Article(id=1311350241312473231, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202603128, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1773072000000, receivedDateStr=2026-03-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579861237, onlineDateStr=2026-09-28, pubDate=1786291200000, pubDateStr=2026-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579861237, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579861237, creator=13701087609, updateTime=1790579861237, updator=13701087609, issue=Issue{id=1311350193946194882, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='15', pageStart='2689', pageEnd='2880', issueExtLink='null', onlineDate='null', pubDate='1786291200000', pubDateStr='2026-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579849945, creator='13701087609', updateTime=1790588319569, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385718195315029, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385718195315030, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2739, endPage=2745, ext={EN=ArticleExt(id=1311350243778723984, articleId=1311350241312473231, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association of the Chinese Healthy Eating Index with musculoskeletal age acceleration in middle-aged and older adults, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

This study aims to investigate the impact of dietary quality on musculoskeletal age acceleration(MuscAgeAccel) in middle-aged and older adults, providing a scientific basis for dietary interventions to slow musculoskeletal aging.

Methods

A cross-sectional study was conducted involving 3 765 adults aged 45 years and above from the West China Health and Aging Cohort Study and the West China Bone Health Cohort. Diet quality was assessed by calculating the Chinese Healthy Eating Index (CHEI), using a simplified food frequency questionnaire (FFQ-25). MuscAgeAccel was calculated as the difference between musculoskeletal biological age predicted from clinical indicators and chronological age. Multiple linear regression models were used to examine the association between the CHEI and MuscAgeAccel, while adjusting for demographic characteristics, lifestyle factors, and chronic diseases. Subgroup analyses were then conducted.

Results

The CHEI score was negatively associated with MuscAgeAccel (rs=-0.09). Compared with participants in the lowest CHEI score group, those in the highest score group exhibited a 0.31-year reduction in MuscAgeAccel (β=-0.31, 95% CI:-0.51~-0.10). Subgroup analyses revealed that the beneficial effect of higher dietary quality on slowing musculoskeletal aging was more pronounced in males, those with body mass index (BMI) > 24 kg/m2, and non-smokers (all P for interaction <0.05).

Conclusion

Adherence to the healthy dietary pattern recommended by the Chinese Dietary Guidelines may attenuate musculoskeletal age acceleration and reduce the risk of diseases related to musculoskeletal aging.

, authors=Zi-lan CHEN1, Mao-yao XIA1, Yang-dan ZHONG1, Yu-qi PANG1, Wen HU2, Tao ZHANG1, Lu LONG1, Meng-yu FAN1, Jia-yuan LI1, Xia JIANG1, authorsList=Zi-lan CHEN, Mao-yao XIA, Yang-dan ZHONG, Yu-qi PANG, Wen HU, Tao ZHANG, Lu LONG, Meng-yu FAN, Jia-yuan LI, Xia JIANG, authorCompany=null, correspAuthors=Xia JIANG, 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=1311350245569691795, articleId=1311350241312473231, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=中国健康饮食指数与中老年人群肌骨生物年龄加速的关联, columnId=1228016573034721597, journalTitle=现代预防医学, columnName=营养与食品卫生, runingTitle=null, highlight=null, articleAbstract=
目的

本研究旨在探讨中老年人群饮食质量对肌骨生物年龄加速的影响,为通过膳食营养策略干预肌骨衰老提供科学依据。

方法

对纳入华西健康增龄队列及华西骨健康队列基线调查数据3 765名45岁及以上中老年人开展横断面研究,采用简化食物频率问卷计算中国健康饮食指数(the Chinese Healthy Eating Index,CHEI)以评估饮食质量。以通过临床指标预测的肌骨生物年龄与实际年龄差值表征肌骨生物年龄加速,控制人口学特征、生活方式、慢性病等潜在混杂因素,采用多元线性回归分析CHEI与肌骨生物年龄加速的关联,并进行亚组分析。

结果

CHEI总分与肌骨生物年龄加速呈负相关(rs=-0.09),与CHEI得分最低组相比,得分最高组肌骨生物年龄加速值降低0.31岁(β=-0.31,95%CI:-0.51 ~ -0.10)。亚组分析显示,在男性、身体质量指数(body mass index,BMI)>24 kg/m2及不吸烟者中,提高膳食质量能更有效延缓肌骨衰老(P交互作用均<0.05)。

结论

遵循中国居民膳食指南的健康饮食模式可减缓肌骨生物年龄加速,降低肌骨衰老相关疾病风险。

, authors=陈子岚1, 夏茂瑶1, 钟扬丹1, 庞玉琦1, 胡雯2, 张韬1, 龙璐1, 樊萌语1, 李佳圆1, 姜侠1, authorsList=陈子岚, 夏茂瑶, 钟扬丹, 庞玉琦, 胡雯, 张韬, 龙璐, 樊萌语, 李佳圆, 姜侠, authorCompany=null, correspAuthors=姜侠, authorNote=

