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Article(id=1241675633479176703, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241675628051755031, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202406288, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1718640000000, receivedDateStr=2024-06-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773968140239, onlineDateStr=2026-03-20, pubDate=1732464000000, pubDateStr=2024-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773968140239, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773968140239, creator=13701087609, updateTime=1773968140239, updator=13701087609, issue=Issue{id=1241675628051755031, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='22', pageStart='4033', pageEnd='4224', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773968138945, creator=13701087609, updateTime=1773968595676, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241677543783322543, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241675628051755031, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241677543783322544, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241675628051755031, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4091, endPage=4095, ext={EN=ArticleExt(id=1241675636134171220, articleId=1241675633479176703, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Dynamic changes of plant-based diet and its relationship with mortality in elderly people in China, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between the dynamics of plant-based diets and mortality in Chinese older adults.

Methods

Based on the data from the Chinese Longitudinal Healthy Longevity and Happy Family Study (CLHLS), older adults who participated in the three surveys from 2011-2018 were selected. The HPDI and UPDI scores of the study participants were calculated in 2011 and 2014, respectively, and they were categorized into four groups based on the median of their two scores: low-low, low-high, high-low and high-high groups. Cox proportional risk regression models were used to analyze the relationship between the dynamics of plant-based diets and mortality in the elderly.

Results

A total of 4 382 subjects were enrolled in this study, and 1 689 (38.5%) of them died during the 7-year follow-up period. The results of Cox proportional hazards regression model showed that after adjusting for confounding factors such as gender, age, and education, the risk of death in the high-high HPDI group was reduced by 17% (HR=0.83, 95% CI: 0.72-0.97), while the risk of death in the high-high UPDI group was increased by 29% (HR=1.29, 95% CI: 1.11-1.49).

Conclusion

Older adults who maintain a healthy plant-based diet have a lower risk of death.

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目的

探讨中国老年人植物性饮食的动态变化与死亡关系。

方法

基于中国老年健康和家庭幸福调查(CLHLS)数据，选择参加2011—2018年三次调查的老年人。分别计算研究对象2011年和2014年健康的植物性饮食指数(HPDI)和不健康的植物性饮食指数(UPDI)得分，并根据其两次得分的中位数将其分为四组，分别为：低-低、低-高、高-低和高-高组。采用Cox比例风险回归模型分析植物性饮食的动态变化与老年人的死亡关系。

结果

本研究共纳入4 382名研究对象，在7年随访期间，共有1 689(38.5%)名研究对象发生死亡。Cox比例风险回归模型结果显示：在调整性别、年龄、学历等混杂因素后，与得分低-低组相比，HPDI得分高-高组发生死亡风险降低了17%（HR=0.83, 95% CI：0.72~0.97），而UPDI得分高-高组发生死亡风险则增加了29%(HR=1.29，95% CI:1.11~1.49)。

结论

保持健康植物性饮食的老年人发生死亡的风险较低。

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方奎， 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=EdgN5ZFDQ+rLfuy7emrJSw==, magXml=oqrY9Ivz5+igiAOnIrTkmw==, pdfUrl=null, pdf=Vqk+Lfe282LLgQhyMbhvSw==, pdfFileSize=703828, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=C97fAEs8AzuSbpHqgQur/w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=InTcZaxtkIQlEWWwIggdpQ==, mapNumber=null, authorCompany=null, fund=null, authors=

郭鉴婷(1988—)，女，本科，护师，研究方向：营养与健康

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郭鉴婷(1988—)，女，本科，护师，研究方向：营养与健康

