Article(id=1323941301246374776, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202504423, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745424000000, receivedDateStr=2025-04-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793581803856, onlineDateStr=2026-11-02, pubDate=1765296000000, pubDateStr=2025-12-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793581803856, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793581803856, creator=13701087609, updateTime=1793581803856, updator=13701087609, issue=Issue{id=1323941237702668764, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='23', pageStart='4225', pageEnd='4416', issueExtLink='null', onlineDate='null', pubDate='1765296000000', pubDateStr='2025-12-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793581788707, creator='13701087609', updateTime=1793581887795, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1323941653374959780, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1323941653374959781, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4296, endPage=4302, ext={EN=ArticleExt(id=1323941301804217209, articleId=1323941301246374776, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between Geriatric Nutritional Risk Index and metabolic syndrome among elderly people of ethnic minorities in Guizhou Province, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between the Geriatric Nutritional Risk Index(GNRI) and metabolic syndrome(MS) among elderly people of ethnic minorities in Guizhou Province, providing scientific evidence for the health management of the elderly in this region.

Methods

Based on the “Southwest Regional Cohort Study of Natural Populations of Ethnic Minorities”, this study included 4 521 elderly individuals aged 60 and above from the Miao, Dong, and Bouyei ethnic groups in Guizhou Province. Data on demographic characteristics, lifestyle, physical examination, and biochemical indicators were collected. Logistic regression, subgroup analyses, and restricted cubic splines (RCS) were used to evaluate the association between GNRI and MS. Within each ethnic group, the optimal cut-offs from ROC curves (107.9 for the overall population, 108.0 for the Miao, 110.1 for the Dong, and 106.0 for the Bouyei) were applied to categorize GNRI into high and low levels for subsequent sensitivity analyses.

Results

The overall prevalence of MS was 23.9%, with prevalence rates of 24.6%, 25.4%, and 21.3% among the Miao, Dong, and Bouyei ethnic groups, respectively. In Model 3, which adjusted for all covariates, GNRI as a continuous variable was positively correlated with MS risk in the total population, Miao, and Dong groups, with OR (95% CI) of 1.07 (1.05-1.09), 1.07 (1.04-1.10), and 1.07 (1.04-1.11), respectively. However, this association was not significant in the Bouyei group (P=0.172). When GNRI was categorized, in the total population and Miao and Dong groups, higher GNRI quartiles(Q2-Q4) were associated with a gradient increase in MS risk compared with the Q1 reference group. However, this association was not statistically significant in the Q2 group or in any quartile group of the Bouyei ethnic group. Sensitivity analysis showed that the high-GNRI group had a significantly increased risk of MS (overall population: OR=1.98; Miao: OR=2.43; Dong: OR=1.76; all P<0.001), whereas the association remained non-significant in the Bouyei population (OR=1.03, P=0.845). Subgroup analysis showed that GNRI interacted with ethnicity and educational level, with stronger associations in the Dong group and among individuals with lower educational levels. RCS analysis indicated a linear positive association between GNRI and MS in the total population, while a non-linear positive association was observed in the Dong, Miao, and Bouyei groups.

Conclusion

Among the elderly Miao and Dong populations in Guizhou, an elevated GNRI was an independent risk factor for MS. No such association was observed in the Bouyei ethnic group. The relationship between GNRI and MS varied by ethnicity, indicating that ethnicity-specific nutritional intervention cut-offs and MS prevention strategies should be developed.

, authors=Shu-yan CHENG, En-hui ZHOU, Fei XIAO, Yuan WANG, Yi-li SHEN, Feng HONG, authorsList=Shu-yan CHENG, En-hui ZHOU, Fei XIAO, Yuan WANG, Yi-li SHEN, Feng HONG, authorCompany=null, correspAuthors=Feng HONG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1323941304887030655, articleId=1323941301246374776, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=老年营养风险指数与贵州省少数民族老年人群代谢综合征的相关性分析, columnId=1228016573034721597, journalTitle=现代预防医学, columnName=营养与食品卫生, runingTitle=null, highlight=null, articleAbstract=
目的

探讨老年营养风险指数(geriatric nutritional risk index,GNRI)与贵州省少数民族老年人群代谢综合征(metabolic syndrome,MS)的相关性,为该地区老年人群的健康管理提供科学依据。

方法

本研究基于西南区域少数民族聚集地世居自然人群队列研究,纳入贵州省60岁及以上苗族、侗族、布依族老年人群共4 521名。收集人口学特征、生活方式、体格检查和生化指标等数据,采用logistic回归、亚组分析及限制性立方样条评估GNRI与MS的关联;进一步在各民族内部采用受试者工作特征曲线最佳切点(总人群为107.9、苗族为108.0、侗族为110.1、布依族为106.0)将GNRI分为高、低两组进行敏感性分析。

结果

MS总检出率为23.9%,苗族、侗族和布依族的检出率分别为24.6%、25.4%和21.3%。在调整所有协变量的模型3中,GNRI作为连续变量时,总人群、苗族和侗族人群中GNRI与MS风险呈正相关,OR值(95% CI)分别为1.07(1.05~1.09)、1.07(1.04~1.10)和1.07(1.04~1.11),但布依族中该关联无统计学意义(P=0.172)。GNRI作为分类变量时,以Q1(GNRI最低四分位数)为参照,总人群、苗族和侗族人群中较高GNRI四分位数(Q2~Q4)与MS风险的增加呈梯度关系,但在Q2组和布依族各四分位分组中均无统计学意义。敏感性分析显示,高GNRI组MS风险显著增加(总人群OR=1.98,苗族OR=2.43,侗族OR=1.76,均P<0.001),布依族仍无意义(OR= 1.03,P=0.845)。亚组分析显示,GNRI与民族和文化程度存在交互作用,侗族人群和文化程度较低者的关联性更强。限制性立方样条分析表明,总人群中GNRI与MS呈线性正相关关系,而侗族、苗族和布依族中呈非线性正相关关系。

