Evidence map›Paper›PMID 30045719›Full record

ArticleNutrition journal2018

Maternal dietary patterns during pregnancy and preterm delivery: a large prospective cohort study in China.

Min-Shan Lu, Jian-Rong He, Qiaozhu Chen, Jinhua Lu, Xueling Wei, Qianling Zhou, Fanfan Chan, Lifang Zhang, Niannian Chen, Lan Qiu and 5 more

Abstract readComparative Study
In one paragraph

Article in Nutrition journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Preconception ambient temperature and preterm birth: a time-series study in rural Henan, China.Environmental science and pollution research international · 2021
    Article
  20. Observational
4 · The record

Corrections and comments

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

15 authors.

Min-Shan LuDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Jian-Rong HeDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Qiaozhu ChenDepartment of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
Jinhua LuDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Xueling WeiDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Qianling ZhouDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Fanfan ChanDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Lifang ZhangDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Niannian ChenDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Lan QiuDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Mingyang YuanDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China.
Kar Keung ChengInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Huimin XiaDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China. huimin.xia@bigcs.org.
Xiu QiuDivision of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Junsui Road, Zhujiang Newtown, Tianhe District, Guangzhou, 510623, China. xiu.qiu@bigcs.org.ORCID 0000-0003-1248-229X
Born in Guangzhou Cohort Study Group

Funding

Guangdong Provincial Department of Science and Technology 2014A020213022Guangzhou Science Technology and Innovation Commission 201508030037National Natural Science Foundation of China 81673181National Natural Science Foundation of China 81703244
6 · The paper itself

Abstract

backgroundEvidence about the associations between maternal dietary patterns and preterm delivery is scarce in Eastern countries. The purpose of this study was to examine the associations between maternal dietary patterns during pregnancy and preterm delivery in a Chinese population.

methodsA total of 7352 mothers were included in the Born in Guangzhou Cohort Study, a prospective study in China. A validated self-administered food frequency questionnaire (FFQ) was used to assess maternal diet at 24-27 weeks of gestation. Dietary patterns were identified by cluster analysis. Gestational age was obtained from routine medical records. Preterm delivery was defined as delivery before 37 completed weeks of gestation, and was further classified into spontaneous and iatrogenic preterm delivery, and also early/moderate and late preterm delivery. Associations between dietary patterns and preterm delivery outcomes were assessed using logistic regression analyses.

resultsSix dietary patterns were identified, including 'Milk', 'Cereals, eggs, and Cantonese soups', 'Meats', 'Fruits, nuts, and Cantonese desserts', 'Vegetables', and 'Varied'. There were 351 (4.8%) preterm deliveries in this study population. Among those of preterm delivery, 16.2 and 83.8% were early/moderate and late preterm delivery, respectively. Compared with women of 'Vegetables' pattern, those of 'Milk' pattern had greater odds of overall preterm delivery (adjusted odds ratio [OR] 1.59, 95% confidence interval [CI] 1.11, 2.29, p < 0.05), spontaneous preterm delivery (adjusted OR 1.73, 95% CI 1.14, 2.62, p < 0.05) and late preterm delivery (adjusted OR 1.73, 95% CI 1.08, 2.62, p < 0.05); those of 'Cereals, eggs, and Cantonese soups' and 'Fruits, nuts, and Cantonese desserts' patterns had greater odds of late preterm delivery (adjusted OR 1.54, 95% CI 1.01, 2.35 for 'Cereals, eggs, and Cantonese soups', adjusted OR 1.61, 95% CI 1.04, 2.50 for 'Fruits, nuts, and Cantonese desserts', respectively).

conclusionMaternal diet with frequent consumption of milk and less frequent consumption of vegetables during pregnancy might be associated with increased odds of preterm delivery. Future interventions should investigate whether increasing vegetable intake reduces preterm deliveries.

Indexed as

DietMaternal Nutritional Physiological PhenomenaAdultAnimalsCandyChinaCohort StudiesEdible GrainEggsFemaleFruitGestational AgeHumansMilkMothersNutsBirth cohortChinese womenCluster analysisDietary patternPregnant womenPreterm delivery

Identifiers

PMID30045719
PMCPMC6060524

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.