06,2.39)1.50(1.01,2.31)1.33(0.90,2.08)103.637<0.001
HDL-C1.07(0.92,1.26)1.06(0.91,1.25)1.08(0.92,1.26)1.08(0.92,1.28)11.033<0.001
LDL-C2.61(2.20,3.06)2.70(2.27,3.11)2.61(2.19,3.06)2.51(2.11,2.96)102.079<0.001
), ArticleFig(id=1241023857071542987, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=CN, label=表2, caption=

不同职业性体力活动强度组煤矿从业人员血脂水平[M(P25，P75)]

, figureFileSmall=null, figureFileBig=null, tableContent=
因素(mmol/L)总体职业体力活动强度HP
低强度中强度高强度
TC4.45(3.89,5.05)4.54(3.98,5.15)4.45(3.89,5.04)4.31(3.79,4.91)94.419<0.001
TG1.48(0.99,2.29)1.57(1.06,2.39)1.50(1.01,2.31)1.33(0.90,2.08)103.637<0.001
HDL-C1.07(0.92,1.26)1.06(0.91,1.25)1.08(0.92,1.26)1.08(0.92,1.28)11.033<0.001
LDL-C2.61(2.20,3.06)2.70(2.27,3.11)2.61(2.19,3.06)2.51(2.11,2.96)102.079<0.001
), ArticleFig(id=1241023858535355094, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=EN, label=Table 3, caption=

Dyslipidemia among coal mine employees in different occupational physical activity intensity groups[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
分型总体职业体力活动强度χ2P
低强度中强度高强度
高TC2.6770.262
否9 726(98.60)3 728(98.36)3 480(98.70)2 518(98.82)
是138(1.40)62(1.64)46(1.30)30(1.18)
高TG36.521<0.001
否7 410(75.12)2 759(72.80)2 628(74.53)2 023(79.40)
是2 454(24.88)1 031(27.20)898(25.47)525(20.60)
低HDL5.0030.082
否6 121(62.05)2 302(60.74)2 204(62.51)1 615(63.38)
是3 743(37.95)1 488(39.26)1 322(37.49)933(36.62)
高LDL4.4380.122
否9 788(99.23)3 752(99.00)3 505(99.40)2 531(99.33)
是76(0.77)38(1.00)21(0.60)17(0.67)
血脂异常22.013<0.001
否4 956(50.24)1 813(47.84)1 771(50.23)1 372(53.85)
是4 908(49.76)1 977(52.16)1 755(49.77)1 176(46.15)
), ArticleFig(id=1241023858656989916, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=CN, label=表3, caption=

不同职业性体力活动强度组煤矿从业人员血脂异常情况[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
分型总体职业体力活动强度χ2P
低强度中强度高强度
高TC2.6770.262
否9 726(98.60)3 728(98.36)3 480(98.70)2 518(98.82)
是138(1.40)62(1.64)46(1.30)30(1.18)
高TG36.521<0.001
否7 410(75.12)2 759(72.80)2 628(74.53)2 023(79.40)
是2 454(24.88)1 031(27.20)898(25.47)525(20.60)
低HDL5.0030.082
否6 121(62.05)2 302(60.74)2 204(62.51)1 615(63.38)
是3 743(37.95)1 488(39.26)1 322(37.49)933(36.62)
高LDL4.4380.122
否9 788(99.23)3 752(99.00)3 505(99.40)2 531(99.33)
是76(0.77)38(1.00)21(0.60)17(0.67)
血脂异常22.013<0.001
否4 956(50.24)1 813(47.84)1 771(50.23)1 372(53.85)
是4 908(49.76)1 977(52.16)1 755(49.77)1 176(46.15)
), ArticleFig(id=1241023858740876001, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=EN, label=Table 4, caption=

Logistic regression model of occupational physical activity intensity and dyslipidemia among coal mine employees

