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Article(id=1241035815745286824, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202407487, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1722009600000, receivedDateStr=2024-07-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815595804, onlineDateStr=2026-03-18, pubDate=1733760000000, pubDateStr=2024-12-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815595804, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815595804, creator=13701087609, updateTime=1773815595804, updator=13701087609, issue=Issue{id=1241035810628235909, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='23', pageStart='4225', pageEnd='4416', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815594584, creator=13701087609, updateTime=1773815743629, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036435843764756, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036435843764757, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4279, endPage=4285, ext={EN=ArticleExt(id=1241035816215048890, articleId=1241035815745286824, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Impact of air pollution on blood pressure control in hypertensive patients and its interactions: a study based on the China Health and Nutrition Survey, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the impact of air pollution on blood pressure control in hypertensive patients.

Methods

Data from the China Health and Nutrition Survey collected between 2011 and 2015 were analyzed, including 2 860 participants from Shanghai, of which 831 were hypertensive patients. Air pollution monitoring data for Shanghai during the same period were obtained from the National Urban Air Quality Release Platform. Demographic information, daily habits, health status, and hypertension-related data were collected via questionnaires. Logistic regression was employed to analyze the effect of air pollutants on achieving blood pressure targets, and a mixed-effects model was used to study interactions among air pollutants and their interactions with antihypertensive medications.

Results

A total of 831 adult hypertensive patients were included, with a blood pressure control rate of 35.14%. The odds ratios (OR) and 95% confidence intervals (CI) for O3 exposure on day 0, the previous 7 days, and the previous 60 days were 1.012 (1.005-1.020), 1.009 (1.002-1.016), and 1.013 (1.003-1.022), respectively. For CO during the same periods, the OR and 95%CI were 1.084 (1.030-1.140), 1.064 (1.030-1.100), and 1.126 (1.050-1.208), respectively. The OR and 95%CI for SO2 on day 0 and the previous 7 days were 1.056 (1.004-1.110) and 1.024 (1.003-1.046), respectively. SO2 exposure on day 0 and the previous 7 days (P=0.008; P=0.043) and CO exposure in the previous 60 days (P<0.001) may influence the effectiveness of antihypertensive medications; CO on day 0 and SO2 on the same day may interact regarding blood pressure control rates (P=0.045); O3 exposure in the previous 7 days, SO2 on the same day, and CO on the same day may also interact concerning blood pressure control rates (P=0.004; P<0.001).

Conclusion

O3, SO2, and CO are associated with blood pressure control rates. Recent and long-term exposure to O3 and CO may affect blood pressure control, while recent exposure to SO2 may influence the efficacy of antihypertensive medications. It is recommended to enhance air pollution monitoring and management, providing guidance for hypertensive patients to improve blood pressure control outcomes.

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目的

探讨空气污染对高血压患者血压控制的影响。

方法

收集2011—2015年中国健康和营养调查的数据，选取上海市2 860名调查对象，其中831名为高血压患者。通过国家城市空气质量发布平台收集同期上海市的空气污染物监测数据。通过调查问卷获取人口统计学信息、日常生活习惯、患病情况和高血压相关数据。使用logistic回归分析空气污染物对血压达标的影响，并使用混合效应模型研究空气污染物间及其与高血压用药的相互作用。

结果

共纳入831名成年高血压患者，血压控制率35.14%。第0 d、前7 d和前60 d的O3的OR值（95%CI）分别为1.012（1.005～1.020）、1.009（1.002～1.016）和1.013（1.003～1.022）；同期的CO的OR值（95%CI）分别为1.084（1.030～1.140）、1.064（1.030～1.100）和1.126（1.050～1.208）；第0 d和前7 d的SO2的OR值（95%CI）分别为1.056（1.004～1.110）和1.024（1.003～1.046）。第0 d和前7 d的SO2（P=0.008；P=0.043）、前60 d的CO（P<0.001）可能对降压药的使用效果有影响；第0 d的CO与当天的SO2可能对血压达标率存在交互作用（P=0.045）；前7 d的O3、当天的SO2与当天的CO可能对血压达标率存在交互作用（P=0.004；P<0.001）。

结论

O3、SO2与CO与血压控制率相关。近期和远期的O3与CO暴露可能影响血压控制效果，而近期SO2暴露可能影响降压药物的效果。建议加强空气污染监测与管理，针对高血压患者提供指导，以改善血压控制效果。

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陈志永，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=B7jqHMgl+IeSea+tEWgvng==, magXml=ynjIbED1vHM1zLklLx2gkA==, pdfUrl=null, pdf=fNay21BmkBmMSdRZIlpZ2w==, pdfFileSize=1884809, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=4aFUGEehJ8aetu9+Gye/Aw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=r3a9AoXZkGYPHH4y1lmqbQ==, mapNumber=null, authorCompany=null, fund=null, authors=

李小强（1993—），男，硕士，助理研究员，研究方向：流行病与卫生统计学

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李小强（1993—），男，硕士，助理研究员，研究方向：流行病与卫生统计学

