Article(id=1322607964129706523, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202505342, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748188800000, receivedDateStr=2025-05-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793263911516, onlineDateStr=2026-10-29, pubDate=1761321600000, pubDateStr=2025-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793263911516, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793263911516, creator=13701087609, updateTime=1793263911516, updator=13701087609, issue=Issue{id=1322607837742747790, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='20', pageStart='3649', pageEnd='3840', issueExtLink='null', onlineDate='null', pubDate='1761321600000', pubDateStr='2025-10-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793263881383, creator='13701087609', updateTime=1793264238791, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322609336933794638, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322609336933794639, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3693, endPage=3697, ext={EN=ArticleExt(id=1322607966222664220, articleId=1322607964129706523, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between comsumption amount of Tibetan traditional food Tsampa and biological age acceleration, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between Tsampa consumption and biological age acceleration.

Methods

Utilizing baseline data from the China Multi-Ethnic Cohort study (CMEC), a composite biomarker-based biological age was constructed using the Klemera-Doubal Method (Biological age based on Klemera and Doubal’s method, KDM-BA). Biological aging was quantified as the difference between KDM-BA and chronological age. Tsampa consumption information was obtained via a Food Frequency Questionnaire (FFQ). Weekly intake was calculated based on consumption frequency and gram weight, and participants were categorized into four groups: non-consumption, low, moderate, and high, based on the 25th and 75th percentiles. Multiple linear regression was employed to analyze the association between Tsampa consumption and biological age acceleration. Stratified analyses were conducted using sex, age, smoking, alcohol consumption, and BMI as stratification factors.

Results

A total of 4 335 participants were included. Compared to non-consumption, Tsampa consumption showed a negative association with biological age acceleration(β=-0.66,95% CI:-0.99- -0.327). A statistically significant association was found for moderate Tsampa consumption (700-1 400 grams)(β=-1.24,95% CI: -2.04- -0.44). Associations for low and high consumption levels were not statistically significant [Low:(β=0.11, 95% CI:-0.67-0.88); High:(β=-0.39,95% CI:-1.37-0.60)]. The protective effect of Tsampa consumption against biological age acceleration was stronger in males than in females [Males: (β=-0.83, 95% CI: -1.24- -0.43); Females:(β=-0.61,95% CI:-1.08- -0.13)].

Conclusion

Tsampa consumption is negatively associated with biological age acceleration, suggesting its potential beneficial role in promoting healthy aging in the Tibetan region.

, authors=Danzengwangjiu1, Yu-ling JIANG2, Zi-jun SONG2, Jia-jie CAI2, Cirenzhuoga1, Labaciren1, Nimaqucuo1, Silangyangzong1, Rui-feng HE1, Nimazhuoga1, authorsList=Danzengwangjiu, Yu-ling JIANG, Zi-jun SONG, Jia-jie CAI, Cirenzhuoga, Labaciren, Nimaqucuo, Silangyangzong, Rui-feng HE, Nimazhuoga, authorCompany=null, correspAuthors=Nimazhuoga, 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=1322607970832204326, articleId=1322607964129706523, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=藏族传统饮食糌粑食用量与生物年龄加速的关联研究, columnId=1228016573034721597, journalTitle=现代预防医学, columnName=营养与食品卫生, runingTitle=null, highlight=null, articleAbstract=
目的

探究糌粑食用量与生物年龄加速的关联。

方法

利用中国西南区域自然人群队列研究(The China Multi-Ethnic Cohort study,CMEC)基线调查数据,采用Klemera-Doubal Method方法构建复合生物指标类生物年龄(Biological age based on Klemera and Doubal’s method,KDM-BA)。以KDM-BA与实足年龄差值量化生物衰老。通过食物频率问卷(Food Frequency Questionnaire,FFQ)获得糌粑食用信息。以食用频率与克重计算周摄入量,并按第25%和75% 百分位数分为不吃、低、中、高 4 组。运用多重线性回归分析糌粑食用量与生物年龄加速的关联,并以性别、年龄、吸烟、饮酒、BMI 为分层因素开展分层分析。

