Article(id=1241023929872085405, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410379, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729353600000, receivedDateStr=2024-10-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812761991, onlineDateStr=2026-03-18, pubDate=1739116800000, pubDateStr=2025-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812761991, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812761991, creator=13701087609, updateTime=1773812761991, updator=13701087609, issue=Issue{id=1241023927812682133, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812761500, creator=13701087609, updateTime=1773812858867, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024336258200259, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024336258200260, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=508, endPage=512, ext={EN=ArticleExt(id=1241023931096822187, articleId=1241023929872085405, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the relationship between follow-up management and blood pressure control in hypertensive patients in Sichuan Province, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the impact of follow-up management on blood pressure control in hypertensive patients in Sichuan Province, so as to improve the blood pressure control rate in the population.

Methods

Based on the data of the Seventh National Health Service Survey in Sichuan province, 3 587 hypertensive patients were included. Descriptive statistical analysis was used to analyze the follow-up management situation, demographic characteristics, lifestyle behaviors and health status of patients. Combined with the multivariate logistic regression model, the follow-up management factors affecting blood pressure control were explored.

Results

The blood pressure control rate was 68.9%. Among the effectively controlled patients, the rate of taking medications regularly as prescribed was 84.6%, the proportion of those with a follow-up frequency of ≥4 was 71.4%, and the rate of family doctor-signed home visits was 48.1%. Among the patients not effectively controlled, the rate of taking medications regularly as prescribed was 73.4%, the proportion of those with a follow-up frequency of ≥4 was 67.6%, and the rate of family doctor-signed home visits was 45.2%. Multivariate Logistic regression analysis showed that not taking medications regularly as prescribed (OR=1.742, 95%CI:1.453-2.089), a follow-up frequency of <4 (OR=1.287, 95%CI: 1.057-1.567) and other follow-up methods (OR=1.286, 95%CI:1.092-1.516) had significant negative impacts on the blood pressure control effect of patients.

Conclusion

Follow-up management of hypertension is beneficial to blood pressure control. The follow-up frequency should be optimized, drug compliance should be improved, and the interaction between the signed doctor and the patient should be enhanced.

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目的

旨在探讨四川省高血压患者随访管理对血压控制的影响,以提高人群血压控制率。

方法

基于四川省第七次国家卫生服务调查数据,纳入3 587名高血压患者。采用描述性统计分析患者的随访管理情况、人口学特征、生活行为及健康状况,结合多因素logistic回归模型探讨影响血压控制的随访管理因素。

结果

血压控制率为68.9%。在有效控制的患者中,按医嘱规律服药率为84.6%,随访频率≥4占比71.4%,签约家庭医生入户随访率为48.1%;未有效控制的患者中,按医嘱规律服药率为73.4%,随访频率≥4占比67.6%,签约家庭医生入户随访率为45.2%。多因素logistic回归分析显示,未按医嘱规律服药(OR=1.742,95%CI:1.453~2.089)、随访频率<4 (OR=1.287,95%CI:1.057~1.567)和其他随访方式(OR=1.286,95%CI:1.092~1.516)对患者血压控制效果有显著的负面影响。

结论

对高血压的随访管理有利于血压控制,应该优化随访频率、提高药物依从性和增强签约医生与患者的互动。

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任晓晖,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=cCWM+MUSW3pImvKcqpXaIw==, magXml=ZJTptv3ejjELKELXJKnvzg==, pdfUrl=null, pdf=r0R0GvVC4RngDx32BmUnEA==, pdfFileSize=485381, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=cwSYSTPAZYB7vZec0JgcAQ==, mapNumber=null, authorCompany=null, fund=null, authors=

喻瑞(1994—),男,硕士,科研助理,研究方向:统计方法在流行病学中的应用

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喻瑞(1994—),男,硕士,科研助理,研究方向:统计方法在流行病学中的应用

