Article(id=1241329576069100046, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241329570129956900, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202411483, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732550400000, receivedDateStr=2024-11-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773885633723, onlineDateStr=2026-03-19, pubDate=1752076800000, pubDateStr=2025-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773885633723, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773885633723, creator=13701087609, updateTime=1773885633723, updator=13701087609, issue=Issue{id=1241329570129956900, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='13', pageStart='2305', pageEnd='2496', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773885632307, creator=13701087609, updateTime=1773885763730, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241330121425080472, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241329570129956900, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241330121425080473, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241329570129956900, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2385, endPage=2389, ext={EN=ArticleExt(id=1241329576438198811, articleId=1241329576069100046, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between dietary patterns and overweight/obesity among children and adolescents in Hebei Province, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate dietary intake and explore the association between dietary patterns and overweight/obesity among children and adolescents aged 6 to 17 years in Hebei Province, providing evidence for early prevention and control.

Methods

Using multistage stratified random sampling, 3 228 children and adolescents aged 6-17 years from 12 monitoring sites in Hebei Province were selected. Data on basic characteristics, food intake, and physical examination were collected. Factor analysis was used to extract dietary patterns, and unconditional logistic regression was employed to analyze the association between dietary patterns and overweight/obesity risk.

Results

The prevalence of overweight/obesity was 28.78% during 2016 and 2017, with significant differences by gender, region, education level, parental education, and boarding status (all P<0.05). After adjusting for gender, region, and boarding status, the high-carbohydrate dietary pattern was identified as a risk factor for overweight/obesity (P<0.05). The high-protein dietary pattern showed a protective effect, with decreasing risk as factor scores increased (Q2 medium group: OR=0.803, 95%CI: 0.665-0.985, P=0.034; Q3 high group: OR=0.742, 95%CI: 0.584-0.942, P=0.014).

Conclusion

The prevalence of overweight/obesity is high among children and adolescents in Hebei Province. Dietary interventions focusing on increasing protein intake and reducing high-carbohydrate foods may help control overweight/obesity.

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目的

了解河北省6~17岁儿童青少年膳食摄入情况,探讨其膳食模式与超重肥胖之间的关系,为早期预防和控制儿童青少年超重肥胖提供依据。

方法

采用多阶段分层随机抽样方法抽取河北省12个监测点3 228名6~17岁儿童青少年为调查对象,收集其基本情况、各类食物摄入和体格检查等数据。采用因子分析法提取膳食模式,采用非条件logistic回归分析膳食模式和超重肥胖发生风险的关联性。

结果

2016—2017年我省6~17岁儿童青少年超重肥胖率为28.78%,不同性别、地区、学段、父母亲文化程度、是否住校学生的超重肥胖率差异有统计学意义(P均<0.05)。校正性别、地区、是否住校等相关因素后,高碳水化合物膳食模式为超重肥胖的危险因素(P<0.05)。高蛋白膳食模式中,随着因子得分的升高,超重肥胖发生风险降低(Q2中分组OR=0.803,95%CI:0.665~0.985,P=0.034;Q3高分组OR= 0.742,95%CI:0.584~0.942,P=0.014)。

结论

河北省儿童青少年超重肥胖率较高,应通过调整饮食结构,增加膳食中蛋白摄入、减少高碳水摄入来控制超重肥胖的发生。

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刘长青,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=LnpmImlJp+UeaJMXKu2FpA==, magXml=nkk91/DBkkwFXL5sz+nQMA==, pdfUrl=null, pdf=Pk+FrRCa9oBajWvyYCBRgQ==, pdfFileSize=613249, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=t8kyrBFA08T4hCFhWfV8CA==, mapNumber=null, authorCompany=null, fund=null, authors=

罗晓燕(1987—),女,硕士,副主任医师,研究方向:营养与食品卫生

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The impact of ultra-processed foods on health[J] . Journal of Hygiene Research, 2023, 52(5): 769-774.(In Chinese), articleTitle=The impact of ultra-processed foods on health, refAbstract=null)], funds=[Fund(id=1241329754800976674, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, awardId=20190140, language=CN, fundingSource=河北省医学科学研究课题计划资助(20190140), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241329750787027467, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, xref=null, ext=[AuthorCompanyExt(id=1241329750795416076, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, companyId=1241329750787027467, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hebei 050021, China), AuthorCompanyExt(id=1241329750803804684, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, companyId=1241329750787027467, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=河北省疾病预防控制中心,河北 石家庄 050021)])], figs=[ArticleFig(id=1241329754104722141, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=EN, label=Table 1, caption=

