Preferred fruit and vegetable consumption and colonic microbiota in young residents of Arkhangelsk

Natalia N. Kukalevskaya; Кукалевская Наталья Николаевна; Tatyana  A. Bazhukova; Бажукова Татьяна Александровна; Michael A. Sabanaev; Сабанаев Михаил Алексеевич; Andrej M. Grjibovski; Гржибовский Андрей Мечиславович

doi:10.17816/humeco633894

年轻阿尔汉格尔斯克居民偏好蔬菜水果的摄入与结肠微生物群的关系

作者: Kukalevskaya N.N.¹, Bazhukova T.A.¹, Sabanaev M.A.¹, Grjibovski A.M.¹^,2^,3
隶属关系:
1. Northern State Medical University
2. Northern (Arctic) Federal University n.a. M.V. Lomonosov
3. M.K. Ammosov North-Eastern Federal University
期: 卷 31, 编号 4 (2024)
页面: 279-290
栏目: ORIGINAL STUDY ARTICLES
##submission.dateSubmitted##: 27.06.2024
##submission.dateAccepted##: 07.10.2024
##submission.datePublished##: 12.12.2024
URL: https://hum-ecol.ru/1728-0869/article/view/633894
DOI: https://doi.org/10.17816/humeco633894
ID: 633894

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详细
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作者简介
参考
补充文件
统计

详细

背景。微生物群的组成受多种环境因素的影响，其中饮食行为是关键因素之一。尽管北方居民饮食特点的研究已有较多文献支持，但有关蔬菜和水果摄入对北方居民微生物群影响的研究仍极其有限。

研究目的。分析阿尔汉格尔斯克年轻居民（以医科大学的学生和工作人员为例）对蔬菜和水果的偏好及其与结肠微生物群组成之间的关系。

材料与方法。研究纳入90名参与者（23名男性和67名女性），均为北方国立医科大学的学生或工作人员。入选标准包括：18至45岁之间、身体健康、体重指数正常，以及在研究期间无急性或慢性炎症性疾病。通过问卷调查评估蔬菜和水果的摄入情况，并通过粪便样本进行结肠微生物群的分子遗传学分析。利用多变量中位数回归模型评估33种微生物群指标与蔬菜和水果摄入的关系，调整因素包括性别、年龄和常住地区。

结果。每日食用蔬菜的参与者占43.33%，每日食用水果的参与者占15.56%。最常食用的蔬菜是番茄（77.78%）和黄瓜（80.00%），土豆和胡萝卜的摄入率相对较低（25.00%）。最常见的水果包括苹果（74.44%）、香蕉（57.78%）和柑橘类水果（41.11%）。显著关联如下：Methanobrevibacter smithii 与番茄（ p =0.008）和胡萝卜（ p =0.006）显著相关；Prevotella spp. 与黄瓜（ p =0.032）显著相关；Blautia spp. 与胡萝卜（ p =0.002）和香蕉（ p =0.020）显著相关；Acinetobacter spp. 与番茄（p=0.036）、土豆（ p =0.028）和柑橘类水果（ p =0.019）显著相关；Bifidobacterium spp. 与土豆（ p =0.039）和柑橘类水果（ p =0.002）显著相关； Bacteroides spp. 与黄瓜（ p =0.023）显著相关。

结论。研究表明，特定蔬菜和水果的摄入显著影响某些微生物的数量和分布。更深入地研究饮食因素对微生物群的影响，有助于为北方居民制定个性化饮食方案，从而改善微生物群的多样性与整体生活质量。

关键词

微生物群, 结肠, 蔬菜, 水果, 北极地区

全文:

Table 1. Regression coefficients and their standard errors for the associations between consumption of selected vegetables and concentrations of gut microbiota species (lg CFU/g)