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Prenatal household air pollution exposure and childhood blood pressure in rural Ghana[J].Environmental Health Perspectives, 2024, 132(3): 37006., articleTitle=Prenatal household air pollution exposure and childhood blood pressure in rural Ghana, refAbstract=null), Reference(id=1241069126320452414, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, doi=null, pmid=null, pmcid=null, year=2011, volume=87, issue=5/6, pageStart=341, pageEnd=349, url=null, language=null, rfNumber=[22], rfOrder=28, authorNames=Polizio AH, Santa-Cruz DM, Balestrasse KB, journalName=Pharmacology, refType=null, unstructuredReference=Polizio AH, Santa-Cruz DM, Balestrasse KB, et al. Heme oxygenase-1 overexpression fails to attenuate hypertension when the nitric oxide synthase system is not fully operative[J]. Pharmacology,2011, 87(5/6): 341-349., articleTitle=Heme oxygenase-1 overexpression fails to attenuate hypertension when the nitric oxide synthase system is not fully operative, refAbstract=null), Reference(id=1241069126412727107, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, doi=null, pmid=null, pmcid=null, year=2023, volume=262, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[23], rfOrder=29, authorNames=Shi H, Chen L, Zhang S, journalName=Ecotoxicology and Environment Safety, refType=null, unstructuredReference=Shi H, Chen L, Zhang S, et al. Dynamic association of ambient air pollution with incidence and mortality of pulmonary hypertension:a multistate trajectory analysis[J]. Ecotoxicology and Environment Safety, 2023, 262: 115126., articleTitle=Dynamic association of ambient air pollution with incidence and mortality of pulmonary hypertension:a multistate trajectory analysis, refAbstract=null), Reference(id=1241069126538556230, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, doi=null, pmid=null, pmcid=null, year=2018, volume=25, issue=8, pageStart=818, pageEnd=825, url=null, language=null, rfNumber=[24], rfOrder=30, authorNames=Vidale S, Campana C, journalName=European Journal of Preventive Cardiology, refType=null, unstructuredReference=Vidale S, Campana C. Ambient air pollution and cardiovascular diseases: from bench to bedside[J]. European Journal of Preventive Cardiology, 2018, 25(8): 818-825., articleTitle=Ambient air pollution and cardiovascular diseases: from bench to bedside, refAbstract=null), Reference(id=1241069126676968267, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, doi=null, pmid=null, pmcid=null, year=2022, volume=10, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[25], rfOrder=31, authorNames=Rehman E, Rehman S, journalName=Front Public Health, refType=null, unstructuredReference=Rehman E, Rehman S. Particulate air pollution and metabolic risk factors: which are more prone to cardiac mortality[J]. Front Public Health, 2022, 10: 995987., articleTitle=Particulate air pollution and metabolic risk factors: which are more prone to cardiac mortality, refAbstract=null)], funds=[Fund(id=1241069121438282345, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, awardId=Y2018025, language=CN, fundingSource=江苏省预防医学科研课题(Y2018025), fundOrder=null, country=null), Fund(id=1241069121538945650, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, awardId=CJ20241132, language=CN, fundingSource=常州市科技计划课题(CJ20241132), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241069114853224597, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, xref=1., ext=[AuthorCompanyExt(id=1241069114865807510, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, companyId=1241069114853224597, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Food and Environmental Diseases Department, Changzhou Center for Disease Control and Prevention, Jiangsu, Changzhou 213022, China), AuthorCompanyExt(id=1241069114874196120, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, companyId=1241069114853224597, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.常州市疾病预防控制中心食品与环境疾病科，江苏 常州 213022)]), AuthorCompany(id=1241069114974859421, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, xref=2., ext=[AuthorCompanyExt(id=1241069114983248031, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, companyId=1241069114974859421, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.常州市疾病预防控制中心学校卫生科)])], figs=[ArticleFig(id=1241069119462764990, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Figure 1, caption=Logistic model results of air pollution and blood pressure control rate, figureFileSmall=RUHbvRXod0/n3fLjEMNkbQ==, figureFileBig=LEESx24FJMyOaIrE6IT0kA==, tableContent=null), ArticleFig(id=1241069119567622598, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=图1, caption=空气污染物与血压达标率的logistic模型结果

注：A为单污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物；B为多污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物。

, figureFileSmall=RUHbvRXod0/n3fLjEMNkbQ==, figureFileBig=LEESx24FJMyOaIrE6IT0kA==, tableContent=null), ArticleFig(id=1241069119722811863, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Figure 2, caption=Logistic model results of air pollutants and systolic blood pressure control rate, figureFileSmall=VkUDv6NoS/s4WvdURNEOSA==, figureFileBig=rOYZRm+MBmnc5srK5RJkpA==, tableContent=null), ArticleFig(id=1241069119836058079, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=图2, caption=空气污染物与收缩压达标率的logistic模型结果

注：A为单污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物；B为多污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物。

, figureFileSmall=VkUDv6NoS/s4WvdURNEOSA==, figureFileBig=rOYZRm+MBmnc5srK5RJkpA==, tableContent=null), ArticleFig(id=1241069119936721384, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Figure 3, caption=Logistic model results of air pollutants and diastolic blood pressure control rate, figureFileSmall=WIuGo9rxFN0c46nCbtVEmg==, figureFileBig=/4BX3UtQ/BpN75Zv5Xestw==, tableContent=null), ArticleFig(id=1241069120062550518, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=图3, caption=空气污染物与舒张压达标率的logistic模型结果