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Heilongjiang Medicine Journal,2024, 37(3): 711-714.(In Chinese), articleTitle=Impact of family doctor contracting service on disease awareness and blood pressure control among hypertensive patients in the community, refAbstract=null)], funds=[Fund(id=1241023935937049199, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, awardId=null, language=CN, fundingSource=四川省2023年卫生服务专项调查, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023931612721605, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, xref=1., ext=[AuthorCompanyExt(id=1241023931616915910, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, companyId=1241023931612721605, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=West China School of Public Health / West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1241023931625304519, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, companyId=1241023931612721605, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.四川大学华西公共卫生学院/华西第四医院,四川 成都610041)]), AuthorCompany(id=1241023931696607692, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, xref=2., ext=[AuthorCompanyExt(id=1241023931704996301, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, companyId=1241023931696607692, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.四川省卫生健康信息中心/四川省医疗大数据中心)])], figs=[ArticleFig(id=1241023935450509912, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, language=EN, label=Table 1, caption=

Comparison of basic characteristics between hypertension controlled group and uncontrolled group [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目全部患者
(n=3 587)
控制组
(n=2 470)
未有效控制组
(n=1 117)
χ2P
年龄(岁)0.8780.349
≥652 433(67.8)1 688(68.3)745(66.7)
<651 154(32.2)782(31.7)372(33.3)
性别2.1010.147
男性1 729(48.2)1 170(47.4)559(50.0)
女性1 858(51.8)1 300(52.6)558(50.0)
城乡70.903<0.001
城市1 828(51.0)1 376(55.7)452(40.5)
农村1 759(49.0)1 094(44.3)665(59.5)
受教育程度30.408<0.001
没上过学811(22.6)520(21.1)291(26.1)
小学或初中2 428(67.7)1 671(67.7)757(67.8)
高中或技校257(7.2)202(8.2)55(4.9)
大专或本科及以上91(2.5)77(3.1)14(1.3)
家庭人均收入(元/年)52.560<0.001
>14 4001 792(50.0)1 335(54.0)457(40.9)
≤14 4001 795(50.0)1 135(46.0)660(59.1)
体育锻炼30.427<0.001
锻炼1 980(55.2)1 440(58.3)540(48.3)
几乎不锻炼1 607(44.8)1 030(41.7)577(51.7)
BMI0.5280.768
正常2087(58.2)1428(57.8)659(59.0)
偏瘦209(5.8)147(6.0)62(5.6)
超重或肥胖1291(36.0)895(36.2)396(35.5)
吸烟状况9.0880.003
从未吸烟2773(77.3)1945(78.7)828(74.1)
吸烟814(22.7)525(21.3)289(25.9)
饮酒状况9.3980.002
从未饮酒2553(71.2)1797(72.8)756(67.7)
饮酒1034(28.8)673(27.2)361(32.3)
糖尿病0.8450.358
2933(81.8)2030(82.2)903(80.8)
654(18.2)440(17.8)214(19.2)
抑郁、焦虑情绪43.909<0.001
2822(78.7)2019(81.7)803(71.9)
765(21.3)451(18.3)314(28.1)
失眠问题38.161<0.001
1549(43.2)1152(46.6)397(35.5)
2038(56.8)1318(53.4)720(64.5)
服药状况62.334<0.001
按医嘱规律服用2910(81.1)2090(84.6)820(73.4)
未按医嘱规律服用677(18.9)380(15.4)297(26.6)
随访频率(次/年)5.2010.023
≥42519(70.2)1764(71.4)755(67.6)
<41068(29.8)706(28.6)362(32.4)
随访形式2.5280.232
签约家庭医生入户随访1694(47.2)1189(48.1)505(45.2)
未随访447(12.5)298(12.1)149(13.3)
其他随访1446(40.3)983(39.8)463(41.5)
), ArticleFig(id=1241023935588921949, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, language=CN, label=表1, caption=

