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Article(id=1228016570874659720, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202503069, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741017600000, receivedDateStr=2025-03-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1770711565941, onlineDateStr=2026-02-10, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770711565941, onlineIssueDateStr=2026-02-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770711565941, creator=13701087609, updateTime=1770711565941, updator=13701087609, issue=Issue{id=1228016566646801206, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='18', pageStart='3265', pageEnd='3456', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770711564932, creator=13701087609, updateTime=1770711815039, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1228017615784833769, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1228017615784833770, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3311, endPage=3317, ext={EN=ArticleExt(id=1228016573747757132, articleId=1228016570874659720, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Exploring the co-morbidity pattern of patients with osteofluorosis in different endemic areas-association rule-based and systematic cluster analysis, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze and compare the characteristics of comorbidity patterns in skeletal fluorosis patients across different endemic regions, laying the foundation for further research on influencing factors, while providing references for healthcare systems to develop more targeted, effective, and cost-efficient chronic disease management plans for this special population.

Methods

This study adopted a cross-sectional design, selecting patients over 40 years old with skeletal fluorosis from Nayong County, Guizhou Province (a coal-burning fluorosis endemic area), Jishan County, Shanxi Province (a water-drinking fluorosis endemic area), and Ruoergai County, Sichuan Province (a tea-drinking fluorosis endemic area) as research subjects. The Apriori algorithm was used to analyze the dataset, and indicators such as the minimum conditional support were set to derive disease association rules. Additionally, Yule’s Q method was applied for systematic cluster analysis, and a dendrogram was drawn to explore the comorbidity patterns of chronic diseases in the elderly.

Results

In the coal-burning type disease area, patients aged over 70 accounted for the highest proportion (43.55%), and the prevalence rates of chronic kidney disease (12.61%), hypertension (33.24%), and cholelithiasis/cholecystosis (11.89%) were higher than those in the drinking-water type and tea-drinking type disease areas. The tea-drinking type disease area was dominated by individuals aged 50-60 years (38.57%), with the highest prevalence of other bone diseases (68.93%). The drinking-water type disease area had the largest proportion of patients aged 60-70 years (43.04%).Comorbidity analysis showed that the coal-burning type disease area had the highest comorbidity rate (43.98%). In terms of comorbidity patterns, the most typical combination of two concurrent diseases was diabetes-coronary heart disease, while the combination of three concurrent diseases was mainly diabetes-coronary heart disease-hypertension. The tea-drinking type disease area had a comorbidity rate of 34.29%, with the main two-disease comorbidity pattern being coronary heart disease-cholelithiasis/cholecystosis, and the three-disease comorbidity pattern adding other bone diseases to the above combination. The drinking-water type disease area had the lowest comorbidity rate (21.43%), with the main two-disease comorbidity being cholelithiasis/cholecystosis-stroke, and the three-disease comorbidity pattern being stroke combined with diabetes and hypertension.Cluster analysis independently showed that the coal-burning type disease area could be clustered into 6 categories (dominated by metabolic cardiovascular diseases), the tea-drinking type disease area into 4 categories (highlighting metabolic skeletal diseases), and the drinking-water type disease area into 5 categories (characterized by multi-system metabolic inflammatory diseases).

Conclusion

There are significant differences in the comorbidity patterns of skeletal fluorosis patients among coal-burning, tea-drinking, and water-drinking fluorosis endemic areas. The coal-burning endemic area is dominated by metabolic and cardiovascular diseases such as diabetes, coronary heart disease, and hypertension. In the tea-drinking endemic area, there is a significant association between coronary heart disease and gallstones/gallbladder cysts, as well as a comorbidity pattern of diabetes and pulmonary tuberculosis. The water-drinking endemic area is characterized by the association between gallstones/gallbladder cysts and stroke; meanwhile, the combination of kidney disease and metabolic diseases highlights multisystem damage.

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目的

分析并比较不同病区氟骨症患者共病模式特点，为下一步的影响因素研究奠定基础，同时为医疗保健系统针对氟骨症患者这一特殊群体制定更具针对性、有效性和经济性的慢性病管理方案提供参考。

方法

本研究采用横断面研究，选取贵州省纳雍县（燃煤型氟中毒病区）、山西省稷山县（饮水型氟中毒病区）和四川省若尔盖县（饮茶型氟中毒病区）的40岁以上氟骨症患者为研究对象。使用Apriori算法分析数据集，设定最低条件支持度等指标得出疾病关联规则，并运用Yule’s Q法系统聚类分析，绘制树状聚类图探讨老年慢性病共病模式。

