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Article(id=1241319150983901566, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202501079, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736092800000, receivedDateStr=2025-01-06, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773883148189, onlineDateStr=2026-03-19, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773883148189, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773883148189, creator=13701087609, updateTime=1773883148189, updator=13701087609, issue=Issue{id=1241319148798669160, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='12', pageStart='2113', pageEnd='2304', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773883147667, creator=13701087609, updateTime=1773885555254, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241329247004971040, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241329247004971041, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2159, endPage=2165, ext={EN=ArticleExt(id=1241319151722099091, articleId=1241319150983901566, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A cohort study on systemic immune inflammatory index and risk of hypertension in petrochemical workers, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the quantitative association and dose-response relationship between systemic immune inflammatory index (SII) and the risk of hypertension among petrochemical workers.

Methods

This cohort study included 2 386 occupational workers from a large petrochemical enterprise in southern China. Baseline data were collected in 2018 through occupational health monitoring, and follow-up data were obtained annually through regular physical exams until 2023. The study gathered demographic information, occupational exposure data, blood pressure, blood sugar, blood lipid levels, and SII results via questionnaires, hazard monitoring, physical exams, and laboratory tests. We used multivariate Cox proportional hazard regression models and restricted cubic spline analysis to examine the quantitative association and dose-response relationship between SII and new-onset hypertension. Stratified analyses were performed based on occupational exposure, age, and gender.

Results

During the follow-up period, 645 new cases of hypertension were identified. SII was positively correlated with hypertension risk in a dose-dependent manner. The SII was categorized into three groups (T1, T2, and T3). After adjusting for covariates, the hypertension risk in the T2 and T3 groups was 1.40 (95% CI:1.16-1.70) and 1.30 (95% CI: 1.06-1.58), respectively, compared to the T1 group. The relationship between SII and hypertension risk followed a nonlinear, inverted U-shape: risk increased with higher SII values up to a point, then decreased (P=0.005, nonlinear P=0.007). Subgroup analysis revealed that the patterns observed in workers under 39 years old and male workers were consistent with the overall population. Noise exposure did not affect the association between SII and hypertension risk, but no such association was found among workers exposed to benzene and its homologs.

Conclusion

SII is positively correlated with hypertension risk in petrochemical workers in a dose-dependent manner, exhibiting a nonlinear dose-response relationship. These findings provide a basis for using SII in hypertension risk assessment and prevention strategies in petrochemical workers.

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目的

探究石化工人全身免疫炎症指数（SII）与高血压发病风险的定量关联和剂量-反应关系。

方法

基于前期在我国南方某大型石化企业建立的职业人群队列（n=2 386），以2018年开展的职业健康监测为基线调查，每年定期职业体检为随访调查至2023年。通过问卷调查、职业有害因素监测、体格检查和实验室检测，获取研究对象的人口基本信息、职业暴露评估、血压、血糖、血脂和SII检测结果。采用多因素Cox比例风险回归模型和限制性立方样条分析分别探索SII与石化工人新发高血压的定量关联和剂量反应关系，并依据职业接触信息、年龄、性别开展分层分析。

结果

随访期内累计新发高血压645例，SII与高血压发病风险呈剂量依赖性正相关。将SII等分为3组（T1、T2、T3），当调整协变量后，T2和T3组的高血压发病风险[HR(95% CI)]相较于T1组分别为1.40(1.16~1.70)和1.30(1.06~1.58)。随着SII增加，高血压的发病风险先上升后下降，呈倒U字形的非线性变化 (P=0.005, 非线性P=0.007)。亚组分析显示男性及39岁以下石化工人的研究结果与总人群一致。接触噪声与否不影响SII与高血压发病风险的关联，且未观察到苯系物接触工人SII与高血压发病风险相关。

结论

SII与石化工人高血压的发病风险呈剂量依赖性正相关，表现为先上升后下降的非线性剂量反应关系。研究结果为SII在石化工人高血压风险评估和预防中的应用提供了研究基础。

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卢次勇，E-mail：
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肖明慧（1988—），女，硕士，副主任医师，研究方向：职业健康风险评估

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肖明慧（1988—），女，硕士，副主任医师，研究方向：职业健康风险评估