结论

在贵州省苗族、侗族老年人群中,GNRI升高是MS的独立危险因子;布依族未观察到该关联。GNRI与MS的关系存在民族差异,应针对不同民族制定相应的营养干预切点与代谢综合征防控策略。

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程淑燕(1999—),女,硕士在读,研究方向:代谢综合征

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洪峰,E-mail:
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International Journal of Molecular Sciences, 2023, 24 (9): 898., articleTitle=Mechanisms of oxidative stress in metabolic syndrome, refAbstract=null), Reference(id=1323941314554901455, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, doi=null, pmid=null, pmcid=null, year=2024, volume=10, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[21], rfOrder=28, authorNames=Ding Y, Wu XL, Cao QY, journalName=JMIR Public Health and Surveillance, refType=null, unstructuredReference=Ding Y, Wu XL, Cao QY, et al. Gender disparities in the association between educational attainment and Cardiovascular-Kidney- Metabolic syndrome: Cross-Sectional study [J]. JMIR Public Health and Surveillance, 2024, 10: e57920., articleTitle=Gender disparities in the association between educational attainment and Cardiovascular-Kidney- Metabolic syndrome: Cross-Sectional study, refAbstract=null)], funds=[Fund(id=1323941310016664497, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, awardId=2017YFC0907301, language=CN, fundingSource=国家重点研发计划课题(2017YFC0907301), fundOrder=null, country=null), Fund(id=1323941310075384754, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, awardId=82173566, language=CN, fundingSource=国家自然科学基金(82173566), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1323941305121911680, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, xref=null, ext=[AuthorCompanyExt(id=1323941305130300289, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, companyId=1323941305121911680, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education,Guizhou Medical University, Guiyang, Guizhou 561113, China), AuthorCompanyExt(id=1323941305134494594, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, companyId=1323941305121911680, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=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)])], figs=[ArticleFig(id=1323941307424584617, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=EN, label=Figure 1, caption=RCS curves of GNRI and MS in different ethnic populations, figureFileSmall=64sprjdCPsURNKjbqDWJvA==, figureFileBig=IZ4ee1pep+389ZgAysNaFg==, tableContent=null), ArticleFig(id=1323941309093917610, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=CN, label=图1, caption=不同民族GNRI与MS的RCS曲线

注:A为总人群;B为苗族;C为侗族;D为布依族;直方图灰色柱表示研究人群在不同GNRI区间的分布密度;黑色虚线标示GNRI参考值。

, figureFileSmall=64sprjdCPsURNKjbqDWJvA==, figureFileBig=IZ4ee1pep+389ZgAysNaFg==, tableContent=null), ArticleFig(id=1323941309442044843, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=EN, label=Table 1, caption=

Basic characteristics of the study participants [M (P25, P75), n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群(n=4 521)非MS组(n=3 439)MS组(n=1 082)χ2/Z值P值
年龄(岁)66.2 (63.1, 70.6)66.3 (63.2, 70.7)66.0 (63.1, 70.4)-0.6230.533
性别5.4000.022
男性1 905 (42.1)1 482 (43.1)423 (39.1)
女性2 616 (57.9)1 957 (56.9)659 (60.9)
民族7.7990.020
苗族1 295 (28.6)977 (28.4)318 (29.4)
侗族1 881 (41.6)1 403 (40.8)478 (44.2)
布依族1 345 (29.8)1 059 (30.8)286 (26.4)
婚姻状况5.8970.100
已婚/同居3 433 (75.9)2 605 (75.7)828 (76.5)
分居/离异84 ( 1.9)56 ( 1.6)28 ( 2.6)
丧偶996 (22.0)773 (22.5)223 (20.6)
从未结婚8 ( 0.2)5 ( 0.1)3 ( 0.3)
文化程度15.046<0.001
高中以下4 104 (90.8)3 154 (91.7)950 (87.8)
高中及以上417 ( 9.2)285 ( 8.3)132 (12.2)
吸烟状态7.5430.023
未吸烟3 407 (75.4)2 565 (74.6)842 (77.8)
目前吸烟829 (18.3)661 (19.2)168 (15.5)
已戒烟285 ( 6.3)213 ( 6.2)72 ( 6.7)
饮酒状态11.5960.003
从不或几乎不饮酒2 722 (60.2)2 040 (59.3)682 (63.0)
偶尔饮酒955 (21.1)719 (20.9)236 (21.8)
经常性饮酒844 (18.7)680 (19.8)164 (15.2)
饮茶状态4.0590.049
从不或几乎不饮茶3 767 (83.3)2 887 (83.9)880 (81.3)
饮茶754 (16.7)552 (16.1)202 (18.7)
高血压285.094<0.001
是1 446 (32.0)874 (25.4)572 (52.9)
否3 075 (68.0)2 565 (74.6)510 (47.1)
糖尿病303.906<0.001
是281 ( 6.2)93 ( 2.7)188 (17.4)
否4 240 (93.8)3 346 (97.3)894 (82.6)
高脂血症94.837<0.001
是173 ( 3.8)78 ( 2.3)95 ( 8.8)
否4 348 (96.2)3 361 (97.7)987 (91.2)
冠心病17.020<0.001
是223 ( 4.9)144 ( 4.2)79 ( 7.3)
否4 298 (95.1)3 295 (95.8)1003 (92.7)
腰围(cm)83.0 (76.0, 90.5)80.2 (74.0, 86.0)92.3 (88.0, 97.0)-34.597<0.001
甘油三酯(mmol/L)1.4 (1.0, 2.0)1.3 (1.0, 1.6)2.3 (1.9, 3.1)-35.837<0.001
HDL-C(mmol/L)1.5 (1.3, 1.7)1.5 (1.3, 1.8)1.3 (1.1, 1.5)-21.282<0.001
血糖(mmol/L)5.3 (5.0, 5.8)5.2 (4.9, 5.6)5.8 (5.2, 6.8)-22.055<0.001
收缩压(mm Hg)133.0 (120.3, 148.3)129.3 (117.3, 144.7)143.0 (132.3, 156.0)-18.418<0.001
舒张压(mm Hg)81.3 (74.3, 89.3)80.0 (73.0, 87.7)86.3 (79.3, 93.3)-15.407<0.001
BMI23.5 (21.1, 26.0)22.7 (20.5, 24.8)26.3 (24.6, 28.4)-30.529<0.001
白蛋白(g/L)45.7 (43.6, 47.9)45.4 (43.4, 47.6)46.5 (44.3, 48.8)-8.219<0.001
GNRI108.4 (104.7, 112.1)107.7 (103.9, 111.4)110.6 (107.5, 114.2)-15.769<0.001
GNRI分层211.363<0.001
Quartile 1 (<104.7)1 137 (25.1)1 002 (29.1)135 (12.5)
Quartile 2 [104.7~108.4)1 135 (25.1)914 (26.6)221 (20.4)
Quartile 3 [108.4~112.1)1 126 (24.9)810 (23.6)316 (29.2)
Quartile 4 (≥112.1)1 123 (24.8)713 (20.7)410 (37.9)
), ArticleFig(id=1323941309542708140, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=CN, label=表1, caption=

