Article(id=1311350442974602225, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202512373, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1766419200000, receivedDateStr=2025-12-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579909317, onlineDateStr=2026-09-28, pubDate=1786291200000, pubDateStr=2026-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579909317, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579909317, creator=13701087609, updateTime=1790579909317, 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=2752, endPage=2759, ext={EN=ArticleExt(id=1311350443159151602, articleId=1311350442974602225, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Survey and analysis of influencing factors on dietary patterns in ethnic minority concentrated areas of Ali, Tibet in 2021, columnId=1228016572783063333, journalTitle=Modern Preventive Medicine, columnName=Nutrition and Food Hygiene, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the dietary patterns and their influencing factors in Ali area, and to provide reference for the prevention and control of chronic diseases via dietary intervention in underdeveloped high altitude areas.

Methods

A stratified cluster sampling method was used to select 606 adult residents in Ali from June to August 2021 for investigation. The food frequency questionnaire was used to collect data on food consumption over the past year. Factor analysis was employed to construct dietary patterns, and stepwise multinomial logistic regression was applied to identify the factors affecting dietary patterns.

Results

Five dietary patterns were extracted. Logistic regression analysis showed that the dried fruit beverage pattern was positively correlated with non-married (P=0.043), other occupations (P=0.027), smoking (P=0.023), weight gain >2.5 kg in the past year (P=0.019), non-clean fuel (P=0.006), and poor self-rated health (P=0.001). The Tibetan pattern was positively correlated with education level (P<0.001) but negatively correlated with non-cadre (P=0.002) and non-clean fuel (P<0.001).The highly processed unhealthy pattern was positively correlated with age (P<0.001) and poor self-rated health (P=0.027),while negatively correlated with non-married (P=0.019), non-cadre (P=0.039), family living standards (P=0.002), smoking (P=0.003), tea drinking (P=0.022), weight gain >2.5 kg in the past year (P=0.004), and non-clean fuel (P=0.004). The modern meat-dominant pattern was positively correlated with age (P=0.011), non-married (P=0.003), non-cadre (P=0.020) and tea drinking (P=0.005), but negatively correlated with drinking (P<0.001), amateur physical exercise (P=0.004) and non-clean fuel(P=0.042). The dietary fiber pattern was positively correlated with non-clean fuel (P=0.030), but negatively correlated with high family living standards (P=0.002) and tea drinking (P=0.018).

Conclusion

This study demonstrates that differences in the distribution of the five dietary patterns among residents of Ali are closely associated with demographic characteristics,socioeconomic status, and lifestyle factors, and some patterns are significantly associated with body weight changes and self-rated health status. Targeted dietary interventions should be implemented based on the local dietary culture and living habits to support the prevention and control of chronic diseases in underdeveloped high-altitude areas.

, authors=Lin NAN1, Jia-yu SHAN2, Yuan-wu ZOU3, Zhi-hui YANG1, Ze MA1, Yan ZHAO4, Li ZHANG5, authorsList=Lin NAN, Jia-yu SHAN, Yuan-wu ZOU, Zhi-hui YANG, Ze MA, Yan ZHAO, Li ZHANG, authorCompany=null, correspAuthors=Li ZHANG, 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=1311350445449241593, articleId=1311350442974602225, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=2021年西藏阿里部分少数民族聚集区膳食模式影响因素调查分析, columnId=1228016573034721597, journalTitle=现代预防医学, columnName=营养与食品卫生, runingTitle=null, highlight=null, articleAbstract=
目的

分析阿里地区人群膳食模式及其影响因素,为欠发达高海拔地区通过膳食干预防控慢性病提供参考。

方法

采用分层整群抽样法,于2021年6—8月抽取606名阿里成年居民开展调查。利用食物频率调查表获取近1年内食物消费情况,运用因子分析构建膳食模式,无序多分类logistic逐步回归识别其影响因素。

结果

共提取五种膳食模式。Logistic回归分析显示,干果饮料模式与非在婚(P=0.043)、其他职业(P=0.027)、吸烟(P=0.023)、近1年体重增加2.5 kg以上(P=0.019)、非清洁燃料(P=0.006)、自评健康差(P=0.001)呈正相关;藏族模式与教育程度(P<0.001)呈正相关,与非干部(P=0.002)、非清洁燃料(P<0.001)呈负相关;高加工不健康模式与年龄(P<0.001)、自评健康差(P=0.027)呈正相关,与非在婚(P=0.019)、非干部(P=0.039)、家庭生活水平(P=0.002)、吸烟(P=0.003)、饮茶(P=0.022)、近1年体重增加2.5 kg以上(P=0.004)、非清洁燃料(P=0.004)呈负相关;现代肉食型模式与年龄(P=0.011)、非在婚(P=0.003)、非干部(P=0.020)、饮茶(P=0.005)呈正相关,与饮酒(P<0.001)、业余体育锻炼(P=0.004)、非清洁燃料(P=0.042)呈负相关;膳食纤维模式与非清洁燃料(P=0.030)呈正相关,与高家庭生活水平(P=0.002)、饮茶(P=0.018)呈负相关。

结论

本研究显示,阿里地区人群五种膳食模式的分布差异与人口学特征、社会经济状况及行为生活方式因素密切相关,且部分模式与体重变化、自评健康状况存在显著关联。应依据本地区饮食文化特点与生活习惯实施精准膳食干预,为欠发达高海拔地区慢性病防控提供支撑。

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南琳(1996—),女,硕士,技师,研究方向:营养流行病学

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张丽,E-mail:
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南琳(1996—),女,硕士,技师,研究方向:营养流行病学