, figureFileSmall=null, figureFileBig=null, tableContent=
分型中强度职业性体力活动高强度职业性体力活动
OR(95%Cl)POR(95%Cl)P
高TC
模型10.79(0.54~1.17)0.7950.72(0.46~1.11)0.716
模型20.82(0.55~1.21)0.3150.73(0.46~1.15)0.174
模型30.88(0.58~1.34)0.5540.95(0.57~1.57)0.834
高TG
模型10.91(0.82~1.01)0.0920.69(0.62~0.78)<0.001
模型20.85(0.77~0.95)0.0050.65(0.57~0.74)<0.001
模型30.92(0.82~1.04)0.1890.81(0.70~0.93)0.004
低HDL
模型10.93(0.84~1.02)0.9280.89(0.81~0.99)0.034
模型20.83(0.75~0.92)<0.0010.78(0.70~0.88)<0.001
模型30.85(0.77~0.95)0.0030.83(0.73~0.93)0.002
高LDL
模型10.59(0.35~1.01)0.0540.66(0.37~1.18)0.161
模型20.60(0.34~1.03)0.0640.68(0.37~1.24)0.207
模型30.64(0.36~1.14)0.1270.83(0.43~1.61)0.586
血脂异常
模型10.91(0.83~1.00)0.0410.79(0.71~0.87)<0.001
模型20.80(0.73~0.88)<0.0010.68(0.61~0.76)<0.001
模型30.84(0.76~0.94)0.0010.77(0.69~0.87)<0.001
), ArticleFig(id=1241023858845733610, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023850490679747, language=CN, label=表4, caption=

煤矿从业人员职业性体力活动强度与血脂异常的logistic回归模型

, figureFileSmall=null, figureFileBig=null, tableContent=
分型中强度职业性体力活动高强度职业性体力活动
OR(95%Cl)POR(95%Cl)P
高TC
模型10.79(0.54~1.17)0.7950.72(0.46~1.11)0.716
模型20.82(0.55~1.21)0.3150.73(0.46~1.15)0.174
模型30.88(0.58~1.34)0.5540.95(0.57~1.57)0.834
高TG
模型10.91(0.82~1.01)0.0920.69(0.62~0.78)<0.001
模型20.85(0.77~0.95)0.0050.65(0.57~0.74)<0.001
模型30.92(0.82~1.04)0.1890.81(0.70~0.93)0.004
低HDL
模型10.93(0.84~1.02)0.9280.89(0.81~0.99)0.034
模型20.83(0.75~0.92)<0.0010.78(0.70~0.88)<0.001
模型30.85(0.77~0.95)0.0030.83(0.73~0.93)0.002
高LDL
模型10.59(0.35~1.01)0.0540.66(0.37~1.18)0.161
模型20.60(0.34~1.03)0.0640.68(0.37~1.24)0.207
模型30.64(0.36~1.14)0.1270.83(0.43~1.61)0.586
血脂异常
模型10.91(0.83~1.00)0.0410.79(0.71~0.87)<0.001
模型20.80(0.73~0.88)<0.0010.68(0.61~0.76)<0.001
模型30.84(0.76~0.94)0.0010.77(0.69~0.87)<0.001
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煤矿从业人员职业性体力活动与血脂异常的关系研究
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罗颖琪 1 , 曾霞 1 , 戴颖诗 1 , 刘燕辉 1 , 蒋柳权 2 , 赵宏霞 2 , 刘改生 2 , 陈青松 1
现代预防医学 | 环境与职业卫生 2025,52(2): 232-239
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现代预防医学 | 环境与职业卫生 2025, 52(2): 232-239
煤矿从业人员职业性体力活动与血脂异常的关系研究
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罗颖琪1, 曾霞1, 戴颖诗1, 刘燕辉1, 蒋柳权2, 赵宏霞2, 刘改生2 , 陈青松1
作者信息
  • 1．广东药科大学公共卫生学院，广东　广州　510310
  • 2．西山煤电（集团）有限责任公司职业病防治所