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Risk factors analysis and risk prediction of hypertension in occupational population of petroleum enterprises[J]. Industrial Health and Occupational Diseases, 2023, 49(2): 130-134. (In Chinese), articleTitle=Risk factors analysis and risk prediction of hypertension in occupational population of petroleum enterprises, refAbstract=null)], funds=[Fund(id=1241319163751363511, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, awardId=A2024233, language=CN, fundingSource=广东省医学科学技术研究基金(A2024233), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241319155245314549, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, xref=1., ext=[AuthorCompanyExt(id=1241319155253703158, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, companyId=1241319155245314549, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Sun Yat-sen University, Guangzhou，Guangdong 510080, China), AuthorCompanyExt(id=1241319155278868985, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, companyId=1241319155245314549, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中山大学公共卫生学院，广东 广州 510080)]), AuthorCompany(id=1241319155383726593, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, xref=2., ext=[AuthorCompanyExt(id=1241319155396309506, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, companyId=1241319155383726593, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广东省职业病防治院)])], figs=[ArticleFig(id=1241319160664355633, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=EN, label=Fig.1, caption=Analysis of SII and RCS curves of new-onset hypertension, figureFileSmall=eNQbeEuFqDEItiXeaeIzUg==, figureFileBig=Sc82kYe/JDOh1QsFKcbMbg==, tableContent=null), ArticleFig(id=1241319162195276607, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=CN, label=图1, caption=SII与新发高血压的RCS曲线分析

注：(A) 为未校正协变量时HR随SII增加而变化的曲线图（模型1），(B)为校正所有协变量时HR随SII增加而变化的曲线图（模型3）；图中实线为剂量效应关系拟合曲线，阴影部分为95%置信区间。

, figureFileSmall=eNQbeEuFqDEItiXeaeIzUg==, figureFileBig=Sc82kYe/JDOh1QsFKcbMbg==, tableContent=null), ArticleFig(id=1241319162476294997, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=EN, label=Table 1, caption=

The Basic characteristics and SII levels in the research subjects

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
（n=2 386）		未发病人群
（n=1 741）		高血压新发人群
（n=645）		统计量P值
年龄(岁，)41.64±8.1640.88±8.3843.68±7.187.522<0.001
工龄(年，)21.13±9.3120.29±9.5423.38±8.267.284<0.001
性别[n(%)]34.190<0.001
女314(13.2)272(15.6)42(6.5)
男2 072(86.8)1 469(84.4)603(93.5)
苯系物接触[n(%)]0.9470.331
未暴露1 805(75.65)1 308(75.1)497(77.1)
暴露581(24.35)433(24.9)148(22.9)
噪声接触[n(%)]0.3650.546
未暴露986(41.32)713(41.0)273(42.3)
暴露1 400(58.68)1 028(59.0)372(57.7)
吸烟[n(%)]3.8870.049
未吸烟1 753(73.47)1 298(74.6)455(70.5)
吸烟633(26.53)443(25.4)190(29.5)
饮酒[n(%)]1.6630.197
未饮酒1 595(66.85)1 177(67.6)418(64.8)
饮酒791(33.15)564(32.4)227(35.2)
糖尿病[n(%)]21.604<0.001
否2 331(97.69)1 716(98.6)615(95.3)
是55(2.31)25(1.4)30(4.7)
血脂异常[n(%)]30.747<0.001
否1 686(70.66)1 285(73.8)401(62.2)
是700(29.34)456(26.2)244(27.8)
中性粒细胞(109/L，)3.81±1.203.77±1.213.92±1.172.6980.007
血小板(109/L，)248.03±52.42247.15±52.35250.40±52.561.3440.179
淋巴细胞(109/L，)2.54±0.692.53±0.692.57±0.691.0720.284
SII(）397.37±194.14394.70±199.76404.59±178.041.1060.269
), ArticleFig(id=1241319162656650082, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=CN, label=表1, caption=

研究对象新发高血压人口基本特征及SII水平

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
（n=2 386）		未发病人群
（n=1 741）		高血压新发人群
（n=645）		统计量P值
年龄(岁，)41.64±8.1640.88±8.3843.68±7.187.522<0.001
工龄(年，)21.13±9.3120.29±9.5423.38±8.267.284<0.001
性别[n(%)]34.190<0.001
女314(13.2)272(15.6)42(6.5)
男2 072(86.8)1 469(84.4)603(93.5)
苯系物接触[n(%)]0.9470.331
未暴露1 805(75.65)1 308(75.1)497(77.1)
暴露581(24.35)433(24.9)148(22.9)
噪声接触[n(%)]0.3650.546
未暴露986(41.32)713(41.0)273(42.3)
暴露1 400(58.68)1 028(59.0)372(57.7)
吸烟[n(%)]3.8870.049
未吸烟1 753(73.47)1 298(74.6)455(70.5)
吸烟633(26.53)443(25.4)190(29.5)
饮酒[n(%)]1.6630.197
未饮酒1 595(66.85)1 177(67.6)418(64.8)
饮酒791(33.15)564(32.4)227(35.2)
糖尿病[n(%)]21.604<0.001
否2 331(97.69)1 716(98.6)615(95.3)
是55(2.31)25(1.4)30(4.7)
血脂异常[n(%)]30.747<0.001
否1 686(70.66)1 285(73.8)401(62.2)
是700(29.34)456(26.2)244(27.8)
中性粒细胞(109/L，)3.81±1.203.77±1.213.92±1.172.6980.007
血小板(109/L，)248.03±52.42247.15±52.35250.40±52.561.3440.179
淋巴细胞(109/L，)2.54±0.692.53±0.692.57±0.691.0720.284
SII(）397.37±194.14394.70±199.76404.59±178.041.1060.269
), ArticleFig(id=1241319162803450734, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=EN, label=Table 2, caption=