结果

燃煤型病区70岁以上患者占比最高(43.55%)，慢性肾病(12.61%)、高血压(33.24%)及胆结石/胆囊肿(11.89%）患病率高于饮水型和饮茶型病区；饮茶型病区以50~60岁为主(38.57%)，其他骨病患病率最高(68.93%)。饮水型病区以60~70岁患者居多(43.04%)。共病分析显示，燃煤型病区共病率最高(43.98%)，两病共患以糖尿病-冠心病组合最为典型，三病共患则以糖尿病-冠心病-高血压为主；饮茶型病区共病率为34.29%，主要两病共患模式为冠心病-胆结石/胆囊肿，共患三种疾病模式则在此基础上增加其他骨病；饮水型病区共病率最低(21.43%)，两病共患主要为为胆结石/胆囊肿-中风，共患三种疾病模式为中风共患糖尿病和高血压。聚类分析独立显示，燃煤型病区可聚为6类（以代谢心血管疾病为主），饮茶型病区4类（突出代谢骨骼疾病），饮水型病区5类（以多系统代谢炎性疾病为特征）。

结论

在燃煤型、饮茶型和饮水型氟中毒病区中，氟骨症患者的共病模式存在显著差异。燃煤型病区以糖尿病、冠心病和高血压等代谢心血管疾病为主，饮茶型病区则表现为冠心病与胆结石/胆囊肿的显著关联，以及糖尿病与肺结核的共病模式，饮水型病区则以胆结石/胆囊肿与中风的关联为特点，同时肾病与代谢性疾病的组合凸显了多系统损害。

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洪峰和罗鹏为共同通信作者。洪峰，E-mail：；
罗鹏，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=fhHSBJ9ofOlW1PRxzo6kew==, magXml=3O2egXZOv2NdDg9agK3OYA==, pdfUrl=null, pdf=MiX0OPfkXO8NgSTsJ6fItA==, pdfFileSize=817234, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=77fvpGPUEOHpBHWODejbnw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=uH2HXRnUbnYOj8YwwIx/Qw==, mapNumber=null, authorCompany=null, fund=null, authors=

陶傅宇（2000—），男，硕士在读，研究方向：环境与慢性病流行病学

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陶傅宇（2000—），男，硕士在读，研究方向：环境与慢性病流行病学

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Chinese Journal of Prevention and Control of Chronic Diseases, 2025, 33(1): 61-65.(In Chinese), articleTitle=Research progress on the pathophysiological mechanism of cardiovascular-renal-metabolic syndrome, refAbstract=null)], funds=[Fund(id=1228016582526436005, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, awardId=20222022YFC2503003, language=CN, fundingSource=2022国家重点研发项目(20222022YFC2503003), fundOrder=null, country=null), Fund(id=1228016582631293610, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, awardId=黔科合重大专项字［2024］015, language=CN, fundingSource=贵州省科技重大专项项目(黔科合重大专项字［2024］015), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1228016576188842262, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, xref=1．, ext=[AuthorCompanyExt(id=1228016576201425176, tenantId=1146029695717560320, journalId=1227665162245664772, 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postcode=null, companyName=null, departmentName=null, remark=4．四川省疾病预防控制中心地方病预防控制所)]), AuthorCompany(id=1228016576687964495, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, xref=5．, ext=[AuthorCompanyExt(id=1228016576692158799, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, companyId=1228016576687964495, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=5．山西省地方病防治研究所)])], figs=[ArticleFig(id=1228016580664164950, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Fig.1, caption=Dendrogram of comorbidity patterns in coal-burning disease area, figureFileSmall=bLBBFaDXzfBXSvZk/RtfbQ==, figureFileBig=77fvpGPUEOHpBHWODejbnw==, tableContent=null), ArticleFig(id=1228016580752245339, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=图1, caption=燃煤型病区共病模式树状聚类图, figureFileSmall=bLBBFaDXzfBXSvZk/RtfbQ==, figureFileBig=77fvpGPUEOHpBHWODejbnw==, tableContent=null), ArticleFig(id=1228016581020680809, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Fig.2, caption=Dendrogram of comorbidity patterns in tea-drinking disease area, figureFileSmall=2hqsQUgc6qHzGlOMP2i1Vg==, figureFileBig=cHqvVKnJYanbdBleWNMAuQ==, tableContent=null), ArticleFig(id=1228016581108761195, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=图2, caption=饮茶型病区共病模式树状聚类图, figureFileSmall=2hqsQUgc6qHzGlOMP2i1Vg==, figureFileBig=cHqvVKnJYanbdBleWNMAuQ==, tableContent=null), ArticleFig(id=1228016581242978930, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Fig.3, caption=Dendrogram of comorbidity patterns in drinking-water diseasearea, figureFileSmall=+ifY+riQIFxmlcPv14vy8g==, figureFileBig=Y9JUO+oLSpYH5Z23CqBmQg==, tableContent=null), ArticleFig(id=1228016581368808055, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=图3, caption=饮水型病区共病模式树状聚类图, figureFileSmall=+ifY+riQIFxmlcPv14vy8g==, figureFileBig=Y9JUO+oLSpYH5Z23CqBmQg==, tableContent=null), ArticleFig(id=1228016581503025790, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Table 1, caption=