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Nutrients, 2020, 12(9): 2671., articleTitle=The role of specific components of a Plant-Based Diet in management of dyslipidemia and the impact on cardiovascular risk, refAbstract=null)], funds=[Fund(id=1241826531534770312, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, awardId=FWZR2020004, language=CN, fundingSource=辽宁省教育厅2020年度科学研究项目(FWZR2020004), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241826526895870959, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, xref=1., ext=[AuthorCompanyExt(id=1241826526904259568, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, companyId=1241826526895870959, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Shengjing Hospital, China Medical University, Shenyang, Liaoning 110022, Liaoning, China), AuthorCompanyExt(id=1241826526912648177, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, companyId=1241826526895870959, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国医科大学附属盛京医院，辽宁　沈阳　110022)]), AuthorCompany(id=1241826527009117175, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, xref=2., ext=[AuthorCompanyExt(id=1241826527017505784, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, companyId=1241826527009117175, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.中国医科大学附属第一医院)])], figs=[ArticleFig(id=1241826530196787264, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=EN, label=Fig.1, caption=Dynamics of HPDI, UPDI in different age groups in relation to mortality, figureFileSmall=YZLCq79EFpmIqOc4ZXXhSw==, figureFileBig=cWukRbTowe4glOgylHTetw==, tableContent=null), ArticleFig(id=1241826530297450565, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=CN, label=图1, caption=不同年龄组HPDI、UPDI的动态变化与死亡关系, figureFileSmall=YZLCq79EFpmIqOc4ZXXhSw==, figureFileBig=cWukRbTowe4glOgylHTetw==, tableContent=null), ArticleFig(id=1241826530435862602, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=EN, label=Fig.2, caption=Dynamics of HPDI and UPDI in different gender groups in relation to mortality, figureFileSmall=9T/XgUdbSC/av1Ko/IAerA==, figureFileBig=6bREOlns2wdy1xxi11PTgg==, tableContent=null), ArticleFig(id=1241826530582663247, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=CN, label=图2, caption=不同性别组HPDI、UPDI的动态变化与死亡关系, figureFileSmall=9T/XgUdbSC/av1Ko/IAerA==, figureFileBig=6bREOlns2wdy1xxi11PTgg==, tableContent=null), ArticleFig(id=1241826530695909461, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=EN, label=Table 1, caption=

Basic characteristics of the study population

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基本特征总人数死亡F/χ2值P值
否是
年龄(岁)778.00<0.001
65~802 104(48.0）1 742(64.7)362(21.4)
>802 278(52.0）951(35.3)1 327(78.6)
性别0.840.358
男2 049(46.8)775(45.9)1 274(47.3)
女2 333(53.2)914(54.1)1 419(52.7)
学历62.17<0.001
文盲1 973(53.0）1 106(48.0)867(61.3)
小学及以上1 747(47.0）1 199(52.0)548(38.7)
定期锻炼25.09<0.001
是1 490(40.4)995(43.6)495(35.2)
否2 199(59.6)1 289(56.4)910(64.8)
吸烟2.620.270
是835(22.4）510(22.1)325(23.0)
过去吸烟522(14.0）310(13.4)212(15.0)
否2 369(63.6）1 490(64.5)879(62.1)
饮酒1.420.491
是801(21.5）511(22.1)290(20.5)
过去喝酒477(12.8）292(12.6)185(13.1)
否2 448(65.7）1 507(65.2)941(66.5)
高血压5.890.015
否2 436(67.9）1 487(66.4)949(70.3)
是1 151(32.1）751(33.6)400(29.7)
中风2.510.113
否3 300(92.7）2 062(93.3)1 238(91.8)
是259(7.30）149(6.70)110(8.2)
心脏病0.880.348
否3 102(87.3）1 914(86.9)1 188(88.0)
是450(12.7）288(13.1)162(12.0)
血脂异常10.52<0.001
否3 218(96.0）1 997(95.2)1 221(97.4)
是133(4.0）101(4.8)32(2.6)
糖尿病0.990.319
否3 383(95.4）2 097(95.1)1 286(95.8)
是164(4.6）108(4.9)56(4.2)
HPDI46.4±5.446.8±5.345.7±5.443.42<0.001
UPDI50.8±6.650.2±6.751.7±6.449.40<0.001
BMI22.8±32.023.5±38.821.7±14.72.770.096
睡眠时长(h)7.6±2.37.4±2.17.9±2.645.96<0.001
), ArticleFig(id=1241826530804961375, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=CN, label=表1, caption=

