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

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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.

          Abstract

          Claire Trelford Roberts and colleagues report on the association of metabolic syndrome in pregnant women with increased risk for adverse pregnancy outcomes such as gestational diabetes and preeclampsia.

          Author summary

          Why was this study done?
          • 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 thoroughly investigated.

          What did the researchers do and find?
          • We assessed the association between MetS, measured at 15 ± 1 weeks’ gestation, and a range of pregnancy complications in low-risk, nulliparous women recruited to the multi-centre, international prospective Screening for Pregnancy Endpoints (SCOPE) study.

          • Women with MetS in early pregnancy had an increased risk for GDM and PE, after adjustment for a range of demographic and lifestyle variables.

          What do these findings mean?
          • Diagnosis of MetS may be useful to broadly identify a group of women at risk for pregnancy complications, which may additionally associate with future CVD risk.

          • Future studies are required to substantiate our findings and to determine whether MetS is a useful discriminator of pregnancy complications in lean and obese women. Future studies are also encouraged to define clear metabolic health phenotypes that will produce the optimal probability threshold for each outcome.

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          Most cited references41

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          Pregnancy and laboratory studies: a reference table for clinicians.

          To establish normal reference ranges during pregnancy for common laboratory analytes. We conducted a comprehensive electronic database review using PUBMED and MEDLINE databases. We also reviewed textbooks of maternal laboratory studies during uncomplicated pregnancy. We searched the databases for studies investigating various laboratory analytes at various times during pregnancy. All abstracts were examined by two investigators and, if they were found relevant, the full text of the article was reviewed. Articles were included if the analyte studied was measured in pregnant women without major medical problems or confounding conditions and if the laboratory marker was measured and reported for a specified gestational age. For each laboratory marker, data were extracted from as many references as possible, and these data were combined to establish normal reference ranges in pregnancy. When possible, the 2.5 and 97.5 percentiles were reported as the normal range. In some of the reference articles, however, the reported range was based on the minimum and maximum value of the laboratory constituent. In those cases, the minimum to maximum range was used and combined with the 2.5 and 97.5 percentile range. We found that there is a substantial difference in normal values in some laboratory markers in the pregnant state when compared with the nonpregnant state. It is important to consider normal reference ranges specific to pregnancy when interpreting some laboratory results that may be altered by the normal changes of pregnancy.
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            Prepregnancy BMI and the risk of gestational diabetes: a systematic review of the literature with meta-analysis.

            The objective of this study is to assess and quantify the risk for gestational diabetes mellitus (GDM) according to prepregnancy maternal body mass index (BMI). The design is a systematic review of observational studies published in the last 30 years. Four electronic databases were searched for publications (1977-2007). BMI was elected as the only measure of obesity, and all diagnostic criteria for GDM were accepted. Studies with selective screening for GDM were excluded. There were no language restrictions. The methodological quality of primary studies was assessed. Some 1745 citations were screened, and 70 studies (two unpublished) involving 671 945 women were included (59 cohorts and 11 case-controls). Most studies were of high or medium quality. Compared with women with a normal BMI, the unadjusted pooled odds ratio (OR) of an underweight woman developing GDM was 0.75 (95% confidence interval [CI] 0.69 to 0.82). The OR for overweight, moderately obese and morbidly obese women were 1.97 (95% CI 1.77 to 2.19), 3.01 (95% CI 2.34 to 3.87) and 5.55 (95% CI 4.27 to 7.21) respectively. For every 1 kg m(-2) increase in BMI, the prevalence of GDM increased by 0.92% (95% CI 0.73 to 1.10). The risk of GDM is positively associated with prepregnancy BMI. This information is important when counselling women planning a pregnancy.
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              Metabolic Syndrome and Incident Diabetes

              OBJECTIVE—Our objective was to perform a quantitative review of prospective studies examining the association between the metabolic syndrome and incident diabetes. RESEARCH DESIGN AND METHODS—Using the title terms “diabetes” and “metabolic syndrome” in PubMed, we searched for articles published since 1998. RESULTS—Based on the results from 16 cohorts, we performed a meta-analysis of estimates of relative risk (RR) and incident diabetes. The random-effects summary RRs were 5.17 (95% CI 3.99–6.69) for the 1999 World Health Organization definition (ten cohorts); 4.45 (2.41–8.22) for the 1999 European Group for the Study of Insulin Resistance definition (four cohorts); 3.53 (2.84–4.39) for the 2001 National Cholesterol Education Program definition (thirteen cohorts); 5.12 (3.26–8.05) for the 2005 American Heart Association/National Heart, Lung, and Blood Institute definition (five cohorts); and 4.42 (3.30–5.92) for the 2005 International Diabetes Federation definition (nine cohorts). The fixed-effects summary RR for the 2004 National Heart, Lung, and Blood Institute/American Heart Association definition was 5.16 (4.43–6.00) (six cohorts). Higher number of abnormal components was strongly related to incident diabetes. Compared with participants without an abnormality, estimates of RR for those with four or more abnormal components ranged from 10.88 to 24.4. Limited evidence suggests fasting glucose alone may be as good as metabolic syndrome for diabetes prediction. CONCLUSIONS—The metabolic syndrome, however defined, has a stronger association with incident diabetes than that previously demonstrated for coronary heart disease. Its clinical value for diabetes prediction remains uncertain.
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                Author and article information