    • 罗颖琪（1998—），女，硕士在读，研究方向：公共卫生

通讯作者:

陈青松与刘改生为共同通信作者；陈青松，E-mail：；
刘改生，E-mail：
Research on the relationship between occupational physical activity and dyslipidemia in coal mine employees
Ying-qi LUO1, Xia ZENG1, Ying-shi DAI1, Yan-hui LIU1, Liu-quan JIANG2, Hong-xia ZHAO2, Gai-sheng LIU2 , Qing-song CHEN1
Affiliations
  • School of Public Health, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510310, China
出版时间: 2025-01-25 doi: 10.20043/j.cnki.MPM.202410259
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摘要
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目的

探索煤矿从业人员职业性体力活动与血脂异常的关系，为提高煤矿从业人员血脂异常防控水平，制定健康策略提供参考。

方法

采用横断面设计的研究方法，选取2023年于西山煤电（集团）有限责任公司职业病防治所职业体检的煤矿从业人员研究对象，共计9 864名煤矿从业人员被纳入分析。采用国际体力活动问卷收集体力活动数据，血脂异常采用《中国成人血脂异常防治指南》进行诊断。运用多因素logistic回归模型分析煤矿从业人员职业性体力活动和血脂异常之间的关系。

结果

煤矿从业人员职业性体力活动低、中、高强度人数占比分别为38.42%、35.75%、25.83%。不同强度职业性体力活动与高TG及血脂异常患病率存在组间差异（P<0.05），这种差异在高TC、低HDL、高LDL患病中未显现（P>0.05）。在调整了性别、年龄、闲暇时间体力活动等因素后，相较于低强度体力活动的煤矿从业人员，中及高强度职业性体力活动的煤矿从业人员血脂异常患病率更低（OR=0.84，95%CI:0.76~0.94；OR=0.77，95%CI:0.69~0.87）；低HDL患病率也更低（OR=0.85，95%CI:0.77~0.95；OR=0.83，95%CI:0.73~0.93）。

结论

煤矿从业人员职业性体力活动与血脂异常呈负相关关系。对于从事低强度职业性体力活动煤矿从业人员，建议针对血脂异常的其他可改变行为危险因素进行干预，以维持血脂的健康水平。

职业性体力活动  /  血脂异常  /  煤矿从业人员
Objective

To explore the relationship between occupational physical activity and dyslipidemia among coal mine employees, providing reference for improving the prevention and control of dyslipidemia among coal mine employees and formulating health strategies.

Methods

This study was conducted in 2023 at Xishan coal electricity corporation occupational disease prevention and control institute. It was a cross-sectional study, with a total of 9 864 coal mine employees included in the analysis. We collected physical activity data using the International Physical Activity Questionnaire, and diagnosed dyslipidemia using the "Chinese Guidelines for the Prevention and Treatment of Adult Blood Lipid Disorders". We analyzed the relationship between occupational physical activity and dyslipidemia among coal mine employees using a multiple factor logistic regression model.

Results

The proportion of low, medium, and high intensity occupational physical activities among coal mine employees were 38.42%, 35.75%, and 25.83%, respectively. There were intergroup differences (P<0.05) in the incidence of high TG and dyslipidemia among occupational physical activities of different intensities, but this difference was not observed in the incidence of high TC, low HDL, and high LDL (P>0.05). After adjusting for factors such as gender, age, and leisure time physical activity, the incidence of dyslipidemia was lower among coal miners engaged in moderate to high-intensity occupational physical activity compared to those engaged in low-intensity physical activity (OR=0.84, 95%CI:0.76-0.94; OR=0.77, 95%CI:0.69-0.87); The incidence of low HDL was also lower (OR=0.85, 95%CI:0.77-0.95; OR=0.83, 95%CI:0.73-0.93).

Conclusion

There is a negative correlation between occupational physical activity and dyslipidemia among coal mine employees. For coal mine workers engaged in low-intensity occupational physical activities, it is recommended to intervene in other modifiable behavioral risk factors related to dyslipidemia to maintain healthy blood lipid levels.