Baseline characteristics of different disease areas ［n(%) ］

, figureFileSmall=null, figureFileBig=null, tableContent=
条目地区
饮水型病区饮茶型病区燃煤型病区
年龄段（岁）
40~4932(5.71)148(26.43)27(3.87)
50~59150(26.79)216(38.57)146(20.92)
60~69241(43.04)132(23.57)221(31.66)
≥70137(24.46)64(11.43)304(43.55)
性别
男222(39.64)251(44.82)251(35.96)
女338(60.36)309(55.18)447(64.04)
慢性病患病情况
慢性肾病13(2.32)9(1.61)88(12.61)
其他骨病182(32.50)386(68.93)320(45.85)
高血压161(28.75)136(24.29)232(33.24)
糖尿病30(5.36)23(4.11)47(6.73)
冠心病45(8.04)23(4.11)33(4.73)
中风13(2.32)10(1.79)15(2.15)
肺结核1(0.18)15(2.68)14(2.01)
慢性肝炎/肝硬化14(2.50)8(1.43)18(2.58)
胆结石/胆囊肿21(3.75)53(9.46)83(11.89)
精神心理疾病0(0.00)1(0.18)2(0.29)
脑外伤3(0.54)6(1.07)11(1.58)
), ArticleFig(id=1228016581616272001, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=表1, caption=

不同病区基线情况［n(%) ］

, figureFileSmall=null, figureFileBig=null, tableContent=
条目地区
饮水型病区饮茶型病区燃煤型病区
年龄段（岁）
40~4932(5.71)148(26.43)27(3.87)
50~59150(26.79)216(38.57)146(20.92)
60~69241(43.04)132(23.57)221(31.66)
≥70137(24.46)64(11.43)304(43.55)
性别
男222(39.64)251(44.82)251(35.96)
女338(60.36)309(55.18)447(64.04)
慢性病患病情况
慢性肾病13(2.32)9(1.61)88(12.61)
其他骨病182(32.50)386(68.93)320(45.85)
高血压161(28.75)136(24.29)232(33.24)
糖尿病30(5.36)23(4.11)47(6.73)
冠心病45(8.04)23(4.11)33(4.73)
中风13(2.32)10(1.79)15(2.15)
肺结核1(0.18)15(2.68)14(2.01)
慢性肝炎/肝硬化14(2.50)8(1.43)18(2.58)
胆结石/胆囊肿21(3.75)53(9.46)83(11.89)
精神心理疾病0(0.00)1(0.18)2(0.29)
脑外伤3(0.54)6(1.07)11(1.58)
), ArticleFig(id=1228016581721129605, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Table 2, caption=

Comorbidity association rules in coal-burning disease area

, figureFileSmall=null, figureFileBig=null, tableContent=
后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
糖尿病冠心病4.5325.813.84
肾病慢性肝炎/肝硬化2.4947.063.66
胆结石/胆囊肿慢性肝炎/肝硬化2.4935.292.98
胆结石/胆囊肿糖尿病6.7323.912.02
高血压糖尿病6.7365.221.95
肾病胆结石/胆囊肿11.8424.691.92
胆结石/胆囊肿冠心病4.5322.581.91
肾病糖尿病6.7323.911.86
肾病肺结核2.0521.431.67
高血压中风2.1953.331.59
其他骨病糖尿病6.7369.571.52
共患三种疾病模式
糖尿病冠心病和高血压2.1946.676.94
糖尿病冠心病和其他骨病2.3431.254.65
肾病糖尿病和其他骨病4.6831.252.43
高血压糖尿病和其他骨病4.6865.631.96
高血压冠心病和其他骨病2.3456.251.68
高血压胆结石/胆囊肿和其他骨病5.9953.661.60
其他骨病糖尿病和高血压4.3970.001.52
), ArticleFig(id=1228016581914067596, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=表2, caption=

燃煤型病区共病关联规则

, figureFileSmall=null, figureFileBig=null, tableContent=
后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
糖尿病冠心病4.5325.813.84
肾病慢性肝炎/肝硬化2.4947.063.66
胆结石/胆囊肿慢性肝炎/肝硬化2.4935.292.98
胆结石/胆囊肿糖尿病6.7323.912.02
高血压糖尿病6.7365.221.95
肾病胆结石/胆囊肿11.8424.691.92
胆结石/胆囊肿冠心病4.5322.581.91
肾病糖尿病6.7323.911.86
肾病肺结核2.0521.431.67
高血压中风2.1953.331.59
其他骨病糖尿病6.7369.571.52
共患三种疾病模式
糖尿病冠心病和高血压2.1946.676.94
糖尿病冠心病和其他骨病2.3431.254.65
肾病糖尿病和其他骨病4.6831.252.43
高血压糖尿病和其他骨病4.6865.631.96
高血压冠心病和其他骨病2.3456.251.68
高血压胆结石/胆囊肿和其他骨病5.9953.661.60
其他骨病糖尿病和高血压4.3970.001.52
), ArticleFig(id=1228016582035702419, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=EN, label=Table 3, caption=