陈子岚(2003—),女,硕士在读,研究方向:营养与食品卫生学

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姜侠,E-mail:
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Effects of different varieties and processing degree grains on blood glucose and blood lipid in rats[J]. 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Research progress on preventive and interventional effects of dairy products on osteoporosis[J]. Food Science,2023, 44(9): 245-258.(In Chinese), articleTitle=Research progress on preventive and interventional effects of dairy products on osteoporosis, refAbstract=null), Reference(id=1311350283641389315, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, doi=null, pmid=null, pmcid=null, year=2024, volume=27, issue=5, pageStart=466, pageEnd=472, url=null, language=null, rfNumber=[23], rfOrder=31, authorNames=Wright VJ, Schwartzman JD, Itinoche R, journalName=Climacteric, refType=null, unstructuredReference=Wright VJ, Schwartzman JD, Itinoche R, et al. The musculoskeletal syndrome of menopause[J]. Climacteric, 2024, 27(5): 466-472., articleTitle=The musculoskeletal syndrome of menopause, refAbstract=null), Reference(id=1311350283716886788, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, doi=null, pmid=null, pmcid=null, year=2020, volume=29, issue=Suppl 2, pageStart=s102, pageEnd=s109, url=null, language=null, rfNumber=[24], rfOrder=32, authorNames=Khan NA, Lawyer G, McDonough S, journalName=Tobacco Control, refType=null, unstructuredReference=Khan NA, Lawyer G, McDonough S, et al. Systemic biomarkers of inflammation, oxidative stress and tissue injury and repair among waterpipe, cigarette and dual tobacco smokers[J]. Tobacco Control,2020, 29(Suppl 2): s102-s109., articleTitle=Systemic biomarkers of inflammation, oxidative stress and tissue injury and repair among waterpipe, cigarette and dual tobacco smokers, refAbstract=null)], funds=[Fund(id=1311350272258048221, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, awardId=2023YFC3606300, language=CN, fundingSource=国家重点研发计划(2023YFC3606300), fundOrder=null, country=null), Fund(id=1311350272320962782, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, awardId=2024NSFTD0030, language=CN, fundingSource=四川省科技厅自然科学基金创新研究群体(2024NSFTD0030), fundOrder=null, country=null), Fund(id=1311350272388071647, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, awardId=2023SY-03, language=CN, fundingSource=四川大学华西公共卫生学院(华西第四医院)实验学科振兴计划(2023SY-03), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1311350248790917268, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, xref=1., ext=[AuthorCompanyExt(id=1311350248837054613, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, companyId=1311350248790917268, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1311350248874803350, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, companyId=1311350248790917268, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.四川大学华西公共卫生学院/华西第四医院,四川 成都 610041)]), AuthorCompany(id=1311350249667526807, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, xref=2., ext=[AuthorCompanyExt(id=1311350250015654040, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, companyId=1311350249667526807, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.四川大学华西医院临床营养科)])], figs=[ArticleFig(id=1311350267652702417, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Figure 1, caption=The flowchart of participants selection, figureFileSmall=ShHJqUMrCEQNStpGtOw5cA==, figureFileBig=7E/6l80D0JkfiapV1uJOWA==, tableContent=null), ArticleFig(id=1311350267719811282, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=图1, caption=研究对象筛选流程图, figureFileSmall=ShHJqUMrCEQNStpGtOw5cA==, figureFileBig=7E/6l80D0JkfiapV1uJOWA==, tableContent=null), ArticleFig(id=1311350269758243027, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Table 1, caption=

CHEI scoring criteria

, figureFileSmall=null, figureFileBig=null, tableContent=
食物组最高分最高分标准最低分标准
谷物5≥2.5标准份/1 000 kcal无摄入
全谷物5≥0.6标准份/1 000 kcal
薯类5≥0.3标准份/1 000 kcal
蔬菜5≥1.9标准份/1 000 kcal
深色蔬菜5≥0.9标准份/1 000 kcal
水果10≥1.1标准份/1 000 kcal
奶类5≥0.5标准份/1 000 kcal
豆类5≥0.4标准份/1 000 kcal
水产类5≥0.6标准份/1 000 kcal
禽类5≥0.3标准份/1 000 kcal
蛋类5≥0.5标准份/1 000 kcal
坚果类5≥0.4标准份/1 000 kcal
红肉类5≤0.4标准份/1 000 kcal≥3.5标准份/1 000 kcal
酒精5≤25 g(男)/15 g(女)≥60 g(男)/40 g(女)
), ArticleFig(id=1311350269816963284, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=表1, caption=

CHEI评分标准

, figureFileSmall=null, figureFileBig=null, tableContent=
食物组最高分最高分标准最低分标准
谷物5≥2.5标准份/1 000 kcal无摄入
全谷物5≥0.6标准份/1 000 kcal
薯类5≥0.3标准份/1 000 kcal
蔬菜5≥1.9标准份/1 000 kcal
深色蔬菜5≥0.9标准份/1 000 kcal
水果10≥1.1标准份/1 000 kcal
奶类5≥0.5标准份/1 000 kcal
豆类5≥0.4标准份/1 000 kcal
水产类5≥0.6标准份/1 000 kcal
禽类5≥0.3标准份/1 000 kcal
蛋类5≥0.5标准份/1 000 kcal
坚果类5≥0.4标准份/1 000 kcal
红肉类5≤0.4标准份/1 000 kcal≥3.5标准份/1 000 kcal
酒精5≤25 g(男)/15 g(女)≥60 g(男)/40 g(女)
), ArticleFig(id=1311350270160896213, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Table 2, caption=