研究对象基本特征

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基本特征总人数死亡F/χ2值P值
否是
年龄(岁)778.00<0.001
65~802 104(48.0）1 742(64.7)362(21.4)
>802 278(52.0）951(35.3)1 327(78.6)
性别0.840.358
男2 049(46.8)775(45.9)1 274(47.3)
女2 333(53.2)914(54.1)1 419(52.7)
学历62.17<0.001
文盲1 973(53.0）1 106(48.0)867(61.3)
小学及以上1 747(47.0）1 199(52.0)548(38.7)
定期锻炼25.09<0.001
是1 490(40.4)995(43.6)495(35.2)
否2 199(59.6)1 289(56.4)910(64.8)
吸烟2.620.270
是835(22.4）510(22.1)325(23.0)
过去吸烟522(14.0）310(13.4)212(15.0)
否2 369(63.6）1 490(64.5)879(62.1)
饮酒1.420.491
是801(21.5）511(22.1)290(20.5)
过去喝酒477(12.8）292(12.6)185(13.1)
否2 448(65.7）1 507(65.2)941(66.5)
高血压5.890.015
否2 436(67.9）1 487(66.4)949(70.3)
是1 151(32.1）751(33.6)400(29.7)
中风2.510.113
否3 300(92.7）2 062(93.3)1 238(91.8)
是259(7.30）149(6.70)110(8.2)
心脏病0.880.348
否3 102(87.3）1 914(86.9)1 188(88.0)
是450(12.7）288(13.1)162(12.0)
血脂异常10.52<0.001
否3 218(96.0）1 997(95.2)1 221(97.4)
是133(4.0）101(4.8)32(2.6)
糖尿病0.990.319
否3 383(95.4）2 097(95.1)1 286(95.8)
是164(4.6）108(4.9)56(4.2)
HPDI46.4±5.446.8±5.345.7±5.443.42<0.001
UPDI50.8±6.650.2±6.751.7±6.449.40<0.001
BMI22.8±32.023.5±38.821.7±14.72.770.096
睡眠时长(h)7.6±2.37.4±2.17.9±2.645.96<0.001
), ArticleFig(id=1241826530901430374, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=EN, label=Table 2, caption=

Relationship between baseline HPDI and UPDI and death

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死亡人数/总人数模型 1模型2
HR值(95% CI)P值HR值(95% CI)P值
HPDI
Q1565/1 1931.0 (ref)1.0 (ref)
Q2519/1 3250.83(0.73~0.93)0.0020.87(0.75~1.01)0.053
Q3334/9720.73(0.63~0.83)<0.0010.83(0.71~0.98)0.031
Q4271/8920.64(0.56~0.74)<0.0010.82(0.69~0.98)0.026
UPDI
Q1348/1 0961.0 (ref)1.0 (ref)
Q2472/1 2581.18(1.03~1.36)0.0181.10(0.93~1.30)0.259
Q3385/9611.26(1.09~1.46)0.0021.11(0.93~1.32)0.265
Q4484/1 0671.43(1.25~1.64)<0.0011.24(1.04~1.47)0.014
), ArticleFig(id=1241826531039842410, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=CN, label=表2, caption=

基线HPDI、UPDI与死亡的关系

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死亡人数/总人数模型 1模型2
HR值(95% CI)P值HR值(95% CI)P值
HPDI
Q1565/1 1931.0 (ref)1.0 (ref)
Q2519/1 3250.83(0.73~0.93)0.0020.87(0.75~1.01)0.053
Q3334/9720.73(0.63~0.83)<0.0010.83(0.71~0.98)0.031
Q4271/8920.64(0.56~0.74)<0.0010.82(0.69~0.98)0.026
UPDI
Q1348/1 0961.0 (ref)1.0 (ref)
Q2472/1 2581.18(1.03~1.36)0.0181.10(0.93~1.30)0.259
Q3385/9611.26(1.09~1.46)0.0021.11(0.93~1.32)0.265
Q4484/1 0671.43(1.25~1.64)<0.0011.24(1.04~1.47)0.014
), ArticleFig(id=1241826531136311408, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=EN, label=Table 3, caption=

