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Gestational Age

Anatomy and Physiology · NLM MeSH · updated 2026-10-31 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 5 min read

The age of the conceptus, beginning from the time of fertilization.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (944 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

The age of the conceptus, beginning from the time of fertilization. In clinical obstetrics, the gestational age is often estimated from the onset of the last menstruation which is about 2 weeks before ovulation and fertilization. It is also estimated to begin from fertilization, estrus, coitus, or artificial insemination.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Age, Gestational; Ages, Gestational; Gestational Ages; Embryologic Age; Age, Embryologic; Ages, Embryologic; Embryologic Ages; Chronologic Fetal Maturity.

Where it fits in the MeSH classification

Broader topics
Fetal Development; Reproductive Physiological Phenomena
See also
Infant, Premature; Crown-Rump Length; Term Birth

Related concepts

  • Fertilization
  • Menstruation
  • Ovulation

Research landscape

PubMed indexes 96,169 records tagged with the MeSH heading “Gestational Age” (counts retrieved 2026-10-31). 14,984 of them (15.6%) were published from 2020 onward, and the busiest period so far is through 1999 with 36,860 records.

Reviews account for 5,298 records (5.5%) and meta-analyses for 699. Randomized controlled trials number 2,834 (2.9%) as a share of all records on the topic.

PubMed records by publication periodthrough 1999: 36,860 records; 2000-2009: 19,140 records; 2010-2019: 25,185 records; 2020 onward: 14,984 records36,860through 199919,1402000-200925,1852010-201914,9842020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 199936,860
2000-200919,140
2010-201925,185
2020 onward14,984
Share of records by publication typeReviews: 5.5 percent; Meta-analyses: 0.7 percent; Randomized controlled trials: 2.9 percentReviews5.5% (5,298)Meta-analyses0.7% (699)Randomized controlled trials2.9% (2,834)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 96,169 PubMed records
TypeRecordsShare
Reviews5,2985.5%
Meta-analyses6990.7%
Randomized controlled trials2,8342.9%

Method: PubMed query "Gestational Age"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.

Reading the evidence in anatomy and physiology

Anatomy describes how body structures are built and physiology describes how they normally work, so most findings here are descriptive or mechanistic rather than evidence about treatment. Much of what is known comes from dissection, imaging, tissue studies and experiments in animals, and measurements in healthy volunteers can differ from those in people with disease or at different ages. Normal ranges vary between individuals and populations. Check whether a result was measured in people or in another species, the age and health of the participants, and the method used.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
The effect of maternal SARS-CoV-2 infection timing on birth outcomes: a retrospective multicentre cohort study
Piekos SN, Roper RT, Hwang YM, Sorensen T, Price ND, Hood L, et al.
2022Research article
Design not recorded in structured metadata
104cc by
PMID 35034863 · DOI · PMC8758153
Distinct placental molecular processes associated with early-onset and late-onset preeclampsia
Ren Z, Gao Y, Gao Y, Liang G, Chen Q, Jiang S, et al.
2021Research article
Design not recorded in structured metadata
73cc by
PMID 33754042 · DOI · PMC7978310
A systematic review of the factors influencing microbial colonization of the preterm infant gut
Aguilar-Lopez M, Dinsmoor AM, Ho TTB, Donovan SM
2021Systematic review
Design not recorded in structured metadata
71cc by
PMID 33818293 · DOI · PMC8023245
Immune pathways and prenatal/perinatal environmental exposures contribute to epigenetic gestational age prediction and acceleration
Eapen AA, Loveless IM, Pan M, Liang X, Urquhart A, Straughen JK, et al.
2026Research article
Design not recorded in structured metadata
1cc by
PMID 41557483 · DOI · PMC12826722

The effect of maternal SARS-CoV-2 infection timing on birth outcomes: a retrospective multicentre cohort study [1]

Research article Piekos SN, Roper RT, Hwang YM, Sorensen T, Price ND, Hood L, et al. · · 2022 · cited 104 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundThe impact of maternal SARS-CoV-2 infection remains unclear.
Closing excerpt
FundingUS National Institutes of Health.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (339 words)

