Evidence map›Paper›PMID 39725876›Full record

ArticleBMC pregnancy and childbirth2024

Integrative development of a concise screening questionnaire for early detection of pregnant women at risk for dystrophy.

Yadi Zhang, Xiaoge Gao, Haiyan Zhu, Qi Zhou, Xiaxia Cai, Pamela Ann Koch, Shengzhi Sun, Huanling Yu

Abstract readValidation Study
In one paragraph

Article in BMC pregnancy and childbirth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yadi ZhangSchool of Public Health, Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, People's Republic of China.
Xiaoge GaoProgram in Nutrition, Department of Health Studies & Applied Educational Psychology, Teachers College, Columbia University, New York, USA.
Haiyan ZhuFuXing Hospital, Capital Medical University, Beijing, People's Republic of China.
Qi ZhouXuanwu Hospital Capital Medical University, Beijing, People's Republic of China.
Xiaxia CaiSchool of Public Health, Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, People's Republic of China.
Pamela Ann KochProgram in Nutrition, Department of Health Studies & Applied Educational Psychology, Teachers College, Columbia University, New York, USA.
Shengzhi SunSchool of Public Health, Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, People's Republic of China. shengzhisun@ccmu.edu.cn.
Huanling YuSchool of Public Health, Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, People's Republic of China. yuhlzjl@ccmu.edu.cn.

Funding

National Natural Science Foundation of China 82473615R&D Program of Beijing Municipal Education Commission KZ202210025039
6 · The paper itself

Abstract

backgroundMaintaining 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.

methodsTo 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.

resultsThe 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).

conclusionsThis tool has great potential for identifying unhealthy dietary behaviors, potentially leading to improved pregnancy outcomes.

trial registrationThis study was preregistered on May 5, 2023, at the Chinese Clinical Trial Registry (ChiCTR2300071126).

Indexed as

Early DiagnosisAdultBirth WeightChecklistDietFeeding BehaviorFemaleFetal MacrosomiaHumansNutrition AssessmentPregnancyPregnant PeopleReproducibility of ResultsSurveys and QuestionnairesAssessmentMalnutritionNutrition and dietPregnancySelf-reportSurvey

Identifiers

PMID39725876
PMCPMC11670376

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.