注：A为单污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物；B为多污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物。

, figureFileSmall=WIuGo9rxFN0c46nCbtVEmg==, figureFileBig=/4BX3UtQ/BpN75Zv5Xestw==, tableContent=null), ArticleFig(id=1241069120184185344, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Figure 4, caption=Logistic model results of air pollutants and blood pressure control rate in people using antihypertensive drugs, figureFileSmall=qOIa1g74yW9lsv3NVTuc+A==, figureFileBig=E/VvjJ5niDprGRNnJ2kA6A==, tableContent=null), ArticleFig(id=1241069120330985995, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=图4, caption=服降压药人群中空气污染物与血压达标率的logistic模型结果

注：A为单污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物；B为多污染物模型，调整了年龄、居住地类型、体重指数、代谢当量、PSS评分和使用降压药物。

, figureFileSmall=qOIa1g74yW9lsv3NVTuc+A==, figureFileBig=E/VvjJ5niDprGRNnJ2kA6A==, tableContent=null), ArticleFig(id=1241069120461009428, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Table 1, caption=

Distribution of variables between groups with poor or good blood pressure control

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名血压控制情况统计量P值
控制不佳 (n=539)控制良好 (n=292)
年龄（岁）*60.77±11.0762.36±9.50-2.1740.030
性别（男）**291 (53.99)138 (47.26)3.4340.064
教育程度**1.5360.674
小学及以下115 (21.34)60 (20.55)
中学300 (55.66)156 (53.42)
职业学校59 (10.95)32 (10.96)
大学及以上65 (12.06)44 (15.07)
工作情况**5.3230.070
其他44 (8.16)34 (11.64)
已退休324 (60.11)184 (63.01)
工作171 (31.73)74 (25.34)
居住地类型**6.0670.014
城市311 (57.70)194 (66.44)
农村228 (42.30)98 (33.56)
医保情况（有）**530 (98.33)286 (97.95)0.1580.691
体重指数（kg/m2）*25.85±3.3425.16±3.182.8930.004
腰臀比*0.91±0.100.90±0.081.5950.112
吸烟**1.9980.368
不吸烟364 (67.53)211 (72.26)
曾吸烟40 (7.42)18 (6.16)
吸烟135 (25.05)63 (21.58)
吸烟时间（年）#0.00 (0.00, 29.00)0.00 (0.00, 22.50)-1.3730.170
饮酒（是）**155 (28.76)87 (29.79)0.0990.753
每周饮酒量（g）#0.00 (0.00, 0.07)0.00 (0.00, 0.10)-0.1980.843
代谢当量（Met-h/w）#53.20 (46.55, 76.53)53.20 (46.55, 67.03)-2.1490.032
高血压病程（年）#2.00 (0.00, 10.00)10.00 (4.00, 15.00)8.711<0.001
糖尿病（是）**63 (11.69)36 (12.33)0.0740.786
肿瘤（是）**19 (3.53)12 (4.11)0.1800.671
心血管疾病（是）**28 (5.19)27 (9.25)5.0310.025
中风（是）**25 (4.64)19 (6.51)1.3190.251
PSS评分#33.00 (27.00, 40.00)35.00 (28.00, 41.00)1.4710.141
使用降压药物（是）**277 (51.39)269 (92.12)139.445<0.001
收缩压（mm Hg）*147.98±12.71128.11±8.1427.382<0.001
舒张压（mm Hg）*89.54±8.4279.85±5.7419.624<0.001
), ArticleFig(id=1241069120616198690, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=表1, caption=

血压控制不佳组和控制良好组的变量分布情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名血压控制情况统计量P值
控制不佳 (n=539)控制良好 (n=292)
年龄（岁）*60.77±11.0762.36±9.50-2.1740.030
性别（男）**291 (53.99)138 (47.26)3.4340.064
教育程度**1.5360.674
小学及以下115 (21.34)60 (20.55)
中学300 (55.66)156 (53.42)
职业学校59 (10.95)32 (10.96)
大学及以上65 (12.06)44 (15.07)
工作情况**5.3230.070
其他44 (8.16)34 (11.64)
已退休324 (60.11)184 (63.01)
工作171 (31.73)74 (25.34)
居住地类型**6.0670.014
城市311 (57.70)194 (66.44)
农村228 (42.30)98 (33.56)
医保情况（有）**530 (98.33)286 (97.95)0.1580.691
体重指数（kg/m2）*25.85±3.3425.16±3.182.8930.004
腰臀比*0.91±0.100.90±0.081.5950.112
吸烟**1.9980.368
不吸烟364 (67.53)211 (72.26)
曾吸烟40 (7.42)18 (6.16)
吸烟135 (25.05)63 (21.58)
吸烟时间（年）#0.00 (0.00, 29.00)0.00 (0.00, 22.50)-1.3730.170
饮酒（是）**155 (28.76)87 (29.79)0.0990.753
每周饮酒量（g）#0.00 (0.00, 0.07)0.00 (0.00, 0.10)-0.1980.843
代谢当量（Met-h/w）#53.20 (46.55, 76.53)53.20 (46.55, 67.03)-2.1490.032
高血压病程（年）#2.00 (0.00, 10.00)10.00 (4.00, 15.00)8.711<0.001
糖尿病（是）**63 (11.69)36 (12.33)0.0740.786
肿瘤（是）**19 (3.53)12 (4.11)0.1800.671
心血管疾病（是）**28 (5.19)27 (9.25)5.0310.025
中风（是）**25 (4.64)19 (6.51)1.3190.251
PSS评分#33.00 (27.00, 40.00)35.00 (28.00, 41.00)1.4710.141
使用降压药物（是）**277 (51.39)269 (92.12)139.445<0.001
收缩压（mm Hg）*147.98±12.71128.11±8.1427.382<0.001
舒张压（mm Hg）*89.54±8.4279.85±5.7419.624<0.001
), ArticleFig(id=1241069120742027817, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Table 2, caption=