Occupational physical activity  /  Dyslipidemia  /  Coal mine employees
罗颖琪, 曾霞, 戴颖诗, 刘燕辉, 蒋柳权, 赵宏霞, 刘改生, 陈青松. 煤矿从业人员职业性体力活动与血脂异常的关系研究. 现代预防医学, 2025 , 52 (2) : 232 -239 . DOI: 10.20043/j.cnki.MPM.202410259
Ying-qi LUO, Xia ZENG, Ying-shi DAI, Yan-hui LIU, Liu-quan JIANG, Hong-xia ZHAO, Gai-sheng LIU, Qing-song CHEN. Research on the relationship between occupational physical activity and dyslipidemia in coal mine employees[J]. Modern Preventive Medicine, 2025 , 52 (2) : 232 -239 . DOI: 10.20043/j.cnki.MPM.202410259
正文
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血脂异常（Dyslipidemia，DL）已成为与心血管疾病（Cardiovascular disease，CVD）风险相关的第二大因素，据报道，该病导致中国与血脂异常直接相关的年度总死亡率从1990年的251万增加到2016年的397万[1-2]。
积极参与体力活动（Physical activity，PA）作为预防心血管疾病和降低全因死亡率的可行措施[3-4]，也可通过改变交感神经、迷走神经的活动及循环炎症标志物数量，从而影响个体的血脂水平[5-6]。体力活动分为4种类型包括职业性体力活动、交通体力活动、家庭体力活动和闲暇时间体力活动[7]。学术界存在有体力活动悖论之说，学者们大都认为闲暇时间体力活动对健康存在益处，但职业性体力活动对健康的影响结论并不完全一致[8-10]。最近一项中国的纵向研究表明[11]，体力活动（尤其是职业性体力活动）对男性的高密度脂蛋白胆固醇（High density lipoprotein cholesterol，HDL-C）有积极影响。一项综述发现，高强度职业性体力活动可降低癌症、冠心病和2型糖尿病等的患病风险，但可增加骨关节炎、睡眠质量差和男性全因死亡率的患病风险[12]。因此需要更多研究说明职业性体力活动与健康的关系。世界卫生组织（WHO）关于体力活动和久坐行为的指南最近也鼓励进一步研究职业性体力活动与健康之间的关联，以提高我们对体力活动对健康的潜在特定领域影响的理解和证据[5,13] 。
我国煤矿行业较为发达，从事煤炭工业的人员众多，这一群体的健康状况也值得关注。另外，大多数煤矿从业人员长期进行大量的体力活动，工作环境恶劣，劳动强度大，吸烟、饮酒比例高，饮水、饮食情况特殊，且该人群职业性体力活动与血脂异常的关系研究缺乏，本研究旨在了解煤矿从业人员职业性体力活动情况，探讨不同强度职业性体力活动与血脂异常的关系，为制定煤矿从业人员健康策略提供参考。
1　对象与方法
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1.1　研究对象
选取2023年期间在西山煤电（集团）职业病防治所进行职业体检的煤矿从业人员为研究对象，41所单位的员工同意参与了体力活动问卷调查。所有研究对象在知晓研究目的及内容后，均自愿参加并签署了知情同意书。煤矿从业人员包括煤矿、选煤厂、矿建公司等煤矿企业工作并获得劳动报酬的全部人员。纳入标准：①参加本次职业体检煤矿从业人员；②知情同意参加本次问卷调查；③工作满一年及以上；④年龄≥18岁。排除标准：①血脂、体力活动情况信息缺失；②基本信息不完整；③离岗、上岗前、行政管理岗人员；④患有严重基础疾病、严重心血管疾病、血液系统疾病、正在调脂治疗的人员。该研究在开始前获得了广东药科大学附属第一医院第一临床医学院医学伦理审查委员会的批准（医伦审【2024】KT第98号）。在严格遵循样本的纳入排除标准后，共有9 864名对象纳入分析。
