Zhang Yadi, Gao Xiaoge, Zhu Haiyan, Zhou Qi, Cai Xiaxia, Koch Pamela Ann, Sun Shengzhi, Yu Huanling
School of Public Health, Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, People's Republic of China.
Program in Nutrition, Department of Health Studies & Applied Educational Psychology, Teachers College, Columbia University, New York, USA.
BMC Pregnancy Childbirth. 2024 Dec 26;24(1):861. doi: 10.1186/s12884-024-07051-4.
Maintaining a healthy diet during pregnancy is vital for reducing the risk of adverse birth outcomes. However, conventional methods of assessing the dietary behavior of pregnant women, such as the FFQ, are often time-consuming. This study aims to develop a concise nutritional screening questionnaire tailored for pregnant women, empowering prenatal healthcare providers to quickly identify key adverse dietary behaviors and provide targeted guidance.
To validate the Pregnancy Nutrition Checklist, we enrolled 208 women in early pregnancy and 200 women were included to analysis (with an average age of 31.54 ± 4.24 years). Spearman rank correlation analysis was used to assess the relative reliability of the Pregnancy Nutrition Checklist compared with the FFQ scale. Exploratory factor analysis was used to test the structural validity of the scale. A generalized linear model was used to analyze the correlation between dietary behavior and birth weight.
The pregnancy nutrition checklist includes 15 dietary items and 3 other lifestyle habit items. Compared with traditional FFQ questionnaires, the correlation analysis of corresponding items in the pregnancy nutrition checklist revealed statistical significance (p < 0.05), except for fat intake. EFA identified three underlying factors, namely, "high-fat foods," "moderate-fat foods," and "low-fat foods," indicating that the questionnaire has good construct validity. Insufficient consumption of vegetables by pregnant women(OR = 2.64, 95% CI: 1.08-6.46, p = 0.033) was associated with a significantly greater risk of developing LGA fetuses. Pregnant women whose sugar, coffee, or tea intake did not exceed the classification criteria had significantly greater fetal birth weights than those whose intake exceeded the classification criteria (OR = 3.38, 95% CI: 1.18-9.68, p = 0.023). In contrast, consuming fewer highly palatable snacks can reduce the incidence of LGA babies (OR = 0.29, 95% CI: 0.11-0.74, p = 0.010).
This tool has great potential for identifying unhealthy dietary behaviors, potentially leading to improved pregnancy outcomes.
This study was preregistered on May 5, 2023, at the Chinese Clinical Trial Registry (ChiCTR2300071126).
孕期保持健康饮食对于降低不良分娩结局的风险至关重要。然而，评估孕妇饮食行为的传统方法，如食物频率问卷（FFQ），往往耗时较长。本研究旨在开发一份专为孕妇量身定制的简明营养筛查问卷，使产前保健提供者能够快速识别关键的不良饮食行为并提供针对性指导。
为验证妊娠营养清单，我们招募了208名孕早期女性，其中200名女性纳入分析（平均年龄31.54±4.24岁）。采用Spearman等级相关分析评估妊娠营养清单与食物频率问卷量表相比的相对可靠性。探索性因素分析用于检验该量表的结构效度。采用广义线性模型分析饮食行为与出生体重之间的相关性。
妊娠营养清单包括15项饮食项目和3项其他生活习惯项目。与传统的食物频率问卷相比，妊娠营养清单中相应项目的相关性分析显示，除脂肪摄入量外，均具有统计学意义（p<0.05）。探索性因素分析确定了三个潜在因素，即“高脂肪食物”、“中等脂肪食物”和“低脂肪食物”，表明该问卷具有良好的结构效度。孕妇蔬菜摄入量不足（OR=2.64，95%CI：1.08-6.46，p=0.033）与巨大胎儿发生风险显著增加相关。糖、咖啡或茶摄入量未超过分类标准的孕妇，其胎儿出生体重显著高于摄入量超过分类标准的孕妇（OR=3.38，95%CI：1.18-9.68，p=0.023）。相反，食用较少的高适口性零食可降低巨大儿的发生率（OR=0.29，95%CI：0.11-0.74，p=0.010）。
该工具在识别不健康饮食行为方面具有巨大潜力，可能有助于改善妊娠结局。
本研究于2023年5月5日在中国临床试验注册中心（ChiCTR2300071126）进行了预注册。