研究人群的基本特征[M(P25,P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群(n=4 521)非MS组(n=3 439)MS组(n=1 082)χ2/Z值P值
年龄(岁)66.2 (63.1, 70.6)66.3 (63.2, 70.7)66.0 (63.1, 70.4)-0.6230.533
性别5.4000.022
男性1 905 (42.1)1 482 (43.1)423 (39.1)
女性2 616 (57.9)1 957 (56.9)659 (60.9)
民族7.7990.020
苗族1 295 (28.6)977 (28.4)318 (29.4)
侗族1 881 (41.6)1 403 (40.8)478 (44.2)
布依族1 345 (29.8)1 059 (30.8)286 (26.4)
婚姻状况5.8970.100
已婚/同居3 433 (75.9)2 605 (75.7)828 (76.5)
分居/离异84 ( 1.9)56 ( 1.6)28 ( 2.6)
丧偶996 (22.0)773 (22.5)223 (20.6)
从未结婚8 ( 0.2)5 ( 0.1)3 ( 0.3)
文化程度15.046<0.001
高中以下4 104 (90.8)3 154 (91.7)950 (87.8)
高中及以上417 ( 9.2)285 ( 8.3)132 (12.2)
吸烟状态7.5430.023
未吸烟3 407 (75.4)2 565 (74.6)842 (77.8)
目前吸烟829 (18.3)661 (19.2)168 (15.5)
已戒烟285 ( 6.3)213 ( 6.2)72 ( 6.7)
饮酒状态11.5960.003
从不或几乎不饮酒2 722 (60.2)2 040 (59.3)682 (63.0)
偶尔饮酒955 (21.1)719 (20.9)236 (21.8)
经常性饮酒844 (18.7)680 (19.8)164 (15.2)
饮茶状态4.0590.049
从不或几乎不饮茶3 767 (83.3)2 887 (83.9)880 (81.3)
饮茶754 (16.7)552 (16.1)202 (18.7)
高血压285.094<0.001
是1 446 (32.0)874 (25.4)572 (52.9)
否3 075 (68.0)2 565 (74.6)510 (47.1)
糖尿病303.906<0.001
是281 ( 6.2)93 ( 2.7)188 (17.4)
否4 240 (93.8)3 346 (97.3)894 (82.6)
高脂血症94.837<0.001
是173 ( 3.8)78 ( 2.3)95 ( 8.8)
否4 348 (96.2)3 361 (97.7)987 (91.2)
冠心病17.020<0.001
是223 ( 4.9)144 ( 4.2)79 ( 7.3)
否4 298 (95.1)3 295 (95.8)1003 (92.7)
腰围(cm)83.0 (76.0, 90.5)80.2 (74.0, 86.0)92.3 (88.0, 97.0)-34.597<0.001
甘油三酯(mmol/L)1.4 (1.0, 2.0)1.3 (1.0, 1.6)2.3 (1.9, 3.1)-35.837<0.001
HDL-C(mmol/L)1.5 (1.3, 1.7)1.5 (1.3, 1.8)1.3 (1.1, 1.5)-21.282<0.001
血糖(mmol/L)5.3 (5.0, 5.8)5.2 (4.9, 5.6)5.8 (5.2, 6.8)-22.055<0.001
收缩压(mm Hg)133.0 (120.3, 148.3)129.3 (117.3, 144.7)143.0 (132.3, 156.0)-18.418<0.001
舒张压(mm Hg)81.3 (74.3, 89.3)80.0 (73.0, 87.7)86.3 (79.3, 93.3)-15.407<0.001
BMI23.5 (21.1, 26.0)22.7 (20.5, 24.8)26.3 (24.6, 28.4)-30.529<0.001
白蛋白(g/L)45.7 (43.6, 47.9)45.4 (43.4, 47.6)46.5 (44.3, 48.8)-8.219<0.001
GNRI108.4 (104.7, 112.1)107.7 (103.9, 111.4)110.6 (107.5, 114.2)-15.769<0.001
GNRI分层211.363<0.001
Quartile 1 (<104.7)1 137 (25.1)1 002 (29.1)135 (12.5)
Quartile 2 [104.7~108.4)1 135 (25.1)914 (26.6)221 (20.4)
Quartile 3 [108.4~112.1)1 126 (24.9)810 (23.6)316 (29.2)
Quartile 4 (≥112.1)1 123 (24.8)713 (20.7)410 (37.9)
), ArticleFig(id=1323941309651760045, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=EN, label=Table 2, caption=