Baseline characteristics of study participants[ M( P 25, P75), n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群(n=3 765)肌骨生物年龄非加速(n=1 819)肌骨生物年龄加速
(n=1 946)
H/χ2值P值
年龄(岁)66.0 (61.0, 70.0)67.0 (62.0, 70.0)65.0 (60.0, 69.0)38.032<0.001
性别64.370<0.001
女性2 538 (67.4)1 342 (73.8)1 196 (61.5)
男性1 227 (32.6)477 (26.2)750 (38.5)
民族0.0001.000
汉族3 728 (99.0)1 801 (99.0)1 927 (99.0)
其他37 (1.0)18 (1.0)19 (1.0)
最高教育学历12.9120.012
未正规上学730 (19.4)316 (17.4)414 (21.3)
小学578 (15.4)278 (15.3)300 (15.4)
初中885 (23.5)427 (23.5)458 (23.5)
高中及以上1 562 (41.5)795 (43.7)767 (39.4)
不清楚10 (0.3)3 (0.2)7 (0.4)
婚姻状况9.1220.010
已婚3 145 (83.5)1 488 (81.8)1 657 (85.1)
其他611 (16.2)328 (18.0)283 (14.5)
不清楚9 (0.2)3 (0.2)6 (0.3)
个人可支配收入3.3170.345
低收入1 104 (29.3)508 (27.9)596 (30.6)
中等收入1 445 (38.4)713 (39.2)732 (37.6)
高收入1 128 (30.0)555 (30.5)573 (29.4)
不清楚88 (2.3)43 (2.4)45 (2.3)
骨质疏松家族史0.8530.653.
是407 (10.8)189 (10.4)218 (11.2)
否3 199 (85.0)1 550 (85.2)1 649 (84.7)
不清楚159 (4.2)80 (4.4)79 (4.1)
数据来源19.784<0.001
华西骨健康队列1 457 (38.7)637 (35.0)820 (42.1)
华西健康增龄队列2 308 (61.3)1 182 (65.0)1 126 (57.9)
吸烟史44.298<0.001
从不吸烟3 029 (80.5)1 542 (84.8)1 487 (76.4)
曾经吸烟418 (11.1)168 (9.2)250 (12.8)
现在吸烟318 (8.4)109 (6.0)209 (10.7)
BMI(kg/m2)23.9 (22.1, 26.0)23.9 (22.2, 26.1)23.9 (22.0, 25.9)3.6420.056
体力活动28.035<0.001
低强度883 (23.5)363 (20.0)520 (26.7)
中等强度1 349 (35.8)656 (36.1)693 (35.6)
高强度1 480 (39.3)770 (42.3)710 (36.5)
不清楚53 (1.4)30 (1.6)23 (1.2)
复合维生素补充剂0.3570.550
是481 (12.8)239 (13.1)242 (12.4)
否3 284 (87.2)1 580 (86.9)1 704 (87.6)
维生素D补充剂1.7930.181
是500 (13.3)256 (14.1)244 (12.5)
否3 265 (86.7)1 563 (85.9)1 702 (87.5)
钙补充剂0.3440.853
是1 469 (39.0)713 (39.2)756 (38.8)
否2 296 (61.0)1 106 (60.8)1 190 (61.2)
糖尿病0.9430.624
有498 (13.2)237 (13.0)261 (13.4)
无3 258 (86.5)1 579 (86.8)1 679 (86.3)
不清楚9 (0.2)3 (0.2)6 (0.3)
高血压1.6690.434
有1 241 (33.0)592 (32.5)649 (33.4)
无2 514 (66.8)1 224 (67.3)1 290 (66.3)
不清楚10 (0.3)3 (0.2)7 (0.4)
), ArticleFig(id=1311350270253170902, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=表2, caption=

研究对象的基本特征[M(P25,P75),n(%)]

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变量总人群(n=3 765)肌骨生物年龄非加速(n=1 819)肌骨生物年龄加速
(n=1 946)
H/χ2值P值
年龄(岁)66.0 (61.0, 70.0)67.0 (62.0, 70.0)65.0 (60.0, 69.0)38.032<0.001
性别64.370<0.001
女性2 538 (67.4)1 342 (73.8)1 196 (61.5)
男性1 227 (32.6)477 (26.2)750 (38.5)
民族0.0001.000
汉族3 728 (99.0)1 801 (99.0)1 927 (99.0)
其他37 (1.0)18 (1.0)19 (1.0)
最高教育学历12.9120.012
未正规上学730 (19.4)316 (17.4)414 (21.3)
小学578 (15.4)278 (15.3)300 (15.4)
初中885 (23.5)427 (23.5)458 (23.5)
高中及以上1 562 (41.5)795 (43.7)767 (39.4)
不清楚10 (0.3)3 (0.2)7 (0.4)
婚姻状况9.1220.010
已婚3 145 (83.5)1 488 (81.8)1 657 (85.1)
其他611 (16.2)328 (18.0)283 (14.5)
不清楚9 (0.2)3 (0.2)6 (0.3)
个人可支配收入3.3170.345
低收入1 104 (29.3)508 (27.9)596 (30.6)
中等收入1 445 (38.4)713 (39.2)732 (37.6)
高收入1 128 (30.0)555 (30.5)573 (29.4)
不清楚88 (2.3)43 (2.4)45 (2.3)
骨质疏松家族史0.8530.653.
是407 (10.8)189 (10.4)218 (11.2)
否3 199 (85.0)1 550 (85.2)1 649 (84.7)
不清楚159 (4.2)80 (4.4)79 (4.1)
数据来源19.784<0.001
华西骨健康队列1 457 (38.7)637 (35.0)820 (42.1)
华西健康增龄队列2 308 (61.3)1 182 (65.0)1 126 (57.9)
吸烟史44.298<0.001
从不吸烟3 029 (80.5)1 542 (84.8)1 487 (76.4)
曾经吸烟418 (11.1)168 (9.2)250 (12.8)
现在吸烟318 (8.4)109 (6.0)209 (10.7)
BMI(kg/m2)23.9 (22.1, 26.0)23.9 (22.2, 26.1)23.9 (22.0, 25.9)3.6420.056
体力活动28.035<0.001
低强度883 (23.5)363 (20.0)520 (26.7)
中等强度1 349 (35.8)656 (36.1)693 (35.6)
高强度1 480 (39.3)770 (42.3)710 (36.5)
不清楚53 (1.4)30 (1.6)23 (1.2)
复合维生素补充剂0.3570.550
是481 (12.8)239 (13.1)242 (12.4)
否3 284 (87.2)1 580 (86.9)1 704 (87.6)
维生素D补充剂1.7930.181
是500 (13.3)256 (14.1)244 (12.5)
否3 265 (86.7)1 563 (85.9)1 702 (87.5)
钙补充剂0.3440.853
是1 469 (39.0)713 (39.2)756 (38.8)
否2 296 (61.0)1 106 (60.8)1 190 (61.2)
糖尿病0.9430.624
有498 (13.2)237 (13.0)261 (13.4)
无3 258 (86.5)1 579 (86.8)1 679 (86.3)
不清楚9 (0.2)3 (0.2)6 (0.3)
高血压1.6690.434
有1 241 (33.0)592 (32.5)649 (33.4)
无2 514 (66.8)1 224 (67.3)1 290 (66.3)
不清楚10 (0.3)3 (0.2)7 (0.4)
), ArticleFig(id=1311350270613881047, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Table 3, caption=