结果

共纳入4 335名研究对象。与不食用糌粑相比,食用糌粑与生物年龄加速呈现负向关联(β=-0.66,95% CI:-0.99~-0.327),中等水平糌粑食用量(700~1 400 g)与生物年龄加速的关联差异具有统计学意义(β =-1.24,95% CI: -2.04~-0.44),低水平和高水平糌粑食用量与生物年龄加速的关联,差异没有统计学意义[低水平:(β=0.11,95% CI:-0.67~0.88),高水平:(β=-0.39,95% CI:-1.37~0.60)]。糌粑食用量对生物年龄加速的保护作用在男性中比女性中更强 [男性:(β=-0.83, 95% CI: -1.24~-0.43),女性:(β=-0.61,95% CI:-1.08~-0.13)]。

结论

糌粑食用量与生物年龄加速呈负向关联,提示食用糌粑在促进西藏地区健康老龄化的潜在有益作用。

, authors=旦珍旺久1, 姜玉玲2, 宋子君2, 蔡佳洁2, 次仁卓嘎1, 拉巴次仁1, 尼玛曲措1, 四郎央宗1, 何瑞峰1, 尼玛卓嘎1, authorsList=旦珍旺久, 姜玉玲, 宋子君, 蔡佳洁, 次仁卓嘎, 拉巴次仁, 尼玛曲措, 四郎央宗, 何瑞峰, 尼玛卓嘎, authorCompany=null, correspAuthors=尼玛卓嘎, authorNote=

旦珍旺久(1991—),男,本科,主管医师,研究方向:传染病防控

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尼玛卓嘎, E-mail:
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Baseline characteristics of the study participants [Median (P25, P75), n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
人群特征总人群(n=4 335)糌粑食用量分组
0 (n=180)1 (n=2 156)2 (n=1 702)3 (n=297)
生物年龄加速(岁)3.3(0.1, 6.7)4.6(1.0, 7.8)4.0(0.8, 7.0)2.2(-0.8, 5.7)3.4(0.6, 7.5)
年龄(岁)48.8(39.7, 56.9)39.8(34.3, 47.0)48.4(39.0, 56.1)50.3(41.3, 58.2)50.2(41.1, 58.4)
性别
男性1 663(38.4)76(42.2)801(37.2)653(38.4)133(44.8)
女性2 672(61.6)104(57.8)1 355(62.8)1 049(61.6)164(55.2)
饮酒
从不或几乎从不饮酒2 966(68.4)87(48.3)1 386(64.3)1 284(75.4)209(70.4)
特殊场合下偶尔喝酒861(19.9)61(33.9)482(22.4)270(15.9)48(16.2)
一年中特定月份喝酒77(1.8)8(4.4)47(2.2)20(1.2)2(0.7)
频率不足每周一次140(3.2)6(3.3)81(3.8)41(2.4)12(4.0)
每周至少喝一次291(6.7)18(10.0)160(7.4)87(5.1)26(8.8)
受教育程度
未正规上学2 412(55.6)59(32.8)1 118(51.9)1 082(63.6)153(51.5)
小学1 310(30.2)64(35.6)738(34.2)398(23.4)110(37.0)
初中及高中505(11.6)45(25.0)260(12.1)167(9.8)33(11.1)
大专及大学(包括研究生)108(2.5)12(6.7)40(1.9)55(3.2)1(0.3)
吸烟状况
不吸烟3 332(76.9)116(64.4)1 631(75.6)1 376(80.8)209(70.4)
吸烟791(18.2)61(33.9)423(19.6)240(14.1)67(22.6)
戒烟212(4.9)3(1.7)102(4.7)86(5.1)21(7.1)
睡眠状况
非失眠2 765(63.8)130(72.2)1 422(66.0)1 027(60.3)186(62.6)
失眠1 570(36.2)50(27.8)734(34.0)675(39.7)111(37.4)
抑郁状况
非抑郁4 243(97.9)176(97.8)2 117(98.2)1 662(97.6)288(97.0)
抑郁92(2.1)4(2.2)39(1.8)40(2.4)9(3.0)
体力活动(MET-h/周)16.1(8.0, 28.5)16.6(7.6, 29.7)16.0(8.0, 28.2)15.8(7.9, 28.6)17.1(9.7, 28.9)
BMI(kg/m2)
<18.564(1.5)1(0.6)25(1.2)34(2.0)4(1.3)
18.5~24.91 036(23.9)32(17.8)500(23.2)456(26.8)48(16.2)
25~29.92 456(56.7)110(61.1)1 271(59.0)858(50.4)217(73.1)
≥30779(18.0)37(20.6)360(16.7)354(20.8)28(9.4)
), ArticleFig(id=1322607989299724910, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607964129706523, language=CN, label=表1, caption=

