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曹烨, 涂青云, 汪秋实, 韩翱瀚, 向全永. 江苏省成年居民不同膳食模式对糖尿病前期患病影响[J]. 中国公共卫生, 2018, 34(3): 423-427. DOI: 10.11847/zgggws1117156
引用本文: 曹烨, 涂青云, 汪秋实, 韩翱瀚, 向全永. 江苏省成年居民不同膳食模式对糖尿病前期患病影响[J]. 中国公共卫生, 2018, 34(3): 423-427. DOI: 10.11847/zgggws1117156
Ye CAO, Qing-yun TU, Qiu-shi WANG, Ao-han HAN, . Influence of different dietary patterns on prevalence of prediabetes among adult residents in Jiangsu province[J]. Chinese Journal of Public Health, 2018, 34(3): 423-427. DOI: 10.11847/zgggws1117156
Citation: Ye CAO, Qing-yun TU, Qiu-shi WANG, Ao-han HAN, . Influence of different dietary patterns on prevalence of prediabetes among adult residents in Jiangsu province[J]. Chinese Journal of Public Health, 2018, 34(3): 423-427. DOI: 10.11847/zgggws1117156

江苏省成年居民不同膳食模式对糖尿病前期患病影响

Influence of different dietary patterns on prevalence of prediabetes among adult residents in Jiangsu province

  • 摘要:
      目的  了解江苏省成年居民不同膳食模式对糖尿病前期患病影响,为采用合理膳食模式干预糖尿病患病提供参考依据。
      方法  采用多阶段整群随机抽样方法于2014年5月 — 2015年12月在江苏省抽取1 865名成年非糖尿病居民进行问卷调查、体格检查和实验室检测;采用因子分析法建立膳食模式,并应用logistic回归模型分析不同膳食模式对糖尿病前期患病的影响。
      结果  江苏省1 865名成年非糖尿病居民中,患糖尿病前期者315例,糖尿病前期患病率为16.9 %;因子分析得到动物型膳食、健康型膳食、传统型膳食和淀粉类植物型膳食4种膳食模式,累积方差贡献率为54.000 %;多因素logistic回归分析结果显示,在调整了性别、年龄、居住地、吸烟情况、饮酒情况、父母是否患糖尿病、体质指数、是否高血压、是否血脂异常等混杂因素后,健康型膳食是江苏省成年居民糖尿病前期患病的保护因素,因子得分处于T3水平居民糖尿病前期患病风险为因子得分处于T1水平居民的0.689倍(OR = 0.689,95 % CI = 0.481~0.986,P = 0.042),因子得分处于T4水平居民糖尿病前期患病风险为因子得分处于T1水平居民的0.518倍(OR = 0.518,95 % CI = 0.356~0.756,P = 0.001)。
      结论  健康型膳食模式可降低江苏省成年居民糖尿病前期患病风险。

     

    Abstract:
      Obective  To explore effects of different dietary patterns on the prevalence of prediabetes in adult residents in Jiangsu province and to provide evidences for the intervention of rational dietary pattern on diabetes.
      Methods  Multistage cluster random sampling was used to select 1 865 non-diabetic adult residents in Jiangsu province from May 2014 through December 2015. Questionnaire survey, physical examination and clinical tests were conducted among the residents to collect essential data. Factor analysis was adopted to identify the dietary patterns and logistic regression model was applied to analyze the influence of the dietary patterns on prediabetes.
      Results  Totally 315 participants with prediabetes were identified and the prevalence of prediabetes was 16.9% among the participants. The results of factor analysis confirmed four dietary patterns in the participants: animal, healthy, traditional, and starchy-vegetable diet patterns and the cumulative contribution of the four dietary patterns to total variance was 54.000%. The results of multivariate logistic regression analysis indicated that healthy diet pattern was a protective factor against prediabetes after adjusting for confounding factors as gender, age, residence, smoking, alcohol drinking, whether with parenal diabetes, body mass index, hypertension, and dyslipidemia. The risk of prediabetes for the participants with a dietary pattern score in the third and the fourth interquartile range were 0.689 (odds ratio OR = 0.689, 95% confidence interval 95%CI: 0.481 – 0.986; P = 0.042) and 0.518 (OR = 0.518 , 95%CI: 0.356 – 0.756; P = 0.001) compared to the participants with the score in the first interquartile range.
      Conclusion  Healthy diet pattern can reduce the risk of prediabetes in adult residents in Jiangsu province.

     

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