高血压患者控制组与未有效控制组基本情况比较[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目全部患者
(n=3 587)
控制组
(n=2 470)
未有效控制组
(n=1 117)
χ2P
年龄(岁)0.8780.349
≥652 433(67.8)1 688(68.3)745(66.7)
<651 154(32.2)782(31.7)372(33.3)
性别2.1010.147
男性1 729(48.2)1 170(47.4)559(50.0)
女性1 858(51.8)1 300(52.6)558(50.0)
城乡70.903<0.001
城市1 828(51.0)1 376(55.7)452(40.5)
农村1 759(49.0)1 094(44.3)665(59.5)
受教育程度30.408<0.001
没上过学811(22.6)520(21.1)291(26.1)
小学或初中2 428(67.7)1 671(67.7)757(67.8)
高中或技校257(7.2)202(8.2)55(4.9)
大专或本科及以上91(2.5)77(3.1)14(1.3)
家庭人均收入(元/年)52.560<0.001
>14 4001 792(50.0)1 335(54.0)457(40.9)
≤14 4001 795(50.0)1 135(46.0)660(59.1)
体育锻炼30.427<0.001
锻炼1 980(55.2)1 440(58.3)540(48.3)
几乎不锻炼1 607(44.8)1 030(41.7)577(51.7)
BMI0.5280.768
正常2087(58.2)1428(57.8)659(59.0)
偏瘦209(5.8)147(6.0)62(5.6)
超重或肥胖1291(36.0)895(36.2)396(35.5)
吸烟状况9.0880.003
从未吸烟2773(77.3)1945(78.7)828(74.1)
吸烟814(22.7)525(21.3)289(25.9)
饮酒状况9.3980.002
从未饮酒2553(71.2)1797(72.8)756(67.7)
饮酒1034(28.8)673(27.2)361(32.3)
糖尿病0.8450.358
2933(81.8)2030(82.2)903(80.8)
654(18.2)440(17.8)214(19.2)
抑郁、焦虑情绪43.909<0.001
2822(78.7)2019(81.7)803(71.9)
765(21.3)451(18.3)314(28.1)
失眠问题38.161<0.001
1549(43.2)1152(46.6)397(35.5)
2038(56.8)1318(53.4)720(64.5)
服药状况62.334<0.001
按医嘱规律服用2910(81.1)2090(84.6)820(73.4)
未按医嘱规律服用677(18.9)380(15.4)297(26.6)
随访频率(次/年)5.2010.023
≥42519(70.2)1764(71.4)755(67.6)
<41068(29.8)706(28.6)362(32.4)
随访形式2.5280.232
签约家庭医生入户随访1694(47.2)1189(48.1)505(45.2)
未随访447(12.5)298(12.1)149(13.3)
其他随访1446(40.3)983(39.8)463(41.5)
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Logistic regression analysis of factors affecting blood pressure control in Sichuan Province

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变量OR值(95%CI)P
年龄(岁)≥65
<651.164(0.985~1.375)0.075
性别男性
女性0.923(0.763~1.116)0.407
城乡城市
农村1.702(1.450~1.997)<0.001
受教育程度没上过学
小学或初中0.856(0.707~1.035)0.108
高中或技校0.636(0.440~0.919)0.016
大专或本科及以上0.458(0.245~0.859)0.015
家庭人均收入(元/年)>14400
≤144001.343(1.145~1.574)<0.001
体育锻炼锻炼
几乎不锻炼1.192(1.022~1.39)0.025
BMI正常
偏瘦0.708(0.511~0.98)0.038
超重或肥胖1.017(0.868~1.192)0.832
吸烟状况从未吸烟
现在或曾经吸烟1.216(0.987~1.498)0.067
饮酒状况从未饮酒
饮酒1.208(1.009~1.447)0.040
糖尿病
1.379(1.137~1.673)0.001
抑郁、焦虑情绪
1.535(1.284~1.836)<0.001
失眠问题
1.402(1.196~1.643)<0.001
服药状况按医嘱规律服用
未按医嘱规律服用1.742(1.453~2.089)<0.001
随访频率(次/年)≥4
<41.287(1.057~1.567)0.012
随访形式签约家庭医生入户随访
未随访1.058(0.794~1.409)0.702
其他随访1.286(1.092~1.516)0.003
), ArticleFig(id=1241023935815414377, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929872085405, language=CN, label=表2, caption=