Cox regression analysis of SII and risk of hypertension

, figureFileSmall=null, figureFileBig=null, tableContent=
SII分组样本量（n）新发病例(n)模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
T1(51.17~300.49)796183参考参考参考
T2(300.50~423.61)7952451.38(1.14~1.67)1.40(1.16~1.70)1.40(1.16~1.70)
T3(423.81~2419.00)7952171.20(0.99~1.46)1.29(1.05~1.57)1.30(1.06~1.58)
P trend0.0750.0140.012
), ArticleFig(id=1241319162941862778, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=CN, label=表2, caption=

SII与高血压发病风险的Cox回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
SII分组样本量（n）新发病例(n)模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
T1(51.17~300.49)796183参考参考参考
T2(300.50~423.61)7952451.38(1.14~1.67)1.40(1.16~1.70)1.40(1.16~1.70)
T3(423.81~2419.00)7952171.20(0.99~1.46)1.29(1.05~1.57)1.30(1.06~1.58)
P trend0.0750.0140.012
), ArticleFig(id=1241319163126412171, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=EN, label=Table 3, caption=

Cox regression subgroup analysis of SII and risk of hypertension in different gender and age subgroups

, figureFileSmall=null, figureFileBig=null, tableContent=
分类亚组SII分组样本量
（n)		新发病例
（n)		模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
年龄<39岁T1(51.17~300.49)24729参考
T2(300.50~423.61)236562.13(1.36~3.34)2.16(1.38~3.39)2.08(1.33~3.27)
T3(423.81~2419.00)227451.76(1.10~2.81)2.02(1.26~3.23)1.90(1.18~3.05)
P trend0.0220.0040.009
≥40岁T1(51.17~300.49)549154参考
T2(300.50~423.61)5591891.22(0.99~1.51)1.26(1.02~1.56)1.16(1.02~1.46)
T3(423.81~2 419.00)5681721.08(0.87~1.34)1.17(0.94~1.45)1.17(0.94~1.46)
P trend0.5240.1760.163
性别女性T1(51.17~300.49)646参考
T2(300.50~423.61)88161.99(0.78~5.08)1.79(0.70~4.56)1.77(0.69~4.56)
T3(423.81~2 419.00)162201.32(0.53~3.28)1.20(0.48~2.98)1.11(0.45~2.79)
P trend0.8730.9680.804
男性T1(51.17~300.49)732177参考
T2(300.50~423.61)7072291.38(1.14~1.68)1.38(1.14~1.68)1.38(1.13~1.68)
T3(423.81~2 419.00)6331971.32(1.08~1.62)1.31(1.07~1.60)1.31(1.07~1.61)
P trend0.0070.0100.009
), ArticleFig(id=1241319163285795731, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=CN, label=表3, caption=

不同性别和年龄亚组SII与高血压发病风险的Cox回归亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
分类亚组SII分组样本量
（n)		新发病例
（n)		模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
年龄<39岁T1(51.17~300.49)24729参考
T2(300.50~423.61)236562.13(1.36~3.34)2.16(1.38~3.39)2.08(1.33~3.27)
T3(423.81~2419.00)227451.76(1.10~2.81)2.02(1.26~3.23)1.90(1.18~3.05)
P trend0.0220.0040.009
≥40岁T1(51.17~300.49)549154参考
T2(300.50~423.61)5591891.22(0.99~1.51)1.26(1.02~1.56)1.16(1.02~1.46)
T3(423.81~2 419.00)5681721.08(0.87~1.34)1.17(0.94~1.45)1.17(0.94~1.46)
P trend0.5240.1760.163
性别女性T1(51.17~300.49)646参考
T2(300.50~423.61)88161.99(0.78~5.08)1.79(0.70~4.56)1.77(0.69~4.56)
T3(423.81~2 419.00)162201.32(0.53~3.28)1.20(0.48~2.98)1.11(0.45~2.79)
P trend0.8730.9680.804
男性T1(51.17~300.49)732177参考
T2(300.50~423.61)7072291.38(1.14~1.68)1.38(1.14~1.68)1.38(1.13~1.68)
T3(423.81~2 419.00)6331971.32(1.08~1.62)1.31(1.07~1.60)1.31(1.07~1.61)
P trend0.0070.0100.009
), ArticleFig(id=1241319163440984993, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=EN, label=Table 4, caption=