General demographic characteristics of study subjects [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数非超重肥胖超重肥胖χ2P
性别14.650<0.001
1 6081 096(68.16)512(31.84)
1 6201 203(74.26)417(25.74)
地区30.641<0.001
城市1 361899(66.05)462(33.95)
农村1 8671 400(74.99)467(25.01)
学段3.9250.048
小学生1 9321 351(69.93)581(30.07)
中学生1 296948(73.15)348(26.85)
父亲文化程度14.044<0.001
高中及以下2 8742 077(72.27)797(27.73)
大专及以上354222(62.71)132(37.29)
母亲文化程度9.9860.002
高中及以下2 8342 045(72.16)789(27.84)
大专及以上394254(64.47)140(35.53)
父母是否外出打工4.2440.236
父母均在外打工242172(71.07)70(28.93)
父亲在外打工639476(74.49)163(25.51)
母亲在外打工4935(71.43)14(28.57)
父母均未在外打工2 2981 616(70.32)682(29.68)
主要照顾人2.0940.553
母亲2 5641 840(71.76)724(28.24)
父亲150101(67.33)49(32.67)
祖父母/外祖父母484337(69.63)147(30.37)
其他3021(70.00)9(30.00)
是否住校34.461<0.001
2 1171 436(67.83)681(32.17)
1 111863(77.68)248(22.32)
人均年收入水平(万元)7.8020.050
<1659494(74.96)165(25.04)
1~<2585404(69.06)181(30.94)
≥2470321(68.30)149(31.70)
不详1 5141 080(71.33)434(28.67)
合计3 2282 299(71.22)929(28.78)
), ArticleFig(id=1241329754205385446, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=CN, label=表1, caption=

调查对象的一般人口学特征[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数非超重肥胖超重肥胖χ2P
性别14.650<0.001
1 6081 096(68.16)512(31.84)
1 6201 203(74.26)417(25.74)
地区30.641<0.001
城市1 361899(66.05)462(33.95)
农村1 8671 400(74.99)467(25.01)
学段3.9250.048
小学生1 9321 351(69.93)581(30.07)
中学生1 296948(73.15)348(26.85)
父亲文化程度14.044<0.001
高中及以下2 8742 077(72.27)797(27.73)
大专及以上354222(62.71)132(37.29)
母亲文化程度9.9860.002
高中及以下2 8342 045(72.16)789(27.84)
大专及以上394254(64.47)140(35.53)
父母是否外出打工4.2440.236
父母均在外打工242172(71.07)70(28.93)
父亲在外打工639476(74.49)163(25.51)
母亲在外打工4935(71.43)14(28.57)
父母均未在外打工2 2981 616(70.32)682(29.68)
主要照顾人2.0940.553
母亲2 5641 840(71.76)724(28.24)
父亲150101(67.33)49(32.67)
祖父母/外祖父母484337(69.63)147(30.37)
其他3021(70.00)9(30.00)
是否住校34.461<0.001
2 1171 436(67.83)681(32.17)
1 111863(77.68)248(22.32)
人均年收入水平(万元)7.8020.050
<1659494(74.96)165(25.04)
1~<2585404(69.06)181(30.94)
≥2470321(68.30)149(31.70)
不详1 5141 080(71.33)434(28.67)
合计3 2282 299(71.22)929(28.78)
), ArticleFig(id=1241329754306048755, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=EN, label=Table 2, caption=

Food factor loadings of dietary patterns

, figureFileSmall=null, figureFileBig=null, tableContent=
食物种类加工食品膳食模式均衡膳食模式高蛋白膳食模式高碳水膳食模式
大米及其制品-0.0260.586-0.047-0.050
小麦及其制品0.108-0.188-0.0830.713
杂粮杂豆类0.0270.0020.0640.739
薯类0.2880.063-0.1030.314
油炸面食0.581-0.110-0.1420.015
坚果大豆0.4180.1750.3130.223
蔬菜-0.0970.441-0.0370.576
菌藻类(蘑菇木耳海带)0.4280.2620.1820.154
水果0.1920.5700.1070.159
牛奶0.2720.5360.137-0.034
猪肉-0.0290.6280.120-0.056
其他畜肉0.0140.0320.8210.009
禽肉0.2130.1290.413-0.066
动物制品0.518-0.0110.1610.105
蛋类0.1030.3550.1810.311
水产类0.1550.0950.752-0.008
小吃蛋糕甜点0.6600.1720.1780.054
饮料0.5400.1230.248-0.145
), ArticleFig(id=1241329754398323453, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=CN, label=表2, caption=