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Nutrients, 2019, 11(11): 2635., articleTitle=Tea consumption patterns in relation to diet quality among children and adults in the United States: analyses of NHANES 2011-2016 data, refAbstract=null)], funds=[Fund(id=1311350451585507385, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, awardId=ALKJ-BJCZ-2021-12, language=CN, fundingSource=西藏阿里地区科技局科技项目(ALKJ-BJCZ-2021-12), fundOrder=null, country=null), Fund(id=1311350451677782074, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, awardId=YJ(YB)202408, language=CN, fundingSource=西安交通大学第二附属医院基金项目(YJ(YB)202408), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1311350445625402362, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, xref=1., ext=[AuthorCompanyExt(id=1311350445633790971, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445625402362, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Cancer Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710061, China), AuthorCompanyExt(id=1311350445642179580, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445625402362, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.西安交通大学第一附属医院癌症中心,陕西 西安 710061)]), AuthorCompany(id=1311350445692511229, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, xref=2., ext=[AuthorCompanyExt(id=1311350445700899838, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445692511229, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.西安交通大学公共卫生学院)]), AuthorCompany(id=1311350445763814399, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, xref=3., ext=[AuthorCompanyExt(id=1311350445772203008, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445763814399, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.陕西省结核病防治院检验科)]), AuthorCompany(id=1311350445877059584, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, xref=4., ext=[AuthorCompanyExt(id=1311350445885448193, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445877059584, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.西安交通大学第一附属医院皮肤科)]), AuthorCompany(id=1311350445956751362, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, xref=5., ext=[AuthorCompanyExt(id=1311350445960945667, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, companyId=1311350445956751362, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=5.西安交通大学第二附属医院老年普通外科,陕西 西安 710004)])], figs=[ArticleFig(id=1311350450604040239, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=EN, label=Figure 1, caption=Scree plot of factor analysis, figureFileSmall=xvRkIVmhDVWyCvacyeuRZQ==, figureFileBig=NNBs4uvXcbWTY+g/J9pJYw==, tableContent=null), ArticleFig(id=1311350450700509232, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=CN, label=图1, caption=因子分析碎石图, figureFileSmall=xvRkIVmhDVWyCvacyeuRZQ==, figureFileBig=NNBs4uvXcbWTY+g/J9pJYw==, tableContent=null), ArticleFig(id=1311350450885058609, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=EN, label=Table 1, caption=

Basic information of the respondents (n=606)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量n(%)
性别男329(54.29)
女277(45.71)
民族其他113(18.65)
藏族493(81.35)
年龄(岁)≤29175(28.88)
30~49264(43.56)
≥50167(27.56)
教育程度小学及以下273(45.05)
中学和大专168(27.72)
大学及以上165(27.23)
婚姻状况在婚422(69.64)
非在婚184(30.36)
职业行政及管理人员126(20.79)
专业技术人员a140(23.10)
家务156(25.74)
其他184(30.37)
人员类别干部180(29.70)
非干部426(70.30)
家庭生活水平低207(34.16)
中214(35.31)
高185(30.53)
家庭人口数(人)≤3309(51.50)
≥4291(48.50)
吸烟否511(84.32)
是95(15.68)
饮酒否521(85.97)
是85(14.03)
饮茶否179(29.54)
是427(70.46)
不健康饮食行为无212(34.98)
有394(65.02)
业余体育锻炼不参加393(64.85)
参加213(35.15)
近1年体重变化无明显变化446(73.60)
增加2.5 kg以上86(14.19)
减少2.5 kg以上74(12.21)
燃料类型清洁285(47.03)
非清洁321(52.97)
自评健康好354(58.42)
一般166(27.39)
差86(14.19)
), ArticleFig(id=1311350450952167474, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=CN, label=表1, caption=

调查对象的基本情况(n=606)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量n(%)
性别男329(54.29)
女277(45.71)
民族其他113(18.65)
藏族493(81.35)
年龄(岁)≤29175(28.88)
30~49264(43.56)
≥50167(27.56)
教育程度小学及以下273(45.05)
中学和大专168(27.72)
大学及以上165(27.23)
婚姻状况在婚422(69.64)
非在婚184(30.36)
职业行政及管理人员126(20.79)
专业技术人员a140(23.10)
家务156(25.74)
其他184(30.37)
人员类别干部180(29.70)
非干部426(70.30)
家庭生活水平低207(34.16)
中214(35.31)
高185(30.53)
家庭人口数(人)≤3309(51.50)
≥4291(48.50)
吸烟否511(84.32)
是95(15.68)
饮酒否521(85.97)
是85(14.03)
饮茶否179(29.54)
是427(70.46)
不健康饮食行为无212(34.98)
有394(65.02)
业余体育锻炼不参加393(64.85)
参加213(35.15)
近1年体重变化无明显变化446(73.60)
增加2.5 kg以上86(14.19)
减少2.5 kg以上74(12.21)
燃料类型清洁285(47.03)
非清洁321(52.97)
自评健康好354(58.42)
一般166(27.39)
差86(14.19)
), ArticleFig(id=1311350451019276339, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=EN, label=Table 2, caption=

Factor load matrix of various foods

, figureFileSmall=null, figureFileBig=null, tableContent=
食物条目干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
大米0.331
杂粮0.322
面食0.436
羊肉0.773
牛肉0.649
大肉0.511
家禽及制品0.610
水产/海鲜品0.693
蛋类及制品0.542
动物内脏0.632
蔬菜0.691
瓜果0.744
土豆及薯类0.689
豆类及制品0.470
牛/羊奶0.758
酸奶0.697
其他奶制品0.532
酥油茶0.768
奶茶0.330
糌粑0.797
酥油0.790
风干肉0.648
奶渣/奶酪0.563
咸菜/泡菜0.619
干菜0.786
坚果0.858
红枣0.847
枸杞0.816
葡萄干0.828
其他果干0.863
豆浆0.673
果汁/蔬菜汁0.673
碳酸饮料0.460
其他饮品0.661
藏式红糖0.447
零食0.721
方便食品0.766
宵夜0.507
熏肉/腊肉0.612
加工肉食0.783
不吃早餐0.430
油炸食品0.670
烧烤0.766
西式快餐0.611
餐馆/小吃店就餐0.642
), ArticleFig(id=1311350451098968116, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=CN, label=表2, caption=

各类食物的因子载荷矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
食物条目干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
大米0.331
杂粮0.322
面食0.436
羊肉0.773
牛肉0.649
大肉0.511
家禽及制品0.610
水产/海鲜品0.693
蛋类及制品0.542
动物内脏0.632
蔬菜0.691
瓜果0.744
土豆及薯类0.689
豆类及制品0.470
牛/羊奶0.758
酸奶0.697
其他奶制品0.532
酥油茶0.768
奶茶0.330
糌粑0.797
酥油0.790
风干肉0.648
奶渣/奶酪0.563
咸菜/泡菜0.619
干菜0.786
坚果0.858
红枣0.847
枸杞0.816
葡萄干0.828
其他果干0.863
豆浆0.673
果汁/蔬菜汁0.673
碳酸饮料0.460
其他饮品0.661
藏式红糖0.447
零食0.721
方便食品0.766
宵夜0.507
熏肉/腊肉0.612
加工肉食0.783
不吃早餐0.430
油炸食品0.670
烧烤0.766
西式快餐0.611
餐馆/小吃店就餐0.642
), ArticleFig(id=1311350451166076981, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=EN, label=Table 3, caption=