1.2　研究方法
1.2.1　问卷调查
通过问卷调查于2023年收集并完善研究对象的基本资料，问卷分为两个部分，第一部分由统一培训过的调查员在体检现场进行一对一询问以保证准确度，该部分主要收集身体活动情况、职业史、既往疾病史和近一年的膳食情况，包括：1）闲暇时间体力活动情况、职业性体力活动情况；2）慢性病患病情况、规律服药及治疗情况、近2周药物服用史、家族史；3）工种、工龄、职业危害因素暴露、夜班情况；4）近一年膳食情况：采用食物频率问卷（Food Frequency，FFQ）。第二部分收集基本人口学信息和日常行为习惯，包括：1）人口学信息：性别、民族、出生日期、婚姻状况、学历、家庭月人均收入等；2）生活行为习惯：吸烟、饮酒、饮茶习惯；该部分问卷采用线上形式进行，由单位提前发送问卷二维码至各单位，由调查对象自行填写。
1.2.2　生物标本采集及实验室检测
调查对象需空腹8小时以上，专业医务人员于职业体检现场使用真空采血管对调查对象的空腹血液样本由进行采集，采用日立3500型全自动生化分析仪检测空腹血糖（Fasting blood glucose，FBG）、血脂四项（胆固醇（Total cholesterol，TC）、甘油三酯（Triglyceride，TG）、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇（Low density lipoprotein cholesterol，LDL-C）），采用糖化血红蛋白分析仪MQ-8000检测糖化血红蛋白（Hemoglobin Alc，HbA1c），所有生化指标均由医院临检科专业检验医师在规定时间按照规范流程进行检测，符合生物安全标准，检测结果由体检管理系统导出。
1.2.3　职业性体力活动强度
问卷中体力活动依据国际体力活动调查表（IPAQ）、国家《体力劳动强度分级》标准进行设计[14]。职业性体力活动包括在目前所在岗位有偿工作期间进行的所有体力活动。通过现场问卷调查职业性体力活动相关信息，包括职业性体力活动强度（分为低、中、高体力活动强度），为便于研究对象的理解，问卷有对各职业性体力活动强度进行描述说明，如低强度体力活动包括①坐姿：手工作业或腿的轻度活动（正常情况下，如打字、缝纫、脚踏开关等）②操作仪器，控制、查看设备，上臂用力为主的装配工作；中强度体力活动包括①手和臂持续动作（如锯木头等）②臂和腿的工作（如卡车、拖拉机或建筑设备等运输操作）③臂和躯干的工作（如锻造、风动工具操作、粉刷、尖端搬运中等重物、除草、锄田、摘水果和蔬菜等）；高强度体力活动包括①臂和躯干的负荷工作（搬重物、铲、锤锻、锯刨或凿硬木、割草木、挖掘等）；②大强度挖掘、搬运、快到极限节律的极强活动。
1.2.4　血脂异常诊断标准
血脂异常：依据《中国成人血脂异常防治指南》（2023）[15]，满足下列四项中的一项及以上：总胆固醇≥6.20 mmol/L、低密度脂蛋白胆固醇≥4.10 mmol/L、甘油三酯≥2.30 mmol/L、高密度脂蛋白胆固醇<1.00 mmol/L。
1.2.5　相关变量定义
高血压[16]（Hypertension，HTN）：收缩压（Systolic blood pressure，SBP）≥140 mmHg和舒张压（Diastolic blood pressure，DBP）≥90 mmHg，或自诉既往有高血压史，目前正在服用降压药者。
糖尿病[17]（Diabetes mellitus，DM）：空腹血糖（FBG）≥7.0 mm/L和（或）糖化血红蛋白（HbA1c）≥6.5%，或自诉既往有糖尿病史，目前正服用降糖药或胰岛素治疗者。
超重肥胖：根据《中国成人超重和肥胖症预防与控制指南》[18]将调查对象按身体质量指数（Body Mass Index，BMI）确定消瘦（BMI≤18.4 kg/m2）、正常体重（18.5 kg/m2≤BMI≤23.9 kg/m2）、超重（24 kg/m2≤BMI≤27.9 kg/m2）及肥胖（BMI≥28 kg/m2）。