研究对象的基线特征[M (P25,P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
人群特征总人群(n=4 335)糌粑食用量分组
0 (n=180)1 (n=2 156)2 (n=1 702)3 (n=297)
生物年龄加速(岁)3.3(0.1, 6.7)4.6(1.0, 7.8)4.0(0.8, 7.0)2.2(-0.8, 5.7)3.4(0.6, 7.5)
年龄(岁)48.8(39.7, 56.9)39.8(34.3, 47.0)48.4(39.0, 56.1)50.3(41.3, 58.2)50.2(41.1, 58.4)
性别
男性1 663(38.4)76(42.2)801(37.2)653(38.4)133(44.8)
女性2 672(61.6)104(57.8)1 355(62.8)1 049(61.6)164(55.2)
饮酒
从不或几乎从不饮酒2 966(68.4)87(48.3)1 386(64.3)1 284(75.4)209(70.4)
特殊场合下偶尔喝酒861(19.9)61(33.9)482(22.4)270(15.9)48(16.2)
一年中特定月份喝酒77(1.8)8(4.4)47(2.2)20(1.2)2(0.7)
频率不足每周一次140(3.2)6(3.3)81(3.8)41(2.4)12(4.0)
每周至少喝一次291(6.7)18(10.0)160(7.4)87(5.1)26(8.8)
受教育程度
未正规上学2 412(55.6)59(32.8)1 118(51.9)1 082(63.6)153(51.5)
小学1 310(30.2)64(35.6)738(34.2)398(23.4)110(37.0)
初中及高中505(11.6)45(25.0)260(12.1)167(9.8)33(11.1)
大专及大学(包括研究生)108(2.5)12(6.7)40(1.9)55(3.2)1(0.3)
吸烟状况
不吸烟3 332(76.9)116(64.4)1 631(75.6)1 376(80.8)209(70.4)
吸烟791(18.2)61(33.9)423(19.6)240(14.1)67(22.6)
戒烟212(4.9)3(1.7)102(4.7)86(5.1)21(7.1)
睡眠状况
非失眠2 765(63.8)130(72.2)1 422(66.0)1 027(60.3)186(62.6)
失眠1 570(36.2)50(27.8)734(34.0)675(39.7)111(37.4)
抑郁状况
非抑郁4 243(97.9)176(97.8)2 117(98.2)1 662(97.6)288(97.0)
抑郁92(2.1)4(2.2)39(1.8)40(2.4)9(3.0)
体力活动(MET-h/周)16.1(8.0, 28.5)16.6(7.6, 29.7)16.0(8.0, 28.2)15.8(7.9, 28.6)17.1(9.7, 28.9)
BMI(kg/m2)
<18.564(1.5)1(0.6)25(1.2)34(2.0)4(1.3)
18.5~24.91 036(23.9)32(17.8)500(23.2)456(26.8)48(16.2)
25~29.92 456(56.7)110(61.1)1 271(59.0)858(50.4)217(73.1)
≥30779(18.0)37(20.6)360(16.7)354(20.8)28(9.4)
), ArticleFig(id=1322607989412971119, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607964129706523, language=EN, label=Table 2, caption=

Association between Zanba Consumption and Biological Age Acceleration [β (95% CI)]

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模型糌粑食用量分类(g/周)线性趋势P值
0(参考组)>0 g/周且≤700 g/周>700 g/周且≤1 400 g/周>1 400 g
模型1a1 (ref)-0.62(-1.40~0.15)-2.29(-3.08~-1.50)-0.77(-1.72~0.28)<0.001
模型2b1 (ref)-0.20(-0.98~0.58)-1.76(-2.55~-0.97)-0.26(-1.21~0.69)<0.001
模型3c1 (ref)0.11(-0.67~0.88)-1.24(-2.04~-0.44)-0.39(-1.37~0.60)<0.001
), ArticleFig(id=1322607989782069872, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607964129706523, language=CN, label=表2, caption=

糌粑食用量与生物年龄加速的关联[β (95% CI)]