Characteristics of the population under the quartile score of different dietary patterns [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
Q1Q3Q1Q3Q1Q3Q1Q3Q1Q3
性别男113(34.3)113(34.3)90(27.4)127(38.6)b124(37.7)98(29.8)b126(38.3)109(33.1)b124(37.7)99(30.1)b
女89(32.1)89(32.1)112(40.4)75(27.1)78(28.2)104(37.5)76(27.4)93(33.6)78(28.1)103(37.2)
民族其他34(30.09)35(30.97)1(0.9)104(92.0)c34(30.1)35(31.0)50(44.3)32(28.3)b51(45.1)23(20.4)b
藏族168(34.1)167(33.9)201(40.8)98(19.9)168(34.1)167(33.9)152(30.8)170(34.5)151(30.6)179(36.3)
年龄(岁)≤2956(32.0)63(36.0)b44(25.1)74(42.3)c81(46.3)30(17.1)c66(37.7)49(28.0)b53(30.3)63(36.0)b
30~49105(39.8)81(30.7)68(25.8)113(42.8)100(37.9)68(25.7)96(36.4)95(36.0)100(37.9)70(26.5)
≥5041(24.6)58(34.7)90(53.9)15(9.0)21(12.6)104(62.3)40(24.0)58(34.7)49(29.3)69(41.4)
教育程度小学及以下63(23.1)110(40.3)c160(58.6)18(6.6)c65(23.8)126(46.2)c71(26.0)96(35.2)b76(27.8)106(38.9)b
中学和大专70(41.7)46(27.4)34(20.3)79(47.0)71(42.3)38(22.6)63(37.5)57(33.9)60(35.7)58(34.5)
大学及以上69(41.8)46(27.9)8(4.9)105(63.6)66(40.0)38(23.0)68(41.2)49(29.7)66(40.0)38(23.0)
婚姻状况在婚154(36.5)134(31.7)b138(32.7)137(32.5)128(30.3)156(37.0)b149(35.3)131(31.0)139(32.9)142(33.7)
非在婚48(26.1)68(36.9)64(34.8)65(35.3)74(40.2)46(25.0)53(28.8)71(38.6)63(32.2)60(32.6)
职业行政及管理人员60(47.6)33(26.2)c9(7.1)76(60.4)c55(43.7)29(23.0)c57(45.2)37(29.4)b51(40.5)29(23.0)b
专业技术人员a60(42.9)40(28.5)15(10.7)82(58.6)47(33.6)35(25.0)55(39.3)43(30.7)54(38.6)39(27.8)
家务44(28.2)60(38.5)88(56.4)13(8.3)54(34.6)64(41.0)44(28.2)56(35.9)46(29.5)66(42.3)
其他38(20.7)69(37.5)90(48.9)31(16.9)46(25.0)74(40.2)46(25.0)66(35.9)51(27.7)68(37.0)
人员类型干部76(42.2)46(25.6)b12(6.7)127(70.6)c67(37.2)49(27.2)79(43.9)51(28.3)b72(40.0)43(23.9)
非干部126(29.6)156(36.6)190(44.6)75(17.6)135(31.7)153(35.9)123(28.9)151(35.4)130(30.5)159(37.3)
家庭生活水平低57(27.5)61(29.5)c94(45.4)38(18.4)c49(23.7)99(47.8)c51(24.6)76(36.7)b53(25.6)88(42.5)c
中64(29.9)87(40.7)86(40.2)59(27.6)82(38.3)61(28.5)70(32.7)68(31.8)69(32.2)72(33.7)
高81(43.8)54(29.2)22(11.9)105(56.8)71(38.4)42(22.7)81(43.8)58(31.3)80(43.2)42(22.7)
家庭人口数(人)≤3102(33.0)102(33.0)83(26.9)113(36.6)b104(33.7)104(33.6)103(33.3)108(35.0)105(34.0)102(33.0)
≥499(34.0)96(33.0)117(40.2)88(30.2)97(33.3)93(32.0)98(33.7)94(32.3)94(32.3)97(33.3)
吸烟否172(33.7)169(33.0)191(37.4)144(28.2)c155(30.3)187(36.6)c159(31.1)174(34.1)a164(32.1)179(35.0)
是30(31.6)33(34.7)11(11.6)58(61.0)47(49.5)15(15.8)43(45.3)28(29.4)38(40.0)23(24.2)
饮酒否176(33.8)175(33.6)188(36.1)159(30.5)c172(33.0)176(33.8)163(31.3)189(36.3)c169(32.4)173(33.2)
是26(30.6)27(31.8)14(16.5)43(50.6)30(35.3)26(30.6)39(45.9)13(15.3)33(38.8)29(34.1)
饮茶否62(34.6)57(31.9)67(37.4)47(26.3)49(27.4)74(41.3)b65(36.3)46(25.7)b47(26.3)74(41.3)b
是140(32.8)145(33.9)135(31.6)155(36.3)153(35.8)128(30.0)137(32.1)156(36.5)155(36.3)128(30.0)
业余体育锻炼不参加110(28.0)141(35.9)b159(40.5)100(25.4)c131(33.3)143(36.4)b115(29.3)141(35.9)b126(32.1)147(37.4)b
参加92(43.2)61(28.6)43(20.2)102(47.9)71(33.3)59(27.7)87(40.9)61(28.6)76(35.7)55(25.8)
近1年无明显变化146(32.7)141(31.6)165(37.0)124(27.8)c140(31.4)165(37.0)c140(31.4)149(33.4)136(30.5)158(35.4)
体重变化增加2.5 kg以上27(31.4)36(41.9)15(17.4)49(57.0)42(48.8)11(12.8)35(40.7)27(31.4)35(40.7)21(24.4)
减少2.5 kg以上29(39.2)25(33.8)22(29.7)29(39.2)20(27.0)26(35.2)27(36.5)26(35.1)31(41.9)23(31.1)
燃料类型清洁121(42.5)70(24.5)c26(9.1)173(60.7)c101(35.4)75(26.3)b103(36.1)98(34.4)115(40.3)72(25.3)c
非清洁81(25.3)132(41.1)176(54.8)29(9.0)101(31.5)127(39.5)99(30.8)104(32.4)87(27.1)130(40.5)
自评健康好156(44.1)91(25.7)c88(24.9)137(38.7)c128(36.2)99(27.9)c137(38.7)104(29.4)b121(34.2)100(28.2)b
一般32(19.3)72(43.4)67(40.4)53(31.9)57(34.3)56(33.8)50(30.1)65(39.2)55(33.1)62(37.4)
差14(16.3)39(45.3)47(54.7)12(13.9)17(19.8)47(54.6)15(17.4)33(38.4)26(30.2)40(46.5)
), ArticleFig(id=1311350451266740278, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=CN, label=表3, caption=

