Evidence map›Paper›PMID 42374308›Full record

ArticleBMC pregnancy and childbirth2026

The link between nutrient intake and anthropometric indices with COVID-19 infection in pregnant women.

Masoomeh Alsadat Mirshafaei, Shiva Khodarahmi, Masoumeh Dorosti, Zahra Falahnejad, Alireza Khosravani, Mohammad Keshavarz Mohammadian, Newsha Faghihshojaei, Seyedeh Hajar Sharami, Niayesh Naghshi, Sara Samiei and 4 more

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Masoomeh Alsadat MirshafaeiDepartment of Sport Physiology, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran.
Shiva KhodarahmiSchool of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Masoumeh DorostiDepartment of Nutrition, Faculty of Medicine, Urmia University of Medical Sciences, Urmia, Iran.
Zahra FalahnejadSchool of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Alireza KhosravaniSchool of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Mohammad Keshavarz MohammadianStudent Research Committee, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Newsha FaghihshojaeiDepartment of microbiology, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
Seyedeh Hajar SharamiReproductive Health Research Center, Department of Obstetrics and Gynecology, Al-Zahra Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Niayesh NaghshiDepartment of Community Nutrition, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Sara SamieiDepartment of Community Nutrition, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Misa Naghdipour MirsadeghiReproductive Health Research Center, Department of Obstetrics and Gynecology, Al-Zahra Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Sara KhoshdoozSchool of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Saeid DoaeiReproductive Health Research Center, Department of Obstetrics and Gynecology, Al-Zahra Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran. doaei@gums.ac.ir.
Forozan MilaniReproductive Health Research Center, Department of Obstetrics and Gynecology, Al-Zahra Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran. forozanmilani@yahoo.com.

Funding

Guilan University of Medical Sciences 4455
6 · The paper itself

Abstract

objectiveThe incidence and severity of COVID-19 complications in pregnant women may be significantly influenced by their nutritional status. So, the present study aimed to investigate the association between nutrient intake and anthropometric indices with COVID-19 infection in pregnant women.

methodsThis case‑control study was conducted on 117 pregnant women infected with COVID-19 as the case group, and 126 non-infected pregnant women as the control group. Information on demographic, social, anthropometric and biochemical indicators was collected. In both groups, food intake data were collected using a valid food frequency questionnaire (FFQ) covering the previous year.

resultsHigher vitamin D levels were associated with reduced odds of COVID-19 (OR = 0.93, CI95%:0.89-0.99, P = 0.02), even after adjusting for age, underlying diseases, caloric intake, and levels of alkaline phosphatase (ALP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST). No significant associations were observed between weight, height, body mass index (BMI), and other dietary nutrients with the risk of COVID-19.

conclusionPregnant women with insufficient dietary vitamin D intake are suggested to be at a significantly higher risk of COVID-19. Therefore, ensuring adequate vitamin D consumption is essential. It is recommended to conduct further longitudinal investigations to obtain more definitive results, particularly among pregnant women.

Indexed as

COVID-19DietPregnancy Complications, InfectiousVitamin DVitamin D DeficiencyAdultAnthropometryBody Mass IndexCase-Control StudiesEnergy IntakeFemaleHumansNutritional StatusPregnancyRisk FactorsVitamin DAnthropometric indicesCovid-19 infectionNutrient intakePregnant womenVitamin D

Identifiers

PMID42374308
PMCPMC13579882

What OpenQuestion holds

Textmetadata
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.