Comorbidity association rules in tea-drinking disease area

, figureFileSmall=null, figureFileBig=null, tableContent=
后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
冠心病胆结石/胆囊肿6.2213.797.14
糖尿病史肺结核2.6813.333.25
胆结石/胆囊肿肺结核2.6820.002.11
高血压史糖尿病4.1134.781.44
高血压史冠心病3.9331.821.32
高血压史其他骨病68.9329.271.21
其他骨病冠心病3.9381.821.19
其他骨病肺结核2.6880.001.16
其他骨病糖尿病4.1178.261.14
其他骨病胆结石/胆囊肿9.4675.471.09
共患三种疾病模式
冠心病胆结石/胆囊肿和其他骨病7.1415.003.82
胆结石/胆囊肿肺结核和其他骨病2.1425.002.64
高血压糖尿病和其他骨病3.2138.891.61
高血压冠心病和其他骨病3.2133.331.38
其他骨病胆结石/胆囊肿和高血压2.1483.331.21
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饮茶型病区共病关联规则

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后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
冠心病胆结石/胆囊肿6.2213.797.14
糖尿病史肺结核2.6813.333.25
胆结石/胆囊肿肺结核2.6820.002.11
高血压史糖尿病4.1134.781.44
高血压史冠心病3.9331.821.32
高血压史其他骨病68.9329.271.21
其他骨病冠心病3.9381.821.19
其他骨病肺结核2.6880.001.16
其他骨病糖尿病4.1178.261.14
其他骨病胆结石/胆囊肿9.4675.471.09
共患三种疾病模式
冠心病胆结石/胆囊肿和其他骨病7.1415.003.82
胆结石/胆囊肿肺结核和其他骨病2.1425.002.64
高血压糖尿病和其他骨病3.2138.891.61
高血压冠心病和其他骨病3.2133.331.38
其他骨病胆结石/胆囊肿和高血压2.1483.331.21
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Comorbidity association rules in drinking-water disease area

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后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
胆结石/胆囊肿中风2.1916.674.36
糖尿病中风2.1916.673.16
冠心病肾病2.1925.003.05
糖尿病慢性肝炎、肝硬化2.3715.382.91
冠心病胆结石/胆囊肿3.8319.052.32
冠心病慢性肝炎、肝硬化2.3715.381.88
高血压糖尿病5.2862.071.36
高血压冠心病8.2060.001.31
高血压肾病2.1958.331.28
高血压中风2.1958.331.28
高血压胆结石/胆囊肿3.8347.621.04
共患三种疾病模式
中风糖尿病和高血压3.2811.115.08
肾病胆结石/胆囊肿和高血压1.8210.004.58
中风胆结石/胆囊肿和高血压1.8210.004.58
冠心病胆结石/胆囊肿和高血压1.8230.003.66
胆结石/胆囊肿冠心病和高血压4.9211.112.90
糖尿病胆结石/胆囊肿和高血压1.8210.001.89
), ArticleFig(id=1228016582383829664, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016570874659720, language=CN, label=表4, caption=

饮水型病区共病关联规则

, figureFileSmall=null, figureFileBig=null, tableContent=
后项前项支持度百分比（%）置信度百分比（%）提升度
共患两种疾病模式
胆结石/胆囊肿中风2.1916.674.36
糖尿病中风2.1916.673.16
冠心病肾病2.1925.003.05
糖尿病慢性肝炎、肝硬化2.3715.382.91
冠心病胆结石/胆囊肿3.8319.052.32
冠心病慢性肝炎、肝硬化2.3715.381.88
高血压糖尿病5.2862.071.36
高血压冠心病8.2060.001.31
高血压肾病2.1958.331.28
高血压中风2.1958.331.28
高血压胆结石/胆囊肿3.8347.621.04
共患三种疾病模式
中风糖尿病和高血压3.2811.115.08
肾病胆结石/胆囊肿和高血压1.8210.004.58
中风胆结石/胆囊肿和高血压1.8210.004.58
冠心病胆结石/胆囊肿和高血压1.8230.003.66
胆结石/胆囊肿冠心病和高血压4.9211.112.90
糖尿病胆结石/胆囊肿和高血压1.8210.001.89
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不同病区氟骨症患者共病模式的探索-基于关联规则与系统聚类分析
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陶傅宇 1 , 卢芸 1, 2 , 叶红兵 3 , 李津蜀 4 , 贾清珍 5 , 罗鹏 1, 2 , 洪峰 1, 2
现代预防医学 | 环境与职业卫生 2025,52(18): 3311-3317
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现代预防医学 | 环境与职业卫生 2025, 52(18): 3311-3317
不同病区氟骨症患者共病模式的探索-基于关联规则与系统聚类分析
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陶傅宇1, 卢芸1, 2, 叶红兵3, 李津蜀4, 贾清珍5, 罗鹏1, 2 , 洪峰1, 2
作者信息
  • 1．贵州医科大学公共卫生与健康学院，环境污染与疾病监控教育部重点实验室，贵州　贵阳　561113
  • 2．贵州医科大学省部共建地方病及民族区域性疾病防控协同创新中心
  • 3．贵州省疾病预防控制中心地方病预防控制所
  • 4．四川省疾病预防控制中心地方病预防控制所
  • 5．山西省地方病防治研究所