Logistic regression analysis of GNRI and MS in different ethnic populations

, figureFileSmall=null, figureFileBig=null, tableContent=
GNRI总人群苗族侗族布依族
OR (95% CI)P值OR (95% CI)P值OR (95% CI)P值OR (95% CI)P值
模型1
连续型变量1.11 (1.09-1.12)<0.0011.09 (1.06~1.11)<0.0011.14 (1.12~1.17)<0.0011.11 (1.08~1.14)<0.001
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.79 (1.42~2.26)<0.0011.85 (1.19~2.87)0.0063.69 (2.01~6.77)<0.0011.51 (1.10~2.08)0.012
Q 32.90 (2.32~3.61)<0.0013.07 (2.04~4.62)<0.0017.52 (4.25~13.29)<0.0011.93 (1.33~2.79)<0.001
Q 44.27 (3.44~5.30)<0.0014.13 (2.74~6.22)<0.00111.17 (6.39~19.53)<0.0013.27 (2.06~5.18)<0.001
模型2
连续型变量1.11 (1.09~1.12)<0.0011.09 (1.06~1.11)<0.0011.14 (1.12~1.17)<0.0011.11 (1.08~1.14)<0.001
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.79 (1.42~2.26)<0.0011.83 (1.18~2.84)0.0073.65 (1.99~6.70)<0.0011.51 (1.10~2.08)0.012
Q 32.90 (2.33~3.63)<0.0013.05 (2.03~4.59)<0.0017.39 (4.18~13.08)<0.0011.93 (1.33~2.79)<0.001
Q 44.31 (3.47~5.36)<0.0014.13 (2.74~6.23)<0.00111.08 (6.34~19.38)<0.0013.27 (2.06~5.18)<0.001
模型3
连续型变量1.07 (1.05~1.09)<0.0011.07 (1.04~1.10)<0.0011.07 (1.04~1.11)<0.0011.03 (0.99~1.06)0.172
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.18 (0.91~1.54)0.2171.55(0.95~2.53)0.0801.65 (0.83~3.28)0.1550.79 (0.54~1.16)0.224
Q 31.65 (1.29~2.13)<0.0012.41 (1.52~3.81)<0.0012.12 (1.10~4.07)0.0240.93 (0.60~1.42)0.713
Q 42.40(1.87~3.07)<0.0013.24 (2.05~5.14)<0.0012.98 (1.57~5.65)<0.0011.36 (0.80~2.34)0.259
), ArticleFig(id=1323941309731451822, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=CN, label=表2, caption=

不同民族人群GNRI与MS的logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
GNRI总人群苗族侗族布依族
OR (95% CI)P值OR (95% CI)P值OR (95% CI)P值OR (95% CI)P值
模型1
连续型变量1.11 (1.09-1.12)<0.0011.09 (1.06~1.11)<0.0011.14 (1.12~1.17)<0.0011.11 (1.08~1.14)<0.001
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.79 (1.42~2.26)<0.0011.85 (1.19~2.87)0.0063.69 (2.01~6.77)<0.0011.51 (1.10~2.08)0.012
Q 32.90 (2.32~3.61)<0.0013.07 (2.04~4.62)<0.0017.52 (4.25~13.29)<0.0011.93 (1.33~2.79)<0.001
Q 44.27 (3.44~5.30)<0.0014.13 (2.74~6.22)<0.00111.17 (6.39~19.53)<0.0013.27 (2.06~5.18)<0.001
模型2
连续型变量1.11 (1.09~1.12)<0.0011.09 (1.06~1.11)<0.0011.14 (1.12~1.17)<0.0011.11 (1.08~1.14)<0.001
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.79 (1.42~2.26)<0.0011.83 (1.18~2.84)0.0073.65 (1.99~6.70)<0.0011.51 (1.10~2.08)0.012
Q 32.90 (2.33~3.63)<0.0013.05 (2.03~4.59)<0.0017.39 (4.18~13.08)<0.0011.93 (1.33~2.79)<0.001
Q 44.31 (3.47~5.36)<0.0014.13 (2.74~6.23)<0.00111.08 (6.34~19.38)<0.0013.27 (2.06~5.18)<0.001
模型3
连续型变量1.07 (1.05~1.09)<0.0011.07 (1.04~1.10)<0.0011.07 (1.04~1.11)<0.0011.03 (0.99~1.06)0.172
分类变量
Q 11 (ref)1 (ref)1 (ref)1 (ref)
Q 21.18 (0.91~1.54)0.2171.55(0.95~2.53)0.0801.65 (0.83~3.28)0.1550.79 (0.54~1.16)0.224
Q 31.65 (1.29~2.13)<0.0012.41 (1.52~3.81)<0.0012.12 (1.10~4.07)0.0240.93 (0.60~1.42)0.713
Q 42.40(1.87~3.07)<0.0013.24 (2.05~5.14)<0.0012.98 (1.57~5.65)<0.0011.36 (0.80~2.34)0.259
), ArticleFig(id=1323941309819532207, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941301246374776, language=EN, label=Table 3, caption=

