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Article(id=1241319151772430741, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410450, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730131200000, receivedDateStr=2024-10-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773883148377, onlineDateStr=2026-03-19, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773883148377, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773883148377, creator=13701087609, updateTime=1773883148377, updator=13701087609, issue=Issue{id=1241319148798669160, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='12', pageStart='2113', pageEnd='2304', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773883147667, creator=13701087609, updateTime=1773885555254, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241329247004971040, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241329247004971041, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241319148798669160, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2186, endPage=2192, ext={EN=ArticleExt(id=1241319154708443608, articleId=1241319151772430741, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between dietary quality and depression: a cross-sectional analysis of NHANES, 2007-2020, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyzing the relationship between dietary quality and depression.

Methods

Data from seven consecutive cycles of NHANES dietary data from 2007-2020. Using HEI-2015, AEHI, MDS, PDI, hPDI, uPDI and CDAI to evaluate dietary quality; analyzing the relationship between various dietary indices and depression through multivariate weighted logistic regression, and through Restricted Cubic Spline (RCS) analyzes the nonlinear relationship between dietary indices and depression, and conducts sensitivity analysis to ensure the stability of the results.

Results

A total of 18 490 study participants were included, with a weighted mean age of 46.39±16.38 years. logistic regression results showed that the risk of depression was reduced in the HEI Q4 group compared with the HEI Q1 group (OR=0.786; 95% CI: 0.664-0.929), and in the PDI Q2 group compared with the PDI Q1 group (OR=0.847; 95% CI: 0.750-0.955). no nonlinear relationship was found between HEI, AHEI, MDS, PDI, hPDI and depression, and a nonlinear relationship was shown between uPDI, CDAI and depression.

Conclusion

The quality of meals has a significant impact on the occurrence of depression. Promote high-quality meals and increase the antioxidant capacity of food, which helps to prevent and slow down the occurrence and development of depression.

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目的

分析膳食质量与抑郁症的关系。

方法

数据来自NHANES 2007—2020年连续七个周期的膳食数据。利用HEI-2015、AEHI、MDS、PDI、hPDI、uPDI和CDAI评估膳食质量；通过多元加权logistic回归分析各类膳食指数与抑郁的关联，选择限制性立方样条分析各膳食指数与抑郁症之间的非线性关系，进行敏感性分析以确保结果的稳定性。

结果

共纳入18 490名研究对象，加权平均年龄为46.39±16.38岁。logistic回归结果显示，与HEI Q1组相比，HEI Q4组抑郁风险降低（OR=0.786；95% CI：0.664~0.929）；与PDI Q1组相比，PDI Q2组抑郁风险降低（OR=0.847；95% CI：0.750~0.955）。HEI、AHEI、MDS、PDI、hPDI与抑郁之间未发现存在非线性关系，uPDI、CDAI与抑郁之间呈现出非线性关系。

结论

膳食质量对抑郁症的发生有着显著影响。促进高质量膳食，增加食物的抗氧化能力，有助于预防和减缓抑郁症发生和发展。

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刘勇，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=9vq9rHNylOTAsP71VB3TgA==, magXml=gNEwCFReRy9/0GsxWz+mCQ==, pdfUrl=null, pdf=fYeuIxkVgi7quErqQdBibQ==, pdfFileSize=1243265, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=gfDUdzx67PDjsxylxm3nAA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=c4+c1wDrhOtfZLU6nfNpaA==, mapNumber=null, authorCompany=null, fund=null, authors=

