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Cited by 182Gestational Diabetes Research and ManagementPregnancy and preeclampsia studiesDiabetes, Cardiovascular Risks, and Lipoproteins

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Metabolic syndrome in pregnancy and risk for adverse pregnancy outcomes: A prospective cohort of nulliparous women

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Grieger, Jessica A., Bianco-Miotto, Tina, Grzeskowiak, Luke E., Leemaqz, Shalem Y., Poston, Lucilla, McCowan, Lesley M., Kenny, Louise C., Myers, Jenny E., Walker, James J., Dekker, Gus A., Roberts, Claire T.·2018·PLOS Medicine
DOI 10.1371/journal.pmed.1002710PMC PMC6279018
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Abstract

BACKGROUND: Obesity increases the risk for developing gestational diabetes mellitus (GDM) and preeclampsia (PE), which both associate with increased risk for type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) in women in later life. In the general population, metabolic syndrome (MetS) associates with T2DM and CVD. The impact of maternal MetS on pregnancy outcomes, in nulliparous pregnant women, has not been investigated. METHODS AND FINDINGS: Low-risk, nulliparous women were recruited to the multi-centre, international prospective Screening for Pregnancy Endpoints (SCOPE) cohort between 11 November 2004 and 28 February 2011. Women were assessed for a range of demographic, lifestyle, and metabolic health variables at 15 ± 1 weeks' gestation. MetS was defined according to International Diabetes Federation (IDF) criteria for adults: waist circumference ≥80 cm, along with any 2 of the following: raised trigycerides (≥1.70 mmol/l [≥150 mg/dl]), reduced high-density lipoprotein cholesterol (<1.29 mmol/l [<50 mg/dl]), raised blood pressure (BP) (i.e., systolic BP ≥130 mm Hg or diastolic BP ≥85 mm Hg), or raised plasma glucose (≥5.6 mmol/l). Log-binomial regression analyses were used to examine the risk for each pregnancy outcome (GDM, PE, large for gestational age [LGA], small for gestational age [SGA], and spontaneous preterm birth [sPTB]) with each of the 5 individual components for MetS and as a composite measure (i.e., MetS, as defined by the IDF). The relative risks, adjusted for maternal BMI, age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex, are reported. A total of 5,530 women were included, and 12.3% (n = 684) had MetS. Women with MetS were at an increased risk for PE by a factor of 1.63 (95% CI 1.23 to 2.15) and for GDM by 3.71 (95% CI 2.42 to 5.67). In absolute terms, for PE, women with MetS had an adjusted excess risk of 2.52% (95% CI 1.51% to 4.11%) and, for GDM, had an adjusted excess risk of 8.66% (95% CI 5.38% to 13.94%). Diagnosis of MetS was not associated with increased risk for LGA, SGA, or sPTB. Increasing BMI in combination with MetS increased the estimated probability for GDM and decreased the probability of an uncomplicated pregnancy. Limitations of this study are that there are several different definitions for MetS in the adult population, and as there are none for pregnancy, we cannot be sure that the IDF criteria are the most appropriate definition for pregnancy. Furthermore, MetS was assessed in the first trimester and may not reflect pre-pregnancy metabolic health status. CONCLUSIONS: We did not compare the impact of individual metabolic components with that of MetS as a composite, and therefore cannot conclude that MetS is better at identifying women at risk. However, more than half of the women who had MetS in early pregnancy developed a pregnancy complication compared with just over a third of women who did not have MetS. Furthermore, while increasing BMI increases the probability of GDM, the addition of MetS exacerbates this probability. Further studies are required to determine if individual MetS components act synergistically or independently.

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Crossref · 10.1371/journal.pmed.1002710

