Evidence map›Paper›PMID 27572074›Full record

ArticlePublic health nutrition2017

Dietary intakes and dietary patterns among pregnant women in Northwest China.

Jiaomei Yang, Shaonong Dang, Yue Cheng, Huizhen Qiu, Baibing Mi, Yufen Jiang, Pengfei Qu, Lingxia Zeng, Quanli Wang, Qiang Li and 3 more

Abstract read
In one paragraph

Article in Public health nutrition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 3 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

44 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  6. Observational
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  20. Maternal Dietary Diversity and Birth Weight in Offspring: Evidence from a Chinese Population-Based Study.International journal of environmental research and public health · 2023
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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

13 authors.

Jiaomei Yang1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Shaonong Dang1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Yue Cheng2Department of Nutrition,School of Public Health,Xi'an Jiaotong University Health Science Center,Xi'an, Shaanxi,People's Republic of China.
Huizhen Qiu1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Baibing Mi1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Yufen Jiang1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Pengfei Qu1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Lingxia Zeng1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Quanli Wang1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Qiang Li1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Yijun Kang1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Yuan Shen1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.
Hong Yan1Department of Epidemiology and Health Statistics,School of Public Health,Xi'an Jiaotong University Health Science Center,No. 76 Yanta West Road,Xi'an, Shaanxi 710061,People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo describe nutrient intakes, characterize dietary patterns and analyse their associations with sociodemographic characteristics among pregnant women in Shaanxi, China.

designPopulation-based cross-sectional survey.

settingTwenty counties and ten districts in Shaanxi Province of Northwest China, 2013. SUBJECTS: Women (n 7462) were recruited using a stratified multistage random sampling method to report diets during pregnancy, at 0-12 months (median 3 months; 10th-90th percentile, 0-7 months) after delivery.

resultsPregnant women had higher intakes of fat, niacin and vitamin E than the nutrient reference values, while most micronutrients such as vitamin A, folate, Ca and Zn were reportedly low. Women in the highest education, occupation and household income groups had higher nutrient intakes than those in the lowest groups. Nutrient intake differences also existed by geographic area, residence and maternal age at delivery. Three dietary patterns were identified: balanced pattern, vegetarian pattern and snacks pattern. Participants with high balanced pattern scores tended to be better educated, wealthier, 25-29 years old at delivery, working outside and living in urban areas and central Shaanxi. Women with high scores on the vegetarian pattern and snacks pattern tended to be in low balanced pattern score groups, and had lower nutrient intakes than those in the high balanced pattern score groups.

conclusionsThe study suggested that pregnant women in Shaanxi, China had low intakes of most nutrients such as vitamin A, folate and Ca. Dietary patterns and most nutrient intakes varied by sociodemographic characteristics. Targeted programmes are needed to improve dietary intakes and dietary patterns among sociodemographically disadvantaged groups.

Indexed as

EatingAdultChinaCross-Sectional StudiesDemographyDietDiet SurveysFeeding BehaviorFemaleFolic AcidHumansMicronutrientsNutritional RequirementsPregnancyPrenatal Nutritional Physiological PhenomenaFolic AcidMicronutrientsDietary intakeDietary patternNorthwest ChinaNutrient intakePregnant women

Identifiers

PMID27572074
PMCPMC10261368

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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.