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模型糌粑食用量分类(g/周)线性趋势P值
0(参考组)>0 g/周且≤700 g/周>700 g/周且≤1 400 g/周>1 400 g
模型1a1 (ref)-0.62(-1.40~0.15)-2.29(-3.08~-1.50)-0.77(-1.72~0.28)<0.001
模型2b1 (ref)-0.20(-0.98~0.58)-1.76(-2.55~-0.97)-0.26(-1.21~0.69)<0.001
模型3c1 (ref)0.11(-0.67~0.88)-1.24(-2.04~-0.44)-0.39(-1.37~0.60)<0.001
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藏族传统饮食糌粑食用量与生物年龄加速的关联研究
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旦珍旺久 1 , 姜玉玲 2 , 宋子君 2 , 蔡佳洁 2 , 次仁卓嘎 1 , 拉巴次仁 1 , 尼玛曲措 1 , 四郎央宗 1 , 何瑞峰 1 , 尼玛卓嘎 1
现代预防医学 | 营养与食品卫生 2025,52(20): 3693-3697
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现代预防医学 |营养与食品卫生 2025 , 52 (20) : 3693 -3697
藏族传统饮食糌粑食用量与生物年龄加速的关联研究
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旦珍旺久1, 姜玉玲2, 宋子君2, 蔡佳洁2, 次仁卓嘎1, 拉巴次仁1, 尼玛曲措1, 四郎央宗1, 何瑞峰1, 尼玛卓嘎1
作者信息
  • 1.西藏自治区疾病预防控制中心应急办,西藏 拉萨 850000
  • 2.四川大学华西公共卫生学院/华西第四医院
通讯作者:
尼玛卓嘎, E-mail:
作者简介:

旦珍旺久(1991—),男,本科,主管医师,研究方向:传染病防控

Association between comsumption amount of Tibetan traditional food Tsampa and biological age acceleration
Danzengwangjiu1, Yu-ling JIANG2, Zi-jun SONG2, Jia-jie CAI2, Cirenzhuoga1, Labaciren1, Nimaqucuo1, Silangyangzong1, Rui-feng HE1, Nimazhuoga1
Affiliations
  • Tibet Center for Disease Control and Prevention, Lhasa, Tibet 850000, China
出版时间: 2025-10-25 doi: 10.20043/j.cnki.MPM.202505342
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目的

探究糌粑食用量与生物年龄加速的关联。

方法

利用中国西南区域自然人群队列研究(The China Multi-Ethnic Cohort study,CMEC)基线调查数据,采用Klemera-Doubal Method方法构建复合生物指标类生物年龄(Biological age based on Klemera and Doubal’s method,KDM-BA)。以KDM-BA与实足年龄差值量化生物衰老。通过食物频率问卷(Food Frequency Questionnaire,FFQ)获得糌粑食用信息。以食用频率与克重计算周摄入量,并按第25%和75% 百分位数分为不吃、低、中、高 4 组。运用多重线性回归分析糌粑食用量与生物年龄加速的关联,并以性别、年龄、吸烟、饮酒、BMI 为分层因素开展分层分析。

结果

共纳入4 335名研究对象。与不食用糌粑相比,食用糌粑与生物年龄加速呈现负向关联(β=-0.66,95% CI:-0.99~-0.327),中等水平糌粑食用量(700~1 400 g)与生物年龄加速的关联差异具有统计学意义(β =-1.24,95% CI: -2.04~-0.44),低水平和高水平糌粑食用量与生物年龄加速的关联,差异没有统计学意义[低水平:(β=0.11,95% CI:-0.67~0.88),高水平:(β=-0.39,95% CI:-1.37~0.60)]。糌粑食用量对生物年龄加速的保护作用在男性中比女性中更强 [男性:(β=-0.83, 95% CI: -1.24~-0.43),女性:(β=-0.61,95% CI:-1.08~-0.13)]。

结论

糌粑食用量与生物年龄加速呈负向关联,提示食用糌粑在促进西藏地区健康老龄化的潜在有益作用。

糌粑食用量  /  生物年龄  /  藏族人群
Objective

To investigate the association between Tsampa consumption and biological age acceleration.