Dynamics of HPDI and UPDI in relation to mortality

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低-低低-高高-低高-高
HPDI
死亡人数/总人数619/1 279302/870313/777455/1 456
模型110.72(0.63~0.82)a0.83(0.73~0.95)a0.65(0.57~0.73)a
模型210.84(0.70~0.99)a0.94(0.80~1.11)0.83(0.72~0.97)a
UPDI
死亡人数/总人数497/1 600323/754314/816555/1 212
模型111.38(1.20~1.59)a1.24(1.08~1.43)a1.47(1.31~1.66)a
模型211.25(1.06~1.49)a1.11(0.93~1.31)1.29(1.11~1.49)a
), ArticleFig(id=1241826531278917755, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241675633479176703, language=CN, label=表3, caption=

HPDI、UPDI的动态变化与死亡关系

, figureFileSmall=null, figureFileBig=null, tableContent=
低-低低-高高-低高-高
HPDI
死亡人数/总人数619/1 279302/870313/777455/1 456
模型110.72(0.63~0.82)a0.83(0.73~0.95)a0.65(0.57~0.73)a
模型210.84(0.70~0.99)a0.94(0.80~1.11)0.83(0.72~0.97)a
UPDI
死亡人数/总人数497/1 600323/754314/816555/1 212
模型111.38(1.20~1.59)a1.24(1.08~1.43)a1.47(1.31~1.66)a
模型211.25(1.06~1.49)a1.11(0.93~1.31)1.29(1.11~1.49)a
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中国老年人植物性饮食的动态变化与死亡关系
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郭鉴婷 1 , 方奎 2
现代预防医学 | 营养与食品卫生 2024,51(22): 4091-4095
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现代预防医学 | 营养与食品卫生 2024, 51(22): 4091-4095
中国老年人植物性饮食的动态变化与死亡关系
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郭鉴婷1, 方奎2
作者信息
  • 1.中国医科大学附属盛京医院，辽宁　沈阳　110022
  • 2.中国医科大学附属第一医院

    • 郭鉴婷(1988—)，女，本科，护师，研究方向：营养与健康

通讯作者:

方奎， E-mail:
Dynamic changes of plant-based diet and its relationship with mortality in elderly people in China
Jian-ting GUO1, Kui FANG2
Affiliations
  • Shengjing Hospital, China Medical University, Shenyang, Liaoning 110022, Liaoning, China
出版时间: 2024-11-25 doi: 10.20043/j.cnki.MPM.202406288
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摘要
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目的

探讨中国老年人植物性饮食的动态变化与死亡关系。

方法

基于中国老年健康和家庭幸福调查(CLHLS)数据，选择参加2011—2018年三次调查的老年人。分别计算研究对象2011年和2014年健康的植物性饮食指数(HPDI)和不健康的植物性饮食指数(UPDI)得分，并根据其两次得分的中位数将其分为四组，分别为：低-低、低-高、高-低和高-高组。采用Cox比例风险回归模型分析植物性饮食的动态变化与老年人的死亡关系。

结果

本研究共纳入4 382名研究对象，在7年随访期间，共有1 689(38.5%)名研究对象发生死亡。Cox比例风险回归模型结果显示：在调整性别、年龄、学历等混杂因素后，与得分低-低组相比，HPDI得分高-高组发生死亡风险降低了17%（HR=0.83, 95% CI：0.72~0.97），而UPDI得分高-高组发生死亡风险则增加了29%(HR=1.29，95% CI:1.11~1.49)。

结论

保持健康植物性饮食的老年人发生死亡的风险较低。

植物性饮食  /  植物性饮食动态变化  /  死亡  /  老年人  /  队列研究
Objective

To explore the relationship between the dynamics of plant-based diets and mortality in Chinese older adults.

Methods

Based on the data from the Chinese Longitudinal Healthy Longevity and Happy Family Study (CLHLS), older adults who participated in the three surveys from 2011-2018 were selected. The HPDI and UPDI scores of the study participants were calculated in 2011 and 2014, respectively, and they were categorized into four groups based on the median of their two scores: low-low, low-high, high-low and high-high groups. Cox proportional risk regression models were used to analyze the relationship between the dynamics of plant-based diets and mortality in the elderly.