Results of correlation analysis of CHEI and different food groups with musculoskeletal age acceleration (rs)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标肌骨生物年龄加速
CHEI-0.09***
谷物0.05**
全谷物-0.04*
薯类-0.02
蔬菜-0.05**
深色蔬菜-0.07***
水果-0.08***
奶类0.00
豆类-0.02
水产类-0.07***
禽类0.02
蛋类0.00
坚果类-0.07***
红肉类-0.02
酒精-0.02
), ArticleFig(id=1311350271008145624, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=表3, caption=

CHEI及不同食物组与肌骨生物年龄加速的关联性分析结果(rs)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标肌骨生物年龄加速
CHEI-0.09***
谷物0.05**
全谷物-0.04*
薯类-0.02
蔬菜-0.05**
深色蔬菜-0.07***
水果-0.08***
奶类0.00
豆类-0.02
水产类-0.07***
禽类0.02
蛋类0.00
坚果类-0.07***
红肉类-0.02
酒精-0.02
), ArticleFig(id=1311350271440158937, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Table 4, caption=

Multiple linear regression analysis of CHEI and MuscAgeAccel

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1a模型2b模型3c
β(95%CI)P值β(95%CI)P值β(95%CI)P值
CHEI总分-0.13 (-0.20 ~ -0.06)0.001-0.10 (-0.17 ~ -0.03)0.008-0.10 (-0.17 ~ -0.03)0.008
Q1 (<42.92)参照组参照组参照组
Q2 (42.92-47.50)-0.21 (-0.40 ~ -0.02)0.033-0.18 (-0.38 ~ 0.01)0.060-0.19 (-0.38 ~ 0.00)0.052
Q3 (47.50-51.76)-0.29 (-0.49 ~ -0.10)0.003-0.25 (-0.44 ~ -0.05)0.013-0.24 (-0.44 ~ -0.05)0.014
Q4 (>51.76)-0.37 (-0.58 ~ -0.17)<0.001-0.31 (-0.51 ~ -0.10)0.003-0.31 (-0.51 ~ -0.10)0.003
P趋势值<0.0010.0020.003
), ArticleFig(id=1311350271528239322, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=表4, caption=

CHEI与肌骨生物年龄加速的多元线性回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1a模型2b模型3c
β(95%CI)P值β(95%CI)P值β(95%CI)P值
CHEI总分-0.13 (-0.20 ~ -0.06)0.001-0.10 (-0.17 ~ -0.03)0.008-0.10 (-0.17 ~ -0.03)0.008
Q1 (<42.92)参照组参照组参照组
Q2 (42.92-47.50)-0.21 (-0.40 ~ -0.02)0.033-0.18 (-0.38 ~ 0.01)0.060-0.19 (-0.38 ~ 0.00)0.052
Q3 (47.50-51.76)-0.29 (-0.49 ~ -0.10)0.003-0.25 (-0.44 ~ -0.05)0.013-0.24 (-0.44 ~ -0.05)0.014
Q4 (>51.76)-0.37 (-0.58 ~ -0.17)<0.001-0.31 (-0.51 ~ -0.10)0.003-0.31 (-0.51 ~ -0.10)0.003
P趋势值<0.0010.0020.003
), ArticleFig(id=1311350271838617819, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=EN, label=Table 5, caption=

Results of subgroup analysis of CHEI and MuscAgeAccel

, figureFileSmall=null, figureFileBig=null, tableContent=
变量样本量β(95%CI)P值P交互作用
年龄(岁)
45 ~ 60656-0.12 (-0.28 ~ 0.04)0.1330.883
>603 109-0.09 (-0.18 ~ -0.01)0.022
性别
女性2 538-0.06 (-0.15 ~ 0.02)0.1640.002
男性1 227-0.13 (-0.23 ~ -0.02)0.021
BMI (kg/m2)
≤ 241 819-0.06 (-0.16 ~ 0.05)0.2980.009
>241 741-0.10 (-0.20 ~ 0.01)0.070
吸烟史
从不吸烟3 029-0.10 (-0.18 ~ -0.02)0.0150.003
曾经或现在吸烟736-0.05 (-0.19 ~ 0.08)0.414
体力活动
低强度883-0.07 (-0.22 ~ 0.08)0.3510.163
中高强度2 829-0.10 (-0.19 ~ -0.02)0.017
糖尿病
无3 258-0.09 (-0.17 ~ -0.01)0.0250.800
有498-0.15 (-0.37 ~ 0.07)0.177
高血压
无2 514-0.09 (-0.18 ~ -0.01)0.0400.711
有1 241-0.11 (-0.25 ~ 0.02)0.096
), ArticleFig(id=1311350271922503900, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350241312473231, language=CN, label=表5, caption=