BackgroundThe impact of maternal SARS-CoV-2 infection remains unclear. In this study, we evaluated the risk of maternal SARS-CoV-2 infection on birth outcomes and how this is modulated by the pregnancy trimester in which the infection occurs. We also developed models to predict gestational age at delivery for people following a SARS-CoV-2 infection during pregnancy.MethodsWe did a retrospective cohort study of the impact of maternal SARS-CoV-2 infection on birth outcomes. We used clinical data from Providence St Joseph Health electronic health records for pregnant people who delivered in the USA at the Providence, Swedish, or Kadlec sites in Alaska, California, Montana, Oregon, or Washington. The SARS-CoV-2 positive cohort included people who had a positive SARS-CoV-2 PCR-based test during pregnancy, subdivided by trimester of infection. No one in this cohort had been vaccinated for COVID-19 at time of infection. The SARS-CoV-2 negative cohort were people with at least one negative SARS-CoV-2 PCR-based test and no positive tests during pregnancy. Cohorts were matched on common covariates impacting birth outcomes, and univariate and multivariate analysis were done to investigate risk factors and predict outcomes. The primary outcome was gestational age at delivery with annotation of preterm birth classification. We trained multiple supervised learning models on 24 features of the SARS-CoV-2 positive cohort to evaluate performance and feature importance for each model and discuss the impact of SARS-CoV-2 infection on gestational age at delivery.FindingsBetween March 5, 2020, and July 4, 2021, 73 666 pregnant people delivered, 18 335 of whom had at least one SARS-CoV-2 test during pregnancy before Feb 14, 2021. We observed 882 people infected with SARS-CoV-2 during their pregnancy (first trimester n=85; second trimester n=226; and third trimester n=571) and 19 769 people who have never tested positive for SARS-CoV-2 and received at least one negative SARS-CoV-2 test during their pregnancy. SARS-CoV-2 infection indicated an increased risk of preterm delivery (pInterpretationThese results suggest that pregnant people would benefit from increased monitoring and enhanced prenatal care after first or second trimester SARS-CoV-2 infection, regardless of acute COVID-19 severity.FundingUS National Institutes of Health.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 35034863 · DOI · PMC8758153

Distinct placental molecular processes associated with early-onset and late-onset preeclampsia [2]

Research article Ren Z, Gao Y, Gao Y, Liang G, Chen Q, Jiang S, et al. · · 2021 · cited 73 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Background: Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known.
Closing excerpt
A few regulators may be the key drivers of the dysregulated molecular pathways.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (206 words)

Background: Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Although several transcriptome studies have been done on placentae from PE patients, only a small number of differentially expressed genes have been identified due to very small sample sizes and no distinguishing of clinical subtypes. Methods: We carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for dysregulated genes and the molecular network and pathways they are involved in. Results: We identified two functionally distinct sets of dysregulated genes in the two major subtypes: 2,977 differentially expressed genes in early-onset severe preeclampsia, which are enriched with metabolism-related pathways, notably transporter functions; and 375 differentially expressed genes in late-onset severe preeclampsia, which are enriched with immune-related pathways. We also identified some key transcription factors, which may drive the widespread gene dysregulation in both early-onset and late-onset patients. Conclusion: These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors. A few regulators may be the key drivers of the dysregulated molecular pathways.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 33754042 · DOI · PMC7978310

A systematic review of the factors influencing microbial colonization of the preterm infant gut [3]

Systematic review Aguilar-Lopez M, Dinsmoor AM, Ho TTB, Donovan SM · · 2021 · cited 71 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization.
Closing excerpt
Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (149 words)

Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study aimed to review the perinatal, physiological, pharmacological, dietary, and environmental factors associated with gut microbiota of PT infants. A total of 587 articles were retrieved from a search of multiple databases. Sixty studies were included in the review after removing duplicates and articles that did not meet the inclusion criteria. Review of this literature revealed that evidence converged on the effect of postnatal age, mode of delivery, use of antibiotics, and consumption of human milk in the composition of gut microbiota of PT infants. Less evidence was found for associations with race, sex, use of different fortifiers, macronutrients, and other medications. Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 33818293 · DOI · PMC8023245

Immune pathways and prenatal/perinatal environmental exposures contribute to epigenetic gestational age prediction and acceleration [4]

Research article Eapen AA, Loveless IM, Pan M, Liang X, Urquhart A, Straughen JK, et al. · · 2026 · cited 1 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
DNA methylation (DNAm), capturing chronological gestational age (GA) and epigenetic gestational age acceleration (EGAA), can be modified by environmental exposures.
Closing excerpt
Our findings highlight enrichment for T cell modulated pathways and antigen presentation as biological processes associated with chronological GA, as well as prenatal/perinatal factors that may affect EGAA.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (250 words)

