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成年居民膳食模式与2型糖尿病风险的关联研究
作者:孙倩 王慧 乔楠 张海霞 崔燕 黄建军 王彤

摘要:

目的  探索膳食模式与2型糖尿病(T2DM)风险的关联。方法  采用两阶段分层随机抽样方法,于2013年从山西省大同市某大型煤矿集团的87个煤矿分公司中抽取3 747名对象。采用自制问卷收集人口学特征、吸烟、饮酒和糖尿病家族史等资料,采用国际体力活动问卷评估体力活动状况,同时进行体格测量和糖脂代谢指标测定,按照T2DM风险得分分为高风险组与低风险组。采用半定量食物频率问卷收集对象既往1年的膳食数据,通过探索性因子分析和聚类分析进行膳食模式判别。采用非条件logistic回归模型分析膳食模式与T2DM风险的关系。结果  研究对象年龄为(41.48±8.62)岁,其中男性2 843名(84.31%),T2DM高风险组1 819名,低风险组1 553名。确定了4类膳食模式,分别为健康膳食、高盐膳食、肉类膳食以及高碳水化合物膳食。调整人口学特征、吸烟和饮酒等因素后,以健康膳食为参照,高盐膳食、高碳水化合物膳食和肉类膳食与T2DM风险的OR(95%CI)值分别为1.54(1.26~1.88)、1.80(1.43~2.28)和1.20(0.99~1.46)。结论  高盐膳食和高碳水化合物膳食与T2DM风险存在正关联,肉类膳食与T2DM无关联。

关键词:饮食习惯;膳食调查;糖尿病,2型;横断面研究

Abstract:

Objective  To explore the association of dietary pattern and type 2 diabetes mellitus (T2DM) risk.Methods  In 2013, 3 747 participants from 87 coalmine branches of a large coal mine group in Datong City, Shanxi Province were selected by using a two-stage cluster stratified sampling method. Data on demographic characteristics, smoking, drinking, and family history of diabetes were collected by using a self-made questionnaire, and the International Physical Activity Questionnaire was used to assess the level of physical activity. Physical, glucose and lipid metabolism indicators were measured and subjects were divided into high-risk groups and low-risk groups of T2DM according to the T2DM risk score. Dietary data were collected by using Semi-quantitative Food Frequency Questionnaire, and dietary patterns were derived by using the exploratory factor analysis and cluster analysis. The unconditional logistic regression model was used to assess the association of dietary patterns and T2DM risk.Results  The age of the subjects was(41.48±8.62) years old, and 2 843 of them were males (84.31%). A total of 1 819 subjects were in the high-risk group and 1 553 in the low-risk group. Four dietary patterns, healthy diet, high-salt diet, meats diet, and carbohydrate-rich diet, were identified in this study. The unconditional logistic regression analysis showed that compared with the healthy diet pattern, after the adjustment of demographic characteristics, smoking, and drinking, the OR (95%CI) of T2DM risk in high-salt diet, carbohydrate-rich diet and meats diet patterns was 1.54 (1.26-1.88), 1.80 (1.43-2.28) and 1.20 (0.99-1.46), respectively.Conclusion  High-salt diet and carbohydrate-rich diet were positively associated with T2DM risk, whereas there was no association of meats diet and T2DM risk.

Key words: Food habits;Diet surveys;Diabetes mellitus, type 2;Cross-sectional studies

发表日期:2020/3

引用本文:

图/表:

  • 10.3760/cma.j.issn.0253-9624.2020.03.007.T001:表1 研究对象基本特征比较[名(%)]

    10.3760/cma.j.issn.0253-9624.2020.03.007.T001:表1 研究对象基本特征比较[名(%)]

  • 10.3760/cma.j.issn.0253-9624.2020.03.007.T002:表2 4类膳食模式的因子评分聚类均值

    10.3760/cma.j.issn.0253-9624.2020.03.007.T002:表2 4类膳食模式的因子评分聚类均值

  • 10.3760/cma.j.issn.0253-9624.2020.03.007.T003:表3 膳食模式与T2DM风险的多因素logistic回归模型分析结果[OR(95%CI)值]

    10.3760/cma.j.issn.0253-9624.2020.03.007.T003:表3 膳食模式与T2DM风险的多因素logistic回归模型分析结果[OR(95%CI)值]

参考文献:

[1]WangL, GaoP, ZhangM, et al. Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013[J]. JAMA, 2017,317(24):2515-2523. DOI: 10.1001/jama.2017.7596.
[2]YangSH, DouKF, SongWJ. Prevalence of diabetes among men and women in China[J]. N Engl J Med, 2010,362(25):2425-2426. DOI: 10.1056/NEJMc1004671.
[3]中华医学会糖尿病学分会.中国2型糖尿病防治指南(2013年版)[J].中华糖尿病杂志, 2014, 6(7): 447-498. DOI: 10.3760/cma.j.issn.1674-5809.2014.07.004.
[4]凌文华.膳食模式与慢性病防治[J].中华预防医学杂志,2018,52(3):217-220. DOI: 10.3760/cma.j.issn.0253-9624.2018.03.001.
[5]Medina-RemónA, KirwanR, Lamuela-RaventósRM, et al. Dietary patterns and the risk of obesity, type 2 diabetes mellitus, cardiovascular diseases, asthma, and neurodegenerative diseases[J]. Crit Rev Food Sci Nutr, 2018,58(2):262-296. DOI: 10.1080/10408398.2016.1158690.
[6]殷召雪,赵文华.膳食模式是营养与健康的关键[J].中华健康管理学杂志,2017,11(1):3-6. DOI: 10.3760/cma.j.issn.1674-0815.2017.01.002.
[7]樊萌语,吕筠,何平平.国际体力活动问卷中体力活动水平的计算方法[J].中华流行病学杂志,2014,35(8):961-964. DOI: 10.3760/cma.j.issn.0254-6450.2014.08.019.
[8]XiangYT, MaX, LuJY, et al. Alcohol-related disorders in Beijing, China: prevalence, socio-demographic correlates,and unmet need for treatment[J]. Alcohol Clin Exp Res, 2009, 33(6): 1111-1118. DOI:10.1111/j.1530-0277.2009.00933.x.
[9]李立明,饶克勤,孔灵芝,等.中国居民2002年营养与健康状况调查[J].中华流行病学杂志,2005,26(7):478-484. DOI: 10.3760/j.issn:0254-6450.2005.07.004.
[10]PerloffD, GrimC, FlackJ, et al. Human blood pressure determination by sphygmomanometry[J]. Circulation, 1993,88(5Pt 1):2460-2470. DOI: 10.1161/01.cir.88.5.2460.
[11]LasserK, BoydJW, WoolhandlerS, et al. Smoking and mental illness: A population-based prevalence study[J].JAMA, 2000,284(20):2606-2610. DOI: 10.1001/jama.284.20.2606.
[12]XiangYT, MaX, LuJY, et al. Alcohol-related disorders in Beijing, China: prevalence, socio-demographic correlates,and unmet need for treatment[J]. Alcohol Clin Exp Res, 2009,33(6):1111-1118. DOI: 10.1111/j.1530-0277.2009.00933.x.
[13]ZhouX, QiaoQ, JiL, et al. Nonlaboratory-based risk assessment algorithm for undiagnosed type 2 diabetes developed on a nation-wide diabetes survey[J]. Diabetes Care, 2013,36(12):3944-3952. DOI: 10.2337/dc13-0593.
[14]HeY, MaG, ZhaiF, et al. Dietary patterns and glucose tolerance abnormalities in Chinese adults[J]. Diabetes Care, 2009,32(11):1972-1976. DOI: 10.2337/dc09-0714.
[15]ZhangX, DagevosH, HeY, et al. Consumption and corpulence in China: A consumer segmentation study based on the food perspective[J]. Food Policy, 2008, 33(1): 37-47. DOI:10.1016/j.foodpol.2007.06.002.
[16]胡良平. SAS统计分析教程[M].北京:电子工业出版社, 2010.
[17]CunhaDB, AlmeidaRM, PereiraRA. A comparison of three statistical methods applied in the identification of eating patterns[J]. Cad Saude Publica, 2010,26(11):2138-2148. DOI: 10.1590/s0102-311x2010001100015.
[18]AbdulaiT, LiY, ZhangH, et al. Prevalence of impaired fasting glucose, type 2 diabetes and associated risk factors in undiagnosed Chinese rural population: the Henan Rural Cohort Study[J]. BMJ Open, 2019,9(8):e029628. DOI: 10.1136/bmjopen-2019-029628.
[19]RadzevicieneL, OstrauskasR. Adding salt to meals as a risk factor of type 2 diabetes mellitus: a case-control study[J]. Nutrients, 2017,9(1). pii: E67. DOI: 10.3390/nu9010067.
[20]AbdulaiT, LiY, ZhangH, et al. Prevalence of impaired fasting glucose, type 2 diabetes and associated risk factors in undiagnosed Chinese rural population: the Henan Rural Cohort Study[J]. BMJ Open, 2019, 9(8): e029628. DOI:10.1136/bmjopen-2019-029628.
[21]HuangL, ShangL, YangW, et al. High starchy food intake may increase the risk of adverse pregnancy outcomes: a nested case-control study in the Shaanxi province of Northwestern China[J]. BMC Pregnancy Childbirth, 2019,19(1):362. DOI: 10.1186/s12884-019-2524-z.
[22]MohanV, RadhikaG, VijayalakshmiP, et al. Can the diabetes/cardiovascular disease epidemic in India be explained, at least in part, by excess refined grain (rice) intake?[J]. Indian J Med Res, 2010,131:369-372.
[23]MozaffarianD. Dietary and policy priorities for cardiovascular disease, diabetes, and obesity: a comprehensive review[J]. Circulation, 2016,133(2):187-225. DOI: 10.1161/CIRCULATIONAHA.115.018585.
[24]SchwingshacklL, HoffmannG, LampousiAM, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies[J]. Eur J Epidemiol, 2017,32(5):363-375. DOI: 10.1007/s10654-017-0246-y.

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