Results

A total of 4 382 subjects were enrolled in this study, and 1 689 (38.5%) of them died during the 7-year follow-up period. The results of Cox proportional hazards regression model showed that after adjusting for confounding factors such as gender, age, and education, the risk of death in the high-high HPDI group was reduced by 17% (HR=0.83, 95% CI: 0.72-0.97), while the risk of death in the high-high UPDI group was increased by 29% (HR=1.29, 95% CI: 1.11-1.49).

Conclusion

Older adults who maintain a healthy plant-based diet have a lower risk of death.

Plant-based diet  /  Plant-based dietary changes  /  Death  /  Elderly  /  Cohort study
郭鉴婷, 方奎. 中国老年人植物性饮食的动态变化与死亡关系. 现代预防医学, 2024 , 51 (22) : 4091 -4095 . DOI: 10.20043/j.cnki.MPM.202406288
Jian-ting GUO, Kui FANG. Dynamic changes of plant-based diet and its relationship with mortality in elderly people in China[J]. Modern Preventive Medicine, 2024 , 51 (22) : 4091 -4095 . DOI: 10.20043/j.cnki.MPM.202406288
正文
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当前，人口老龄化已成为全球大多数国家面临的重大挑战。据统计，2017年全球60岁及以上的人口数量已达到9.62亿，并预计到2050年将成倍增长[1]。而在中国，2010—2020年间65岁及以上的老年人口已从8.9%增长到13.5%，预计到2050年将达到30.0%[2]。因此，改善老年人的健康状况并提高他们的生活品质已成为一个全球重要议题。
饮食习惯作为一种可调整的生活习惯，对人们健康的影响巨大，好的饮食习惯有助于提高人们的身体素质。但由于人们日常摄入的食物种类并不是单一的，很难通过某一食物评估人们的饮食习惯。因此，考虑到人们日常摄入食物种类的多样性和摄入频率的复杂性，Satija等研究者[3]为各类食物设定了相应的权重，进而创建了两个独特的饮食指数：健康的植物性饮食指数（Healthy plant-based diet index, HPDI)和不健康的植物性饮食指数（unhealthy plant-based diet index, UPDI）。先前的研究发现，植物性饮食指数与死亡风险之间存在关联，即健康的植物性饮食指数有助于降低死亡风险[4]。
然而，饮食习惯是动态变化的，目前尚不清楚植物性饮食的动态变化是否与老年人的死亡风险存在关联。因此，本研究通过一项全国性的前瞻性队列研究，探讨了植物性饮食的动态变化对老年人死亡风险的影响。
1　对象和方法
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1.1　研究对象
本研究数据来源于中国老年健康和家庭幸福调查(Chinese Longitudinal Healthy Longevity and Happy Family Study, CLHLS)。这项调查由北京大学健康老龄化与发展研究中心实施，其目标群体为中国65岁及以上的老年人，该调查始于1998年，并在2000年、2002年、2005年、2008年、2011年、2014年和2018年进行随访，主要了解老年人的健康状况、家庭情况以及生活习惯等信息[5]。
本研究主要利用2011年至2018年三次调查数据，总共调查了16 406名老年人。在数据筛选阶段，首先排除了在2011年和2014年调查时饮食数据缺失的研究对象；其次还排除了年龄低于65岁和发生失访的研究对象，最终本研究共纳入了4 382人。CLHLS 项目已获北京大学伦理委员会审批（IRB00001052-13074），所有研究对象在参与前均签署了知情同意书。
