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      Associations of maternal dietary inflammatory potential and quality with offspring birth outcomes: An individual participant data pooled analysis of 7 European cohorts in the ALPHABET consortium

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          Abstract

          Background

          Adverse birth outcomes are major causes of morbidity and mortality during childhood and associate with a higher risk of noncommunicable diseases in adult life. Maternal periconception and antenatal nutrition, mostly focusing on single nutrients or foods, has been shown to influence infant birth outcomes. However, evidence on whole diet that considers complex nutrient and food interaction is rare and conflicting. We aim to elucidate the influence of whole-diet maternal dietary inflammatory potential and quality during periconceptional and antenatal periods on birth outcomes.

          Methods and findings

          We harmonized and pooled individual participant data (IPD) from up to 24,861 mother–child pairs in 7 European mother–offspring cohorts [cohort name, country (recruitment dates): ALSPAC, UK (1 April 1991 to 31 December 1992); EDEN, France (27 January 2003 to 6 March 2006); Generation R, the Netherlands (1 April 2002 to 31 January 2006); Lifeways, Ireland (2 October 2001 to 4 April 2003); REPRO_PL, Poland (18 September 2007 to 16 December 2011); ROLO, Ireland (1 January 2007 to 1 January 2011); SWS, United Kingdom (6 April 1998 to 17 December 2002)]. Maternal diets were assessed preconceptionally ( n = 2 cohorts) and antenatally ( n = 7 cohorts). Maternal dietary inflammatory potential and quality were ranked using the energy-adjusted Dietary Inflammatory Index (E-DII) and Dietary Approaches to Stop Hypertension (DASH) index, respectively. Primary outcomes were birth weight and gestational age at birth. Adverse birth outcomes, i.e., low birth weight (LBW), macrosomia, small-for-gestational-age (SGA), large-for-gestational-age (LGA), preterm and postterm births were defined according to standard clinical cutoffs. Associations of maternal E-DII and DASH scores with infant birth outcomes were assessed using cohort-specific multivariable regression analyses (adjusted for confounders including maternal education, ethnicity, prepregnancy body mass index (BMI), maternal height, parity, cigarettes smoking, and alcohol consumption), with subsequent random-effects meta-analyses.

          Overall, the study mothers had a mean ± SD age of 29.5 ± 4.9 y at delivery and a mean BMI of 23.3 ± 4.2 kg/m 2. Higher pregnancy DASH score (higher dietary quality) was associated with higher birth weight [β(95% CI) = 18.5(5.7, 31.3) g per 1-SD higher DASH score; P value = 0.005] and head circumference [0.03(0.01, 0.06) cm; P value = 0.004], longer birth length [0.05(0.01, 0.10) cm; P value = 0.010], and lower risk of delivering LBW [odds ratio (OR) (95% CI) = 0.89(0.82, 0.95); P value = 0.001] and SGA [0.87(0.82, 0.94); P value < 0.001] infants. Higher maternal prepregnancy E-DII score (more pro-inflammatory diet) was associated with lower birth weight [β(95% CI) = −18.7(−34.8, −2.6) g per 1-SD higher E-DII score; P value = 0.023] and shorter birth length [−0.07(−0.14, −0.01) cm; P value = 0.031], whereas higher pregnancy E-DII score was associated with a shorter birth length [−0.06(−0.10, −0.01) cm; P value = 0.026] and higher risk of SGA [OR(95% CI) = 1.18(1.11, 1.26); P value < 0.001]. In male, but not female, infants higher maternal prepregnancy E-DII was associated with lower birth weight and head circumference, shorter birth length, and higher risk of SGA ( P-for-sex-interaction = 0.029, 0.059, 0.104, and 0.075, respectively). No consistent associations were observed for maternal E-DII and DASH scores with gestational age, preterm and postterm birth, or macrosomia and LGA. Limitations of this study were that self-reported dietary data might have increased nondifferential measurement error and that causality cannot be claimed definitely with observational design.