CHEI与肌骨生物年龄加速的亚组分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量样本量β(95%CI)P值P交互作用
年龄(岁)
45 ~ 60656-0.12 (-0.28 ~ 0.04)0.1330.883
>603 109-0.09 (-0.18 ~ -0.01)0.022
性别
女性2 538-0.06 (-0.15 ~ 0.02)0.1640.002
男性1 227-0.13 (-0.23 ~ -0.02)0.021
BMI (kg/m2)
≤ 241 819-0.06 (-0.16 ~ 0.05)0.2980.009
>241 741-0.10 (-0.20 ~ 0.01)0.070
吸烟史
从不吸烟3 029-0.10 (-0.18 ~ -0.02)0.0150.003
曾经或现在吸烟736-0.05 (-0.19 ~ 0.08)0.414
体力活动
低强度883-0.07 (-0.22 ~ 0.08)0.3510.163
中高强度2 829-0.10 (-0.19 ~ -0.02)0.017
糖尿病
无3 258-0.09 (-0.17 ~ -0.01)0.0250.800
有498-0.15 (-0.37 ~ 0.07)0.177
高血压
无2 514-0.09 (-0.18 ~ -0.01)0.0400.711
有1 241-0.11 (-0.25 ~ 0.02)0.096
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中国健康饮食指数与中老年人群肌骨生物年龄加速的关联
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陈子岚 1 , 夏茂瑶 1 , 钟扬丹 1 , 庞玉琦 1 , 胡雯 2 , 张韬 1 , 龙璐 1 , 樊萌语 1 , 李佳圆 1 , 姜侠 1
现代预防医学 | 营养与食品卫生 2026,53(15): 2739-2745
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现代预防医学 |营养与食品卫生 2026 , 53 (15) : 2739 -2745
中国健康饮食指数与中老年人群肌骨生物年龄加速的关联
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陈子岚(2003—),女,硕士在读,研究方向:营养与食品卫生学

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陈子岚(2003—),女,硕士在读,研究方向:营养与食品卫生学

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陈子岚1, 夏茂瑶1, 钟扬丹1, 庞玉琦1, 胡雯2, 张韬1, 龙璐1, 樊萌语1, 李佳圆1, 姜侠1
作者信息
  • 1.四川大学华西公共卫生学院/华西第四医院,四川 成都 610041
  • 2.四川大学华西医院临床营养科
通讯作者:
姜侠,E-mail:
作者简介:

陈子岚(2003—),女,硕士在读,研究方向:营养与食品卫生学

Association of the Chinese Healthy Eating Index with musculoskeletal age acceleration in middle-aged and older adults
Zi-lan CHEN1, Mao-yao XIA1, Yang-dan ZHONG1, Yu-qi PANG1, Wen HU2, Tao ZHANG1, Lu LONG1, Meng-yu FAN1, Jia-yuan LI1, Xia JIANG1
Affiliations
  • West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2026-08-10 doi: 10.20043/j.cnki.MPM.202603128
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目的

本研究旨在探讨中老年人群饮食质量对肌骨生物年龄加速的影响,为通过膳食营养策略干预肌骨衰老提供科学依据。

方法

对纳入华西健康增龄队列及华西骨健康队列基线调查数据3 765名45岁及以上中老年人开展横断面研究,采用简化食物频率问卷计算中国健康饮食指数(the Chinese Healthy Eating Index,CHEI)以评估饮食质量。以通过临床指标预测的肌骨生物年龄与实际年龄差值表征肌骨生物年龄加速,控制人口学特征、生活方式、慢性病等潜在混杂因素,采用多元线性回归分析CHEI与肌骨生物年龄加速的关联,并进行亚组分析。

结果

CHEI总分与肌骨生物年龄加速呈负相关(rs=-0.09),与CHEI得分最低组相比,得分最高组肌骨生物年龄加速值降低0.31岁(β=-0.31,95%CI:-0.51 ~ -0.10)。亚组分析显示,在男性、身体质量指数(body mass index,BMI)>24 kg/m2及不吸烟者中,提高膳食质量能更有效延缓肌骨衰老(P交互作用均<0.05)。

结论

遵循中国居民膳食指南的健康饮食模式可减缓肌骨生物年龄加速,降低肌骨衰老相关疾病风险。

中国健康饮食指数  /  肌骨生物年龄加速  /  横断面研究
Objective

This study aims to investigate the impact of dietary quality on musculoskeletal age acceleration(MuscAgeAccel) in middle-aged and older adults, providing a scientific basis for dietary interventions to slow musculoskeletal aging.

Methods

A cross-sectional study was conducted involving 3 765 adults aged 45 years and above from the West China Health and Aging Cohort Study and the West China Bone Health Cohort. Diet quality was assessed by calculating the Chinese Healthy Eating Index (CHEI), using a simplified food frequency questionnaire (FFQ-25). MuscAgeAccel was calculated as the difference between musculoskeletal biological age predicted from clinical indicators and chronological age. Multiple linear regression models were used to examine the association between the CHEI and MuscAgeAccel, while adjusting for demographic characteristics, lifestyle factors, and chronic diseases. Subgroup analyses were then conducted.