Cox regression subgroup analysis of SII and risk of hypertension in different subgroups of exposure to different occupational hazards

, figureFileSmall=null, figureFileBig=null, tableContent=
分类亚组样本量
（n)		新发病例
（n)		模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
是否接触苯系物
不接触T1(51.17~300.49)626143参考
T2(300.50~423.61)5991881.41(1.14~1.75)1.44(1.16~1.78)1.43(1.15~1.78)
T3(423.81~2419.00)5801661.27(1.02~1.59)1.357(1.08~1.70)1.36(1.08~1.70)
P trend0.0350.0080.008
接触T1(51.17~300.49)17040参考
T2(300.50~423.61)196571.28(0.85~1.91)1.29(0.86~1.94)1.30(0.87~1.95)
T3(423.81~2419.00)215511.01(0.67~1.53)1.09(0.72~1.65)1.08(0.71~1.63)
P trend0.9760.7450.783
是否接触噪声
不接触T1(51.17~300.49)31372参考
T2(300.50~423.61)317951.33(0.98~1.81)1.35(0.99~1.83)1.34(0.99~1.82)
T3(423.81~2419.00)3561061.31(0.97~1.76)1.37(1.02~1.86)1.37(1.01~1.85)
P trend0.0930.0450.049
接触T1(51.17~300.49)483111参考
T2(300.50~423.61)4781501.41(1.10~1.80)1.43(1.12~1.83)1.44(1.13~1.84)
T3(423.81~2419.00)4391111.12(0.86~1.45)1.22(0.94~1.59)1.23(0.95~1.61)
P trend0.3830.1230.104
), ArticleFig(id=1241319163566814120, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319150983901566, language=CN, label=表4, caption=

接触不同职业有害因素亚组SII与高血压发病风险的Cox回归亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
分类亚组样本量
（n)		新发病例
（n)		模型1
HR（95% CI）		模型2
HR（95% CI）		模型3
HR（95% CI）
是否接触苯系物
不接触T1(51.17~300.49)626143参考
T2(300.50~423.61)5991881.41(1.14~1.75)1.44(1.16~1.78)1.43(1.15~1.78)
T3(423.81~2419.00)5801661.27(1.02~1.59)1.357(1.08~1.70)1.36(1.08~1.70)
P trend0.0350.0080.008
接触T1(51.17~300.49)17040参考
T2(300.50~423.61)196571.28(0.85~1.91)1.29(0.86~1.94)1.30(0.87~1.95)
T3(423.81~2419.00)215511.01(0.67~1.53)1.09(0.72~1.65)1.08(0.71~1.63)
P trend0.9760.7450.783
是否接触噪声
不接触T1(51.17~300.49)31372参考
T2(300.50~423.61)317951.33(0.98~1.81)1.35(0.99~1.83)1.34(0.99~1.82)
T3(423.81~2419.00)3561061.31(0.97~1.76)1.37(1.02~1.86)1.37(1.01~1.85)
P trend0.0930.0450.049
接触T1(51.17~300.49)483111参考
T2(300.50~423.61)4781501.41(1.10~1.80)1.43(1.12~1.83)1.44(1.13~1.84)
T3(423.81~2419.00)4391111.12(0.86~1.45)1.22(0.94~1.59)1.23(0.95~1.61)
P trend0.3830.1230.104
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石化工人全身免疫炎症指数和高血压发病风险的队列研究
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肖明慧 1, 2 , 曹丹燕 2 , 吴雪华 2 , 杨爱初 2 , 郭集军 2 , 王恰 2 , 卢次勇 1
现代预防医学 | 环境与职业卫生 2025,52(12): 2159-2165
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现代预防医学 | 环境与职业卫生 2025, 52(12): 2159-2165
石化工人全身免疫炎症指数和高血压发病风险的队列研究
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肖明慧1, 2, 曹丹燕2, 吴雪华2, 杨爱初2, 郭集军2, 王恰2, 卢次勇1
作者信息
  • 1.中山大学公共卫生学院，广东 广州 510080
  • 2.广东省职业病防治院

    • 肖明慧（1988—），女，硕士，副主任医师，研究方向：职业健康风险评估

通讯作者:

卢次勇，E-mail：
A cohort study on systemic immune inflammatory index and risk of hypertension in petrochemical workers
Ming-hui XIAO1, 2, Dan-yan CAO2, Xue-hua WU2, Ai-chu YANG2, Ji-jun GUO2, Qia WANG2, Ci-yong LU1
Affiliations
  • School of Public Health, Sun Yat-sen University, Guangzhou，Guangdong 510080, China
出版时间: 2025-06-25 doi: 10.20043/j.cnki.MPM.202501079
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摘要
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目的