Subgroup Analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
变量OR (95% CI)P值P for interaction
性别0.479
男性1.10 (1.08 ~ 1.12)<0.001
女性1.11 (1.09 ~ 1.13)<0.001
民族0.014
苗族1.09 (1.06 ~ 1.11)<0.001
侗族1.14 (1.12 ~ 1.17)<0.001
布依族1.11 (1.08 ~ 1.14)<0.001
文化程度0.002
高中以下1.11 (1.10 ~ 1.13)<0.001
高中及以上1.04 (1.00 ~ 1.08)0.041
吸烟状态0.855
未吸烟1.11 (1.08 ~ 1.13)<0.001
目前吸烟1.09 (1.04 ~ 1.14)<0.001
已戒烟1.10 (1.03 ~ 1.16)0.003
饮酒状态0.812
从不或几乎不饮酒1.11 (1.09 ~ 1.13)<0.001
偶尔饮酒1.10 (1.07 ~ 1.13)<0.001
经常性饮酒1.10 (1.06 ~ 1.14)<0.001
饮茶状态0.963
从不或几乎不饮茶1.11 (1.09 ~ 1.12)<0.001
饮茶1.11 (1.07 ~ 1.14)<0.001
冠心病0.223
是1.07 (1.02 ~ 1.13)0.004
否1.11 (1.09 ~ 1.12)<0.001
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亚组分析

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变量OR (95% CI)P值P for interaction
性别0.479
男性1.10 (1.08 ~ 1.12)<0.001
女性1.11 (1.09 ~ 1.13)<0.001
民族0.014
苗族1.09 (1.06 ~ 1.11)<0.001
侗族1.14 (1.12 ~ 1.17)<0.001
布依族1.11 (1.08 ~ 1.14)<0.001
文化程度0.002
高中以下1.11 (1.10 ~ 1.13)<0.001
高中及以上1.04 (1.00 ~ 1.08)0.041
吸烟状态0.855
未吸烟1.11 (1.08 ~ 1.13)<0.001
目前吸烟1.09 (1.04 ~ 1.14)<0.001
已戒烟1.10 (1.03 ~ 1.16)0.003
饮酒状态0.812
从不或几乎不饮酒1.11 (1.09 ~ 1.13)<0.001
偶尔饮酒1.10 (1.07 ~ 1.13)<0.001
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饮茶1.11 (1.07 ~ 1.14)<0.001
冠心病0.223
是1.07 (1.02 ~ 1.13)0.004
否1.11 (1.09 ~ 1.12)<0.001
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老年营养风险指数与贵州省少数民族老年人群代谢综合征的相关性分析
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程淑燕 , 周恩慧 , 肖斐 , 王媛 , 申毅力 , 洪峰
现代预防医学 | 营养与食品卫生 2025,52(23): 4296-4302
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现代预防医学 |营养与食品卫生 2025 , 52 (23) : 4296 -4302
老年营养风险指数与贵州省少数民族老年人群代谢综合征的相关性分析
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程淑燕, 周恩慧, 肖斐, 王媛, 申毅力, 洪峰
作者信息
  • 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
通讯作者:
洪峰,E-mail:
作者简介:

程淑燕(1999—),女,硕士在读,研究方向:代谢综合征

Association between Geriatric Nutritional Risk Index and metabolic syndrome among elderly people of ethnic minorities in Guizhou Province
Shu-yan CHENG, En-hui ZHOU, Fei XIAO, Yuan WANG, Yi-li SHEN, Feng HONG
Affiliations
  • School of Public Health, Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education,Guizhou Medical University, Guiyang, Guizhou 561113, China
出版时间: 2025-12-10 doi: 10.20043/j.cnki.MPM.202504423
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目的

探讨老年营养风险指数(geriatric nutritional risk index,GNRI)与贵州省少数民族老年人群代谢综合征(metabolic syndrome,MS)的相关性,为该地区老年人群的健康管理提供科学依据。

方法

本研究基于西南区域少数民族聚集地世居自然人群队列研究,纳入贵州省60岁及以上苗族、侗族、布依族老年人群共4 521名。收集人口学特征、生活方式、体格检查和生化指标等数据,采用logistic回归、亚组分析及限制性立方样条评估GNRI与MS的关联;进一步在各民族内部采用受试者工作特征曲线最佳切点(总人群为107.9、苗族为108.0、侗族为110.1、布依族为106.0)将GNRI分为高、低两组进行敏感性分析。

结果

MS总检出率为23.9%,苗族、侗族和布依族的检出率分别为24.6%、25.4%和21.3%。在调整所有协变量的模型3中,GNRI作为连续变量时,总人群、苗族和侗族人群中GNRI与MS风险呈正相关,OR值(95% CI)分别为1.07(1.05~1.09)、1.07(1.04~1.10)和1.07(1.04~1.11),但布依族中该关联无统计学意义(P=0.172)。GNRI作为分类变量时,以Q1(GNRI最低四分位数)为参照,总人群、苗族和侗族人群中较高GNRI四分位数(Q2~Q4)与MS风险的增加呈梯度关系,但在Q2组和布依族各四分位分组中均无统计学意义。敏感性分析显示,高GNRI组MS风险显著增加(总人群OR=1.98,苗族OR=2.43,侗族OR=1.76,均P<0.001),布依族仍无意义(OR= 1.03,P=0.845)。亚组分析显示,GNRI与民族和文化程度存在交互作用,侗族人群和文化程度较低者的关联性更强。限制性立方样条分析表明,总人群中GNRI与MS呈线性正相关关系,而侗族、苗族和布依族中呈非线性正相关关系。