Exposure to air pollutants in patients with poor or good blood pressure control

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名血压控制情况统计量P值
控制不佳 (n=539)控制良好 (n=292)
第0 d PM2.5（μg/m3）*141.22±39.48136.26±41.001.7010.089
第0 d PM10（μg/m3）#65.00 (51.00, 73.00)61.00 (51.00, 73.00)-0.7840.433
第0 d O3（μg/m3）#27.00 (14.00, 49.00)37.00 (26.00, 55.00)3.753<0.001
第0 d CO（mg/m3）#7.00 (5.00, 11.00)6.00 (5.00, 9.00)-3.1440.002
第0 d SO2（μg/m3）#9.00 (6.00, 10.00)9.00 (6.00, 10.00)-1.2170.224
第0 d NO2（μg/m3）#25.00 (16.00, 34.00)29.00 (19.00, 34.00)0.8380.402
前7 d PM2.5（μg/m3）*143.66±45.03139.24±43.081.3690.171
前7 d PM10（μg/m3）#71.00 (58.00, 95.00)65.00 (56.00, 91.00)-1.6530.098
前7 d O3（μg/m3）#37.00 (15.00, 56.00)43.00 (24.00, 55.00)2.6370.008
前7 d CO（mg/m3）#7.00 (6.00, 13.00)7.00 (6.00, 12.00)-3.312<0.001
前7 d SO2（μg/m3）#9.00 (7.00, 11.00)9.00 (7.00, 11.00)-1.7960.073
前7 d NO2（μg/m3）#30.00 (20.00, 37.00)29.50 (23.00, 37.00)-0.3580.721
前60 d PM2.5（μg/m3）*126.42±33.08123.98±31.661.0280.304
前60 d PM10（μg/m3）#54.00 (48.00, 70.00)51.00 (48.00, 67.00)-0.4920.622
前60 d O3（μg/m3）#38.00 (27.00, 50.00)36.00 (25.00, 44.00)-1.9690.049
前60 d CO（mg/m3）#6.00 (5.00, 7.00)6.00 (5.00, 6.00)-2.7310.006
前60 d SO2（μg/m3）#7.00 (5.00, 9.00)7.00 (5.00, 9.00)-0.7130.476
前60 d NO2（μg/m3）#21.00 (17.00, 25.00)21.00 (17.00, 23.00)-0.2750.783
), ArticleFig(id=1241069120893022769, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=表2, caption=

血压控制不佳组和控制良好组的大气污染物暴露情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名血压控制情况统计量P值
控制不佳 (n=539)控制良好 (n=292)
第0 d PM2.5（μg/m3）*141.22±39.48136.26±41.001.7010.089
第0 d PM10（μg/m3）#65.00 (51.00, 73.00)61.00 (51.00, 73.00)-0.7840.433
第0 d O3（μg/m3）#27.00 (14.00, 49.00)37.00 (26.00, 55.00)3.753<0.001
第0 d CO（mg/m3）#7.00 (5.00, 11.00)6.00 (5.00, 9.00)-3.1440.002
第0 d SO2（μg/m3）#9.00 (6.00, 10.00)9.00 (6.00, 10.00)-1.2170.224
第0 d NO2（μg/m3）#25.00 (16.00, 34.00)29.00 (19.00, 34.00)0.8380.402
前7 d PM2.5（μg/m3）*143.66±45.03139.24±43.081.3690.171
前7 d PM10（μg/m3）#71.00 (58.00, 95.00)65.00 (56.00, 91.00)-1.6530.098
前7 d O3（μg/m3）#37.00 (15.00, 56.00)43.00 (24.00, 55.00)2.6370.008
前7 d CO（mg/m3）#7.00 (6.00, 13.00)7.00 (6.00, 12.00)-3.312<0.001
前7 d SO2（μg/m3）#9.00 (7.00, 11.00)9.00 (7.00, 11.00)-1.7960.073
前7 d NO2（μg/m3）#30.00 (20.00, 37.00)29.50 (23.00, 37.00)-0.3580.721
前60 d PM2.5（μg/m3）*126.42±33.08123.98±31.661.0280.304
前60 d PM10（μg/m3）#54.00 (48.00, 70.00)51.00 (48.00, 67.00)-0.4920.622
前60 d O3（μg/m3）#38.00 (27.00, 50.00)36.00 (25.00, 44.00)-1.9690.049
前60 d CO（mg/m3）#6.00 (5.00, 7.00)6.00 (5.00, 6.00)-2.7310.006
前60 d SO2（μg/m3）#7.00 (5.00, 9.00)7.00 (5.00, 9.00)-0.7130.476
前60 d NO2（μg/m3）#21.00 (17.00, 25.00)21.00 (17.00, 23.00)-0.2750.783
), ArticleFig(id=1241069121023046206, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=EN, label=Table 3, caption=