探究石化工人全身免疫炎症指数（SII）与高血压发病风险的定量关联和剂量-反应关系。

方法

基于前期在我国南方某大型石化企业建立的职业人群队列（n=2 386），以2018年开展的职业健康监测为基线调查，每年定期职业体检为随访调查至2023年。通过问卷调查、职业有害因素监测、体格检查和实验室检测，获取研究对象的人口基本信息、职业暴露评估、血压、血糖、血脂和SII检测结果。采用多因素Cox比例风险回归模型和限制性立方样条分析分别探索SII与石化工人新发高血压的定量关联和剂量反应关系，并依据职业接触信息、年龄、性别开展分层分析。

结果

随访期内累计新发高血压645例，SII与高血压发病风险呈剂量依赖性正相关。将SII等分为3组（T1、T2、T3），当调整协变量后，T2和T3组的高血压发病风险[HR(95% CI)]相较于T1组分别为1.40(1.16~1.70)和1.30(1.06~1.58)。随着SII增加，高血压的发病风险先上升后下降，呈倒U字形的非线性变化 (P=0.005, 非线性P=0.007)。亚组分析显示男性及39岁以下石化工人的研究结果与总人群一致。接触噪声与否不影响SII与高血压发病风险的关联，且未观察到苯系物接触工人SII与高血压发病风险相关。

结论

SII与石化工人高血压的发病风险呈剂量依赖性正相关，表现为先上升后下降的非线性剂量反应关系。研究结果为SII在石化工人高血压风险评估和预防中的应用提供了研究基础。

石化工人  /  高血压  /  全身免疫炎症指数  /  发病风险  /  队列研究
Objective

To explore the quantitative association and dose-response relationship between systemic immune inflammatory index (SII) and the risk of hypertension among petrochemical workers.

Methods

This cohort study included 2 386 occupational workers from a large petrochemical enterprise in southern China. Baseline data were collected in 2018 through occupational health monitoring, and follow-up data were obtained annually through regular physical exams until 2023. The study gathered demographic information, occupational exposure data, blood pressure, blood sugar, blood lipid levels, and SII results via questionnaires, hazard monitoring, physical exams, and laboratory tests. We used multivariate Cox proportional hazard regression models and restricted cubic spline analysis to examine the quantitative association and dose-response relationship between SII and new-onset hypertension. Stratified analyses were performed based on occupational exposure, age, and gender.

Results

During the follow-up period, 645 new cases of hypertension were identified. SII was positively correlated with hypertension risk in a dose-dependent manner. The SII was categorized into three groups (T1, T2, and T3). After adjusting for covariates, the hypertension risk in the T2 and T3 groups was 1.40 (95% CI:1.16-1.70) and 1.30 (95% CI: 1.06-1.58), respectively, compared to the T1 group. The relationship between SII and hypertension risk followed a nonlinear, inverted U-shape: risk increased with higher SII values up to a point, then decreased (P=0.005, nonlinear P=0.007). Subgroup analysis revealed that the patterns observed in workers under 39 years old and male workers were consistent with the overall population. Noise exposure did not affect the association between SII and hypertension risk, but no such association was found among workers exposed to benzene and its homologs.

Conclusion

SII is positively correlated with hypertension risk in petrochemical workers in a dose-dependent manner, exhibiting a nonlinear dose-response relationship. These findings provide a basis for using SII in hypertension risk assessment and prevention strategies in petrochemical workers.