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Fig 1 Forest plots for each pregnancy complication, the relative risk, the number of women with MetS or its individual components (N), and the number of women with the outcome (n). All models (except BMI on the forest plot, which represents BMI <30 kg/m2 as the reference compared to BMI ≥30 kg/m2) were adjusted for maternal BMI, age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex. N = number of women with the metabolic abnormality; n = number of cases (i.e., women who had the outcome). HDL-C, high-density lipoprotein cholesterol; MetS, metabolic syndrome; RR, relative risk.
Fig 1 Forest plots for each pregnancy complication, the relative risk, the number of women with MetS or its individual components (N), and the number of women with the outcome (n). All models (except BMI on the forest plot, which represents BMI <30 kg/m2 as the reference compared to BMI ≥30 kg/m2) were adjusted for maternal BMI, age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex. N = number of women with the metabolic abnormality; n = number of cases (i.e., women who had the outcome). HDL-C, high-density lipoprotein cholesterol; MetS, metabolic syndrome; RR, relative risk.CC BY · PubMed Central
Fig 2 Predicted probability of each pregnancy outcome for women who did and did not have MetS and the interaction with BMI, estimated from the generalised additive model. Models adjusted for maternal BMI (as a spline), age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex, with an interaction term between the metabolic groups and BMI. GDM, gestational diabetes mellitus; LGA, large for gestational age; MetS, metabolic syndrome; PE, preeclampsia; SGA, small for gestational age; sPTB, spontaneous preterm birth.
Fig 2 Predicted probability of each pregnancy outcome for women who did and did not have MetS and the interaction with BMI, estimated from the generalised additive model. Models adjusted for maternal BMI (as a spline), age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex, with an interaction term between the metabolic groups and BMI. GDM, gestational diabetes mellitus; LGA, large for gestational age; MetS, metabolic syndrome; PE, preeclampsia; SGA, small for gestational age; sPTB, spontaneous preterm birth.CC BY · PubMed Central

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Metadata

Authors
Grieger, J. A., Bianco-Miotto, T., Grzeskowiak, L. E., Leemaqz, S. Y., Poston, L., McCowan, L. M., Kenny, L. C., Myers, J. E., Walker, J. J., Dekker, G. A., & Roberts, C. T.
Affiliations
  • The University of Adelaide (AU)
  • St Thomas' Hospital (GB)
  • University of Auckland (NZ)
  • University of Liverpool (GB)
  • University of Manchester (GB)
  • University of Leeds (GB)
Corresponding author
  • Grieger, Jessica A.
  • Grzeskowiak, Luke E.
  • Leemaqz, Shalem Y.
  • Poston, Lucilla
  • McCowan, Lesley M.
  • Kenny, Louise C.
  • Myers, Jenny E.
  • Walker, James J.
  • Roberts, Claire T.
ORCID
Venue
PLOS Medicine
Publisher
Public Library of Science (PLoS)
Published
2018-12-04
Volume
15
Issue
12
Pages
e1002710
ISSN
  • 1549-1277 (ISSN-L)
  • 1549-1676
DOI
10.1371/journal.pmed.1002710
PMC
PMC6279018
OpenAlex
W2902051656
Cited by
182
References
61
Citations by year
2026: 18 · 2025: 18 · 2024: 25 · 2023: 39 · 2022: 30 · 2021: 22 · 2020: 21 · 2019: 9
FWCI
14.60
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Medicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (publishedVersion, cc-by)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Research Portal (King's College London) (submittedVersion, other-oa)
Funders
  • Health Research Board (12/RC/2272, CSA/2007/2)
  • Government of South Australia
  • Auckland District Health Board
  • Australian Government
  • National Institute for Health and Care Research (NIHR-CS-011-020)
  • King's College London
  • University of Leeds
  • Science Foundation Ireland (12/RC/2272, 12/RC/)
  • Cerebra
  • Tommy's
  • Directorate for Biological Sciences
  • Medical Research Council
  • National Health and Medical Research Council (1099422, 1020749, 1070421)
Topics
  • Health Sciences › Medicine › Obstetrics and Gynecology › Gestational Diabetes Research and Management
  • Health Sciences › Medicine › Obstetrics and Gynecology › Pregnancy and preeclampsia studies
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Keywords
metabolic syndrome, pregnancy, nulliparous women, gestational diabetes mellitus, preeclampsia, adverse pregnancy outcomes, large for gestational age, small for gestational age, preterm birth, type 2 diabetes risk, cardiovascular risk, maternal obesity, waist circumference, hypertriglyceridemia, low HDL cholesterol, hypertension in pregnancy
MeSH terms
Adult, Australia, Female, United Kingdom, Humans, Ireland, New Zealand, Parity, Pregnancy, Pregnancy Complications, Pregnancy Outcome, Prospective Studies, Risk Factors, Cohort Studies, Metabolic Syndrome, Internationality

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