各类膳食模式的食物因子荷载

, figureFileSmall=null, figureFileBig=null, tableContent=
食物种类加工食品膳食模式均衡膳食模式高蛋白膳食模式高碳水膳食模式
大米及其制品-0.0260.586-0.047-0.050
小麦及其制品0.108-0.188-0.0830.713
杂粮杂豆类0.0270.0020.0640.739
薯类0.2880.063-0.1030.314
油炸面食0.581-0.110-0.1420.015
坚果大豆0.4180.1750.3130.223
蔬菜-0.0970.441-0.0370.576
菌藻类(蘑菇木耳海带)0.4280.2620.1820.154
水果0.1920.5700.1070.159
牛奶0.2720.5360.137-0.034
猪肉-0.0290.6280.120-0.056
其他畜肉0.0140.0320.8210.009
禽肉0.2130.1290.413-0.066
动物制品0.518-0.0110.1610.105
蛋类0.1030.3550.1810.311
水产类0.1550.0950.752-0.008
小吃蛋糕甜点0.6600.1720.1780.054
饮料0.5400.1230.248-0.145
), ArticleFig(id=1241329754519958277, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=EN, label=Table 3, caption=

Multivariate Logistic regression analysis of the relationship between dietary patterns and overweight/obesity among children and adolescents

, figureFileSmall=null, figureFileBig=null, tableContent=
膳食模式组别模型1a模型2b
OR(95%CI)值POR(95%CI)值P
加工食品膳食模式Q111
Q20.951(0.788~1.147)0.5991.062(0.868~1.300)0.559
Q30.922(0.764~1.111)0.3911.048(0.837~1.311)0.684
均衡膳食模式Q111
Q20.946(0.784~1.142)0.5640.989(0.811~1.205)0.912
Q30.854(0.708~1.029)0.0960.867(0.700~1.073)0.189
高蛋白膳食模式Q111
Q20.762(0.629~0.923)0.0060.803(0.655~0.985)0.034
Q30.638(0.528~0.771)<0.0010.742(0.584~0.942)0.014
高碳水膳食模式Q111
Q21.158(0.964~1.391)0.1161.148(0.945~1.395)0.165
Q31.437(1.119~1.735)<0.0011.494(1.200~1.859)<0.001
), ArticleFig(id=1241329754603844365, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241329576069100046, language=CN, label=表3, caption=

儿童青少年膳食模式和超重肥胖关系的多因素logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
膳食模式组别模型1a模型2b
OR(95%CI)值POR(95%CI)值P
加工食品膳食模式Q111
Q20.951(0.788~1.147)0.5991.062(0.868~1.300)0.559
Q30.922(0.764~1.111)0.3911.048(0.837~1.311)0.684
均衡膳食模式Q111
Q20.946(0.784~1.142)0.5640.989(0.811~1.205)0.912
Q30.854(0.708~1.029)0.0960.867(0.700~1.073)0.189
高蛋白膳食模式Q111
Q20.762(0.629~0.923)0.0060.803(0.655~0.985)0.034
Q30.638(0.528~0.771)<0.0010.742(0.584~0.942)0.014
高碳水膳食模式Q111
Q21.158(0.964~1.391)0.1161.148(0.945~1.395)0.165
Q31.437(1.119~1.735)<0.0011.494(1.200~1.859)<0.001
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河北省儿童青少年膳食模式与超重肥胖的关系研究
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罗晓燕 , 乔晓芳 , 苗润晓 , 田美娜 , 周雨天 , 周园园 , 刘长青
现代预防医学 | 营养与食品卫生 2025,52(13): 2385-2389
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现代预防医学 | 营养与食品卫生 2025, 52(13): 2385-2389
河北省儿童青少年膳食模式与超重肥胖的关系研究
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罗晓燕, 乔晓芳, 苗润晓, 田美娜, 周雨天, 周园园, 刘长青
作者信息
  • 河北省疾病预防控制中心,河北 石家庄 050021
  • 罗晓燕(1987—),女,硕士,副主任医师,研究方向:营养与食品卫生

通讯作者:

刘长青,E-mail:
Association between dietary patterns and overweight/obesity among children and adolescents in Hebei Province
Xiao-yan LUO, Xiao-fang QIAO, Run-xiao MIAO, Mei-na TIAN, Yu-tian ZHOU, Yuan-yuan ZHOU, Chang-qing LIU
Affiliations
  • Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hebei 050021, China
出版时间: 2025-07-10 doi: 10.20043/j.cnki.MPM.202411483
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目的

了解河北省6~17岁儿童青少年膳食摄入情况,探讨其膳食模式与超重肥胖之间的关系,为早期预防和控制儿童青少年超重肥胖提供依据。

方法

采用多阶段分层随机抽样方法抽取河北省12个监测点3 228名6~17岁儿童青少年为调查对象,收集其基本情况、各类食物摄入和体格检查等数据。采用因子分析法提取膳食模式,采用非条件logistic回归分析膳食模式和超重肥胖发生风险的关联性。

结果

2016—2017年我省6~17岁儿童青少年超重肥胖率为28.78%,不同性别、地区、学段、父母亲文化程度、是否住校学生的超重肥胖率差异有统计学意义(P均<0.05)。校正性别、地区、是否住校等相关因素后,高碳水化合物膳食模式为超重肥胖的危险因素(P<0.05)。高蛋白膳食模式中,随着因子得分的升高,超重肥胖发生风险降低(Q2中分组OR=0.803,95%CI:0.665~0.985,P=0.034;Q3高分组OR= 0.742,95%CI:0.584~0.942,P=0.014)。

结论

河北省儿童青少年超重肥胖率较高,应通过调整饮食结构,增加膳食中蛋白摄入、减少高碳水摄入来控制超重肥胖的发生。

超重  /  肥胖  /  膳食模式  /  因子分析
Objective

To investigate dietary intake and explore the association between dietary patterns and overweight/obesity among children and adolescents aged 6 to 17 years in Hebei Province, providing evidence for early prevention and control.

Methods

Using multistage stratified random sampling, 3 228 children and adolescents aged 6-17 years from 12 monitoring sites in Hebei Province were selected. Data on basic characteristics, food intake, and physical examination were collected. Factor analysis was used to extract dietary patterns, and unconditional logistic regression was employed to analyze the association between dietary patterns and overweight/obesity risk.

Results

The prevalence of overweight/obesity was 28.78% during 2016 and 2017, with significant differences by gender, region, education level, parental education, and boarding status (all P<0.05). After adjusting for gender, region, and boarding status, the high-carbohydrate dietary pattern was identified as a risk factor for overweight/obesity (P<0.05). The high-protein dietary pattern showed a protective effect, with decreasing risk as factor scores increased (Q2 medium group: OR=0.803, 95%CI: 0.665-0.985, P=0.034; Q3 high group: OR=0.742, 95%CI: 0.584-0.942, P=0.014).

Conclusion

The prevalence of overweight/obesity is high among children and adolescents in Hebei Province. Dietary interventions focusing on increasing protein intake and reducing high-carbohydrate foods may help control overweight/obesity.