          Conclusions

          In this cohort study, we observed that maternal diet that is of low quality and high inflammatory potential is associated with lower offspring birth size and higher risk of offspring being born SGA in this multicenter meta-analysis using harmonized IPD. Improving overall maternal dietary pattern based on predefined criteria may optimize fetal growth and avert substantial healthcare burden associated with adverse birth outcomes.

          Abstract

          In this cohort analysis, Ling-Wei Chen and colleagues explore associations of maternal dietary patterns with offspring birth outcomes.

          Author summary

          Why was this study done?
          • Adverse birth outcomes are associated with higher morbidity and mortality during childhood and a higher risk of noncommunicable diseases in adult life.

          • The Developmental Origins of Health and Diseases (DOHaD) theory posits that maternal periconceptional and intrauterine nutrition can alter the health trajectory of the offspring.

          • Although individual maternal dietary factors have been studied widely, evidence on the impact of whole-diet maternal dietary inflammatory potential and quality on birth outcomes is scarce and conflicting.

          What did the researchers do and find?
          • We investigated whether maternal prepregnancy and antenatal dietary quality and inflammatory potential are associated with birth outcomes in a consortium of 7 European cohorts in 5 countries using harmonized individual participant data from up to 24,861 mother–child pairs.

          • After adjusting for confounders, we found that a low-quality and pro-inflammatory maternal diet during pregnancy is significantly associated with lower offspring birth weight and higher risk of offspring being born small-for-gestational-age (SGA).

          • In male, but not female, infants higher maternal prepregnancy energy-adjusted Dietary Inflammatory Index (E-DII) score was associated with lower birth weight and head circumference, shorter birth length, and higher risk of SGA.

          What do these findings mean?
          • Improving overall maternal dietary quality and reducing dietary inflammatory potential may optimize fetal growth and avert substantial healthcare burden associated with adverse birth outcomes.

          • Policies to ensure availability of affordable healthy foods and programmatic efforts to inform and support women of reproductive age, such as raising awareness of the importance of maternal diet and prenatal and antenatal counseling would help women achieve a healthier diet.

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          Most cited references58

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            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              This paper examines eight published reviews each reporting results from several related trials. Each review pools the results from the relevant trials in order to evaluate the efficacy of a certain treatment for a specified medical condition. These reviews lack consistent assessment of homogeneity of treatment effect before pooling. We discuss a random effects approach to combining evidence from a series of experiments comparing two treatments. This approach incorporates the heterogeneity of effects in the analysis of the overall treatment efficacy. The model can be extended to include relevant covariates which would reduce the heterogeneity and allow for more specific therapeutic recommendations. We suggest a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: MethodologyRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: 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
                21 January 2021
                January 2021
                : 18
                : 1
                : e1003491
                Affiliations
                [1 ] HRB Centre for Health and Diet Research, School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Dublin, Republic of Ireland
                [2 ] Université de Paris, Centre for Research in Epidemiology and StatisticS (CRESS), Inserm, Inrae, Paris, France
                [3 ] Cancer Prevention and Control Program, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
                [4 ] Connecting Health Innovations, LLC, Columbia, South Carolina, United States of America
                [5 ] Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
                [6 ] The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
                [7 ] Department of Pediatrics, Division of Respiratory Medicine and Allergology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
                [8 ] UCD Perinatal Research Centre, School of Medicine, University College Dublin, National Maternity Hospital, Dublin, Republic of Ireland
                [9 ] MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
                [10 ] Nofer Institute of Occupational Medicine, Lodz, Poland
                [11 ] Department of Hygiene and Epidemiology, Medical University of Lodz, Lodz, Poland
                [12 ] MRC Lifecourse Epidemiology Unit (University of Southampton) Southampton General Hospital, Southampton, United Kingdom
                [13 ] Department of Pediatrics, Division of Neonatology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
                University of Edinburgh, UNITED KINGDOM
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: JRH owns controlling interest in Connecting Health Innovations LLC (CHI), a company that has licensed the right to his invention of the dietary inflammatory index (DII) from the University of South Carolina in order to develop computer and smart phone applications for patient counselling and dietary intervention in clinical settings. NS is an employee of CHI. All other authors declare no support from any organisation for the submitted work other than those described above; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