1.2　资料收集
由专业调查员对研究对象进行信息收集。调查内容主要包括一般人口学特征（如性别、年龄、学历等）、生活习惯（如吸烟、饮酒、饮食习惯等）、疾病史（如高血压、糖尿病、心脏病史）等。
1.3　相关定义
1.3.1　植物性饮食
本研究通过简化的食物频率问卷（FFQ）收集研究对象的饮食习惯。FFQ问卷已经过广泛验证，其信度和效度均已得到证实。该问卷涵盖了中国16种常见的食物类别，并根据其对健康的潜在影响分为三类：健康的植物性食物（全谷物、新鲜水果、蔬菜、豆类、大蒜、植物油、坚果和茶）、不健康的植物性食物（精制谷物、腌制蔬菜和糖）以及动物性食物（动物脂肪、鸡蛋、鱼和水产品、肉类、牛奶和乳制品）。植物性饮食涵盖了上述16种食物，并根据摄入频率为每种食物赋予相应的分数，最高为5分，最低为1分。
研究对象HPDI的计算方式为：对于健康的植物食物，摄入频率越高，计分越高；而对于不健康的植物性食物和动物性食物，则摄入频率越高，计分越低。UPDI的计算方式为：对于健康的植物性食物和动物性食物，摄入频率越高，计分越低，而对于不健康的植物性食物，则摄入频率越高计分越高。
1.3.2　植物性饮食的动态变化
在本研究中，我们分别计算了研究对象2011年和2014年的HPDI和UPDI得分，首先根据其得分中位数将研究对象分为两组，其次再根据HPDI和UPDI得分的动态变化情况，将研究对象分为四组，分别为低-低，低-高，高-低和高-高组。
1.3.3　随访时间及结局
2011年为研究对象的随访起点，随访终点为研究对象发生死亡或随访结束，随访时间为两次时间之差，具体死亡时间由研究对象家属提供。
1.4　统计学方法
SPSS 26.0和R 4.2.2用于数据分析。符合正态分布的计量资料使用均数和标准差()表示，单因素方差分析用来比较组间差异；对不符合正态分布的计量资料以中位数和第25、75百分位数［M(P25,P75)］表示，采用Wilcoxon秩和检验比较组间差异；计数资料使用频数和构成比(n,%)表示，卡方检验用来比较组间差异。在数据分析过程中，首先将基线HPDI、UPDI四分位，构建Cox 比例风险回归模型分析两种植物性饮食与老年人的死亡风险，其次分析两种植物性饮食的动态变化与老年人的死亡风险；最后通过亚组分析调查植物性饮食的动态变化和死亡风险是否存在性别和年龄差异。检验水准α=0.05。
2　结果
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2.1　研究对象基本特征
本研究共纳入4 382人，其中男性2 049人(46.8%），80岁老年人2 278人(52.0%)，研究对象平均年龄为82.3±10.4岁。在七年随访期间，共有1 689(38.5%)名研究对象死亡。死亡者中女性占比较高，受教育程度较低，且具有低锻炼史。此外，基线时研究对象的HPDI得分较低，UPDI得分较高，见表1。
2.2　基线HPDI、UPDI与老年人死亡的关联
将基线HPDI、UPDI得分按照四分位数进行分组，在调整性别、年龄、学历、吸烟、饮酒等混杂因素后（模型2），与HPDI得分Q1组相比，Q3组和Q4组发生死亡的风险分别降低17%和18%，其HR和95% CI分别为0.83(0.71~0.98)、0.82(0.69~0.98)；而与UPDI得分Q1组相比，Q4组发生死亡的风险则增加了24%，其HR和95% CI为1.24(1.04~1.47)，见表2。
2.3　HPDI、UPDI的动态变化与老年人死亡的关联
HPDI和UPDI得分的动态变化与死亡风险密切相关。在调整性别、年龄、学历等混杂因素后，与HPDI得分稳定的低-低组相比，低-高组和高-高组发生死亡的风险分别降低16%和17%，而高-低组虽然也会降低死亡风险，但该差异不具有统计学意义(P>0.05)。而与UPDI得分稳定的低-低组相比，低-高组和高-高组发生死亡的风险则上升了25%和29%，其HR和95% CI分别为1.25(1.06~1.49)，1.29(1.11~1.49)，见表3。
2.4　不同年龄组HPDI、UPDI的动态变化与老年人死亡的关联
HPDI、UPDI的动态变化与老年人死亡风险关系如图1所示。在65~80岁年龄段内，与稳定的低-低组相比，HPDI得分高-高组发生死亡风险降低了39%，而UPDI得分高-高组发生死亡的风险则升高了64%；而在年龄>80岁年龄组，仅发现UPDI得分低-高组会增加其死亡风险 (HR=1.31,95% CI:1.08~1.58)。
2.5　不同性别组HPDI、UPDI的动态变化与老年人死亡的关联