    • 陶傅宇（2000—），男，硕士在读，研究方向：环境与慢性病流行病学

通讯作者:

洪峰和罗鹏为共同通信作者。洪峰，E-mail：；
罗鹏，E-mail：
Exploring the co-morbidity pattern of patients with osteofluorosis in different endemic areas-association rule-based and systematic cluster analysis
Fu-yu TAO1, Yun LU1, 2, Hong-bing YE3, Jin-shu LI4, Qing-zhen JIA5, Peng LUO1, 2 , Feng HONG1, 2
Affiliations
  • School of Public Health and Health Sciences, Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
出版时间: 2025-09-25 doi: 10.20043/j.cnki.MPM.202503069
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摘要
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目的

分析并比较不同病区氟骨症患者共病模式特点，为下一步的影响因素研究奠定基础，同时为医疗保健系统针对氟骨症患者这一特殊群体制定更具针对性、有效性和经济性的慢性病管理方案提供参考。

方法

本研究采用横断面研究，选取贵州省纳雍县（燃煤型氟中毒病区）、山西省稷山县（饮水型氟中毒病区）和四川省若尔盖县（饮茶型氟中毒病区）的40岁以上氟骨症患者为研究对象。使用Apriori算法分析数据集，设定最低条件支持度等指标得出疾病关联规则，并运用Yule’s Q法系统聚类分析，绘制树状聚类图探讨老年慢性病共病模式。

结果

燃煤型病区70岁以上患者占比最高(43.55%)，慢性肾病(12.61%)、高血压(33.24%)及胆结石/胆囊肿(11.89%）患病率高于饮水型和饮茶型病区；饮茶型病区以50~60岁为主(38.57%)，其他骨病患病率最高(68.93%)。饮水型病区以60~70岁患者居多(43.04%)。共病分析显示，燃煤型病区共病率最高(43.98%)，两病共患以糖尿病-冠心病组合最为典型，三病共患则以糖尿病-冠心病-高血压为主；饮茶型病区共病率为34.29%，主要两病共患模式为冠心病-胆结石/胆囊肿，共患三种疾病模式则在此基础上增加其他骨病；饮水型病区共病率最低(21.43%)，两病共患主要为为胆结石/胆囊肿-中风，共患三种疾病模式为中风共患糖尿病和高血压。聚类分析独立显示，燃煤型病区可聚为6类（以代谢心血管疾病为主），饮茶型病区4类（突出代谢骨骼疾病），饮水型病区5类（以多系统代谢炎性疾病为特征）。

结论

在燃煤型、饮茶型和饮水型氟中毒病区中，氟骨症患者的共病模式存在显著差异。燃煤型病区以糖尿病、冠心病和高血压等代谢心血管疾病为主，饮茶型病区则表现为冠心病与胆结石/胆囊肿的显著关联，以及糖尿病与肺结核的共病模式，饮水型病区则以胆结石/胆囊肿与中风的关联为特点，同时肾病与代谢性疾病的组合凸显了多系统损害。

氟骨症  /  共病模式  /  关联规则  /  聚类分析
Objective

To analyze and compare the characteristics of comorbidity patterns in skeletal fluorosis patients across different endemic regions, laying the foundation for further research on influencing factors, while providing references for healthcare systems to develop more targeted, effective, and cost-efficient chronic disease management plans for this special population.

Methods

This study adopted a cross-sectional design, selecting patients over 40 years old with skeletal fluorosis from Nayong County, Guizhou Province (a coal-burning fluorosis endemic area), Jishan County, Shanxi Province (a water-drinking fluorosis endemic area), and Ruoergai County, Sichuan Province (a tea-drinking fluorosis endemic area) as research subjects. The Apriori algorithm was used to analyze the dataset, and indicators such as the minimum conditional support were set to derive disease association rules. Additionally, Yule’s Q method was applied for systematic cluster analysis, and a dendrogram was drawn to explore the comorbidity patterns of chronic diseases in the elderly.