膳食模式因子得分三分位分组下研究人群特征[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
Q1Q3Q1Q3Q1Q3Q1Q3Q1Q3
性别男113(34.3)113(34.3)90(27.4)127(38.6)b124(37.7)98(29.8)b126(38.3)109(33.1)b124(37.7)99(30.1)b
女89(32.1)89(32.1)112(40.4)75(27.1)78(28.2)104(37.5)76(27.4)93(33.6)78(28.1)103(37.2)
民族其他34(30.09)35(30.97)1(0.9)104(92.0)c34(30.1)35(31.0)50(44.3)32(28.3)b51(45.1)23(20.4)b
藏族168(34.1)167(33.9)201(40.8)98(19.9)168(34.1)167(33.9)152(30.8)170(34.5)151(30.6)179(36.3)
年龄(岁)≤2956(32.0)63(36.0)b44(25.1)74(42.3)c81(46.3)30(17.1)c66(37.7)49(28.0)b53(30.3)63(36.0)b
30~49105(39.8)81(30.7)68(25.8)113(42.8)100(37.9)68(25.7)96(36.4)95(36.0)100(37.9)70(26.5)
≥5041(24.6)58(34.7)90(53.9)15(9.0)21(12.6)104(62.3)40(24.0)58(34.7)49(29.3)69(41.4)
教育程度小学及以下63(23.1)110(40.3)c160(58.6)18(6.6)c65(23.8)126(46.2)c71(26.0)96(35.2)b76(27.8)106(38.9)b
中学和大专70(41.7)46(27.4)34(20.3)79(47.0)71(42.3)38(22.6)63(37.5)57(33.9)60(35.7)58(34.5)
大学及以上69(41.8)46(27.9)8(4.9)105(63.6)66(40.0)38(23.0)68(41.2)49(29.7)66(40.0)38(23.0)
婚姻状况在婚154(36.5)134(31.7)b138(32.7)137(32.5)128(30.3)156(37.0)b149(35.3)131(31.0)139(32.9)142(33.7)
非在婚48(26.1)68(36.9)64(34.8)65(35.3)74(40.2)46(25.0)53(28.8)71(38.6)63(32.2)60(32.6)
职业行政及管理人员60(47.6)33(26.2)c9(7.1)76(60.4)c55(43.7)29(23.0)c57(45.2)37(29.4)b51(40.5)29(23.0)b
专业技术人员a60(42.9)40(28.5)15(10.7)82(58.6)47(33.6)35(25.0)55(39.3)43(30.7)54(38.6)39(27.8)
家务44(28.2)60(38.5)88(56.4)13(8.3)54(34.6)64(41.0)44(28.2)56(35.9)46(29.5)66(42.3)
其他38(20.7)69(37.5)90(48.9)31(16.9)46(25.0)74(40.2)46(25.0)66(35.9)51(27.7)68(37.0)
人员类型干部76(42.2)46(25.6)b12(6.7)127(70.6)c67(37.2)49(27.2)79(43.9)51(28.3)b72(40.0)43(23.9)
非干部126(29.6)156(36.6)190(44.6)75(17.6)135(31.7)153(35.9)123(28.9)151(35.4)130(30.5)159(37.3)
家庭生活水平低57(27.5)61(29.5)c94(45.4)38(18.4)c49(23.7)99(47.8)c51(24.6)76(36.7)b53(25.6)88(42.5)c
中64(29.9)87(40.7)86(40.2)59(27.6)82(38.3)61(28.5)70(32.7)68(31.8)69(32.2)72(33.7)
高81(43.8)54(29.2)22(11.9)105(56.8)71(38.4)42(22.7)81(43.8)58(31.3)80(43.2)42(22.7)
家庭人口数(人)≤3102(33.0)102(33.0)83(26.9)113(36.6)b104(33.7)104(33.6)103(33.3)108(35.0)105(34.0)102(33.0)
≥499(34.0)96(33.0)117(40.2)88(30.2)97(33.3)93(32.0)98(33.7)94(32.3)94(32.3)97(33.3)
吸烟否172(33.7)169(33.0)191(37.4)144(28.2)c155(30.3)187(36.6)c159(31.1)174(34.1)a164(32.1)179(35.0)
是30(31.6)33(34.7)11(11.6)58(61.0)47(49.5)15(15.8)43(45.3)28(29.4)38(40.0)23(24.2)
饮酒否176(33.8)175(33.6)188(36.1)159(30.5)c172(33.0)176(33.8)163(31.3)189(36.3)c169(32.4)173(33.2)
是26(30.6)27(31.8)14(16.5)43(50.6)30(35.3)26(30.6)39(45.9)13(15.3)33(38.8)29(34.1)
饮茶否62(34.6)57(31.9)67(37.4)47(26.3)49(27.4)74(41.3)b65(36.3)46(25.7)b47(26.3)74(41.3)b
是140(32.8)145(33.9)135(31.6)155(36.3)153(35.8)128(30.0)137(32.1)156(36.5)155(36.3)128(30.0)
业余体育锻炼不参加110(28.0)141(35.9)b159(40.5)100(25.4)c131(33.3)143(36.4)b115(29.3)141(35.9)b126(32.1)147(37.4)b
参加92(43.2)61(28.6)43(20.2)102(47.9)71(33.3)59(27.7)87(40.9)61(28.6)76(35.7)55(25.8)
近1年无明显变化146(32.7)141(31.6)165(37.0)124(27.8)c140(31.4)165(37.0)c140(31.4)149(33.4)136(30.5)158(35.4)
体重变化增加2.5 kg以上27(31.4)36(41.9)15(17.4)49(57.0)42(48.8)11(12.8)35(40.7)27(31.4)35(40.7)21(24.4)
减少2.5 kg以上29(39.2)25(33.8)22(29.7)29(39.2)20(27.0)26(35.2)27(36.5)26(35.1)31(41.9)23(31.1)
燃料类型清洁121(42.5)70(24.5)c26(9.1)173(60.7)c101(35.4)75(26.3)b103(36.1)98(34.4)115(40.3)72(25.3)c
非清洁81(25.3)132(41.1)176(54.8)29(9.0)101(31.5)127(39.5)99(30.8)104(32.4)87(27.1)130(40.5)
自评健康好156(44.1)91(25.7)c88(24.9)137(38.7)c128(36.2)99(27.9)c137(38.7)104(29.4)b121(34.2)100(28.2)b
一般32(19.3)72(43.4)67(40.4)53(31.9)57(34.3)56(33.8)50(30.1)65(39.2)55(33.1)62(37.4)
差14(16.3)39(45.3)47(54.7)12(13.9)17(19.8)47(54.6)15(17.4)33(38.4)26(30.2)40(46.5)
), ArticleFig(id=1311350451384180791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=EN, label=Table 4, caption=