Petrochemical workers  /  Hypertension  /  Systemic Immune Inflammatory Index  /  Risk assessment  /  Cohort study
肖明慧, 曹丹燕, 吴雪华, 杨爱初, 郭集军, 王恰, 卢次勇. 石化工人全身免疫炎症指数和高血压发病风险的队列研究. 现代预防医学, 2025 , 52 (12) : 2159 -2165 . DOI: 10.20043/j.cnki.MPM.202501079
Ming-hui XIAO, Dan-yan CAO, Xue-hua WU, Ai-chu YANG, Ji-jun GUO, Qia WANG, Ci-yong LU. A cohort study on systemic immune inflammatory index and risk of hypertension in petrochemical workers[J]. Modern Preventive Medicine, 2025 , 52 (12) : 2159 -2165 . DOI: 10.20043/j.cnki.MPM.202501079
正文
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高血压是引发全球过早死亡和残疾的主要且可预防的风险因素之一[1]。2019年中国15~49岁人群高血压的归因死亡率相较于1990年增长14.50%，增长率高于其他年龄人群[2]。职业工人工作环境中接触有害因素以及轮班等诸多因素导致其更易受到高血压的威胁。患病率较高的职业依次为机动车驾驶员（28.7%）、特定机械师及维修工人（28.4%）、清洁及建筑服务行业（27.6%）、制造装配工人（27.5%）[3]。石化工人长期接触的苯及其同系物（苯系物）以及噪声等职业有害因素可增加工人的高血压患病风险[4-8]。因此，加强高血压预防控制对促进石化工人的职业健康具有重要的公共卫生意义。低度炎症和免疫反应在诱发高血压和维持高血压生理状态中扮演着关键角色[9-10]。全身免疫炎症指数（Systemic immune-inflammation index, SII）是一种基于中性粒细胞、淋巴细胞和血小板计数评估炎症的一种指标，能够更客观反映机体炎性变化，是评估高血压发病风险的潜在生物标志物之一[11]。但是，SII在石化工人中与高血压发病风险的剂量反应关系仍不明晰，其表征接触不同有害因素的石化工人高血压风险的潜能还有待进一步研究。因此，本研究基于前期在我国南方某大型石化企业建立的人群队列，探究石化工人的高血压发病风险及其与SII间的量效关系，为石化工人的高血压发病风险评估和防控提供研究数据。
1　材料与方法
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1.1　研究设计和研究对象
本研究基于前期在广东省建立的石化工人职业队列开展；该队列以2018年参加职业健康检查的车间工人为研究对象，以该年的职业健康体检为基线调查，每年随访1次、随访至2023年共计5次随访。研究对象的纳入标准如下：（1）基线调查时年龄≥18岁且未被专业医疗机构诊断为高血压；（2）在研究期间进行的5次随访检查中，均完成血常规、血糖、血脂、既往病史、职业史调查；（3）研究期间并未变更岗位或更换职业暴露因素。排除标准如下：（1）职业史中具有粉尘暴露；（2）具有严重神经精神疾患或无法沟通者；（3）明确拒绝调查工人；（4）具有严重传染病、肿瘤末期患者及孕妇。本研究共纳入2 386名石化工人；研究方案得到了中山大学伦理学审查办公室批准（No.2018118），所有研究对象签署知情同意书。
1.2　苯系物和噪声监测
按照GBZ/T300.66-2017《工作场所空气有毒物质测定 第66部分：苯、甲苯、二甲苯和乙苯》测量所有岗位的苯系物含量，将采用FDS-30的粉尘采样器的吸入口放置在被检查工人的呼吸带位置，收集有害气体，采用型号为7890B气相色谱仪分析采集样品的苯系物含量。按照GBZ/T 189.8-2007《工作场所物理因素测量 第8部分：噪声》测量所有岗位噪声值，采用Soundpro声级计测量现场噪声，以EDGE个体噪声计测量研究对象的个体噪声实际接触水平，即等效连续A声级（LAeq）。等效连续A声级按照GBZ/T 189.8-2007《工作场所物理因素测量 第8部分：噪声》公式换算成8h等效声级，LAeq,8h≥80 dB即为噪声暴露。
1.3　问卷检查
健康调查问卷基于前期文献调研和自身专业知识并参照《环境与健康调查 横断面调查(HJ 839-2017)》的要求与原则制定，主要内容包括：基本情况、行为习惯、职业史和既往病史和家族史等。问卷调查由广东省职业病防治院的专业医护人员通过面对面的访谈形式进行；问卷填写完毕并通过质量核查后方可入库，不合格问卷需研究对象补充相应的信息。问卷信息使用 EpiData software V 3.1 软件建立数据库并由双人录入信息，并进行质量控制和质量检查。
1.4　血压测量
研究对象在基线和后续每个随访时间节点，由本单位专业体检医生在安静舒适的诊室中坐姿使用电子血压计（欧姆龙）进行测量。每次测量时间均为早上8点到11点30分。每次测量时，袖带均与心脏同水平面。测量时，参与者均被要求在测量前至少30分钟内避免吸烟、饮用酒、咖啡、茶等饮料和剧烈运动。测量时，均至少测量三次，并记录最低值。高血压判定标准：经专业人员测量血压后，收缩压≥140 mm Hg和（或）舒张压≥90 mm Hg或研究对象自我报告且出具正规医疗机构高血压诊断报告。