1.2.6　质量控制
实施严格的数据质量控制措施，包括逻辑性检查和错误数据的排除，以确保数据的准确性和可靠性。在现场调查时，由具备流行病学现场调查基本知识及调查技巧的调查员进行面对面调查，且在调查前进行严格统一的培训，统一标准，提问准确规范，避免诱导式提问。对于获得的数据，检查易错变量及质控题是否填写正确，发现异常值或不合理的数据，需要及时进行排查和处理，确认其来源和原因，并进行必要的纠正或剔除。对问卷调查收集的数据进行清洗和整理，检查数据的完整性、一致性和准确性，并形成可供分析的数据库。
1.2.7　统计分析
应用SPSS 25.0软件进行统计分析，人口学特征采用描述性分析，对计量指标进行Kolmogorov Smirnov（正态性检验），不符合正态分布，用“M（P25，P75）进行描述；分类资料用频数（n）和百分比（%）表示。采用非参数检验、卡方检验比较不同职业性体力活动强度组煤矿从业人员基本情况及血脂异常情况。并且运用logistic回归模型分析煤矿从业人员职业性体力活动情况与血脂异常关联性，模型对年龄、性别、BMI、学历、婚姻、家庭月人均收入、工种、目前岗位工龄、夜班情况、噪声暴露、粉尘暴露、有毒有害气体暴露、吸烟情况、饮酒情况、闲暇时间体力活动、饮茶习惯、红肉摄入频率、油摄入量、糖摄入量、糖尿病、高血压及高尿酸血症因素进行调整，检验水准α=0.05。
2　结果
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2.1　不同职业性体力活动强度组煤矿从业人员基本情况描述
低、中、高强度职业性体力活动强度人数占比分别为38.42%、35.75%、25.83%。不同职业性体力活动强度煤矿从业人员的性别、年龄、学历、家庭月人均收入、婚姻状况、吸烟情况、饮酒情况、饮茶习惯、闲暇时间体力活动、工种、目前岗位工龄、噪声暴露、粉尘暴露、夜班情况、有毒有害气体暴露、糖尿病患病情况、高尿酸血症患病情况、高血压患病情况、精制糖的使用量存在差异（P<0.05），而其在不同BMI、红肉摄入频率、食用油使用量组别间无显著统计学差异（P>0.05），见表1。
2.2　不同职业性体力活动强度组煤矿从业人员血脂水平
表2展示了研究对象总体及低、中、高强度体力活动组的血脂水平，结果显示不同职业性体力活动强度煤矿从业人员的胆固醇、甘油三酯、高密度脂蛋白、低密度脂蛋白水平存在差异（P<0.05）。
2.3　不同职业性体力活动强度组煤矿从业人员血脂异常情况
高TG、高TC、低HDL、高LDL、血脂异常患病率分别为1.40%、24.88%、37.95%、0.77%、49.76%。具体煤矿从业人员血脂异常患病情况，见图1。不同职业性体力活动强度煤矿从业人员的高TG（c2=36.521，P<0.001）、血脂异常（c2=22.013，P<0.001）患病率均存在差异，这种差异在高TC、低HDL、高LDL患病中未显现（P>0.05），见表3。
2.4　煤矿从业人员职业性体力活动强度与血脂异常的logistic回归分析
如表4所示，模型2调整年龄、性别、BMI等因素后，我们发现：相较于低强度职业性体力活动组，中及高强度职业性体力活动组的煤矿从业人员低HDL患病率更低（OR=0.83，95%CI:0.75~0.92；OR=0.78，95%CI:0.70~0.88）；且中及高强度职业性体力活动水平的煤矿从业人员血脂异常患病率更低（OR=0.80，95%CI:0.73~0.88；OR=0.68，95%CI:0.61~0.76）。模型3中增加工种、目前岗位工龄、闲暇时间体力活动等因素调整模型时，这些关联没有显著变化。