Multinomial logistic regression analysis of influencing factors of dietary patterns

, figureFileSmall=null, figureFileBig=null, tableContent=
变量干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值
年龄(岁)≤291.001.00
30~491.67(0.92~3.05)0.0922.00(1.17~3.42)0.011
≥5011.07(5.32~23.06)<0.0012.32(1.22~4.39)0.010
教育程度小学及以下1.00
中学和大专4.35(2.11~8.97)<0.001
大学及以上12.59(4.62~34.31)<0.001
婚姻状况在婚1.001.001.00
非在婚1.62(1.02~2.58)0.0430.52(0.30~0.90)0.0192.10(1.29~3.42)0.003
职业行政及管理人员1.00
专业技术人员a1.61(0.84~3.10)0.153
家务1.94(0.90~4.17)0.091
其他2.26(1.10~4.65)0.027
人员类型干部1.001.001.00
非干部0.27(0.12~0.61)0.0020.54(0.30~0.97)0.0391.93(1.11~3.36)0.020
家庭生活水平低1.001.00
中0.41(0.24~0.72)0.0020.68(0.42~1.10)0.114
高0.33(0.17~0.64)0.0010.41(0.24~0.71)0.002
吸烟否1.001.00
是2.06(1.11~3.85)0.0230.35(0.17~0.70)0.003
饮酒否1.00
是0.27(0.14~0.54)<0.001
饮茶否1.001.001.00
是0.56(0.34~0.92)0.0221.95(1.22~3.11)0.0050.58(0.37~0.91)0.018
业余体育锻炼不参加1.00
参加0.52(0.33~0.81)0.004
近1年无明显变化1.001.00
体重变化增加2.5 kg以上2.13(1.14~4.01)0.0190.32(0.15~0.70)0.004
减少2.5 kg以上0.88(0.44~1.75)0.7101.48(0.74~2.95)0.271
燃料类型清洁1.001.001.001.001.00
非清洁2.27(1.26~4.10)0.0060.12(0.06~0.22)<0.0010.40(0.22~0.74)0.0040.58(0.34~0.98)0.0421.64(1.05~2.56)0.030
自评健康好1.001.00
一般3.34(2.00~5.58)<0.0011.24(0.73~2.12)0.427
差3.28(1.62~6.65)0.0012.30(1.10~4.81)0.027
), ArticleFig(id=1311350451451289656, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350442974602225, language=CN, label=表4, caption=

膳食模式影响因素的多分类logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量干果饮料模式藏族模式高加工不健康模式现代肉食型模式膳食纤维模式
OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值
年龄(岁)≤291.001.00
30~491.67(0.92~3.05)0.0922.00(1.17~3.42)0.011
≥5011.07(5.32~23.06)<0.0012.32(1.22~4.39)0.010
教育程度小学及以下1.00
中学和大专4.35(2.11~8.97)<0.001
大学及以上12.59(4.62~34.31)<0.001
婚姻状况在婚1.001.001.00
非在婚1.62(1.02~2.58)0.0430.52(0.30~0.90)0.0192.10(1.29~3.42)0.003
职业行政及管理人员1.00
专业技术人员a1.61(0.84~3.10)0.153
家务1.94(0.90~4.17)0.091
其他2.26(1.10~4.65)0.027
人员类型干部1.001.001.00
非干部0.27(0.12~0.61)0.0020.54(0.30~0.97)0.0391.93(1.11~3.36)0.020
家庭生活水平低1.001.00
中0.41(0.24~0.72)0.0020.68(0.42~1.10)0.114
高0.33(0.17~0.64)0.0010.41(0.24~0.71)0.002
吸烟否1.001.00
是2.06(1.11~3.85)0.0230.35(0.17~0.70)0.003
饮酒否1.00
是0.27(0.14~0.54)<0.001
饮茶否1.001.001.00
是0.56(0.34~0.92)0.0221.95(1.22~3.11)0.0050.58(0.37~0.91)0.018
业余体育锻炼不参加1.00
参加0.52(0.33~0.81)0.004
近1年无明显变化1.001.00
体重变化增加2.5 kg以上2.13(1.14~4.01)0.0190.32(0.15~0.70)0.004
减少2.5 kg以上0.88(0.44~1.75)0.7101.48(0.74~2.95)0.271
燃料类型清洁1.001.001.001.001.00
非清洁2.27(1.26~4.10)0.0060.12(0.06~0.22)<0.0010.40(0.22~0.74)0.0040.58(0.34~0.98)0.0421.64(1.05~2.56)0.030
自评健康好1.001.00
一般3.34(2.00~5.58)<0.0011.24(0.73~2.12)0.427
差3.28(1.62~6.65)0.0012.30(1.10~4.81)0.027
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2021年西藏阿里部分少数民族聚集区膳食模式影响因素调查分析
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南琳 1 , 陕嘉宇 2 , 邹远妩 3 , 杨志慧 1 , 马泽 1 , 赵延 4 , 张丽 5
现代预防医学 | 营养与食品卫生 2026,53(15): 2752-2759
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现代预防医学 |营养与食品卫生 2026 , 53 (15) : 2752 -2759
2021年西藏阿里部分少数民族聚集区膳食模式影响因素调查分析
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南琳1, 陕嘉宇2, 邹远妩3, 杨志慧1, 马泽1, 赵延4, 张丽5
作者信息
  • 1.西安交通大学第一附属医院癌症中心,陕西 西安 710061
  • 2.西安交通大学公共卫生学院
  • 3.陕西省结核病防治院检验科
  • 4.西安交通大学第一附属医院皮肤科
  • 5.西安交通大学第二附属医院老年普通外科,陕西 西安 710004
通讯作者:
张丽,E-mail:
作者简介:

南琳(1996—),女,硕士,技师,研究方向:营养流行病学

Survey and analysis of influencing factors on dietary patterns in ethnic minority concentrated areas of Ali, Tibet in 2021
Lin NAN1, Jia-yu SHAN2, Yuan-wu ZOU3, Zhi-hui YANG1, Ze MA1, Yan ZHAO4, Li ZHANG5
Affiliations
  • Cancer Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710061, China
出版时间: 2026-08-10 doi: 10.20043/j.cnki.MPM.202512373
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目的

分析阿里地区人群膳食模式及其影响因素,为欠发达高海拔地区通过膳食干预防控慢性病提供参考。

方法

采用分层整群抽样法,于2021年6—8月抽取606名阿里成年居民开展调查。利用食物频率调查表获取近1年内食物消费情况,运用因子分析构建膳食模式,无序多分类logistic逐步回归识别其影响因素。

结果

共提取五种膳食模式。Logistic回归分析显示,干果饮料模式与非在婚(P=0.043)、其他职业(P=0.027)、吸烟(P=0.023)、近1年体重增加2.5 kg以上(P=0.019)、非清洁燃料(P=0.006)、自评健康差(P=0.001)呈正相关;藏族模式与教育程度(P<0.001)呈正相关,与非干部(P=0.002)、非清洁燃料(P<0.001)呈负相关;高加工不健康模式与年龄(P<0.001)、自评健康差(P=0.027)呈正相关,与非在婚(P=0.019)、非干部(P=0.039)、家庭生活水平(P=0.002)、吸烟(P=0.003)、饮茶(P=0.022)、近1年体重增加2.5 kg以上(P=0.004)、非清洁燃料(P=0.004)呈负相关;现代肉食型模式与年龄(P=0.011)、非在婚(P=0.003)、非干部(P=0.020)、饮茶(P=0.005)呈正相关,与饮酒(P<0.001)、业余体育锻炼(P=0.004)、非清洁燃料(P=0.042)呈负相关;膳食纤维模式与非清洁燃料(P=0.030)呈正相关,与高家庭生活水平(P=0.002)、饮茶(P=0.018)呈负相关。

结论

本研究显示,阿里地区人群五种膳食模式的分布差异与人口学特征、社会经济状况及行为生活方式因素密切相关,且部分模式与体重变化、自评健康状况存在显著关联。应依据本地区饮食文化特点与生活习惯实施精准膳食干预,为欠发达高海拔地区慢性病防控提供支撑。

膳食模式  /  影响因素  /  因子分析  /  高海拔
Objective

To analyze the dietary patterns and their influencing factors in Ali area, and to provide reference for the prevention and control of chronic diseases via dietary intervention in underdeveloped high altitude areas.

Methods

A stratified cluster sampling method was used to select 606 adult residents in Ali from June to August 2021 for investigation. The food frequency questionnaire was used to collect data on food consumption over the past year. Factor analysis was employed to construct dietary patterns, and stepwise multinomial logistic regression was applied to identify the factors affecting dietary patterns.

Results

Five dietary patterns were extracted. Logistic regression analysis showed that the dried fruit beverage pattern was positively correlated with non-married (P=0.043), other occupations (P=0.027), smoking (P=0.023), weight gain >2.5 kg in the past year (P=0.019), non-clean fuel (P=0.006), and poor self-rated health (P=0.001). The Tibetan pattern was positively correlated with education level (P<0.001) but negatively correlated with non-cadre (P=0.002) and non-clean fuel (P<0.001).The highly processed unhealthy pattern was positively correlated with age (P<0.001) and poor self-rated health (P=0.027),while negatively correlated with non-married (P=0.019), non-cadre (P=0.039), family living standards (P=0.002), smoking (P=0.003), tea drinking (P=0.022), weight gain >2.5 kg in the past year (P=0.004), and non-clean fuel (P=0.004). The modern meat-dominant pattern was positively correlated with age (P=0.011), non-married (P=0.003), non-cadre (P=0.020) and tea drinking (P=0.005), but negatively correlated with drinking (P<0.001), amateur physical exercise (P=0.004) and non-clean fuel(P=0.042). The dietary fiber pattern was positively correlated with non-clean fuel (P=0.030), but negatively correlated with high family living standards (P=0.002) and tea drinking (P=0.018).

Conclusion

This study demonstrates that differences in the distribution of the five dietary patterns among residents of Ali are closely associated with demographic characteristics,socioeconomic status, and lifestyle factors, and some patterns are significantly associated with body weight changes and self-rated health status. Targeted dietary interventions should be implemented based on the local dietary culture and living habits to support the prevention and control of chronic diseases in underdeveloped high-altitude areas.