罗龙鹏（2000—），男，硕士在读，研究方向：流行病和卫生统计

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BMC Public Health, 2022, 22(1): 1513., articleTitle=The association between dietary inflammatory index, dietary antioxidant index, and mental health in adolescent girls: an analytical study, refAbstract=null)], funds=[Fund(id=1241319168155381868, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, awardId=2023CX104, language=CN, fundingSource=南昌大学大学生创新项目(2023CX104), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241319160668549938, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, xref=null, ext=[AuthorCompanyExt(id=1241319160676938547, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, companyId=1241319160668549938, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Nanchang University, Jiangxi Key Laboratory of Preventive Medicine, Nanchang, Jiangxi 330000, China), AuthorCompanyExt(id=1241319160685327156, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, companyId=1241319160668549938, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=南昌大学公共卫生学院，江西省预防医学重点实验室，江西 南昌 330000)])], figs=[ArticleFig(id=1241319165022236686, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Fig.1, caption=Correlation of seven dietary indices, figureFileSmall=kP830AbmmNANLaLc+XJSig==, figureFileBig=gfDUdzx67PDjsxylxm3nAA==, tableContent=null), ArticleFig(id=1241319166527991829, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=图1, caption=七个膳食指数的相关性, figureFileSmall=kP830AbmmNANLaLc+XJSig==, figureFileBig=gfDUdzx67PDjsxylxm3nAA==, tableContent=null), ArticleFig(id=1241319166934839334, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Fig.2, caption=Subgroup analysis of HEI versus depression, figureFileSmall=y9DAIAuk16axK/+WzWAoHQ==, figureFileBig=gc5Msb0XAiNrJB9/TR4hKQ==, tableContent=null), ArticleFig(id=1241319167052279855, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=图2, caption=HEI与抑郁的亚组分析, figureFileSmall=y9DAIAuk16axK/+WzWAoHQ==, figureFileBig=gc5Msb0XAiNrJB9/TR4hKQ==, tableContent=null), ArticleFig(id=1241319167173914675, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Fig.3, caption=RCS curves between dietary index and depression, figureFileSmall=iQ0J1Z2x3EBotmRiVPbvxA==, figureFileBig=+aDKWvcrd3o/LwNqAy/MSQ==, tableContent=null), ArticleFig(id=1241319167295549498, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=图3, caption=各膳食指数与抑郁症之间的RCS曲线, figureFileSmall=iQ0J1Z2x3EBotmRiVPbvxA==, figureFileBig=+aDKWvcrd3o/LwNqAy/MSQ==, tableContent=null), ArticleFig(id=1241319167400407102, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Fig.4, caption=Ranking of the importance of each study variable, figureFileSmall=rJUqZa6zltEWtzXnDyvv2Q==, figureFileBig=+97FRFYlZnngt4QsEXi9pA==, tableContent=null), ArticleFig(id=1241319167563984968, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=图4, caption=各研究变量的重要性排序, figureFileSmall=rJUqZa6zltEWtzXnDyvv2Q==, figureFileBig=+97FRFYlZnngt4QsEXi9pA==, tableContent=null), ArticleFig(id=1241319167689814094, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Table 1, caption=

General condition of the study population

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总数非抑郁抑郁t/χ2P
性别[n(%)]1 525 232<0.001
男9 643(52.15)7 712(53.73)1 931(41.01)
女8 847(47.85)6 157(46.27)2 690(58.99)
年龄()46.39±16.3846.69±16.4945.40±15.975.553<0.001
种族[n(%)]263 731<0.001
非西班牙裔白人8 940(48.35)6 783(74.75)2 157(70.54)
非西班牙裔黑人4 135(22.36)3 043(9.44)1 092(11.86)
墨西哥裔美国人2 708(14.65)2 053(7.99)655(9.34)
其他种族2 707(14.64)1 990(7.81)717(8.27)
教育程度[n(%)]1 484 931<0.001
高中以下3 424(18.52)2 328(10.16)1 096(15.84)
高中4 297(23.24)3 099(21.28)1 198(27.07)
大专及以上10 769(58.24)8 442(68.56)2 327(57.09)
婚姻状况[n(%)]2 066 444<0.001
从未结婚3 602(19.48)2 543(17.70)1 059(21.68)
已婚或与伴侣同居11 006(59.52)8 732(67.08)2 274(53.67)
离婚或丧偶或分居3 882(21.00)2 594(15.22)1 288(24.65)
家庭收入水平[n(%)]4 679 950<0.001
低水平5 161(27.91)3 299(14.69)1 862(28.94)
中等水平6 907(37.36)5 167(32.61)1 740(37.73)
高水平6 422(34.73)5 403(52.70)1 019(33.33)
BMI[n(%)]882 744<0.001
<25 kg/m24 943(26.73)3 815(29.32)1 128(26.24)
25~30 kg/m26 492(35.11)5 174(35.05)1 318(28.86)
>30 kg/m27 055(38.16)4 880(35.63)2 175(44.90)
吸烟状况[n(%)]3087 340<0.001
不吸烟12 463(67.64)9 823(73.95)2 640(57.96)
环境暴露804(4.35)582(3.61)222(3.92)
吸烟5 223(28.25)3 464(22.44)1 759(38.12)
饮酒状况[n(%)]927 365<0.001
轻度8 471(45.81)6 117(39.94)2 354(47.85)
中度6 872(37.17)5 455(42.16)1 417(32.60)
重度3 147(17.02)2 297(17.90)850(19.54）
HEI-2015()50.56±13.7851.30±13.8248.10±13.3512.786<0.001
AHEI()39.65±13.6040.39±13.6837.16±13.0213.901<0.001
MDS()3.49±1.683.58±1.683.16±1.6113.471<0.001
PDI()33.85±6.5734.04±6.5733.25±6.525.329<0.001
hPDI()37.23±7.3837.38±7.4436.70±7.154.794<0.001
uPD()40.56±6.7240.19±6.6941.81±6.68-13.910<0.001
CDAI()0.37±3.950.50±3.99-0.08±3.757.909<0.001
), ArticleFig(id=1241319167794671701, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=表1, caption=

