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食物环境的地理空间分析表明与妊娠期糖尿病有关联。

Geospatial analysis of food environment demonstrates associations with gestational diabetes.

作者信息

Kahr Maike K, Suter Melissa A, Ballas Jerasimos, Ramin Susan M, Monga Manju, Lee Wesley, Hu Min, Shope Cindy D, Chesnokova Arina, Krannich Laura, Griffin Emily N, Mastrobattista Joan, Dildy Gary A, Strehlow Stacy L, Ramphul Ryan, Hamilton Winifred J, Aagaard Kjersti M

机构信息

Department of Obstetrics and Gynecology, Division of Maternal Fetal Medicine, Baylor College of Medicine, Houston, TX.

Environmental Health Section, Chronic Disease Prevention and Control Research Center, Baylor College of Medicine, Houston, TX.

出版信息

Am J Obstet Gynecol. 2016 Jan;214(1):110.e1-9. doi: 10.1016/j.ajog.2015.08.048. Epub 2015 Aug 28.

Abstract

BACKGROUND

Gestational diabetes mellitus (GDM) is one of most common complications of pregnancy, with incidence rates varying by maternal age, race/ethnicity, obesity, parity, and family history. Given its increasing prevalence in recent decades, covariant environmental and sociodemographic factors may be additional determinants of GDM occurrence.

OBJECTIVE

We hypothesized that environmental risk factors, in particular measures of the food environment, may be a diabetes contributor. We employed geospatial modeling in a populous US county to characterize the association of the relative availability of fast food restaurants and supermarkets to GDM.

STUDY DESIGN

Utilizing a perinatal database with >4900 encoded antenatal and outcome variables inclusive of ZIP code data, 8912 consecutive pregnancies were analyzed for correlations between GDM and food environment based on countywide food permit registration data. Linkage between pregnancies and food environment was achieved on the basis of validated 5-digit ZIP code data. The prevalence of supermarkets and fast food restaurants per 100,000 inhabitants for each ZIP code were gathered from publicly available food permit sources. To independently authenticate our findings with objective data, we measured hemoglobin A1c levels as a function of geospatial distribution of food environment in a matched subset (n = 80).

RESULTS

Residence in neighborhoods with a high prevalence of fast food restaurants (fourth quartile) was significantly associated with an increased risk of developing GDM (relative to first quartile: adjusted odds ratio, 1.63; 95% confidence interval, 1.21-2.19). In multivariate analysis, this association held true after controlling for potential confounders (P = .002). Measurement of hemoglobin A1c levels in a matched subset were significantly increased in association with residence in a ZIP code with a higher fast food/supermarket ratio (n = 80, r = 0.251 P < .05).

CONCLUSION

As demonstrated by geospatial analysis, a relationship of food environment and risk for gestational diabetes was identified.

摘要

背景

妊娠期糖尿病(GDM)是最常见的妊娠并发症之一,其发病率因产妇年龄、种族/族裔、肥胖、产次和家族史而异。鉴于近几十年来其患病率不断上升,环境和社会人口统计学协变量因素可能是GDM发生的其他决定因素。

目的

我们假设环境风险因素,特别是食物环境指标,可能是糖尿病的一个促成因素。我们在美国一个人口众多的县采用地理空间建模来描述快餐店和超市的相对可及性与GDM之间的关联。

研究设计

利用一个包含超过4900个编码的产前和结局变量(包括邮政编码数据)的围产期数据库,根据全县食品许可证登记数据,对8912例连续妊娠进行GDM与食物环境之间的相关性分析。妊娠与食物环境之间的关联是基于经过验证的5位邮政编码数据实现的。从公开的食品许可证来源收集每个邮政编码每10万居民中超市和快餐店的患病率。为了用客观数据独立验证我们的发现,我们在一个匹配子集(n = 80)中测量糖化血红蛋白水平作为食物环境地理空间分布的函数。

结果

居住在快餐店患病率高的社区(第四四分位数)与发生GDM的风险增加显著相关(相对于第一四分位数:调整后的优势比,1.63;95%置信区间,1.21 - 2.19)。在多变量分析中,在控制潜在混杂因素后,这种关联仍然成立(P = .002)。在一个匹配子集中,糖化血红蛋白水平的测量与居住在快餐/超市比例较高的邮政编码区域显著相关(n = 80,r = 0.251,P < .05)。

结论

通过地理空间分析表明,食物环境与妊娠期糖尿病风险之间存在关联。

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