结论

在贵州省苗族、侗族老年人群中,GNRI升高是MS的独立危险因子;布依族未观察到该关联。GNRI与MS的关系存在民族差异,应针对不同民族制定相应的营养干预切点与代谢综合征防控策略。

老年营养风险指数  /  代谢综合征  /  少数民族  /  老年人群
Objective

To investigate the association between the Geriatric Nutritional Risk Index(GNRI) and metabolic syndrome(MS) among elderly people of ethnic minorities in Guizhou Province, providing scientific evidence for the health management of the elderly in this region.

Methods

Based on the “Southwest Regional Cohort Study of Natural Populations of Ethnic Minorities”, this study included 4 521 elderly individuals aged 60 and above from the Miao, Dong, and Bouyei ethnic groups in Guizhou Province. Data on demographic characteristics, lifestyle, physical examination, and biochemical indicators were collected. Logistic regression, subgroup analyses, and restricted cubic splines (RCS) were used to evaluate the association between GNRI and MS. Within each ethnic group, the optimal cut-offs from ROC curves (107.9 for the overall population, 108.0 for the Miao, 110.1 for the Dong, and 106.0 for the Bouyei) were applied to categorize GNRI into high and low levels for subsequent sensitivity analyses.

Results

The overall prevalence of MS was 23.9%, with prevalence rates of 24.6%, 25.4%, and 21.3% among the Miao, Dong, and Bouyei ethnic groups, respectively. In Model 3, which adjusted for all covariates, GNRI as a continuous variable was positively correlated with MS risk in the total population, Miao, and Dong groups, with OR (95% CI) of 1.07 (1.05-1.09), 1.07 (1.04-1.10), and 1.07 (1.04-1.11), respectively. However, this association was not significant in the Bouyei group (P=0.172). When GNRI was categorized, in the total population and Miao and Dong groups, higher GNRI quartiles(Q2-Q4) were associated with a gradient increase in MS risk compared with the Q1 reference group. However, this association was not statistically significant in the Q2 group or in any quartile group of the Bouyei ethnic group. Sensitivity analysis showed that the high-GNRI group had a significantly increased risk of MS (overall population: OR=1.98; Miao: OR=2.43; Dong: OR=1.76; all P<0.001), whereas the association remained non-significant in the Bouyei population (OR=1.03, P=0.845). Subgroup analysis showed that GNRI interacted with ethnicity and educational level, with stronger associations in the Dong group and among individuals with lower educational levels. RCS analysis indicated a linear positive association between GNRI and MS in the total population, while a non-linear positive association was observed in the Dong, Miao, and Bouyei groups.

Conclusion

Among the elderly Miao and Dong populations in Guizhou, an elevated GNRI was an independent risk factor for MS. No such association was observed in the Bouyei ethnic group. The relationship between GNRI and MS varied by ethnicity, indicating that ethnicity-specific nutritional intervention cut-offs and MS prevention strategies should be developed.