Results

The CHEI score was negatively associated with MuscAgeAccel (rs=-0.09). Compared with participants in the lowest CHEI score group, those in the highest score group exhibited a 0.31-year reduction in MuscAgeAccel (β=-0.31, 95% CI:-0.51~-0.10). Subgroup analyses revealed that the beneficial effect of higher dietary quality on slowing musculoskeletal aging was more pronounced in males, those with body mass index (BMI) > 24 kg/m2, and non-smokers (all P for interaction <0.05).

Conclusion

Adherence to the healthy dietary pattern recommended by the Chinese Dietary Guidelines may attenuate musculoskeletal age acceleration and reduce the risk of diseases related to musculoskeletal aging.

Chinese Healthy Eating Index  /  Musculoskeletal age acceleration  /  Cross-sectional study
陈子岚, 夏茂瑶, 钟扬丹, 庞玉琦, 胡雯, 张韬, 龙璐, 樊萌语, 李佳圆, 姜侠. 中国健康饮食指数与中老年人群肌骨生物年龄加速的关联. 现代预防医学, 2026 , 53 (15) : 2739 -2745 . DOI: 10.20043/j.cnki.MPM.202603128
Zi-lan CHEN, Mao-yao XIA, Yang-dan ZHONG, Yu-qi PANG, Wen HU, Tao ZHANG, Lu LONG, Meng-yu FAN, Jia-yuan LI, Xia JIANG. Association of the Chinese Healthy Eating Index with musculoskeletal age acceleration in middle-aged and older adults[J]. Modern Preventive Medicine, 2026 , 53 (15) : 2739 -2745 . DOI: 10.20043/j.cnki.MPM.202603128
相较于时序年龄,生物年龄(biological age)作为一种综合多种衰老相关标志物的指标,能更准确地反映个体实际衰老状态,已广泛用于年龄相关疾病的风险预测[1]。由于不同器官系统衰老程度存在异质性,近年来研究开始关注器官特异性生物年龄的构建,如肌骨生物年龄(musculoskeletal age)[2]。相较于单一的肌骨疾病临床指标,肌骨生物年龄以年龄为标尺,通过整合临床影像学与人体测量指标,能更精准地反映肌肉骨骼系统的生物衰老程度。肌骨生物年龄加速(musculoskeletal age acceleration)作为肌骨生物年龄与实际年龄的差值,量化了个体相较于同龄人肌肉骨骼系统的相对衰老水平,为肌肉骨骼疾病的早期评估与风险预测提供了新视角。
生物衰老进程在一定程度上可通过早期干预加以调节。膳食作为可干预的核心生活方式因素,在调控衰老相关机制中发挥着重要作用[3]。已有研究表明,地中海饮食、得舒饮食等膳食模式可通过抗炎、抗氧化、维持代谢稳态及改善肠道微生态等途径,对全身生物衰老产生积极影响[4]。然而,适用于中国人群的膳食模式与基于生物年龄的肌骨衰老之间的关联尚未得到系统探讨。为此,本研究基于中国本土人群数据,采用中国健康饮食指数(Chinese Healthy Eating Index,CHEI)评估饮食质量,分析CHEI及其各组分与肌骨生物年龄加速之间的关联,以期为通过膳食干预延缓肌肉骨骼系统衰老提供基于中国人群的科学依据。
数据来源于华西健康增龄队列(原华西老年人群健康队列)[5]及华西骨健康队列基线调查[6]。华西健康增龄队列基线评估于2022年5月—2023年12月进行,包括10 626名年龄在54岁及以上的社区居民。华西骨健康队列基线调查于2023年5月启动,包括1 518名年龄在25岁及以上的门诊参与者。数据采集均涵盖问卷调查、体格检查、影像学检查及生物标志物检测等多个方面。在这两项队列的参与者中,3 878名有完整膳食数据及肌骨生物年龄计算指标。排除45岁以下24名、合并恶性肿瘤52名、报告极端能量摄入37名,最终确定3 765名参与者纳入研究,研究经伦理委员会批准(HXSY-EC-2025057,HXSY-EC-2025059)。完整筛选流程见图1。
饮食信息由受过培训的调查员采用经验证的简化食物频率问卷(food frequency questionnaire,FFQ25)通过面对面访谈收集[7]。该问卷详细记录了调查对象过去一年内各类食物的消费频率(包括每日、每周、每月摄入次数)及单次摄入量。