1.5　样本采集及指标检测
由护士在职业健康体检过程中采集研究对象的空腹肘静脉抗凝和促凝血液各5 mL并通过专业的冷链运输公司运送至实验室。血样采集当天完成使用全自动血液参数分析仪和血生化自动检测仪完成血细胞计数、血糖、血脂等指标检测。按照公式1计算SII；依据研究对象SII的三分位数（33.33%和66.66%）将全体研究对象分为3组，分别命名为T1、T2、T3组。本研究参照《中国2型糖尿病防治指南（2020 版）》中将空腹血糖≥ 7.0 mmol/L 或糖化血红蛋白（HbA1c）≥ 6.5%以及出具的专业机构的糖尿病诊疗报告的研究对象明确为糖尿病患者[12]；类似地，依据《中国成人血脂异常防治指南（2016年修订版）》[13]将血脂指标出现以下任何一项诊断为血脂异常：血清总胆固醇（TC）≥6.20 mmol/L；血清甘油三酯（TG）≥2.30 mmol/L；低密度脂蛋白胆固醇（LDL-C）≥ 4.10 mmol/L；高密度脂蛋白胆固醇（HDL-C）< 1.00 mmol/L。SII=中性粒细胞计数×血小板计数÷淋巴细胞计数，式中，细胞数以109/L为计量单位。
1.6　统计分析
对于正态或近似正态的资料，使用平均数和标准差（）描述，并采用t检验进行组间均数的比较。对于非正态分布的计量资料，使用中位数（M）和四分位数间距（IQR）进行描述，并采用Wilcoxon秩和检验进行组间的比较。计数资料使用百分比（%）表示，组间比较采用χ2检验。以T1组作为参照，采用Cox比例风险回归模型分析SII分组与新发高血压的关系。采用限制性立方样条探究SII与新发高血压非线性剂量反应关系。本研究依据年龄、性别和是否存在噪声或苯系物接触对研究对象进行分层分析。统计分析中对研究对象的年龄、性别、体质指数（BMI）、吸烟、饮酒、是否噪声接触、是否高温接触、是否糖尿病患者、是否血脂异常等。使用SPSS 24.0和R 4.3进行数据分析，检验水准α=0.05（双侧）。
2　结果
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表1所示，研究对象基线的平均年龄为41.64±8.16岁，平均工龄为21.13±9.31年，男性为2 072人（86.8%），吸烟工人为633人；其中，高血压新发645例人，发病人群的基线平均年龄、平均工龄和男性及吸烟工人比例均高于未发病人群。但新发高血压人群中糖尿病和血脂异常的现患率显著高于未发病人群。总人群的中性粒细胞、血小板和淋巴细胞计数基线水平分别为（3.81±1.20）×109/L、（248.03±52.42）×109/L和（2.54±0.69）×109/L，新发高血压人群基线中心粒细胞计数的平均水平显著高于未发病人群。未发病人群和新发高血压人群SII的基线水平分别为394.70±199.76和SII为404.59±178.04，两组差异无统计学意义。
表2展示了SII与高血压发病风险的cox回归分析的结果。在未调整协变量时，T2组相较于T1组高血压的发病风险为1.38倍，HR(95% CI)为1.38(1.14~1.67)。逐步调整协变量后，SII与高血压发病率的关联强度依然稳健。例如在完全调整协变量的模型3中，T2和T3组的高血压发病风险分别为T1组的1.40倍和1.30倍，HR(95% CI)分别为1.40(1.16~1.70)和1.30倍，HR(95% CI)为1.30(1.06~1.58)。RCS模型进一步拟合了SII与新发高血压的非线性剂量反应关系（图1）。如图1(B)所示，当校正所有协变量后，随着SII增加，新发高血压的HR呈先上升后下降，呈倒U字形的非线性变化特征(P =0.005, 非线性P =0.007)。
表3分析了不同性别与年龄的石化工人SII与高血压发病风险的关联。研究发现在<39岁组的工人中，SII与高血压发病风险呈显著趋势性相关（P trend <0.05），T2和T3组的高血压发病风险的HR(95% CI)为2.08(1.33~3.27)和1.90 (1.18~3.05)。在≥40岁组的工人中仅发现T2组的SII与高血压发病率存在正相关，HR (95% CI)为1.16(1.02~1.46)。而在男性工人发现SII与高血压发病风险显著正相关，关联强度和趋势性检验与总人群中基本一致；但未观察到在女性中存在显著关联。
表4分析了接触不同有害因素下SII与高血压发病风险的关联。在不接触苯系物的石化工人，本研究发现SII与高血压发病率呈显著正相关（P trend <0.05），其中T2和T3组的HR(95% CI)相较T1组分别为1.15(1.15~1.78)和 1.36(1.08~1.70)。而在苯系物接触人群中，尚未发现SII与高血压发病率具有统计学意义。此外，在不接触噪声的石化工人中也发现SII与高血压发病率呈显著正相关（P trend <0.05），T3组的HR(95% CI)为1.37(1.01~1.85)；并且在接触噪声的石化工人中，尽管未发现显著趋势（P trend >0.05），但T2组中SII与高血压发病风险显著相关HR(95% CI)为1.44(1.13~1.84)。
3　讨论