研究人群的一般情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总数非抑郁抑郁t/χ2P
性别[n(%)]1 525 232<0.001
男9 643(52.15)7 712(53.73)1 931(41.01)
女8 847(47.85)6 157(46.27)2 690(58.99)
年龄()46.39±16.3846.69±16.4945.40±15.975.553<0.001
种族[n(%)]263 731<0.001
非西班牙裔白人8 940(48.35)6 783(74.75)2 157(70.54)
非西班牙裔黑人4 135(22.36)3 043(9.44)1 092(11.86)
墨西哥裔美国人2 708(14.65)2 053(7.99)655(9.34)
其他种族2 707(14.64)1 990(7.81)717(8.27)
教育程度[n(%)]1 484 931<0.001
高中以下3 424(18.52)2 328(10.16)1 096(15.84)
高中4 297(23.24)3 099(21.28)1 198(27.07)
大专及以上10 769(58.24)8 442(68.56)2 327(57.09)
婚姻状况[n(%)]2 066 444<0.001
从未结婚3 602(19.48)2 543(17.70)1 059(21.68)
已婚或与伴侣同居11 006(59.52)8 732(67.08)2 274(53.67)
离婚或丧偶或分居3 882(21.00)2 594(15.22)1 288(24.65)
家庭收入水平[n(%)]4 679 950<0.001
低水平5 161(27.91)3 299(14.69)1 862(28.94)
中等水平6 907(37.36)5 167(32.61)1 740(37.73)
高水平6 422(34.73)5 403(52.70)1 019(33.33)
BMI[n(%)]882 744<0.001
<25 kg/m24 943(26.73)3 815(29.32)1 128(26.24)
25~30 kg/m26 492(35.11)5 174(35.05)1 318(28.86)
>30 kg/m27 055(38.16)4 880(35.63)2 175(44.90)
吸烟状况[n(%)]3087 340<0.001
不吸烟12 463(67.64)9 823(73.95)2 640(57.96)
环境暴露804(4.35)582(3.61)222(3.92)
吸烟5 223(28.25)3 464(22.44)1 759(38.12)
饮酒状况[n(%)]927 365<0.001
轻度8 471(45.81)6 117(39.94)2 354(47.85)
中度6 872(37.17)5 455(42.16)1 417(32.60)
重度3 147(17.02)2 297(17.90)850(19.54）
HEI-2015()50.56±13.7851.30±13.8248.10±13.3512.786<0.001
AHEI()39.65±13.6040.39±13.6837.16±13.0213.901<0.001
MDS()3.49±1.683.58±1.683.16±1.6113.471<0.001
PDI()33.85±6.5734.04±6.5733.25±6.525.329<0.001
hPDI()37.23±7.3837.38±7.4436.70±7.154.794<0.001
uPD()40.56±6.7240.19±6.6941.81±6.68-13.910<0.001
CDAI()0.37±3.950.50±3.99-0.08±3.757.909<0.001
), ArticleFig(id=1241319167916306525, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=EN, label=Table 2, caption=