CHEI是根据中国居民膳食指南建立的膳食评价工具[8-9],通过换算每类食物的摄入量及份数,并依据推荐摄入量计算17个条目的得分,包括膳食指南建议的12类“适宜量”摄入的食物(谷物、全谷物、薯类、蔬菜、深绿色蔬菜、水果、奶制品、豆类、水产品、禽肉、蛋类、坚果)和五类限制摄入的食物(红肉、食用油脂、钠、添加糖、酒精)。对于每一类食物,零摄入或达到推荐值将分别得0分或最高分,而介于0和推荐值之间的摄入量则按比例进行赋分。由于本研究未收集食用油脂、钠及添加糖的摄入信息,故这3个条目未纳入总分计算,因此本研究的CHEI最高可能得分为75分,分数越高代表对中国居民膳食指南的依从性越高。除酒精外,所有食物摄入量均按能量密度(每1 000 kcal)进行调整。评分标准见表1。
本研究首先在华西健康增龄队列中选取了25个肌肉骨骼相关指标,包括影像学、功能学和血液生化、激素等指标,采用机器学习方法构建了一个性别特异的多模态肌骨衰老时钟,并在独立的华西骨健康队列及苏州骨质疏松症预防项目(osteoporosis preventive project,OPP)[10]中进行了验证。最终男性与女性的肌骨衰老时钟模型分别包含14项和9项指标,包括双能X射线吸收法测定的股骨颈骨密度、腰椎骨密度、握力、6 m步行时间、体重、身高、腰围、臀围、上臂围、小腿围、上臂肌围、去脂体重、骨骼肌质量、骨骼肌指数、骨矿物质含量。通过该肌骨衰老时钟计算的肌骨生物年龄对常见的衰老相关肌肉骨骼疾病都有更强的诊断能力,比实际年龄更能反映个体肌肉骨骼系统的实际衰老状态。肌骨生物年龄加速计算为实际年龄回归肌骨生物年龄的残差,可用于衡量个体肌肉骨骼系统的老化速度。
协变量的选择基于可能影响膳食行为的常规因素以及潜在混杂因素:人口统计学因素(年龄、性别、受教育水平、个人可支配收入、婚姻状况)、身体测量指标[身体质量指数(body mass index,BMI),kg/m2]、健康相关行为(吸烟史、体力活动、钙、维生素D、复合维生素等补充剂的使用)、慢性疾病(高血压、糖尿病)、骨质疏松或脆性骨折家族史及数据来源。
使用Shapiro-Wilk检验评估连续变量的正态性,对于不符合正态分布的连续变量以中位数(四分位数间距)表示,使用Kruskal-Wallis秩和检验评估组间差异;分类变量以频数(百分比)描述,使用χ2检验评估组间差异。连续变量缺失值采用中位数填补,分类变量缺失值则处理成单独的一类(不清楚)。统计分析前,对连续变量(CHEI总分、年龄、BMI)进行Z-score标准化(均值为0,标准差为1)。
采用Spearman相关分析CHEI及其各组分与肌骨生物年龄加速的关联。采用多元线性回归模型逐步控制混杂因素,以分析CHEI总分对肌骨生物年龄加速的独立效应。模型1调整年龄、性别、最高教育学历、个人可支配收入、婚姻状况、骨质疏松及脆性骨折家族史、数据来源;模型2在模型1基础上进一步调整吸烟史、BMI、体力活动、钙补充剂、维生素D补充剂、复合维生素补充剂使用情况;模型3在模型2基础上进一步调整糖尿病、高血压患病情况。为探索人群特征对CHEI总分与肌骨生物年龄加速之间关系的潜在影响,按年龄、性别、BMI、吸烟史、体力活动、糖尿病、高血压患病状况进行亚组分析。交互作用检验采用乘法交互项法进行评估,即在模型中分别引入CHEI总分与分组变量的乘积项,并对交互项系数进行Wald检验以判断统计学显著性。采用R软件(4.4.2版)进行数据处理和统计分析,显著性水平设为双侧检验,检验水准α=0.05。
研究最终纳入3 765名中老年人,年龄中位数为66.0(61.0,70.0)岁,女性占比67.4%。其中肌骨生物年龄加速>0和<0分为肌骨生物年龄加速组和非加速组,分别为1 946(51.7%)和1 819人(48.3%)。与肌骨生物年龄非加速组相比,加速组人群年龄更小,男性、低学历、已婚、现在吸烟及低体力活动的比例更高,两组上述差异具有统计学意义(P<0.05),见表2。为评估选择偏倚,本研究进一步比较了纳入研究对象(n=3 765)与排除研究对象(n=8 379)的基本特征。结果显示,纳入人群的年龄更小,女性、高学历、已婚、从不吸烟的比例更高,BMI及高血压、糖尿病的患病率更低,差异均具有统计学意义(P<0.05)。
Spearman相关性分析结果显示,CHEI总分与肌骨生物年龄加速呈负相关,其中全谷物、蔬菜、深色蔬菜、水果、水产类、坚果类均与肌骨生物年龄加速呈负相关;谷物与肌骨生物年龄加速呈正相关。结果见表3。
F检验结果显示,3个模型均具有统计学意义(以模型3为例:F=26.969,P<0.001)。模型调整R2为0.157,表明该模型中自变量能够解释因变量中约15.7%的变异。此外,所有模型中方差膨胀因子均小于5,不存在严重的共线性,结果较为可靠。在调整所有上述协变量后,结果显示CHEI总分每增加1个标准差,肌骨生物年龄加速值降低0.10岁。与CHEI得分最低四分位数组相比,CHEI得分最高四分位数组降低肌骨生物年龄加速值的效应更强(P趋势=0.003),见表4。敏感性分析表明,剔除协变量缺失的个体后,上述关联保持稳健。
按年龄、性别、BMI、吸烟史、体力活动强度、糖尿病及高血压患病状况进行亚组分析,调整协变量与模型3相同。CHEI与肌骨生物年龄加速的负相关在不同亚组中总体保持一致,尽管某些亚组中未达到统计学显著性,见表5。交互作用检验显示,CHEI对肌骨生物年龄加速的影响在男性、BMI>24 kg/m2、从不吸烟者中更强(P交互作用均<0.05)。
本研究基于中国西南地区中老年人群,探讨了CHEI及其各组分与肌骨生物年龄加速之间的关联。主要发现如下:(1)遵循中国居民膳食指南的饮食模式(即较高的CHEI总分)与更慢的肌骨生物衰老相关,其中全谷物、蔬菜(特别是深色蔬菜)、水果、水产品及坚果的充足摄入是构成这一保护作用的关键组分;(2)上述关联存在人群异质性,CHEI的保护作用在男性、超重/肥胖(BMI>24 kg/m2)及从不吸烟者中更为显著。