Overweight  /  Obesity  /  Dietary pattern  /  Factor analysis
罗晓燕, 乔晓芳, 苗润晓, 田美娜, 周雨天, 周园园, 刘长青. 河北省儿童青少年膳食模式与超重肥胖的关系研究. 现代预防医学, 2025 , 52 (13) : 2385 -2389 . DOI: 10.20043/j.cnki.MPM.202411483
Xiao-yan LUO, Xiao-fang QIAO, Run-xiao MIAO, Mei-na TIAN, Yu-tian ZHOU, Yuan-yuan ZHOU, Chang-qing LIU. Association between dietary patterns and overweight/obesity among children and adolescents in Hebei Province[J]. Modern Preventive Medicine, 2025 , 52 (13) : 2385 -2389 . DOI: 10.20043/j.cnki.MPM.202411483
近年来,我国儿童青少年超重和肥胖检出率均呈现上升趋势[1]。据《中国居民营养与慢性病状况报告(2020年)》统计,我国6~17岁儿童青少年超重肥胖率为19%[2],已成为危害儿童青少年健康的公共卫生问题。儿童青少年正处于生长发育的关键时期,超重肥胖不仅会影响儿童青少年的正常发育,还会对其心理和生理健康产生负面影响。与此同时,早年建立的饮食习惯往往会持续到成年,并且儿童青少年超重肥胖可能会增加成年后慢性病的发生风险[3-5]。超重肥胖的影响因素多且复杂,其中膳食是关键因素[3]。膳食模式将营养流行病学的重点从单一营养素转向整体饮食,食物不是孤立的营养素而是作为相互作用的营养成分组合被摄入[6]。本研究通过对河北省6~17岁儿童青少年超重肥胖现状及其膳食模式进行分析,探索其膳食模式与超重肥胖的关系,以期从膳食营养的角度为维持儿童青少年健康体重提供科学指导。
数据来源于“2016—2017年中国儿童与乳母营养健康监测”河北省数据。采用多阶段分层随机抽样方法,在河北省抽取12个区(县)监测点开展调查,调查对象为6~17岁儿童青少年。共计发放问卷3 360份,排除缺失及异常数据后,回收有效问卷3 228份,问卷合格率96.07%。经河北省疾病预防控制中心伦理评审委员会审查通过[IRB2016-008,IRB(函)2017-052],6~11岁调查对象由监护人签署知情同意书,12~17岁调查对象由监护人和本人签署知情同意书。
调查问卷包括:(1)基本信息问卷,性别、年龄、家庭收入以及父母外出工作等;(2)食物频率调查问卷,根据饮食习惯将食物分为18类,包括大米及其制品、小麦及其制品、杂粮杂豆类、薯类、油炸面食、坚果大豆、蔬菜类、菌藻类、水果类、乳类、猪肉、其他畜肉、禽肉、动物制品、水产类、蛋类、小吃糕点类和饮料类;(3)体格检查,身高、体重等。
采用统一问卷,在取得儿童青少年或其监护人知情同意后由统一培训并考核合格的调查员进行面对面调查。使用食物频率调查表对调查对象过去一个月膳食情况进行调查。在清晨空腹状态下,由经过统一培训的疾控人员按照《中华人民共和国行业标准人体健康监测人体测量方法(WS/T 424-2013)》的要求进行身高、体重测量,电子体重秤及金属立柱式身高计使用前均按国家计量认证要求进行了校准。
采用体重指数(BMI)判断是否超重或肥胖,参照标准为《学龄儿童青少年超重与肥胖筛查》(WS/T 586-2018)[7]
为保证监测质量,制定统一方案、手册和问卷,统一培训与考核,统一抽样,统一检测仪器与方法,统一数据管理和清洗,以减少系统误差的产生,使数据具有代表性。组建省级质控队伍,对各个监测点抽样和现场调查进行质控和技术指导。
采用因子分析法提取膳食模式,将18类食品摄入频次纳入因子模型,根据KMO检验和Bartlett球形检验结果,判断是否适合进行因子分析,累计方差贡献率>40%确定因子个数,即膳食模式。采用方差最大正交旋转法对因子成分矩阵进行旋转,旋转后的因子载荷>0.3的食品代表各因子的食物类型,并结合专业知识和经验对提取的各类膳食模式进行命名。
采用WPS 2019和R 3.4.1软件进行数据处理和统计学分析。单因素分析采用χ2检验,多因素分析采用非条件logistic回归分析模型分析膳食模式和超重肥胖发生风险的关联性。检验水准α=0.05。
本次共调查3 228人,其中男生1 608人,占49.8%。超重肥胖学生929名,超重肥胖率为28.78%。超重肥胖率男生高于女生(χ2=14.650,P<0.001),城市地区高于农村地区(χ2=30.641,P<0.001),小学生高于中学生(χ2=3.925,P=0.048),父母文化程度为大专及以上高于父母文化程度为高中及以下的学生(χ2=14.044,P<0.001;χ2=9.986,P=0.002),非住校生高于住校生(χ2=34.461,P<0.001)。见表1