Results

In the coal-burning type disease area, patients aged over 70 accounted for the highest proportion (43.55%), and the prevalence rates of chronic kidney disease (12.61%), hypertension (33.24%), and cholelithiasis/cholecystosis (11.89%) were higher than those in the drinking-water type and tea-drinking type disease areas. The tea-drinking type disease area was dominated by individuals aged 50-60 years (38.57%), with the highest prevalence of other bone diseases (68.93%). The drinking-water type disease area had the largest proportion of patients aged 60-70 years (43.04%).Comorbidity analysis showed that the coal-burning type disease area had the highest comorbidity rate (43.98%). In terms of comorbidity patterns, the most typical combination of two concurrent diseases was diabetes-coronary heart disease, while the combination of three concurrent diseases was mainly diabetes-coronary heart disease-hypertension. The tea-drinking type disease area had a comorbidity rate of 34.29%, with the main two-disease comorbidity pattern being coronary heart disease-cholelithiasis/cholecystosis, and the three-disease comorbidity pattern adding other bone diseases to the above combination. The drinking-water type disease area had the lowest comorbidity rate (21.43%), with the main two-disease comorbidity being cholelithiasis/cholecystosis-stroke, and the three-disease comorbidity pattern being stroke combined with diabetes and hypertension.Cluster analysis independently showed that the coal-burning type disease area could be clustered into 6 categories (dominated by metabolic cardiovascular diseases), the tea-drinking type disease area into 4 categories (highlighting metabolic skeletal diseases), and the drinking-water type disease area into 5 categories (characterized by multi-system metabolic inflammatory diseases).

Conclusion

There are significant differences in the comorbidity patterns of skeletal fluorosis patients among coal-burning, tea-drinking, and water-drinking fluorosis endemic areas. The coal-burning endemic area is dominated by metabolic and cardiovascular diseases such as diabetes, coronary heart disease, and hypertension. In the tea-drinking endemic area, there is a significant association between coronary heart disease and gallstones/gallbladder cysts, as well as a comorbidity pattern of diabetes and pulmonary tuberculosis. The water-drinking endemic area is characterized by the association between gallstones/gallbladder cysts and stroke; meanwhile, the combination of kidney disease and metabolic diseases highlights multisystem damage.