仅关注单一食物成分可能难以全面捕捉整体饮食模式对健康的更广泛益处,因为多种食物成分往往共同摄入且相互关联[11]。因此,本研究聚焦于基于中国人群膳食特点构建的综合健康饮食指数CHEI,并发现其与肌骨生物年龄加速存在稳健的负相关。这一发现与地中海饮食、得舒饮食等国际公认的膳食模式在促进健康衰老、降低肌骨疾病风险方面的证据相一致[12-14]。与地中海饮食类似,高CHEI饮食模式也强调全谷物、蔬菜(尤其是深色蔬菜)、水果、水产品、奶类、豆类和坚果等食物组的充足摄入。这些食物组富含优质蛋白、钙、镁、维生素D、维生素K等与肌肉骨骼健康密切相关的营养素,为骨骼与肌肉的合成与维持提供重要营养支撑[15-18]。
尽管CHEI总分呈现保护效应,但各食物组分与肌骨生物年龄加速的关联存在一定差异。值得注意的是,谷物组分显示出微弱的正相关。这可能主要反映了当前我国居民以精制谷物为主的摄入模式,全谷物、杂豆及薯类的摄入仍普遍偏低[19]。精制谷物加工过程中损失了麸皮和胚芽中富含的膳食纤维、B族维生素、矿物质及植物化学物[20],且升糖指数较高,长期过量摄入可能促进慢性低度炎症和氧化应激[21]。因此,鼓励以全谷物替代部分精制谷物摄入对我国中老年人肌骨健康至关重要。此外,奶类作为钙与维生素D的良好来源[22],在本研究中并未显示出与肌骨衰老加速的关联,这可能与本研究中老年人群奶类摄入量普遍较低有关,难以检测到与结局的真实关联。在实际膳食指导中,仍应强调中老年人摄入足量乳制品以维持肌骨健康。
亚组分析进一步揭示了膳食效应的人群异质性。男性因肌肉与骨量基数较大,可能对营养干预产生更为显著的绝对反应;而在女性中,健康膳食带来的潜在收益可能尚不足以完全抵消因雌激素水平变化而加剧的肌骨生物衰老进程[23]。超重/肥胖人群则可能通过改善代谢状态、减轻系统性炎症而增强饮食的抗衰老作用。吸烟作为一种强烈的外源性氧化应激源[24],可能掩盖或削弱膳食抗氧化成分的保护效应,这进一步凸显了全面健康生活方式的重要性。上述发现提示,未来在制定膳食干预策略时,应充分考虑不同人群的特征,以制定更具针对性的措施,从而最大化干预效果。
本研究的优势在于首次采用符合国家膳食指南的饮食质量评价指标CHEI,从生物年龄的维度探讨其对肌骨生物衰老的影响,为膳食干预延缓肌骨衰老提供了基于中国人群的见解。然而,研究还存在一些局限性。第一,横断面设计无法推断因果关系。第二,膳食数据基于参与者回顾,存在一定的回忆偏倚。同时,简化FFQ仅25个食物组条目,份量估算存在主观差异,可能存在测量误差。此外,受数据可及性限制,CHEI评分未能纳入食用油、添加糖和钠的评估。第三,尽管本研究已尽可能控制潜在的混杂因素,但仍可能存在未测量混杂。第四,本研究还存在一定的选择偏倚,纳入人群相较于基线总人群更年轻,有更优势的社会人口学特征及更健康的生活方式和身体状况,通常也伴随着更高的膳食质量,可能导致CHEI与肌骨生物年龄加速的关联强度被低估,外推需谨慎。未来研究可采用纵向设计,在更具代表性的人群中验证本研究的发现,并进一步完善对食用油、添加糖和钠等膳食组分的评估,为肌肉骨骼健康的预防与干预提供更全面的证据支持。
中老年人群中,遵循中国居民膳食指南的健康饮食模式,特别是保证充足的全谷物、深色蔬菜、水果、水产品、坚果摄入,有助于延缓肌肉骨骼系统的生物衰老,尤其对男性、超重/肥胖及不吸烟者更有益。建议进一步推广中国居民膳食指南,加强居民营养教育,并结合其他健康生活方式干预,共同助力健康老龄化。
  • 国家重点研发计划(2023YFC3606300)
  • 四川省科技厅自然科学基金创新研究群体(2024NSFTD0030)
  • 四川大学华西公共卫生学院(华西第四医院)实验学科振兴计划(2023SY-03)
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doi: 10.20043/j.cnki.MPM.202603128
  • 接收时间:2026-03-10
  • 首发时间:2026-09-28
  • 出版时间:2026-08-10
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  • 收稿日期:2026-03-10
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国家重点研发计划(2023YFC3606300)
四川省科技厅自然科学基金创新研究群体(2024NSFTD0030)
四川大学华西公共卫生学院(华西第四医院)实验学科振兴计划(2023SY-03)
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    1.四川大学华西公共卫生学院/华西第四医院,四川 成都 610041
    2.四川大学华西医院临床营养科

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2种不同金属材料的力学参数
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genus
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species
占总种数比例
Percentage of
total species (%)
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species
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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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