四川省城乡居民高血压患者血压控制情况随访管理因素logistic回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量OR值(95%CI)P
年龄(岁)≥65
<651.164(0.985~1.375)0.075
性别男性
女性0.923(0.763~1.116)0.407
城乡城市
农村1.702(1.450~1.997)<0.001
受教育程度没上过学
小学或初中0.856(0.707~1.035)0.108
高中或技校0.636(0.440~0.919)0.016
大专或本科及以上0.458(0.245~0.859)0.015
家庭人均收入(元/年)>14400
≤144001.343(1.145~1.574)<0.001
体育锻炼锻炼
几乎不锻炼1.192(1.022~1.39)0.025
BMI正常
偏瘦0.708(0.511~0.98)0.038
超重或肥胖1.017(0.868~1.192)0.832
吸烟状况从未吸烟
现在或曾经吸烟1.216(0.987~1.498)0.067
饮酒状况从未饮酒
饮酒1.208(1.009~1.447)0.040
糖尿病
1.379(1.137~1.673)0.001
抑郁、焦虑情绪
1.535(1.284~1.836)<0.001
失眠问题
1.402(1.196~1.643)<0.001
服药状况按医嘱规律服用
未按医嘱规律服用1.742(1.453~2.089)<0.001
随访频率(次/年)≥4
<41.287(1.057~1.567)0.012
随访形式签约家庭医生入户随访
未随访1.058(0.794~1.409)0.702
其他随访1.286(1.092~1.516)0.003
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四川省高血压患者随访管理与血压控制情况关系研究
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喻瑞 1 , 谢嘉龙 1 , 唐雪薇 1 , 张雪莉 2 , 任晓晖 1
现代预防医学 | 健康与社会行为 2025,52(3): 508-512
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现代预防医学 | 健康与社会行为 2025, 52(3): 508-512
四川省高血压患者随访管理与血压控制情况关系研究
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喻瑞1, 谢嘉龙1, 唐雪薇1, 张雪莉2, 任晓晖1
作者信息
  • 1.四川大学华西公共卫生学院/华西第四医院,四川 成都610041
  • 2.四川省卫生健康信息中心/四川省医疗大数据中心
  • 喻瑞(1994—),男,硕士,科研助理,研究方向:统计方法在流行病学中的应用

通讯作者:

任晓晖,E-mail:
Study on the relationship between follow-up management and blood pressure control in hypertensive patients in Sichuan Province
Rui YU1, Jia-long XIE1, Xue-wei TANG1, Xue-li ZHANG2, Xiao-hui REN1
Affiliations
  • West China School of Public Health / West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-02-10 doi: 10.20043/j.cnki.MPM.202410379
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目的

旨在探讨四川省高血压患者随访管理对血压控制的影响,以提高人群血压控制率。

方法

基于四川省第七次国家卫生服务调查数据,纳入3 587名高血压患者。采用描述性统计分析患者的随访管理情况、人口学特征、生活行为及健康状况,结合多因素logistic回归模型探讨影响血压控制的随访管理因素。

结果

血压控制率为68.9%。在有效控制的患者中,按医嘱规律服药率为84.6%,随访频率≥4占比71.4%,签约家庭医生入户随访率为48.1%;未有效控制的患者中,按医嘱规律服药率为73.4%,随访频率≥4占比67.6%,签约家庭医生入户随访率为45.2%。多因素logistic回归分析显示,未按医嘱规律服药(OR=1.742,95%CI:1.453~2.089)、随访频率<4 (OR=1.287,95%CI:1.057~1.567)和其他随访方式(OR=1.286,95%CI:1.092~1.516)对患者血压控制效果有显著的负面影响。

结论

对高血压的随访管理有利于血压控制,应该优化随访频率、提高药物依从性和增强签约医生与患者的互动。

高血压  /  血压控制  /  随访管理  /  第七次国家卫生服务调查
Objective

To explore the impact of follow-up management on blood pressure control in hypertensive patients in Sichuan Province, so as to improve the blood pressure control rate in the population.

Methods

Based on the data of the Seventh National Health Service Survey in Sichuan province, 3 587 hypertensive patients were included. Descriptive statistical analysis was used to analyze the follow-up management situation, demographic characteristics, lifestyle behaviors and health status of patients. Combined with the multivariate logistic regression model, the follow-up management factors affecting blood pressure control were explored.

Results

The blood pressure control rate was 68.9%. Among the effectively controlled patients, the rate of taking medications regularly as prescribed was 84.6%, the proportion of those with a follow-up frequency of ≥4 was 71.4%, and the rate of family doctor-signed home visits was 48.1%. Among the patients not effectively controlled, the rate of taking medications regularly as prescribed was 73.4%, the proportion of those with a follow-up frequency of ≥4 was 67.6%, and the rate of family doctor-signed home visits was 45.2%. Multivariate Logistic regression analysis showed that not taking medications regularly as prescribed (OR=1.742, 95%CI:1.453-2.089), a follow-up frequency of <4 (OR=1.287, 95%CI: 1.057-1.567) and other follow-up methods (OR=1.286, 95%CI:1.092-1.516) had significant negative impacts on the blood pressure control effect of patients.