                Contributors
                Role: MethodologyRole: Writing – original draft
                Role: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                4 December 2018
                December 2018
                : 15
                : 12
                : e1002710
                Affiliations
                [1 ] Robinson Research Institute, University of Adelaide, Adelaide, Australia
                [2 ] Adelaide Medical School, University of Adelaide, Adelaide, Australia
                [3 ] Waite Research Institute, School of Agriculture, Food and Wine, University of Adelaide, Adelaide, Australia
                [4 ] Department of Women and Children’s Health, King’s College London, St. Thomas’ Hospital, London, United Kingdom
                [5 ] Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
                [6 ] Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
                [7 ] Maternal and Fetal Health Research Centre, University of Manchester, Manchester, United Kingdom
                [8 ] Obstetrics and Gynaecology Section, Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, United Kingdom
                [9 ] Women and Children’s Division, Lyell McEwin Hospital, Adelaide, Australia
                University of Cambridge, UNITED KINGDOM
                Author notes

                I have read the journal's policy and the authors of this manuscript have the following competing interests: LCK is a minority shareholder in Metabolomic Diagnostics, an SME which has licensed IP pertaining to biomarkers predictive of pre-eclampsia which LCK invented. JEM receives a stipend as a specialty consulting editor for PLOS Medicine and serves on the journal's editorial board.

                Author information
                http://orcid.org/0000-0001-8554-4696
                http://orcid.org/0000-0001-9915-7873
                http://orcid.org/0000-0002-8922-083X
                Article
                PMEDICINE-D-17-04510
                10.1371/journal.pmed.1002710
                6279018
                30513077
                9d342bfb-c40a-4eae-89b7-6ea0916cbcf7
                © 2018 Grieger et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 December 2017
                : 2 November 2018
                Page count
                Figures: 2, Tables: 1, Pages: 16
                Funding
                The SCOPE database is provided and maintained by MedSciNet AB ( http://medscinet.com). The Australian SCOPE study was funded by the Premier’s Science and Research Fund, South Australian Government ( http://www.dfeest.sa.gov.au/science- research/premiers-research-and-industry-fund). The New Zealand SCOPE study was funded by the New Enterprise Research Fund, Foundation for Research Science and Technology; Health Research Council (04/198); Evelyn Bond Fund, Auckland District Health Board Charitable Trust. The Irish SCOPE study was funded by the Health Research Board of Ireland (CSA/2007/2; http://www.hrb.ie). The UK SCOPE study was funded by National Health Service NEAT Grant (Neat Grant FSD025), Biotechnology and Biological Sciences Research council ( www.bbsrc.ac.uk/funding; GT084) and University of Manchester Proof of Concept Funding (University of Manchester); Guy’s and St. Thomas’ Charity (King’s College London) and Tommy’s charity ( http://www.tommys.org/; King’s College London and University of Manchester); and Cerebra UK ( www.cerebra.org.uk; University of Leeds). JAG was supported by the NHMRC Centre for Research Excellence (GNT1099422) awarded to CTR and GAD. LEG is supported by an Australian National Health and Medical Research Council (NHMRC) Early Career Fellowship (ID 1070421). LCK is supported by a Science Foundation Ireland Program Grant for INFANT (12/RC/2272). CTR was supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (GNT1020749). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
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                Women's Health
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                Pregnancy Complications
                Medicine and Health Sciences
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                Obstetrics and Gynecology
                Pregnancy
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                Biology and Life Sciences
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                Custom metadata
                The SCOPE study, which commenced recruitment in 2004, did not seek specific consent from participants for sharing their data publicly. However, the SCOPE Consortium Scientific Advisory Board invites applications to use the collected data via email to the chairperson, Amy Aherne at amy.aherne@ 123456ucc.ie . Applicants will be asked to complete a Research Application Form specifying details for their planned study which will then be reviewed by the SCOPE Scientific Advisory Board. The SCOPE Consortium is keen to promote collaboration among researchers and to see our unique SCOPE database and pregnancy biobank used in studies which meet our ethics and consenting process. The SCOPE consortium is a member of the International Pregnancy Collaboration ( https://pregnancycolab.tghn.org/) and has participated in several studies involving shared data.

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