Nuts, vegetables, fruits, and protein dietary pattern during pregnancy is inversely associated with risk of childhood allergies: a case–control study

Author:

Adineh Parisa,Amini Shirin,Abolnezhadian Farhad,Jafari Fatemeh,Ebrahimian Niayesh

Abstract

AbstractAllergic diseases are prevalent chronic conditions among children and can lead to significant health and economic issues. It is hypothesized that healthy and high quality diet during pregnancy can prevent the onset of allergic diseases in offspring. This study aimed to investigate the potential relationship between major dietary patterns during pregnancy and allergies in children under one year of age. This case–control study was conducted involving 244 participants (122 mothers of allergic children and 122 healthy controls) who visited pediatricians and allergy outpatient clinics in Khuzestan Province, Iran, between June 2022 and March 2023. Demographic information was recorded using a socio-demographic questionnaire. A food frequency questionnaire was used to identify the foods consumed during pregnancy. Major dietary patterns were extracted using principal component analysis, and the potential relationship between these patterns and childhood allergies was investigated using multivariable logistic regression models. The crude odds ratio (OR) analysis showed that the fourth quartile of "Nut, vegetables, fruits, and protein" dietary pattern was associated with lower occurrence of childhood allergies (OR: 0.214, 95% CI = 0.068–0.679; P trend = 0.211). After adjusting for cofactors in Model 3, this association was still observed in the fourth quartile (OR = 0.108, 95% CI = 0.019–0.613; P trend, 0.001). However, no significant association was observed between "Carbohydrate and cereals" and "Salty" dietary patterns and childhood allergies. The study findings suggest that a maternal dietary pattern rich in nuts, vegetables, and fruits during pregnancy may reduce the risk of allergic diseases in offspring.

Funder

Vice-Chancellor for Research Affairs of the Shoushtar Faculty of Medical Sciences, Shoushtar City, Iran

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3