Skeletal fluorosis  /  Comorbidity pattern  /  Association rule  /  Systematic clustering
陶傅宇, 卢芸, 叶红兵, 李津蜀, 贾清珍, 罗鹏, 洪峰. 不同病区氟骨症患者共病模式的探索-基于关联规则与系统聚类分析. 现代预防医学, 2025 , 52 (18) : 3311 -3317 . DOI: 10.20043/j.cnki.MPM.202503069
Fu-yu TAO, Yun LU, Hong-bing YE, Jin-shu LI, Qing-zhen JIA, Peng LUO, Feng HONG. Exploring the co-morbidity pattern of patients with osteofluorosis in different endemic areas-association rule-based and systematic cluster analysis[J]. Modern Preventive Medicine, 2025 , 52 (18) : 3311 -3317 . DOI: 10.20043/j.cnki.MPM.202503069
正文
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氟元素对人体健康存在双重效应，适量的氟作为人体必需微量元素，然而，若长期过量摄入氟，则会诱发氟中毒现象。地方性氟中毒属于一种慢性全身性疾病，在全球范围内广泛流行，地方性氟中毒主要有三种类型：燃煤型氟中毒、饮水型氟中毒及饮砖茶型氟中毒[1]。氟骨症作为氟中毒最严峻的病理状态，是地方性氟中毒病区居民因氟化物摄入过量，引发四肢大关节、颈、腰部疼痛，伴有关节、神经功能障碍，以及骨和关节 X 线征象异常的慢性代谢性骨病[2]。其中，有研究表明，氟骨症患者健康状况较一般人差[3-4]，同时目前氟骨症患者普遍为中老年人，老年人健康问题的突出特点之一就是“共病”，又称“多病共存”，是指老年人个体同时存在2种及以上慢性健康问题[5]。对于已经患有氟骨症的患者，重点是采取综合救助救治措施帮助其缓解症状、减轻痛苦，提高生存质量。氟骨症患者的治疗和服务管理已成为当前地方病防治的重点任务[6]，这与当下国家政策呼应。而三个病区的生活环境、文化、饮食均有所差异，共病模式可能也会有所不同。了解氟骨症患者的共病模式有利于医疗保健系统针对氟骨症患者这一特殊群体制定更具针对性、有效性和经济性的慢性病管理方案。
本研究采用 Apriori 关联规则与系统聚类分析，探究氟骨症患者共病模式。Apriori算法挖掘共病关联规律，系统聚类揭示疾病层次结构，二者互补验证结果可靠性。研究发现特定共病组合，有助于实施个体化健康管理，改善患者生存质量。
1　对象与方法
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1.1　研究内容
本研究来源于2022年国家重点研发计划项目“地方性氟中毒早期识别和精准诊疗关键技术研究”（课题编号：2022YFC2503003）中课题3 氟中毒有效治疗药物的筛选及诊疗效果评价研究支持，已通过伦理审查（贵州医科大学人体试验伦理委员会 2023伦审第（189）号），以贵州省纳雍县（燃煤型氟中毒病区）、山西省稷山县（饮水型氟中毒病区 ）和四川省若尔盖县（饮茶型氟中毒病区 ）为研究地点，结合 WS/T 192—2021 地方性氟骨症诊断标准可诊断为地方性氟骨症患者。本研究采用横断面调查设计，对40岁以上自愿参与该队列研究的氟骨症患者人群进行调查。贵州地区纳入698名氟骨症患者；饮水型病区纳入560名氟骨症患者；饮茶型病区纳入560名氟骨症患者。采集了这些患者的社会人口学信息（如性别、年龄等）、疾病相关资料（如现病史登记情况等）。
1.2　统计学方法
本研究运用SPSS Modeler 18.0数据挖掘软件，采用Apriori算法挖掘疾病关联规则。通过系统调整最低条件支持度、最小规则置信度与最大前项数，获取最优关联规则，并基于置信度、规则支持度及提升度开展规则筛选与评价。同时，运用Yule Q 法进行系统聚类分析，通过计算逻辑距离并绘制树状聚类图，探究老年慢性病共病模式。
在不同病区共病模式挖掘中，研究采用差异化参数设置策略：燃煤型病区数据量大且分布集中，初始设支持度≥2%、置信度≥20%、提升度≥1.5、最小项集数2，识别11种两病共患模式；提升置信度至≥30%、最小项集数设为3后，获得7种三病共患模式。饮茶型病区数据稀疏，设支持度≥2.5%、置信度≥10%、提升度≥1、最小项集数2，发现10种两病共患模式；调整置信度至≥15%、最小项集数3后，识别出5种三病共患模式。饮水型病区采用支持度≥2%、置信度≥15%、提升度≥1、最小项集数2，得到11种两病共患模式；调整支持度至≥1.5%、置信度≥10%、最小项集数3后，确定6种三病共患模式。各病区参数设置充分考量数据特征，通过提升度筛选强关联规则，并对三病共患模式设定更高置信度标准，以保障复杂关联规则的可靠性。
2　结果
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2.1　基线情况
表1结果显示，在不同病区中，饮水型病区以60~70岁人群居多，占比43.04%；饮茶型病区50~60岁人群占比 38.57%；燃煤型病区70岁以上人群占比 43.55%。性别上，各病区均是女性多于男性。慢性病患病情况显示，燃煤型病区慢性肾病患病率显著高于其他病区（12.61%），饮茶型病区其他骨病患病率最高（68.93%），而高血压在燃煤型病区更为常见（33.24%）。此外，胆结石/胆囊肿在燃煤型病区的患病率也较高（11.89%）。
2.2　燃煤型病区共病模式分析
在燃煤型病区中，307例氟骨症患者存在共病现象，患病率达43.98%。基于关联规则提升度分析，两病共患模式主要为糖尿病合并冠心病、肾病合并慢性肝炎/肝硬化、胆结石/胆囊肿合并慢性肝炎/肝硬化；三病共患模式则以糖尿病合并冠心病与高血压、糖尿病合并冠心病与其他骨病、肾病合并糖尿病与其他骨病为主（表2）。
聚类分析将11种慢性病划分为6类疾病模式：第一类为消化代谢系统疾病模式，包含肾病、慢性肝炎/肝硬化、胆结石/胆囊肿；第二类是代谢心血管疾病模式，涵盖糖尿病、冠心病、高血压；第三类为精神心理疾病模式；第四类为脑外伤模式；第五类是神经骨骼系统疾病模式，包括其他骨病、中风；第六类为肺结核模式（图1）。