Interaction of O3, CO, and SO2 with antihypertensive drugs using by mixed linear model

, figureFileSmall=null, figureFileBig=null, tableContent=
变量血压控制收缩压控制舒张压控制
F值P值F值P值F值P值
第0 d O3×降压药使用1.370.1291.490.0771.670.033
第0 d CO×降压药使用1.700.0691.990.0271.370.181
第0 d SO2×降压药使用2.430.008——1.490.138
前7 d O3×降压药使用1.370.1231.440.091——
前7 d CO×降压药使用1.470.139——
前7 d SO2×降压药使用1.850.043——
前60 d O3×降压药使用1.000.453——1.600.055
前60 d CO×降压药使用3.20<0.0012.480.0092.220.019
第0 d O3×第0 d SO21.960.162——5.980.015
第0 d O3×第0 d CO2.150.1430.940.3321.700.192
第0 d CO×第0 d SO24.050.045——26.50<0.001
前7 d O3×第0 d SO28.450.004————
前7 d O3×第0 d CO10.740.00111.60<0.001
前7 d CO×第0 d SO28.500.004————
前60 d O3×前60 d CO0.080.774——5.740.017
), ArticleFig(id=1241069121144681030, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035815745286824, language=CN, label=表3, caption=

O3、CO、SO2和降压药使用的混合线性模型交互项

, figureFileSmall=null, figureFileBig=null, tableContent=
变量血压控制收缩压控制舒张压控制
F值P值F值P值F值P值
第0 d O3×降压药使用1.370.1291.490.0771.670.033
第0 d CO×降压药使用1.700.0691.990.0271.370.181
第0 d SO2×降压药使用2.430.008——1.490.138
前7 d O3×降压药使用1.370.1231.440.091——
前7 d CO×降压药使用1.470.139——
前7 d SO2×降压药使用1.850.043——
前60 d O3×降压药使用1.000.453——1.600.055
前60 d CO×降压药使用3.20<0.0012.480.0092.220.019
第0 d O3×第0 d SO21.960.162——5.980.015
第0 d O3×第0 d CO2.150.1430.940.3321.700.192
第0 d CO×第0 d SO24.050.045——26.50<0.001
前7 d O3×第0 d SO28.450.004————
前7 d O3×第0 d CO10.740.00111.60<0.001
前7 d CO×第0 d SO28.500.004————
前60 d O3×前60 d CO0.080.774——5.740.017
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空气污染对高血压患者血压控制的影响及其交互作用——基于中国健康营养调查的研究
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李小强 1 , 陈小岳 1 , 陈志永 1 , 武常倩 2 , 谷令 1 , 王珂 1
现代预防医学 | 环境与职业卫生 2024,51(23): 4279-4285
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现代预防医学 | 环境与职业卫生 2024, 51(23): 4279-4285
空气污染对高血压患者血压控制的影响及其交互作用——基于中国健康营养调查的研究
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李小强1, 陈小岳1, 陈志永1 , 武常倩2, 谷令1, 王珂1
作者信息
  • 1.常州市疾病预防控制中心食品与环境疾病科，江苏 常州 213022
  • 2.常州市疾病预防控制中心学校卫生科

    • 李小强（1993—），男，硕士，助理研究员，研究方向：流行病与卫生统计学

通讯作者:

陈志永，E-mail:
Impact of air pollution on blood pressure control in hypertensive patients and its interactions: a study based on the China Health and Nutrition Survey
Xiao-qiang LI1, Xiao-yue CHEN1, Zhi-yong CHEN1 , Chang-qian WU2, Ling GU1, Ke WANG1
Affiliations
  • Food and Environmental Diseases Department, Changzhou Center for Disease Control and Prevention, Jiangsu, Changzhou 213022, China
出版时间: 2024-12-10 doi: 10.20043/j.cnki.MPM.202407487
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摘要
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目的

探讨空气污染对高血压患者血压控制的影响。

方法

收集2011—2015年中国健康和营养调查的数据，选取上海市2 860名调查对象，其中831名为高血压患者。通过国家城市空气质量发布平台收集同期上海市的空气污染物监测数据。通过调查问卷获取人口统计学信息、日常生活习惯、患病情况和高血压相关数据。使用logistic回归分析空气污染物对血压达标的影响，并使用混合效应模型研究空气污染物间及其与高血压用药的相互作用。