但在职业性体力活动强度与高TG的分析中，模型调整后关联性减弱。当模型2调整混杂因素后，相较于低强度职业性体力活动组，中及高强度职业性体力活动组的煤矿从业人员高TG患病率更低（OR=0.85，95%CI:0.77~0.95；OR=0.65，95%CI:0.57~0.74）；在模型3调整混杂因素后，相较于低强度职业性体力活动，中强度职业性体力活动与高TG患病无关（P>0.05），高强度职业性体力活动组与高TG患病风险下降相关（OR=0.81，95%CI:0.70~0.93）。另外，相较于低强度职业性体力活动组，中及高强度职业性体力活动组与高TC、高LDL患病均不存在关联（P>0.05）。
3　讨论
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本研究探索了煤矿从业人员职业性体力活动与血脂异常的关系。结果显示，低、中、高强度职业性体力活动人数占比分别为38.42%、35.75%、25.83%，高TC、高TG、低HDL、高LDL、血脂异常患病率分别为1.40%、24.88%、37.95%、0.77%、49.76%，职业性体力活动与血脂异常存在关联，煤矿从业人员从事高强度职业性体力活动患血脂异常风险更低。因此，对于低强度职业性体力活动煤矿从业人员，建议针对血脂异常的其他可改变行为危险因素进行干预，以维持血脂的健康水平。
另外，我们观察到随着职业性体力活动强度的增加，血脂异常的患病风险有所下降。然而，发现并非所有血脂异常的类型都可以得到预测。本研究中，模型3调整工种、目前岗位工龄、闲暇时间体力活动等混杂后，与低强度职业性体力活动组相比，中及高强度职业性体力活动组煤矿从业人员低HDL患病率降低，中强度职业性体力活动煤矿从业人员患低HDL的风险降低了15%，高强度职业性体力活动煤矿从业人员患低HDL的患病风险降低了17%。与以往的研究结果一致，HDL-C已被观察到最有可能因体力活动而改善的血脂类型，Zou Q的研究表明，与低水平相比，高水平的总体力活动与HDL-C浓度呈正相关，男性低HDL的患病风险降低了31%[3]。Ge研究说明，与无职业性体力活动水平相比，高强度职业性体力活动与HDL-C呈正相关（OR=0.063，95%CI:0.043~0.083）[19]。Opoku等观察发现，日常体力活动与血脂异常患病风险呈负相关。与无日常体力活动相比，日常体力活动将高TC、低HDL、高LDL和高TG的患病风险分别降低了4%、5%、6%和11%[20]。
高浓度的LDL-C会增加心血管并发症的风险。然而，HDL-C将脂质转运回肝脏进行循环和处理[21]，因此HDL-C对心血管系统具有保护作用。尽管目前体力活动对血脂水平的影响机制尚不明显，且职业性体力活动与血脂水平的关系仍存在争议。但一项全基因组研究指出，较高强度的体力活动水平增强了细胞质连接蛋白相关蛋白1（Cytoplasmic linker protein-associated proteins，CLASP1）、LIM同源框1（LIM homeobox 1，LHX1）和α1-互生蛋白（Syntrophinalpha 1，SNTA1）基因位点的HDL-C增加作用，并减弱了接触蛋白相关蛋白2（Contactin-associated protein-like 2，CNTNAP2）位点的LDL-C增加作用。CLASP1、LHX1 和 SNTA1 内附近的基因位点含有与肌肉功能和脂质代谢相关的基因，这与骨骼肌利用血脂作为能量来源的能力差异有关，这将影响体力活动对血脂水平的作用[22]。这将一定程度解释了本研究从事中、高强度职业性体力活动煤矿从业人员低HDL患病风险较低的结果。
在调整混杂因素后发现，高TG的患病风险仅与高强度职业性体力活动有关联，与低强度职业性体力相比，高强度职业性体力活动煤矿从业人员高TG患病率降低，高强度职业性体力活动煤矿从业人员患高TG的风险降低了19%。Jui-Hua Huang等人的研究发现，与低强度的职业性体力活动相比，高强度的职业性体力活动个体腹部肥胖（OR=0.64，95%CI:0.49~0.84）和高TG（OR=0.71，95%CI:0.55~0.90）的风险显著降低，同样支持本研究的结果[23]。