                Author information
                https://orcid.org/0000-0002-2661-8752
                https://orcid.org/0000-0003-0441-8896
                https://orcid.org/0000-0002-6418-983X
                https://orcid.org/0000-0002-5381-6287
                https://orcid.org/0000-0003-0861-7630
                https://orcid.org/0000-0002-4229-3599
                https://orcid.org/0000-0002-2715-9930
                https://orcid.org/0000-0002-3212-2307
                https://orcid.org/0000-0001-7162-2569
                https://orcid.org/0000-0002-1937-0090
                https://orcid.org/0000-0002-9524-1127
                https://orcid.org/0000-0002-8194-2512
                https://orcid.org/0000-0003-3510-0709
                https://orcid.org/0000-0001-6731-9452
                https://orcid.org/0000-0002-1565-1629
                https://orcid.org/0000-0002-0677-2672
                https://orcid.org/0000-0001-9548-4914
                https://orcid.org/0000-0003-4916-4463
                Article
                PMEDICINE-D-20-03443
                10.1371/journal.pmed.1003491
                7819611
                33476335
                17e0834f-68e0-4076-a641-d66f16956106
                © 2021 Chen 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
                : 17 July 2020
                : 18 December 2020
                Page count
                Figures: 4, Tables: 2, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100013279, Joint Programming Initiative A healthy diet for a healthy life;
                Award ID: 696295
                Funded by: funder-id http://dx.doi.org/10.13039/501100001602, Science Foundation Ireland;
                Award ID: SFI/16/ERA-HDHL/3360
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/P028179/1 and BB/P028187/1
                Award Recipient :
                Funded by: National Centre for Research and Development
                Award ID: ERA-HDHL/01/ALPHABET/1/2017
                Award Recipient :
                Funded by: the ZonMW The Netherlands
                Award ID: no 529051014; 2017
                Award Recipient :
                Funded by: French National Agency of Research
                Award ID: reference AnrR16227KK
                Award Recipient :
                This work was supported by an award from the European Union’s Horizon 2020 research and innovation programme under the ERA-Net Cofund of the Joint Programming Initiative Healthy Diet for Healthy Life (JPI-HDHL) ( http://www.healthydietforhealthylife.eu) action number 696295 (Biomarkers for Nutrition and Health). Co-funding was provided by Science Foundation Ireland, Ireland (Grant Number SFI/16/ERA-HDHL/3360) to CMP (used to support LWC’s salary); the UK Biotechnology and Biological Sciences Research Council (ERA-HDHL Biomarkers: BBSRC: BB/P028179/1 and BB/P028187/1) to CLR and NCH; National Centre for Research and Development (ERA-HDHL/01/ALPHABET/1/2017) to KP (used to partially support KP’s and WH’s salaries); the ZonMW The Netherlands (no 529051014; 2017) ALPHABET project (no 696295; 2017)) to LD; the French National Agency of Research (reference AnrR16227KK) to BH (used to support AMA’s and JYB’s salaries). Cohort-specific sources of funding are listed in S1 Text. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Birth Weight
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Biology and Life Sciences
                Immunology
                Immune Response
                Inflammation
                Medicine and Health Sciences
                Immunology
                Immune Response
                Inflammation
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Inflammation
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Birth
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Birth
                Biology and Life Sciences
                Nutrition
                Diet
                Food
                Medicine and Health Sciences
                Nutrition
                Diet
                Food
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Birth
                Labor and Delivery
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Birth
                Labor and Delivery
                Custom metadata
                Data cannot be shared publicly because of ethical (participants confidentiality) and legal (data owned by cohorts and institutions located in different countries) restrictions. Data are available for researchers who meet the criteria for access to confidential data, subject to approval from respective executive committees of the individual cohorts and institutions. Contacts for data requests for each cohort are listed in S2 Table.

                Medicine
                Medicine

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