Weighted logistic regression results of dietary indicators and depression

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1
OR(95% CI)		模型2
OR(95% CI)		模型3
OR(95% CI)
HEI-2015(ref，Q1)
Q20.905(0.777~1.054)0.925(0.786~1.088)0.920(0.782~1.081)
Q30.918(0.807~1.045)0.902(0.784~1.036)0.905(0.788~1.039)
Q40.773(0.660~0.906)0.773(0.654~0.906)0.786(0.664~0.929)
AHEI(ref，Q1)
Q20.956(0.833~1.097)0.965(0.835~1.115)1.005(0.864~1.168)
Q30.974(0.838~1.133)0.995(0.851~1.163)1.060(0.904~1.243)
Q40.855(0.718~1.017)0.896(0.747~1.074)0.976(0.808~1.180)
MDS(ref，Q1)
Q20.876(0.757~1.014)0.874(0.752~1.017)0.906(0.781~1.052)
Q30.845(0.725~0.983)0.856(0.735~0.999)0.901(0.775~1.047)
Q40.771(0.583~1.020)0.795(0.606~1.044)0.863(0.655~1.138)
PDI(ref，Q1)
Q20.863(0.763~0.977)0.855(0.756~0.966)0.847(0.750~0.955)
Q30.915(0.791~1.060)0.955(0.817~1.117)0.946(0.808~1.109)
Q40.911(0.779~1.066)0.970(0.819~1.150)0.949(0.801~1.126)
hPDI(ref，Q1)
Q21.003(0.878~1.147)1.037(0.902~1.191)1.036(0.904~1.187)
Q31.110(0.988~1.247)1.144(1.012~1.294)1.127(0.997~1.275)
Q41.090(0.938~1.265)1.118(0.952~1.311)1.093(0.934~1.280)
uPDI(ref，Q1)
Q21.103(0.934~1.303)1.054(0.893~1.244)1.067(0.901~1.263)
Q31.135(0.942~1.366)0.999(0.822~1.213)1.013(0.835~1.229)
Q41.334(1.114~1.596)1.101(0.916~1.324)1.126(0.938~1.350)
CDAI(ref，Q1)
Q20.806(0.714~0.909)0.876(0.774~0.992)0.924(0.815~1.048)
Q30.729(0.627~0.849)0.849(0.726~0.994)0.885(0.757~1.042)
Q40.805(0.680~0.952)1.000(0.995~1.001)1.054(0.889~1.248)
), ArticleFig(id=1241319168008581217, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241319151772430741, language=CN, label=表2, caption=

各膳食指标与抑郁的加权logistic回归结果

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变量模型1
OR(95% CI)		模型2
OR(95% CI)		模型3
OR(95% CI)
HEI-2015(ref，Q1)
Q20.905(0.777~1.054)0.925(0.786~1.088)0.920(0.782~1.081)
Q30.918(0.807~1.045)0.902(0.784~1.036)0.905(0.788~1.039)
Q40.773(0.660~0.906)0.773(0.654~0.906)0.786(0.664~0.929)
AHEI(ref，Q1)
Q20.956(0.833~1.097)0.965(0.835~1.115)1.005(0.864~1.168)
Q30.974(0.838~1.133)0.995(0.851~1.163)1.060(0.904~1.243)
Q40.855(0.718~1.017)0.896(0.747~1.074)0.976(0.808~1.180)
MDS(ref，Q1)
Q20.876(0.757~1.014)0.874(0.752~1.017)0.906(0.781~1.052)
Q30.845(0.725~0.983)0.856(0.735~0.999)0.901(0.775~1.047)
Q40.771(0.583~1.020)0.795(0.606~1.044)0.863(0.655~1.138)
PDI(ref，Q1)
Q20.863(0.763~0.977)0.855(0.756~0.966)0.847(0.750~0.955)
Q30.915(0.791~1.060)0.955(0.817~1.117)0.946(0.808~1.109)
Q40.911(0.779~1.066)0.970(0.819~1.150)0.949(0.801~1.126)
hPDI(ref，Q1)
Q21.003(0.878~1.147)1.037(0.902~1.191)1.036(0.904~1.187)
Q31.110(0.988~1.247)1.144(1.012~1.294)1.127(0.997~1.275)
Q41.090(0.938~1.265)1.118(0.952~1.311)1.093(0.934~1.280)
uPDI(ref，Q1)
Q21.103(0.934~1.303)1.054(0.893~1.244)1.067(0.901~1.263)
Q31.135(0.942~1.366)0.999(0.822~1.213)1.013(0.835~1.229)
Q41.334(1.114~1.596)1.101(0.916~1.324)1.126(0.938~1.350)
CDAI(ref，Q1)
Q20.806(0.714~0.909)0.876(0.774~0.992)0.924(0.815~1.048)
Q30.729(0.627~0.849)0.849(0.726~0.994)0.885(0.757~1.042)
Q40.805(0.680~0.952)1.000(0.995~1.001)1.054(0.889~1.248)
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膳食质量与抑郁症的关联：NHANES 2007—2020的横断面分析
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罗龙鹏 , 聂艳武 , 邓紫苏 , 刘勇
现代预防医学 | 营养与食品卫生 2025,52(12): 2186-2192
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现代预防医学 | 营养与食品卫生 2025, 52(12): 2186-2192
膳食质量与抑郁症的关联：NHANES 2007—2020的横断面分析
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罗龙鹏, 聂艳武, 邓紫苏, 刘勇
作者信息
  • 南昌大学公共卫生学院，江西省预防医学重点实验室，江西 南昌 330000