另外我们研究也发现，在调整混杂因素后，与低强度职业性体力活动组相比，中强度职业性体力活动组煤矿从业人员血脂异常患病风险降低16%，高强度职业性体力活动组血脂异常患病风险降低23 %。一项对来自南美人群的7 512名成年人进行的研究发现，高强度职业性体力活动与更好的血脂水平相关[24]。Gómez-Recasens等人研究发现，职业性体力活动强度与血脂异常患病呈负相关[9]。这些均支持我们对煤矿从业人员职业性体力活动的研究发现。
大多研究认为体力活动能维持人体血脂的健康水平[10,25]。既往很多研究论证了闲暇时间体力活动，Stanton等指出中强度和高强度运动都与致动脉粥样硬化血脂谱有关，HDL-C的增加证明了这一点[26]。我们的研究从职业性体力活动也证实了这种关系，即职业性体力活动强度与血脂异常患病呈负相关，中强度和高强度职业性体力活动都与低HDL、血脂异常患病风险降低相关。
哥本哈根城市研究结果中对CVD的部分危险因素支持体力活动健康悖论，闲暇时间体力活动与CVD风险降低相关，职业性体力活动与CVD风险增加相关[8]。而本研究发现职业性体力活动强度与血脂异常患病风险降低相关。评估职业性体力活动与CVD关联的研究结果之间的差异可归因于（1）调查对象的异质性;（2）模型中调整可能混杂变量的差异;（3）职业性体力活动测量的差异。
本研究存在以下局限。首先，职业性体力活动信息是采用主观问卷收集数据，可能存在回忆偏倚，但该信息的问卷调查方式为经过培训后的调查员对受试者进行一对一询问，能一定程度降低偏倚。其次，本研究为横断面研究，无法探明煤矿从业人员职业性体力活动与血脂异常之间的因果关系。最后，本研究仅获取了职业性体力活动强度的数据，维度较为单一，未对职业性体力活动的时间进行量化，这些因素可能影响结果的稳定性。
综上所述，本研究发现煤矿从业人员职业性体力活动强度与血脂异常呈负相关，从事高强度职业性体力活动的煤矿从业人员血脂异常患病风险更低。因此对于从事低强度职业性体力活动的煤矿从业人员，建议针对血脂异常的其他可改变行为危险因素进行干预，以维持血脂的健康水平。需进一步研究职业性体力活动与健康的关系。
基金
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  • 广州市科技计划基金项目(2025A03J3722)
  • 广东省自然科学基金项目(2022A1515011357)
  • 广州市科技计划基金项目(2025A03J3722)
  • 广州市科技局基金项目(SL2022A04J00361)
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参考文献 引证文献
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2025年第52卷第2期
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doi: 10.20043/j.cnki.MPM.202410259
  • 接收时间：2024-10-18
  • 首发时间：2026-03-18
  • 出版时间：2025-01-25
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  • 收稿日期：2024-10-18
基金
广州市科技计划基金项目(2025A03J3722)
广东省自然科学基金项目(2022A1515011357)
广州市科技计划基金项目(2025A03J3722)
广州市科技局基金项目(SL2022A04J00361)
作者信息
    1．广东药科大学公共卫生学院，广东　广州　510310
    2．西山煤电（集团）有限责任公司职业病防治所

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陈青松与刘改生为共同通信作者；陈青松，E-mail：；
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