Dietary pattern  /  Influencing factors  /  Factor analysis  /  High altitude
南琳, 陕嘉宇, 邹远妩, 杨志慧, 马泽, 赵延, 张丽. 2021年西藏阿里部分少数民族聚集区膳食模式影响因素调查分析. 现代预防医学, 2026 , 53 (15) : 2752 -2759 . DOI: 10.20043/j.cnki.MPM.202512373
Lin NAN, Jia-yu SHAN, Yuan-wu ZOU, Zhi-hui YANG, Ze MA, Yan ZHAO, Li ZHANG. Survey and analysis of influencing factors on dietary patterns in ethnic minority concentrated areas of Ali, Tibet in 2021[J]. Modern Preventive Medicine, 2026 , 53 (15) : 2752 -2759 . DOI: 10.20043/j.cnki.MPM.202512373
不健康行为生活方式广泛流行,严重导致人口寿命损失和各种疾病发生[1],已成为中低收入国家及地区的重大公共卫生挑战。缺乏体育活动、不健康膳食、吸烟及有害饮酒等可改变的行为生活方式常共现于个体,促发机体代谢紊乱间接引发多种不良健康结局,被《柳叶刀》列为优先干预方向[2]。我国成年人中,同时具备不吸烟、适量饮酒、膳食合理、体重体脂正常及积极运动等全维度健康行为生活方式者仅占0.7%[3]。膳食在日常暴露频率最高,常与其他生活方式协同作用于慢性病[4],而健康高质量膳食可有效降低慢性病发病风险[5-6]。
高海拔地区人群膳食融合宗教礼仪与地域习俗,呈高热量、耐储存特征,这种适应极端环境的传统膳食模式可能存在微量营养素供给不足问题,与环境的叠加效应直接影响居民健康。阿里地区平均海拔高度4 500米以上,近年来膳食结构随现代文化交融发生变迁,但藏区膳食行为调查数据匮乏,膳食模式分析及干预研究鲜少。探索高海拔地区膳食模式及其影响因素,对识别营养干预目标人群,改善膳食健康极具价值。
本研究于2021年6—8月以阿里地区7县成年常住居民为调查对象,采用分层整群随机抽样法,按4 500 m海拔高度分为<4 500 m和≥4 500 m两层,分别按人口比例整群抽取2个、1个行政村。样本量依据公式估算,设定d=5.5%,当地慢性病粗患病率p=55.0%[7],计入20%失访并考虑1.5倍整群抽样设计效应,需调查567人。剔除关键变量缺失及异常问卷后,最终获得有效问卷606份。纳入标准:该地区常住≥12个月且自愿参与的成年居民。排除标准:长时间外出、不能独立完成问卷或清晰回答者。本研究方案经阿里地区人民医院医学伦理委员会审核批准(aldqrmyy [2021]No.001),所有受试者均自愿参与并签署书面知情同意书。
采用自编居民健康状况问卷开展入户调查[7],内容涵盖一般情况、行为生活方式、膳食、环境暴露、疾病和健康状况。膳食摄入由基于中国人群食物频率问卷[8],结合当地独特饮食文化和生活习惯[9]进行本土化修订与优化后的食物频数调查表评估,含47种食物条目及特定饮食行为,调查员询问过去1年内各种食物和特定饮食行为的消费频率(不吃,1~3次/月,1~3次/周,4~6次/周,每天)与每次食用量(两)。选取30人预调查,Cronbach α系数是0.943,信度良好。运用Kaiser-Meyer-Olkin(KMO)检验评价问卷结构效度,KMO=0.931,效度良好。
采用因子分析确定膳食模式,将全部食物消费频率纳入主成分分析,经方差最大化正交旋转,根据方差贡献率、特征根≥1.5、碎石图及理论合理性筛选主要膳食模式,因子载荷系数绝对值>0.3为命名依据。计算个体对各类膳食模式的独立因子得分,得分越高则越倾向该膳食模式,后将因子得分从低到高进行三分位法(Q1~Q3),用于分析不同依从度水平下研究人群的基本信息及影响因素差异。
现场调查员与质控人员均经统一标准化培训并考核合格,调查时确保至少1名调查员可双语(藏/汉语)交流,质控人员现场核查问卷,确认无误后统一运送保存。数据实施双录入,并进行一致性核查。
采用Epidata 3.1软件创建数据库,STATA16.0软件进行统计处理。用均数和标准差()描述符合正态分布的连续型变量;用频数(n)和百分比(%)描述分类变量。采用χ2检验比较各膳食模式因子得分三分位数分组下的人群特征。通过主成分法构建家庭财富指数,依据第一主成分权重按三分位法划分以反映家庭生活水平。将单因素分析中16个自变量纳入无序多分类logistic逐步回归模型,分析膳食模式的影响因素,设定α入=0.05、α出=0.10,似然比检验P<0.05验证模型拟合度。上述统计采用双侧检验,检验水准α=0.05。
本次调查共计606人,男女比例1.19∶1,藏族居多,平均年龄(40.74±16.42)岁,教育程度为小学及以下占45.05%,在婚占69.64%,70.30%为非干部。见表1。
KMO=0.931,Bartlett球形检验χ2=17 753.44,P<0.001,满足因子分析条件。结合碎石图、方差贡献率及专业实际意义,严格提取特征根≥1.50的公因子,最终得到五种膳食模式。五个公因子特征根依次为13.67、5.24、3.56、2.27、1.65,方差贡献率分别为17.13%、12.03%、11.96%、6.31%、5.73%,累积方差贡献率为53.16%。干果饮料模式富含多种干果和饮料;藏族模式富含糌粑、酥油、牛羊肉等本土化食材;高加工不健康模式由不健康的特定饮食行为构成,具高盐高糖高脂特征;现代肉食型模式拥有畜禽肉、水产海鲜、蛋类等大众化动物源性食物;膳食纤维模式包含多种瓜果蔬菜。见图1、表2。
结果显示:五种膳食模式在年龄、教育程度、职业、家庭生活水平、业余体育锻炼、自评健康间分布具有统计学差异(P<0.05)。此外,干果饮料模式在婚姻状况、人员类型、燃料类型间分布有统计学差异;藏族模式在性别、民族、人员类型、家庭人口数、吸烟史、饮酒史、近1年体重变化、燃料类型间分布有统计学差异;高加工不健康模式在性别、婚姻状况、吸烟史、饮茶史、近1年体重变化、燃料类型间分布有统计学差异;现代肉食型模式在性别、民族、人员类型、吸烟史、饮酒史、饮茶史间分布有统计学差异;膳食纤维模式在性别、民族、饮茶史、燃料类型间分布有统计学差异。见表3。