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本研究发现在SII与石化工人的高血压发病风险呈剂量依赖性相关，较高的SII石化工人高血压发病风险更高。一项横断面研究发现 SII与高血压患病率之间存在正相关，较高SII指数的人群高血压患病风险要高1.20倍[14]；并且，SII与非睡眠周期性高血压的发病率相关，可以作为该疾病早期预警参数，提示了SII在高血压防治方面的潜力[15]。由SII计算公式可知，当中性粒细胞和血小板增加、淋巴细胞减少时，SII则会增加。与此同时，炎症指标或炎症细胞与高血压之间的正向关联已经被陆续报道。Bautista等首次提出C反应蛋白可能是高血压的独立危险因素[16]并在韩国的研究中得到证实[17]。Kawada等指出外周血中性粒细胞计数与高血压风险成正相关[18]。Bautista等还发现TNF-α和白细胞介素-6可能是健康受试者高血压的独立危险因素[19]。动物模型进一步验证了中性粒细胞在促进高血压血管疾病的发生中的作用[20]。因此，本研究进一步揭示了SII在石化工人高血压发病风险的定量关联，提示了其在高血压健康风险评估以及风险管控中的应用前景。
本研究还指出随着SII的增加高血压的发病风险呈先增加后减少的倒U型变化趋势。在美国成年人中也发现SII水平升高与高血压风险之间存在非线性关联[21]。另有研究指出SII在501.2有截断值，临界点左侧的SII与高血压的患病率无关，在临界值右侧的高血压患病率随SII的增加而增加，并且这种非线性关联在不同性别、年龄、BMI、糖尿病和心血管疾病亚组中仍然稳定存在[22]。中性粒细胞作为SII的关键参数之一，其病理性增加是许多急慢性疾病恶化的临床特征[23-24]。当机体受到感染时，中性粒细胞是最快增殖的细胞，并聚集在感染部位[25-26]。同时，人体免疫炎症水平极易受到外界的干扰，尤其是长期暴露于有害因素的人群。Ou-Yang等发现HIV感染者的淋巴细胞和单核细胞在长期受到病理性影响的情况下，仍然被观察到炎症指标全身炎症反应指数、C反应蛋白和中性粒细胞与单核细胞比值与高血压风险呈正相关[27]。因此，过高的SII是因人体受外界感染、粉尘吸入等暂时性病理变化因素的影响，促进炎症因子的产生而引起，这或可解释SII与高血压的关系呈非线性关系，即过高或过低的SII均无法预测高血压发病风险。未来应进一步在石化工人等研究人群中探究SII与高血压发病的阈值效应。
在39岁以下的工人中，SII与高血压的发病率呈正相关。年龄是时间积累的表现，长期保持慢性炎症状态的人群更容易罹患高血压。慢性炎症现在被理解为一种潜在的病理状况，炎症细胞分泌过多促炎介质可在较长时间内影响血管，并推动动脉血管硬化的发展[28]。由于脂质和纤维元素在血管壁中积累，导致血管内壁不可逆的增厚，堵塞血流和降低血管弹性引起高血压[29]。SII反应了全身炎症水平，衰老会加重全身炎症反应，全身炎症的水平随年龄增长而增加[30]。因此，在较为年长的石化工人中过高的SII无法表征高血压的发病风险，反而在中青年工人中的升高与新发高血压显著正相关。
本研究存在如下的局限性：第一,本研究通过问卷形式调查获取研究对象的基本情况，例如吸烟和饮酒状态，未对血液中的可替宁进行实测，调整的协变量可能存在报告偏倚；第二，职业暴露信息，尤其是苯系物的暴露评估主要依据作业环境中毒害物质环境监测，缺乏生物监测数据，可能对研究对象存在暴露错分；第三，高血压等慢性疾病发病周期长，基线调查时可能已有潜伏病例并且随访期内可能并未收集到所有潜在的新发病例；第四，石化厂内男性工人为主，对女性工人的风险评估受限于样本量在外推时存在不确定性。第五，本研究主要依据单一的职业人群队列，研究对象年龄、性别组成、高血压的检出率等与海南、华北等地的石化工人存在差异[31-32]，在引用本研究结果时需充分考虑研究人群存在的选择偏倚。
4　结论
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基于我国南方某大型石化企业的职业人群队列研究发现全身免疫炎症指数与高血压的发病风险呈剂量依赖性相关，表现为先上升后下降的非线性剂量反应关系，并且相关性在男性和中青年工人中的关联更为显著。研究结果提示了SII具有作为表征石化工人高血压发病风险的生物标志物的潜能，未来还需要从分子机制方面对本研究结果予以验证和确认。
基金
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  • 广东省医学科学技术研究基金(A2024233)
文献
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2025年第52卷第12期
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doi: 10.20043/j.cnki.MPM.202501079
  • 接收时间：2025-01-06
  • 首发时间：2026-03-19
  • 出版时间：2025-06-25
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  • 收稿日期：2025-01-06
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广东省医学科学技术研究基金(A2024233)
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    1.中山大学公共卫生学院，广东 广州 510080
    2.广东省职业病防治院

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卢次勇，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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