图2展示了不同性别组中HPDI、UPDI的动态变化与老年人死亡风险关系。在男性组中仅观察到UPDI得分低-高组和高-高组会增加老年人的死亡风险，其HR和95% CI分别为1.27(1.01~1.61)，1.28(1.02~1.61)；而在女性组，与稳定的低-低组相比，HPDI得分低-高组发生死亡风险降低了21%，而UPDI得分高-高组发生死亡的风险则升高了25%。
3　讨论
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本研究主要调查了老年人植物性饮食的动态变化与死亡风险关系。研究结果发现保持健康植物性饮食的老年人发生死亡风险较低。与低-低组相比，HPDI得分高-高组发生死亡的风险降低了17%，而UPDI得分高-高组发生死亡的风险则增加了29%。
植物性饮食与健康的关系一直是人们研究的焦点。过去，对植物性饮食的研究较为表面，主要是因为人们习惯性地将食物简单划分为素食和非素食两大类，未曾深入研究食物之间的质量差异[6]。实际上，不同种类的食物在营养成分和健康效益上都存在着显著的差异。研究显示，摄入健康的植物性食物，如全谷物、蔬菜、水果和坚果等，能够显著降低全因死亡风险[7-8]。然而，摄入过多不健康的植物性食物，如高糖食品和咸菜等，可能会增加患心血管疾病和死亡的风险[9]。因此Satija等研究者创建的涵盖16种食物的植物性饮食指数能全面地评估人们的饮食情况，了解人们的饮食习惯。
本研究发现基线时健康的植物性性饮食会降低死亡风险，而不健康的植物性饮食则会增加死亡风险，这和先前的研究相一致[10-11]。然而，植物性饮食的动态变化与死亡风险之间的关系尚未被充分研究。一项来自美国的历经12年深入追踪的大型队列研究结果表明：保持健康的植物性饮食能够显著降低心血管疾病的死亡率和总体死亡率；相反，长期维持不健康的植物性饮食则会增加心血管疾病死亡率和死亡风险[12]。在我们的研究中，同样观察到了类似结果，即保持健康植物性饮食的研究对象，其死亡风险也会显著降低。但值得注意的是，在80岁及以上的高龄老人中，保持健康的植物性饮食似乎并未对死亡风险产生显著影响，这可能与高龄老人身体各方面机能下降有关。在这一时期，由于机体的自然衰老，即使改善了饮食习惯，饮食调整所带来的益处也往往被掩盖或减弱。
健康的植物性饮食之所以能够降低死亡风险，可能与多种机制有关。一方面，植物性饮食中的全谷物、水果、蔬菜和茶叶富含膳食纤维、儿茶素以及茶黄素等成分，它们具有显著的抗炎和抗氧化功效，有助于维护身体机能的稳态与健康[13]。另一方面，植物性饮食减少了高糖高脂食物的摄入，从而降低了罹患高血压、糖尿病等心血管疾病的风险[14]，进而降低了死亡风险。
尽管本研究是一项具有全国代表性的前瞻性队列研究，但本研究仍存在一些不足。首先，饮食信息是通过自我报告的方式收集的，这可能会存在回忆偏差。其次，本研究未考虑膳食补充剂对研究结果的潜在影响，这可能会使研究结果不够全面。最后需要指出的是，本研究的研究对象主要是65岁及以上的老年人，这会在一定程度上限制我们将研究结论推广到其他人群。
综上所述，本研究发现保持健康的植物性饮食可以显著降低老年人的死亡风险。因此，在以后的生活中，老年人应多吃水果蔬菜，保持健康饮食习惯。
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  • 辽宁省教育厅2020年度科学研究项目(FWZR2020004)
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2024年第51卷第22期
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doi: 10.20043/j.cnki.MPM.202406288
  • 接收时间：2024-06-18
  • 首发时间：2026-03-20
  • 出版时间：2024-11-25
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  • 收稿日期：2024-06-18
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辽宁省教育厅2020年度科学研究项目(FWZR2020004)
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    1.中国医科大学附属盛京医院，辽宁　沈阳　110022
    2.中国医科大学附属第一医院

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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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