因子分析共提取出4个因子(KMO=0.794,Bartlett球形检验P<0.01)。因子1与油炸面食、坚果大豆、菌藻类、动物制品、小吃蛋糕甜点和饮料有关,命名为加工食品膳食模式。因子2与大米及其制品、蔬菜、水果、牛奶、猪肉和蛋类有关,命名为均衡膳食模式。因子3与坚果大豆、其他畜肉、禽肉和水产类有关,命名为高蛋白膳食模式。因子4与小麦及其制品、杂粮杂豆类、蔬菜和蛋类有关,偏素食和主食,命名为高碳水膳食模式。见表2
将膳食模式因子得分进行三等分,分别为Q1,Q2,Q3。结果显示,校正性别、居住地区和学段等相关因素后,与Q1组相比,高碳水膳食模式Q3组超重肥胖可能性更高(OR=1.494,95%CI:1.200~1.859,P<0.001)。高蛋白膳食模式中,随着因子得分的升高超重肥胖风险降低(Q2组OR=0.803,95%CI: 0.665~0.985,P=0.034;Q3组OR=0.742,95%CI: 0.584~0.942,P=0.014)。见表3
随着我国社会经济的快速发展和居民生活水平的提高,儿童青少年超重肥胖问题已成为不容忽视的公共卫生问题。本次调查发现,2016—2017年河北省儿童青少年超重肥胖检出率为28.78%,相对于2010—2012年的19.71%显著升高[8],高于云南省同期6~17岁儿童青少年的14.44%[9],低于河南省同期同年龄段儿童青少年的42.3%[10],与全国2016年中小学生31.4%的超重肥胖率近似[11]。提示河北省儿童青少年超重肥胖问题突出,应采取有效的措施积极干预。
本研究显示,与非超重肥胖组相比,超重肥胖组更可能为男生、居住在城市、处于小学学段、父母文化程度高、非住校人群,与既往研究结果一致[12-14]。现实生活中摄入动物蛋白时常伴随着脂肪的摄入,尤其是高脂肪的猪肉,而牛肉、禽肉和水产类等动物食品蛋白质含量高且脂肪含量较低。我们发现,以坚果大豆、除猪肉外的其他畜肉、禽肉和水产类为主的高蛋白膳食模式为儿童青少年超重肥胖的保护因素。《儿童青少年肥胖食养指南(2024年版)》指出儿童青少年正处于生长发育的重要阶段,应保证保证蛋白质摄入,选择富含优质蛋白质食物[3]。一项针对6~18岁超重肥胖人群的meta分析发现短期高蛋白饮食干预能够改善超重肥胖患儿的体质指数状态[15]。王涛等人[16]通过动物实验表明,在12周膳食干预下,大豆蛋白和猪肉蛋白的高蛋白饮食组均可降低肥胖小鼠体质量、炎症因子,并改变其肠道菌群结构。通过分组喂养小鼠的实验研究也发现高蛋白饮食能够降低体重增长率,显著改善炎症因子,可能与改变肠道菌群结构,增加肠道中微生物群落的丰富性和多样性有关[17]。然而,蛋白质过量对身体也是有危害的,例如会肝肾负担、心血管动脉粥样硬化风险[18]
本研究高碳水膳食模式包含小麦及其制品、杂粮杂豆类、薯类、蔬菜和蛋类,与Q1组的儿童相比,Q3组的儿童超重肥胖的可能性明显更高。张继国等人[19]也发现以小麦、杂粮、薯类为代表的传统北方膳食模式,高分组儿童患肥胖症的可能性会更高,与本研究结果一致。此外一项关于中国成人的研究显示,以小麦及其制品为主食的北方膳食模式中,当碳水化合物摄入量相对较高(占能量的60%)、脂肪摄入量相对较低时(占能量的20%),出现超重/肥胖的风险最高[20]。本研究中蔬菜、蛋类在高碳水和均衡膳食模式中均存在,我们推测高碳水膳食模式对超重肥胖的作用可能受主食类的影响更大。综上,膳食模式优化是管理儿童青少年超重肥胖的关键,我省儿童青少年应注意减少精制碳水摄入、适当增加优质蛋白摄入,同时注意摄入食物的多样性。此外,既往研究显示超加工食品摄入会增加超重肥胖的发生风险[21],本次研究未发现加工膳食模式与超重肥胖相关,原因有待进一步研究。
儿童青少年超重和肥胖的根本原因在于能量摄入大于消耗,各种膳食模式并不都是相互冲突的,调整生活方式如适量增加身体活动时间,结合自己的口味和生活习惯选择合理的均衡膳食模式,在限制总能量摄入的同时保持营养素均衡摄入才能达到健康减重的目的。本研究局限性:膳食数据收集为回顾性,可能存在回忆偏倚;另外,关于膳食模式的研究是横断面的而非膳食模式的长期轨迹分析,因此无法推断因果关系。
  • 河北省医学科学研究课题计划资助(20190140)
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2025年第52卷第13期
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doi: 10.20043/j.cnki.MPM.202411483
  • 接收时间:2024-11-26
  • 首发时间:2026-03-19
  • 出版时间:2025-07-10
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  • 收稿日期:2024-11-26
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河北省医学科学研究课题计划资助(20190140)
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    河北省疾病预防控制中心,河北 石家庄 050021

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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