Род/вид представителя микробиоты толстой кишки Genus/species of colon microbiota	Регрессионные коэффициенты и их стандартные ошибки Regression coefficients and their standard errors
	Томаты Tomato	Огурцы Cucumber	Морковь Carrot	Картофель Potato
Acinetobacter spp	0,18 (0,08)*	0,18 (0,09)	-	-0,18 (0,08)*
Agathobacter rectalis	-0,05 (0,37)	-0,36 (0,40)	0,08 (0,36)	0,03 (0,32)
Akkermansia muciniphila	0 (0,80)	1,63 (2,76)	0 (2.69)	-3,00 (2,49)
Bacteroides spp	-0,18 (0,26)	0.65 (0.28)*	0.07 (0.25)	0,07 (0,24)
Bacteroides thethaiotaomicron	-0,17 (1,01)	0,47 (0,88)	-0.10 (0.89)	-0,68 (0,83)
Bifidobacterium spp	0.46 (0.38)	0.13 (0.37)	0.16 (0.33)	0.65 (0.31)*
Blautia spp	-0,52 (2,23)	-0,52 (2,31)	6.85 (2.12)*	0,21 (2,08)
Escherichia coli	0,12 (0,44)	0.14 (0.45)	0.52 (0.42)	0,11 (0,39)
Faecalibacterium prausnitzii	0 (0,23)	0,55 (0,19)*	-0.08 (0.21)	-0,18 (0,23)
Methanobrevibacter smithii	5,63 (2,06)*	1,10 (2,12)	-5,54 (1,97)*	-0,52 (1,88)
Prevotella spp	0,89 (0,96)	-2,00 (0,92)*	-0,56 (0,97)	0,14 (0,89)
Roseburia inulinivorans	0,15 (0,34)	0,01 (0,37)	-0,07 (0,32)	-0,10 (0,31)
Ruminococcus spp	-1.00 (1.71)	0 (2,20)	0 (2,04)	0,57 (1,97)
Streptococcus spp	0,04 (0,44)	0,78 (0,47)	0,25 (0,46)	0,23 (0,42)

Table 2. Regression coefficients and their standard errors for the associations between consumption of selected fruits and concentrations of gut microbiota species (lg CFU/g)

Род/вид представителя микробиоты толстой кишки Genus/species of colon microbiota	Регрессионные коэффициенты и их стандартные ошибки Regression coefficients and their standard errors
	Бананы Bananas	Цитрусовые Citrus	Яблоки Apple
Acinetobacter spp	0,00 (1,00)	0,15 (0,06)*	0.00 (1.00)
Agathobacter rectalis	-0,12 (0,34)	0,09 (0,31)	-0.60 (0.32)
Akkermansia muciniphila	0,00 (1,00)	-0,21 (2,34)	-3.09 (2.74)
Bacteroides spp	-0,13 (0,91)	-0,17 (0,77)	0.34 (0.88)
Bacteroides thethaiotaomicron	-0,12 (0,24)	0,05 (0,22)	0.15 (0.25)
Bifidobacterium spp	-0,17 (0,33)	-0,70 (0,22)*	-0.59 (0.32)
Blautia spp	4,77 (2,01)*	0,00 (1,00)	0.00 (1.00)
Escherichia coli	-0,14 (0,36)	-0,44 (0,35)	-0.30 (0.44)
Faecalibacterium prausnitzii	-0,15 (0,18)	-0,22 (0,16)	0.00 (1.00)
Methanobrevibacter smithii	-0,24 (1,81)	0,10 (1,70)	-0.97 (2.04)
Prevotella spp	-0,23 (0,84)	-1,30 (0,87)	-0.79 (1.04)
Roseburia inulinivorans	0,05 (0,30)	0,15 (0,29)	-0.36 (0.38)
Ruminococcus spp	-0,30 (1,90)	-0,49 (1,81)	0.48 (2.07)
Streptococcus spp	-0,13 (0,44)	-0,30 (0,35)	0.02 (0.81)

* - уровень значимости р менее 0,05

Fig.1. Frequency fruits and vegetables consumption in the study sample.

Fig.2. Frequency of consumption of selected fruits and vegetables in the study sample

作者简介

Natalia Kukalevskaya

Northern State Medical University

编辑信件的主要联系方式.
Email: n.kukalevskaya@yandex.ru
ORCID iD: 0000-0003-3371-1485
SPIN 代码: 1844-4439
俄罗斯联邦, 51 Troitski ave., 163069 Arkhangelsk

Tatyana Bazhukova

Northern State Medical University

Email: tbazhukova@yandex.ru
ORCID iD: 0000-0002-7890-2341
SPIN 代码: 2220-2151

Dr. Sci (Med), Professor

俄罗斯联邦, 51 Troitski ave., 163069 Arkhangelsk

Michael Sabanaev

Northern State Medical University

Email: mix.sabanaeff@gmail.com
ORCID iD: 0000-0001-5642-3019
SPIN 代码: 8585-3051
俄罗斯联邦, 51 Troitski ave., 163069 Arkhangelsk

Andrej Grjibovski

Northern State Medical University; Northern (Arctic) Federal University n.a. M.V. Lomonosov; M.K. Ammosov North-Eastern Federal University

Email: a.grjibovski@yandex.ru
ORCID iD: 0000-0002-5464-0498
SPIN 代码: 5118-0081

MD, MPhil, PhD

俄罗斯联邦, 51 Troitski ave., 163069 Arkhangelsk; Arkhangelsk; Yakutsk

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