结果

共纳入831名成年高血压患者，血压控制率35.14%。第0 d、前7 d和前60 d的O3的OR值（95%CI）分别为1.012（1.005～1.020）、1.009（1.002～1.016）和1.013（1.003～1.022）；同期的CO的OR值（95%CI）分别为1.084（1.030～1.140）、1.064（1.030～1.100）和1.126（1.050～1.208）；第0 d和前7 d的SO2的OR值（95%CI）分别为1.056（1.004～1.110）和1.024（1.003～1.046）。第0 d和前7 d的SO2（P=0.008；P=0.043）、前60 d的CO（P<0.001）可能对降压药的使用效果有影响；第0 d的CO与当天的SO2可能对血压达标率存在交互作用（P=0.045）；前7 d的O3、当天的SO2与当天的CO可能对血压达标率存在交互作用（P=0.004；P<0.001）。

结论

O3、SO2与CO与血压控制率相关。近期和远期的O3与CO暴露可能影响血压控制效果，而近期SO2暴露可能影响降压药物的效果。建议加强空气污染监测与管理，针对高血压患者提供指导，以改善血压控制效果。

高血压  /  空气污染  /  血压控制  /  中国健康和营养调查
Objective

To investigate the impact of air pollution on blood pressure control in hypertensive patients.

Methods

Data from the China Health and Nutrition Survey collected between 2011 and 2015 were analyzed, including 2 860 participants from Shanghai, of which 831 were hypertensive patients. Air pollution monitoring data for Shanghai during the same period were obtained from the National Urban Air Quality Release Platform. Demographic information, daily habits, health status, and hypertension-related data were collected via questionnaires. Logistic regression was employed to analyze the effect of air pollutants on achieving blood pressure targets, and a mixed-effects model was used to study interactions among air pollutants and their interactions with antihypertensive medications.

Results

A total of 831 adult hypertensive patients were included, with a blood pressure control rate of 35.14%. The odds ratios (OR) and 95% confidence intervals (CI) for O3 exposure on day 0, the previous 7 days, and the previous 60 days were 1.012 (1.005-1.020), 1.009 (1.002-1.016), and 1.013 (1.003-1.022), respectively. For CO during the same periods, the OR and 95%CI were 1.084 (1.030-1.140), 1.064 (1.030-1.100), and 1.126 (1.050-1.208), respectively. The OR and 95%CI for SO2 on day 0 and the previous 7 days were 1.056 (1.004-1.110) and 1.024 (1.003-1.046), respectively. SO2 exposure on day 0 and the previous 7 days (P=0.008; P=0.043) and CO exposure in the previous 60 days (P<0.001) may influence the effectiveness of antihypertensive medications; CO on day 0 and SO2 on the same day may interact regarding blood pressure control rates (P=0.045); O3 exposure in the previous 7 days, SO2 on the same day, and CO on the same day may also interact concerning blood pressure control rates (P=0.004; P<0.001).

Conclusion

O3, SO2, and CO are associated with blood pressure control rates. Recent and long-term exposure to O3 and CO may affect blood pressure control, while recent exposure to SO2 may influence the efficacy of antihypertensive medications. It is recommended to enhance air pollution monitoring and management, providing guidance for hypertensive patients to improve blood pressure control outcomes.