Methods

Utilizing baseline data from the China Multi-Ethnic Cohort study (CMEC), a composite biomarker-based biological age was constructed using the Klemera-Doubal Method (Biological age based on Klemera and Doubal’s method, KDM-BA). Biological aging was quantified as the difference between KDM-BA and chronological age. Tsampa consumption information was obtained via a Food Frequency Questionnaire (FFQ). Weekly intake was calculated based on consumption frequency and gram weight, and participants were categorized into four groups: non-consumption, low, moderate, and high, based on the 25th and 75th percentiles. Multiple linear regression was employed to analyze the association between Tsampa consumption and biological age acceleration. Stratified analyses were conducted using sex, age, smoking, alcohol consumption, and BMI as stratification factors.

Results

A total of 4 335 participants were included. Compared to non-consumption, Tsampa consumption showed a negative association with biological age acceleration(β=-0.66,95% CI:-0.99- -0.327). A statistically significant association was found for moderate Tsampa consumption (700-1 400 grams)(β=-1.24,95% CI: -2.04- -0.44). Associations for low and high consumption levels were not statistically significant [Low:(β=0.11, 95% CI:-0.67-0.88); High:(β=-0.39,95% CI:-1.37-0.60)]. The protective effect of Tsampa consumption against biological age acceleration was stronger in males than in females [Males: (β=-0.83, 95% CI: -1.24- -0.43); Females:(β=-0.61,95% CI:-1.08- -0.13)].

Conclusion

Tsampa consumption is negatively associated with biological age acceleration, suggesting its potential beneficial role in promoting healthy aging in the Tibetan region.