DNA methylation (DNAm), capturing chronological gestational age (GA) and epigenetic gestational age acceleration (EGAA), can be modified by environmental exposures. The Asthma&Allergy array is a new DNAm array developed with content focused on asthma and allergy loci. The association between content on the Asthma&Allergy array and chronological GA and EGAA has not been evaluated alone or in the context of prenatal/perinatal exposures. We performed an epigenome wide association study (EWAS) chronological GA at single CpG sites and regions in cord blood from 391 newborn children from a Detroit-based birth cohort. We further constructed a multi-CpG site methylation model to predict chronological GA. Also, associations between prenatal/perinatal environmental factors with GA, epigenetic gestational age (EGA), and EGAA were assessed. We identified 2,435 CpG sites associated with chronological GA, and CpGs within the HLA class II locus (HLA-DRB1, HLA-DQB1, HLA-DRB6) were among the most significantly associated with chronological GA. Our multi-CpG site model attained higher predictive accuracy (R2 = 0.88) comparable to other published methods. Using genes implicated in region-based analyses (n = 395 regions), the pathways most significantly enriched with chronological GA-associated CpGs included T helper 1(Th1) and 2(Th2) activation, B-cell development, and IL-10 signaling, which were also enriched in at least one of the other published epigenetic GA clocks. In multi-exposure models, infant's first-born status and maternal parity were associated with EGAA. Our findings highlight enrichment for T cell modulated pathways and antigen presentation as biological processes associated with chronological GA, as well as prenatal/perinatal factors that may affect EGAA.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41557483 · DOI · PMC12826722

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article An overview of mortality and sequelae of preterm birth from infancy to adulthood [5]
    Saigal S, Doyle LW · Lancet · 2008 · cited 2,021 times (Europe PMC)
  • Research article Committee Opinion No 700: Methods for Estimating the Due Date [6]
    · Obstet Gynecol · 2017 · cited 498 times (Europe PMC)
  • Research article "Late-preterm" infants: a population at risk [7]
    Engle WA, Tomashek KM, Wallman C, Committee on Fetus and Newborn, American Academy of Pediatrics · Pediatrics · 2007 · cited 467 times (Europe PMC)
  • Research article Aspirin for the prevention of preterm and term preeclampsia: systematic review and metaanalysis [8]
    Roberge S, Bujold E, Nicolaides KH · Am J Obstet Gynecol · 2018 · cited 444 times (Europe PMC)
  • Research article Screening for fetal aneuploidies at 11 to 13 weeks [9]
    Nicolaides KH · Prenat Diagn · 2011 · cited 399 times (Europe PMC)
  • Research article Age terminology during the perinatal period [10]
    Engle WA, American Academy of Pediatrics Committee on Fetus and Newborn · Pediatrics · 2004 · cited 391 times (Europe PMC)

References

  1. Piekos SN, Roper RT, Hwang YM, Sorensen T, Price ND, Hood L, et al.. The effect of maternal SARS-CoV-2 infection timing on birth outcomes: a retrospective multicentre cohort study. . 2022. PMID 35034863 · DOI · PMC8758153
  2. Ren Z, Gao Y, Gao Y, Liang G, Chen Q, Jiang S, et al.. Distinct placental molecular processes associated with early-onset and late-onset preeclampsia. . 2021. PMID 33754042 · DOI · PMC7978310
  3. Aguilar-Lopez M, Dinsmoor AM, Ho TTB, Donovan SM. A systematic review of the factors influencing microbial colonization of the preterm infant gut. . 2021. PMID 33818293 · DOI · PMC8023245
  4. Eapen AA, Loveless IM, Pan M, Liang X, Urquhart A, Straughen JK, et al.. Immune pathways and prenatal/perinatal environmental exposures contribute to epigenetic gestational age prediction and acceleration. . 2026. PMID 41557483 · DOI · PMC12826722
  5. Saigal S, Doyle LW. An overview of mortality and sequelae of preterm birth from infancy to adulthood. Lancet. 2008. PMID 18207020 · DOI
  6. . Committee Opinion No 700: Methods for Estimating the Due Date. Obstet Gynecol. 2017. PMID 28426621 · DOI
  7. Engle WA, Tomashek KM, Wallman C, Committee on Fetus and Newborn, American Academy of Pediatrics. "Late-preterm" infants: a population at risk. Pediatrics. 2007. PMID 18055691 · DOI
  8. Roberge S, Bujold E, Nicolaides KH. Aspirin for the prevention of preterm and term preeclampsia: systematic review and metaanalysis. Am J Obstet Gynecol. 2018. PMID 29138036 · DOI
  9. Nicolaides KH. Screening for fetal aneuploidies at 11 to 13 weeks. Prenat Diagn. 2011. PMID 21210475 · DOI
  10. Engle WA, American Academy of Pediatrics Committee on Fetus and Newborn. Age terminology during the perinatal period. Pediatrics. 2004. PMID 15520122 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-31.

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At a glance

96,169
PubMed records on this heading
16%
published since 2020
5,298
review articles
2,834
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-31; they show how much has been written, not how strong the evidence is.

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