    • 罗龙鹏（2000—），男，硕士在读，研究方向：流行病和卫生统计

通讯作者:

刘勇，E-mail：
Association between dietary quality and depression: a cross-sectional analysis of NHANES, 2007-2020
Long-peng LUO, Yan-wu NIE, Zi-su DENG, Yong LIU
Affiliations
  • School of Public Health, Nanchang University, Jiangxi Key Laboratory of Preventive Medicine, Nanchang, Jiangxi 330000, China
出版时间: 2025-06-25 doi: 10.20043/j.cnki.MPM.202410450
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摘要
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目的

分析膳食质量与抑郁症的关系。

方法

数据来自NHANES 2007—2020年连续七个周期的膳食数据。利用HEI-2015、AEHI、MDS、PDI、hPDI、uPDI和CDAI评估膳食质量；通过多元加权logistic回归分析各类膳食指数与抑郁的关联，选择限制性立方样条分析各膳食指数与抑郁症之间的非线性关系，进行敏感性分析以确保结果的稳定性。

结果

共纳入18 490名研究对象，加权平均年龄为46.39±16.38岁。logistic回归结果显示，与HEI Q1组相比，HEI Q4组抑郁风险降低（OR=0.786；95% CI：0.664~0.929）；与PDI Q1组相比，PDI Q2组抑郁风险降低（OR=0.847；95% CI：0.750~0.955）。HEI、AHEI、MDS、PDI、hPDI与抑郁之间未发现存在非线性关系，uPDI、CDAI与抑郁之间呈现出非线性关系。

结论

膳食质量对抑郁症的发生有着显著影响。促进高质量膳食，增加食物的抗氧化能力，有助于预防和减缓抑郁症发生和发展。

饮食质量  /  抑郁症  /  CDAI  /  NHANES
Objective

To analyzing the relationship between dietary quality and depression.

Methods

Data from seven consecutive cycles of NHANES dietary data from 2007-2020. Using HEI-2015, AEHI, MDS, PDI, hPDI, uPDI and CDAI to evaluate dietary quality; analyzing the relationship between various dietary indices and depression through multivariate weighted logistic regression, and through Restricted Cubic Spline (RCS) analyzes the nonlinear relationship between dietary indices and depression, and conducts sensitivity analysis to ensure the stability of the results.

Results

A total of 18 490 study participants were included, with a weighted mean age of 46.39±16.38 years. logistic regression results showed that the risk of depression was reduced in the HEI Q4 group compared with the HEI Q1 group (OR=0.786; 95% CI: 0.664-0.929), and in the PDI Q2 group compared with the PDI Q1 group (OR=0.847; 95% CI: 0.750-0.955). no nonlinear relationship was found between HEI, AHEI, MDS, PDI, hPDI and depression, and a nonlinear relationship was shown between uPDI, CDAI and depression.

Conclusion

The quality of meals has a significant impact on the occurrence of depression. Promote high-quality meals and increase the antioxidant capacity of food, which helps to prevent and slow down the occurrence and development of depression.