Conclusion

Follow-up management of hypertension is beneficial to blood pressure control. The follow-up frequency should be optimized, drug compliance should be improved, and the interaction between the signed doctor and the patient should be enhanced.

Hypertension  /  Blood pressure control  /  Follow-up management  /  Seventh National Health Service Survey
喻瑞, 谢嘉龙, 唐雪薇, 张雪莉, 任晓晖. 四川省高血压患者随访管理与血压控制情况关系研究. 现代预防医学, 2025 , 52 (3) : 508 -512 . DOI: 10.20043/j.cnki.MPM.202410379
Rui YU, Jia-long XIE, Xue-wei TANG, Xue-li ZHANG, Xiao-hui REN. Study on the relationship between follow-up management and blood pressure control in hypertensive patients in Sichuan Province[J]. Modern Preventive Medicine, 2025 , 52 (3) : 508 -512 . DOI: 10.20043/j.cnki.MPM.202410379
高血压为全球最重要的慢性疾病之一,截至2019年,全球约有13亿人患有高血压,30~79岁成人中的高血压患病率为33.0%,其控制情况及其相关危险因素的研究,一直是公共卫生领域的重点。尽管高血压药物治疗已经广泛普及,但在经济欠发达地区和农村人群中,血压控制率仍然偏低[1]。我国高血压的患病率、伤残率较高,而知晓率、控制率较低,未控制的高血压对社会经济造成了沉重的负担[2]。现已有大量研究探讨了高血压患者的生活方式、人口学特征及共病情况对血压控制的影响[3],但关于高血压患者接受的随访服务与血压控制之间的关系的研究相对较少[4]。若能早期探讨高血压患者随访服务情况对于心血管健康的收益,可为高血压防治提供一定参考。
本研究基于四川省第七次国家卫生服务调查数据,探讨按医嘱规律服药、随访频率、随访形式、人口学特征等多个因素对高血压控制的影响,旨在为高血压患者的管理和干预策略的制定提供科学依据,以提高高血压的管理水平,最终改善患者的健康预后。
本研究采用2023年四川省第七次国家卫生服务调查数据,调查采用多阶段分层随机抽样方法,在四川省随机抽取14个市(州),每个市(州)随机抽取1个县(市、区),每个县(市、区)随机抽取5个乡镇(街道),每个乡镇(街道)中随机抽取2个村(居委会),最后在每个村(居委会)随机抽取60户,共计8 403个居民户,18 035个居民。本研究纳入3 587例高血压患者进行分析。纳入标准为:(1)年龄15岁及以上;(2)医生诊断明确的高血压患者;(3)当地常住人口。本研究经四川大学伦理委员会审查并批准(审批: Gwll2022090),所有调查对象参与调查前均签署了知情同意书。
采用入户调查方式,利用计算机辅助面访系统进行面对面询问,收集的信息包括基本人口学特征、个人生活行为方式、慢性疾病患病情况等,高血压随访管理内容包括高血压患者按医嘱规律服药情况、随访频率及形式情况。血压控制情况是根据《全国第七次卫生服务调查指导手册》中的相关条目,即“您目前(最近一次测量)血压是否正常”定义。调查指导员对数据进行审核验证。
使用R 4.3.3进行数据整理与统计分析。描述性分析变量包括人口学特征、生活行为方式、高血压随访管理以及慢性病患病情况等,计数资料组间比较采用χ2检验。采用多因素logistic回归分析高血压的影响因素,血压控制定义为0,未控制为1。计算比值比(OR)与95%置信区间(95%CI)。双侧检验水准α=0.05。
本研究共纳入3 587名高血压患者,年龄≥65岁的高血压患者占67.8%,男性占48.2%,城市人口占51.0%,有体育锻炼习惯的患者占55.2%,从未饮酒占比71.2%,从不吸烟占比77.3%。81.1%的患者按医嘱规律服药,70.2%的患者高血压随访频率达到4次及以上,患者签约家庭医生入户随访占47.2%。3 587名高血压患者中,2 470人血压正常,血压控制率为68.9%。血压控制组中,按医嘱规律服药的患者比例为84.6%,高于未控制组的73.4% (P<0.001)。高血压控制患者随访次数≥4的比例为71.4%,高于未控制组的67.6%(P=0.023)。见表1