Tsampa consumption  /  Biological age  /  Tibetan population
旦珍旺久, 姜玉玲, 宋子君, 蔡佳洁, 次仁卓嘎, 拉巴次仁, 尼玛曲措, 四郎央宗, 何瑞峰, 尼玛卓嘎. 藏族传统饮食糌粑食用量与生物年龄加速的关联研究. 现代预防医学, 2025 , 52 (20) : 3693 -3697 . DOI: 10.20043/j.cnki.MPM.202505342
Danzengwangjiu, Yu-ling JIANG, Zi-jun SONG, Jia-jie CAI, Cirenzhuoga, Labaciren, Nimaqucuo, Silangyangzong, Rui-feng HE, Nimazhuoga. Association between comsumption amount of Tibetan traditional food Tsampa and biological age acceleration[J]. Modern Preventive Medicine, 2025 , 52 (20) : 3693 -3697 . DOI: 10.20043/j.cnki.MPM.202505342
中国已成为世界上老年人口最多的国家[1],老龄化问题日益显著,面临严重衰老相关的非传染性疾病风险和负担[2]。生物衰老是一种与年龄相关的疾病、残疾和功能障碍易感性增加的潜在过程,并不完全等同于实足年龄的增长,通常用生物年龄(Biological age, BA)来刻画。西藏自治区,位于中国的西南边陲,地理海拔高、气候复杂多样,交通欠发达。近年来,随着经济和交通系统的发展,藏族人民的生活条件得到了一定程度的改善。然而,西藏的医疗卫生整体水平仍然低于中国其他地区[3],预计2035年西藏人民的预期寿命排行在中国各省中处于末位[4],西藏地区>60岁人口的比例明显低于汉族人口[5]。考虑到西藏的高原环境以及受限的医疗资源,延缓生物衰老进程、改善西藏高原地区人民的健康状况至关重要。
研究表明,生物衰老可通过饮食干预延缓进程,进而促进健康老龄化[6]。“糌粑”是以高原大麦炒熟后磨成面粉制作而成,是高原特有的一种高蛋白、高纤维、高维生素、低脂肪、低糖的谷物,在西藏地区的饮食结构中,糌粑的食用量占比最为突出[7]。有研究显示,糌粑的制作原料——高地大麦,相较于其余大麦品种,含更多的生物活性成分,能够有效预防或治疗如阿尔茨海默病、心脏病和癌症等衰老相关疾病[8]。另有研究显示,食用糌粑亦可能降低心血管疾病、糖尿病等衰老相关疾病的发病风险[9]。然而食用糌粑是否能够延缓生物衰老目前尚无相关研究证据。
因此,本研究基于中国西南区域自然人群队列(China Multi-Ethnic cohort,CMEC,以下简称西南队列)基线数据,探讨糌粑食用量与生物年龄加速之间的关联关系。
西南队列是在中国西南地区的五个省份建立的一项多民族大规模前瞻性队列研究,基线调查于2018年5月—2019年9月进行,共纳入99 556名参与者。参与者需要通过体检和临床实验室检测获得各项生理指标,以及面对面访谈完成电子问卷。西南队列获得了四川大学医学伦理审查委员会 (K2016038)的伦理批准,所有参与者都签署了知情同意[10]。本研究纳入西藏地区人群4 632名,排除了生物年龄缺失(68)、食用糌粑情况缺失(9),食用量极端异常值(160)以及协变量缺失(60)的参与者,最终共纳入4 335名研究对象。
糌粑食用量的相关信息通过问卷收集。本研究要求研究对象自报是否食用糌粑、食用频率(每天、每周、每月或每年食用次数)以及每次食用克数(熟重)。根据研究对象自报的食用频率以及每次食用克数,计算出研究对象每周糌粑食用量(克)。再根据四分位数间距(700,1 400),将研究人群按照每周糌粑食用量分为不吃(0 g/周)、低水平食用量(>0 g/周且≤700 g/周)、中等水平食用量(>700 g/周且≤1 400 g/周)、高水平食用量(>1 400 g/周)四个组。
Klemera-Doubal Method(KDM)方法是一种基于复合生物标志物测量生物年龄(BA)的常用方法,已在欧洲和亚洲人群中得到充分验证,并在预测与年龄相关的健康结局方面表现出良好的性能[11-12]。本研究使用KDM法,基于基线调查的临床生化检测指标以及人体测量学数据来构建生物年龄[13]。指标的筛选考虑了既往研究中的利用、数据集中是否包含、缺失率、与实足年龄 (chronological age,CA)的相关性以及生物标志物在衰老过程中的功能等。最终本研究共纳入15个生物标志物,包括收缩压 (SBP)、腰臀比 (WHR)、呼气峰流量、低密度脂蛋白胆固醇、高密度脂蛋白胆固醇、糖化血红蛋白 (HbA1c)、甘油三酯 (TG)、天冬氨酸氨基转移酶 (AST)、γ-谷氨酰转肽酶 (GGT)、白蛋白 (ALB)、碱性磷酸酶 (ALP)、肌酐、尿素、平均红细胞体积 (MCV) 和血小板计数。基于KDM法的BA计算基于以下公式[13]:
其中BAEC是估计的生物年龄。xj是第j个生物标志物的测量值。kj、qj和Sj分别表示从参考人群中第j个生物标志物的实足年龄回归中获得的斜率、截距和均方根误差,CA是实足年龄。是由参考人群中选定的生物标志物集解释的CA估计方差。BA会随着年龄的增长而增加。考虑年龄的影响,本研究计算KDM-BA和CA之间的差异获得KDM-BA 加速,KDM-BA加速为正值,可能表明与参考人群相比,个体的生物学年龄较大,反之亦然。
协变量的信息主要通过问卷获得。本研究通过构建有向无环图(DAG)(图1)来正确确定潜在的混杂因素。根据提出的 DAG 和后门准则,本研究确定了以下协变量:年龄、性别、受教育程度、职业、吸烟状况、饮酒状况、DASH饮食指数、藏面摄入情况、酥油茶摄入情况、清茶摄入情况、生牛肉摄入情况、总能量摄入、失眠症状、抑郁症状、体力活动、体重指数 (BMI) 和自我报告的医生诊断的非传染性慢性疾病(NCDs),包括糖尿病、高血压、高脂血症、冠心病、中风。
本文基于基线调查数据对相关研究进行探讨,首先描述研究人群基线特征。连续型变量以均值和25%、75%分位数的形式描述,分类变量以频数和百分比的形式描述。以不吃糌粑的人群为参考组,采用多因素线性回归分析探究不同类别糌粑食用量与BA之间的关联,同时探讨了每周糌粑食用量(kg)与生物年龄加速之间的关联关系。在全模型中,控制了年龄、性别、受教育程度、职业状况、吸烟状况、饮酒状况、DASH饮食指数、藏面摄入情况、酥油茶摄入情况、清茶摄入情况、生牛肉摄入情况、总能量摄入、失眠症状、抑郁症状、体力活动、体重指数 (BMI)。以性别、年龄、是否吸烟、是否饮酒、BMI为分层因素进行分层分析,探究糌粑食用量与生物衰老的关系是否因人群特征而不同。对于饮食指数的控制,既往有研究证实DASH指数具有较高证据质量[14],能够很好地反映整体膳食质量,所以本研究采用DASH指数作为饮食的整体控制指标。最后,为了判断结果的稳健性,本研究排除了基线患病的人群进行敏感性分析。采用R 4.4.4软件进行统计分析。
本研究共纳入4 335名研究对象,对全人群及不同糌粑食用水平:0(不吃糌粑)、1(低水平糌粑食用量)、2(中度水平糌粑食用量)、3(高水平糌粑食用量)分别进行基线特征描述,结果见表1。与不食用糌粑者相比,食用糌粑者的人多为女性、不饮酒者、不吸烟者及超重者。
糌粑食用量与生物衰老的关联关系见表2。模型1为未调整协变量的模型,模型 2 调整了年龄与性别,模型3调整了年龄、性别、受教育程度、职业状况、吸烟状况、饮酒状况、DASH饮食指数、藏面摄入情况、酥油茶摄入情况、清茶摄入情况、生牛肉摄入情况、总能量摄入、失眠状况、抑郁症状、体力活动、BMI等协变量。3种模型的结果均显示,随着糌粑食用量的增加,糌粑食用量在较低水平(>0 g/周且≤700 g/周)及较高水平(>1 400 g)与生物衰老之间关联无统计学意义,而中等食用水平(>700 g/周且≤1 400 g/周)呈现有统计学意义的负向关联。每周糌粑食用量(kg)与生物衰老的结果表明,食用量每增加1 kg,生物年龄加速减少0.66岁(β=-0.66,95% CI: -0.99~-0.33)。
本研究根据性别、年龄、吸烟、饮酒及 BMI 进行了分层分析,结果见图2。就性别而言,男性和女性中糌粑食用量均与KDM-BA加速呈负向关联,且关联强度在男性中高于女性[男性:(β=-0.83,95% CI:-1.24~-0.43),女性:(β=-0.61,95% CI:-1.08~-0.13)]。就年龄而言,在<55岁人群中糌粑食用量与KDM-BA加速之间存在显著负向关联,而在≥55岁人群中该关联无统计学意义[<55岁:(β=-0.84,95% CI:-1.23~-0.45),≥55岁:(β=-0.44,95% CI:-1.08~0.20)]。就BMI不同水平而言,消瘦和肥胖人群中未见糌粑食用量与KDM-BA加速之间存在显著关联;而在BMI正常和超重人群中,糌粑食用均呈现保护效应,但随着BMI增加,该保护作用逐渐减弱[正常:(β=-1.14,95% CI: -1.81~-0.47),超重:(β=-0.64,95% CI:-1.06~-0.21)]。就吸烟和饮酒而言,糌粑食用量对于从不吸烟、从不饮酒者的KDM-BA加速均有较显著的保护作用。[从不吸烟:(β=-0.69,95% CI:-1.10~-0.28),从不饮酒:(β=-0.88,95% CI:-1.31~-0.45)]。
排除了基线自报患病人群后,分析结果虽无统计学意义,但趋势与主分析保持一致,即每周糌粑食用量增加1kg,生物年龄加速减少0.36岁 (β=-0.36,95% CI: -0.90~0.18)。
本研究基于西南队列的基线数据,探究了糌粑食用量与KDM-BA加速之间的关系。研究发现,糌粑食用量可能与KDM-BA加速之间存在负向关联。此外,糌粑食用量与生物年龄加速在中剂量组(>700 g/周且≤1 400 g/周)中的关联存在统计学意义,提示适量食用糌粑可能与生物衰老减速有关,且结果受年龄及性别影响较大。