Geriatric Nutritional Risk Index  /  Metabolic syndrome  /  Ethnic minorities  /  Elderly population
程淑燕, 周恩慧, 肖斐, 王媛, 申毅力, 洪峰. 老年营养风险指数与贵州省少数民族老年人群代谢综合征的相关性分析. 现代预防医学, 2025 , 52 (23) : 4296 -4302 . DOI: 10.20043/j.cnki.MPM.202504423
Shu-yan CHENG, En-hui ZHOU, Fei XIAO, Yuan WANG, Yi-li SHEN, Feng HONG. Association between Geriatric Nutritional Risk Index and metabolic syndrome among elderly people of ethnic minorities in Guizhou Province[J]. Modern Preventive Medicine, 2025 , 52 (23) : 4296 -4302 . DOI: 10.20043/j.cnki.MPM.202504423
随着我国人口老龄化加剧,老年人健康问题备受关注。代谢综合征(metabolic syndrome, MS)是一种以代谢紊乱为核心的症候群,涉及多系统、多脏腑的病变[1],它作为一种与生活方式密切相关的慢性疾病,已成为全球公共卫生的重要挑战,其主要特征包括肥胖、高血压、高血糖和血脂异常[2]。MS显著增加2型糖尿病患者慢性并发症、死亡及心脑血管事件风险[3-4]。根据我国统计,60岁及以上老年人群的MS患病率为58.1%[5]。另有研究显示,中国老年人群MS的患病率随年龄增长而显著升高,尤其是高龄人群[6]。
贵州省作为我国少数民族聚居的地区,其独特的地理环境、饮食习惯和生活方式可能对老年人群的MS发生具有特殊影响。例如,研究显示贵州省少数民族老年人群的膳食结构和营养状况存在显著差异,这可能与MS的发生密切相关[7]。老年营养风险指数(geriatric nutritional risk index, GNRI)作为一种评估老年人营养状况的工具,已被广泛应用于多种疾病的预后预测中[8-10]。然而,目前关于GNRI与贵州省少数民族老年人群MS的关系尚不明确。因此,本研究旨在探讨GNRI与贵州省少数民族老年人群MS的相关性,以期为该地区老年人群的健康管理提供科学依据。
研究对象来源于“西南区域少数民族聚集地世居自然人群队列研究”,该队列于2018年7月—2019年8月在贵州省建立,纳入60岁及以上苗族、侗族、布依族世居自然人群,共5 025名。排除标准包括:缺少基线资料(如人口学信息)、血常规数据(如血糖、甘油三酯和白蛋白等)以及身体测量数据(如血压、腰围等)的受检者。最终,共有4 521名研究对象纳入本研究。本研究已获得四川大学医学伦理委员会(K2016038)和贵州医科大学附属医院医学伦理委员会[2018(094)]的批准,所有参与者均为自愿加入,并已签署知情同意书。
(1)问卷调查:调查表采用“西南区域少数民族聚集地世居自然人群队列研究”基线问卷,包括人口学特征(性别、年龄、民族、婚姻状况、文化程度)、吸烟、饮酒、饮茶情况和疾病患病情况(高血压、糖尿病、高脂血症和冠心病)。
(2)体格检查:包括身高、体重、腰围、收缩压、舒张压。
(3)生化指标:包括白蛋白、高密度脂蛋白胆固醇(high-density lipoprotein cholesterol,HDL-C)、甘油三酯、空腹血糖。
(1)吸烟状态:未吸烟;吸烟(至今吸烟超过100支);已戒烟(戒烟超过半年及以上)。
(2)饮酒状态:从不或几乎不饮酒;偶尔饮酒(只在特殊场合下,如喜庆或节假日偶尔喝,或一年当中只在特定几个月里饮酒,如农忙或夏季,而其他季节一般不喝酒);经常性饮酒(一年当中不分季节,基本上每周至少喝一次酒)。
(3)饮茶状态:从不或几乎不饮茶;饮茶(曾经每周都喝茶并且持续半年以上)。
(4)身体质量指数(body mass index,BMI):体重/身高的二次方(kg/m2)。
(5)老年营养风险指数(GNRI)计算公式[11]:[1.489×白蛋白(g/L)]+[41.7×(体重/理想体重)]。理想体重使用Lorentz公式计算,男性:身高-100-[(身高-150)/4],女性:身高-100-[(身高-150)/2.5],身高的单位为cm。如果受检者的体重超过理想体重,则将体重与理想体重之比设置为1。
(6)血压:血压数据采用基线调查时三次测量结果的平均值。
根据《中国2型糖尿病防治指南(2020年版)(下)》[12],我国关于MS的诊断标准如下:具备三项或更多项即可诊断。
(1)腹型肥胖(即中心型肥胖):腰围男性≥90 cm,女性≥85 cm;(2)高血糖:空腹血糖≥6.1 mmol/L或糖负荷后2h血糖≥7.8 mmol/L和(或)已确诊为糖尿病并治疗者;(3)高血压:血压≥130/85 mm Hg(1 mm Hg=0.133 kPa)和(或)已确认为高血压并治疗者;(4)空腹甘油三酯≥1.70 mmol/L;(5)空腹HDL-C<1.04 mmol/L。
不服从正态分布的定量资料采用[M(P25,P75)]描述,定性资料采用频数(构成比)表示,定量和定性资料分别采用非参数检验和χ2检验比较受检者基线特征在MS组和非MS组的分布差异。Logistic回归模型分析GNRI与MS之间的关系,以OR和95%置信区间(confidence interval,CI)评估风险大小;logistic回归分析建立三个模型(将在MS组和非MS组中分布有统计学意义的协变量纳入相应模型):模型1未调整变量,模型2调整性别变量,模型3调整性别、文化程度、吸烟状态、饮酒状态、饮茶状态、冠心病和BMI变量。此外,通过亚组分析进一步探讨GNRI与MS之间的关联。采用限制性立方样条(restricted cubic splines, RCS)曲线来评价GNRI与MS的剂量反应关系。为评估GNRI与MS关联的稳健性,本研究进一步在各民族内部采用受试者工作特征(receiver operating characteristic,ROC)曲线最佳切点(总人群为107.9、苗族为108.0、侗族为110.1、布依族为106.0)将GNRI分为高(大于等于切点)、低(小于切点)两组进行敏感性分析。统计分析软件采用R 4.4.3,双侧检验,检验水准α=0.05。
本研究共纳入4 521例60岁及以上的老年居民,其中苗族1 295例,侗族1 881例,布依族1 345例。MS总检出率为23.9%,苗族、侗族和布依族检出率分别为24.6%、25.4%和21.3%。MS和非MS者在年龄和婚姻状况分布上差异无统计学意义(P>0.05),但在其他变量上分布差异有统计学意义(P<0.05)。见表1。
总体来看,GNRI作为连续变量时,GNRI与MS的关联在总人群、苗族和侗族人群的三个模型中均具有统计学意义(均P<0.001),而布依族在模型3中该关联不具有统计学意义(P=0.172)。具体来看,在调整所有变量的模型3中,总人群、苗族和侗族人群中GNRI每增加一个单位,MS的患病风险皆增加7%。GNRI作为分类变量时,在调整所有变量的模型3中,总人群、苗族和侗族的Q2~Q4组(以Q1为参照)MS患病风险随GNRI升高呈梯度增加,但在Q2组中无统计学意义。布依族在模型3中所有四分位分组均无统计学意义(P>0.05)。见表2。