Diet quality  /  Depression  /  CDAI  /  NHANES
罗龙鹏, 聂艳武, 邓紫苏, 刘勇. 膳食质量与抑郁症的关联：NHANES 2007—2020的横断面分析. 现代预防医学, 2025 , 52 (12) : 2186 -2192 . DOI: 10.20043/j.cnki.MPM.202410450
Long-peng LUO, Yan-wu NIE, Zi-su DENG, Yong LIU. Association between dietary quality and depression: a cross-sectional analysis of NHANES, 2007-2020[J]. Modern Preventive Medicine, 2025 , 52 (12) : 2186 -2192 . DOI: 10.20043/j.cnki.MPM.202410450
正文
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1　前言
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随着现代社会的快速发展，人们承受的压力也不断增大，导致心理问题日渐凸显。现如今，抑郁症已成为当今世界最为严峻的公共健康问题之一。WHO 2023年发布的抑郁症实况报道指出，全球估计有3.8%的人口患有抑郁症[1]。据统计，全球有记录的抑郁症患者从1990—2019年增长了0.59%[2]。
近年来，越来越多的研究表明饮食质量与抑郁症发生风险有关。大量研究表明，较高的饮食质量与较低的抑郁症风险相关[3-5]，单独食物组检查显示，较高的蔬菜摄入量与较低的抑郁、焦虑和恐惧严重程度有关[6]。另外，大量研究指出抗氧化饮食是抑郁症的保护因素[7-8]，在一项膳食复合抗氧化指数（CDAI）与中老年人群抑郁关系研究中表明，CDAI与抑郁症呈线性负相关，食物来源的抗氧化物质能降低抑郁症的发病风险[9]。
大多数研究只在单一营养素与抑郁症的关系中进行，缺少从饮食整体的质量层面与抑郁症关系的研究。因此，本研究旨在分析饮食质量与抑郁症的关系，探讨饮食质量对抑郁症发生的影响。
2　方法
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2.1　研究设计和人群
数据来自于2007—2020年七个连续周期的美国国家健康和营养检查调查（NHANES）。NHANES是一项基于访谈和体检，旨在评估美国成人和儿童健康和营养状况的研究计划。其内容主要包括人口统计学资料、膳食数据、检查数据、相关问卷调查，以及由训练有素的医务人员进行的实验室检查[10]。
NHANES使用患者健康问卷（PHQ-9）评估研究对象的抑郁状态。PHQ-9是初级保健中广泛使用的抑郁症诊断和确定抑郁症严重程度的一项诊断工具[11]，共包含9个项目，旨在评估过去两周内的抑郁相关症状，每个项目赋予0~3分（0 =从不，1 =几天，2=超过一半的天数，3 =几乎每天），总分从0~27分，≥5分被认为是患有抑郁症[12]。
研究的纳入标准：（1）具有完整的资料信息；（2）年龄≥20岁。NHANES2007—2020年期间共有66 148名参与者，根据纳排标准，最终本研究共纳入18 490名研究对象。
2.2　膳食质量评估
NHANES膳食数据中提供了研究对象24 h饮食回忆访谈数据，包括食物和营养素的摄入。在访谈开始前，所有访谈员必须完成为期一周的强化培训课程，学习如何进行膳食访谈。同时在独立工作之前，访谈员需要进行监督下的实践访谈，以确保掌握正确的流程和技巧，并且每年进行一次再培训课程，以强化正确的操作规范和技术。此外，针对访谈数据，以电子方式发送并导入美国农业部开发的计算机辅助食品编码和数据管理系统（Survey Net），并利用膳食研究食品与营养素数据库（FNDDS）处理膳食摄入量。编码员需在培训后通过认证测试，在工作时受到例行监控。对摄入量数据进行编码后，食品调查研究组（FSRG）科学家进行各种类型的审查和质量保证程序，以确保数据的质量。
健康饮食指数-2015（HEI-2015）包含13种组分，包括总水果（包括新鲜、冷冻、罐装和干燥水果等所有形式的水果）、全水果（仅包括完整的水果，不包括果汁等加工形式的水果）、总蔬菜（涵盖叶菜类、根茎类、茄果类等各种蔬菜，包括鲜品、冷冻品、罐头等）、绿色蔬菜和豆类（指富含维生素、矿物质和膳食纤维的绿叶蔬菜，如菠菜、生菜等，以及豆类，像黑豆、红豆、绿豆等）、全谷物、乳制品、总蛋白食品、海鲜和植物蛋白、脂肪酸比例、精制谷物、钠、添加糖和饱和脂肪。各组分的评分标准见表S1。总分从0~100分，分数越高表示饮食质量越高。
替代健康饮食指数（AHEI）包含11种组分，包括蔬菜、水果、坚果和豆类、添加糖、全谷物、红肉和加工肉类、多不饱和脂肪酸和单不饱和脂肪酸、反式脂肪酸、omega-3脂肪酸、钠和酒精。各组分评分从0~10分，用于衡量居民饮食是否接近高质量的饮食指南[13]。由于NHANES膳食数据不包含反式脂肪酸，故本研究通过排除反式脂肪酸来构建AHEI评分，总分从0~100分。