2.3　饮茶型病区共病模式分析
饮茶型病区192名氟骨症患者存在共病，共病患病率34.29%。基于提升度，两病共患模式主要为冠心病共患胆结石/胆囊肿、糖尿病共患肺结核、胆结石/胆囊肿共患肺结核；三病共患模式以冠心病、胆结石/胆囊肿与其他骨病，胆结石/胆囊肿、肺结核与其他骨病，以及高血压、糖尿病与其他骨病等组合为主（表3）。
聚类分析将11种慢性病聚为4簇：代谢骨骼疾病簇含其他骨病、高血压等；创伤与感染疾病簇涵盖肺结核等；循环泌尿消化系统簇包括肾病等；精神心理疾病单独成簇（图2）。
2.4　饮水型病区共病模式分析
在饮水型病区中，120名氟骨症患者存在共病情况，共病患病率为 21.43%。提升度排名前三的共病模式显示，两病共患主要为胆结石/胆囊肿合并中风、糖尿病合并中风、冠心病合并肾病；三病共患主要为中风合并糖尿病和高血压、肾病合并胆结石/胆囊肿和高血压、中风合并胆结石/胆囊肿和高血压（表4）。聚类分析将11种慢性病分为5类疾病模式，依次为多系统代谢炎性疾病（中风、肺结核、其他骨病、胆结石/胆囊肿、糖尿病）、心肾血管系统疾病（肾病、冠心病、高血压）、精神心理疾病、脑外伤及慢性肝脏疾病（图3）。
3　讨论
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自21世纪以来，全球疾病谱发生显著转变，传染病患病率呈下降趋势，而慢性非传染性疾病（慢性病）发病率持续攀升。慢性病仍是老年人口发病与死亡的重要诱因[7-8]，共病问题已成为全球公共卫生领域的严峻挑战[9]。当前，慢性病共病研究多聚焦于一般中老年人群，针对氟骨症患者慢性病共病状况的研究在国内外仍相对匮乏。
氟中毒通过过量氟化物摄入，对人体多系统产生广泛影响，其核心机制与氟的氧化应激作用紧密相关。氟化物在体内可诱导活性氧（ROS）生成[10]，引发氧化应激，进而损伤细胞膜、蛋白质和DNA，诱发炎症反应与代谢紊乱。这种氧化应激机制或为三个病区共病模式中糖尿病、高血压、冠心病等代谢性疾病高发的共同病理基础。此外，氟化物还可通过干扰酶活性、破坏钙磷代谢及内分泌平衡[11-12]，加剧多系统损害。因此，三个病区的氟骨症患者普遍呈现以代谢综合征为核心，涵盖心血管疾病、肾病和胆道疾病的共病模式。
在燃煤型病区，氟骨症患者中糖尿病与冠心病表现出较高关联度，这与既往研究中糖尿病会增加心血管疾病风险的结论一致[13]。糖尿病、冠心病和高血压的三病共患模式较为常见，凸显了代谢综合征在该群体中的重要性。系统聚类分析将疾病分为6簇，消化代谢系统疾病和代谢心血管疾病为主要疾病簇，与现有研究结论相符[14]。此外，精神心理疾病和神经骨骼系统疾病簇的存在，提示该群体心理与神经骨骼健康问题不容忽视。对此，燃煤型病区应强化代谢性疾病早期筛查与综合管理，重点关注心血管和心理健康，同时提供心理支持与骨骼健康干预。
饮茶型病区中，冠心病与胆结石/胆囊肿关联显著，这或与当地居民高脂肪、高胆固醇饮食习惯及高海拔环境有关[15-16]。此外，肺结核与糖尿病的共病模式值得关注，已有研究表明糖尿病患者因免疫功能下降，结核感染风险更高[17]。聚类结果显示，代谢骨骼疾病和循环泌尿消化系统疾病为主要疾病簇，且其他骨病患病率较高，提示可能存在复杂共病网络。因此，饮茶型病区应改善饮食结构，减少高脂肪、高胆固醇食物摄入，倡导健康饮茶习惯。
在饮水型病区，胆结石/胆囊肿与中风的关联较为突出，这可能与胆道疾病引发的慢性炎症和血栓形成风险增加有关[18]。过量氟摄入可损害消化系统与血管系统，影响肝脏代谢和胆汁成分，促进胆结石形成[19]；同时损伤血管内皮细胞，诱发炎症反应，增加中风风险[20]。糖尿病与中风的共病模式也与代谢性疾病的血管并发症相关。肾病、胆结石/胆囊肿和高血压的组合，表明肾脏疾病在代谢性疾病多系统影响中的重要作用[21]。疾病聚类结果显示，多系统代谢—炎性相关性疾病以及心肾血管系统综合疾病的聚类，强调了代谢性疾病与炎症反应的协同作用。针对饮水型病区，需加强胆道疾病和心血管疾病预防，重点关注慢性炎症和血栓风险。
本研究存在一定局限性。关联规则挖掘的参数设定依赖经验判断，虽结合各病区数据特征调整，但仍可能因主观选择导致规则偏差；且作为横断面研究，缺乏长期随访数据，难以明确疾病发生时序与因果关联。未来研究可采用队列研究设计追踪疾病发展，结合机器学习算法优化参数选择，深入探究共病模式差异的影响因素。
尽管存在不足，本研究填补了不同类型氟中毒疾病共病规律的研究空白，为氟中毒相关疾病防控提供新思路，有望推动区域性精准干预策略的发展。
基金
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  • 2022国家重点研发项目(20222022YFC2503003)
  • 贵州省科技重大专项项目(黔科合重大专项字［2024］015)
文献
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doi: 10.20043/j.cnki.MPM.202503069
  • 接收时间：2025-03-04
  • 首发时间：2026-02-10
  • 出版时间：2025-09-25
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  • 收稿日期：2025-03-04
基金
2022国家重点研发项目(20222022YFC2503003)
贵州省科技重大专项项目(黔科合重大专项字［2024］015)
作者信息
    1．贵州医科大学公共卫生与健康学院，环境污染与疾病监控教育部重点实验室，贵州　贵阳　561113
    2．贵州医科大学省部共建地方病及民族区域性疾病防控协同创新中心
    3．贵州省疾病预防控制中心地方病预防控制所
    4．四川省疾病预防控制中心地方病预防控制所
    5．山西省地方病防治研究所

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洪峰和罗鹏为共同通信作者。洪峰，E-mail：；
罗鹏，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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