我们按性别、民族、文化程度、吸烟状态、饮酒状态、饮茶状态和冠心病进行了亚组分析。民族和文化程度存在明显交互作用(P for interaction值分别为0.014和0.002),侗族人群(OR=1.14)关联性高于布依族(OR=1.11)和苗族(OR=1.09),高中以下人群(OR=1.11)关联性强于高中及以上人群(OR=1.04)。性别、吸烟状态、饮酒状态、饮茶状态及冠心病亚组的交互作用均无统计学意义(P for interaction>0.05)。见表3。
如图1所示,RCS曲线分析显示,在总人群(A)中,GNRI与MS之间存在线性关系(P for nonlinear =0.053),而在苗族(B)、侗族(C)和布依族(D)中,GNRI与MS之间存在非线性关系(P for nonlinear <0.05),在所有人群中,随着GNRI的增加,MS的风险逐渐升高(P for overall <0.001)。
敏感性分析采用ROC曲线确定的民族特异性切点(总人群为107.9、苗族为108.0、侗族为110.1、布依族为106.0)将GNRI分为高、低两组。在充分调整混杂因素的模型3中,高GNRI组MS风险增加:总人群OR为1.98(1.67~2.34),苗族OR为2.43(1.78~3.33),侗族OR为1.76(1.34~2.32)(均P<0.001);布依族未见统计学意义(P=0.845),与主分析结果一致,验证了GNRI与MS关联的稳健性及民族差异。
本研究通过分析贵州省4 521名少数民族老年人群的数据,发现MS总检出率为23.9%,苗族、侗族和布依族的检出率分别为24.6%、25.4%和21.3%,低于云南少数民族的27.1%[13]。这一差异可能与贵州省少数民族独特的饮食结构有关,如布依族以糯米、蔬菜和豆类为主食,其低脂高纤维的膳食模式可能有助于降低MS风险[14],这一发现与Na G等人[15]的研究一致,表明特定饮食成分(如糙米)对糖代谢的改善具有潜在益处。此外,贵州省少数民族的基因多态性也可能导致MS较低的检出率。例如,贵州省荔波县的研究表明,布依族女性的MTHFR C677T位点TT基因型频率显著低于汉族女性[16]。MTHFR基因多态性会影响叶酸代谢,进而影响同型半胱氨酸(Hcy)水平。较低的TT基因型频率可能降低布依族女性高Hcy血症的风险,而高Hcy血症是MS的独立危险因素之一[17],这可能在一定程度上降低了MS的患病风险。
本研究发现,GNRI与贵州省苗族和侗族老年人的MS风险呈正相关,但与布依族老年人的MS风险关联无统计学意义。采用ROC切点的敏感性分析在不同民族中均复现了主分析方向,进一步支持GNRI与MS的关联稳健;惟布依族效应消失,提示该关联可能因民族特异代谢或生活方式差异而强弱不一。值得一提的是,RCS分析显示布依族中GNRI与MS存在非线性正相关趋势,可能因样本量限制、数据分布及布依族独特生理代谢特征,目前证据尚不充分。未来将纳入其他可能未识别的因素,如遗传因素、体力劳动和心理压力等,以明确GNRI与布依族老年人MS风险的关系。RCS分析的结果表明:苗族、侗族和布依族人群中,当GNRI值分别约为109、112和107时,OR值开始大于1,且苗族和布依族人群中随着GNRI的增加,MS的风险逐渐升高,侗族人群中,当GNRI值约为115时,随着GNRI的增加,MS的风险基本保持平稳。这表明需要分民族关注GNRI临界值对MS的影响。目前,暂无更多证据显示GNRI与MS的关联,但GNRI在不同疾病中的作用得到验证,例如,Chen等[9]研究发现GNRI与术后谵妄风险呈负相关,GNRI与老年人骨质疏松症风险之间存在非线性负相关[18],较低的GNRI与中风相关性肺炎的较高患病率有关[19]。GNRI与MS呈正相关性而与其他疾病(如术后谵妄)呈负相关,可能是因为营养状态的双刃剑效应,GNRI通过白蛋白和体重指标评估营养风险,较高的GNRI通常反映较好的营养状态。然而,在MS的背景下,较高的体重(尤其是肥胖)可能通过增加内脏脂肪堆积、胰岛素抵抗和慢性炎症直接促进MS的发生[20]。
此外,我们发现文化程度、民族在GNRI与MS的关联中存在交互作用,低文化程度人群、侗族人群的关联性更强。可能与健康知识获取能力及饮食行为差异有关[21]。不同民族的饮食模式有所不同,前期研究显示侗族以油脂饮食模式为主,油脂饮食通过促进肥胖,使GNRI的“保护作用”转化为“风险信号”。
本研究为贵州省少数民族老年人群的健康管理提供了科学依据,揭示了少数民族间MS风险及GNRI作用的异质性,以更好地识别高风险人群。然而,本研究也存在一些局限性。一是,研究仅基于横断面数据,无法确定因果关系。二是,研究未考虑其他可能影响MS的因素,如遗传因素、体力劳动和心理压力等,未来需结合多组学数据进一步验证。
综上所述,在贵州省苗族、侗族老年人群中,GNRI升高是MS的独立危险因子;布依族未观察到该关联。GNRI与MS的关系存在民族差异,应针对不同民族制定相应的营养干预切点与MS防控策略。
  • 国家重点研发计划课题(2017YFC0907301)
  • 国家自然科学基金(82173566)
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2025年第52卷第23期
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doi: 10.20043/j.cnki.MPM.202504423
  • 接收时间:2025-04-24
  • 首发时间:2026-11-02
  • 出版时间:2025-12-10
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  • 收稿日期:2025-04-24
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国家重点研发计划课题(2017YFC0907301)
国家自然科学基金(82173566)
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    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

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2种不同金属材料的力学参数
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属
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species
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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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