地中海饮食评分（MDS）包含10个组分，包括全谷物、豆类、水果和坚果、蔬菜、鱼类、单不饱和脂肪酸与饱和脂肪酸的比例、红肉及其制品、家禽、乳制品、酒类。总分从0~10分，分数越高表示对地中海饮食模式的依从性越好[14]。
植物性饮食指数（PDI）、健康植物性饮食指数（hPDI）和不健康植物性饮食指数（uPDI）通过15种食物组的摄入量进行评分，将食物组分为三类：健康的植物性食物、不健康的植物性食物和动物性食物（表S2）[15]。各食物组的得分相加即为每个指数的总分，从15~75分。
复合膳食抗氧化指数（CDAI）是根据食物来源的六种矿物质和维生素（锌、硒、维生素A、维生素E、维生素C、胡萝卜素）所计算出来的，是用于评估饮食的整体抗氧化特性的一种有效且可靠的工具[16]，其公式如下所示。
其中，I表示营养素的摄入量，s为各摄入量的平均值，s为标准差。
2.3　协变量
研究纳入的协变量包括：（1）人口统计学资料，包括性别、年龄、种族（墨西哥裔美国人、非西班牙裔白人、非西班牙裔黑人、其他种族）、婚姻状况（已婚或与伴侣同居、离婚或丧偶或分居、从未结婚）、教育水平（高中以下、高中、大专及以上）、家庭收入水平（由贫困收入比率（PIR）定义，分为低水平（PIR<1.30）、中等水平（1.30≤PIR<3.50）和高水平（PIR≥3.50）[17]）、BMI（分为<25 kg/m2、25~30 kg/m2和>30 kg/m2)；（2）吸烟状况：根据血清可替宁水平分为三类：①不吸烟（<1.0 ng/ml）；②环境烟草烟雾（ETS）暴露（1.0~9.9 ng/ml）；③吸烟（≥10 ng/ml）；（3）饮酒状况：根据饮酒问卷计算出受试者过去12个月每周平均饮酒量，分为三个等级（轻度：<1杯；中度：1~7杯；重度：≥8杯）[18]，一杯酒被定义为12盎司啤酒、5盎司葡萄酒或1.5盎司烈酒。
2.4　统计分析
由于NHANES涉及多阶段复杂抽样设计，因此在数据分析时纳入了权重。连续变量用加权均值±标准差表示，使用t检验进行比较，分类变量用数量（加权百分比）表示，使用加权卡方检验进行比较。利用Pearson相关系数分析各膳食指数之间的相关性。通过加权logistic回归分析各膳食指数与抑郁间的关联，并根据协变量的调整构建了3个模型。利用限制性立方样条（RCS）评估各膳食指数与抑郁之间的非线性关系，选择随机森林模型评估各研究变量在抑郁中的重要性。所有统计分析均在R（版本4.4.1）中进行，检验水准α=0.05。
3　结果
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3.1　一般情况
共纳入18 490名研究对象，其一般情况见表1。研究人群的加权平均年龄为46.39±16.38岁，与非抑郁组相比，抑郁组女性比例高于男性，年龄、HEI-2015、AHEI、MDS、PDI、hPDI、CDAI较非抑郁组低（P<0.05），uPDI较非抑郁组高（P<0.05）。
3.2　各膳食指数的相关性分析
使用相关性分析评估七个膳食指数间的相关性（图1），各指标间相互关联（P<0.05），uPDI与其他指标之间均呈负相关；CDAI与AHEI、MDS、HEI、PDI之间呈正相关，与hPDI之间呈负相关。
3.3　各膳食质量指数与抑郁症的关系
将各膳食指数按四分位数水平分为4组（Q1、Q2、Q3、Q4），使用多因素加权logistic回归分析，结果如表2所示。HEI Q4组、PDI Q2组在3个模型中均显示出与抑郁风险的统计学差异，在模型3中分别较参考组降低21.4%和15.3%。
3.4　HEI与抑郁之间的亚组分析
选择logistic回归结果较为稳定的HEI进行与抑郁之间的亚组分析，如图2。在所有分组中HEI与抑郁呈现负相关关系，女性人群中HEI与抑郁的相关性具有统计学意义（OR=0.988；95% CI：0.983~0.993）。此外，小于60岁、非西班牙裔白人、大专及以上、离婚或丧偶或分居、轻度饮酒、不吸烟、低收入水平、BMI<25 kg/m2的这些群体可能是一个显著相关人群，易受到HEI的影响，导致抑郁症的发生率降低。另外，在性别和BMI分组中检测到交互作用（P<0.05）。
3.5　各膳食指数与抑郁之间的线性关系
为进一步探索和可视化各膳食指数与抑郁之间的关系，绘制了RCS曲线，并对所有协变量进行了调整，如图3。HEI、AHEI、MDS、PDI、hPDI与抑郁之间未发现非线性关系（P for nonlinear>0.05），uPDI、CDAI与抑郁之间呈现出非线性相关关系（P for nonlinear<0.05），其图形曲线类似于“U”型。
3.6　各研究变量的重要性排序
采用随机森林模型进一步研究各变量在抑郁中的重要性，其结果见图4，性别、HEI的平均准确率减少值（MDA)分别为58.2和50.2，提示性别和HEI在抑郁症中的重要程度较高。
3.7　敏感性分析