Hypertension  /  Air pollution  /  Blood pressure control  /  China Health and Nutrition Survey
李小强, 陈小岳, 陈志永, 武常倩, 谷令, 王珂. 空气污染对高血压患者血压控制的影响及其交互作用——基于中国健康营养调查的研究. 现代预防医学, 2024 , 51 (23) : 4279 -4285 . DOI: 10.20043/j.cnki.MPM.202407487
Xiao-qiang LI, Xiao-yue CHEN, Zhi-yong CHEN, Chang-qian WU, Ling GU, Ke WANG. Impact of air pollution on blood pressure control in hypertensive patients and its interactions: a study based on the China Health and Nutrition Survey[J]. Modern Preventive Medicine, 2024 , 51 (23) : 4279 -4285 . DOI: 10.20043/j.cnki.MPM.202407487
正文
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高血压是一种常见的慢性病，其发病率和死亡率在全球范围内呈上升趋势[1]，但高血压患者的血压却难以得到有效控制[2-3]。而空气污染是当今全球面临的重要环境问题之一，已成为危害公众健康的主要因素之一[4]。越来越多的研究表明，空气污染与高血压发病和血压控制有着密切的联系[5-8]。
目前已有许多研究探讨了PM2.5、O3、CO、SO2等污染物对人群高血压发病的影响。其中，PM2.5作为最常见的污染物与高血压的发病率和死亡率呈正相关[7]；O3是一种强氧化剂，长期暴露会对人体健康产生不良影响[9]；CO和SO2是有毒气体，对呼吸系统和心血管系统有明显的危害[10-11]。而不同污染物之间的协同作用对血压水平产生更大的影响[12]。虽然现有研究已经初步揭示了空气污染可以影响高血压治疗方式的有效性[13]，但是目前主要关注单一污染物对高血压控制的影响，较少考虑多种污染物的共同作用[9]。空气污染物能够影响一些慢性疾病控制措施的效果[13-14]，而空气污染物与用药等血压控制措施间的相互作用也缺乏相关研究。
本研究旨在探索空气污染物对高血压患者血压控制的影响，并分析空气污染物对高血压控制措施效果的影响，为降低空气污染对高血压患者的危害提出建议。
1 资料与方法
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1.1 资料来源
收集2011—2015年中国健康和营养调查（China Health and Nutrition Survey，CHNS）中来自上海市的2 860名调查对象，获取其人口统计学信息、日常生活习惯、患病情况和高血压相关数据。识别出成年高血压患者831名作为研究对象。从国家城市空气质量发布平台收集同期上海市6种空气污染物检测指标（PM2.5、PM10、O3、CO、SO2、NO2）。
1.2 相关变量
研究收集了人口统计学信息（年龄、性别、教育程度、工作情况、居住地类型、医保信息、体重指数、腰臀比）、日常生活习惯（吸烟、饮酒、运动）、患病情况（高血压病程、糖尿病、肿瘤、心血管疾病、中风、压力）和高血压相关情况（服药情况、收缩压、舒张压）。压力水平使用压力感知量表（perceived stress scale，PSS）进行测量[15]。根据中国高血压防治指南(2024年修订版)[16]，将血压<140/90 mm Hg的高血压患者定义为血压控制良好。按照世界卫生组织(WHO)推荐使用代谢活动当量量化活动强度。收集调查对象接受调查时的当天、前7 d和前60 d上海市PM2.5、PM10、O3、CO、SO2、NO2等6种空气污染物指标。
1.3 统计学分析
正态分布的计量资料使用（均值±标准差）描述，组间差异使用t检验分析；非正态分布的计量资料使用中位数和四分位数描述，组间差异使用Wilcoxon秩和检验分析；计数资料使用例数和百分比描述，组间差异使用χ2检验分析。使用多重插补法填充缺失数据。使用logistic回归分析空气污染物对血压达标的影响，并使用混合效应模型分析空气污染物间及其与高血压用药的相互作用。采用SAS 9.4（SAS Institute Inc., Cary, NC, USA）软件进行数据分析，检验水准α=0.05。
2 结果
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2.1 描述性结果
纳入研究的831人平均年龄为（61.32±10.56）岁，其中539人（64.86%）血压控制不佳，男性429人（51.26%）。血压控制不佳组年龄更低、农村人口更多、体重指数更高、高血压病程更短、心血管疾病更少、降压药使用率更低，见表1。两组人群空气污染物暴露情况如表2所示，第0 d、前7 d和前60 d的O3浓度更低而CO浓度更高（P值均小于0.05）。
2.2 空气污染物与血压达标率的关联性分析
血压达标率时，单污染物模型分析中，第0 d、前7 d和前60 dO3的OR值［95%置信区间（confidence interval，CI）］分别为1.012（1.005～1.020）、1.009（1.002～1.016）和1.013（1.003～1.022）；同期CO的OR值（95%CI）分别为1.084（1.030～1.140）、1.064（1.030～1.100）和1.126（1.050～1.208）；第0 d和前7 dSO2的OR值（95%CI）分别为1.056（1.004～1.110）和1.024（1.003～1.046）。多污染物模型中，第0 d、前7 d和前60 dO3的OR值（95%CI）分别为1.107（1.048～1.168）、1.012（1.053～1174）和1.017（1.004～1.031）；同期CO的OR值（95%CI）分别为1.086（1.003～1.150）、1.107（1.022～1.200）和1.172（1.020～1.347）；第0 dSO2的OR值（95%CI）为1.070（1.003～1.175）。见图1。O3、CO和SO2可能与血压达标率相关。
分析收缩压达标率时，单污染物模型中，第0 d的O3的OR值（95%CI）为1.085（1.033～1.140）；第0 d和前60 d的CO的OR值（95%CI）分别为1.057（1.004～1.104）和1.072（1.002～1.148）。多污染物模型中，第0 d和前7 d的O3的OR值（95%CI）分别为1.087（1.034～1.143）和1.004（1.001～1.015）；第0 d和前60 d CO的OR值（95%CI）分别为1.043（1.022～1.063）和1.218（1.071～1.384）。见图2。O3和CO可能与收缩压达标率相关。