本研究基于临床复合生物标志物采用KDM法构建了BA,结果提示糌粑食用量可能与生物衰老存在负向关联。高原大麦是制作糌粑的原料,本质是将其作为全谷物食品食用[15]。既往研究表明全谷物的食用与健康老龄化有关[16],并可能提高预期寿命[17]。既往研究关注糌粑食用量与代谢综合征疾病之间的联系[9],提示食用糌粑能降低代谢综合征疾病的发病风险,而代谢综合征患病率与年龄之间呈现正向关联。亦有研究提示,代谢综合征可能加速端粒缩短,从而导致衰老相关的退行性疾病[18]。此外,从生物学机制来看,糌粑富含多种营养物质,这可能是其与生物衰老减速相关的重要原因。以β-葡聚糖为例,其在糌粑中含量丰富[19-20],研究表明,β-葡聚糖能够清除体内的自由基,避免自由基过度氧化,从而发挥延缓衰老的作用[21],而在免疫调节上,β-葡聚糖可激活免疫细胞,增强机体免疫力,有助于抵抗病原体入侵,减少炎症反应对机体细胞和组织的损伤,可能间接延缓衰老进程。此外,糌粑中还含有维生素E、类黄酮等抗氧化物质。其中,维生素 E 可阻止自由基的链式反应,保护细胞免受氧化损伤[22],而类黄酮具有抗氧化、免疫调节、清除自由基等多种功效,能够减轻炎症反应,对延缓衰老可能发挥作用[23]。纵观各项研究的联系,尚可认为食用糌粑能延缓衰老,且相较于代谢综合征,BA指标反映更加全面的衰老水平,作为生物衰老的预测是直观且可行的。
同时,本研究还发现,糌粑食用量对于从不吸烟、从不饮酒者的KDM-BA加速均有较显著的保护作用,但对于吸烟者、饮酒者而言,无论暴露频次如何改变,糌粑食用量与生物衰老的关联几乎未表现出任何统计学意义。由前文所述,考虑到糌粑富β-葡聚糖,同样有研究显示,β-葡聚糖可以显著降低血清酒精浓度,抵消乙醇的损害作用[24],饮酒可能抵消了糌粑的有益作用,导致其对生物衰老的减速作用不显著,此外,同样有研究表明,吸烟可通过影响DNA甲基化影响衰老基因表达[25],可能掩盖了糌粑对生物衰老的减速作用。但饮酒与吸烟两者之间是否存在交互作用,及其综合影响生物衰老的具体机制尚不明确。
本研究还发现,相较于女性,糌粑食用量对男性生物衰老的减速作用更强,且在年龄<55岁的人群中亦显著。其关联方向与既往研究类似,一项横断面研究研究提示,西藏地区人群中男性相较于女性会摄入更多谷类食物,且年轻人群18~30岁比超过50岁人群食用更多谷类食物[7],其中包含糌粑,提示在适量范围内(>700 g/周且≤1 400 g/周),糌粑食用量越多对于男性及<55岁人群生物衰老的延缓作用可能越强,但仍需进行证据强度更高的研究核实。此外,本研究还发现对于体重正常及超重人群而言,糌粑食用量对于生物衰老的减缓作用明显,但对于肥胖人群效果尚不显著,提示在控制体重的情况下,适量食用糌粑有可能延缓生物衰老进程,然而具体机制尚不明确,需进一步研究证明。
本研究是首个探索藏族特色饮食糌粑食用量与生物衰老的关联研究。然而本研究同样具有局限性,首先本研究虽然基于纵向队列研究,但采用横断面设计,原因在于相较于基线调查,后续随访调查所纳入的样本量较少,且在排除缺失值影响后,尚不能获得具有足够代表性的样本。由此可能存在未测量混杂以及反向因果的问题。其次,本研究分层分析仅用糌粑食用量作为定量变量分析,相较于作为分类变量进行分析,其解释效果相对较差,同时难以转化为政策建议;另外,糌粑食用量均为自报数据,可能存在回忆偏倚、暴露错分的情况;最后,样本数据受限于中国西南地区的藏族人群,应谨慎将结论外推至其他人群。
综上,糌粑食用量与生物衰老呈现负向关联,鉴于糌粑为藏族人群地方特色饮食,本研究可为推行糌粑及其相关饮食产物,为可能替代的健康饮食以及促进健康老龄化提供科学依据。
  • 国家重点研发计划(2017YFC0907300,2017YFC0907302)
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doi: 10.20043/j.cnki.MPM.202505342
  • 接收时间:2025-05-26
  • 首发时间:2026-10-29
  • 出版时间:2025-10-25
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出版历史
  • 收稿日期:2025-05-26
基金
国家重点研发计划(2017YFC0907300,2017YFC0907302)
作者信息
    1.西藏自治区疾病预防控制中心应急办,西藏 拉萨 850000
    2.四川大学华西公共卫生学院/华西第四医院

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尼玛卓嘎, E-mail:
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https://castjournals.cast.org.cn/joweb/xdyfyx/CN/10.20043/j.cnki.MPM.202505342
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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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