敏感性分析将抑郁评分作为连续变量进行未加权的多重线性回归，结果见表S3。在3个模型中，HEI均显示出与抑郁的负相关关系，而uPDI均显示出与抑郁的正相关关系。总体而言，敏感性分析证实了加权logistic回归分析结果的稳定性和可靠性。
4　讨论
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近年来，随着对饮食健康和抑郁症的关注增加，膳食因素与抑郁症的关系逐渐被人们所探讨。一项基于人群的队列研究表明，瑞典中年女性对地中海饮食依从性较高与后期患抑郁症的风险较低有关[19]。另一项关于产后抑郁症的研究中，产后抑郁症的发生与膳食过量和膳食失衡相关[20]。另外，在一项关于膳食模式与中国四省55岁及以上人群抑郁症状的关联性研究中表明，多摄入畜肉、加工肉制品、动物内脏、油炸面食、松花蛋，少摄入杂粮、水果、液态奶/奶粉/奶酪、蛋类(除松花蛋)、坚果的膳食模式，与抑郁症呈正相关[21]。
本研究基于NHANES 2007—2020年调查数据，分别计算了七种膳食指数并分析了各膳食指数与抑郁症之间的关系。结果显示，性别是抑郁症发生的重要影响因素，这与之前的研究中女性群体较男性群体有着更高的抑郁风险相似[22]。同时，相比于较低的收入水平，较高的收入水平显示出对抑郁的保护作用，这在此前的研究中也具有类似结论[23]。此外，研究发现婚姻状况对抑郁症发生有着重要影响，离婚或丧偶或分居这一群体有着较高的抑郁风险，这与其他婚姻状况和抑郁之间的研究结论相一致[24]。
将各膳食指数分为四分位数，加权logistic回归模型结果显示，较高水平的HEI与抑郁风险呈负相关。有研究显示健康的饮食能够降低抑郁症的发生风险[25]，一项病例对照研究结果显示，HEI在减少重度抑郁症方面有着显著关系[26]。此外，较高水平的uPDI与抑郁风险呈正相关，提示不健康的植物性食物会增加抑郁症的发生风险，在一项关于中老年人群植物性饮食的质量以及痴呆和抑郁的风险的前瞻性研究中得到了类似的结果[4]，相关研究指出，对于富含膳食纤维的植物性食物，能够影响肠道菌群的数量和结构，同时肠道菌群的变化与各种神经退行性疾病有关[27]，维持和恢复肠道菌群的正常状态有助于预防和治疗精神障碍[28]，通过使用益生菌、益生元和健康饮食来恢复肠道微生物群和肠脑轴的功能可能会缓解抑郁症状，特别是将其作为抗抑郁药的辅助治疗，可以改善精神障碍[29]。
先前的研究表明，氧化应激（OS）是神经退行性病变的主要原因，其参与重度抑郁症的发生和发展[30]，在抑郁症患者中表现为抗氧化能力减弱，氧化应激升高[31]，同时，OS可能通过导致机体产生线粒体损伤、神经炎症、微生物群-肠-脑轴紊乱等促使抑郁的发生[32]。因此，有许多研究表明CDAI与抑郁之间呈负相关[33-35]。然而，本研究在未控制协变量的logistic回归分析中显示CDAI与较低的抑郁症风险相关，但在进一步调整所有协变量之后，其相关性变得不显著，因此，需进一步探索CDAI与抑郁之间的关系。
然而，本研究也存在诸多局限性，首先，本研究依赖于自我报告的24 h膳食回忆数据和PHQ-9问卷，且只利用了第一天的饮食数据，易产生回忆偏倚；其次，本研究属于横断面研究，只能初步了解饮食质量与抑郁间的相关性，不能进一步对因果关系进行判断；此外，高血压、糖尿病等因素被认为是抑郁症的潜在的危险因素，但本研究未被纳入进行分析；另外，在进行AHEI计算时将反式脂肪酸排除，掩盖了不健康饮食的真实风险，对研究结论产生影响；最后，由于缺少任何变量的数据，47 658名研究对象被排除在外，这可能会影响结果的准确性。
膳食质量对抑郁症的发生有着显著影响。较高水平的HEI能降低抑郁症的发生风险；同时，较高水平的uPDI会增加抑郁症的发生风险。促进高质量膳食，增加食物的抗氧化能力，结合健康的生活方式，可能是预防和减少抑郁症发生和发展的有效方法。
基金
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  • 南昌大学大学生创新项目(2023CX104)
文献
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doi: 10.20043/j.cnki.MPM.202410450
  • 接收时间：2024-10-29
  • 首发时间：2026-03-19
  • 出版时间：2025-06-25
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  • 收稿日期：2024-10-29
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    南昌大学公共卫生学院，江西省预防医学重点实验室，江西 南昌 330000

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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