分析舒张压达标率时，单污染物模型中，第0 d和第60 d O3的OR值（95%CI）分别为1.182（1.147～1.283）和1.017（1.008～1.026）；前60 d CO的OR值（95%CI）为1.076（1.007～1.151）；第0 d SO2的OR值（95%CI）为1.066（1.014～1.122）。多污染物模型中，第60 d O3的OR值（95%CI）为1.014（1.002～1.026；第0 d SO2的OR值（95%CI）为1.074（1.007～1.147）。见图3。O3、CO和SO2可能与舒张压达标率相关。
2.3 O3、CO、SO2和降压药使用的联合作用分析
分析血压控制率的结果显示，第0 d和前7 d的SO2以及前60 d的CO可能对降压药的使用效果有影响（P=0.008；P=0.043；P<0.001）；第0 d的CO与当 天的SO2（P=0.045）、前7 d的O3与当天的SO2（P= 0.004）、前7 d的O3与当 天的CO（P=0.001）、前7 d的CO与当天的SO2（P=0.004）均可能存在交互作用。分析收缩压控制率的结果显示，第0 d和前60 d的CO可能对降压药的使用效果有影响（P=0.027；P= 0.009）；前7 d的O3与当天的CO可能对收缩压达标率存在交互作用（P<0.001）。分析舒张压控制率的结果显示，第0 d的O3和前60 d的CO可能对降压药的使用效果有影响（P=0.033；P=0.019）；第0 d的CO与当天的SO2（P<0.001）、前60 d的O3与前60 d的CO（P=0.017）均可能存在交互作用。见表3。
2.4 服降压药人群中空气污染物与血压达标率的关联性分析
分析血压达标率时，在单污染物模型中，第0 d、前7 d和前60 d O3的OR值（95%CI）分别为1.102（1.040～1.167）、1.094（1.034～1.159）和1.019（1.008～1.030）；第0 d和前60 d CO的OR值（95%CI）分别为1.078（1.015～1.144）和1.150（1.058～1.253）；第0 d SO2的OR值（95%CI）为1.082（1.020～1.148）。多污染物模型中，第0 d和前7 d O3的OR值（95%CI）分别为1.099（1.036～1.167）和1.102（1.039～1.168）；第0 d、前7 d和前60 d CO的OR值（95%CI）分别为1.094（1.003～1.193）、1.106（1.013～1.208）和1.326（1.134～1.550）；第0 d SO2的OR值（95%CI）为1.089（1.002～1.184）。见图4。与全部研究人群中的结果类似。
3 讨论
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空气污染增加高血压进展为心血管疾病的风险，有效控制血压对于降低疾病负担有重要意义[17]。本研究结果显示，O3、CO、SO2与高血压患者的血压控制率相关，空气污染物间可能存在联合作用并影响降压药物的效果。一项干预收缩压的大型实验发现，当高血压患者暴露于PM2.5时，强化降压治疗比标准降压治疗更能有效控制患者血压，且其效果取决于既往PM2.5暴露。空气污染物引起的血管弹性降低可能影响患者的血压控制和强化治疗的收益[18]。研究指出SO2暴露会影响高血压患者的血压控制并增加入院率[11,19]。CO作为一种抗炎药物在临床上已被应用[20]，可能有助于降低血压。但也研究发现CO暴露会引起血压的升高[21]，这可能与血管内皮的一氧化氮合酶功能不全有关[22]。虽然上海市的空气污染水平较低，我们仍发现O3、CO、SO2与高血压患者血压控制率相关，表明这些污染物可能影响患者的血压控制。我们还观察到O3、CO、SO2之间可能存在交互作用，而污染物的协同作用会使患者的血压控制更加困难。此外，近期和远期的O3和CO暴露均可能影响降压药对患者血压的控制效果，近期SO2暴露同样可能产生影响。这意味着需要根据高血压患者所暴露的主要污染物调整其降压药物的剂量，或综合使用其他治疗方法以优化血压。这为临床医生制定治疗方案提供了指导。
空气污染物可能通过如下机制影响患者血压的控制。首先，炎症/促氧化因子的释放可引发全身炎症，进而提高血压[23]。其次，污染物可通过肺泡膜直接进入血液，影响血管舒缩活性和NO信号通路[18]。最后，污染物可以激活肺树中受体介导的反射行为，影响血压和心率[24]。这些机制可能同时存在，其相对重要性与污染物的浓度和类型有关[25]。
基于研究结果，建议采取以下措施降低空气污染对患者血压控制效果的影响： （1）加强空气污染监测和管理，及时发布空气质量报告以便患者采取防护措施；（2）开展健康教育，提高公众对空气污染健康影响的认识；（3） 加强医疗机构对高血压患者的管理和指导，定期检查和评估，并根据环境污染情况调整治疗方案，从而提高血压控制效果。
本研究中收缩压和舒张压控制率的结果与整体血压控制率相似，且降压药服用人群的分析结果一致，表明研究结果较为稳健。然而研究仍存在一些局限性。首先，样本量限制导致无法对季节等因素进行分层分析。其次，由于CHNS数据库的限制，无法获得个体暴露数据，可能导致对实际空气污染暴露情况的估计存在误差。此外，尽管CHNS在血压测量时设有统一标准，但由于参与人数众多，可能出现测量异质性。最后，某些潜在混杂因素未得到充分控制。
基金
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  • 江苏省预防医学科研课题(Y2018025)
  • 常州市科技计划课题(CJ20241132)
文献
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2024年第51卷第23期
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doi: 10.20043/j.cnki.MPM.202407487
  • 接收时间：2024-07-27
  • 首发时间：2026-03-18
  • 出版时间：2024-12-10
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  • 收稿日期：2024-07-27
基金
江苏省预防医学科研课题(Y2018025)
常州市科技计划课题(CJ20241132)
作者信息
    1.常州市疾病预防控制中心食品与环境疾病科，江苏 常州 213022
    2.常州市疾病预防控制中心学校卫生科

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