干果饮料模式:非在婚、其他职业、吸烟、近1年体重增加2.5 kg以上、非清洁燃料、自评健康差因子得分较高;藏族模式:教育程度越高因子得分越高,非干部、非清洁燃料因子得分较低;高加工不健康模式:50岁及以上、自评健康差因子得分较高,非在婚、非干部、家庭生活水平越高、吸烟、饮茶、非清洁燃料、近1年体重增加2.5 kg以上因子得分较低;现代肉食型模式:年龄越大、非在婚、非干部、饮茶因子得分较高,饮酒、参加业余体育锻炼、非清洁燃料因子得分较低;膳食纤维模式:非清洁燃料因子得分较高,家庭生活水平高、饮茶因子得分较低。见表4。
膳食模式囊括复杂的膳食摄入特征,因社会经济地位、民族、文化等因素而异[10],在疾病风险表征中具有重要价值[11]。西藏阿里地处青藏高原西北部,为典型超高海拔区域,常年低温严寒、耕地稀缺、新鲜果蔬及优质副食自产能力不足;加之地理位置偏远、长途物流成本高昂,制约当地居民膳食选择,促使人群倾向摄入高热量、耐储存的传统食物,以适配高海拔环境下的生理代谢需求。同时,地域习俗传承、游牧与定居并存的生产生活方式及区域社会经济水平形成叠加效应,共同塑造了该地区独特的膳食与饮食行为特征。本研究调查了阿里部分成年居民的膳食摄入情况,构建五种契合当地饮食特征的膳食模式,结果显示,该地区出现了不健康的高加工膳食模式、干果饮料模式和现代肉食型模式,这与我国近年营养转变趋势一致[12]。当地传统的藏族模式与现代肉食型模式虽均呈现高蛋白摄入特征,但蛋白来源、脂肪构成、主食结构、饮食习惯完全不同。膳食纤维模式在高海拔地区相关研究报道中缺乏[13],未发现富含肉蛋、果蔬、豆类及海鲜的平衡模式。
Logistic回归分析显示,膳食模式的影响因素不尽相同。非在婚、吸烟、近1年体重增加2.5 kg以上、非清洁燃料、自评健康差者倾向不健康的干果饮料模式[14-15]。非在婚者多独居,饮食追求便捷且无需迎合家庭需求;吸烟、饮酒、缺乏体育锻炼致使体质指数增高的人更倾向该模式[16],吸烟者味觉和嗅觉敏感度降低,倾向味道浓郁风味突出的食物[17];使用清洁燃料者对干果饮料模式的依从性尚未得到其他研究的论证;而自评健康差的人往往健康素养缺乏,对健康模式的依从性较低[18]。以牛羊肉为主的藏族模式属健康模式但成本较高,教育程度高者更注重食物营养价值,且可能拥有较高收入支撑该消费;而非干部、非清洁燃料人群受经济制约该消费模式并不日常。年龄较大、自评健康差者倾向高加工不健康模式,非干部、家庭生活水平高、吸烟、饮茶、近1年体重增加2.5 kg、非清洁燃料等与之呈负相关。高龄人群饮食偏好固化,受教育程度不高,健康素养不足,同时可能因味觉减退或经济下行,易选择便宜的糖脂丰富的食物[19];自评健康差者常伴负面情绪,该类食物能刺激多巴胺分泌缓解压力;国外研究表明,家庭年收入低下与零食消费有关,在本研究中零食是高加工不健康模式的重要条目,家庭生活水平高者拥有高健康素养,遵循健康膳食模式[20],非干部、使用非清洁燃料者多为牧民,经济水平有限较少消费该类食物;当地茶饮多为酥油茶,富含酥油、乳蛋白及茶单宁,可直接补充机体所需能量并调节代谢,其自带的适度脂糖可与糌粑、淡煮肉等本味清淡膳食适配,逐渐形成“以茶补能”的饮食行为习惯,进一步弱化对高盐高脂高糖膳食的摄入需求。关于体重增加呈现的负相关,我们猜想体重增加者可能低估了致肥胖食物的摄入频率。年龄越大、非在婚、非干部、饮茶者倾向现代肉食型模式,饮酒与该模式呈负相关。国内既往研究未发现年龄、饮酒对现代肉食型模式的影响[21]。本研究推测高龄者味觉嗅觉衰退,动物蛋白较植物蛋白更契合口感与营养需求;当地酥油茶本身富含动物源性蛋白,饮茶场景通常搭配牛羊肉或风干肉,进一步增强了饮茶者对该模式的倾向性;非干部者多从事体力劳动对动物蛋白需求高;饮酒的人往往搭配烧烤、小吃而非高蛋白肉类。经济决定购买能力,非清洁燃料使用者经济低下,更倾向节俭的膳食纤维模式,较高家庭生活水平、饮茶与该模式呈负相关。家庭生活水平高者能突破高原食材单一限制,主动补充膳食纤维以平衡高动物蛋白膳食实现食物多样性;美国成人茶消费者膳食纤维摄入更高,而亚洲人浓茶饮用更普遍,茶常替代高纤维食物可能导致负相关[22],另外,研究地区饮茶场景下通常习惯搭配动物蛋白而非植物性膳食纤维。
本研究有一些局限性:(1)横断面调查仅能揭示膳食模式与人口学特征、行为生活方式间的相关关系,无法体现因果关联;(2)膳食与健康状况依赖居民自报,可能存在回忆偏倚;(3)自编食物频率问卷未能获取各类食物具体摄入量,仅使用频率暴露数据;(4)调查地区处高海拔偏远区域,交通不便,调查局限于三个行政村的成年居民,且为单次横断面调查,研究结论外推至其他高海拔地区时需谨慎。
综上,本研究进一步证实膳食模式与多种行为生活方式密切相关。欠发达少数民族高海拔聚集区膳食实践具强烈地域与民族特色,膳食结构不均衡,应以合理膳食与科学营养为抓手,调控动物性食品、油盐糖及饮料消费,增加果蔬与水产品摄入,强化该地区慢性病防控。
  • 西藏阿里地区科技局科技项目(ALKJ-BJCZ-2021-12)
  • 西安交通大学第二附属医院基金项目(YJ(YB)202408)
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2026年第53卷第15期
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doi: 10.20043/j.cnki.MPM.202512373
  • 接收时间:2025-12-23
  • 首发时间:2026-09-28
  • 出版时间:2026-08-10
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  • 收稿日期:2025-12-23
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西藏阿里地区科技局科技项目(ALKJ-BJCZ-2021-12)
西安交通大学第二附属医院基金项目(YJ(YB)202408)
作者信息
    1.西安交通大学第一附属医院癌症中心,陕西 西安 710061
    2.西安交通大学公共卫生学院
    3.陕西省结核病防治院检验科
    4.西安交通大学第一附属医院皮肤科
    5.西安交通大学第二附属医院老年普通外科,陕西 西安 710004

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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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