多因素logistic回归分析表明,按医嘱规律服药情况、随访频率和随访方式对高血压患者血压控制有重要影响。未按医嘱规律服药(OR=1.742,95%CI:1.453~2.089)、每年随访频率少于四次(OR=1.287,95%CI:1.057~1.567的患者血压未控制风险增加。相较于签约家庭医生入户随访,其他随访方式不利于血压控制(OR=1.286,95%CI:1.092~1.516)。见表2
本研究利用四川省第七次国家卫生服务调查数据,分析了四川高血压患者的血压控制现状,探讨了随访管理因素对血压控制的影响。结果显示,2023年四川地区高血压患者中血压控制正常的比例为68.85%。高于第六次国家卫生服务调查我国居民自报高血压患者血压控制率为52.32%,四川地区为54.6%的结果[5]。这表明,近年来四川地区的高血压患者在血压控制方面取得了一定的进步,可能与加强的随访管理和医疗服务的改进密切相关。不良的血压控制是心血管疾病和脑血管疾病最常见的可归因风险因素,包括出血性中风(58%)、缺血性中风(50%)、缺血性心脏病(55%)以及其他心血管疾病(58%)[6-7]。尽管过去几十年中,全球已实施多项行动以提升高血压的认知和控制水平[8-9],但血压控制率仍不理想。本研究结果距离全球高血压“80-80-80”控制目标,即知晓率、治疗率和治疗控制率均达到80%,仍有较大的差距。因此,进一步优化高血压随访管理显得尤为重要。建议在未来的公共卫生策略中,继续提升患者的高血压认知和自我管理能力,增加基层卫生服务的可及性,加强对高危人群的定期筛查和干预,从而有效降低高血压相关的心脑血管疾病负担。
本研究从按医嘱规律服药情况、随访频率和随访形式三方面评估高血压随访管理对血压控制的影响。结果显示,良好的服药依从性能够明显提高血压控制率,从而降低心血管事件的发生风险[10-13]。因此,可通过多种大众健康教育(媒体、宣传栏等)和进一步加强临床医生指导来提高高血压患者的服药依从性。《国家基本公共卫生服务(第三版)》要求对于原发性高血压患者,每年至少提供四次随访。本研究结果表明,随访频率未达标,即<4次随访的患者,其血压控制不如接受更多随访的患者,与田海艳等[14]研究结论一致。定期的随访不仅有助于监测患者的血压情况,还可通过持续的健康教育和行为干预来增强患者的治疗依从性和自我管理能力。本研究发现,签约家庭医生入户随访相较于其他随访方式(如前往医疗机构就诊或随访、其他医生入户随访、电话随访或网络随访)对血压控制的效果更佳。家庭医生能够根据患者在治疗过程中遇到的问题,例如不良反应、生活方式调整的困难等,提供更为个性化和贴近患者生活的医疗服务,从而在患者的血压管理中发挥更积极的作用[15]。因此,为了提高高血压患者的血压控制率,应从多方面加强随访管理,确保随访频率达到每年至少4次,并通过个性化治疗方案、药物教育和用药评估,增强患者对治疗的理解与信任。研究表明,签约家庭医生入户随访可提高血压控制率,因此应强化家庭医生制度,促进医患沟通,提升依从性和随访效果。
本研究也存在一些局限性:一是,由于本研究为横断面设计,无法确定血压控制与随访管理之间的因果关系。二是,潜在的混杂因素没有控制完全,这可能会导致结果出现偏倚。未来研究应考虑采用纵向设计,全面探索影响血压控制的多种因素,从而为制定更有效的干预策略提供科学依据。
  • 四川省2023年卫生服务专项调查
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2025年第52卷第3期
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doi: 10.20043/j.cnki.MPM.202410379
  • 接收时间:2024-10-20
  • 首发时间:2026-03-18
  • 出版时间:2025-02-10
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  • 收稿日期:2024-10-20
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四川省2023年卫生服务专项调查
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    1.四川大学华西公共卫生学院/华西第四医院,四川 成都610041
    2.四川省卫生健康信息中心/四川省医疗大数据中心

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